Pakistan : Employment, Output and Productivity

ISSUES IN DEVELOPMENT Discussion Paper 33

PAKISTAN: Employment, Output and Productivity

Nomaan Majid

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ACKNOWLEDGEMENTS ...... vii

PREFACE ...... viii

INTRODUCTION ...... 1 A. Recent changes in the macro environment ...... 1 B. The argument ...... 1

CHAPTER ONE - Labour Force and Employment ...... 7 1. The data ...... 7 2. Growth of population and labour force ...... 8 3. Labour force and employment ...... 9 Definitions of labour utilization ...... 9 The self-employed amongst the employed ...... 10 Underemployment ...... 10 Unemployment ...... 11 Employment and labour force: An overview ...... 12 4. Changing trends in the rural-urban distribution of labour force ...... 12 5. Why are labour force participation rates (LFPRs) low? ...... 13 Education and the labour force ...... 14 Emigration and the labour force ...... 14 Gender and the labour force ...... 14 6. On the changing abilities of the labour force ...... 15 Labour force expectations and the structure of the job market ...... 16 7. Upshot ...... 16 Data ...... 16 Participation Rates ...... 17 Training and skills ...... 17 Implications for a strategy ...... 17

CHAPTER TWO - Output Employment and Productivity: Lessons for an Employment Strategy .. 18 1. A dual focus ...... 18 2. Examining shares of employment and output ...... 18 3. Sectoral shares of employment and output ...... 19 4. Growth of employment and output ...... 19 5. Sectoral employment absorption ...... 20 6. Decomposing output growth ...... 22 7. Wages and poverty ...... 22 Real Wages ...... 23 Poverty Trends ...... 24 Poverty, Wages and Growth ...... 25 8. Elasticity, employment, labour productivity and output: An integrated view ..... 26 9. Employment and output growth linkages ...... 28 10. The agenda for an employment strategy ...... 29

CHAPTER THREE - The Agricultural Sector ...... 31 1. Introduction ...... 31 2. The special nature of employment and output in agriculture ...... 31

iii Measurement of employment ...... 31 The special nature of output ...... 31 A combined effect ...... 32 3. Output and employment growth rates in Pakistan’s agriculture ...... 33 4. Agricultural employment and total employment ...... 34 5. Decomposing the sources of output growth ...... 34 6. Unemployment and underemployment ...... 35 7. Labour demand ...... 36 Cropping patterns and profitability ...... 36 Size and productivity: Increasing family labour use ...... 37 Mechanization: Reducing labour requirements ...... 37 Tenurial shifts: Creating an available labour pool ...... 37 8. Wages and poverty ...... 37 9. Upshot ...... 38

CHAPTER FOUR - The Manufacturing Sector ...... 40 1. Introduction ...... 40 2. Elasticity, employment and output growth ...... 40 3. Decomposing output growth in the manufacturing sector ...... 41 4. Output and employment in the manufacturing sector ...... 42 5. The large-scale sector: Main features ...... 44 6. An examination of productivity in the large-scale manufacturing sector ...... 45 7. The structure of large-scale manufacturing in the 1980s and 1990s ...... 46 The high-growth 1980s ...... 47 The 1990s: A period of low growth ...... 49 8. Towards a policy outline ...... 50 Criteria of sectoral choices in an employment-friendly investment plan ... 51 Fiscal expansion and demand ...... 51 The budget deficit and working capital ...... 51 Promotion of sub-sectors through tariff rationalizations ...... 51 Capital pricing and directing new investment ...... 51 The co-ordination of capital flows ...... 52 The revival of sick industries ...... 52 Tax policy and flow of goods ...... 52 Energy pricing ...... 52 9. Upshot ...... 52

CHAPTER FIVE - The Small-Scale Enterprise Sector ...... 54 1. Information and data ...... 54 2. Definitions ...... 54 3. Estimates of output and employment in SSE manufacturing ...... 54 4. Characteristics of the SSE sector ...... 56 The SSE firm: Subcontracting and demand ...... 56 Labour use in the SSEs ...... 57 Capital stock ratios ...... 57 Credit ...... 58 Incomes ...... 58 5. Overview ...... 59

iv 6. The Supply and demand for sse goods and services ...... 59 Changes in purchasing power of social groups and demand ...... 59 Remittances ...... 60 The green revolution and differentiation of the peasantry ...... 60 The income and technical change effect of the green revolution ...... 60 Depreciation of exchange rates ...... 60 7. Some inferences ...... 61 8. Policy areas ...... 61 Credit policy ...... 62 Tax policy ...... 62 Infrastructure policy ...... 62 9. A strategic policy corollary and some specific measures ...... 62 10. Upshot ...... 63

CHAPTER SIX - An Employment Strategy ...... 65 1. Elements of an employment strategy ...... 65 On labour force and employment ...... 65 On sectoral strategies ...... 66

APPENDIX -The Economic Reforms Context of Growth and Employment ...... 70 The periodization and salient features of Pakistan’s development history ...... 70 The non-economic correlates of macroeconomic policies and growth ...... 71 Two symptoms of the problem of growth ...... 72 Assessing the policy-growth linkage ...... 73 The aggregate overview ...... 73 Indicators on economic growth ...... 74 Indicators on price stability in the economy ...... 75 Indicator on external balance ...... 75 Indicators on labour market conditions ...... 75 A thematic assessment ...... 76 On the sequencing of reforms and the reform policies ...... 76 Fiscal Policy ...... 77 Monetary Policy ...... 79 Trade and exchange rate liberalization ...... 82 Exchange Rate Reforms (1982- ) ...... 82 Trade liberalization (1983- ) ...... 83 Non-tariff barriers ...... 83 Tariff reforms (1990-) ...... 84 Upshot ...... 85

ANNEXES ...... 88

CHAPTER ONE Annex 1.1: Sources of data on labour and human resources ...... 89 Annex 1.2: Youth employment and child labour ...... 91 Annex 1.3: Tables ...... 95

CHAPTER TWO Annex 2. Tables ...... 105

v CHAPTER THREE Annex 3. Tables ...... 115

CHAPTER FOUR Annex 4 Tables ...... 128

CHAPTER FIVE Annex 5.1: The small-scale enterprise sector in main data sources ...... 137 Rates of growth ...... 137 Broad characteristics ...... 137 Annex 5.2: Tables ...... 142

BIBLIOGRAPHY ...... 159

vi Acknowledgments

This report is based on the work carried out during 1997-98. Nomaan Majid of the Employment Sector of the ILO, Geneva is the coordinator and principal author of the report. The work is based on contributions from a team comprising of Arshad Zaman Associates, A.R.Kemal, M. Irfan, M. Mahmood, G. Chaudhry and Nomaan Majid. Particular thanks are due to A.K. Ghose, M. Mahmood and Akmal Hussain for detailed comments on earlier drafts. Thanks are also due to Samir Radwan, Rolph Van der Hoeven and Rashid Amjad for suggestions on the final draft. A.S.Oberai of ILO-SAAT, provided constant support and encouragement for the project from its inception. ILO-SAAT, the ILO Office in Islamabad and the UNDP in Islamabad actively facilitated the progress of this report, in its most critical phases. Very special thanks are due to them.

vii PREFACE

This report is an outcome of work done by the ILO, on an employment strategy for Pakistan during 1997 and 1998, an activity which was funded under the UNDP’s SPPD facilty. One objective of the core work done for this exercise was to contribute an input to Planning Commission for their employment and manpower related work on the Ninth five Year Plan. Another objective was to produce a employment strategy document, that was cognizant both of sectoral employment issues and the macro economic environment in which a future employment strategy needs to be conceived. It is hoped that work is seen as a step in the right direction. More thinking however, needs to be done in detailing the proposed employment strategy, in addition to addressing the implications of this strategy for social groups within sectors. It is expected that the ILO in collaboration with the UN agency system will carry this work further.

Two central issues need to be emphasized. This document argues that in the Pakistan context the key to an employment growth revival is the revival of the manufacturing sector. The particular forms that such a revival may take, the linkages with other sectors, and some of the policy elements required for such a revival are delineated. The document also suggests in a separate section why the role of the macro policy environment in the growth process is critical from an employment perspective. It argues where and how Pakistan came to its fiscal crisis. This event, which is a result of imperatives on the part of State as well as ill-conceived reform sequencing on the part of donors, preceded the post nuclear situation of additional economic constraints that the country has faced and the more recent changes in government.

Today when the elements of adjustment packages and their relationship to growth are being seriously questioned by Bretton Woods institutions themselves because of the high social costs of adjustment as evidenced by the Asian and Russian crises, it is important to directly examine the nature of policy packages necessary for a revival of employment-friendly growth in developing countries. The challenge is not easy for Pakistan, but the international environment is sufficiently changed and the domestic employment crisis sufficiently serious, to pursue the matter with new vigour.

Samir Radwan Director, Development Policies Department

viii INTRODUCTION

This study on employment in Pakistan was conducted in 1997-98. Its objective has been to analyse trends in the labour market in the country, and develop possible elements of an employment strategy during Pakistan’s Ninth Five Year Plan period ( 1997-98 to 2001-02).

A. Recent Changes in the macro environment.

Since the completion of this work in 1998, some factors have entered into Pakistan’s planning process that have affected it significantly. The first is a rapidly changing macro environment. The second are the results of the 1998 Population Census. The report argues that these factors heighten the need for an employment strategy being proposed in this document. Its should however be finessed towards the transforming macro environment, and our better post-census perception of it.

Pakistan’s macroeconomic performance, while showing indications of improvement at the time of the 1998 budget, has since been subject to fiscal stress. The central point that is worth making is that over the fiscal year 1997/98, growth had picked up in Pakistan to the five per cent level, while the IMF stipulated targets in macro fundamentals were met to the satisfaction of the evaluating mission to Pakistan at the time. However, domestic fiscal policy, perhaps in anticipation of an impending sanctions based global environment due to the nuclearisation of the country, (and possible investment behaviour based on this global environment), moved towards regulation in a number of areas1. A major result of this macro transformation had been the cessation of the Enhanced Structural Adjustment Facility (ESAF) and Extended Fund Facility (EFF) agreements signed with the IMF, and a renegotiated new loan.

Although the external environment is now more stable, and donor links have been reestablished, changes in the macro environment need to be tracked as they can have critical implications for growth and employment in Pakistan. Clearly this issue needs to be assessed in future work. It is also critical to recognise the status of the specific macroeconomic policy environment for the question of whether growth is employment-friendly or not. Since the link between macropolicies and employment is generally mediated by growth, this provides an overarching context to understanding different phases of (employment focussed) economic development in Pakistan. The report devotes a separate Appendix to this issue. The reason to keep this discussion separate from the main body of the report is two fold. First that the assessment of the linkage between macropolicies and employment in this report is itself limited to an historical overview. Second, that it is the last phase of macropolicies in operation in Pakistan that are of greater importance to an employment strategy, than what can be argued for earlier phases.

B. The argument

The position of this study on employment and its determinants in Pakistan is the following. Wage employment in Pakistan is approximately one half of all employment, its proportion is high for a

1 The policy of non convertibility of domestic foreign currency deposits that was compelled, according to the central bank, by excessive public borrowing against these deposits, was an effort to miser precious foreign reserves. low income country. On the other hand self-employment comprises the other half of employment (Chapter 1). The share of the labour force in the estimated population for 1997, according to pre-1998 Census projections( on which this study has been based, and on which more below) is low. It was 37 million from a universe 135 million, which suggests a low participation rate. In fact the labour force participation rate (LFPR) in Pakistan has been decreasing over time. It is now down to around 27 per cent, therefore implying a high and increasing dependency ratio for the rest of the population. While we can explain to some extent, the drop in the LFPR to be due to increasing school enrollments (which is therefore in some respect desirable), there is clearly a possible trade off involved due the narrowing of the earning base in the country, which can put downward pressures on per capita income. This can have implications for poverty and living conditions of households. We actually find a mixed result on poverty in Pakistan, but it is one which is not inconsistent with the hypothesis of a downward pressure on living standards due to increasing dependence during the growth process.

The next question the report asks is what determines the low labour force participation and its income? The labour force, by definition, comprises of the employed and the unemployed, given at around 35 million and 2 million respectively. Before summarising the answer to this question, some qualifiers need to be made. There has been considerable debate and now recognition, in Pakistan, that women’s income enhancing labour, whether in self-employment or in the wage labour market has been considerably under-enumerated due to non-sampling errors like male social biases, that render women’s labour “invisible”. This feature also reduces the overall estimates of the size of the employed. The second qualification is that under enumeration of the unemployed obtains because the survey- definition used in Pakistan requires them to be available for work in the reference week. Moreover it is to be remembered that these qualifiers obtain in the context of a labour market where formal institutions for employment are eclipsed by informal institutions. So, our estimates of both the employed and the unemployed, and the size of the total labour force are probably low.

This study assumes that given the labour force size, perhaps in this case based on consistent underestimation, what will determine the level of employment in the economy is firstly growth itself. On the other hand what determines the earnings of the employed are the wage rate and returns to self-employment in different sectors of the economy. In order to investigate the relationship between employment and growth, this study uses two analytical devices. One is a standard elasticity coefficient for employment with respect to growth. Problematic as the specific magnitude of the elasticity measure is, in the view taken here, it is considered at least qualitatively and directionally indicative of the employment-output linkage. This of course gives a range of values indicating say high, medium, or low responsiveness of employment to growth. The second device dis-aggregates change in output over time into (i) an output change caused by employment change; (ii) an output change that is caused by productivity changes; and (iii) an output change that is caused by a multiple effect of both employment and productivity changes. We refer to this as the decomposition exercise. The results of both exercises ( elasticity and decomposition) are used as summary perspective devices in the overview as well as sectoral chapters.

Chapter 2 of this study shows that over the last three decades, Pakistan’s growth has been high for a low income country, around six per cent on trend till 1992/93, with a two per cent variation. However, against this high GDP growth, employment growth has been much lower, at two per

2 cent on trend. As a result the elasticity of employment has remained medium to low, ranging between 0.6 and 0.3. The periodicity of this growth of output and employment is revealing, if we abstract for the moment from the issue of the particular periodisation chosen.

Output growth in Pakistan was low over the 1970s at under five per cent, it increased over the 1980s to above six per cent, and has dropped again over the 1990s to near about four per cent. Employment growth interestingly follows an opposite pattern, being at its highest at three per cent over the 1970s and lapsing to two per cent over the 1980s and the 1990s. Does this constitute some prima facie evidence for a trade off between employment and output growth? A further subdivision of these periods shows that there was a period of high employment in the 1970s, stable employment till the mid-1980s and a total break between growth and employment subsequently. The aforementioned decomposition exercise adds an insight to this pattern. Growth of output was based predominantly on an employment effect in the 1970s, on a productivity effect in the 1980s, and a mixed productivity and employment effect in the 1990s. So the answer to the trade off question posed above is not straight forward, and apart from having a source of output growth dimension ( productivity or employment) the answer is likely to have a sectoral dimension as well.

We know that generally low elasticities accompanying growth in Pakistan tend to conceal the fact that the source of growth (employment or productivity) itself has been varying over time. This is an important point to note. It is this changing relationship between growth of output and employment over time that is traced to its major sectoral components in the rest of the report.

In output growth, manufacturing is the leading sector (and agriculture contributes progressively less over time), over the low growth period of the 1970s, the high growth period of the 1980s, and the lower growth period of the 1990s. In employment growth, during the low growth period of the 1970s manufacturing leads, and with the relapsed of growth of the 1990s, employment growth in manufacturing turns negative.

The explanation for the changing overall relationship between output and employment growth over time then finds a possible sectoral reason. It has been said that employment growth was high over the 1970s and then stable till the mid 1980s, after which it de-linked from output growth. Manufacturing contributed relatively more to employment growth than agriculture in the 1970s, relatively less than agriculture in the 1980s, and negatively in the 1990s. So the overall break between output growth and employment seems to be more associated with the manufacturing sector. It is also true that we find some evidence to suggest that agriculture and construction are becoming possible refuge sectors for labour after this de-linking of employment and output growth. This explanation is further enhanced when we examine output and employment growth relationships at the sectoral level through the same two analytical devices of sectoral elasticities and the decomposition exercises. Chapters 3 to 5 examine sectors.

Chapter 3 on agriculture shows that output growth and employment growth (and therefore, employment elasticity) were stable in the 1970s till the mid-1980s, barring states of nature based interventions. Therefore, output and employment growth are connected till the mid-1980s. After the mid-1980s, output and employment growth became volatile. The elasticity of employment in agriculture is thus positive and stable till the mid-1980s then subsequently starts fluctuating. The decomposition exercise for agriculture shows that agricultural output growth was driven

3 predominantly by the employment effect in the 1970s, largely by the productivity effect in the 1980s and then again largely by the employment effect in the 1990s. The report does pursue alternative explanations for the contribution of agriculture to the fluctuations in employment from the mid-1980s onwards, in terms of the increasing sensitivity of a post-High Yielding Variety (HYV) agriculture to states of nature, and the casualisation of the labour force based on increasing mechanisation.

In contrast, to agriculture, Chapter 4 shows that in the case of manufacturing, employment growth was stable and high over the 1970s, when in fact output growth was low. In the 1980s, output growth in manufacturing rose, but employment growth dropped to a stable low, the aforementioned critical disjuncture become evident by 1980. By the mid 1980s, output and employment growth both become unstable. Elasticity of employment in manufacturing, barring a peak in the mid-1970s remains at a continuously low level. The decomposition exercise for the manufacturing sector highlights this break between employment and output growth after the 1970s. Over the 1970s output growth in manufacturing is driven equally by the employment effect and the productivity effect. Over the 1980s the employment effect becomes negligible, while over the 1990s it turns negative.

So, the disjuncture between employment and output growth rates in manufacturing reflect and track the economy-wide break between employment and output growth rates better. Low output growth accompanies high employment in the aggregate over the 1970s, high output growth accompanies low but stable employment growth till the mid-1980s, after which employment and output growth become volatile. It is fairly clear that both agriculture and manufacturing contribute to output through a predominant employment effect in the 1970s, but for the 1980s and 1990s, only agriculture contributes through an employment effect, while manufacturing’s employment growth breaks away from its growth of output.

Having focussed on the manufacturing sector, we need to trace the causality further. In other words we need to determine the causes for this break between employment and output growth in manufacturing itself. The first point to note here is that while the share of manufacturing in GDP has increased over time from 15 per cent to 18 per cent, its share in employment has declined from 14 per cent to 10 per cent. To explain why the manufacturing sector has become entirely labour productivity driven rather than in some measure employment-driven, we have to recognise some structural features of the sector. The critical feature of manufacturing in Pakistan, as in many developing economies is its duality. The large scale (LS) sector and a small scale (SS) sector are two classifications of manufacturing and the cutoff point between the two has been defined variously over time by the government of Pakistan (GOP)2. The LS sector (examined in Chapter 4), produces two-thirds of the value added in manufacturing, but employs only 17 pre cent of the approximately 4 million labour force in manufacturing. The SS sector (examined in Chapter 5), produces one third of the value added in manufacturing, but employs 83 per cent of the labour. So the LS sector dominates output, while the SS sector dominates employment. Further, the output and employment shares of the LS and SS sectors have remained fairly stable over the last two decades.

2 For effective purposes the 1934 Factories Act cuts off enterprises employing more than ten workers, from those employing less.

4 The differential between the two manufacturing sectors, LS and SS, is in labour productivity; and this in turn is reflected in a differential in their capital-labour ratios. The LS sector has a higher capital labour ratio by a factor of 17, and therefore a much higher labour productivity. It also has higher wage rates and greater job security, and it is argued over the course of Chapters 3 and 4, that LS growth rates are higher growth rates than those in the SS sector. Other production characteristics of the SS sector are detailed in Chapter 5, these are fragile vending linkages to other parts of the economy and negligible formal credit. The typical SS unit is based on self employment and family labour; with earnings approximating the LS sector’s wage rate, with low vintage, and limited vertical transition out of the sector. These characteristics of the SS sector, while not completely homogenising potentially render a large part of it, a refuge labour sector in Pakistan.

The following question then is, if the SS sector has in large part been or become moribund with all its disincentives, why has the LS sector failed to expand its employment levels significantly over time, say between 1980 and 1995, when employment grew at 2.3 per cent, employment in the LS sector grew at under 1.8 per cent. The first element in our answer is an increase in capital productivity in large scale manufacturing over time3. Furthermore, Chapter 4 also shows for the LS sector, that while this increase in capital productivity was positively correlated to labour productivity, it was significantly negatively correlated to employment. As a result the wage share in output dropped from 0.4 to 0.29. This is accompanied by the fact, as Chapter 1 shows, that the real wage in Pakistani industry barely creeps up over the last two decades. It is worth pointing out that this pattern of growth in the LS sector was enabled by a large increase in investment in manufacturing, and liberal financial sector lending. So over the period 1982/83 to 1992/93, private investment in manufacturing increased from 1.7 per cent of GDP to 4.2 per cent. In other words, the pattern of investment and growth in manufacturing, over the 1980s, was capital augmenting and labour displacing, and it increased profitability and reduced the wage share in output. The evidence tends to favour this view 4.

The second element in our answer to the disjuncture between growth of output and employment in the LS sector lies in the creation of excess capacity in the 1990s. Private investment in manufacturing halves after 1993/94 from 4.2 per cent of GDP to 2.2 per cent with a declining trend, as Chapter 4 shows. This results in a declining trend in capacity utilisation in the four major industries of the LS sector, spinning, weaving, cement and sugar. The economic position taken here is that this downturn in investment, capacity utilisation, and growth in manufacturing is caused in large part by a failure in demand, significantly associated with the deflationary policies pursued by GOP in accordance with the Structural Adjustment (SA) programme signed with the IMF, in successive protocols since the 1988 .

What probably happened was a coincidence of events. Growth in Pakistan has always been susceptible to states of nature caused downs in agriculture, given its preponderant reliance on the

3 Chapter 4 shows that over the 1980s the capital labour ratio in the LS sector increased from Rs. 50,000/ to Rs. 192,000/.

4 This was akin to the pattern of restructuring of capital followed in some Industrialised countries (ICs) over the 1980s, in reprisal to the three decades of post-war Keynesian full employment policies.

5 textile industry and export of cotton and its products. The dips in GDP in each decade, examined in Chapter 2, are related to flooding in agriculture in the early 1970s and in the early 1980s, and a pest attack on cotton in 1992/93. However in the 1970s and the 1980s, the economy recovered with a one to two-year lag, returning to trend growth. In the 1990s, however, this return to trend growth has arguably been inhibited by the simultaneity of deflationary SA policies with the massive decline in cotton output for two years running. Just when the state of nature caused slump needed a reflationary policy, the SA programme veered the economic managers towards policies effectively increasing the incidence of general taxation and a decline in subsidies. This was affected through the imposition of a Value Added Tax (VAT) and successive annual increases in its rate and coverage; and through a reduction in the budgetary deficit especially affecting agricultural subsidies and therefore production and recovery. This was also manifested in a decreased purchasing power and effective demand.

In summary, we have found that the relationship between growth in employment and output is strong over the 1970s, and stable over the first half of the 1980s, but becomes negative subsequently. Manufacturing is the leading sector in growth of output and employment in the 1970s, but contributes little to employment in the 1990s. The manufacturing sector is seen to be characterised by a dualism, with an LS sector dominating output, and an SS sector dominating employment over time. Given low capital labour ratios in the SS sector and all the disadvantages in production conditions that this entails, the central question that emerged was why the relatively more advantaged LS sector had constrained its employment levels over time, especially over the 1980s and the 1990s. Two elements were identified to answer this question. One, that over the 1980s, the LS sector in Pakistan followed an internationally established pattern of capital augmenting, labour substituting growth, increasing profit shares and reducing the wage share. Two, that over the 1990s, deflationary SA policies dampened recovery from a state of nature caused blip in growth, especially for manufacturing, constraining capacity utilisation and employment further.

An employment strategy for Pakistan must then seek to redress this disjuncture between growth of output and employment, caused in large part by the LS sector in manufacturing. This is what is proposed in this report. The key constraints are an overwhelming capital augmenting growth path, and deflationary SA policies. This brings us back full circle to the starting point this argument. With an impending, and even larger, SA programme in the offing, Pakistan faces the prospect of possibly low growth and low rate of recovery from a fiscal crisis as in 1992/93, and possibly employment-less growth as in the 1980s. This makes a planned employment strategy for the NFYP period difficult but imperative. On the other hand, the more recent changes in the thinking of Bretton Woods institutions, with respect to the recognition of social outfalls of adjustment programmes, allows Pakistan, as indeed other developing countries, a better context in which to make a case for a macro and social policy framework which is consistent with a positive employment strategy.

6 CHAPTER ONE Labour Force and Employment

1. THE DATA

A well-known shortcoming of analysis on labour markets in Pakistan is the internal limitations of the data produced on population, labour force and employment. Coverage of the labour force surveys (LFS) is known to be low, with the result that both participation rates and employment elasticities based on LFS data are thought to be underestimated. The population census scheduled for 1991 had been delayed, leaving a gap of over seventeen years since the previous census was taken. The full results of the Population Census of 1998 were still unavailable at the time of the writing of this report. The absence of regular and better data confines us to work, with due care, with the data available (Annex 1). There is, however, a distinction (if not a choice) here which needs to be made. In view of the weight of empirical evidence that does (or does not) exist, there are two courses open for further investigation. The first is to accept the trends from large-scale data as a starting point and then investigate the issues and problems this data throws up at the disaggregated level, in order to qualify the existing trends – both sectorally and with respect to special categories/groups of labour that require focus. The second course is to reject the census and survey data on the grounds that the true labour supply is understated1 and proceed with analyses supported by the micro evidence that can be marshalled, without regard for the larger picture.

The view taken in this report is that there is a need for greater caution in rejecting the burden of numerous surveys, irregular and imperfect as they may be and even if they yield apparent inconsistencies in their results, as surveys anywhere are apt to do. The size of the information that does exist in Pakistan is substantial. In order to judge the validity of anomalies in the larger data sets, what is ideally needed is a specific survey, of equal or greater coverage, which provides empirical proof of the alleged bias in previous census and survey data. There is both an absence and a critical need for information on labour market indicators in Pakistan. Given the lack of a perfect series or a second-best one, we will work with what is available, using annual data from labour force surveys. These are subject to much fluctuation, suggesting a weakness in data source. Our emphasis is therefore more on trends than on explaining annual fluctuations, where they seem inexplicable.

The earliest and, probably, still the more reliable data on population and labour force are provided by the population censuses of 1951, 1961, 1972, and 19812 (See tables A1.1, A1.2 and A1.3). In lieu of the much delayed census for 1991, we have used population and labour force data from the Demographic Survey of 1991 and the annual labour force surveys carried out since. These are used to assess the employment situation, especially after 1981 (Table A1.2).3

1 For example, due to exclusion of women’s household work and of women and men’s work in the informal sector (especially in the school-going age group).

2 Population censuses have been conducted every ten years 1880. The census for 1971 was delayed by one year, and that for 1991 has not been conducted so far. There is now evidence to show that there may be serious problems associated with the 1961 census. Consequently the need for a consistent series is real. The 1997 figures are estimates.

3 Since 1990-91 the surveys are based on an improved questionnaire.

7 2. GROWTH OF POPULATION AND LABOUR FORCE

The labour force (around 37 million in 1997) is not a very large proportion of the population (135 million in 1997) in Pakistan. Its is estimated to be around 28-29 per cent. Population growth had been increasing over the years, up to and including 1970s. Although the last census was carried out in 1980, projections on the population growth rate suggest that it is likely to have fallen and has probably stabilized now to just under 3 per cent4.

Labour force growth rates on the other hand were higher than that of population in 1970s (figure 1.1 and Table A1.1) but have been generally lower after the 1970s. Although the labour force survey figures for the 1990s can also be interpreted to suggest a decline in labour force growth on trend5, there are problems in comparing the labour force trends before and after 1990-916. There is however a clear decline between the two definitionaly comparable periods of the 1970s and 1980s.

This means that labour force growth, which is significantly lower than population growth, is likely to be falling while the growth of population is likely to be stabilizing.

Figure 1.1: Growth of Population, Labour Force and 8.00 Employment

6.00

4.00

2.00 %

-2.00

-4.00 Grth(Pop) YearsGrth(LF) Grth(Emp)

4 This is subject to confirmation by the impending Population Census.

5 Average growth of population for the 1970s (1970-80) was 3.14 per cent; for the 1980s (1981-1990) it was 3.10 per cent and for the 1990s (1992-1996) it has been estimated at 2.98 per cent. Labour force growth for the same periods has been 3.31 per cent; 2.42 per cent and 2.4 per cent. The last-mentioned is the case only if we exclude 1990-91(which is the definitional change year). Strictly speaking, it is not legitimate to compare trends before and after 1990-91. The 1970s to 1980s trend shows a decline in labour force growth, which is likely to have continued.

6 The 1990-91 Labour Force Survey changed some definitions in such a way that (a) activity rates of women increased by inclusion of some homeworkers as part of the labour force; (b) total labour force increased; and (c) unemployment rates increased. This essentially makes the comparison of pre- and post-1990-91 LFSs difficult.

8 Figure 1.2: Population, Labour Force and Employment

160

140

120

100

Population Lab. For. Employed Labour force

If serious data problems are excluded as a cause, then one of the main reasons for falling labour force growth rates is reflected in the decline in participation rates due to withdrawal of sections of persons of working age from the labour force. Educational enrolments for an increasingly younger population of working age mean that the labour force growth will begin to rise in the near future. This has implications for trends on unemployment and underemployment in the present situation. These are likely to be magnified with an increase the growth rate of the labour force in the future.

3. LABOUR FORCE AND EMPLOYMENT

Definitions of labour utilization

The “economically active population” comprises persons of either sex who furnish the supply of labour for the production of goods and services, during a specified time reference period. But not all these persons are currently active (or in the labour force) at any particular point of time. In Pakistan, the currently active population or labour force comprises of all persons ten years of age and over who fulfil the requirements for inclusion among employed or unemployed, defined as follows, during the reference period i.e. one week preceding the date of interview.7

• The “employed” comprise all persons ten years of age and over who worked at least one hour during the reference period, and were either “paid employed” or “self-employed”. (Persons holding permanent jobs, who for any reason had not worked during the reference period are treated as employed).

7 Pakistan uses the “labour force” approach, to measure employment, unemployment and underemployment. This approach uses hours of work as the criterion and aims basically at measuring labour utilization. The definitions used in the recently conducted surveys are given above. The differences in the old (1987-88 and prior) and new (1990-91) concepts may be seen in Annex 1.

9 • The “unemployed” comprise all persons ten years of age and over who during the reference period were: – “Without work,” i.e. were not in paid employment or self-employment; – “Currently available for work,” i.e. were available for paid employment or self- employment; and – “Seeking work,” i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. • The underemployed comprise all employed persons who during the reference period were working less than the “normal” duration on an involuntary basis and were seeking or were available for additional work. In Pakistan, the underemployment rate is estimated as a ratio of the employed (who worked less than 35 hours a week) to total labour force. With the help of the available data, we analyze below the latest employment, unemployment and under-employment situation in Pakistan.

The self-employed amongst the employed

Employment is divided into two categories in Pakistan: the self-employed and the hired. The self-employed are only marginally less in number than the hired within the labour force. During 1983-95, the self- employed, on an average, constituted 44 per cent of the employed work force: 46 per cent in the rural areas and 37 per cent in the urban areas. The percentage of the self-employed increased from 40.3 in 1982-83 to 47.9 in 1987-88 but was at 42.3 in 1994-95. This percentage increased in the rural areas and declined in urban areas during the period 1982-83 and 1994-95 (table A10).

In 1987-88, the agricultural sector accounted for 53.6 per cent of the self-employed, followed by trade (16.8 percent) and manufacturing (10.9 percent). In the rural areas, agriculture accounted for 66.6 per cent of the self-employed followed by 9.8 per cent in trade. In the urban areas, the wholesale and retail trade sector accounted for the major share of 41.8 per cent (Table A1.11).

Another distinct feature of the self-employed is that compared to the national average, the share of self- employed who worked full time was higher (except for women in rural areas). Moreover, the level of education of the self-employed was also lower than the national average (Table A1.12).

The self-employed are sizeable, significantly agrarian, work long hours and are relatively less literate than their counterparts in employment. It is important to bear in mind that self-employment in Pakistan is predominantly in agriculture and more symptomatic of poverty than prosperity.

Underemployment

The underemployment rate is estimated as a ratio of employed who worked less than 35 hours a week to the total labour force (Table A1.13). There were nearly 4 million persons underemployed in Pakistan in 1994-95.

The proportion of employed persons who worked for less than 35 hours, which had declined from 14 per cent of the employed work force in 1982-83 to 11.1 per cent in 1987-88, was at 12.2 per cent in 1994-95. Underemployment was much more prevalent in rural than in urban areas. In 1987-88, it was 2.8 times that of urban areas. In 1993-94 it was almost double. Unpaid family helpers constituted about half of the underemployed, followed by the self-employed. This is true in the aggregate as well as in the rural areas. Underemployment among employers was almost negligible.

10 Within rural areas the share of underemployed declined from 16.3 per cent in 1982-83 to 13.4 per cent in 1987-88, but was at 14 per cent in 1994-95. In contrast, the share of underemployed in urban areas declined from 7 per cent in 1982-83 to 4.8 per cent in 1987-88, but was at 7.1 per cent in 1994-95 (Table A1.14).

It is also interesting note that in the 1993-94 LFS (when this question was asked) a four-fifths majority of those who were underemployed, considered their working hours as “normal”. This implies a “normality” of being permanently underemployed, in an “enclave” of the labour market where most of the underemployed are not so out of choice (only 2.6 per cent in this group describe their underemployment as voluntary) and where the severity of underemployment is unlikely to decrease.

Unemployment

In a developing economy characterized by significant poverty, minimal social insurance and welfare mechanisms, unemployment is probably the least appropriate indicator of labour market conditions. Most people of working age, who are not in full-time education, need to work to survive. With this proviso in mind, we will examine unemployment data.

First, it is necessary to clarify a definitional problem. Before 1990-91, the LFS recorded those persons as unemployed who were without work (i.e. were not in paid employment or self-employment) and were both currently available and seeking work during the reference period of one week. Those who may have been available for work but for some reason were not seeking it (i.e. not taken specific steps to seek paid or self- employment) were not recorded as unemployed. The unemployment rates prior to this period were therefore recorded at a low figure of about 3 per cent. From 1990-91 onwards, the condition of being available for work was sufficient to be recorded as unemployed. This resulted in the unemployment rate in 1990-91 jumping to 6.3 from 3.1 per cent in 1989-90 (Table A1. 15) and implies that comparisons on unemployment8 are not legitimate across the year 1990-91.

The number of unemployed persons was two million in 1990-91. This figure was one million in 1989-90 and much of the increase occurred because of the change in definition of the term. The overall unemployment rate declined in 1991-92 and 1992-93 but it went up in 1993-94 and remained at the same level in 1994-95 and declined again afterwards. There is no real trend which is discernible9. For general policy purposes, it may not be wrong to assume that currently about two million people are unemployed in Pakistan. According to data, 63 per cent are men and 37 per cent women. Of the total unemployed in 1994-95, about 60 per cent were in rural areas. However, the unemployment rate (ratio of unemployed persons 10 years of age and over to labour force) was much higher in urban areas (6.51 per cent in urban as against 4.22 per cent in rural areas). Available figures for 1984-85 to 1987-88 show that the severity of unemployment as judged by its duration as well as the percentage of unemployed with previous experience has been increasing (Table A1.16).

8 This is also true for female participation rates as we shall see below.

9 There is slight decline between the 1970s and 1980s and no pattern after in the 1990s. Comparisons with the 1990s are, however, suspect for this category.

11 Unemployment rates are higher both for older and younger workers. Whereas the high unemployment rates for the 10-14 age group may be attributed to restrictions on (child) labour below the age of 14, the high rates in the 60 plus age group is explained by the non-availability of jobs suiting older workers.10 Within the unemployed, the share of literates has increased on trend from 42.8 per cent to 48.8 per cent (Table A1.17).

At the aggregate level the unemployment rate has averaged around 5.0 per cent a year during 1990-91 to 1994-95. Of two million unemployed in Pakistan, nearly half of them are literate and the severity of their unemployment is likely to be increasing.

Employment and labour force: An overview

Employment growth rates generally increased in the 1970s, and from the end of the 1970s declined on trend till the late 1980s. In the 1990s, although it is difficult to make a comparative statement, employment growth is falling on trend.11 The variability in growth rates is partly explained by definitional changes.12 In sum:

• the gap between the number of persons in the labour force (employed or otherwise) and the population is likely to widen for a little longer before it starts closing;13

• the size of the underemployed is around 4 million (12 per cent underemployment rate) and is likely to have been increasing in recent years; and

• close as they are in levels compared to the population, the gap between the labour force and the employed within it as a proportion of the labour force, is wider now it was during the 1970s and suggests a persisting unemployment problem.

Given that labour force growth is expected to increase in the future, those employment-related problems that exist now, under falling labour force growth conditions, are likely to worsen.

We now make some further observations on the data available.

4. CHANGING TRENDS IN THE RURAL-URBAN DISTRIBUTION OF LABOUR FORCE

In absolute numbers, the labour force in Pakistan has increased from 18.1 million to 35.2 million between 1972 and 1995 (Table A1.3). The male labour force has increased from 16.7 million to 30.5 million and the female labour force from 1.4 million to 4.7 million. Compared to an average annual increase of 2.7 per

10 See Annex 1: Labour and Employment Statistics

11 Employment levels are generally close to those of the labour force and both have increased steadily over the years. However, growth rates of employment have both been lower as well as higher than that of the labour force in the past. There is some pattern. Up to the mid-1970s employment growth rates were higher than labour force growth; from the mid-1970s to the early 1980s they were lower. In the mid-1980s they were higher again and since the late 1980s they have remained lower for most years.

12 The 1990-91 Labour Force Survey changed definitions in such a way that unemployment rates as well as female participation rates increased.

13 The education-based withdrawals are likely to swell the labour force with a time lag.

12 cent in the total labour force between 1972-95, the urban labour force increased by 3.5 per cent per year, while the rural labour force increased by 2.5 per cent per year in the same period. As a result, the share of the urban labour force in the total labour force increased from 23.3 per cent in 1971-72 to 27.3 per cent in 1994-95. This difference in growth rates was largely the result of rural-urban migration. The growth of the rural labour force in the late 1970s and the first half of the 1980s was also affected (restricted) by emigration, which is much less important today.

Traditionally, and certainly since 1975 onwards the growth of the urban labour force has been faster than that of the rural labour force. This was to be expected. However, the reversal of trends in growth rates in the 1990s (rural labour force growth rates being higher than urban ones)14 suggest that, if no serious data problem exists, there may be an emerging barrier on internal rural urban migration15 (Table A1.3). This issue has implications for the size of the labour force in the rural areas, particularly in agriculture, and needs to be explored.

5. WHY ARE LABOUR FORCE PARTICIPATION RATES (LFPRS) LOW?

The size of the labour force is determined by the size of the working-age population and its activity or participation rates16, adjusted for migration into and out of the country. This population has already been born; the demographic changes which occur today will affect labour supply with a time lag of about 10 years. The “activity rate” is therefore the key determinant of the currently active population or labour supply.

We need to explain why the participation rates of labour force are declining in Pakistan. The LFPR peaked to 31 per cent in 1978-79 and declined to 27.5 per cent in 1994-95. The falling labour force participation rate has clearly restrained the growth of the domestic labour force (Table A1.4).17 It is worth noting that rural participation rates are generally higher than urban ones, another reason why when labour force growth declines it does so less in rural areas. This is also reflected in the fact that while the rates of male participation in the labour force do not vary so much across the rural and urban divide, and they do so less over time, the gap between rural and urban participation rates for women is significant and persists over time. The greater participation in rural areas is due to a greater inclusion of women in what constitutes the labour force, in spite of the reporting biases on women's household activities in both rural and urban areas. This feature comes into sharp relief when we consider the size of the excluded labour force in Pakistan.

We discuss below three tendencies for changes in the LFPRs in Pakistan whose net impact is clearly a decline. These pertain to education, emigration and gender.

14 For the period 1991-92 to 1996-97 (estimated), the rate of growth of the overall labour force is 2.42 per cent; it is 2.96 per cent for the rural labour force and 1.08 for the urban labour force.

15 Differences in urban and rural LF growth can be attributed to the net effects of rural-to-urban and urban- to-overseas migration and reverse flows, none of which are precisely known.

16 The crude activity rate, also called the crude labour force participation rate (LFPR), is defined as the ratio of labour force to the population. The participation rate of the labour force was around 27.5 per cent in 1994-95. This is not only extremely low but has been declining on trend (Table A1.4).

17 The 1990-91 LFS improved the activity rates for women due to definitional changes.

13 Education and the labour force

High population growth in Pakistan has also been associated with an increasing proportion of population in the lowest age cohorts (Table A1.5). The proportion of population in the 0-14 years age group increased from 44.5 per cent in 1981 to 45.8 per cent in 1988 and to 46.3 per cent in 1995, thus raising dependency ratios and depressing labour force participation rates. In part, age compositions do explain why the overall participation rates are low. The 10-14 years age group show a decline in participation rates, suggesting a withdrawal of the young (who are counted as economically active) from the labour force, possibly due to increased school attendance.18 The decline in participation rates, in the 15-19 years age group may be similarly attributed to increasing college enrolment.

Emigration and the labour force

Increasing emigration from the mid-1970s to the mid-1980s had constrained growth in domestic labour. According to the report of the National Manpower Commission (Government of Pakistan, 1989, p. 101), during 1978-83, almost 25 per cent of the incremental labour force found employment abroad. This helped in sustaining employment growth at 2.8 per cent. However, return migration in 1982-87 dominated the stream of migration and may have played some part in accentuating pressures on the domestic employment situation (Table A1.6). For the more recent sub-period there is evidence of net out-migration. The net outflow in 1993-95 period is, however, a much lower percentage of the labour force, in comparison with the past peak of the 1980s. The size of the labour force today is not subject to pressures return migration and is unlikely to be seriously constrained by out-migration.

Gender and the labour force

This is an area which requires serious analytical and empirical disentangling.

Due to the way the term ‘labour force’ is defined, a number of persons, particularly women engaged in household duties, are not included in the term ‘population currently active’ or labour force (table A7). This reduces the number of labour force as well as the participation rate, a shortcoming that was partly made up for in Pakistan by adopting a new definition in the 1990-91 LFS, in which women were identified as employed if they spent time on any of the 14 specified agricultural and non-agricultural activities defined in the Intentional Standard Industrial Classification, (ISIC).19 This partly redresses the definitional bias. However, it is interesting to note that in 1994-95 about 59 per cent of the economically active population were excluded from the labour force. Of these, about 27 per cent were men and 73 per cent were women. Clearly, the bulk of the ‘excluded labour force’ are women.20

An obvious reason for this in Pakistan is that social perceptions restrict the ‘admission’ of the existence of female work, by a not too insignificant section of the population. This implies a reporting bias due to

18 This fact has implications for the incidence of child labour. We should expect it decline (Annex 2).

19 Non-inclusion of housewives (home-makers) as well as other categories of persons such as rentiers, thieves beggars, smugglers, prostitutes, etc., in the labour force has been a matter of debate for a long time. Until the definition of the term

20 The figures are telling that after accounting for students enrolled in government institutions, about 32.8 million persons, comprising 2.7 million men and 30.1 million women, were not in the labour force.

14 which female participation rates and employment can be seriously under-reported. Secondly, in Pakistan, much of the employment data, irrespective of its source, is collected by male investigators interviewing male respondents.21 Apart from the degree of authenticity of responses, variations in reported employment may also result from variations in the education, training or supervision of investigators; the periods chosen for the survey; and the language used in the questionnaire.22 These elements vary from survey to survey and can lead to serious inconsistencies in the published data.

The definitional changes in LFSs in 1990-91 (apart from increasing the proportion of unemployed in the labour force) improved women’s participation rates in general. This may be more an effect of a categorical change and less of an actual improvement in women participation rates, which are still very low. This low rate accounts for the low overall level of participation of the labour force shows up as a trend decline in participation rates and the labour force growth over the years. For the 1990s the improvement in coverage of working women is offset by the withdrawal of the young from the labour force.

6. ON THE CHANGING ABILITIES OF THE LABOUR FORCE

The composition of labour force by level of education has witnessed changes in Pakistan (Table A1.8). With the improvement in the literacy rate, the proportion of the literate labour force has increased from 39.9 per cent in 1990-91 to 43.6 per cent in 1994-95. While the share of literate men in the labour force increased from 37.3 per cent to 40.1 percent, that of women increased only marginally from 2.57 per cent to 2.67 per cent.23 Clearly, if one criterion for employability is literacy, then an explanation of low participation rates of women is low literacy, which needs to be a policy focus.

The literacy rate of the labour force has risen from 35.3 per cent in 1987-88 to 43.2 per cent in 1994-95. Over this period, the share of degree holders has shown the sharpest rise (from 1.8 per cent to 2.9 per cent), followed by that of matriculates (from 9.4 per cent to 13.2 per cent). The composition of employed work force by the level of education has also undergone significant changes (Table A1.9).24

Within the literate labour force, employment growth rates have been positive for all levels of education except for the holders of degrees in medicine and those with no formal education25. The proportion of literates in the labour force is also increasing albeit slowly.

21 See Sathar and Kazi (1997).

22 Shah and Sathar (1978).

23 Within the literate labour force, pre-matriculates in 1994-95 accounted for a major share (57 per cent) followed by matriculates (23 per cent) and those with intermediate degrees (9 per cent). Graduates accounted for about 9 percent of the literate labour force. Within graduates, about 90 percent hold degrees in subjects other than engineering, medicine and agriculture. Engineering graduates were 12.3 percent; medical, 4.5 percent; and agricultural graduates, 1.2 percent.

24 The composition of employed work force by sectors shows wide variations. According to the latest LFS (1994- 95), about 74 per cent of the employed labour force in the agriculture sector was illiterate as against 7.8 per cent in finance, insurance and business services, and 17.1 per cent in the electricity and gas distribution sectors. Next to agriculture, the illiterate accounted for 69.4 per cent in construction and 58.3 per cent in mining sectors. Within the literate, the most highly qualified persons were found in finance, services and electricity and gas sectors.

25 The declining share of medical graduates is not easily explained. Perhaps they are included in the “postgraduate” group, which has registered a growth of about 13.3 per cent per annum.

15 Although literacy is increasing 56 per cent of the labour force are still illiterate and about another 10 per cent literate only at pre-matriculate levels or with no formal education. Efforts to introduce new technologies and management techniques in the short-run, essential for the improvement of productivity and efficiency, are likely to be constrained.

Labour force expectations and the structure of the job market

Although it may be true that economic growth itself is fundamental as a final adjuster of the labour market in the medium run, it is also arguable that, at least in part, mechanisms of adjustment depend upon the perceptions of those who bear the burden of adjustment in the labour market, namely the unemployed and the underemployed.

A question was put in the LFS of 1993-94 to those who were not working in the reference week regarding work expectations. These expectations are indicative of a mismatch with prevailing sectoral, as well as locational, conditions of employment. This is an interesting finding, which needs some elaboration. In the LFS of 1993-94, nearly two-thirds of the unemployed expressed the wish for employment with government, a proportion which, if realized, would be more than twice the current governmental share in employment. Nearly one-fourth of the unemployed preferred clerical and related jobs. This is mainly the response of the matriculates and intermediates. On the other hand, only 1 per cent of the unemployed said that they would like to work in the agricultural sector while nearly half of Pakistan’s employed are still in the occupational category of agriculturalists and forestry workers. Occupational preferences of the unemployed do partly reflect their educational background, but the dissonance which is being reflected here is really between the development of an educational system and the production structure and needs of the economy.

Orientating a future labour force (which will increase in growth and literacy) towards the types of activities the future holds should be an essential part of the training and skilling efforts being made today. This is an important challenge for the future of both the labour force and the country.

7. UPSHOT

Pakistan had a population of around 128.3 million in 1994-95 of whom 85.4 million were above the age of 10. The labour force size is 35.2 million (29.3 employed; 4.0 underemployed and 2 unemployed). Those who were outside the labour force, excluding students (17.4 million) were around 32.8 million, 30.1 million of whom were women. The growth of the labour force has been lower than that of population on trend in the past. Urban labour forces have also been growing faster than rural ones due to rural-urban migration, although there are some indicators in the 1990s that internal migration may be halting and trends could be reversing.

The rate of growth of the labour force in Pakistan has been falling in the past but it is expected to rise in the near future. Unemployment and underemployment trends suggest a worsening or certainly no improvement in the recent past. This means that the problems associated with those who are not fully employed is likely to increase when labour force growth picks up. The labour force is also slowly becoming more literate in Pakistan.

Apart from the matters pertaining to restrictions in the growth of population, there are three areas which require focusing from an employment perspective. These relate to data, participation rates and training.

Data

The coverage of the LFS must improve. This is with respect to the excluded sections of the adult population, which are dominated by women. Moreover, definitions need to further improve to include home workers, as well as other categories of persons who may be excluded for non-technical reasons. The Population Census must be

16 conducted without delay. It is the fundamental basis of any serious policy work, quite apart from being a necessary cross-check on the Labour Force Surveys. A country the size of Pakistan cannot afford to avoid a Population Census for seventeen years, no matter what the domestic political fall out of this may be. Consistency exercises must continue to be in built into data collection, as was the case in the 1990-91, whenever definitional changes take place, so that trends can be readjusted. A consistent series of best-possible estimates of all labour market indicators in Pakistan needs to be built, which adjusts and reconciles the data available from different sources.

Participation Rates

Clearly, participation rates have been very low and declining in Pakistan. These need to be improved for the productive absorption of the labour force in the economy. The issue of female participation rates is a subset of the general issue. The reason for the increase in the low participation rates for women is not necessarily only because more women are working but because definitions have improved. The causes for the low participation rates as well as high incidence of women in those excluded from the labour force need to be ascertained carefully. The extent to which this is due to social factors, definitional problems, or coverage need to be distinguished empirically. On a general plane, the low participation rates needs to be improved to effect a more productive use of labour in the economy.

Training and skills

There must be a conscious attempt made to bring the expectations of the literate labour force which is either not in employment or likely to come into the labour force in the future, into line with actual possibilities in the job market. This should be done both at an educational level as well as at the level of training programmes.

Implications for a strategy

From the perspective of a strategy, two issues are important:

• the labour force growth is expected to increase in the future;

• problems associated with those who are less than fully employed, are likely to worsen with the expected rise in labour force growth.

17 CHAPTER TWO Output Employment and Productivity: Lessons for an Employment Strategy

1. A DUAL FOCUS

The magnitude of the employment problem facing Pakistan in the future is considerable. Even if the rate of growth of the labour force is likely to pick up in the near future, the deteriorating employment situation is likely to worsen more than present trends anticipate.

There are two related matters for concern: the gap between population and the labour force and a rising labour force in comparison to the “fully employed” within it. An increasing gap between population and labour force growth for a given output implies the increasing dependency of a rapidly growing part of the population on a slowly rising labour force. Under these same conditions, the increase in the gap between the fully employed and the labour force implies constraints on the earning capacity of the labour force itself. This has direct and demonstrable implications for poverty.1

One goal of a future employment strategy is therefore to reduce the growth of population. The other, and what we are concerned with in this report, is to productively increase the participation of the labour force in the economy. In doing so, the aim is to improve aggregate employment and attack the twin problems of unemployment and underemployment head on. The next sections take a more detailed view of the employment situation.

2. EXAMINING SHARES OF EMPLOYMENT AND OUTPUT

Given the critical situation described above, employment strategies need to be devised in order to face the employment challenge. The absorption of a larger percentage of population in gainful work, as well as the reduction of the under employed and unemployed, are important goals.

It would, however, be hazardous to proceed as if all that needs doing is to direct efforts towards an expansion of sectors with higher employment elasticities and wait for employment to happen. The precarious nature of estimating elasticities of employment in Pakistan has been discussed elsewhere2. For the purposes of the present analysis, our position is that elasticity estimates, though useful in the generation of ball-park projections, are on their own, insufficient for planning an employment strategy. Moreover, the estimates tend to become more inconclusive the better the methodology used. Elasticities have generally been low in Pakistan and they have been lower in the high growth period of the 1980s

1 On their criteria of “basket of basic needs”, (Gazdar et al. 1994) find a very drastic decline (18.7 per cent) in poverty in Pakistan between 1984-85 and 1987-88, which is clearly a period when employment growth outstripped labour force growth. Their estimates for 1990-91 show a much smaller decline (9.1 per cent), which was a period in which labour force growth was generally matched by employment growth. Poverty gap measures like the ‘poverty gap’ (PG) and ‘Forster-Greer- Thorbecke’ (FGT) Index, which take into account the average income of the poor and its distance to the poverty line confirm this observation more conclusively. From 1984-85 to 1987-88 to 1990-91 the PG declined from .111 to .077 to .071, while the FGT declined from .038 to .023 to .022 (Table A2.8).

2 ILO-SAAT, Arshad Zaman Associates, 1997 (mimeo).

18 than they were in the relatively lower growth periods of the 1970s and 1990s 3. The increasing trend in employment elasticities are however, is not a simple index of ascertaining the “labour absorption capacity”of an economy. We need to look at other indicators implicit in the elasticity measure, in order to make some judgements on the quality of the labour absorption which the elasticity measure signifies.

Although sector-specific analyses are necessary for producing the details of an employment strategy that can lead to concrete policies, an aggregative analysis of the sort attempted in this chapter can still provide a plausible a sectoral prioritization within an economy-wide framework. The following sections examine the sectoral trends in employment in Pakistan before proceeding to study the indicators of employment implicit in an elasticity measure: growth in output, employment and labour productivity.

3. SECTORAL SHARES OF EMPLOYMENT AND OUTPUT

As far as sectoral distribution of output shares are concerned, in the long run agriculture’s share declined from 39 per cent in 1971 to 24.3 per cent in 1997 (Table A2.2). GDP shares of manufacturing have increased on trend; they were 14.16 per cent in 1971 and 17.92 per cent in 1997. There are small increases in other sectors’ GDP shares. The decline has essentially been for agriculture and the gain for most of the other major sectors. This is to be expected in the process of development.

Sectoral shifts have also taken place in employment shares over time. Once again for agriculture there has been a long-run trend decline but from the mid-1980s the share has been fluctuating between the 45 per cent and 55 per cent mark (Table A2.3). It can be argued that although the share of employment has declined for agriculture, over the longer-run period, it has been fluctuating within a range in the last decade. On the other hand, contrary to expectation, there has been a declining trend in the share of manufacturing in employment from 1969-70 (15.57 per cent) to 1993-94 (10.12 per cent), although employment shares on average rose slightly from the 1970s to the 1980s and then declined in the 1990s. All other sectors which include construction, trade and the “other” activities category over a longer-run period, from say 1970-71 to 1994-95, have shown an increase in employment shares. It is therefore quite reasonable to argue that accompanying the longer run decline in employment in agriculture, say from 1969-70 onwards, there have been increases in employment shares of sectors other than manufacturing.

In the recent and shorter-run period of the 1990s, however, agriculture’s fluctuating share of employment forms no trend (except that it breaks from the past trend of a declining share of employment), while the share of manufacturing (and mining) in employment has definitely fallen from 12.54 per cent in 1990-91 to 10.12 per cent in 1993-94.

4. GROWTH OF EMPLOYMENT AND OUTPUT

Although we need to be aware of the standard limitations of the elasticity measure, it is still worth examining the trend in employment elasticities, and of output and employment growth for the economy as a whole over the years. This in conjunction with other measures can help identify general trends. Figure 2.1 below splits the employment elasticity measure into its two components: employment growth and output growth.

3 They have increased in the 1990s compared to the 1980s.

19 Figure 2.1: Growth of Real GDP & Employment, and the Output-Elasticity of Employment, 1971-72 to 1996-97 2.00

8.00 1.50 6.00

1.00 4.00

0.50 2.00 Elasticity - 0.00 Growth Rate (%)

-2.00 -0.50 Fiscal Years Ending June 30

-4.00 -1.00 GDP Employment Elasticity

The economy-wide picture shows a few features clearly.

• GDP growth rates were low in the 1970s, highest in the 1980s and have fallen in the 1990s again. Excluding the past couple of years, they are nevertheless reasonable growth rates.

• In relation to GDP growth, employment growth has been low in Pakistan’s economy. In the early 1970s employment growth hit a sustained high level. During the high growth period of the 1980s, employment growth was very low and since the mid-1980s it has been much more variable.

• The elasticities of employment have generally followed employment growth, confirming the view that output growth has been the relatively more stable part of the employment elasticity measure in Pakistan.

This leaves the matter of the recent volatility in employment growth, which appears seems to be a new structural feature in the Pakistan economy, as an issue that needs to be explained. Examining sectoral employment changes over time delineates the sources of this volatility.

5. SECTORAL EMPLOYMENT ABSORPTION

One question that needs answering in an economy-wide context is: why has the structure of employment growth become so volatile?3 As a first step, this requires one to explore sectoral trends in employment in more detail. The Figure below presents data on annual changes in the number of persons employed by sectors.4

3 The answer as to why GDP growth has declined from the 1980s to the 1990s is complex and requires both a sector specific view as well as analysis of macroeconomic policies.

4 The net change in any year is the difference between the positive change and the negative change.

20 Figure 2.2. Changes in Employment (000) 1971-96

2.00

1.50

1.00

0.50

- 70- 71- 72- 73- 74- 75- 76- 77- 78- 79- 80- 81- 82- 83- 84- 85- 86- 87- 88- 89- 90- 91- 92- 93- 94- 95- 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 -0.50

-1.00

-1.50 Agriculture Mining & Manufacturing Construction Trade

-2.00 Others Elec.Gas& Trans.

-2.50

Although the data presented are not free of problems,5 they do show that:

1. Three kinds of trends are discernible: first, a period of high and rising labour absorption in the early 1970s (until 1978-79); second, a period of stable job creation (about 500,000 jobs per year) from 1979-80 to 1984-85; third, an unstable trend in labour absorption since then, which reached a high in the 1991-92 period and seems to be on a cyclical downward trend. 2. Employment in general has definitely become more volatile since the mid-1980s and agriculture to account for the largest share of changes in employment (positive and negative). Volatility in employment is thus partly connected to the agricultural sector. 3. Unlike the early years (the 1970s), manufacturing has not played a major role in labor absorption, although it has contributed both positively and negatively in specific years (especially 1986-87, 1987-88, and 1992-93). This means that manufacturing is also a contributor to the volatility in employment. 4. In recent years (especially since the late 1980s) the wholesale and retail trade sector tends to play a large role in employment creation. This also true for the residually defined “others” category. A large part of these sectors are likely to be in the SSE (Small-Scale Enterprise) sector.

5 Especially the significant falls in employment in agriculture in 1990-91 (when there were major floods) and 1994- 95, lesser declines including in “other” sectors in six other years, and the sharp rise in 1986-87, which requires further investigation.

21 6. DECOMPOSING OUTPUT GROWTH

The employment swings discussed above and the trends in elasticity observed are consistent with the decomposition of output growth presented for the 1970s, 1980s and 1990s decades in Table 2.1 below. Output growth decomposes into two contributing components: employment expansion and labour productivity and accordingly periodizes the Pakistan economy since the 1970s.6

Table 2.1: Decomposing output growth, productivity and employment effects MM P @@ Nto'M'M Y MM N @@ Pto 'M'M Y Productivity Employment MM N @@ MM P'M'M Y Effect Effect Multiple Effect

1969/70 – 1980/81 0.292 0.615 0.118 1980/81-1990/92 0.578 0.273 0.148 1991/92 – 1994/95 0.400 0.571 0.028

Source: National Income Accounts and Labour Force Survey (various years).

The employment effect was strongest in the 1970s after which there was productivity- led growth in the 1980s. The high growth period (1980s) was least driven by employment expansion as a contributor. In the 1990s, there was a shift back towards a growth process which is partly based on increasing employment. Given that the 1990s are a relatively lower growth period, we need to probe further into the nature of this employment expansion. In the section following we examine the employment conditions which charactercized the changes, as reflected in wages and poverty.

7. WAGES AND POVERTY

Where organized labour is not the largest part of the hired labour force7, and where a multiplicity of contractual arrangements exist, it is important to analyse not only real wages over time but poverty as well. Unfortunately, the database on wages is limited in Pakistan and poverty assessments not only differ in methodology but are also constrained by data sources that are not current. The importance of wages and poverty indicators necessitates an attempt at their assessment. We start by discussing wage rates (Table A2.10).

6 The following is a symbolic decomposition of Output change in to: (i) employment effects, (ii) productivity effects, and (iii) multiple (of employment and productivity ) effects. The basic symbols are:Output = Y; Employment = N; Productivity = P; Intitial time period = to ; Change over time = M . P= Y'N N= Y'P Y= P @ N Then, Change in Output is: M Y = M P @ Nto % M N @ Pto % M N@ M P Dividing by M Y M P @ Nto'M Y % M N @ Pto 'M Y % M N@ M P'M Y = 1 The Change in Output decomposes in to: (i) An employment effect=M N @ Pto 'M Y (ii)A productivity effect=M P @ Nto'M Y (iii)A multiple effect = M N@ M P'M Y

7 For a recent review see Amjad and Kemal, 1997, (mimeo) ILO-SAAT.

22 Real Wages

Wages rates are clearly more relevant to that part of the labour force which is hired, a figure previously mentioned as not much more than half of the employed labour force. About 56 per cent of the employed labour force is hired., the rest are self-employed. It is, however, not inconceivable that the poorer sections of the self-employed in Pakistan (particularly in agriculture) also offer themselves on the labour market as part-time casual workers. 8

The percentage of hired labour which is permanent relative to those on casual contracts is likely to be small. Much of this organized labour force is either in salaried government jobs or in the organized private sector of the economy. A smaller proportion is likely to be in the organized industrial workforce. Consequently, the dominant form of hired labour in Pakistan, in an economy-wide sense, is casual workers, some who offer themselves on casual wages throughout the year, others who do casual work only as a part- time activity.

There are three wage rates available for the agricultural sector from the 1980s. One for each season (Rabi and Kharif), and a general casual wage rate. It can be argued that the dominant type of casual labour used in agriculture is season-specific and not of a general variety, the latter usually representing the casual labour available in rural areas. The wage rates for two seasons (Rabi and Kharif) in agriculture show an increase up to the end of 1980s and then a decline in the 1990s. The general and non-seasonally specific casual wage rates in agriculture also suggest an increasing trend till the end of 1980s and have then fluctuated. It is clear that overall real wage rates in agriculture increased in the 1980s and are witnessing a decline in the 1990s (Figure 2.3a).

Real wages of the organized industrial sector, have increased on trend from the 1970s, although there is no data available for recent years. As suggested earlier, this is likely to be a small proportion of the total employed labour force ( not exceeding 10 per cent). The category of skilled workers can be seen in real wages of masons: an increase in real wages in the 1970s, a decline in the early 1980s and an increase on trend from the late 1980s onwards (Figure 2.3b).

2.3 a: Real Wage Index- Industrial and Skilled 200

150

100

50 0 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 Industry Masons

8 An indication of this can be gauged from the distribution of job by the organization. In 1993-94 LFS 9.5 per cent of the employed were the `formal’ employment, the rest were in semi-formal (22.9 per cent), agriculture (47.8 per cent) and informal (19.8 per cent) employed. It is also the case that in 1993-94 only 33 per cent of the employed were categorized as `employees’. If we add the semi-formal and informal employed nearly 43 per cent are likely to be “unorganized” workers. This is the lower-bound since the bulk of hired workers in agriculture are also likely to be of the casual variety, and therefore a part of the unorganized labour force.

23 Figure 2.3 b: Real Wage Index - Seasonal Agricultulture 140 120 100 80 60 40 20 0 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 Rabi(ag) Kharif(ag)

The real wage index of unskilled labourers is based on data of casual workers in construction. It can be taken as a proxy for non-agricultural urban casual workers, which are likely to dominate the urban small- scale and informal enterprise sector. This also shows a trend increase in the 1970s, and then a decline till the mid-1980s, which increases briefly during the late 1980s and then shows a slow decline through the 1990s. The pattern is clearer for real wages of unskilled casual labour an increase in the 1970s and a decline in the 1990s (Figure 2.3c).

Poverty Trends

Trends in poverty are difficult to estimate in Pakistan because research is often based on different poverty lines and a number of problems also exist with the types of data often available. There is, however, a need to view the trends in poverty in Pakistan, both rural and urban, from an employment perspective.9 Malik (1988) has estimated poverty lines from 1963-64 to 1984-85 on a consistent methodology based on calorie norm.10 Figure 2.4 shows that poverty increased in Pakistan during the 1960s (although urban poverty declined). It began declining during the 1970s and this decline continued up to the late 1980s. After the late 1980s (1987-88) there is every likelihood that poverty increased, at least up to 1990-91, after which it has either increased or remained the same. The 1990s trend is therefore likely to be one of increase.11 It is true that the total poverty trend described above is generally reflected in the trends in rural poverty and not urban poverty. Urban poverty has shown significant declines when total poverty has increased (1960s and the 1990s). Urban poverty may have started declining again in the 1990s, while rural poverty is probably either not declining or is increasing. This is of immediate relevance for our impression of wages for the early 1990s and is quite consistent with the reversal of past urban-rural labour force growth trends in the 1990s.

9 The reason is that employment conditions in Pakistan are reflected in the poverty levels of a society which is characterized by multiple contractual arrangements (implicit and explicit) and extended family systems.

10 The consumption limit is that of 2250 calories per day. The methodology is from Mujahid (1973) . The same methodology is used to estimate the series through to the 1990s. The Figure on poverty trends is based on this series. It is a consistent series.

11 It is true that if a poverty trend is fitted over the longer term then poverty will appear to be declining on trend. This however is not legitimate, there seems to be some change coming about in the late 1980s. This argument is sometimes used in order to imply a correspondence between economic reforms and poverty alleviation and is not legitimate.

24 2.3 c: Real Wage Index: Agricultural/Rural (Casual) Urban Unskilled(Casual) 150

100

Agriculture Unskilled Labour

Figure 2.4: Poverty in Pakistan:Head Counts

Total Rural Urban 2 per. Mov. Avg. (Rural) 2 per. Mov. Avg. (Total) 2 per. Mov. Avg. (Urban)

30 %

Poverty, Wages and Growth

It is also useful to make some qualitative assessments about poverty and wages and growth taken together.

For the 1970s, it is fairly clear that poverty declines in both urban and rural areas were matched by a universal increase in all types of real wage rates for most of the period. Whereas GDP growth was not so high, the growth that took place was driven by employment expansion. It very clearly demonstrates the inverse relation between poverty and real wages.12

In the 1980s, when poverty continued to decline but less fast than it did in the 1970s, we have a mixed picture of real wages. In this situation we need to make judgements on the weight of activities in the

12 One needs to be careful in qualifying this inverse relation. The relevant real wage is important. The correlation between real wages ( industrial) which have been increasing over time and poverty which on trend in the longer run is decreasing can be shown to be reflective of the inverse relation. In fact it is not because industrial wage earners are in a minority in the employed labour force.

25 economy for which the real wage is a proxy. In our view it is the casual wages in agriculture, especially the seasonal ones and the urban casual unskilled wage rates which would affect most of those offering themselves on the labour market. General agricultural/rural wage rates (which reflect the rural non- farm sector as well) showed an increase until the late 1980s; agricultural (seasonal) wages increased on trend in this period. The wages of the unskilled urban workers declined and increased again. There was an increase in skilled workers wages and that of the organized industrial sector. On the whole those real wages which showed a cyclical trend balanced out, while others increased until the late 1980s. The net effect was an increase in real wages and reduction in poverty. This period was one of high growth which was dominantly labour-productivity driven. The inverse relation between real wages and poverty is therefore maintainable for the 1980s.

The 1990s show a decline in real wages of the agricultural seasonally specific wages and a fluctuating cyclical trend in general agricultural/rural wages. Unskilled urban casual wages have also declined. Poverty as we know has probably increased and has certainly not declined in the 1990s. This too confirms the inverse relation between poverty and real wages. It is, however, also evident that the 1990s (like the 1970s) are not a high growth period such as the 1980s were. Growth in the 1990s is less driven by employment expansion than was the case in the 1970s.

In general it may be arguable that in Pakistan, although poverty and real wages are related inversely, as should be the case in an economy in which hired labour constitutes more than half of the employed, both high and low GDP growth situations have led to the alleviation of poverty. However, in the low growth scenario the composition of growth needs to be dominated by employment expansion (as opposed to labour productivity), in order to reduce poverty and improve employment conditions. This is probably not happening in Pakistan in the 1990s. We can now return to examining the employment indicators implicit in the elasticity measure which, as we have seen, had increased from the 1980s to 1990s.

8. ELASTICITY, EMPLOYMENT, LABOUR PRODUCTIVITY AND OUTPUT: AN INTEGRATED VIEW

Quite apart from problems of estimation,13 it is the case that employment elasticities implicitly contain information that may be useful in assessing the employment situation. The overall association of productivity growth and employment growth in any given period is implicit in the elasticity measure by definition. It is, however,m partly determined by technological relationships that obtain within sectors, which are likely to differ across sectors and which are smoothed out or concealed when represented (implicitly) in an elasticity measure or aggregated at an economy-wide level.

It can be argued that during the development process a negative relationship between labour productivity growth and employment growth is to be expected, even a strengthening one. This can be consistent with both employment and productivity increasing at positive rates. Four interesting cases may be defined.

Case 1: When employment and productivity growth are both sizably positive, and there is the likelihood of continuing conditions of healthy economic growth which are not employment unfriendly.

Case 2: When very low (or negative) growth rates in both employment and productivity occur, it may be a sign of a potential sectoral slowdown towards stabilization. This is acceptable,

13 ILO-SAAT/Arshad Zaman Associates, 1997 (mimeo).

26 as long as the sector is unlikely to become a natural refuge sector for labour, in times of overall deceleration of growth.

Case 3: When there is negative or very low productivity growth and there is sizeable positive growth in employment, it may be indicative of stagnation in the sector. This is likely to be accompanied by increasing surplus labour and underemployment and falling real wage rates. It is important to note that this may be owing not to an unsatisfactory rate of output growth in the sector but to the employment expansion taking place within it. This is characteristic of a classic refuge sector.

Case 4: When there is positive growth in productivity and a negative or very low growth in employment, it may be indicative of a fundamental technological shift taking place in the sector.14

We now discuss productivity and employment growth simultaneously, for the major sectors (Tables A2.5 and A2.6). The following observations can be made from examining the data.

1. A negative association between productivity growth and employment growth is discernible (Table A2.6). It was weakest in the 1970s and strongest in the 1980s but the intensity of the measure in the 1990s is still greater than that of the 1970s. What it does show is that the economy in the 1990s, as a whole, is less able to absorb labour than was the case in the 1970s, although the situation has altered somewhat compared to the 1980s. It is, however, very important to note the increase in intensity of this negative relation for agriculture and construction over the same periods, particularly as sectors are usually associated with high shares of employment.

2. In the first period (1970s) productivity increased at a low rate, output growth was reasonable, and high growth in employment took place. In the 1980s, productivity growth was higher than the 1970s, employment growth lower, and output growth very high. In the 1990s productivity growth has fallen again, employment growth continues near the 1980s rate, while output growth has also declined. What has happened is that the lower output growth of 1990s is sustaining an employment growth at a level which was associated with the higher output growth of the 1980s, which has meant a decline in productivity growth. Employment elasticities, as we know, were higher in the 1970s, declined in the 1980s and rose again in the 1990s.

3. In agriculture, productivity growth was negative in the 1970s, increased in the 1980s and has shown a decline in the 1990s, employment growth has shown gradual decline over the period but is still positive.15 Output growth has followed the pattern of productivity growth: it increased between the first two decades and then declined slightly in the 1990s. It should be noted that employment and productivity growth rates have all fallen in agriculture over the 1980s and the 1990s while the rate of output growth of the sector improved from the 1970s to the 1980s and, even in the 1990s when it declined somewhat, it has not been unsatisfactory.16 So output growth,

14 Depending upon the importance of the sector for overall growth, it is entirely possible that such a shift has positive employment effects on the rest of the economy, even if employment levels are contracting in the sector itself.

15 The relationship between agricultural productivity and poverty is a negative one, Amjad and Kemal, ILO-SAAT, 1997 ( mimeo).

16 It needs to be explicitly recognized that sustained agricultural output and increasing productivity in are necessary for the economy not only because it produces the main input (cotton) for manufacturing, which goes in to Pakistan’s major export industry ( textiles), but because it also provides a large portion of the economy’s wage goods. In order for growth to

27 though slightly falling has been reasonable (around 3.4 per cent) and productivity growth has declined to a lower rate. Employment growth on the other hand has also fallen, although it is still positive. This does not explain the new volatility in agricultural employment observed earlier. Further sector-specific investigation is needed. The situation in the agricultural sector in Pakistan is similar to Case 2 (low-productivity/low employment-growth) described above.

4. The construction sector’s productivity growth has consistently fallen from the 1970s to the 1980s and 1990s, when it became negative. Employment growth in this sector has fallen although it has remained high and positive throughout. Output growth has fallen consistently over the three periods. Therefore construction seems to be a sector which is likely to be facing a crisis with increasing employment and negative productivity. This is similar to Case 3 (a stagnating refuge sector) described above.

5. In the manufacturing sector, productivity growth was very low (1.3 per cent) in the 1970s, it increased to a very high rate in the 1980s (7 per cent) and has declined to a middling (4.6 per cent) rate in the 1990s. Employment growth has very clearly seen a decline from the 1970s, through the 1980s to the 1990s. During the 1990s it has become negative. Output growth in manufacturing was around 4.7 in the 1970s, it rose to a very high 8.4 per cent in the 1980s and returned to a lower level of 4.2 per cent in the 1990s. Clearly, manufacturing is a sector where there is prima facie evidence on a de-linking of output and employment growth. The case of manufacturing is similar to Case 4 (technological shifts) described above.

6. There has been a high growth of employment in the retail and trade sector in the 1990s, as well as the residually defined “other” sector as was observed in the 1970s. Many activities in these sectors are likely to be located in the non- manufacturing smaller scale and informal sectors.

If the indicative schema and observations made above are to be accepted, then the agricultural sector is likely to be moving towards low productivity conditions (although from the productivity perspective it is not as bad as the 1970s) while manufacturing is likely to be undergoing a fundamental technological shift, in which its growth process is becoming de-linked, at least from direct employment generation. Construction is likely to have become a sponge or refuge sector, which is simply absorbing labour at negative productivity levels. There is an increase in employment growth in the retail and trade sector and the ‘other’ sectors group in the 1990s which is symptomatic of informal and small-scale enterprise sectors growth. This expansion seems associated with relatively lower levels of GDP growth (1970s and 1990s). It has also played an active role in labour absorption in the 1990s, as we have seen earlier.

9. EMPLOYMENT AND OUTPUT GROWTH LINKAGES

It is fairly obvious that the growth of the manufacturing sector has strong growth multiplier effects on the rest of the economy (Table A2.7iii), but in looking at employment growth rates for different sectors of the economy we find an interesting set of relationships between employment growth in manufacturing and employment growth in the rest of the economy. Examining simple correlations between sectoral employment growth rates (Table A2.7i), it is clear that growth in manufacturing employment is most strongly related to economy-wide employment growth and, in particular, has positive and relatively stronger linkage effects on employment growth in most other (non-agricultural) sectors of the economy. This is an encouraging finding from the point of view of setting up guidelines for an employment strategy.

proceed smoothly agricultural surpluses are critical.

28 The greater the extent to which growth in manufacturing is employment-based, the greater will be its employment multiplier effects on the rest of the economy. However, promoting employment friendly growth does have a potential problem that employment elasticities in manufacturing are low and productivity growth during the 1990s has been associated with a negative employment growth. Hence, the situation in manufacturing is that output growth cannot be expected to generate much direct employment. This is an area which requires special focus in a sector-specific analysis, with special attention paid to the distinctions between the large and small-scale manufacturing sectors.

10. THE AGENDA FOR AN EMPLOYMENT STRATEGY

The trends in the labour force and employment in Pakistan suggest that with the already low and declining participation rates of labour in the economy, labour force growth is itself declining. In this situation, unemployment persists and underemployment is increasing. The indicators of employment conditions, i.e. real wages and poverty, reflect this worsening in the 1990s. In our view, there are also good reasons to expect an increase in labour force growth in the near future. This swelling in the labour force growth is also likely to change the composition of the labour force to a more literate one. In short, the current employment problems facing the economy are likely to magnify in the near future. The major challenge is to attack the problems of unemployment and underemployment and to increase aggregate employment significantly as well.

Apart from controlling population growth, which is an important part of an employment strategy, we need to look closely at the changing features of employment as a whole and in particular sectors of the economy. These issues stand out:

1. An important matter that has emerged concerns growth itself. It is clear from the periodization of Pakistan’s history that although high growth periods, lead by increases in labour productivity, can be accompanied by improving wage rates and declining poverty, a low growth period, if it is to improve wage rates and decrease poverty, cannot be based excessively on labour productivity.

2. There is a certain volatility to employment patterns observable in recent years at the economy-wide level. This may reflect widespread shifts in contractual arrangements and is an essential issue to explore.

3. The role of agriculture in future employment absorption needs to be very seriously examined. Until now it has only performed reasonably in terms of growth but appears to have been involved in the swings in employment absorption in recent years. Rural-urban labour force growth rates may also be reversing, and this requires special consideration from the point of view of agriculture. Since poverty is inversely related to productivity in agriculture, a swelling of the labour force in rural areas, if there is insufficient absorptive capacity in the rural non-farm sector, could put pressure on the already low and slowly increasing productivity growth rates.

4. There is a growth and employment linkage between the economy as a whole and the manufacturing sector.

5. Manufacturing is not only critical for output growth but its role in employment-generation needs to be explored. It has clearly faced a crisis of sorts in recent years, but it should be noted that its output growth, though much lower than the 1980s, has not been all that low in the 1990s, exclusing the past two years. Manufacturing is critical for growth and growth is crucial for productive employment. However, the crisis is in employment within manufacturing. For an employment strategy, both a ‘revival of output growth’ of manufacturing as a whole and the

29 location of its employment crisis need to be assessed. The manner in which employment linkages are affected between manufacturing and other sectors is also important to assess. In short, the revival of growth and the nature of low employment elasticities must be the critical focus of an employment review of manufacturing.

6. There is a need to examine the growth of the small-scale enterprise sector and its employment absorption which not only covers manufacturing but other labour intensive-sectors of the economy. The necessary focus is on the nature of growth and the potential in it for employment-generation. Taking into account the caution required for greater employment absorption in agriculture and the apparent limits to employment growth in manufacturing, it is clear that those sectors of the economy covered by the SSE sector become critical from the perspective of an employment strategy.

30 CHAPTER THREE The Agricultural Sector

1. INTRODUCTION

Agriculture in Pakistan has had reasonable output growth in the past.1 At the aggregate level, its growth was showing signs of decline from the 1980s to the 1990s.2 On the other hand, employment growth in the sector continued to be positive though it also declined on trend in the 1990s. The sector could be moving towards a situation where it may be forced to absorb large sections of the labour force, possibly unemployable in other sectors that face a slow-down in output growth. This possibility is also reflected in labour absorption in the sector, which showed that it was the main sector ‘adjusting’ to employment fluctuations in the economy. Part of the reason for this is external to the sector. When the overall economy faces a slowdown, its largest employer (even if its sectoral employment share is declining over the longer run) is likely to experience a swelling in its labour force relative to the output it produces. In the present chapter, we explore these external causes of change as well as what may have happened to the structure of output and employment within the agricultural sector.

2. THE SPECIAL NATURE OF EMPLOYMENT AND OUTPUT IN AGRICULTURE

Some points need to be noted about employment and output that are specific to agriculture and necessary for interpreting the trends in Pakistan.

Measurement of employment

Employment in agriculture is family-based and also uses hired labour both on a casual/part-time and well as a permanent basis. In other words, employment in agriculture is non-homogenous3 and does not directly depend on the labour market for all its supply of labour. Seasonal demand for agricultural labour means that those employed, can be expected to be “underemployed” at least some of the time. The notion of full- time work; the role of the labour market in the supply of labour and the aggregation of different types of workers into the employed category are less straightforward in the agricultural sector.

The special nature of output

The determinants of agriculture output are also different from those of output in other sectors. In agriculture, output is partly dependent on external uncertainty, this means that weather is an important determinant of output, especially at low levels of output. Therefore, whenever there are conditions of an immanent collapse of output, labour which has already been employed, appears less productive

1 Although it has expectedly been lower than overall rates of growth.

2 See Chapter1 Annex Table A1.5.

3 The assumption that is implicitly made is on the duration of work-time and effort associated with a unit of labour. The quantitative difference between family labour and hired permanent labour which are both full-time is that the former requires supervision while the latter does not. Therefore aggregating the two may not be strictly appropriate. But there is an even more fundamental and qualitative difference between a ‘unit’ of family labour and permanent labour on the one hand, and casual labour on the other. No assumptions on comparability can be made on time and effort between these two units, yet employment figures do a headcount of all labour. Non-homogeneity in agricultural labour can lead to a fallacy of aggregation.

31 (productivity declines). Agricultural output collapses are less often failures of demand and are more supply- side determined. Clearly then the measure of labour productivity in such a situation is not so much a proxy of the contribution of labour assuming employment is counted properly) to production but reflects the overdetermining influence of other external causes that influence output.

Thus, we need to be cautious in using ‘employment’ and ‘output’ categories in themselves or in standard measurements, when analyzing the agricultural sector. We now select two features of this discussion, external uncertainty with output and casual labour use in employment, to posit a combined effect which may be of special relevance in Pakistan.

A combined effect

The degree of external risk in agriculture is also sensitive to the technological features of the production process. The HYV technical input package, in use in Pakistan, which is based on robust varieties of seeds, also requires the use of complementary inputs,4 the application of which is subject to serious time constraints.5 It can be argued that the widespread use of the package, though growth- enhancing on average could also increase the sensitivity of the production process to this external uncertainty. If this is the case then it should be reflected not only in an increasing level of output on average but also in relative output instability post-adoption.

One response to increased external risk (due to the profitable technological package and uncertainty), is that land-owning employers move towards flexible arrangements with labour, to reduce a part of their wage-cost risk due to the vagaries of weather. The use of casual labour,6 particularly during labour demand peaks, can generate this flexibility.

It also means that the greater the proportion of casual labour in the agricultural labour force, the more closely the employment growth trend in agriculture is likely to follow the output growth trend, because it is precisely the casual labour component of the labour force that becomes its variable part.

This would also imply that in conditions of economy-wide low growth, levels of surplus labour in the agrarian economy will be high and underemployment and poverty due to the changes in the composition of the labour force and its casualisation will become increasingly visible.

4 The application of complementary inputs (seeds, fertilizers, pesticides, irrigation, labour) may also be costly as everyone does not have equal access to the capital market.

5 See e.g. Sen (1980).

6 There are other reasons for the increased use of casual labour: (a) the profitability considerations of land owners in a situation where potentially higher yields prevail; and (b) their need to expand production on wage labour and reduce share tenancy (in which output sharing parameters are considered to be norm-determined and inflexible). The problems with permanent labour are supervision costs and underemployment due to seasonality. This suggests casual labour use as a solution. Increasing landlessness also tends to provide a pool for such labour.

32 3. OUTPUT AND EMPLOYMENT GROWTH RATES IN PAKISTAN’S AGRICULTURE

The growth of output in agriculture has been positive and increasing (tables A3.1 and A3.2, A3.3) in Pakistan. The sector has by and large under-performed GDP growth but its growth rate is reasonable. Figure 3.1 shows that the pattern of output and employment growth has been fluctuating much more since the mid-1980s. Although it is quite true that output growth was much more stable in the 1970s, which meant stable employment growth and stable elasticities, it is likely that the fluctuations apparent from the mid-1980s have contributing factors other than external uncertainty.

Figure 3.1: Agriculture Growth of Real Value-Added & Employment, and the Output-Elasticity of Employment 15.0 5.0

4.0

10.0 3.0

2.0 5.0

1.0

0.0 Elasticity Growth Rate (%)

-1.0 -5.0 Fiscal Year Ending June 30 -2.0

-10.0 -3.0 Value added Employment Elasticity

These patterns may have something to do with the changing nature of both output and employment. For output, the country-wide use of the HYV technological package by the 1980s (tables A3.3a and 3.3b) meant that its sensitivity to the timing of inputs, as well as external weather conditions with respect to that timing, became more accentuated. This may explain the increasing amplitude of movements in output growth over the years as shown in Figure 3.1.7

Because family labour and permanent labour are a constant part of the employed labour force in agriculture, the changes that may result from output booms and slumps are likely to be due to changes in the employment of the casual labour force. We therefore need to examine changes in the composition of the labour force (table A3.4). According to Agricultural Census data agricultural “employment” witnessed a 0.62 per cent annual growth in the 1980s. This excludes casual labour use, which is known to have increased phenomenally in the same period (see table A3.5)8. Permanent hired labour use has altered but

7 Agricultural output growth was been 2.1 per cent for the 1970s; 3.9 per cent for 1980s and 3.3 per cent for the 1990s (See Chapter Two, A3, table A3).

8 Labour force survey figures are therefore more appropriate for capturing total employment growth rates The data on casual labour use in agriculture are available on the incidence of farms using casual labour in the Agricultural Census. This show s 60 per cent and 48 per cent increases in casual labour over the decade of the 1970s and the 1980s respectively.

33 the weight of permanent hired labour in the census figures of permanent agricultural employment is not large enough to warrant comment (2.7 per cent).

4. AGRICULTURAL EMPLOYMENT AND TOTAL EMPLOYMENT

Throughout the 1970s the rate of growth of economy-wide employment has been, on a trend, higher than that of agricultural employment. The LFS figures are, as suggested earlier, likely to capture employment in agriculture data, which includes casual labour (table A3.5) and are therefore preferable, at least in terms of coverage, to the Agricultural Census (AC) figures. Both figures for the 1980s (AC and LFS) are, however, lower than the overall growth rate of employment. Since the mid-1980s (which is also the peak period of growth after which a gradual decline sets in), there is no longer a discernible pattern; agricultural employment growth has been higher as well as lower from the overall rate of employment growth (table A3.2). There is also a changing pattern of rural-urban migration, with rural Pakistan increasingly retaining more of the labour force (table A3.6).9 It is worth noting that for the second half of the 1980s decade,10 there is a greater increase in growth of ‘agricultural employment’ than is the case in the first half (table A3.4).11 Consequently, there are signs of a swelling in the size of the agricultural labour force.

5. DECOMPOSING THE SOURCES OF OUTPUT GROWTH

In the 1970s output growth was not too high (2.0 per cent) but it was positive and so was employment (2.1 per cent). This trend altered in the 1980s, when output growth on average was higher (3.9 per cent), and employment growth remained a little lower (1.9 per cent) but switched to an increased use of casual labour. In the 1990s output growth continues at a slightly lower rate (3.3 per cent) and employment growth is also low (1.6 per cent) but both output and employment growth patterns are more volatile (table A3.2).

We now come to the decomposition of growth exercise, which looks at the contribution of labour productivity and employment expansion to output growth, bearing in mind the qualifications made earlier regarding output, employment and productivity in agriculture. Basically, employment expansion-based growth dominated in the 1970s, shifting to productivity-dominated growth in the 1980s, and shifting back to employment expansion based growth in the 1990s, though it is now ‘shared’ with labour productivity.

In the 1970s, a more stable period of lower output growth, the employment expansion effect dominated the productivity effect for several reasons . The nineteen seventies were a period when the green revolution, although significant, had not spread nationwide (table A3.7a). The popular belief that effective land reform may come about in Pakistan encouraged landed agriculturists with significant holdings to stay in sector. This was also reflected in a spate of land resumptions, a decline in absenteeism and the expansion of

9 Growth rates of the labour force have been positive and declining since 1989-90.The percentage drop in the rural labour force growth rate from 1989-90 to 1994-95 was -10.1 per cent ; the drop in the urban labour force growth rate for the period was -39.9 per cent; and the overall drop in the growth rate of the labour force as a whole was -20.2 per cent.

10 Note this period corresponds to what is the slump in employment of the small-scale enterprises (SSE) sector of which rural employment is very significant.

11 We have already observed the phenomenon of relative decline in the rural urban labour force growth rates in the chapter on labour force.

34 cultivable land cultivation. Also, growth in other sectors is this period was low. A combination of these conditions may explain the dominance of the employment effect.12

Table 1: Decomposing output growth , productivity and employment effects -agriculture

Year Productivity Effect Employment Effect Multiple Effect

1969/70 - 1980/81 0.063 0.918 0.018

1980/81 - 1991/92 0.664 0.236 0.100

1991/92 - 1994/95 0.361 0.623 0.040

The 1980s story is slightly different. Labour productivity dominated contributions to output growth (which was also higher than in the 1970s). Reasons include the less costly expansion of land frontier (already done in the 1970s); the widespread use of a HYV input package (Table A3.7 a and A3.7 b), and greater tractorisation in parts of the country other than the Punjab, where the green revolution had become widespread earlier. The possibility of land reform had also receded from the agenda of the then military regime. But equally significantly, the decline in the employment contribution to growth in the 1980s may be due to higher growth in other sectors of the economy. Sectors that were drawing productive labour out of agriculture particularly manufacturing. It is worth noting that SSE manufacturing, which has a large rural component, was witnessing employment and output growth at least up to the mid-1980s.

The 1990s reverted to an employment expansion based effect (at levels of agricultural output growth similar to the 1980s but more volatile on an annual basis) and may reflect a deceleration of growth in other sectors, particularly manufacturing. There is nonetheless a significant contribution of labour productivity in this period as well.

Employment expansion in the presence of as large a casual labour force as exists in Pakistan in the 1990s says little about the quantum of labour used or its returns. It is worth recalling that the composition of the agricultural labour force has changed in the 1990s compared with the 1980s, and volatility of output in the sector is reflected more in employment growth than previously it is also likely to have generated a precariousness in the livelihoods of those now employed as ‘casual labour’ in the agricultural sector.

6. UNEMPLOYMENT AND UNDEREMPLOYMENT

Agricultural employment is a dominant part of rural employment. Trends of unemployment and underemployment in the rural areas reflect labour market conditions in the agricultural sector. However, unemployment, in a developing country context, in particular in agriculture, is not a good indicator of labour market conditions. In the absence of social welfare and insurance, the unemployed are generally available for work in any sector, and often do work to survive. Underemployment is therefore a better indicator of conditions in the labour market. The trends in unemployment and underemployment are examined below.

12 See Mahmood (1993), Hussain (1980), Majid (1995).

35 The data (table A3.8) show that unemployment increased on trend in the 1980s, from 1979-80 to 1987- 88. It is not legitimate to observe trends on unemployment without qualification across the year 1990-91 when LFS data is used, as in this year definitional changes took place which particularly affected the unemployed. The data show that unemployment was increasing on trend in rural Pakistan during the 1980s and was showing a trend decline in the 1990s.13

The case for rural underemployment is also mixed. It shows a decline from early to mid-1980s and an increasing trend through the second half of the 1980s and the 1990s.14 What is clear is that the rural underemployment rate is high in Pakistan.

By 1993-94 about 20 per cent of the rural labour force was either not working or only partially working in rural areas, consistent with a fluctuating pattern of growth in output and employment, which as we argued is increasingly based on the use of casual labour.15 An agricultural sector with low levels of productivity, coexisting with other sectors with limited employment absorption capacities, is likely to have a large reserve army of the underemployed with a high degree of underemployment.

If non-farm employment growth (which is the rural part of the SSE sector) had started slowing down since mid-1980s, then it can be assumed that the bulk of labour absorption in the 1990s would be in the agricultural sector, possibly as underemployment and casual labour.16

7. LABOUR DEMAND

It has been suggested above that, owing to the non-homogenous nature of the employed, increasing levels of employment (numbers of employed) may not translate into increasing use of labour (amount of labour). Consequently we need to look at the requirements of labour and the many factors which affect them. In the short-run they are best reflected in estimations based on cropping patterns.

Cropping patterns and profitability

Driven by profitability considerations, there has been an increase in the cultivation of crops with a higher labour input in Pakistan. This is clearly a trend across the 1980s and 1990s (table A3.9 ). These changes in cropping patterns which require more labour are also consistent with trends in rates of profits of individual crops (table A3.10 ).

There are two ways to respond to increases in labour requirements. One is by actually increasing labour inputs to meet those requirements. The other is by capital-labour substitutions which may reduce those

13 Between 1990-91 and 1991-92 there is continuity, a drop in 1993-94 , continuity in 1993-94 and then an increase again to 1994-95. The general trend across the 1980s and 1990s may be of an increase, it is unlikely to be of a decline.

14 It is arguable that underemployment in the 1980s was lower than what it was in the 1990s, which fits in with the picture of economy-wide high growth 1980s, continuing rural-urban migration and increases in the SSE manufacturing sectors employment in the first half of the decade and a possible decline in the second.

15 A given level of underemployed in the labour force is likely to understate the degree of underemployment more, the greater the proportion of casual labour in the labour force.

16 Although the share of rural non-farm employment in rural areas on trend has increased since the 1980s (table A3.11), agriculture was around 62 per cent of rural employment and has shown a fluctuating pattern of employment shares from 1991-92 to 1993-94.

36 requirements. Increasing labour inputs can be done by hiring additional labour or by increasing the use of existing labour (either family or hired or both).

Size and productivity: Increasing family labour use

Changes in average sizes of farms may have automatically led to the internalization of some of these increased labour requirements due to changing cropping patterns. The changes in farm size over the intercensal period have increased the incidence of small farms in Pakistan. It can be argued from research on the farm size–productivity relationship in Pakistan, that an inverse relation between farm size and labour input exists (table A3.12 ).17 So the fall in farm size due to the sub-division of holdings18 over time would increase the potential availability of labour inputs, especially family labour inputs.

It is also the case that small farms have higher total productivities and greater cropping intensities than larger ones, whereas they may have lower individual-crop yields than large farms ( Mahmood, 1997b, mimeo).

This means that small farms maximize returns through their choice of cropping patterns and greater use of labour. This response to the increasing requirements of labour is one that automatically comes about when productivity led cropping pattern changes made possible by the new technology take place over time. Large farms still have to contend with the hiring-in of extra labour, much of which is likely to be of a casual variety.

Mechanization: Reducing labour requirements The second way to respond to increasing labour requirements is mechanization 19. Some economy- wide evidence exists here as well. Farm area exclusively using bullock power has declined over the 1980s. On the other hand, farm area using a mix of bullocks and tractors as well as tractors exclusively has increased. It is clear that the effect of tractor use is the displacement of labour (table A3.13).

Tenurial shifts: Creating an available labour pool

Changes in land tenure which have taken place in Pakistan in the last two decades (a decline in tenancy) may or may not have increased productivity. Evidence is mixed and depends on the existence of disincentives in tenancy compared with owner-farming as well as on who is resuming the tenanted land. It is likely that over time disincentives in tenancy have become marginal and insignificant, at least in the Sindh province in Pakistan where the bulk of tenancy exists (Majid, 1994). Reduction in tenancy releases labour into the labour market as landless labour, which needs to get absorbed. Tenancy has also clearly declined in Pakistan (table A3.14).

8. WAGES AND POVERTY

17 The relationship is slightly exaggerated because of the casual-worker factor, as larger farms are likely to use casual labour which does not figure in the calculations. In general the relationship is supposed to be the most robust for the relation between size and of productive factors.

18 Or due to the resumption of land from owner-cum-tenants.

19 There are limits to activities within agriculture which can feasibly be mechanized. Mechanization is especially difficult for peak period labour activities, which is where the demand of labour is concentrated.

37 Results from a recent study (Gazdar, Howe and Zaidi, World Bank, 1994) shows that in rural areas, households headed by tenants and agricultural labourers have a very high incidence of poverty (table A3.15).20 These workers are at the bottom end of the range of human capital and physical assets categories. This suggests that casual workers constitute one of the poorest sections of the agricultural labour force and, given that tenancy has declined and casual labour increased, these workers are likely to be a growing section of the rural poor.

We have already discussed wage and poverty trends in Chapter Two, but a restatement is in order in the agricultural context. Nominal wage data are available on seasonal agricultural casual workers (table A3.16). Although real wages of agricultural workers improved up to the mid- 1980s, during the 1990s they have probably declined. The wage data again corroborates our expectations about the continuing slow-down of the rural non-farm employment growth since the late-1980s and the swelling of the casual labour force in agriculture. The assumption here is on the nature of the labour market and its extent of isolation. In our view the agricultural casual labour market does function in rural Pakistan; in an overall sense the wage rates are a signal of supply and demand conditions and there is some evidence to support this view. 21 Recent poverty studies in Pakistan also tend to show a decline in rural poverty from 1969-70 up to 1987-88. There is an increase in rural poverty after 1987-88 up to 1990-91, according to one study (Malik, 1996) and a slight decline according to another (Gazdar et. al., 1994), owing to differences in assumptions made to calculate poverty lines (Kemal and Amjad, 1997). However, it can be claimed with some degree of certainty that the declining trend in rural poverty either reversed or witnessed a severe slowdown in 1987-88 to 1990-91, the latest data period available. In our view the increase in rural poverty seems to be a more plausible result.

9. UPSHOT

Agricultural output growth rates were reasonable in the 1980s and 1990s. Employment growth and productivity growth have declined commensurately, leaving a more or less constant elasticity of employment (.48). However, the low employment–low productivity growth situation is sensitive to growth conditions in the rest of the economy and the sector needs to be protected on this count. An overview of the employment situation in agriculture suggests that over the 1970s, 1980s and 1990s, profitability-driven cropping pattern changes based on the new technological package may have increased labour requirements in the sector. The changing distribution of operated holdings, mechanization and tenurial shifts may have partially adapted to, as well as reduced, these increases. The rest of the adjustment has had to be borne by the new hired casual labour force, the size of which is increasing. The nature of this labour force is reflected in the extent of rural underemployment, wage rates and poverty. While underemployment is sizable (around 20 per cent including the unemployed) it has shown signs of an increasing trend since the late 1980s. The returns to casual labour suggest that both the levels of real wages and the size of the non- poor in the rural economy of Pakistan have either stagnated or declined in the last period for which information exists (1987-88 to 1990-91 for poverty and up to 1994-95 for wages).

20 As do non-agricultural casual workers and self-employed workers with assets less than Rs 1000.

21 There is a negative relationship over time between the average ( seasonal average) real agricultural wage rates and the rural participation rate (-.69), which suggests that, imperfect as it may be, the casual labour market does operate, in some basic sense as a conventional market. This is of course not a good thing in itself. Normally labour markets where wage also performs a signaling function are downwardly rigid at levels reasonably above the poverty line. This may not be the case for the agricultural casual labour market.

38 These changes have been accompanied by what can be seen as structural change in the agricultural sector. This change is manifest both at the level of the production and labour process on the one hand and the supply of agricultural labour on the other. Both these changes are noteworthy from a policy point of view.

First, on the production and the labour process. What is significant about the growth of output and employment in the agricultural sector in Pakistan, is not so much their rates of growth, but the changing composition of the labour force on the one hand and the increased variability in the pattern of its production over time, on the other. There is much greater volatility in agricultural output since the mid- 1980s, connected to the widespread assimilation of technical changes in the rural economy and now embedded in the production process. This translates into a fluctuating trend in the employed labour force, with the increasing casual labour component on the receiving end of the adjustments to this volatility in output.

The second matter concerns the expanding and impoverished pool of labour reserve from which this casual labour springs. Landlessness and near-landlessness as a consequence of declining tenancy and the subdivision of holdings is one element in this. The other may be a return labour flow into the agricultural sector because of low growth in other sectors of the economy, especially the rural SSE sector. These tendencies are likely to exacerbate the size of the labour reserve in rural areas, which then has to ‘forcibly’ get ‘absorbed’ in agriculture as a last resort.

An effective policy focus to promote future growth and employment in the agricultural sector needs to have a dual aim: the dampening of the relationship between the volatility of output and the livelihoods of the workforce; and making the livelihoods of casual labour within this workforce more sustainable.

39 CHAPTER FOUR The Manufacturing Sector

1. INTRODUCTION

In Chapter Two, we concluded that at an aggregate level an employment strategy in Pakistan has to have the manufacturing sector as a critical focus. The argument was based on two observations. First, that given the problems with the elasticity measure, at least a simultaneous examination of employment and labour productivity growth was needed. Second, that cross-sectoral employment linkages also seemed to be important. It was consequently argued that despite the fact that there was limited room within the manufacturing sector to generate employment directly, if manufacturing growth could be employment- based, it would have positive employment effects on the rest of the economy.

Within manufacturing, a distinction can be made between “small-” vs. “large-scale” manufacturing.1 This section looks at manufacturing as a whole and then focuses on large-scale sector. In a separate chapter (Chapter Five) devoted to the Small-Scale Enterprise Sector (SSE), we look at small-scale manufacturing.

2. ELASTICITY, EMPLOYMENT AND OUTPUT GROWTH

Figure 4.1 gives a visual plot of employment elasticity, as well as employment and output growth rates, in the manufacturing sector over the years in Pakistan. Plotting growth rates of employment and output is useful for an overview and we can start with the same point we made at the economy-wide level about the limitations of elasticity measures taken on their own. A stable and very low elasticity has accompanied fairly diverse output and employment growth patterns in manufacturing over the years in Pakistan. What can be claimed with some degree of confidence is that elasticity of employment is low2 in manufacturing, and this at least seems to be a structural feature of the sector. The latest period of the 1990s in Pakistan is showing a decline in both output and employment growth and this is a seriously worrying matter for the sector3. The reason for this low elasticity of employment in Pakistan’s manufacturing sector is therefore a critical policy question.

1 For statistical purposes, manufacturing and mining are added together in Pakistan. Large-scale industries (defined as consisting of registered factories employing more than five persons) are equivalent by definition to industries covered by the census of manufacturing industries. The census covers all factories registered under section 2(j) and 5(l) of the Factories Act 1934, as amended from time to time. Effectively, until 1967 this meant a coverage of all registered factories which employed ten or more persons, and since October 1972, five or more persons.

2 Estimates depend on the estimation method and time frame. We have already shown that employment elasticities in manufacturing have been declining on trend.

3 It is because of the rates of these relative declines in employment and output growth in very recent years of the 1990s that elasticity seems to be increasing now.

40 Figure 4. 1 Growth of Real Value-Added & Employment, and the Output-Elasticity of Employment:Manufacturing &Mining

15.0 15.0

10.0 10.0

5.0 5.0

- 0.0 Elasticity -5.0 -5.0 Growth Rate (%)

-10.0 -10.0

-15.0 -15.0

Value added Employment Elasticity

3. DECOMPOSING OUTPUT GROWTH IN THE MANUFACTURING SECTOR

Having observed the trend of output and employment growth, we will now conduct a ‘decomposition of growth’ exercise for the manufacturing sector.4 We will first examine how the contributions of labour productivity and employment relate to output growth, and second, whether any trend can be observed in these contributions.

In the first period of the 1970s, although growth itself was uneven (higher in the first half, lower in the second) it was roughly equally divided between productivity and employment. The next period of 1980-81 to 1991-92, the period of consistent high output growth, was based dominantly on the productivity effect (about 81 per cent) while the contribution of employment to growth was low (8 per cent). Clearly, a shift was already taking place in this period of high growth of the manufacturing economy. The last period of the 1990s is one of low and declining growth, especially in the recent years, and the contribution of employment to output growth has been negative. The entire growth process now seems to be based on labour productivity.5 This trend makes the task of boosting and restructuring the industrial sector, from an employment perspective, somewhat difficult. We need to bear in mind the cross-sectoral employment linkage caveat made in the Chapter Two, to emphasize the role of manufacturing.

4 Although such a decomposition is very useful for the periodization of employment growth in a sector in an economy and does not make restrictive assumptions on the nature of production functions, it does stop short of deconstructing labour productivity itself.

5 We examine the sources of labour productivity increases later.

41 Table 4.1: Decomposing output growth: productivity and employment effects – manufacturing

Year Productivity Effect Employment Effect Multiple Effect

1969/70 – 1980/81 0.460 0.419 0.120

1980/81 – 1991/92 0.816 0.089 0.094

1991/92 – 1994/95 1.868 -0.680 -0.188

4. OUTPUT AND EMPLOYMENT IN THE MANUFACTURING SECTOR

A low elasticity of employment has been observed in the manufacturing sector in Pakistan. Progressively over the last two decades growth in manufacturing has become more labour-productivity driven (than employment-expansion driven) and in the 1990s it seems to have been de-linked from employment expansion altogether. This picture is quite consistent with the low and declining elasticities of employment already observed. The sources of this growth need to be further explored.

While the share of manufacturing in GDP has increased from 15.1 per cent to 18.2 per cent, its share in employment declined from 13.54 per cent to 10.12 per cent. The rate of growth of value added in the manufacturing sector as a whole has been declining on a trend in Pakistan, over the Plan periods since 1982-83. This is true for manufacturing as a whole as well for large-scale manufacturing. In particular, large-scale manufacturing has experienced a serious slowdown from 1994 onwards and growth was negative in 1996-97. The 1980s were the high growth period of the manufacturing sector in Pakistan. There has been a clear decline, on trend, in the growth of output ever since6.

Table 4.2: Growth rates of manufacturing output over the sixth, seventh and eighth plan periods

Period Total Large-scale 1982-83 to 1987-88 8.2 8.1 1987-88 to 1992-93 5.9 4.9 1992-93 to 1996-97 3.8 1.7 1992-93 5.4 4.1 1993-94 5.5 4.3 1994-95 3.6 1.5 1995-96 4.4 2.2 1996-97 1.8 -1.4

Source: Based on Economic Survey (1996-97 and previous issues).

6 Data produced in the Pakistan Economic Surveys show consistently higher total growth rates than growth rates of the large-scale sector, the implication being that small-scale sector growth in manufacturing is very high. We will return to this important matter in another section. But this qualification has a bearing on the official figures for manufacturing taken as a whole.

42 Manufacturing comprises both the small-scale and large-scale sectors in Pakistan. The small-scale sector dominates employment in it, while the large-scale sector dominates output. Table 4.3 shows that although output growth has taken place in the manufacturing sector in both its small and large-scale sections, employment began to decline in the small-scale sector in the mid-1980s. There seems to be some constraint that the small-scale sector begins to face at this time. In other words, the de-linking of employment from growth which was taking place in the manufacturing sector in the 1980s, may have been due to the overwhelming weight of the declining employment in the small-scale manufacturing sector and not because of the large-scale sector as such. The picture after 1990-91 is constructed on the basis of National Income Accounts (NIA) and the labour force surveys (LFS), and there is not much that can be said about the large-scale and small-scale manufacturing sector separately here, except that overall growth of the sector has fallen further, and there has been a negative employment growth. It would seem that at least the same trend with respect to the small-scale sector employment can be assumed.

Table 4.3: Output and employment in manufacturing

Output Employment in Growth Share of rate of Employment manufacturing Period total (Mill. nos.) sector in total Large- Small- Large Small employ- Total employment scale scale Scale Scale ment manufac. manufac.

1982/83 45.60 33.80 11.70 3.50 13.54 0.465 3.04 0.30

1983/84 49.20 36.50 12.70 3.61 13.69 0.476 3.13 3.10

1984/85 53.20 39.40 13.80 3.73 13.84 0.493 3.24 3.30

1985/86 57.20 42.20 15.00 3.62 13.40 0.507 3.11 2.30

1986/87 61.50 45.30 16.20 4.08 14.23 0.532 3.55 12.70

1987/88 67.60 50.00 17.60 3.72 12.84 0.515 3.21 -8.20

1988/89 70.30 51.20 19.10 3.84 12.84 - - 3.20

1989/90 74.30 53.70 20.70 3.96 12.84 - - 3.10

1990/91 79.00 56.60 22.40 3.70 12.38 0.623 3.08 -6.60

1991/92 85.30 61.00 24.30 3.88 12.53 - - 4.90

1992/93 89.90 63.60 26.30 3.53 11.00 - - -10.00

1993/94 94.70 66.20 28.50 3.34 10.12 - - -4.20

1994/95 98.20 67.30 30.90 3.49 10.50 - - 3.30

Sources: Economic Survey, 1996-97; Labour Force Surveys; Censuses of Manufacturing Industries; Censuses of Small-scale and Household Establishments.

43 5. THE LARGE-SCALE SECTOR: MAIN FEATURES

Large-scale manufacturing in Pakistan is dominated by the so-called “Big Four” industries – sugar, textiles (cotton yarn and cloth), cement, and fertilizers while accounting for only 6.9 per cent of the units in the sector in 1991, consisted of 37.6 per cent of net output, 40.2 per cent of exports, 35.0 per cent of employment and 43.2 per cent of the capital stock employed in large-scale manufacturing.7 Unlike its contribution to output and exports, the large-scale sector’s contribution to employment has been moderate, even in periods of rapid growth. On the whole, manufacturing industries in Pakistan, have failed to create sufficient employment: employment levels were almost the same in 1994-95 as they were in1982-83. During 1980-95, when total employment grew by 2.3 per cent per year, employment in large-scale manufacturing increased at only 1.8 per cent per year.8 Over the same period (1980-95), large-scale industry absorbed only 1.4 percent of the additional employment in the economy.9 Slow job creation in large-scale manufacturing was accompanied by a substantial rise in capital intensity and labour productivity in the period 10, as assets employed per worker increased from Rs. 50,000 in 1980-81 to Rs. 192,000 in 1990-91. As a result, the labour content in output and the share of wages in value added dropped in most industries (table A4.3). It is therefore quite clear that labour productivity as well as capital intensity have risen on trend in the large-scale manufacturing sector in Pakistan (table A4.6).

It has also been suggested above that, despite the slowdown of overall growth, employment and output growth have not moved in opposite directions in the large-scale sector until very recently, whereas they showed signs of this in the small-scale sector as early as the mid-1980s. The share of large-scale manufacturing employment has been around 17 per cent of manufacturing employment in 1990-91, while its output share was around 70 per cent in the same year.

From an employment point of view the separation of large from small-scale as well as the distinctness of the high-growth 1980s and low-growth 1990s are important facts. The centrepiece of an employment strategy within manufacturing is the small-scale sector, which is larger in weight and has been facing problems since the mid-1980s, In contrast the primary focus of the revival of growth is relevant to the large-scale sector where the bulk of manufacturing output is produced and where employment is still growing, albeit slowly. It is this sector’s growth which is likely to have positive linkages with other sectors, including activities in the manufacturing as well as non-manufacturing small-scale sector. Since we are discussing the large-scale sector in the present section, this difference must be kept in mind.

7 Of the four, textiles account for the major share of output, employment and exports.

8 As a result, the sector has always accounted for less than 2.5 per cent of total employment (in 1990-91, 2.1 per cent), although its share has varied between 6-8 per cent of urban employment, and between 3-6 per cent of non-agricultural employment.

9 During the 1984-90 sub-period however employment in large-scale manufacturing grew by 3.9 per cent per year, with textiles and food processing accounting for 48.8 per cent and 15.5 per cent of the growth respectively.

10 The increase in labour productivity in the 1980s was spread unevenly across sectors. The largest gains were in petroleum refining, while textiles, paper and board, and drugs and pharmaceuticals also registered significant gains. Capital intensity measures can be seen in table A4.2.

44 6. AN EXAMINATION OF PRODUCTIVITY IN THE LARGE-SCALE MANUFACTURING SECTOR

Apart from describing some specific features of the manufacturing sector in Pakistan, the discussion above highlighted that the growth process in the large-scale manufacturing sector is characterized by a low employment elasticity and that if it is decomposed over time, labour productivity dominate employment expansion as the source of growth. We also saw that both labour productivity and capital intensity have increased in the large-scale manufacturing sector.

We now attempt to examine the determinants of labour productivity as well as employment over time in a more systematic way. There are two basic sources of increases in labour productivity. First, there can be an autonomous increase, arising from better management, skill upgrades (possibly via training), longer working hours and greater effective effort. Productivity gains that result from better management and skill upgrades are desirable. These are likely to show up over time.

Second, productivity can increase from increases in the use of machinery and non-labour inputs. This would largely be reflected as the effect of capital intensity.11

The question to ask at this stage is: given that labour productivity has shown an increase over time, what is the extent to which it has been driven by changes in the composition of capital (the capital-labour ratio) and to what extent is it due to autonomous increases in productivity? Since it is expected that in the course of development the composition of capital effect is dominant, we are interested in knowing whether autonomous increases in productivity have any potential in manufacturing in Pakistan.

A regression analysis conducted for the period 1980-97 (see table A4.4), which focuses on the determinants of labour productivity and employment in large-scale manufacturing, suggests that labour productivity in Pakistan has been influenced by changes in capital intensity (i.e., the capital-labour ratio) as well as increases in ‘autonomous’ productivity. The capital intensity effect on productivity clearly dominates in manufacturing.

Labour productivity and capital intensity have a significant positive relationship (for equations in which it used), and this is according to expectation. The level of value added in manufacturing also has a positive relationship with labour productivity (it is significant in two specifications out of three) which suggests that high value added production is associated with high labour productivity, which is also expected. The positive relation also holds true for the time variable (statistically significant in two equations), which can be seen as a proxy for skills development, learning or ‘autonomous’ increases in productivity.12 So there are some grounds to expect a potential for autonomous productivity increases in Pakistan.

Employment on the other hand is significantly and positively associated with value added (in two out of three equations). The capital-labour ratio, the measure of capital intensity, is significantly and negatively related to employment. The time variable simply shows a negative sign showing the growth rate trend. Three matters are deducible from this analysis which have strategic implications. First, that increasing capital intensity which increases labour productivity also has a negative effect on employment. Second, that higher value added production, though positively related to labour productivity and capital intensity, is likely also to have a direct beneficial impact on employment. This means that the promotion of high

11 Aggregate productivity can also increase if labour flows into sectors with higher levels of labour productivity, in other words through the expansion of high productivity sectors, although this is subject to demand constraints.

12 Actually, the time and value added seem to be correlated.

45 value added production has two possible effects on employment, through capital intensity it is likely to reduce employment, but through the overall positive association between increase valued added production and employment it is likely to increase employment.

Third, and most importantly, we know from the analysis that autonomous increases in productivity are not unknown in Pakistan. This is a significant finding and can provide a basis for an employment-friendly investment plan.

7. THE STRUCTURE OF LARGE-SCALE MANUFACTURING IN THE 1980S AND 1990S

We now try to differentiate the two periods of the 1980s and 1990s. We know that one was a low-growth period and the other a high-growth period. We also know that the overall trend is of increasing labour productivity and capital intensity in the sector. A decomposition of total factor productivity is useful in this context. 13 The increase in productivity in the large-scale manufacturing sector shows that the increase in total factor productivity from 1982-83 to 1996-97 has been slight, and has been declining, on trend, since 1992-93. Labour productivity, as we know, has shown an increase on trend, (except for the decline for 1996-97). Capital productivity shows an increase up to 1992-93 and then shows declines. Therefore, it is really both capital and labour productivity which increased in the 1980s boom. In contrast, while labour productivity continued to increase, capital productivity showed a decline in the lower growth 1990s. This is a crucial difference.14

Table 4.4: Productivity in large-scale manufacturing (1980-81=100)

Labour productivity Capital productivity Total factor productivity

1982-83 122.5 110.1 101.2

1987-88 166.9 136.3 102.5

1992-93 205.2 155.8 103.0

1994-95 208.9 148.9 102.7

1995-96 211.9 143.1 102.4

1996-97 201.7 135.6 102.4

Source: DRI/PIDE Study on Technology 1997.

The output and employment growth policy in manufacturing needed in Pakistan is intrinsically tied to the labour productivity-led growth process which the country began to witness in the 1980s. The causes for

13 Total Factor Productivity is decomposable into Labour and Capital Productivity. Decomposition is based on assumptions made on the production function.

14 Declining capital productivity also suggests that a substitution between labour and capital is likely to have begun in the 1990s. Sectoral decompositions of total factor productivity can be seen in table A4.5.

46 increases in labour productivity are critical to assess. We have done this across the two periods fairly systematically in the regression analysis above, which suggested that while the capital intensity effect dominated, autonomous productivity increases were not unknown. For a periodized decomposition of total factor productivities we found that the difference between the 1980s and 1990s was located in capital, not labour productivity. The 1980s saw an increase in the latter, the 1990s a decline. We now attempt an assessment for the 1980s and 1990s separately and at a sectorally more disaggregated level.

The high-growth 1980s

The 1980s were a high-growth period, particularly for the period 1982-82 to 1987-88, after which a decline set in. Indicators of capital intensity for parts covering the period also tend to confirm that capital intensity increased in this period. This process has continued between the high-growth 1980s and the low-growth 1990s (table A4.2), but for different reasons. It is reasonable to argue that if growth is positive, as it was in the 1980s, and capital intensity also increases, as was also the case in 1980s, then labour productivity (value added per unit of labour) is also likely to rise. This is the case for the evidence we have for the 1980s (table A4.6). So the increasing capital intensity argument behind the high labour productivity is further corroborated for the 1980s.

There are some other indicators which explain the 1980s story a little more. Data on investment for the 1980s suggest that it remained around a 3 per cent proportion of GDP from 1983-88 and increased to 4.7 per cent by 1992-93 (table A4.7). This is not only consistent with the capital intensity argument made above, but it also shows that it was the increase in value of capital stock as well as employment increases which characterized growth in the 1980s. Labour productivity driven growth in the 1980s, was due to increasing overall capital intensity and the number of persons employed, which was being sustained by a relatively stable investment pattern.

Alterations in the composition of investment began in the 1980s. There are falls (table A4.8) during 1982- 83 to 1988-89 in the shares of the chemicals sector and the cement sector, while there are increases in the textiles and food sectors. So it would appear from investment patterns that while the overall intensity of capital seemed to be increasing, a sectoral shift was also taking place in the 1980s to less-capital intensive sectors. We need to examine the capital intensities of sub-sectoral shifts to explain this.

During the period 1980-81 to 1990-91, in the large-scale sector, the share of food products declined from 24.3 per cent to 14.2 per cent (table A4.9). This is interesting because food was not a highly capital intensive sector, and although the share in value added of the food sector was declining, investment in it was increasing;15 the share of textiles increased from 24.3 per cent to 26 per cent and textiles on the whole are even less capital-intensive than food. It is also clear that both food and textiles are on the middle to lower end of the capital intensity scale in the large-scale sector taken as a whole. The chemical sectors share increased from 13.2 per cent in 1980-81 to 23.5 per cent in 1985-86 and then declined to 14.9 per cent in 1987-88 and further to 13 per cent by 1990-91. Industrial chemicals constitute the larger part of this sector and are very capital- intensive. Investment figures reported earlier which show a decline for the chemical sector after 1985-86 tend to suggests that there was over-capitalization in the sector in the early 1980s.16 These are the only significant changes in the period; the rest of the sectors are mostly not major

15 This is partly due to the fact that food figures include the sugar sector and while the rest of the food sector was in decline, there was investment in the sugar industry. Moreover food production was moving towards lower value added activities and thus losing its share in total value added.

16 The causes for over-capitalization in chemicals (as well as cement) may have something to do with lending criteria. It has been shown above that despite the slowdown in the manufacturing economy some investment is still taking place. Given that there is under-utilized capacity in an industry, it is pertinent to ask what causes investment based increases

47 and generally tend to fluctuate with respect to their value added shares in smaller margins. It appears that the net result of sectoral shifts has been an increase in capital intensity and this needs to be explained.

There are two factors at work here. Although the major sectoral changes (as well as investment patterns) suggest production may have been moving towards relatively less capital-intensive sectors in the 1980s, it is also the case that 16 out of 24 sub-sectors have individually experienced an increase in capital intensity even in the period 1987-88 to 1990-91 (table A4.2). Furthermore, while the food sector’s (the major loser) capital intensity, contrary to the trend actually declined in the period , the capital intensity of the textile sector (the main gainer) increased. Capital intensity of the chemicals sector also declined during the late 1980s.

It can be argued that taking into account overall increases in capital intensity across the manufacturing sector, and the specific changes in the capital intensity of the main losers and gainers, the sub-sectoral shifts in the 1980s are likely to have accompanied increasing capital intensity on the whole. Although, counterfactually speaking, had the shifts in the major sectors not taken place the capital intensity would have increased even more.17

Finally, data on capital-output ratios is also available. An increasing capital output ratio suggests that the value of capital stock in relation to the value of output is rising. Assuming stable prices, this is consistent with either an increase in capital stock or a decline in production. A decline in production, which would tend to raise the capital- output ratio, is consistent with a crisis of demand and excess capacity building in industry. Therefore rising capital-output ratios are consistent with building excess capacity. Falling capital-output ratios suggest the opposite. The latter was the case in Pakistan during the 1980s (table A4.3). To the extent, excess capacity that it existed was being used up in the 1980s. It was a relative increase in output despite the increases in capital stock which characterized the capital intensive–labour productivity driven growth of the Pakistan economy in the 1980s.18

We now return to the issue of the low elasticity of the manufacturing economy. It is arguable that the 1980s high-growth period’s low elasticity of employment and shifting source of growth (from being unequally shared between employment and labour productivity to being labour productivity driven) is consistent not only with an increasing capital intensity in general across the large-scale sector, but also a compositional shift to relatively less capital intensive sub-sectors within manufacturing.

By the end of the 1980s, a slowdown in growth began to take place. What were the characteristics of this slowdown and what were its causes?

The 1990s: A period of low growth

of capacity when it is under utilized to start with? Clearly this is what is also partly responsible for the observed increasing capital intensity in an industry. There are two sides to the issue in Pakistan. One is simply that new entrants in a free market structure can enter the industry (unless it is a monopoly) even if there is excess capacity in it. The matter clearly turns on the gains as well as profitability of the enterprise for the individual investor and pricing of capital. This is discussed later.

17 In a situation of positive growth, if capital flows into sectors which have higher levels of labour productivity(which produce more value added per employed person), then aggregate labour productivity would increase. These high productivity sectors could be correlated to higher capital intensity sectors. It is therefore not plausible to argue that sectoral flows were mainly causing a general increase in capital intensity in manufacturing in Pakistan.

18 Investment financing and the use of capital are related directly to capacity utilization. It can be argued that one of the reasons for the recent lower levels of productivity in Pakistan is the under-utilization of capacity. Increases in capacity utilization in the sector would therefore tend to increase productivity (and reduce domestic resource costs).

48 During the 1990s growth has moved from positive to negative. We cannot say much about employment levels because of data constraints. With increasing flexibility in labour markets, it is likely that employment may have declined, and contractual changes occurred.19

Even if growth is declining and turns negative (output increases less and less and then declines) a capital intensity rise (which reduces employment in relation to capital) will show up as an increase in labour productivity (the production of output or value added per unit of labour) but this will be for different reasons than in a high growth situation. Capital intensity can rise for two reasons: an increase in capital stock and a decline in employment. In a period of zero or negative growth, a rise in capital intensity is likely to be due to a decline in employment as opposed to an increase in capital stock.20 This means that if labour productivity increases it does so because the rate of fall of output (value added) is less than the rate of fall of employment. The issue really turns on how flexible the labour market is. If the number of employed decline, and output declines as well, an increase in labour productivity is as possible as a decline is. It depends on the respective rates of decline. It is not clear whether Pakistan is already in this situation, but it may be close to it.

Consequently, the same indicators of increasing capital intensity and increasing labour productivity can characterize two very different situations. It is fairly clear from the data that growth in the 1990s slowed down (table 4.2). Declining and low as it was it is equally clear that growth was even more dominantly based on labour productivity increases than employment expansion than in the 1980s. What was the sectoral basis of this rising labour productivity?

Investment declined in the sector from 4.7 per cent of GDP to 2.7 per cent from 1992-93 to by 1996-97. It is, however, still likely that capital intensity in the sector increased, from the foregoing discussion and the data at our disposal. The 1990s also indicate only slight changes in the composition of output (table A4.10). 21 By and large, shares of output show variations of a small margin for the main sectors. The 1990-91 pattern of industrial composition continues. The only sector which shows any serious increase is the textile sector. The relatively more capital-intensive sectors reveal a trend decline within a small margin.

It is, however, very clear that unlike the 1980s, there is an excess capacity build-up in some of the major sectors of the economy (table A4.11). We have information for 1990-91 when capacity utilization was around 60 per cent. Recent trends based on Planning Division estimates suggest a declining trend in selected sub-sectors. In the recent period from 1992-93 to 1995-96, capacity utilization has declined on trend in the spinning, sugar, and cement sectors. It has remained stagnant in weaving and increased only in fertilizers. This clearly suggests an overall decline.

It can be argued that the 1990s picture is characterized partly by a failure of demand in the large-scale manufacturing sector. The low level and declining growth of output and employment, declining investments and the build-up of excess capacity all point to this failure. The increase in capital intensity (like the increasing labour productivity in the 1990s) which characterizes the growth process, needs to be matched

19 Estimates of contract workers vary. They increased from 4.9 per cent (1980-81) to 6.3 per cent (1987-88) of the total industrial labour force (Shahid Associates, 1989). It is very likely that this process has continued through the 1990s.

20 Some investment is likely to occur, to replace existing capital in a low-growth situation and may itself raise the capital–labour ratio.

21 As previously mentioned, the Census of Manufacturing Industries (CMI) data are unfortunately unavailable for periods after 1990-91. Physical production data collected by the Federal Bureau of Statistics are used for estimating value added for the large-scale sector after 1990-91.

49 with declining capital productivity and is therefore more indicative of shrinking employment than an increasing capital stock and value of output.

What is responsible for the slowdown in growth? Apart from the general failure of demand argument, there are two broad answers to this question. One relates to macroeconomic policies and the other to the investment climate.

From the macroeconomic perspective, Pakistan has pursued deflationary policies since the beginning of the reforms in 1988. This is supposed to have short-run consequences for growth, which are not inconsistent with what can be discerned for the 1990s. Among other issues this also includes the withdrawal of the public sector in the economy under depressed demand conditions.22

Since the decline in investment is also for the more recent years, it may partly be due to the unstable conditions of production and investment (i.e., the law and order situation) in both Karachi and the Punjab, which have clearly deteriorated in the recent past.

8. TOWARDS A POLICY OUTLINE

The challenge for the manufacturing sector in Pakistan is considerable. A concerted effort is needed towards increasing the low elasticity of employment as well as output growth. This effort needs to focus on reviving demand and improving the social climate for investment, on increasing the utilization of existing capacity and promoting growth in sectors with a potential for autonomous productivity increases.

Criteria of sectoral choices in an employment-friendly investment plan

Some of the above findings can assist in the formulation of an employment-friendly investment plan for the future. It is therefore recommended that in the selection of activities to be promoted, the following factors must be borne in mind when developing the criteria for sectoral choice:

• sectors should have some potential for autonomous productivity growth; • sectors should have some employment-generating capacity; • sectors should be producing sufficient value added (such that the capital intensity/negative employment effect is offset by the expansion-high value added/positive employment effect); and • there should be a separate assessment of demand conditions in such sub-sectors and those which seem relatively unconstrained must be promoted.

The mechanism of sectoral promotion should be affected through two means. First, via the banking system, which should try to guide investment. Sub-sectors fulfilling composite measures based on the above criteria need to be identified and a system of incentives offered through the financial system to realize the desired flows into these sub-sectors.

Fiscal expansion and demand

22 The point is general, but one that is often missed. An adjustment and reform period is likely to depress demand and an overall slowdown in growth and investment is to be expected. This affects the investment climate. If the adjustment process is also accompanied by the withdrawal of public sector from the economy, it is more than likely that the private sector would not, due to the altered investment climate, immediately step into public-sector shoes. Even if the theory is right, this move is likely to take place after a substantial lag. In the case of Pakistan it is arguable that there has been a failure in the sequencing of reforms which may have affected growth.

50 Given that part of the problem may be in government pursual of deflationary policies under the reforms, which has led to a decline in demand for manufactured goods, it may be worth examining the worth of expansionary fiscal policies, to revive demand. To the extent that capacity is under-utilized (investment requirements become less) and the manufacturing sector is not primarily export-based, the case may have some merit.23

The budget deficit and working capital

A critical factor in freeing affordable resources for the manufacturing sector is the degree to which the government budgetary deficit falls and the government borrows a smaller amount of money from the banking sector. Capacity utilization and employment can increase without substantial increases in investment. There is a clear link between the budget reform government and the relief of working capital constraints in manufacturing. This is, however, not inconsistent with the selective fiscal expansion suggested above.24

Promotion of sub-sectors through tariff rationalizations

In order to revive growth in manufacturing, the profitability issue needs to be addressed directly. This entails a serious examination of the structure of tariff rationalizations and the matter is likely to be critical. The development of the manufacturing sector has become somewhat lop-sided over the years, as production has moved against high value added products. If corrected this may benefit the sector as a whole. Tariff rationalization can result in improvements in the relative profitability of the chemicals and engineering sectors (the sectors falling behind) and arrest the trend in the overall composition of investment and output in the large-scale sector. This is important to do for the general health of the large- scale manufacturing sector, even though it may be true that some parts of these non-traditional sectors may comprise relatively capital intensive activities.

Capital pricing and directing new investment

Another issue concerns investment itself and the price of capital. It is questionable if capital is priced in relation to its opportunity cost. If capital were priced at its opportunity cost with prudential regulations, then the true costs of investment would be transparent to investors and lenders. This is clearly not the case in Pakistan, and the crisis of bad loans that the financial sector is facing is testimony to this fact. Arguably the weakest link in the financial sector reforms which have taken place in Pakistan, it also highlights something that is fairly obvious but often ignored, namely that in many instances market-based reform must be complemented by institutional reform in order to be effective.

23 The idea is to decrease unproductive as opposed to productive expenditure of government.

24 In fact one of the failures of sequencing of economic reforms in Pakistan has been to go ahead with financial liberalization before a budget reform.

51 The co-ordination of capital flows

Unlike the earlier period, when credit plans were coordinated by government to put sectoral ceilings on bank lending, direct leverage for credit allocation is no longer used by government and credit is controlled indirectly through discount rates, open-market operations and liquidity requirements. It is, however, still possible for banks to collude with respect to sectoral lending priorities, as they have a significant interest in the setting up of new plants and improving the overall use of capital. Banks therefore clearly have a stake in the provision of capital which is invested and there is much that can be done in this area.

The revival of sick industries

There is another important issue which needs to be assessed concerning capacity utilization and the performance of the manufacturing sector in Pakistan . A large number of industrial units have closed down over the last few years and a considerable number are operating below capacity; as many as 2,533 industrial units are closed and another 1,252 units are running losses (Report of Committee on Sick Mills, 1996). The units have become ‘sick’ for several reasons which need to be distinguished. The checklist includes: over-capitalization of different industrial units; over-capacity in the unit’s industry as a whole; inappropriate site selection; inappropriate choice of technology, lack of working capital; and basic mismanagement. Units operating below capacity could also be facing a slackness in demand, energy constraints via load shedding, or the non-availability of complementary inputs. Solutions vary according to the dominant cause of the sickness of unit and these must be identified in a fair amount of detail for a serious attempt at devising revival strategies. In general, the question is whether anything can be done to increase the utilization of capacity in the present circumstances.

Tax policy and flow of goods

As indicated above, in recent years Pakistan has been pursuing deflationary policies in the context of economic reforms, with a direct influence on the decline in demand for manufactured goods. The increase in sales tax and regulatory duties on raw materials and intermediate inputs has at the same time made domestic manufacturing less competitive against smuggled goods. It is therefore important to assess the effect of government taxation efforts on competition, in the presence of leaky borders. There may be something which can be done here.

Energy pricing

Load shedding has been a constraint to industrial growth in the past in Pakistan. It is expected to be overcome because of increased capacity, although the whole matter of an inefficient energy distribution system still needs to be addressed. Whatever the determinants and cost parameters associated with the growth of the energy sector, it is fairly clear the issue of energy prices will be critical for the growth process. Higher energy prices may still constrain the utilization of capacity. Consequently, a critical factor in the increase in the utilization of capacity in manufacturing is the degree to which energy prices increase in the economy.

9. UPSHOT

We have attempted to explain the trends of employment and growth in the manufacturing sector in Pakistan over the 1980s and 1990s. There are some features of this review which need to be highlighted. A low employment elasticity is a structural feature of the manufacturing sector in Pakistan. We find that trends in growth rates suggest a decline. The 1980s were a high growth period while the 1990s are characterized by low growth. Growth in manufacturing since the 1980s has been driven by labour

52 productivity as opposed to employment expansion; the last period in which employment expansion took place was the (low growth) period of 1970s. It can be argued that output growth began de-linking itself from employment in the 1980s and became de-linked from employment expansion altogether in the 1990s. Part of the explanation of this feature lies in the distinction between the small and large-scale sectors in manufacturing in Pakistan. It is the small-scale manufacturing sector employment which declined in the mid 1980s, while its output grew. In the large-scale sector both employment and output growth have been positive in the 1980s and most of the 1990s. In other words, the de-linking of employment from output growth which was taking place in the manufacturing sector in the 1980s and which was established in the 1990s, may have been due to the overwhelming weight of declining employment in the small-scale manufacturing sector and not because of the large-scale sector as such.

A policy implication of the above is that employment growth needs to be promoted in the small-scale manufacturing sector, while output growth needs to be revived and the low elasticity of employment increased in the large-scale sector. Therefore the centrepiece of an ‘employment generation’ strategy within manufacturing should be the small-scale sector, which is larger in weight (around 83 per cent). In contrast, the primary focus of a ‘revival of growth’ strategy is the large-scale sector where the bulk of manufacturing output (around 70 per cent) is produced. It is this sector’s growth which is likely to have positive linkages with other sectors, including the activities in small-scale manufacturing as well as small- scale non-manufacturing.

Examining labour productivity, the engine of growth in the sector, it is fairly clear that labour productivity in Pakistan’s large-scale sector has been dominantly due to increasing capital intensity, but it is worth noting that autonomous increases in productivity are not unknown. The labour-productivity led growth is not alarming in itself since such increases are expected over time. The periods of high growth in the 1980s and low growth in the 1990s need to be differentiated on other grounds. While both periods are characterized by increasing capital intensity and labour productivity in large-scale manufacturing, investment trends in the 1980s are stable and positive while in the 1990s they are declining, just as excess capacity is declining in the 1980s and is increasing in the 1990s. The examination of total factor productivities sums up the situation well. These increased in the 1980s and declined in the 1990s. The difference was not in labour productivities which rose in both periods, but in capital productivities which increased in the 1980s and declined in the 1990s.

The challenge for the manufacturing sector in Pakistan is considerable. A concerted effort needs to be made towards increasing the low elasticity of employment as well as reviving growth. From our analysis it is clear that a crisis of demand may be in the process of setting in the large-scale manufacturing sector. The causes are complex and multiple but two issues can be singled out which may explain the slowdown of the 1990s. One concerns the investment climate in Pakistan which has not only deteriorated but spread from the 1980s to 1990s; the second relates to post-reform deflationary policies adopted by the government (and their sequencing) in the late 1980s and 1990s, (which were accompanied by privatization and public-sector retrenchments). These are likely to have dampened demand and the supply of working capital for the manufacturing sector.

A multifaceted policy initiative is required in order to revive growth in the large-scale manufacturing sector. This effort in the large-scale sector needs to focus on reviving demand and improving the social climate for investment, on increasing the utilization of existing capacity and promoting growth in sectors which also have a potential for autonomous productivity increases. Some policies consistent with these aims have been suggested.

53 CHAPTER FIVE The Small-Scale Enterprise Sector

1. INFORMATION AND DATA

There is a serious limitation of information on the Small-scale Enterprise Sector (SSE) in Pakistan and wide discrepancies exist between data available from different sources. Our earlier discussion suggests that this sector is of critical importance with respect to employment, especially its manufacturing component. Manufacturing employment growth as a whole has linkages with employment in other sectors of the economy. The structure of employment in manufacturing is such that the bulk of the manufacturing sector’s employed persons are located in the SSE sector. Thus, it is the SSE manufacturing sector which has employment absorption potential. In this chapter, we look at the SSE sector as a whole but with particular emphasis on SSE manufacturing.

As the data on the sector in Pakistan is often incomplete, irregular, and varying in definitions, the task of producing an ‘overview’ is difficult. In making this attempt, we rely on National Income Accounts, the Labour Force Surveys, each of the major surveys done for the SSE sector in Pakistan, as well as some important micro studies done with the SSE as a focus.

2. DEFINITIONS

Small-scale Enterprises are defined in this section as firms using less than 10 workers. However, different definitions are used in Pakistan for varying purposes. The definition intended for statistical use and data generation has undergone a change from being asset value (Rs. 2 million or less in 1976-77) based to being labour (less than 10 workers) based.

Definitions which are not for classification purposes but entail ‘policy support’ to the SSEs in the form of loans and tax relief, differ widely according to the assessing authority and are almost always capital based. For example, the State Bank of Pakistan, the central government as well as provincial governments, each involved in lending decisions related to the sector, have different cut-off capital values which ‘constitute’ for them, the SSE sector.

3. ESTIMATES OF OUTPUT AND EMPLOYMENT IN SSE MANUFACTURING

Partial estimates of the output and employment of the sector based on National Income Accounts (NIA) and Labour Force Surveys (LFS) are reported in the Economic Surveys (ES). They suggest that the SSE’s output share in manufacturing is around 30per cent while its employment share is nearly 83 per cent (tables A5.1 and A5.2). These figures have already been encountered in our general discussion on manufacturing. Data reported in the Economic Survey (ES), however, calculate the size of the small-scale sector as a residual. In short, according to this data we have a very high share of employment within manufacturing which goes to the SSE. Another characteristic of the SSE sector is its allegedly high growth rate of output. The combination of its high employment absorption capacities and as its high growth rate makes this sector an appropriate focus from an employment perspective.

54 Levels of employment and growth rates, as reported in the Economic Survey, are shown in tables A5.3 and A5.4. Our alternative sources of information are mentioned.1 On the basis of a thorough review of much the information available on the SSE sector in Pakistan (Appendix 1) in the major surveys, we present our synthesis of employment output and growth in the sector below:

4. The decline in SSE manufacturing employment in the mid-1980s discernible from the Economic Surveys is plausible and the pattern is likely to continue. Since comparing alternative surveys over time is not feasible, the trend is likely to have continued, especially since we do know that overall GDP growth declined and has not since picked up in the 1990s. Employment growth in SSE manufacturing is likely to have therefore declined on trend, if it has not been negative during the post-1991 period.

5. The level of employment in SSE manufacturing is likely to be lower than the three million ball park figure (in 1988) based on LFSs. How much lower is a matter of guess work, it may be as low as even half that figure, but its level does not alter our view on the trend of employment growth.

6. The growth of output of SSE manufacturing, estimated for the sector in NIA is likely to be very seriously lower than what is reported in the Economic Surveys. Instead of averaging around the 8 per cent mark, it was probably closer to 4.3 per cent in the 1976-77 to 1983-84 period and 4.7 per cent for the 1983-84 to the 1988 period; and a much lower 2.6 per cent from 1983-84 to 1992- 93. Therefore the 1980s figure is closer to 4-5 per cent and the 1990s figure is much lower.

7. The SSE manufacturing value added or employment shares are unlikely to exceed a quarter of total value added and employment in the sector. Within sub-sectors in manufacturing it is textiles, food, wood products and fabricated metals which dominate both value added and employment. Textiles in turn are dominated by weaving and the carpet industry, which also have dynamic export linkages.

Apart from our findings on the size and growth of the sector synthesized above, mean incomes are also found to be lower in SSE manufacturing than in the large-scale sector. As its growth is unlikely to be as high as is assumed in the data reported in the ES, we need to emphasize both the revival of growth and employment generation in any strategy for the sector.

We have based our synthesis on a careful assessment of the numbers available from different sources. There are some implications:

1 The major surveys are: The Small Household and Manufacturing Industries (SHMI) 1983-84, 1988; The Census of Establishments 1987-88, The Household Integrated Economic Survey (HIES) 1987-88, 1990-91; The Integrated Survey of Service and Manufacturing Industries-Small, (ISSMI-Small), 1992. There are three micro studies based on sample surveys which are comprehensive in their coverage of many important structural characteristics of the SSE and are of interest to us. These will be referred to by name in the text. The largest survey of 1417 firms is also the most recent, conducted in 1992, by Kemal and Mehmood [Kemal A.R. and Mahmood Z., 1993]. The second largest survey of 806 firms was conducted in the mid- 80s by Cohen and Havinga, [Cohen S.I. and Havinga I., 1988]. The third largest of these surveys is of 328 firms conducted in 1989 by Nadvi, [Nadvi K., 1990]. Two other surveys have larger samples, but their results are more limited in terms of our characteristics. One is a survey by Burki in collaboration with the Freidrich Ebert Stiftung (FES), of 2,030 apprentices and their masters (Ustaads and their Shagirds), [Burki A.A., 1989]. The other is a survey of 600 rural firms conducted in the late 1980s by Aftab, [Aftab K., 1990]. In addition there are two assessments of the role of the Panjab Small Industries Corporation and its established industrial estates by the Panjab Economic Research Institute (PERI) [PERI, 1985, 1988]. Finally there are a large number of purposely partial sector coverage studies on women and children in the SSE sector; two policy studies by Frerks, Thomas, and Thomson, [Frerks G.E., Thomas H. and Thomson L.B.M., 1989], and the World Bank, [World Bank, 1991].

55 First, there are sufficient grounds for re-examining the growth rates assumed for the SSE manufacturing sector in the National Income Accounts. A much more detailed investigation is necessary, but the background research done for this report has taken a first step in this direction.2

Second, these qualifications do not alter the thrust of our employment strategy for the manufacturing sector as a whole, or the SSE component of it. Employment is still much higher in SSE manufacturing than large- scale manufacturing. The trend of an arrested or declining employment growth evidenced in the mid-1980s is still likely to be valid.

Third, the focus of a strategy for the SSE manufacturing sector is employment expansion through growth, as this is where many of the employment linkage effects discernible for `manufacturing’ at the aggregate level may be forged into the rest of the economy.

4. CHARACTERISTICS OF THE SSE SECTOR

The size of the rest of the SSE sector compared with its manufacturing component is likely to be much larger both in terms of value added and employment. It could employ anywhere from four to six and a half million persons. In our view, the figure is a closer to the former than the latter. In Annex 5.1, we examine the basic sectoral profile of the SSE sector which can be gauged from the large-scale surveys done in Pakistan during the 1980s and 1990s. It is worth noting that trade and services are the largest sub-sectors in SSE manufacturing, which may employ up to 70 per cent of the persons working in the sector.

There are a large number of micro sample surveys of the SSE in Pakistan. We focus on four of the important micro analyses. These are: Kemal and Mehmood (Kemal A.R. and Mahmood Z., 1993; Cohen and Havinga, (Cohen S.I. and Havinga I., 1988); Nadvi, (Nadvi K., 1990), and Aftab (Aftab K., 1990) from now on referred to by the authors’ names. Our objective is both to get some answers to questions of policy relevance and to qualify the estimates of what we already know about the broad attributes of the sector from the data in major surveys. We focus on two important areas: the demand and output of the SSE firm; and its productivity and returns. The larger survey: ISSMI-Small, 1992-93, is mainly used as the benchmark.

The SSE firm: Subcontracting and demand

ISSMI-Small for 1992-93 shows that the SSE sector was not ‘fully integrated’ into the large-scale sector, with no firms solely reliant on sub-contracting. SSE sector firms also seemed to be transient, the vintage of over one-third of the firms being the 1990s.

We can try and qualify this with reference to other studies. For the four sub-sectors it examines, Kemal and Mehmood’s study finds that sub-contracting is predominant (63 per cent of firms) in manufacturing only. Cohen and Havinga differentiate between substantially self-sufficient firms (SS) and firms linked to the modern sector (ML). They find (almost by definition), the ML firms rely more on hired labour with outward sources of inputs and outward sources of demand such as wholesalers, middlemen and government. Aftab’s survey, distinguishing between household and small-scale firms, finds sub-contracting to be very low in rural areas. Nadvi distinguishing between household firms (HH) and larger firms which he calls small-scale (SC) finds a high incidence of household firms tied into sub-contracting. This appears like a ‘putting out’ system where suppliers are the main entrepreneurs and households the main labourers.

2 ILO-SAAT, Mahmood, M., 1997 (mimeo).

56 This sub-contracting is unlikely to be a phenomenon exclusive to a large number of SSE firms, although in manufacturing it is likely to exist non-exclusively in a significant degree for many SSEs. It is also likely to rely on household enterprises and have a higher urban incidence.

This clarifies a point made for the manufacturing sector in the overall employment strategy, where we viewed the growth of manufacturing sector employment as critical for employment growth elsewhere in the economy because of linkage effects. It is now clear that there is a growth-based linkage between the large- scale manufacturing sector and the small-scale manufacturing sector through sub-contracting. Since the bulk of manufacturing employment is in the SSE manufacturing sector, it is arguable that a decline in growth of the large-scale sector and loss of incomes (as in the 1990s) could adversely affect the demand side for goods produced in the SSE manufacturing sector. Consequently the growth of the large-scale sector would tend to revive these sub-contracting links and increase effective demand for the SSE manufacturing sector. It is through this revival that employment linkages with other sub-sectors (particularly with trade and services) could be realized.

Labour use in the SSEs

The ISSMI-Small data shows (table A5.13), that 94 per cent of SSE firms were individual proprietorships. About 41 per cent of firms hired one employee, another 35 per cent employed two persons and another 20 to 30 per cent employed between three and four persons.

Kemal and Mehmood find firms rely for about 50 per cent of labour force on family labour, with 37 per cent self-employment and 13 per cent family help. The other 50 per cent of the labour force is hired, consisting of 38 per cent employees and 12 per cent apprentices. They also find a higher working week for all types of SSE labour compared with the large-scale sector. Cohen and Havinga find their self-sufficient ‘SS’ firms relying more on family labour while Nadvi finds what he terms household ‘HH’ firms relying more on family labour.

Kemal and Mehmood find a high incidence of skilled labour in this sector, which is also confirmed for ML firms by Cohen and Havinga. There is a clear tendency for the SSE to rely significantly on family and household labour, which is used quite intensively.

Capital stock ratios

ISSMI–Small shows a low capital base for the SSE sector. However, two types of firms can be distinguished, particularly in the manufacturing sector (tables A5.14 and A5.15). Firms with 5 persons or less had a capital-labour ratio which is around Rs 20,000. Those with more employment (excluding one size category) had a capital-labour ratio which jumps a scalar of 1.5 to 2. These ‘capital-starved’ firms of less than five persons comprised 83 per cent of manufacturing units. In general, just under a quarter of firms have assets between Rs 1,000 and 10,000, while 84 per cent of firms have assets of a value less than 100,000.

Kemal and Mehmood find a lower capital-output ratio for the sector compared with the large-scale sector, consistent with its low capital intensity. On labour productivity, Cohen and Havinga find that their ML firms have a higher labour productivity compared with their SS firms. Capacity utilization, however, varies in their ML firms and suggests unstable demand, which shows up as low capital-productivity.

The capital intensities in all the micro surveys vary according to expectation. Nadvi’s SC firms and Cohen and Havinga’s ML firms have higher capital-labour ratios than their household or self-sufficient

57 counterparts. The Kemal and Mahmood comparison of the SSE to large-scale sector shows the capital- labour ratio in the SSE to be nearly half that of the large-scale sector.

Capital intensity is low in the SSE sector is low, although firms can be differentiated on two grounds: those which have external linkages are also more capital intensive; those which are capital starved, employ less than five persons and are in a majority in manufacturing. This also implies that it is precisely the capital- starved firm employing a lower number of persons per unit that is likely to be part of a refuge sector within the SSE sector.

Credit

The low capital base in the SSE sector can be explained by low access to the formal credit market. The SHMI 1988 data on credit is available for the manufacturing sector (table A5.16). From a total investment of Rs 1.7 billion in 1988 over 91 per cent came from private savings, 9 per cent from the informal credit market and 1 per cent from the formal credit market. This is consistent with the World Bank findings which estimate around 2 per cent of the loans flowing to the SSE from the formal sector (World Bank, 1991).

HIES 1990-91 (table A5.11) also has data on loan access and its impact on the SSE sector. Of the 4.4 million units of the SSE, 26 per cent had taken loans from both formal and informal sources. The proportion was highest for manufacturing (35 per cent) and lowest for hotels (19 per cent). Formal market commercial loans were however limited to only 1.5 per cent of the total units, the highest being in trade (2.4 per cent). Some impact of these formal and informal loans on income or employment of these units can be seen. The average monthly income of an SSE without any loan is Rs. 2086; of an SSE with only an informal sector loan is Rs. 1796; and of an SSE with a formal sector loan is Rs. 2627. Similarly, in firms with zero-borrowing average employment is 1.53 persons; firms with only informal loans have a similar employment level of 1.51; but SSEs with formal sector loans employ 2.06 persons on an average. Formal sector credit can have a significant impact on the employment and income of SSEs.

The informal credit market is the main external source of funds for the SSE sector. A report by the World Bank (World Bank, 1991) identifies different forms of urban informal credit mechanisms operating in the sector, although these are likely to be relevant in both urban and rural contexts.3 The access to a formal credit market is therefore weak, especially for household-based firms, although it is clear that the links with it are beneficial for the SSE sector.

Incomes

The returns to self-employment in the SSE sector, which are returns to both capital and labour, are four times greater than the hired wage rate in the SSE sector.4 The hired labour wage is also significantly lower than the large-scale sector wage in Kemal and Mehmood’s study. Cohen and Havinga find that their ML firms compared with their SS firms have 66 per cent higher income. They also find income inequalities between owners and labour to be higher for ML firms than SS firms.

3 These mechanisms of informal credit include: high interest rate supplier’s credit which varies with the repayment period (up to 15 per cent per month ); buyer’s advance with high implicit interest rates (up to 16 per cent per month); the ‘parchi’ system based on discounted cash sales and IOUs; and what is known as the ‘Committee system’, which is based on a central fund with lots drawn for lump-sum withdrawals by members of the group who, on winning, exclude themselves from subsequent draws. Remittances, funds taken from relatives, and ‘own savings’ are also sources of capital. Moneylenders are the most unpopular form of borrowing for the SSEs in Pakistan.

4 The general results of the self-employed being `poor’ encountered earlier in Chapter One is therefore largely due to the agricultural sector.

58 It is appears that returns to both capital and labour for owners and labour are generally low in the SSE sector compared with the large-scale sector. There is demand based differentiation within the SSE sector between modern sector linked (ML) and self-contained/self-sufficient(SS) firms. External linkage in the ML firms is likely to improve their incomes.

5. OVERVIEW

These indicators show the SSE sector as partly a refuge sector, inflated by low productivity employment absorption in agriculture on the one hand and a small registered formal sector on the other. They also show it to be partly integrated into the mainstream economy where its market demand is based on growing export niches in textiles, in metal fabrication, and a growing domestic demand for consumption and capital goods. In particular the analysis of the sector finds:

• The output growth rate of the SSE manufacturing sector is not as high as the official 8 per cent per annum, and may be between a half to a quarter of this for the last decade. The size of the entire SSE sector is large, with employment estimated to be around 4.4 million persons.

• The largest sub-sectors are trade and services which account for 60 per cent of the employment in the SSE sector. Manufacturing accounts for around 26 per cent of the employment, (and, within manufacturing, textiles account for 12 per cent of total employment), followed by catering with 11 per cent and fabricated metals and food processing (3 per cent each).

• Within the manufacturing sector as a whole (i.e., large-scale and SSE), the SSE employs the bulk of the labour force. The share of the SSE sector in manufacturing value added is around 33 per cent. However its share of capital assets is a much lower. This gives the SSE sector a capital- labour ratio which is lower than the large-scale sectors. The estimates of the difference are wide, ranging from a factor of 2 to 17. As a result of its low (and depreciating) capital and technology base, the SSE sector has a capital-output ratio which is considerably lower than the large-scale sector’s (probably by a factor of 10).

• The SSE manufacturing sector does however display a rich dualism within itself. Some of its enterprises appear more integrated into the mainstream economy, act entrepreneurially, are based on hired labour, have better access to the formal credit market, have higher capital assets, a higher productivity, and better returns. Other enterprises are more involuted, appear to be recipients of a ‘putting-out’ system, are based more on family labour, are more reliant on the informal credit market, have lower capital assets, lower productivity, and lower returns.

6. THE SUPPLY AND DEMAND FOR SSE GOODS AND SERVICES

We now examine some supply and demand side issues that have policy implications for the SSE sector. Our objective is to explore some potential sources of promoting the employment and output growth of the sector.

Changes in purchasing power of social groups and demand

It is worth investigating this issue of demand. We know from the foregoing that if our dualism hypothesis is correct, then the dynamic part of the SSE is more linked into the structures of demand in the economy than its involuted part. Demand for the sector can be articulated through cross-sectoral linkages (sub-

59 contracting) as well as through changes in the purchasing power of consumer groups. Further this demand for the sector’s output can be directly policy-induced, as well as a result of wider changes in the economy. The latter are often expressed through changes in the purchasing power of social groups.

Remittances

An increase in the purchasing power of a significant group in the economy can lead to an increase in demand of the SSE and large-scale sectors. Remittances have clearly had an impact on the purchasing power of families of the migrants. Pakistan has had a history of migration during the 1970s and 1980s to the Gulf states. Many of the migrants have originated from rural areas of the country. The migration-based remittances from the Gulf arguably had a demand-boosting effect on the SSE (Hamid, 1983). However now that migration is not a major phenomenon in Pakistan, it is unlikely that the demand effect on SSE goods would further increase from this source. Historically speaking, it is likely that (and especially to the extent that this migration was rural) there was an initial boost to SSE consumption goods demand from remittances but with increases and stabilization in the wealth of recipients this should have been slowly shared with demand for goods from the large-scale sector.

The green revolution and differentiation of the peasantry

A possible new source of purchasing power is the differentiation of a largely self-subsisting peasantry producing their own consumption goods, into landless wage labour demanding both capital goods as well as consumption goods to supplement their incomes. There has been increasing landlessness in the agricultural sector in the past two decades (Mahmood, 1993). The increased demand from these lower income groups will tend to be largely from the SSE sector. The assumption here is of course that landless labourers’ share of consumption goods (and capital goods) from SSE production is greater than the respective share of landlords and large owner operators.

An effect of remittance and landlessness should be evidenced in the growth of consumption goods in the SSE, (especially in the food, textiles, and wood sub-sectors) over the 1970s and 1980s.5 Since both out- migration and the remittance effects are now likely to be small, the landlessness effect should be what is of relevance. It is important to note that although it has the same effect on the SSE sector, the landlessness effect is not unambiguously a result of increasing prosperity, as is the case with the remittance effect.

The income and technical change effect of the green revolution

Another source of increasing purchasing power in Pakistan has been the profitability-enhancing, input- intensive green revolution in agriculture. The High Yielding Variety (HYV) inputs and accompanying mechanization increased demand for capital goods from higher income groups such as large farmers and landlords. The resultant profitability should have increased the demand for consumption goods from both the SSE and the large-scale sector. It would seem that these income groups, after some time in which capital and wealth are accumulated, tend to switch expenditure to the products from the large-scale sector.

Depreciation of exchange rates

A drop in the real exchange rate can increase the demand for SSE goods. The exchange rate depreciation has been in effect in Pakistan for the past two decades. The idea is that more expensive imports of capital

5 These effects should result in a relatively greater growth of the capital goods sector in the later 1980s to account for a lag in the accelerator of demand for consumption feeding the demand for capital goods.

60 and consumer goods, mainly in the large-scale sector can increase the demand for the domestic products of the SSE sector.6

7. SOME INFERENCES

If survey data SHMI for three points in time is assessed (See table A5.9), we can infer the following:

– The food sector's share in value added, assets, employment, and the number of units has increased between 1976/77 and 1988, as expected. The data show that the textile and leather sectors have not increased their share over this period.7 The share of the weaving sector increases in terms of value added, assets, employment, and the number of units. This supports our hypothesis about consumption goods produced by the SSE sector and is consistent with the landlessness and remittance effects improving the purchasing power of the poorer sections of society with respect to the SSE.

– It is also clear that while the fabricated metal sector decreases its share over time, the share of agricultural machinery increases marginally, while the textile machinery sector is born.8 All the variables (unit numbers, asset values, employment and value added) for these sub-sectors increase. This supports the posited income and technical change effects of the green revolution.

– The CE 1987/88 data (table A5.17) gives the vintage of firms for three periods: pre-1970, 1970 to 1979, and 1980 to 1988. It shows that at least 70 per cent of the SSE firms in manufacturing have a post-1980 vintage. This may reflect the short life of SSEs or a recent growth spurt. However, at least in relative terms, the food, textiles, and wood sub-sectors have the highest proportion of vintages for the 1970s. The metals, fabricated metals, and chemicals sub-sectors have the highest proportion of vintages for the 1980s, which is also consistent with our hypotheses.

The above discussion suggests that many factors may work simultaneously to affect the demand of SSE sector and that these may not always work in the same direction. For example, the remittance effect is likely to favour the SSE more in the initial period. The differentiation of the peasantry (through landlessness) associated with the green revolution, would largely affect the SSE sector positively. Both these effects are likely to feed into the capital goods sector with a lag. On the other hand, the income and technical change effects of green revolution may be biased in favour of the large-scale sector.

8. POLICY AREAS

6 The impact of devaluation can be ambiguous, as seen in the analytical model by Mahmood (Mahmood, ILO-SAAT, 1997). As imports drop, both the large-scale and the SSE sector can gain, depending upon the demand factors and how the landlessness and remittance effects are balanced by the technical change effect. That is, the share of the SSE sector relative to the share of the large-scale sector in the production of consumption goods can increase, decrease, or remain constant. Similarly, the share of the SSE sector relative to the large-scale sector in the production of capital goods can increase, decrease, or remain constant.

7 This is probably due to the exogenously given demand for carpets whose share drops over time.

8 The technical change effect does not feed through to the SSE sector fabricated metals in general, although it must be contributing to the increase in share of agricultural and textile machines.

61 Government policy, as a whole, towards the SSE sector is likely to fall into two categories, committed and omitted. Committed policy is GOP attempts to help the SSE sector. Omitted policy is default policy, the actual impact of all its macro policy for non-SSE and SSE sectors, on the SSE sector.

There are three areas in which policy of the government can be strengthened.

Credit policy

The SSE sector gets an estimated 2 per cent to 4 per cent of its credit from the formal sector, despite all the institutional schemes - this is committed policy. However, more recent data sources like ISSMI-Small show that formal market credit for the SSE sector may be higher, or may have increased by 1992/93 to about 19 per cent of the units. Omitted policy is the high volume of concessionary credit mainly flowing to the large-scale sector, which results in a disincentive to invest in the SSE sector. The net result of both committed and omitted policy is the low levels of investment and depreciating capital base seen for the SSE sector in manufacturing.

The provincial government credit programmes are based on subsidized mark-ups below the market rate, and along with the GOP programmes have low recovery ratios. Subsidized credit is not viable in the long run: it contributes to low recovery ratios and is not as important a condition for growth as access to credit. The low recovery ratios reflect bad programme management, remote relationships with the clientele, the latter's shortfalls in working capital and weak investment planning.

Tax policy

The SSE sector gets fiscal incentives through tax holidays for rural and under-developed areas, and reduction in import duties and excise taxes on industrial estates. Being less import-intensive than the large- scale sector, customs rebates do not affect the SSE significantly. The impact of tax holidays, and reduced excise taxes on industrial estates also has the impact of industrial relocation rather than generating new net investment. This is the impact of committed policy. Omitted policy is that the SSE sector has to comply with 57 tax and regulation ordinances. Withholding taxes on 19 income sources and a turnover tax have been added to these since 1992/93. This raises the cost of `formalization’ of the SSE sector and acts as a disincentive. Increases in indirect taxes passed on to the consumer reduce the demand for SSE products. A reduction in import duties through liberalization increase cheaper competitive imports for the products of the SSE sector.

Infrastructure policy

Of the infrastructural support programme, the industrial estates programme is relatively ineffective, and the skilling centres programme is nascent and small in comparison to its target groups.

9. A STRATEGIC POLICY COROLLARY AND SOME SPECIFIC MEASURES

If the SSE sector is partly a refuge sector, then survival compulsions will force some SSEs to subsist in conditions of high financial and fiscal distortions. However, within the sequencing of decision making in the production process, the cost of the input (distorted or otherwise) will often be a secondary issue, preceded by the first choice of what and how to produce. This first choice is based upon technology and skilling. Moreover, technology skilling and an increase in the knowledge base can reduce the high financial and fiscal costs caused by policy distortions.

62 Given the dichotomous nature of the SSE sector with capital, productivity, profitability and employment (definitionally) rising discretely for enterprises employing above five workers, the provision of skilling and credit needs to be oriented towards the different nature of these two types of enterprise. Enterprises employing below five workers can be characterized as refuge labour and the principal constraint on their expansion, given their SSE-internal demand, is that they are credit- starved.

Enterprises employing above five workers can be characterized as refuge capital and the principal constraint on their expansions given their non SSE/external demand is that they are skill-starved to increase their demand. In fact, the appropriate characteristic for each of these two types of SSE enterprises is that they are differentiated by their principal constraint. Enterprises, employing below five workers have a primary supply constraint-credit. Enterprises employing above five workers share a primary demand constraint - they need to increase demand, which can only be done by increasing their skill and product levels.9

This analysis implies that policy should direct relatively more credit towards the enterprises employing below five workers and relatively more skilling towards the enterprises employing above five workers. Conversely, in the first stage, the refuge labour sub-sector will not be able to absorb skilling and the refuge capital sector will not have a primary credit constraint relative to their demand and production levels. What good future policy must be predicated upon is a thorough study of the poor/informal/SSE sector which identifies its heterogeneity more precisely in terms of the sector’s own perceived needs and constraints. What is needed is a participatory appraisal (PRA) methodology applied to a conventional empirical survey and analysis of the SSE sector.

Some specific policy measures which are likely to enhance employment and growth in the SSE sector are:

• Elimination of subsidies in credit programmes and increasing credit lines through SSE targeted institutions.

• A major source of effective domestic demand, as seen in East Asia, is agrarian reform. Extending ownership rights or making tenancy rights effective will boost the demand for SSE products. • If expansion of social infrastructure, education, health, water supply, sanitation, and shelter are decentralized down to the sub-district level, their domestic and SSE component will increase. Further, if community programs are associated with this expansion of social infrastructure, then decentralization reaches the village level and the domestic and SSE component will increase even more.

• The probability of export market niching increases with the skill base. This skill base should be expanded through dedicated institutions.

10. UPSHOT

The main point to note from the above review is that growth rates for SSE manufacturing may not be as high as the 8 per cent estimated by the National Income Accounts, since survey-based estimates suggest about half this growth rate. This does not mean that the emphasis on the SSE sector for employment is misplaced. However, nor is it as great a panacea for resolving the employment problem as its growth estimates suggest, and we may need to direct policy as much on growth as on employment generation.

9 Institutional support programmes, even internationally like the Grameen Bank’s credit programme in Bangladesh, tend not to discriminate sufficiently between the heterogenous segments of their poor/informal/small-scale clientele.

63 Consequently, there is little ground from a policy perspective to be complacent about SSE growth rates. Manufacturing is around a quarter of the SSE sector in terms of employment and is much the majority in employment for the manufacturing sector taken as a whole.

This review of existing major surveys, apart from bringing in a perspective on the growth rate problem, also allows us to disaggregate the macro estimates derived for the SSE sector. The macro estimate we settle on, shows the SSE sector employing approximately four and a half million workers. Characteristics indicate the SSE to be in substantial part a refuge sector based on a spillover of surplus labour unabsorbable in other sectors. The review also shows that trade and services account for the bulk of the SSE sector. The SSE sector is also likely to be underinvested.

Examining small micro analyses, this ‘aggregate’ view of the SSE sector can be disaggregated. There are some important findings. The first is that the SSE may not be one large refuge sector, but instead is characterized by a classic dualism. The micro surveys suggest that one part of the SSE sector may comprise firms more integrated into the mainstream economy, while the other part comprises of firms that are more involuted. The more integrated firms are characterized by stronger demand and input linkages, entrepreneurial decision making, better access to the formal credit market, more use of hired labour, higher capital intensity, higher capital and labour productivity, and higher returns. The SSE displays a rich dualism in structural characteristics.

A critical and operational result of this dualism is to have a ‘different’ policy focus on SSEs with less or more than five persons employed. This has implications for specific policies. Targeting and improving formal credit access and skills, simplifying tax and regulation ordinances affecting the SSE sector are crucial supply-side measures in general, but the focus of targeting credit must be on the capital-starved, self-contained smaller-sized firms while the concentration of training must be on skill starved, external demand linked, larger sized ones. On the demand, side the aim should be to promote export market niches with a skills base, to have a decentralized expansion of social infrastructure and conduct agrarian reform which at least makes tenancy rights more effective. These would be useful measures for the promotion of the SSE sector in Pakistan.

On a broader policy note, it should be recalled that the argument made in this report is that the growth of manufacturing-sector employment is critical for employment growth elsewhere in the economy because of cross-sectoral linkage effects. These are connected to the two types of demand linkages for the SSE manufacturing sector identified in this chapter. One sort of SSE demand linkage which has been identified is an internal one for the manufacturing sector, i.e. the sub-contracting one, which links modern-sector manufacturing firms to SSE manufacturing. The second type of link is that which is based on direct consumer demand, which pertains to changes occurring in the purchasing power of social groups. These are likely to have cross- sectoral implications for other sectors. Promoting both these links is important.

Since the bulk of manufacturing employment is in the SSE manufacturing sector, it is arguable that a decline in growth of the large-scale sector and loss of incomes (as witnessed in the 1990s) could have adversely affected the demand side for goods produced in the SSE manufacturing sector (the sub- contracting effect). Consequently, the growth of the large-scale sector could revive these subcontracting links and increase effective demand for goods in the SSE manufacturing sector. It is through such a revival as well as the promotion of direct consumer demand through the suggested policy measures, that employment linkages with other sub-sectors (particularly with trade and services) could be realized.

64 CHAPTER SIX Outline of an Employment Strategy

1. ELEMENTS OF AN EMPLOYMENT STRATEGY

This chapter marshals the main features of the employment strategy proposed in this report. As a preliminary, it must be stated that an effective employment strategy requires as its basis reliable information. There is a need to develop a consistent data series on the labour force and other indicators of employment conditions in Pakistan based on existing information. In this respect, the urgency of publishing the full the Population Census is of prime importance.

The employment strategy, as we have outlined it, has two areas of focus. The first concerns general goals pertaining to the labour force and employment. The second concerns sectoral strategies which provide the means of achieving these goals.

On labour force and employment

For the labour force, we have found that its size with respect to the population of working age is small. This is clearly reflected in low participation rates. The rate of growth of the labour force has also been falling over recent years and, though it has been lower than that of population , it is likely that this labour force growth will pick up in the near future due to the re-absorption of the young who have opted out of it due to education, as well as the increasing participation of women in the economy. The problems observed today with respect to those sections of the labour force `not fully employed will be magnified in the years to come. In other words, the widening gap between the labour force and the fully employed labour force observable over the medium-run past suggests that, small as it is, the unemployment problem is likely to persist and underemployment that has of late been increasing on trend, will continue to do so. The 16 per cent of the present labour force (the unemployed and underemployed) who are 'not fully employed' are therefore likely to increase even if the present trend of a declining labour force growth were to continue. If we expect an increase in the growth rate of the labour force for the reasons cited above, then the situation is likely to become worse. This is the core problem of an employment strategy.

There is a need not only to eliminate the persisting gap between the labour force and the fully employed but to significantly increase the growth of aggregate employment in the economy as well.

There are two general implications of the above goal that this report emphasizes:

• Preparing the labour force for the future: Since one of the reasons for the decline in the labour force growth has been the withdrawals of an increasingly younger population due to educational enrolment, the literacy levels in the labour force though presently low and increasing, will further increase. The withdrawal of a younger labour force because of education today, will be mean a swelling in the ranks of the educated labour force tomorrow. This will pose a serious employment concern in the years to come. The prospect has implications for planning an educational, training and skilling strategy commensurate with the abilities of a more literate labour force and the needs of the economy of the future.

• Improving the productive participation of women in the economy: The other feature of the labour force and employment trends worth emphasizing is the low participation rates for women. There can be various reasons for this, and those related to data quality and information gathering need improvement. Nevertheless, female participation rates are very low in Pakistan, and there is need to find out why and increase them. If this means yet another factor which increases ‘the growth rate’ of the labour force, then there is all the more reason to address the issue of productive

65 absorption of labour from the demand side.

On sectoral strategies

The report argues that an employment strategy for the future needs to be sector-specific. It has to look to sectors other than agriculture for increasing productive employment and focus on the manufacturing and the small-scale enterprise sector for employment growth. The main points of the argument are presented below.

The overview of the employment situation in agriculture suggests that over the 1970s, 1980s and 1990s, profitability-driven cropping pattern changes based on the new technological package may have increased labour requirements in the sector. The changing distribution of operated holdings, mechanization and tenurial shifts may have partially adapted to, as well as reduced, these increases. The rest of the adjustment has had to be borne by the new hired casual labour force, the size of which is increasing. The nature of this labour force is reflected in the extent of rural underemployment, wage rates and poverty. While underemployment is sizeable (around 20 per cent including the unemployed) it has shown signs of an increasing trend since the late 1980s. The returns to casual labour suggest that both the levels of real wages and the size of the non-poor in the agrarian economy of Pakistan have either stagnated or declined in the last period for which information exists (1987-88 to 1990-91 for poverty and up to 1994-95 for wages).

At the aggregate level of analysis, it can be said that although agricultural growth performance has not been unsatisfactory, an employment strategy for the future has to look to sectors other than agriculture for increasing productive employment because of low and declining rates of productivity growth in the sector and the already massive share of employment it supports. The main focus in agriculture should be to increase agricultural productivity, which will also mean a reduction in rural poverty, a critical indicator of rural employment conditions in agriculture.

The structural change in the agricultural sector is manifest at the level of both the production and labour process on the one hand and the supply of agricultural labour on the other. Both these changes are noteworthy from a policy point of view.

First, on the production and the labour process. What is significant about the growth of output and employment in the agricultural sector in Pakistan, is not so much their rates of growth, but the changing composition of the labour force on the one hand and the increased variability in the pattern of its production over time, on the other. There is much greater volatility in agricultural output since the mid-1980s which is connected to the widespread assimilation of technical changes in the rural economy, now embedded in the production process. This translates into a fluctuating trend in the employed labour force, with the increasing casual labour component on the receiving end of the adjustments to this volatility in output.

The second matter concerns the expanding and impoverished pool of labour reserve from which this casual labour springs. Landlessness and near landlessness as a consequence of declining tenancy and the sub„¼division of holdings is one element. The other may be a return labour flow into the agricultural sector because of low growth in other sectors of the economy, especially the rural SSE sector. These tendencies are likely to exacerbate the size of the labour reserve in rural areas, which then has to forcibly get absorbed in agriculture as a last resort.

A policy focus which promotes growth and employment in the agricultural sector in the future therefore needs to have as a dual aim:

• the dampening of the relationship between the volatility of output and the livelihoods of the workforce; and

• making the livelihoods of casual labour within this workforce more sustainable.

66 The whole area of provisions of micro credit in rural areas to reduce the enforced dependence of a growing labour force on the sector and related efforts for the promotion of productive rural non-farm employment, are of immediate relevance. On the other hand autonomous expansion of employment if it is to take place in as large a sector as agriculture, needs to be integrated with poverty alleviation programmes.

The active focus of an employment strategy must move towards manufacturing. Manufacturing output growth is not only strongly related to the growth of output in other sectors but to economy-wide employment growth. In particular, it does have positive and relatively stronger linkage effects on employment growth in most other (non-agricultural) sectors of the economy. Therefore, the greater the extent to which growth in manufacturing is employment based, the greater will be its employment multiplier effects on the rest of the economy. Promoting employment-friendly growth through manufacturing does have a potential problem: employment elasticities in it are low and productivity growth during the 1990s has been associated with a negative employment growth. The situation in manufacturing therefore, at least on the face of it, has the problem that output growth cannot be expected to generate much direct employment. This requires us to make critical distinction between the large-scale and small-scale manufacturing sectors.

The report argues that the manufacturing sector has a role to play in the revival of employment growth just as it has a role to play in output growth, despite popular perceptions regarding its jobless-growth characteristics. It has to be a lead sector from the point of view of future employment generation through its multiplier effects. We find that trends in output growth rates suggest a decline. The 1980s were a high growth period while the 1990s are characterized by low growth. Growth in manufacturing since the 1980s has been driven by labour productivity as opposed to employment expansion, the last period in which employment expansion took place was the (low growth) period of the1970s. It can be argued that output growth began de-linking itself from employment in the 1980s and became de-linked from employment expansion altogether in the 1990s. Part of the explanation lies in the distinction between small and large scale sectors in manufacturing in Pakistan. It is the small-scale manufacturing sector employment which declined in the mid 1980s while its output grew. In the large-scale sector both employment and output growth have been positive in the 1980s and most of the 1990s. In other words, the de-linking of employment from output growth which was taking place in the manufacturing sector in the 1980s and which was established in the 1990s, may have been due to the overwhelming weight of the declining employment in the small-scale manufacturing sector and not because of the large-scale sector as such.

An implication of the above is that employment growth needs to be promoted in the small-scale manufacturing sector, while output growth needs to be revived and the low elasticity of employment increased in large-scale-scale sector. Therefore the centrepiece of an employment generation strategy within manufacturing should be the small-scale sector, which is larger in weight (around 83 per cent). In contrast the primary focus of a revival of growth strategy is the large-scale sector where the bulk of manufacturing output (around 70 per cent) is produced. It is this sectors growth which is likely to have positive linkages with other sectors including activities in small-scale manufacturing as well as small-scale non„manufacturing. The challenge for the manufacturing sector in Pakistan is considerable. A concerted effort needs to be made towards increasing the low elasticity of employment as well as reviving growth.

From the analyses in this report it is also clear that a crisis of demand may be in the process of setting in the large„scale manufacturing sector. The causes of this are complex and multiple but two issues need to be singled out which may go some way towards explaining the slowdown of the 1990s. One concerns the investment climate which has not only deteriorated but spread (from Karachi to the Punjab) in Pakistan from the 1980s to 1990s. The second aspect is related to post-reform deflationary policies adopted by the government in the late 1980s and 1990s, (which were accompanied by privatization and public-sector retrenchments). These are likely to have dampened demand for the manufacturing sector.

A multifaceted policy initiative is required in order to revive growth in the large-scale manufacturing sector.

67 This effort in the large-scale sector needs to focus on reviving demand and improving the social climate for investment, on increasing the utilization of existing capacity; and promoting growth in sectors which also have a potential for autonomous productivity increases. Policies in many areas consistent with these aims have been suggested in this report. These include suggestions on:

• Criteria of sectoral choices in an employment friendly investment plan

• Fiscal expansion and demand

• The Budget deficit and working capital

• Promotion of sub-sectors through tariff rationalizations

• Capital pricing and directing new investment

• The co-ordination of capital flows

• The revival of sick industries

• Taxation and flow of goods

• Energy pricing

The report further argues that the sector which may still have potential for direct employment generation is the SSE sector, there are likely to be labour„intensive activities. Dynamic sub-sectors need to be identified in the SSE sector and practical selection criteria for support need to be developed.

For the SSE sector, a central point to note from our analysis is that growth rates for SSE manufacturing may not be as high as 8 per cent, as estimated by the National Income Accounts, since survey based estimates suggest about half this growth rate. This does not of course mean that the emphasis on the SSE sector for employment is misplaced. However, nor is it as great a panacea for resolving the employment problem as may be imagined and we may need to direct policy as much on growth as on employment generation. It is therefore arguable that there is little ground from a policy perspective to be complacent about SSE growth rates. Manufacturing is around a quarter of the SSE sector in terms of employment and is much the majority in employment for the manufacturing sector taken as a whole. Since the bulk of manufacturing employment is in the SSE manufacturing sector, it is arguable that a decline in growth of the large„scale sector and loss of incomes (as witnessed in the 1990s) could have adversely affected the demand side for goods produced in the SSE manufacturing sector (the sub„contracting effect). Consequently, the growth of the large„scale sector could revive these sub„contracting links and increase effective demand for goods in the SSE manufacturing sector. It is through such a revival as well as the promotion of direct consumer demand, that employment linkages with other sub-sectors (particularly with trade and services) could be realized.

The review of existing major surveys, apart from bringing in a perspective on the growth rate problem, also allows us to disaggregate the macro estimates derived for the SSE sector. The macro estimate we settle on, shows the SSE sector employing approximately four and a half million workers. Characteristics indicate the SSE to be in substantial part a refuge sector based on a spillover of surplus labour unabsorbable in other sectors. The review also shows that trade and services account for the bulk of the SSE sector. The SSE sector is also likely to be underinvested.

This ‘aggregate’ view of the SSE sector has been ‘disaggregated’ in this report by an assessment of the important micro surveys on the subject. There are some relevant findings. The first is that the SSE may not be one large refuge sector, but is instead characterized by a classic dualism. The micro surveys suggest that

68 one part of the SSE sector may comprise firms more integrated in to the mainstream economy, while the other part comprises of firms that are more involuted. The more integrated firms are characterized by stronger demand and input linkages, entrepreneurial decision making, better access to the formal credit market, more use of hired labour, higher capital intensity, higher capital and labour productivity and higher returns. The SSE displays a rich dualism in structural characteristics.

A critical and operational result of this dualism is to have a different policy focus on with less or more than five persons employed. This has implications for specific policies. Improving formal credit access and skills, simplifying tax and regulation ordinances affecting the SSE sector are crucial supply-side measures in general, but the focus of targeting credit must be on the capital starved, self-contained smaller sized firms while the concentration of training demand should be on skill-starved, external demand linked larger sized enterprises.

Government policy, as a whole, towards the SSE sector is likely to fall into two categories, committed and omitted. Committed policy is the States attempts to help the SSE sector. Omitted policy is default policy, the actual impact of all its macro policy, on the SSE sector. In particular, some areas in which government policy can be strengthened with respect to the SSE have been emphasized in this report. These relate to credit, taxation, infrastructure, training and demand creation. Some the specific policies advocated in this report concern:

• Refocusing committed and omitted credit policy through the elimination of subsidies in credit programmes and increasing credit lines through SSE targeted institutions.

• Restructuring omitted and committed taxation policies.

• Decentralization of infrastructural programmes

• Tying of skills and export markets

• Creating effective demand for SSE products

On the whole employment strategy for the future in Pakistan must aim to eliminate the gap between the ‘labour force’ and ‘the fully employed’ within it. It must act not only by attacking unemployment and underemployment head-on but by adopting policies that simultaneously and significantly increase aggregate employment. The strategy must function at a sectoral basis. This report argues that an employment growth strategy for the future must be built with three aims:

• the growth of output and employment in the manufacturing sector

• the limitation of increased labour absorption in agriculture

• the promotion of dynamic sub„sectors within the small-scale enterprise sector

The overarching objective of these aims is to revive growth in such a way that its employment multiplier effects in the economy are significant and there is minimum downward pressure on productivity in agriculture. The positive focus of the strategy is based on manufacturing and the small-scale enterprise sector. In the view taken by this report, this triadic approach constitutes the way towards an improved employment situation in Pakistan.

69 APPENDIX

The Economic Reforms Context of Growth and Employment

1. The periodisation of growth and status of macro-economic policies

This appendix attempts to provide a macro-economic and growth context to the issue of employment in Pakistan. A serious study of macro-economic policies and their effects on the different parts of the real economy is a more complex and detailed exercise, which is beyond the scope of the present report. It is however, the view taken here, that a perspective on macroeconomic policies and growth is a necessary starting point for an analysis of the employment situation in Pakistan today. In fact, in a dynamic sense, it may be necessary to take in to account the macro policy regime, for a revival of growth that entails employment expansion.

The link between macroeconomic policies followed by the government on the one hand and employment on the other, is mediated by the level and pattern of growth. In Pakistan the links between macro policies and growth, at least until recently, have involved both economic and non economic aspects. Examining trends over the longer historical period we find, that although macroeconomic policies undoubtedly influenced growth, the periodisation of growth itself into high and low phases, introduces factors that are beyond economic policy itself.

To emphasize the point about non-economic factors, and as a useful perspective on Pakistan’s growth process, Table 7.1 attempts a periodisation of its economic and political history simultaneously. There are many ways in which periods can be distinguished. Of the many demarcation criteria for periods of development in Pakistan, the timing of the flow of foreign aid; the forms of political governments; the two martial law periods (1958-73 and 1977-85); and legal-institutional watersheds such as the three constitutions (1956, 1962, and 1973) are important markers. Another criterion, which is more economic policy related is the set of eight Five-Year Plans – especially the Second Plan (1965-70) and to a much lesser extent the Sixth Plan (1982-87) – which lay out strategies and policy frameworks. Since the role of macroeconomic policies has acquired centre stage in policy debates in the economic reforming Pakistan of today, the periodisation is also given according to both pre and post-economic reform periods. In addition our focus within this classification is the set of macro economic policies of the early period of reforms and the more recent years.

A brief description of the longer historical period is in order, as a starting point..The first two periods in the Table 1.1 correspond to a Pakistan which includes what is now Bangladesh (1947-71), while the last three periods (1971-97) correspond to the present boundaries of Pakistan1. Under pre-1971 Pakistan, four phases can be identified: 1947-53, was characterized by reconstruction and self-reliant development; 1953- 58 was occupied with the preparation of the First Five-Year Plan (1955-60), achieved with considerable external assistance; 1958-65 were the “miracle” years of aid reliant development; and 1965-71 can be seen as a period of disintegration, leading to the independence of the eastern wing of the country as a separate nation State.

In the contemporary period (1971-97), three political phases can be readily identified. In the first, 1971-77, an elected government sought to re-orient the path of growth that Pakistan had embarked upon in the 1960s, and ushered in a period of greater state intervention in the economy characterized by widespread nationalizations. In the next period, 1977-88, a military government which replaced the elected

1 For a detailed discussion, See ILO-SAAT/ Arshad Zaman Associates (1997).

70 government, undid the nationalizations of the first period. In the present phase, 1988-98 , democratic governments returned to the country and the economy was re-oriented towards private-sector-led growth. This period is also characterized by economic reforms which the government is now in the process of implementing and which are the focus of this Appendix..

Table 1.1:Growth and structural change, 1950-58a 1958-71a 1971-77 1977-88 1988-97 1950-97

Growth rates (% p.a. by OLS method)

Population 2.5 2.8 3.2 3.1 3.0

Real GNP (mp) per capita 0.9 4.2 3.3 3.0 1.1

Consumer prices 2.3 3.2 17.4b 7.5 10.4

Real GDP (fc) 3.3 6.2 4.8 6.6 4.8 Value added in agriculture 1.8 4.3 2.2 3.9 3.9 Value added in LS manufacturing 19.8 12.1 2.3 9.4 4.0

Employment .. 1.6 3.0 2.4 2.1 In agriculture .. 0.8 1.8 2.0 1.0 In large-scale manufacturing .. 3.6 3.0 1.7 - 0.9

Structure (% GDP, end period)

Agriculture 51.8 41.2 36.6 22.9 22.4

Large-scale manufacturing 6.1 11.9 10.3 11.6 11.1

Overall budget deficit (-) .. .. -8.6 -8.5 -6.3

Trade deficit (-) -4.9 -3.2 -7.8 -5.0 -4.8

Current account deficit on the BOP (-) .. .. -7.0 -4.4 -7.1

M< external debt (DOD US$ billion) .. .. 8.3 20.0 30.0 (as % of GNP) .. .. 52.6 49.9 46.6

Liquid external reserves (US$ billion) .. 0.1 0.4 0.5 2.5 (as months of merchandise imports) (..) (2.3) (1.9) (0.9) (2.5)

Notes: All growth rates have been calculated by fitting an ordinary least squares (OLS) trend. .. not available. a (West) Pakistan only. b Only 11.1% (OLS, or 9.5% simple average), if 1971-72 and 1973-74 (when imported inflation was an extraordinarily high) are excluded.

Source: Economic Surveys, Annual, and Federal Bureau of Statistics. See ILO-SAAT/Arshad Zaman Associates (1997).

The non-economic correlates of macro-economic policies and growth

In general it can be argued that in Pakistan, the degree of causality between macro policies and growth is weak and it may be difficult explicitly inferring outcomes from the policy. The argument for the

71 importance of non-economic policy factors is straight forward. Two overdetermining correlates of the phases of growth (high/low) in Pakistan are:

• the timing of flows of external assistance (economic and military aid) which the State has received over time; and

• the performance of the agricultural sector.

It is noteworthy that both correlates are subject to external influences which are governed in part by non economic considerations. In the case of external flows, there is a whole set of international geo-strategic considerations as well as the nature of government, which may be of relevance. In the case of agricultural performance, there is clearly a feature of external natural uncertainty at work. It can be argued that throughout the almost 50-year period the volume of external assistance received (on which reliable data is easier to acquire on the economic side) and the performance of the agricultural sector have been the proximate determinants of economic performance. If this is indeed the case, it leads to a peculiar difficulty in attempting any serious analysis of the impact of development strategies and macro-policies on economic outcomes.

This knowledge of crucial external determinants at the policy level has implications for institutional behaviour. It has meant that economic strategy and policy statements have been, at least in some measure, motivated by a concern for maximizing foreign assistance. In particular, the nature of this relation between ‘stated growth strategy’ and ‘access to capital’ has had two specific effects on policy making in Pakistan. One concerns state action and the other the robustness of policy itself. First, it has made plans of action by government, subject to ad hoc executive decisions, which are not transparent. Second, and at the analytical level, the link between ‘strategy’ and ‘outcome’, when it has been invoked, has often been a fortuitous one, even though plan and programme reviews submitted by government to donors have on occasion sought to establish such links.

However, in the present phase , it is precisely the adoption of specific macro-policies themselves that have arguably come to play an influencing role in the timing of external flows. It is therefore important to assess if these policies have performed the role that they were supposed to, given their raison d’etre.

In any periodization of the political economy of Pakistan, therefore, broader conditions for the sources and flow of foreign assistance must constitute an important criterion of demarcation. This slightly cross-cuts our classification of decades, the 1970s , 1980s and 1990s phases chosen for the analysis of the labour force and sectors of the economy.

Given the external determinants of past growth and their impact on the nature of the decision making process in Pakistan, two important symptoms of what can be termed the problem of growth and development in Pakistan become easier to understand.

Two symptoms of the problem of growth

There are two important symptoms of the problem of growth and development in Pakistan, which need to be singled out for the purpose of our discussion. First, the country’s economic performance has been such that growth and structural change have not improved the lives of a majority of the population by anywhere

72 near what that growth process could have achieved. Growth has been insensitive to distribution.2 A second symptom of the problem of Pakistan’s growth has been the government’s inability to establish a sustainable pattern of public finance, historically relying first on foreign grants, then loans, supplemented by domestic non-bank borrowing, and of late, even by borrowing from short-term private sources. As a result, Pakistan faces a profile of high increasing future debt service payments. These two symptoms are also mutually reinforcing. A growth process insensitive to distribution is complemented by the unwillingness or the inability of the State to tax the better-off sections of society (which, in part, is what makes the public finance structure narrow and precarious).

Assessing the policy-growth linkage

The employment situation in Pakistan, both in general and at a sectoral level, has been discussed in this report. One central concern in this assessment pertains to the 1990s overall slowdown of growth after the 1980s boom and, in particular, the crisis of growth in the manufacturing sector. In our view, this constitutes a critical matter to address, for any future employment revival strategy. Here we attempt a macro policy based explanation of what happened to growth in the 1980s and 1990s.

Notwithstanding the problems in choosing the right periodization and the matter of external determinants of growth, an basic assessment of the association between growth and macro-economic policies is at both an aggregate as well as a thematic level is attempted below.

The aggregate assessment gauges the impact of macro policies taken together during a pre-selected period ( i.e. the reform period). The same assessment also to distinguishes between sub-periods within the reform period. The thematic assessment on the other hand, gauges results of each type of macro policy area (e.g. trade, fiscal or monetary policy). The latter can also be phased in terms of the pre given periodization (e.g. trade policy in the reform period) or can move across periods (e.g. trade policy from the 1970s onwards). Particular reform policies undertaken by government are distinct insofar as they pertain to different areas of the macroeconomy as well as their implementation over different time periods. Finally, since the expected effects of macro policies on growth depend, in part, on the interaction between the individual policies themselves, it is important to look out for sequencing of reform policies as well.

The aggregate overview

For the aggregate overview, the reform policies can be taken as the ‘package’ and the reform period as starting from when the first reform initiatives were taken up, to the present. However, in order ask the larger question on the ‘effect of reforms’, we first need to identify some core objectives of the reforms and then select the appropriate indicators of their performance. We list below what can be termed the three core objectives of the economic reforms:

• One objective is that of sustainable growth, if the reform package ‘as a whole’ works it should be reflected in a healthy growth process which is sustainable.

• A second objective is to achieve price stability

• A third objective is balance of payments viability.

2 The argument which can be developed here can be based on two points. The first point is that a long history of non-democratic periods of government entrenches State structures that are less pressured to be distribution-sensitive. Secondly, a history of excessive reliance on external flows of funds erodes the institutional incentives to develop a progressive taxation system to be applied on civil society in order to finance economic development.

73 Figure 1 presents trends in major macroeconomic variables since 1971, along with a demarcation of the periods identified (for data on period averages, see Table 7.1 above).3 We have separated the reform from the pre-reform period. Moreover, the reform period has been divided into two sub-periods. It is the case that one phase of the sub-division can be associated with the part of the 1980s in which manufacturing growth occurred. In terms of a reform history, the first reform period marks the first extended fund facility (EFF, 1980-83) obtained for debt rescheduling from the International Monetary Fund (IMF) by Pakistan. In 1982, the World Bank (WB) also extended a structural adjustment loan (SAL) to complement the IMF’s EFF,4 which was later abandoned and then followed by two sectoral adjustment loans (SECALS). The third period (from 1988 to the present) has been characterized throughout by intermittent long-term arrangements with the IMF.5

The indicator on economic growth

The data represented in Figure 1 suggests that there has been a downward drift in the rate of economic growth, on average at least since the mid-1980s. Therefore, for the initial part of the 1980s, it can be argued that reforms, to whatever extent they were occurring at the time, did not harm growth and may have enhanced it. In fact, if we recall the data on large scale manufacturing in Chapter Four, the bulk of the high growth during the 1980s was in 1982-83 and 1987-88 (the growth rate in this period was 8.2 per cent). Since the reforms affected large scale manufacturing more directly than other sectors, a growth-enhancing relationship can be posited for this period.6 By the same logic, the next period is one of economic slowdown and declining growth, which can be associated with the nature of reforms undertaken in that second phase.7

3 Because annual data is presented we can do different periodizations. We have also stated on the x-axis a classification based on reforms and forms of government.

4 The SAL broke down eventually because of differences between the government and the lender. Accordingly, it was followed by sectoral adjustment loans (SECALs) in energy (1985) and export development (1986). The latter was a compromise option, as the government was not prepared to accept the trade liberalization measures being proposed by the WB for a trade sector loan at the time.

5 The government has presently negotiated a US$1.6 billion extended structural adjustment facility (ESAF) and EFF, with a first tranche of US$200-250 million.

6 It is of course possible to argue that the reforms undertaken in this period were ‘soft’, and this freedom of not being forced in to taking ‘hard’ options was due the political and diplomatic relationships that Pakistan enjoyed internationally at the time.

7 We will see later, in a thematic assessment, that exchange rate reforms and import liberalization (non-tarrif barrier removal) were the focus of the first period and financial sector liberalization and tariff reforms the added focus of the second.

74 Figure 1: Growth, Inflation, Unemployment Rate, Budget Deficit & the Current Account Deficit on the Balance of Payments State Capitalism / Reform Reform Period II / Elected Period I / Elected Governments Government Military Government

12 35 1st 10 EFF 30 25 8 20 6 15

4 per cent 10 2

Deficit (% of GDP) 5 0 0 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 Fiscal Years Ending June 30

Budget Deficit BOP Deficit Growth Inflation Unemployment Rate

The indicator on price stability in the economy

There has been a secular upward drift in the rate of inflation, during the later reform years. Inflation fell below 5 per cent in 1987, but has been rising sharply since then. It is the second reform period which is associated with rising prices. It is to be noted that these trends on performance indicators appear to be independent of the size of the budget or the balance of payments deficits - although, naturally, it is counterfactually arguable that higher deficits would have led to higher inflation and lower growth.

Indicator on external balance

On the count of the balance of payments situation, Pakistan continues to seek extraordinary external finance despite over ten years of adjustment programmes, as figure 7.1 shows.

Indicators on labour market conditions

It is useful to review the results in Chapter Two, of the indicators of labour market conditions in Pakistan. Although improvement here may not be an explicit reform objective, labour market conditions have been affected in the period and are a central concern for the ILO. The rate of unemployment rose after 1975, stabilized (at around 5 per cent) from 1979 to 1990 and, given comparability problems, is unlikely to have declined since then. We have, however, seen in detail (in Chapter One) the underemployment situation as well, which is a better indicator of employment conditions and, in our assessment, this situation is not improving. Indicators on poverty and wages (in Chapter Two), which are probably even more comprehensive signals of labour market conditions in countries where formal labour markets are limited in scale and scope, show a deterioration in the 1990s.

The overall assessment of the reform experience in Pakistan, taken across sub-periods, therefore requires circumspection. It is clear from the above evidence that adjustment programmes may not have been able

75 to achieve at least three of their main aims: (i) sustainable growth; (ii) price stability; and (iii) balance of payments viability – in the sense that at the end of the programme there would be no need for further extraordinary external financing. In addition, labour market indicators of employment conditions have deteriorated in the recent period. However, on balance, it also seems clear that it is the second period of adjustment that has been characterized by falling growth, rising inflation and worsening employment conditions, while in the first period the economy had performed better.

On the evidence of these indicators, we need to look more closely at the type and nature of reforms being undertaken in the first period, largely covering the 1980s and those in the second period (from the late 1980s to the present). This is a periodic demarcation which is suggested by the distinctness of the indicators of achievement in the two periods and brings us directly to the thematic analysis referred to above, the focus of the next section.

7. A THEMATIC ASSESSMENT

On the sequencing of reforms and the reform policies

Why have the achievements of the reform package been so modest in Pakistan? One argument is that the sequencing of reform policies is as critical as their content, and that there has been improper sequencing of reforms in Pakistan. There is ample evidence from both IMF/WB studies and from independent research that macroeconomic stability - which in Pakistan also means budgetary stability is an essential precondition for the success of economic liberalization.8

Unfortunately, in the face of binding political constraints to budget and institutional reform (especially when democratically elected governments are in power) international lending and financial agencies, possibly facing their own operational exigencies, have gone ahead with such “reforms” as the government could agree to. This may have occurred even though the sequencing conditions considered important for the success of these reforms may not have been met.

There is much to be said about sequencing, although it must be emphasized that the argument invoking a sequencing failure is agnostic on the validity or appropriateness of the individual policies whose sequencing is in question. These must be assessed on their own merit. In other words, correct sequencing is only a necessary condition for reform success; the individual reforms must also be suitable for the country involved. This is important to bear in mind because of a tendency in policy debate to use “sequencing failure” as a reason to ignore the assessment of individual reform measures.

Having noted the important issue of sequencing, which will be illustrated by example later, we now examine three thematic areas of intervention by government which circumscribe the main reform agenda. These pertain to fiscal policy, monetary policy and the trade regime.

8 See Thomas et. al., 1991.

76 Fiscal Policy

Fiscal policy can be seen as a set of measures taken by the State, that are concerned with income and expenditure of government. On the income side, there is direct revenue generation (taxation) and deficit financing; the expenditure side is self-evident. In the absence of a formal model, we use the likely key static first-round effects of the impact of fiscal policy on economic growth as described in the following processes:

• government revenues reduce disposable income and hence private savings, private investment and growth. The effect on growth is therefore likely to be negative;

• deficit financing, which absorbs a large share of private savings and raises interest rates, reduces investment and growth (among other effects). Thus the growth effect is also likely to be negative;

• government expenditures can lead to domestic income redistribution, incremental demand for goods and services and capital formation, all of which should have a likely net positive impact on investment and growth, depending on the level and composition of government expenditure. So the growth effect is likely to be positive.

In principle, the tax-revenue effect and the deficit financing effect are negative and the expenditure effect is positive. Consequently, in principle, as long as fiscal policy is also redistributive, the expenditure effect can be made to dominate the expected negative tax and deficit-financing effects. It should be recalled that in the opening section we noted two symptoms of the weakness of the growth process in Pakistan: namely that it was insensitive to distribution and relied on a narrow base of public finance. This combination is clearly not conducive to a growth-enhancing fiscal policy thrust.

Government revenues in Pakistan have remained at around 17 per cent of GDP for a very long time - the higher budget targets for the present years are unlikely to be attained. Also, the direct impact of the revenue-effect on disposable incomes and saving has not been onerous. The bulk of tax revenues, however, arise from indirect taxes, mainly import duties; their effects on industrial incentives will be examined further in our discussion of trade policy. Over the last decade, sales tax (mainly as a surcharge on import duties) and excise duties (collected mainly from a few items) have grown. On balance, however, the average burden of taxation has been moderate, although the incidence of salaried tax-payers already in the tax net had become quite high. This has been corrected in the 1997-98 budget.

The major impact of the budget on investment and growth, however, has come from expenditures and their non-revenue financing. First, the accumulated burden of inadequate taxation has led to an unsustainable rise in the debt burden so that, over the decade, debt service payments have been growing, at a rate of nearly 20 per cent per year.

As a result of the rising burden of debt service payment and government expenditure on defence, development and civil administration have been severely curtailed. Clearly the restriction on development expenditure is not without social costs, particularly when indicators of labour market conditions are also worsening. The decline in public investment has arguably had both a direct impact on capital formation and an indirect one on conditions of work through inadequate provision of public goods (especially the physical and social infrastructure). Also, as the government has sought to mobilize increasingly higher amounts of money from the capital markets, interest rates have risen and private investment incentives have deteriorated.

77 Table 2: Indicators of fiscal policy, 1980-97

1979-80 1987-88 1994-95 1995-96a 1996-97b

Structure (as % of GDP)

Revenues 16.4 17.3 16.9 17.5 18.7

Expenditures 23.3 26.7 22.8 23.9 22.7

Debt service 4.6 6.8 8.7 8.7 9.3

Foreign 3.4 3.2 4.4 4.1 4.5

Domestic 1.2 3.6 4.3 4.6 4.8

Defence 5.4 7.0 5.6 5.5 5.2

Development 9.3 6.9 4.4 4.3 4.2

Administration, etc. 4.0 6.0 4.1 5.4 4.0

Overall deficit 6.3 8.5 5.6 6.3 4.0

Domestic financing (Net) 3.3 6.6 4.0 5.1 3.3

Non-Bank 0.6 4.5 2.6 2.7 2.5

Banking System 2.7 2.1 1.4 2.4 0.8

External financing (Net) 3.0 1.9 1.6 1.2 0.7

Memorandum (as % of GNP):

Public Debtc .. 73.9 79.0 79.3 ..

External debtc .. 33.0 36.5 37.3 ..

Domestic debt .. 40.9 42.5 41.9 ..

External liquidity (as % of imports) 17.5 7.7 29.4 21.9 ..

Notes: Consolidated federal and provincial government budget figures, as presented by the Ministry of Finance in their Economic Survey. In the past few years, these figures have differed from those presented by the State Bank of Pakistan (SBP) in its Annual Report. The overall deficit is the difference between revenues and expenditures plus the surplus of autonomous bodies (not shown). .. not available. a Provisional actuals. b Budget estimates. c Outstanding and disbursed.

Source: Economic Survey 1996-97, Statistical Supplements, and SBP Annual Reports.See ILO-SAAT/Arshad Zaman Associates (1997).

78 Figure 2 External Debt & Debt Service 25 2500

20 2000

15 1500

10 1000 US$ billion US$ million

5 500

0 0 1991 1992 1993 1994 1995 1996 Fiscal Years Ending June 30 LT Debt ST Debt LT Debt Service ST Debt Service

Thus, the pattern of government expenditure has become less growth-enhancing and has relied for its income more on non-revenue-based deficit finance. The net impact of the government’s fiscal operations especially in the 1990s, has therefore been to contribute to macroeconomic instability and lower the rate of investment and growth.

Monetary Policy

Monetary policy primarily affects investment and growth through its impact on incentives to save, invest and produce. It does so mainly by ensuring that credit is available, at as low interest rates as possible, in a stable macroeconomic environment. Until February 1994, when the State Bank of Pakistan Act, 1956 was amended to give the State Bank greater autonomy, monetary policy in Pakistan was conducted largely to accommodate the financial requirements of government.9 It is still too early to predict the impact of this new autonomy on the government’s future conduct. Although early signs suggest possible areas of conflict between an elected government’s need to facilitate its own access to capital and a central bank’s responsibility to have a broader economy-wide stability as an objective10 . In the past, however, the role of monetary policy per se had been minor, as the State Bank’s intervention in financial markets had consisted mainly of the direct regulation of credit, in support of the government’s economic objectives.

9 The State Bank of Pakistan Order 1948 was succeeded by the State Bank of Pakistan Ordinance of 6 July 1955 (converted to an Act of 18 April 1956).

10 According to Hasan (1997, p. 10): “…reliance on credit controls has not disappeared completely although formal credit controls no longer exist. In practice, formal controls have been replaced by equally effective jawboning [i.e. making firm ‘suggestions’ which are carried out for fear of offending the authorities] when a bank’s credit expansion gets out of line in the opinion of the authorities.”

79 There have been three major landmarks in the history of credit regulation in Pakistan11. More recently, in 1990-91, under a Financial Sector Adjustment Loan (FSAL) from the World Bank and technical assistance from the IMF, a transition from instruments of direct control over credit to indirect influence of monetary aggregates (mainly through open-market operations) was effected.12

Whether it had other costs or not, there should be little controversy in assuming that the direction of credit flows to priority sectors led to an improved fulfilment of the government’s priorities: promoting investment and growth, and partly meeting its distributional objectives. At the same time, there is considerable evidence that without prior budget reform, financial – sector reform can be seriously counterproductive. In the context of Pakistan, this essentially translates into putting in place legislative constraints to fiscal indiscipline. It is reasonable to argue that financial-sector liberalization was premature. Whatever impact it had on the efficiency of the banking sector,13 the rise in interest rates that followed had disastrous consequences for the budget,14 and may have led to a crowding-out of genuine private investment.

The idea that, by confronting government with higher interest rates, the government’s recourse to non-bank domestic borrowing would be curtailed, was flawed from the start. In the event, after the switchover to market-based instruments, recourse to domestic non-bank borrowing - after turning negative in the year of the switchover, 1991-92 - rose rapidly, and at higher rates of interest (Figure 7.3).

The common-sense view was that without putting in place effective constraints on budgetary indiscipline, financial sector liberalization would lead to higher interest rates and hence a rise in the government deficit.15 On the basis (presumably) of a judgement that budget deficits could be controlled, the financial sector liberalization was supported through substantial loans. Surprisingly, and on a priori reasoning, it was held that the higher interest cost on market-based government borrowing (estimated at Rs 3.2 billion over the nine-year period 1985-86 to 1996-97) would be offset by lower

11 First, there was the Credit Inquiry Commission of 1959 and the Credit Inquiry Committee of 1962 , that provided the State Bank of Pakistan (SBP) with clear directions to micro-manage the process of credit distribution - to primary-producing sectors, and small and medium-scale enterprises – through the establishment of new institutions. Second, under the banking reforms introduced in May 1972, elaborate institutions, consisting of the National Credit Consultative Committee (NCCC) and its sub-committees, were set up to ensure that the credit needs of specific sub-sectors were met.

12 As distinct from monetary policy, the financial sector in Pakistan was affected by three major developments in the banking sector. First, the establishment of United Bank Limited (UBL) in 1959 introduced the culture of aggressive deposit mobilization in commercial banking in Pakistan. Second, the nationalization of banks on 1 January 1974 inaugurated an eventful era of government control over banks. This era came to a close in 1991 when the government partially disinvested two nationalized banks, and granted licenses to 10 new private banks, while 6 investment banks (licensed earlier in 1989) started operations.

13 Serious questions can be raised about the contribution to higher profits of inadequacies in banking supervision and regulation and the lack of competition in the banking sector.

14 High interest rates have also inhibited private investment, although there have been other non-economic reasons for this as well.

15 In an important report, the World Bank (1987, vol. 2, pp. 6-7) also stressed the need for “careful sequencing” of reforms – identifying price stability and the maintenance of external balance, through deficit reduction, exchange rate action, and conservative monetary policies, as pre-requisites for the success of trade reform, financial sector reform and deregulation – and warned that “financial sector reform will not be successful unless accompanied by reduction in the budget deficit.”

80 short-term rates on national saving schemes and greater dividends and taxes from increased earnings of the banking sector (estimated at Rs 14.5 billion):16

‘‘Overall, the government would gain Rs 17 billion, over a nine year period, (US$100 million equivalent per year) if it pursued the proposed strategy as against following the existing financing pattern.” (Underlining in original)

These expectations did not materialize. First, budget deficits did not decline progressively from 8.7 per cent of GDP in 1986-87 to 4.2 per cent in 1996-97, leading to much larger borrowing requirements than had been anticipated. Second, the rise in interest rates on domestic public debt envisaged - from 11.2 per cent in the base case to 11.67 per cent in the recommended (staged introduction of market-based borrowing) case – proved unrealistic. Both the interest cost and the stock of government domestic debt rose much faster, as figure 7.3 shows.17 Finally, the assumption that government would be able to “earn an additional Rs 14.5 billion through higher earnings of SBP/NCB [State Bank of Pakistan/Nationalized Commercial Banks]” proved to be incorrect.18

Consequently, monetary policy as far as it brought in financial sector liberalization, led to an interactive sequencing problem with respect to fiscal policy, and this has been an important cause of macroeconomic instability, the drying up of investment and the slowdown in growth.

Figure 3 Domestic Debt: Interest Rate & Stock Outstanding

1000 14 800 12 10 600 8 400 6

Rs billion 4

200 2 % per year 0 0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Fiscal Year Ending June 30

Outstanding Debt Interest Rate

16 World Bank 1987, vol. 1, p. 27.

17 Figure 3 is based on data provided by State Bank of Pakistan (1996, p. 91). The interest rate is estimated as the ratio of interest payments to the stock of debt outstanding at the end of the previous year.

18 This was compounded by the fact of an early disinvestment of some of the banks and the losses absorbed by the State Bank on the provision of forward exchange cover [i.e forward selling of foreign exchange at a fixed rate].

81 Trade and exchange rate liberalization

The second area where the government undertook reforms, pending meaningful action on the budget, was that of external finances. These involved exchange rate depreciation, trade liberalization (i.e. reduction of non-tariff barriers) and tariff reforms (i.e. reduction - and the lowering of dispersion – of import duties). These matters need to be assessed separately.

Exchange Rate Reforms (1982- )

In February 1982, as part of the first Extended Fund Facility (EFF), Pakistan de-linked the rupee from the US dollar, and initiated the current regime of the managed float.19 The immediate motivation for devaluation or depreciation of the rupee has always been to shore up foreign exchange reserves, even though of late the action is sometimes justified as having a beneficial long-term impact on resource allocation.

There is, however, some controversy about the efficacy of exchange rate action in Pakistan’s circumstances. First, it can be argued that unless there is prior action to curtail excess demand arising from the budget – demand for debt service or military expenditures which are insensitive to the exchange rate – a lowering of the exchange rate merely exacerbates budgetary pressures without alleviating the root cause of macroeconomic instability. Second, given that the demand for Pakistan’s major exports (cotton and cotton-based textiles and garments) is relatively price-inelastic, a depreciation of the rupee does not lead to a rise in export receipts. Finally, and more generally, structural rigidities in factor markets inhibit a reallocation of resources (from non-tradeables to tradeables), which are necessary to realize the fuller efficiency gains from currency depreciation. Figure 4 presents the basic data on nominal and real (consumer price index deflated) exchange rates and the trade and current account deficits on the balance of payments (as ratios of GDP).

Despite the heavy nominal depreciation of the rupee, in real terms the rate of exchange has remained fairly constant. On the “before-and-after” assessment, it would seem on balance that exchange rate depreciation has not had any appreciable impact on external deficits. On a “counterfactual” reading, however, it can be maintained that had the nominal value of the rupee been maintained at a higher level the deficits would have been larger. There is probably some positive impact of currency devalution on the the deficit.

Basically, the argument for devaluation resulting in a feedback mechanism for an export boom has not materialized. This argument assumes a structure of exports which is essentially different from Pakistan’s. Clearly, exchange rate reforms were not sufficiently drastic to alter the structure of incentives in production and ensure a smooth transition between tradeable and non-tradeable production in the economy. The budgetary effect of exchange rates has been adverse and is mainly felt through price-insensitive items such as defense and debt repayments.

19 In historical terms, the exchange control system inherited at independence in 1947 was modified by two major external developments in the initial years (1947-55): the devaluation of the British pound, and consequently of a number of sterling area currencies, in 1949; and the Korean War boom and following slump of the early 1950s. Pakistan first devalued the rupee in 1955, and following setbacks in exchange and trade liberalization (pursued during 1959-65) once again in 1972.

82 Figure 4. Exchange Rate (Rs/US$) & External Deficits (% of GDP) 12 0 5 10 10 8 15 20 6 25 4 30

% of GDP (mp) 35 2 40 Exchange Rates (Rs/US$) 0 45 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 Fiscal Years Ending June 30 Trade Deficit Current Account Deficit Nominal Exchange Rate Real Exchange Rate Linear (Current Account Deficit)

Trade liberalization (1983- )

Non-tariff barriers

Traditionally, non-tariff barriers (NTBs) were used in Pakistan to curb imports in the face of acute shortages of foreign exchange. In time, they were justified on grounds of industrial promotion, even though their adverse impact on government revenues (and efficiency of resource use) was recognized. Until 1982- 83, only those goods could be imported which were on the “free” list (for which imports were allowed, subject to quantitative restrictions (QRs), after obtaining an import license) or the “tied” list (which regulated mainly public-sector imports from specified sources).

Under the first EFF, the government agreed to a radical change in its import policy. In 1980, 406 of 435 products on the free list were subject to QRs. As part of its agreement with the IMF, by 1983 the government had reduced these QRs to 5, and by 1985 no product was subject to QRs. Even more significantly, the 1983 import policy replaced the free and tied lists with a “negative” list (and a transitional, “restricted” or “conditional” list),20 leaving all items not on the two lists to be freely importable. Initially, the negative (and the conditional) list was quite large. Over the years, however, and especially since 1988, these lists have been narrowed parallel with successive IMF agreements.21 In recent years, the import licensing requirement has also been removed so that an importer can open a letter of credit with a bank and import any of the importable goods.

20 The restricted list was a revised version of the tied list and sought to protect Pakistan’s trade commitments under a variety of bilateral agreements.

21 The bulk of the reduction took place in 1987-88 and the next three years, respectively: 136, 169, 70 and 97 items were removed from the negative list, and 10, 51, 20 and 43 items, from the restricted list.

83 What has been the impact of the removal of NTBs? While increased efficiency of resource use is hard to document, trade liberalization has certainly led to an increase in government revenues from import duties on previously banned imports. This gain however, has been at the expense of increased imports, and the loss of an instrument of strategic intervention in trade policy.

Tariff reforms (1990- )

One major thrust of the adjustment programmes in the second period has been the reduction of import tariffs and the elimination of export duties. The purported objective is a reduction in effective protection rates (EPRs), and in the dispersion of EPRs.

Figure 5 is a visual representation of the share of customs tariff line items in the (most favored nation, MFN) statutory tariff rates in (fiscal years ending June 30) 1982, 1990, 1993, 1996 and 1998.22 In addition to the tariff slabs represented in Figure 7.5, the coverage of specific tariffs fell from 4.1 per cent in 1982, to 2.3 per cent in 1990, but rose to 2.6 per cent in 1993 (to meet revenue needs), before falling again to 1.3 per cent in 1996 and 1.2 per cent in 1998. As a result of these changes, in the same four years, the average rate of import tariffs fell from 79.2 per cent, to 59.8 per cent, to 58.2 per cent, to 44.3 per cent, while the dispersion in these rates was reduced from 49.8 per cent, to 33.9 per cent, to 24.6 per cent, to 23.1 per cent (and the coefficient of variation from 62.9 per cent in 1982 to 51.3 per cent in 1996). In addition to tariff reductions, adjustment programmes have sought to reduce (and eliminate) the numerous exemptions and concessions provided to specific commodities, plants, industries, and even importers.

Figure 5. Tariff Reform, 1982-98

60 1982 40 1993 20 % of lines 1998 0 Free 15 25 35 45 60 75 85 120 160 200 300 MFN Statutory Import Tariffs (%)

On the export side and unlike the matter of reduction of import tariffs, there is greater unanimity of views among economists that a good case exists for imposing export duties where the exporting country enjoys some degree of monopoly power in the export market. Even when this is not so, there is a case for collective action by developing countries. This is a fairly credible position to take.23

22 Data up to 1996 are from Arshad Zaman Associates (Pvt.) Ltd. (1997, p. 63), data for 1998 are estimated from Government of Pakistan, Import Policy Order 1997-98, Ministry of Commerce, 1997.

23 John Williamson (1991, p. 74). (Williamson is now the Chief Economist, South Asia Region, World Bank.) writes: “Every economist knows that for a country with monopoly power in world trade, equalization of domestic resource costs would require an ‘optimum tariff,’ but the relevance of this principle for developing countries is denied on the grounds that they do not possess any significant monopoly power. Although that is true for individual countries, it is not true for developing countries collectively (most notably beverages). A common export tax on those commodities, by enabling low-income countries

84 The government has eliminated all export duties, despite the fact that Pakistan enjoys considerable monopoly power in 8 export items (at the Standard International Trade Classification, SITC, 3-digit level) which account for 52.6 per cent of its 1990-91 merchandise exports (see Table 7.3 below). Clearly, there is a case on both revenue and trade policy grounds for reconsidering the government’s policy of eliminating export taxes on these items.

Table 3: Pakistan’s major exports, among 70 leading commodity exports of developing Countries at the SITC revision 2, group (3-digit) level As percentage of 1990-91 SITC (Revision 2) Code World Value Country Developing World

Commodity Group Rank (US$ ‘000) Total Countries Total

263 Cotton 1 560,626 8.17 13.25 6.58

611 Leather 6 244,339 3.56 7.30 2.71

651 Textile yarn 2 1,222,853 17.81 13.57 4.99

653 Woven man-made FIB fabric 7 429,189 6.25 3.93 1.75

655 Knitted or crochetted fabric 9 50,357 0.73 1.39 0.69

658 Textile articles NES 2 632,691 9.22 12.96 6.83

848 Headgear non-textile 8 340,379 4.96 5.07 3.40 clothing

894 Toys, sporting goods, etc. 10 132,111 1.92 1.27 0.58

Source: United Nations, Handbook of International Trade Statistics, 1994, New York: United Nations. See ILO-SAAT/Arshad Zaman Associates (1997).

What has been the overall impact of trade liberalization and tariff reforms on growth and employment? First, there has been a fall in government revenues – even though it has been compensated by a diversification of the structure of government revenues. Second, there has been a rise in import payments due to cheaper imports. Third, a reduction in protection to industry has affected industrial output and employment adversely. On the exports side, there is a case to be made for an unnecessary loss of duties on certain critical items, which are a much needed source of revenue.

9. UPSHOT

Whereas international circumstances of resource flows (a critical correlate of growth phases in Pakistan) have changed over time, macro policies remain an important consideration in the present period of economic reform, precisely because the adoption of these policies have become a correlate of the timing

to redistribute income toward themselves at the expense of the rich, seems to me worthy of encouragement rather than the reverse.”

85 of the resource flows themselves. This is apparent especially in the successive reform that the country has gone through.

First, there is a question to be raised on the appropriateness of some reform policies to Pakistani conditions. This is especially so for those pertaining to the trade regime. Second, there has also been a clear sequencing problem in the implementation of some reform policies that have adversely affected the stability of the macroeconomic environment and, therefore, growth. This adverse impact on the economy has worked largely through the budget itself, from its direct and indirect impact on macroeconomic stability, to the investment climate and then ultimately to growth and employment. With budget reforms politically infeasible, what happened in Pakistan in practice was that, in return for balance of payments support, such “reforms” as could be carried out were carried out. The sequence in which some of these policies were implemented was insensitive to the institutional and structural realities of the country’s political economy.

We can also demarcate the basic differences in the policies of the two sub-periods of reform, the second of which was the more difficult one as by that time Pakistan was arguably weakened in its geo-strategic position due to changed international circumstances.

In the first instance (which began with EFF 1980-83) the major movement was on exchange rates and import liberalization, along with disinvestment, deregulation, and privatization. Clearly, as stated, these were also times when resources flowed into Pakistan easily. It can nevertheless be argued that disinvestment, deregulation and privatization had an initial beneficial effect on the private sector and the industrial growth climate of the time.

Over time, and by the second phase of reforms not only did the direct effect of fiscal contraction in productive public investment lead to a decline in capital formation, but the government’s revenue base persisted in remaining very narrow. Its continued non-revenue-based financing of expenditure in the changed, financially liberated internal capital market environment, led to a very serious crisis of domestic debt in this second reform period. This crisis, apart from starving the private sector for resources, has contributed to the macroeconomic instability facing the country today.

On the monetary policy front, it is again the interaction of the liberated financial sector’s soaring interest rates and government’s propensity to borrow which has been the most explosive.

Exchange rate reforms, due to the structure of exportable items produced in Pakistan, may also not have had the desired effect of substantially boosting Pakistani exports, for which demand in general is relatively price inelastic. On the other hand, the devaluations have put serious pressures on the budget, owing to the price-insensitive ‘necessary’ expenditures embedded in it.

Trade reform has increased government revenues on import duties, but imports have also increased, and exports have not picked up. There is a gradual loss of revenue, associated with the removal of tariffs. The removal of all export duties, on the other hand, may not have been necessary, and has been done in some haste.

With hindsight, it seems that in the absence of prior budget reforms, both tariff reform and financial sector liberalization may have been premature, but in particular it was the financial-sector reforms in the second reform sub-period which are likely to have significantly contributed to the present crisis of growth.

What can be said about the macroeconomic policies and employment? Clearly, some links have been established between the macroeconomic policies adopted and the slowdown of growth in the 1990s. It has

86 also been argued separately in this report that the employment problem can best be addressed with a growth revival strategy. This is the subject of the rest of the rest of the report.

There are a few policy lessons that need to be further explored and constitute areas in which follow-up work is urgent.

• First an attempt must be made to minimize sources of macroeconomic instability that arise from the actions of government itself.

• Second, trade policy has to be reassessed in the light of maximizing gains for the country given its production structure, as opposed to hoping that market signals on their own will transform and diversify the production structure. There is obvious room here for expanding the revenue base for government without adversely impacting output.

• The focus of government expenditure should be on growth-enhancing and demand-generating activities that have a strong re-distributive side.

• Lastly and most critically, a central aim of the government should be to produce and develop a new breed of employment-friendly alternative adjustment programmes. These must examine the feasibility of expansionary macroeconomic policies in Pakistan and be used as working documents for negotiation with donors, carrying explicit improvements on social indicators as part of their short and medium-run goals.

87 ANNEXES

88 CHAPTER ONE

ANNEX 1.1: SOURCES OF DATA ON LABOUR AND HUMAN RESOURCES

Agencies Type of Data

Federal Bureau of Labour force surveys, censuses of manufacturing industries, household income Statistics (FBS) and expenditure surveys, Inquiry on Labour Welfare, Establishments Inquiry, wage rates of unskilled agricultural workers, labour productivity indices in selected industries, wage rate survey of manufacturing establishments, wage rates of construction workers in cities, and many adhoc inquiries, surveys, etc. Population Census Conducted in 1951, 1961, 1972 and 1981. Organization (Decennial) Agriculture Census Org. Agriculture Census: 1962, 1972, 1980, 1990. Mostly data on family (Decennial) Org. (Decennial) : members and use of hired labour family workers. Provincial Bureau of Employment and wages in manufacturing sector, teaching staff, health Statistics (Punjab & Sindh) personnel, number of posts by Basic Scales in the Budget, number of persons migrated abroad. Ministry of Industries Category-wise employment, salaries and wages Annual Report of Public Sector Industries. Management Services Census of Federal Government Civil Servants (Triennial). Division Year Book of Information Annual data on persons employed by Departments and total cost of (Railways) employment. Registrar Pakistan Medical Data on medical and para-medical personnel registered. Council Registrar Pakistan Data on engineers registered with the council. Engineering council Annual Reports of These reports provide information on employment, wages and salaries and Corporate Bodies social security benefits etc. Economic Advisers Wing, Economic Survey and Annual Reports (now discontinued) of Public Sector Ministry of Finance Corporations. Research Institutions Data generated through research, and special surveys and studies on employment, poverty alleviation, human resource development and wages. PC-I of Projects PC-I of Development Projects(Part-C)contains information on labour requirements by major occupation groups.

A cursory glance of the list of agencies and the types of data generated by them would give an impression that labour market information system in Pakistan is well developed and integrated and that most of the information required for policy formulation and research is available. However, this is not the case and the real problem emerges when one attempts to use and analyze the data. Official statistics suffer from serious definitional and measurement problems and also render the inter-temporal comparison difficult. Specialized

89 studies exist but are usually too limited in coverage to be representative. Some comments on the available data are given below:

• Decennial population censuses constitute a major source of information on population and civilian labour force. An inter-temporal comparison of the censuses data can neither be made between censuses themselves nor with other surveys, as surveys are not undertaken in the census year. For example, unlike the 1961 census where total enumeration was used to obtain data on employment, in subsequent censuses data on employment was obtained through sample surveys. The last census was conducted in 1981.

• Agriculture censuses conducted every ten years, provide data on the use of hired labour, family workers, and economically inactive family members. The coverage of data is confined to employment in agriculture and livestock activities. The rural agriculture employment estimated on the basis of agriculture census differ widely from data obtained through other sources in number as well as in concept. The characteristics of employed persons are restricted to the total number of hired labour and family members sub-divided in full time and part time workers.

• Labour force surveys carried out by the Federal Bureau of Statistics since July, 1963, constitute the most commonly used major source of information on labour force and employment. The survey is based on a representative sample. However, the labour force participation and unemployment rates obtained through these surveys do not show any significant changes over the period.

Pakistan has been using the “labour force approach” recommended by the ILO to define economically active, employment and unemployment. The sample size and inadequacy of the concepts used, may have influenced the quality and size of data generated through these surveys. Moreover, the Federal Bureau of Statistics have also been changing the concepts. The 1990-91 round is based on new questionnaire developed in the light of ILO recommendations made at 13th International conference of Labour Statisticians in 1982. A comparative picture of old and new definition of labour force concepts is given in table A1.2.

For example, the share of agriculture, animal husbandry, forestry and fishing in employed work-force jumped from 14.2 per cent in 1987-88 to 46.6 per cent in 1990-91, while that of production and related workers dropped from 58.4 per cent to 26 percent. Similarly the crude participation rate in 1990-91 improved to 27.97 (both sexes) under new concept from 27.19 under the old concept, of female increased from 7.61 to 8.23, while that of male increased to 46.36 from 45.45. Similarly the age specific activity rate derived from new concepts were also higher than derived from old concept. Usually the data has a time lag of 3 years. The summary results of LFS(1994-95) were released in April 1997. The data for mining and manufacturing (both large and small-scale) is reported in combined form and as such can not be cross checked with CMIs data.

The Census of Manufacturing Industries (CMI) conducted annually, provides information on employment and employment cost by major groups of industries in large scale. The data is reported in aggregate form and is usually available three to four years after the collection. Similarly the data collected by other agencies shown in the annex, is restricted to a particular activity or profession and are collected for meeting the internal requirements of the management concerned. Except the LFS, the coverage of statistics collected by other agencies is restricted to aggregate number and wage bill and that too in areas of vested interest. The national requirement is best served by the LFS(s), though LFS also need improvement in concept, size, and timely releases.

90 Comparative statement showing old and new definition of labour force concepts

Contents Old definition New Definition

1. Labour Force It includes all non- The “Labour Force” or “currently Active institutional civilian population population” consists of all persons 10 years of 10 years of age and above who age: and above who are either “employed” or are found employed or “unemployed” during the reference period i.e. one unemployed during the week preceding the date of interview. reference week preceding the date of inter view. 2. Employed It includes all persons: who, The “employed” comprises all persons of 10 years Persons during the reference week, age & above who worked at least one hour during were either working for pay or the reference week in the following profit in cash or kind, including categories: unpaid family helpers (who (i) Paid employment (1) “at work” persons who had worked for any period of during the reference week, performed some time during the reference work for wage or salary, in cash or in kind; week)or had a job but did not (2)”with a job but not at work”: persons work who, having already worked in their present job, were temporarily not at work during reference week due to some reasons such as absence, leave, illness: and strike etc. but had a formal attachment to their job; (ii) Self-employment (1) “at work”: persons who, during the reference week, performed some work for profit or family again, in cash or in kind (2) “with an enterprise but not at work” persons with an enterprise, which may be a business enterprise, a farm or a service undertaking, who temporarily not at work during reference week for some specific reasons such as absence, leave, illness & strike etc. 3. Unemployed Include all persons who, during The “unemployed” comprises all persons of 10 Persons the reference week were either years of age and above who during the reference looking for work, or not week were either: looking for work because of (i) “available for work” i.e. were available illness, or not looking for work for paid employment or self-employment; or believing job not available or (ii) “seeking work “ had taken specific steps in a temporarily or indefinitely laid specified recent period to seek paid off, or waiting to report to new employment or self-employment. It also job or willing to work if job is includes persons who were not available for provided, or apprentice with no work during the reference week due to certain guaranteed job or have some reasons such as illness, will take a job within usual occupation but were a month, temporary laid off and apprentice doing nothing during the and not will to work. reference period.

91 Annex 1.2: Youth employment and child labour

The exploitation of child labour is one of the most odious aspects of global labour markets. In most developing countries, it has not been possible to put an end to child labour (including child prostitution inspired by the tourist industry) despite the fact that almost all these countries have satisfactory legislation in this respect. The abolition of child labour and more generally the protection of children and young persons against work of a character or condition unsuitable to their age have been a serious concern to the government and social activists in Pakistan, especially during the last decade or so.

The Census of Population and Labour Force Surveys are the two main sources of manpower statistics but they do not provide information about child labour. In the absence of information, there are various guesstimates of varying credibility. According to the summary results of 1994-95 LFS, 1.7 million children in the age group of 10-14 years constituted 5.07 per cent of the employed persons. The total population in the age group 10-14 was 16.5 million or 12.9 per cent of total population.

The Child Labour Survey (CLS) conducted in 1996 by the Federal Bureau of Statistics in collaboration with the Ministry of Manpower & Overseas Pakistanis and under the auspices of the International Programme on Elimination of Child Labour (IPEC), revealed that among 40 million children aged 5-14 years, 3.3 million (8.3 per cent) were economically active. Out of the total, 2.4 million (73 per cent) were boys and 0.9 million (27 per cent) were girls. The absolute size of male child labour in the age group of 10-14 years was 2.1 millions while that of female child labour in the same age group was found to be 0.6 million. Child labour in rural areas was about eight times higher than in urban areas, due mainly to a large proportion of unpaid family helpers.

The data also revealed that about 33.2 per cent of the total children employed in the labour market, were literate from the formal system of education. Of the boys workers about 40.3 per cent were pre-matric while only 11.2 per cent of the female child workers were pre-matric. Similarly about 41 per cent of the total child workers in urban areas as against 32 per cent in rural areas were pre-matric.

As regard the major industrial groups, about 67 per cent of the children were engaged in agriculture, followed by 11 per cent in manufacturing. The wholesale and retail trade and services (community, social and personal services) sectors absorbed 9 per cent and 8 per cent of the employed children, respectively.

By occupation, the survey revealed that about 71 per cent of 3.3 million employed children were engaged in unskilled occupations relating to agriculture, fisheries, sales and services. Craft and related trade activities were the next major occupational groups which absorbed about 19 per cent of the working children. Only 0.31 per cent child workers were found working as plant and machine operators. Children as service and sales workers constituted 9.24 per cent of the working community.

Besides the Child Labour Survey and Labour Force Surveys, studies on the pattern of child labour in a few cities have also been conducted. According to these studies most of the children are working in manufacturing, transport and services sectors. In the manufacturing sector they are generally found in food processing, textiles, footwear, printing, publishing, brick-making, carpet-weaving and sports goods.

The Labour Force Surveys show that the age-specific activity rate for the age group 10-14 years is declining as shown below:

92 93 Table 1: Percentage share of children age 10-14 years

1982-83 1987-88 1990-91 1994-95

Total Share in population 18.8 18.7 18.1 19.3 Share in Labour Force 4.0 3.1 2.5 2.2 Participation rate 21.5 16.6 13.6 11.6 Share in employed force 8.4 6.7 5.5 5.1 Males Share in population 10.0 9.9 9.9 10.4 Share in Labour Force 3.3 2.6 1.9 1.7 Participation rate 33.0 26.6 19.3 16.6 Share in employed force 7.6 6.4 5.0 4.4 Females Share in population 8.8 8.8 8.2 8.9 Share in Labour Force 0.7 0.5 0.6 0.5 Participation rate 8.3 5.5 6.8 5.7 Share in employed force 14.1 9.6 9.4 9.7

Source: Labour Force Surveys.

Both the age-specific participation rate and the share of children in total employed force are declining, mainly due to higher enrolment at primary and high schools level. Children constitute 6.2 per cent of work force in rural areas compared to 2.9 per cent in urban areas. The size of child labour revealed by CLS and LFS (1994-95) is compared below:

Table 2: Child labour (million)

Age group (10-14) Total Male Female

CLS (1996) 2.7 2.1 0.6

LFS (1994-95) 1.9 1.5 0.5

Source: CLS and LFS.

94 There is not much detailed work done which explores the relationship between the level of family income and the incidence of child labour, or on other social-economic compulsions that force children to work in hazardous environments. Although it can be argued that part of the problem certainly derives from insufficient enforcement of legislation. The major causes for the existence of child labour include poverty, lack of proper educational facilities, large size of informal economy and the socio-economic background of the parents. As such it is a complex issue which does not yield to simplistic analyses. Employers in the informal sector prefer to hire child workers because there is no law specifying the rights of child workers with respect to minimum wages, maximum work hours and social security benefits. Children also help as unpaid workers in family-owned and managed business.

The existence of child labour is a worrisome aspect of the condition of the poor in Pakistan. All countries have enacted suitable legislation for the protection of children against exploitation, abolition of child labour and against work unsuitable to their age or sex. Articles 11 (3) of the Constitution of the Islamic Republic of Pakistan states that “no child below the age of fourteen years shall be engaged in any factory or mine or any other hazardous employment.” Article 37(a) provides that the state shall “remove illiteracy and provide free and compulsory secondary education within a minimum period.” Article 37(c) says that the state shall “ensure that children and women are not employed in vocations unsuitable to their age or sex.”

The above provisions of Pakistan Constitution clearly show the concern of Pakistan regarding child labour. Pakistan is a signatory to the Declaration of the Rights of the Child adopted by the UN General Assembly in 1959. The legislation enacted and enforced in the country for the protection of children include:

• The Mines Act, 1923. • Factories Act, 1934. • The Employment of Children Act, 1938. • West Pakistan Shops and Establishment Ordinance, 1969.

Most recently the government has set up a National Commission on child welfare in response to UN Convention on the Rights of Children. As a consequence, the Employment of Children Act, 1991 has also been enacted to promote the cause of working children. The government has also enacted the Bonded Labour System (Abolition) Act, 1992, Pakistan, through a Memorandum of Understanding signed in 1994 with the ILO, has joined the International Programme for Elimination of Child Labour (IPEC), which aims at gradual elimination of child labour. A National Steering Committee has been set up to supervise the programme and a child labour unit has been established in the Ministry of Labour and Manpower to monitor the administration of IPEC.

95 ANNEX 1.3: TABLES

Table A1.1: Growth of population and labour force (% per annum)

Growth of Growth of labour force Period population Total Rural Urban 1972-75 3.2 2.9 3.1 2.2 1975-79 3.0 4.4 3.9 6.3 1979-83 3.1 2.4 2.0 3.6 1983-88 3.1 2.1 1.7 3.3 1988-91 3.1 2.1 0.9 5.1 1991-95 3.0 2.6 3.4 0.5 Average(1972-95) 3.1 2.7 2.5 3.5

Source: Population censuses and labour force surveys.

Table A1.2: Census data on population, labour force and employment

Numbers (in ‘000 or %) Growth rate (% p.a.)b

1951- 1961- 1972- 1951 1961a 1972 1981 1961 1972 1981 Population (‘000) 33,817 42,978 a 65,321 84,254 2.4a 3.7a 3.1 Urban 6,019 9,654 16,594 23,841 4.8 4.8 4.4 Under 10 Years of Age .. 2,956 4,942 7,131 .. 4.5 4.4 Over 10 Years of Age .. 6,698 11,652 16,710 .. 4.9 4.4 Rural 27,797 33,324 48,727 60,413 1.8 3.3 2.6 Under 10 Years of Age .. 11,156 17,462 19,274 .. 3.9 1.2 Over 10 Years of Age .. 22,168 31,265 41,139 .. 3 3.3 Labour Force (‘000) 10,370 13,880 19,520 25,780 3 3 3.3 Urban .. 2,872 5,128 7,254 .. 5.1 4.2 Rural .. 11,008 14,392 18,526 .. 2.3 3 Employment (‘000) .. 13,640 18,550 24,700 .. 2.7 3.4 Urban .. 2,790 4,814 7,009 .. 4.8 4.5 Rural .. 10,850 13,736 17,691 .. 2.1 3 Unemployment Rate (%) .. 1.73 4.97 4.19 Urban .. 3.06 6.12 3.37 Rural .. 1.63 4.56 3.37

Notes: a Official figures for 1961 are adjusted by 7.5 per cent, for under enumeration. This gives a 1961 population of 46.2 million, and hence inter-censal growth rates of 3.21 per cent for 1951-61 and 3.02 per cent for 1961-72. b In calculating average annual population growth rates, the month in which the census was carried out is taken into account (February 1951, March 1961, October 1972, and March 1981). c Civilian labour force only.

96 Table A1.3: Population, labour force and employment, 1990-97

Fiscal Years Ending June 1990 1991 1992 1993 1994 1995 1996 1997 30:

Population (‘000) 110.4 113.8 117.3 120.8 124.5 128 131.6 135.3

Urban 32.7 35.8 37.0 36.9 36.2 36.9 37.9 39.0

Under 10 Years of Age 10.1 11.6 12.6 11.5 11.0 10.8 11.3 11.5

Over 10 Years of Age 22.6 24.2 24.4 25.4 25.2 26.1 26.8 27.5

Rural 77.7 77.9 80.4 83.9 88.3 91.1 93.7 96.3

Under 10 Years of Age 26.7 28.4 27.9 29.9 30.9 32.0 32.9 63.8

Over 10 Years of Age 51.0 49.5 52.4 54.1 57.4 59.2 60.8 62.5

Labour Force (‘000) 31.8 31.8 33.0 33.7 34.7 35.2 36.1 37.2

Urban 8.6 9.5 9.7 9.5 9.3 9.6 9.9 10.2

Rural 23.2 22.4 23.3 24.1 25.4 25.5 26.2 27.0

Employment (‘000) 30.8 29.8 31.0 32.1 33.0 33.3 34.2 35.2

Urban 8.2 8.7 9.0 9.0 8.7 9.0 9.2 9.5

Rural 22.6 21.2 22.0 23.1 24.3 24.3 25.0 25.7

Unemployment Rate (%) 3.1 6.3 5.9 4.7 4.8 5.4 5.4 5.4

Urban 4.6 8.2 7.0 5.9 6.5 6.9 6.9 6.9

Rural 2.6 5.5 5.4 4.3 4.2 4.8 4.8 4.8

Source: Labour Force Surveys, cited in Government of Pakistan (1997, Statistical Appendix, pp. 19-20). Figures for 1996 and 1997 are estimates by the Economic Adviser’s Wing, Ministry of Finance, based on the 1994-95 labour force survey. (See Annex 4, Table 1.3.)

97 Table A1.4: Crude labour force participation rates

Total labour force Rural labour force Urban labour force Year Total Male Female Total Male Female Total Male Female

1971-72 29.9 51.9 5.3 31.0 53.3 5.6 26.5 53.2 2.6

1974-75 29.5 52.1 4.3 30.8 52.1 5.1 26.5 48.0 2.4

1978-79 31.0 52.3 7.9 32.6 53.1 9.7 27.1 47.3 3.7

1982-83 30.2 51.5 7.2 31.8 53.1 8.9 26.3 47.7 3

1984-85 29.6 51.7 5.8 30.7 52.7 7.1 27.1 49.4 2.8

1985-86 28.7 50.0 6.0 29.9 51.2 7.5 25.8 47.1 2.4

1986-87 29.4 49.5 7.9 30.8 50.7 9.8 26.3 47.0 3.5

1987-88 28.8 49.4 6.8 29.9 50.2 8.2 26.3 47.5 3.4

1990-91 28 46.4 8.2 28.7 46.9 9.4 26.4 45.1 5.8

1991-92 28.1 46.1 9.2 29.0 46.5 10.7 26.1 45.1 5.5

1992-93 27.9 45.9 8.6 28.8 46.3 10.1 25.8 45.0 5.0

1993-94 27.9 45.7 8.9 28.7 45.9 10.5 25.8 45.4 4.9

1994-95 27.5 45.9 7.6 28.0 46.0 8.7 26.1 45.7 4.9

Source: Labour Force Surveys.

Table A1.5: Age specific participation rates

Age group 1982-83 1987-88 1994-95

36446 21.5 16.6 11.5

15-19 40.3 36.4 32.3

20-24 50.8 48.3 47.9

25 & above 52.0 53.0 52.8

Source: Labour Force Surveys.

98 Table A1.6: Out and return migration for different years

Emigration Per Year Return Per Year Net Out Per Year Period BOI (000) Migration (000) Migration (000)

1977-81 659715 132 98176 19 561539 112

1982-87 592279 98 642448 107 -50169 -9 98642 448107 50169-9

1988-92 642494 128 450000 90 192494 60

1993-95 394633 131 213008 71 181625 60

Sources: ILO-SAAT/ M. Irfan , 1997. 1 1977-81 (Iqbal & Khan) 1981 2 1982-87 and 1993-95 (Bureau of Emigration) based on Airport Surveys. 3 1988-92 (M. Irfan’s ,estimation on the basis of the estimated flows of preceding and the following periods.

Table A1.7: Persons included and excluded from the labour force, 1994-95 (million)

Total Male Female

Population 128.3 66.3 61.8

Age 10 years and above 85.4 44.2 41.2

Labour Force 35.2 30.5 4.7

Fully Employed 29.3 27 2.4

Underemployed 4 2.3 1.7

Unemployed 1.9 1.2 0.7

Outside Labour Force 50.2 13.7 36.5

Students 17.4 11.0 6.4

Others 32.8 2.7 30.1

Source: Labour Force Survey, 1994-95.

99 Table A1.8: Composition of labour force by sex and level of education

1990-91 1994-95 Growth (% p.a.)

Total M F Total M F Total M F

Total 31.8 27.30 4.5 35.20 30.5 4.7 2.6 2.8 1.1

Illiterate 19.11 15.43 3.68 19.86 16.10 3.76 1.0 1.1 0.5

Literate 12.69 11.87 0.82 15.34 14.40 0.94 4.8 4.9 3.5

Literate 100 100 100 100 100 100 4.8 4.9 3.6

No formal education 3.95 3.60 9.01 2.89 2.67 6.31 -3.0 -2.6 -5.2

Pre-Matriculate 60.68 61.70 45.95 57.37 58.60 37.84 3.4 3.6 -1.1

Matriculate 20.91 20.61 24.32 22.59 22.36 25.23 6.9 7.1 4.7

Intermediate 7.20 7.08 9.01 8.51 8.24 12.61 9.3 9.0 12.6

Engineering Degree 1.05 1.06 0.90 1.06 1.01 1.80 5.2 3.6 24.8

Medical Degree 0.52 0.43 0.90 0.39 0.36 0.90 -2.4 -2.7 0

Agriculture Degree 0.06 0.06 - 0.11 0.12 0.00 20.7 20.7 0

Other Degree 4.30 4.10 7.21 5.17 4.80 10.81 9.7 9.1 14.7

Post-Graduate 1.39 1.30 2.70 1.89 1.78 3.60 13.3 13.5 11.5

Source: Based on Labour Force Surveys.

100 Table A1.9: Percentage Distribution of Employed by Sex and Level of Literacy

1987-88 1990-91 1994-95

Total M F Total M F Total M F

Total 100 88.35 11.65 100 87.40 12.60 100 87.85 12.15

Illiterate 64.67 54.51 10.16 60.40 49.90 10.50 56.80 46.98 9.82

Literate 35.3 33.8 1.49 39.6 37.5 2.1 43.2 40.9 2.33

No Formal education - - - 1.54 1.36 0.18 1.28 1.11 0.17

Formal education 35.33 33.84 1.49 38.06 36.13 1.92 31.92 39.76 2.16

K.G Nursery 0.06 0.06 - 0.41 0.39 0.02 0.18 0.17 0.01

K.G but below Prim. 3.49 3.36 0.10 3.54 3.38 0.16 3.01 2.92 0.10

Primary but below 12.26 11.81 0.46 12.81 12.29 0.52 13.30 12.72 0.58 middle

Middle but below 7.39 7.24 0.15 7.50 7.24 0.26 8.50 8.31 0.18 Matric

Matric but below inter 7.14 6.80 0.34 8.09 7.60 0.49 9.60 9.03 0.57

Inter but below degree 2.20 2.06 0.14 2.81 2.63 0.18 3.63 3.35 0.28

Degree in Engineering - - - 0.41 0.40 0.02 0.43 0.39 0.04

Degree in Medicine 1.84 1.64 0.20 0.20 0.17 0.03 0.17 0.15 0.02

Degree in Agriculture - - - 0.03 0.03 - 0.04 0.04 -

Degree in other subj. 0.80 0.69 0.11 1.70 1.53 0.17 2.25 1.96 0.29

Post Graduate 0.19 0.18 0.01 0.56 0.48 0.08 0.81 0.71 0.09

Source: Labour Force Surveys.

101 Table A1.10: Rural-urban share of self-employed (%)

1982-83 1987-88 1994-95 Average

Total 40.3 47.9 42.3 43.6 Rural 41.7 51 45.2 46.1

Urban 36.1 39.5 34.3 36.6

Table A1.11: Distribution of self-employed by sectors

1982-83 1987-88 Sectors T R U T R U Agriculture 54.3 67.5 7.6 53.6 66.6 7.2 Manufacturing 13.6 11.1 22.1 10.9 8.7 19.1 Trade 19.6 12.4 45.1 16.8 9.8 41.8 Transport 3.3 2.2 6.8 8.3 3.4 8.2 Services 6.6 4.8 12.8 6.0 4.1 12.8 Others 2.6 2.0 5.6 4.4 7.4 10.9 Total 100.0 100.0 100.0 100.0 100.0 100

Source: Labour Force Surveys.

Table A1.12: Share of full-time (over 35 hours) and educated workers among the self-employed, 1994-95

Share of full-time workers Share of educated workers (%) (%) Middle Matric but Degree and Pakistan Rural Urban and below below Degree above National Total 87.8 86.0 92.9 62.6 28.5 8.9 Male 92 90.8 95.0 Female 57.7 55.8 67.5 Self-employed Total 91.9 90.9 95.1 74.4 22.1 3.5 Male 93.2 92.4 95.9 Female 59.4 51.1 71.0

Source: Labour Force Surveys.

102 Table A1.13: Underemployment among the employed (%)

1982-83 1987-88 1993-94 Status Total Rural Urban Total Rural Urban Total Rural Urban

Employer 0.2 0.3 0 0.2 0.2 0.1 0.1 0.1 0.2

Self-Employed 3.8 4.2 2.8 3.5 4.1 1.9 3.4 4.1 1.7

Unpaid Family 7.4 9.2 1.7 6.1 7.9 1.2 5.7 7.2 1.3 Helpers

Employees 2.6 2.6 2.5 1.3 1.2 1.6 3.0 2.6 3.9

Total 14 16.3 7 11.1 13.4 4.8 12.2 14 7.1

Source: Labour Force Surveys

Table A1.14: Underemployment rates in rural and urban areas

1982-83 1987-88 1993-94

T R U T R U T R U

Labour Force (mill.) 26.9 20.0 6.9 29.9 21.9 8.1 35.2 25.6 9.6

Employed (mill.) 25.8 19.3 6.5 29.0 21.3 7.7 33.3 24.4 8.9

Underemployed 3.6 3.1 0.5 3.2 2.9 0.4 4.1 3.4 0.6

Underemployment Rate 13.4 15.5 7.2 10.7 13.2 4.9 11.6 13.3 6.3

Source: Calculated from Labour Force Survey Data.

103 Table A1.15: Number of unemployed and unemployment rates

Unemployed labour force (million) Unemployment rate Year Total Rural Urban Total Rural Urban 1986-87 0.90 0.55 0.35 3.05 2.50 4.51

1987-88 0.94 0.57 0.37 3.13 2.60 4.58 1988-89 0.97 0.59 0.38 3.13 2.60 4.58

1989-90 1.00 0.60 0.40 3.13 2.60 4.58

1990-91 2.00 1.23 0.77 6.28 5.48 8.19

1991-92 1.93 1.26 0.67 5.85 5.40 6.97

1992-93 1.60 1.03 0.57 4.74 4.29 5.88

1993-94 1.68 1.04 0.64 4.84 4.22 6.31 1994-95(E) 1.73 1.06 0.68 4.84 4.22 6.51

Source: Federal Bureau of Statistics.

Table A1.16: Duration of unemployment

Duration of unemployment Nature of Year Less than 1 6 months and experience Total 1-6 months month over 1984-85 Total 100.0 46.4 18.5 35.1 w.past.exp. 41.9 14.7 11.6 15.6 without p.exp. 58.1 31.7 6.9 19.5 1985-86 Total 100.0 23.0 37.2 39.8 w.p.exp. 41.4 16.4 12.6 12.5 without p.exp. 58.6 6.7 24.6 27.3 1986-87 Total 100.0 28.7 35.9 35.5 w.p.exp. 43.6 15.0 12.7 15.9 without p.exp. 56.4 13.6 23.1 19.6 1987-88 Total 100.0 22.7 36.9 40.4 w.p.exp. 44.3 14.9 16.9 12.5 without p.exp. 55.7 7.7 20.1 28.0

Source: LFS.FBS Economic Survey of Pakistan 1995-96 Note: w.p.exp= with past experience; without p.exp.= without past experience.

104 Table A1.17: Percentage distribution of educated unemployed

1982-83 1987-88 1993-94

Total M F Total M F Total M F

Total 100 - - 100 96.7 3.3 100 68.1 31.9

Illiterate 57.2 - - 51.0 48.9 2.1 51.2 27.1 24.2

Literate 42.8 - - 49.0 47.8 1.3 48.8 41.0 7.7

Pre-matric 27.9 - - 29.6 29.3 0.3 24.1 21.3 2.7

Matric 10.5 - - 12.6 12.1 0.5 14.2 11.5 2.7

Inter 2.4 - - 4.2 4.1 0 4.6 3.5 1.1

Degree. Of which 1.2 - - 2.1 1.8 0.4 3.4 3.0 0.4

Professional ------0.6 0.6 0.1

Post Graduates 0.5 - - 0.5 0.5 0.1 0.9 0.7 0.2

No formal education ------1.6 1.0 0.6

Source: Labour Force Surveys.

105 CHAPTER TWO

ANNEX 2: TABLES

Table A2.1a: Growth rates of population labour force and employed labour force in Pakistan

Year Growth (Pop) Growth (LF) Growth (Emp)

1973 3.01 1.28 0.98 1974 4.03 3.54 3.72 1975 3.05 2.60 2.70 1976 3.06 2.58 2.73 1977 3.06 4.36 3.84 1978 3.06 4.36 3.84 1979 3.05 4.36 3.84 1980 3.05 4.39 3.92 1981 3.07 2.37 2.24 1982 3.05 2.31 2.28 1983 3.10 2.42 2.31 1984 3.10 2.44 2.30 1985 3.10 2.01 2.13 1986 3.10 2.00 2.12 1987 3.10 0.18 0.22 1988 3.10 5.53 6.22 1989 3.10 1.11 1.01 1990 3.10 3.14 3.14 1991 3.10 3.08 3.08 1992 3.10 0.03 -3.21 1993 3.10 3.58 4.06 1994 3.00 2.12 3.35 1995 3.00 3.03 2.90 1996 2.86 1.33 0.76 1997 2.83 2.82 2.83 1998 2.77 2.79 2.78

106 Table A2.1b: Levels of population, labour force and employed labour force in Pakistan

Employed labour Year Population Labour force force

1971 61.49 18.70 18.37 1972 63.34 18.94 18.55 1973 65.89 19.61 19.24 1974 67.90 20.12 19.76 1975 69.98 20.64 20.30 1976 72.12 21.54 21.08 1977 74.33 22.48 21.89 1978 76.60 23.46 22.73 1979 78.94 24.49 23.62 1980 81.36 25.07 24.15 1981 83.84 25.65 24.70 1982 86.44 26.27 25.27 1983 89.12 26.91 25.85 1984 91.88 27.45 26.40 1985 94.73 28.00 26.96 1986 97.67 28.05 27.02 1987 100.70 29.60 28.70 1988 103.82 29.93 28.99 1989 107.04 30.87 29.90 1990 110.36 31.82 30.82 1991 113.78 31.83 29.83 1992 117.31 32.97 31.04 1993 120.83 33.67 32.08 1994 124.45 34.69 33.01 1995 128.01 35.15 33.26 1996 131.63 36.14 34.20 1997 135.28 37.15 35.15

107 14.70 14.69 14.54 15.42 15.30 15.07 14.61 14.90 15.03 15.05 15.06 15.36 15.60 15.69 16.12 16.18 16.20 16.59 16.66 16.49 16.45 16.39 16.50 16.23 16.14 16.38 16.32 Trade 8.55 8.56 9.31 9.07 9.12 8.93 8.84 9.36 9.58 9.53 9.65 9.72 9.83 9.34 9.51 9.58 9.82 9.67 9.86 10.23 10.16 10.02 10.16 10.19 10.24 10.16 10.05 Transport 1.67 1.72 1.87 2.05 1.76 1.77 1.99 2.01 2.09 2.18 2.39 2.26 2.26 2.46 2.33 2.44 2.54 2.78 3.00 3.29 3.46 3.50 3.64 3.59 3.99 3.82 4.14 and gas Electicity

3.57 2.92 3.16 3.25 3.69 4.26 4.11 4.13 4.13 4.28 4.67 4.59 4.18 4.06 4.09 4.10 4.36 4.30 4.19 4.13 4.14 4.07 4.21 4.10 3.93 3.88 3.86 Construction 9.99 9.71 9.97 11.15 10.85 11.09 10.94 10.37 10.19 10.53 11.08 11.91 11.89 12.32 12.23 12.34 12.50 12.98 12.69 12.70 12.69 12.71 12.94 12.89 12.45 12.21 11.68 large scale Maunfacturing 14.16 14.01 14.26 14.12 13.66 13.42 13.28 13.61 13.96 14.37 15.11 15.98 16.02 16.62 16.52 16.71 16.98 17.55 17.40 17.59 17.71 17.76 18.30 18.44 18.17 18.14 17.92 Manufacturing 0.39 0.39 0.37 0.38 0.37 0.35 0.40 0.38 0.37 0.39 0.42 0.44 0.41 0.40 0.42 0.48 0.49 0.53 0.51 0.54 0.56 0.53 0.54 0.54 0.49 0.50 0.50 Mining 14.55 14.40 14.63 14.50 14.03 13.76 13.68 13.99 14.34 14.76 15.53 16.42 16.42 17.02 16.94 17.19 17.47 18.07 17.92 18.13 18.27 18.29 18.83 18.98 18.66 18.64 18.41 Mining and manufacturing 39.04 39.48 37.58 36.44 34.33 34.74 34.63 33.03 32.26 32.02 30.83 30.01 29.34 26.86 27.41 27.30 26.64 25.71 26.22 25.83 25.68 26.11 24.18 24.34 24.65 24.81 24.24 GDP ( at factor cost) sectoral shares Agriculture 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 Year Table A2.2:

108 Table A2.3: Distribution of the employed by sector

Manufacturing Construction Electricity Period Agriculture Transport Trade Others and mining distribution and gas

1969-70 57.03 15.57 3.93 0.41 4.73 9.89 8.44 1970-71 57.58 15.25 3.60 0.25 4.88 10.89 7.56 1971-72 57.32 12.92 3.41 0.37 4.84 9.89 11.25 1972-73 56.47 13.20 3.66 0.41 4.85 10.27 11.15 1973-74 55.62 13.49 3.92 0.45 4.86 10.67 10.99 1974-75 54.80 13.78 4.20 0.49 4.87 11.09 10.77 1975-76 54.25 13.99 4.37 0.54 4.83 11.09 10.92 1976-77 53.71 14.21 4.55 0.60 4.80 11.09 11.04 1977-78 53.71 14.44 4.73 0.67 4.76 11.08 11.15 1978-79 52.65 14.66 4.92 0.74 4.73 11.08 11.22 1979-80 52.67 14.37 4.89 0.82 4.69 11.29 11.26 1980-81 52.69 14.09 4.86 0.91 4.66 11.50 11.28 1981-82 52.71 13.81 4.83 1.02 4.62 11.72 11.29 1982-83 52.73 13.54 4.80 1.13 4.59 11.94 11.27 1983-84 51.63 13.69 5.18 0.88 4.89 11.74 11.99 1984-85 50.56 13.84 5.60 0.69 5.20 11.54 12.57 1985-86 54.01 13.40 5.24 0.52 4.42 11.40 11.01 1986-87 49.24 14.23 6.01 0.73 5.25 12.05 12.50 1987-88 51.15 12.84 6.38 0.59 4.89 11.93 12.22 1988-89 51.15 12.84 6.38 0.59 4.89 11.93 12.22 1989-90 51.15 12.84 6.38 0.59 4.89 11.93 12.22 1990-91 47.45 12.38 6.62 0.83 5.24 13.24 15.22 1991-92 48.27 12.53 6.33 0.79 5.51 13.10 13.48 1992-93 47.54 10.89 6.94 0.85 5.52 13.31 14.95 1993-94 50.04 10.12 6.50 0.87 4.95 12.78 15.56

Source: Labour Force Surveys.

109 Table A2.4: Decomposing output growth, productivity and employment effects

Nto (DP) Pto (DN) DP (DN) DY DY DY Productivity Employment Multiple Effect Effect Effect

1969/70 – 1980/81 Agriculture 0.063 0.918 0.018 Manufacturing 0.460 0.419 0.120 Construction 0.178 0.695 0.127 Transport 0.416 0.431 0.153 Trade 0.045 0.927 0.028 Other 0.145 0.731 0.124 TOTAL 0.292 0.615 0.118

1980/81-1990/92 Agriculture 0.664 0.236 0.100 Manufacturing 0.816 0.089 0.094 Construction 0.041 0.932 0.026 Transport 0.334 0.501 0.163 Trade 0.425 0.390 0.184 Other 0.339 0.491 0.170 TOTAL 0.578 0.273 0.148

1991/92 – 1994/95 Agriculture 0.361 0.623 0.0140 Manufacturing 1.868 -0.680 -0.188 Construction -1.250 2.522 -0.272 Transport 1.090 -0.077 -0.013 Trade -0.599 1.710 -0.110 Other -0.089 1.107 -0.018 TOTAL 0.400 0.571 0.028

Source: National Income Accounts and Labour Force Survey (various years). Note: P = Productivity; N = Employment; Y = Output; D = Change; to = original time period.

110 Table A2.5: Employment, output and productivity growth rates (OLS estimates)

1970s 1980s 1990s

Productivity Total (GDP) 1.50 3.90 1.80 Agriculture -0.10 2.00 1.70 Manufacturing 1.30 7.00 4.60 Construction 0.90 -0.30 -2.20 Transport 2.50 3.40 3.20 Trade 0.50 4.70 -0.90 Employment Total 3.20 2.40 2.40 Agriculture 2.10 1.90 1.60 Manufacturing 3.00 1.40 -0.40 Construction 7.00 6.00 4.90 Electricity and gas 12.80 -3.90 2.40 Transport 3.00 3.20 0.50 Trade 4.40 2.80 5.00 Others 6.40 3.50 4.30 Output Total (GDP) 4.70 6.30 4.20 Agriculture 2.00 3.90 3.30 Manufacturing 4.30 8.40 4.20 Construction 7.90 5.70 2.70 Electricity and gas 8.50 9.90 7.40 Transport 5.50 6.60 3.70 Trade 4.90 7.50 4.10 Others 6.40 3.50 4.30 Elasticity Total (GDP) 0.68 0.38 0.57 Agriculture 1.05 0.49 0.48 Manufacturing 0.70 0.17 -0.10 Construction 0.89 1.05 1.81 Electricity and gas 1.51 -0.39 0.32 Transport 0.55 0.48 0.14 Trade 0.90 0.37 1.22

Note: The estimates are based on Ordinary Least Squares Regression Coefficients.

111 Table A2.6: Corelation coefficents productivity and employment growth

Sectors cor (1970-96) cor (1970s) cor (1980s) cor (1990s) All -0.71 -0.25 -0.81 -0.43 Agriculture -0.72 -0.13 -0.49 -0.66 Manufacturing and mining -0.89 -0.86 -0.93 -0.96 Construction -0.41 0.42 -0.72 -0.95 Electricity and gas -0.91 -0.61 -0.95 -0.87 Transport -0.84 0.041 -0.93 -0.83 Trade -0.80 -0.67 -0.86 -0.92

Table A2.7:

(i) Correlation matrix between sectoral employment growth rates 1971-97

Electricity All Agriculture Manufacturing Construction Transport Trade and gas All 1 Agriculture 0.42 1 Manufacturing 0.62 -0.07 1 Construction 0.49 -0.37 0.56 1 Electricity 0.14 -0.46 0.04 0.12 1 and gas Transport 0.50 -0.49 0.59 0.69 0.46 1 Trade 0.17 -0.53 0.61 0.63 0.27 0.50 1

(ii) Correlation matrix between sectoral productivity growth rates 1971-97

Electricity All Agriculture Manufacturing Construction Transport Trade and gas All 1 Agriculture 0.56 1 Manufacturing 0.45 -0.08 1 Construction 0.35 -0.04 0.06 1 Electricity and 0.28 -0.20 0.16 0.04 1 gas Transport 0.44 -0.33 0.56 0.43 0.43 1 Trade 0.39 -0.13 0.56 0.07 0.32 0.41 1

112 (iii) Correlation matrix between sectoral output growth rates 1971-97

Electricity All Agriculture Manufacturing Construction Transport Trade and gas

All 1 Agriculture 0.58 1 Manufacturing 0.76 0.17 1 Construction 0.34 -0.04 0.25 1 Electricity 0.15 0.04 0.26 -0.10 1 and gas Transport 0.54 -0.13 0.62 0.28 0.14 1 Trade 0.88 0.40 0.63 0.22 0.12 0.39 1

Table A2.8: Poverty GAP (P1) & Foster-Greer-Thorbecke index (P2) 1984-85, 1987-88,1990-91

Gazdar et.al (1994) Basket of Basic Needs All Pakistan (P1) (P2)

1984-85 0.111 0.038

1987-88 0.077 0.023

1990-91 0.071 0.022

Source: Gazdar, et.al. (1994) and Malik, S. (1996).

113 Table A2.9: Growth rates of output productivity and employment

Output Productivity Employment Year growth growth growth 1971 - - - 1972 2.3 1.3 1.0 1973 6.8 3.0 3.7 1974 7.5 4.6 2.7 1975 3.9 1.1 2.7 1976 3.3 -0.6 3.8 1977 2.8 -1.0 3.8 1978 7.8 3.8 3.8 1979 5.6 1.6 3.9 1980 7.4 5.0 2.2 1981 6.0 3.7 2.3 1982 7.6 5.1 2.3 1983 6.8 4.4 2.3 1984 4.0 1.8 2.1 1985 8.7 6.5 2.1 1986 6.4 6.1 0.2 1987 5.8 -0.4 6.2 1988 6.4 5.4 1.0 1989 4.8 1.6 3.1 1990 4.6 1.5 3.1 1991 5.6 9.1 -3.2 1992 7.7 3.5 4.1 1993 2.3 -1.0 3.4 1994 4.5 1.6 2.9 1995 5.2 4.4 0.8 1996 4.6 1.7 2.8 1997 3.1 0.3 2.8

114 Table A2. 10: Real Wage Trends in Selected Sectors 1971 to 1996 (Index base year 1984)

Manufacturing Constructionc1 Agriculture Year Small rural casual Large Rabi Kharif scale and Labour Carpenters Masons workersdl scaleal householdbl

1971 58 ------1972 ------1973 ------1974 -- -- 84 85 91 ------1975 -- -- 83 86 90 ------1976 58 161 91 92 103 ------1977 68 -- 94 100 108 ------1978 72 -- 98 98 105 ------1979 78 -- 115 114 111 ------1980 81 -- 111 113 110 ------1981 81 -- 116 113 110 ------1982 83 -- 104 104 104 ------1983 95 -- 103 104 105 ------1984 100 100 100 100 100 100 100 100 1985 104 -- 97 97 110 102 104 102 1986 113 -- 100 98 111 107 108 104 1987 123 -- 103 101 114 110 118 105 1988 132 138 107 104 116 110 109 114 1989 -- -- 103 103 116 108 117 115 1990 -- -- 104 103 118 111 129 127 1991 138 -- 101 100 121 110 118 118 1992 -- -- 104 98 117 116 118 116 1993 -- -- 103 100 124 105 107 112 1994 -- -- 99 97 119 121 116 111 1995 -- -- 99 96 121 113 -- -- 1996 -- -- 96 96 127 114 -- --

Note: Money wages deflated by the consumer price index. al – Economic survey 1986-87, 1990-91, 1996-97. bl – Census of Small & Household Manufacturing Industries 1976-77, 1983-84, 1988. cl – Economic survey 1986-87, 1996-97, average of Karachi, Lahore, Quetta, Peshawar wages. Data pertains to month of November each year. dl – Monthly Statistical Bullein Jan. 1997, Jan.1992 & Nov. 1988.

115 CHAPTER THREE

ANNEX 3: TABLES

Table A3.1: Selected indicators of employment and output for the economy and agriculture

GDP Force Year GDP POP L F EMP PRDY (AG) (AG) Emp (AG) 1971 14.80 5.80 61.49 18.70 18.37 10.58 0.54 1972 15.1 6.0 63.34 18.94 18.55 10.63 0.57 1973 16.1 6.1 65.89 19.61 19.24 10.82 0.57 1974 17.3 6.3 67.90 20.12 19.76 10.99 0.58 1975 18.0 6.2 69.98 20.64 20.30 11.12 0.55 1976 18.6 6.5 72.12 21.54 21.08 11.44 0.57 1977 19.1 6.6 74.33 22.48 21.89 11.76 0.57 1978 20.6 6.8 76.60 23.46 22.73 12.09 0.57 1979 21.8 7.0 78.94 24.49 23.62 12.43 0.57 1980 23.4 7.5 81.36 25.07 24.15 12.72 0.59 1981 24.8 7.6 83.84 25.65 24.70 13.01 0.59 1982 26.7 8.0 86.44 26.27 25.27 13.32 0.60 1983 28.5 8.4 89.12 26.91 25.85 13.63 0.61 1984 29.6 8.0 91.88 27.45 26.40 13.63 0.59 1985 32.2 8.8 94.73 28.00 26.96 13.63 0.64 1986 34.2 9.3 97.67 28.05 27.02 14.60 0.63 1987 36.2 9.6 100.70 29.60 28.70 14.13 0.69 1988 38.5 9.9 103.82 29.93 28.99 14.83 0.67 1989 40.4 10.6 107.04 30.87 29.90 15.29 0.70 1990 42.20 10.9 110.36 31.82 30.82 15.77 0.70 1991 44.60 11.5 113.78 31.83 29.83 14.15 0.80 1992 48.00 12.5 117.31 32.97 31.04 14.98 0.83 1993 49.10 11.9 120.83 33.67 32.08 15.25 0.78 1994 51.40 12.5 124.45 34.69 33.01 16.52 0.75 1995 54.1 13.3 128.01 35.15 33.26 15.56 0.85 1996 56.5 14.0 131.63 36.14 34.20 16.00 0.88 1997 58.3 14.1 135.28 37.15 35.15 16.45 0.85

Note: GDP = Gross domestic product; VA = Value added; POP = Population; LF = Labour force; EMP = Employment; PRDY = Productivity

Source: Labour Force Survey and Natural Income Accounts, various years.

116 Table A3.2: Selected growth indicators of employment and output for the economy and agriculture

YEAR VA EMP EMP(AG)

1973 1.67 3.72 1.79 1974 4.18 2.70 1.57 1975 - 2.12 2.73 1.18 1976 4.47 3.84 2.88 1977 2.53 3.84 2.80 1978 2.82 3.84 2.81 1979 3.10 3.92 2.81 1980 6.61 2.24 2.33 1981 2.06 2.28 2.28 1982 4.72 2.31 2.38 1983 4.40 2.30 2.33 1984 -4.82 2.13 0.00 1985 10.92 2.12 0.00 1986 5.95 0.22 7.12 1987 3.25 6.22 -3.22 1988 2.73 1.01 4.95 1989 6.87 3.14 3.10 1990 3.03 3.08 3.14 1991 4.96 - 3.21 - 10.27 1992 9.50 4.06 5.87 1993 - 5.29 3.35 1.80 1994 5.23 2.90 8.33 1995 6.57 0.76 - 5.81 1996 5.27 2.83 2.83

VA = Value added; EMP = Employment Source: Labour Force Survey and Natural Income Accounts, various years.

117 Table A3.3a: Output levels and trends in agriculture from 1979-80 to 1994-95

Description 1979-80 1984-85 1989-90 1994-95 A. Value added at constant factor cost of 1959-60 (Rs. billion) for: (vii) Agricultural sector 15.83 18.60 23.26 28.21 (viii) Crop sector 11.20 12.75 15.29 17.74 (ix) Livestock sector 4.42 5.85 7.51 9.41 B. Output (mil tonnes) of: • Wheat 10.59 11.70 14.72 17.00 • Cotton 0.73 1.01 1.46 1.48 • Sugarcane 27.50 32.14 35.49 47.12 C. Annual growth rates (% ) over preceeding five years 1. Agricultural sector - 3.28 4.57 3.93 2. Crop sector - 2.63 3.70 3.02 3. Livestock sector - 4.77 6.12 5.70 4. Wheat output - 2.01 4.12 3.49 5. Cotton output - 6.71 7.65 0.27 6. Sugarcane output - 3.12 2.00 12.89 7. Rice output - 1.19 -0.61 1.39

Source: Calculation based on data in Pakistan (1997).

Table A3.3b: Use of Agricultural Inputs for Cultivated Acre 1969-70,1979-80, 1984-85, 1989-90 and 1994-95

Acreage input (kgs) per cultivated acre of:

Improved Number of Year Fertilizer nutrients seed Pesticides tractors per distributed 100 Acres

(1) (2) (3) (4) (5) 1969-70 16.00 0.83 0.10 0.17 - 1979-80 51.62 3.01 0.22 0.48 - 1984-85 - 60.81 4.19 0.77 0.76 1989-90 - 90.26 2.90 0.50 - 1994-95 101.53 3.57 1.01 1.17 -

Source: Columns 2-4 from Pakistan (1996 and 1997) and Col. 5 from United Consultants (Private) Limited (1989) and Agricultural Census Organization (1997) Pakistan 1994 Census of Agricultural Machinery. Lahore: Statistics Division, Government of Pakistan

118 Table A3.4: Growth rates of employment in agriculture from alternative sources at mid and end points of the decades since 1969-70

Annual growth rate during: Source and description 1969-70 to 1979-80 1979-80 to 1989-90 1989-90 to 1994-95 A. Agricultural Census Data 1. Family labour 3.14 0.59 - 2. Permanent hired labour -3.44 2.33 - 3. Total permanent labour 2.94 0.62 - B. Labour Force Surveys* 1. Labour force employed in 2.30 2.17 2.40 agriculture (2.96) C. Labour input changes due to: 1. Cropping pattern change 0.75 0.34 0.74 2. Crop land increase 1.70 1.11 0.62 3. Per acre labour input increase 0.13 0.75 0.19 4. Total 2.58 2.20 1.55 (2.61)

Note: Figures in parentheses refer to growth rates during 1984-85 to 1989-90. * Growth rates based on labour force survey data reported in Pakistan (1997) Table 1.10. Source: For A. Pakistan (1975, 1983 and 1993, for B, C-1 and C-2 Pakistan 1984 and 1997) and for C-3 PERI (n.d.).

Table A3.5: Farms using casual labour and number of permanent hired workers as percentage of total permanent labour working in agriculture during 1972, 1980 and 1990

Number (‘000) during the agricultural Description census of: 1972 1980 1990 A. Total number of farms 3,762 4,070 5,071 1. Farms using casual labour 1,102 1,753 2,557 2. Percentage using casual labour 29.29 43.07 50.42 3. Growth rate of farms using casual labour 5.64 3.85 4. Percentage change of farms using casual labour 59.10 95.90 B. Total permanent labour (family + permanent 13,366 16,853 17,943 labour) C. Permanent hired labour 512 387 487 D. C as percentage of B 3.83 2.30 2.71

Source: Pakistan (1975, 1983 and 1993).

119 Table A3.6: Population and labour force estimates and trends according to Labour Force Survey Data

Population Labour force Crude Areas and year activity rate Number Growth (%) Number Growth (mn) rate (%) (mn) rate (%)

A. Rural areas

1979-80 58.34 - 31.03 18.10 -

1984-85 68.30 3.20 30.65 20.93 2.98

1989-90 77.71 2.62 29.90 23.23 2.08

1994-95 91.12 3.24 28.00 25.51 1.89

B. Urban areas

1979-80 23.02 - 27.17 6.25 -

1984-85 26.43 2.80 27.07 7.16 2.58

1989-90 32.66 4.32 26.28 8.59 3.88

1994-95 36.89 2.47 26.12 9.64 2.33

C. All Areas

1979-80 81.36 - 29.95 24.35 -

1984-85 94.73 3.09 29.59 28.09 2.89

1989-90 110.36 3.10 28.99 31.82 2.52

1994-95 128.01 3.01 27.35 35.15 2.01

Source: Labour Force Survey data given in Pakistan (1997).

120 Table A3.7a: Use of agricultural inputs per cultivated acre 1969-70, 1979-80, 1984-85, 1989-90 and 1994-95

Acreage input (kgs) per cultivated acre of:

Year Number of Fertilizer Improved seed distributed Pesticides tractors per 100 nutrients Acres (1) (2) (3) (4) (5) 1969-70 16.00 0.83 0.10 0.166 1979-80 51.62 3.01 0.22 0.476 1984-85 60.81 4.19 0.77 0.763 1989-90 90.26 2.90 0.50 - 1994-95 101.53 3.57 1.01 1.173

Table A3.7b: Area under high yielding varieties (HYVs) of wheat, rice and cotton since 1979-80

Agricultural Area (million acres) under the crop during: crops and area 1979-80 1984-85 1989-90 1994-95 A. Total area under: Wheat 17.11 17.94 19.38 20.19 Rice 5.03 4.94 5.21 5.25 Cotton 4.99 5.54 6.42 6.56 B. Area under HYV’s of: Wheat 13.81 16.18 17.99 18.93 Rice 4.31 4.33 4.81 4.97 Cotton 4.61 5.22 6.20 6.35 C. HYV areas as % of total area Wheat 71.30 90.19 92.83 93.76 Rice 85.69 87.65 92.32 94.67 Cotton 92.38 94.22 96.57 96.80

Source: Pakistan (1996).

121 Table A3.8: Rates of rural unemployment and underemployment in Pakistan and provinces

Percentage of labour force (%) Period Pakistan Baluchistan NWPF Punjab Sindh

A. Rate of unemployment 1979-80 2.33 2.96 2.00 2.54 1.64 1982-83 3.19 3.07 7.53 3.43 0.40 1984-85 2.95 1.03 3.53 3.43 1.28 1985-86 3.12 3.19 5.71 3.27 0.80 1986-87 2.50 0.64 3.83 2.82 0.63 1987-88 2.60 0.44 4.57 2.80 0.67 1990-91 5.47 4.09 5.48 6.46 2.19 1991-92 5.40 2.73 5.51 6.21 2.85 1992-93 4.28 2.24 5.50 4.82 1.98 1993-94 4.22 1.58 5.23 4.61 2.36 1994-95 4.80 4.09 7.10 4.86 2.28

B. Underemployment (working less than 35 hours per week) 1982-83 16.24 4.96 9.28 17.65 17.51 1984-85 11.64 8.64 10.76 11.68 12.92 1985-86 12.00 6.46 12.33 11.90 13.49 1986-87 12.68 1.19 15.23 13.80 9.44 1987-88 13.27 3.62 20.41 14.58 4.96 1990-91 14.83 11.63 19.43 18.45 9.90

1991-92 16.51 11.39 18.78 18.62 7.75 1992-93 15.02 14.12 21.05 15.91 7.75 1993-94 15.26 13.87 20.29 14.69 10.94

Note: Underemployment rates for 1979-80 and 1994-95 are not available. Source: Pakistan (1984, n.d. and 1997).

122 Table A3.9: Cropping pattern and average labour input per crop acre for various years and provinces

Percentage (%) area under: Geographical area and year Fruits and Other Wheat Rice Cotton Sugarcane vegetables crops

A. Pakistan Labour input 40.7 34.7 47.1 169.5 74.6 20.0 (Man-days per acres) 1979-80 36.0 10.6 10.8 3.7 2.3 36.6 1984-85 36.6 10.0 11.2 4.6 3.1 34.5 1989-90 36.5 9.8 12.1 4.0 3.4 34.2 1994-95 36.9 9.6 12.0 4.6 4.1 33.8 B. Punjab 1979-80 38.1 9.1 11.4 3.8 2.0 35.6 1984-85 37.9 8.2 11.5 4.6 2.9 34.9 1989-90 37.9 8.5 13.6 3.3 3.1 33.6 1994-95 37.7 8.6 14.3 4.2 3.4 31.8 C. Sindh 1979-80 26.3 19.2 15.3 3.3 2.3 33.6 1984-85 22.7 18.5 18.0 4.8 2.7 28.3 1989-90 27.7 17.6 14.9 6.7 3.2 29.9 1994-95 30.3 17.1 11.7 7.1 3.7 30.1 D. NWFP 1979-80 39.8 3.7 - 4.7 2.6 49.2 1984-85 40.7 3.6 - 5.2 2.1 48.4 1989-90 41.4 3.0 - 4.9 3.5 47.2 1994-95 41.0 2.9 - 4.8 3.8 47.5 E. Baluchistan 1979-80 45.2 9.5 - - 9.5 35.8 1984-85 43.8 18.8 - - 10.9 26.5 1989-90 42.9 15.7 - - 12.9 28.5 1994-95 37.4 13.3 - - 17.6 31.8

Source: Pakistan (1996) for crop shares and Chaudhry (1982) for labour input.

123 Table A3.10: Rate of profit in Pakistan's agriculture: 1982-83 to 1991-92

Commodity and Rate of profit (percentage) during: province 1982-83 1983-84 1984-85 1985-86 1986-87 1987-88 1988-89 1989-90 1990-91 1991-92 1. Wheat Punjab -1.70 -12.57 -3.71 6.67 0.38 0.98 7.46 15.11 16.55 10.32 Sindh -1.70 8.29 5.74 17.47 11.11 11.79 6.38 16.08 15.70 11.71 2. Rice coarse Punjab - -11.23 -14.39 -8.01 -11.49 -12.59 -8.84 -5.96 -4.76 -18.11 Sindh - -11.23 27.60 26.13 31.56 22.22 8.70 12.82 5.01 0.00 3. Sugarcane Punjab - - 14.20 13.26 26.77 24.11 23.43 23.87 15.53 10.20 Sindh - - 16.09 15.14 35.80 32.78 35.37 35.92 32.35 25.95 4. Seed cotton Punjab - 9.77 5.43 4.43 19.58 11.56 10.11 13.47 13.11 11.69 Sindh - - - - 65.50 16.30 15.50 18.30 14.30 11.40 5. Rice basmati Punjab - -5.51 2.35 2.38 6.92 31.45 21.18 22.75 7.99 7.90

Source: Afzal et al (1992 and 1993).

Table A3.11: Relative shares of agricultural and non-agricultural sectors in rural employment since 1979-80

Percentage of Share of Employment rural Years employment in non-agricultural labour force agriculture sector 1979-80 100.00 68.76 31.24 1982-83 100.00 67.69 32.31 1984-85 100.00 66.69 33.31 1985-86 100.00 70.94 29.06 1986-87 100.00 65.24 34.76 1987-88 100.00 67.49 32.51 1990-91 100.00 63.74 36.26 1991-92 100.00 63.26 36.74 1992-93 100.00 63.76 36.24 1993-94 100.00 64.76 35.24 1994-95 100.00 61.94 38.06

Source: Population Census 1981, Pakistan (1997) and Various Labour Force Surveys.

124 Table A3.12: Area and permanent (hired and family) labour input per acre by farm size for 1979-80 and 1989-90

Area and permanent labour input during:

1979-80 1989-90 Farm size Area Labour (man- Area Labour (%) years) (%) (man-years)

All sizes 100.00 0.2820 100.00 0.2898 Under 1.0 acre 0.19 4.2559 0.39 3.9914 1.0 - 2.5 acres 1.75 1.5215 3.28 1.3842 2.5 - 5.0 acres 5.10 0.5941 7.56 0.7128 5.0 - 7.5 acres 8.54 0.5342 10.31 0.4654 7.5 - 12.5 acres 18.76 0.3619 17.32 0.3097 12.5 - 25.0 acres 24.67 0.2477 21.58 0.2007 25.0 - 50.0 acres 17.81 0.1528 15.83 0.1200 50.0 - 150.0 acres 14.68 0.0786 13.64 0.0633 150.0 acres and above 8.50 0.0309 10.09 0.2610

Source: Pakistan (1983 and 1993).

Table A3.13: Proportionate area and labour input (man-hours per crop acre) under various technological packages

Bullocks Bullock-cum- Tractor Description only tractor only

A. Percentage area 1979-80 57.67 29.45 12.88 1989-90 17.69 30.33 52.98

B. Labour input Family and permanently hired 184 141 110 Casual labour 42 85 70

Source: Pakistan (1983 and 1993) and United Consultants (1989).

125 Table A3.14: Changing patterns of land tenure between 1979-80 and 1989-90

Number of farms (‘000) and operational farm area (million acres) Census years and tenurial classes Number of farms Operational farm area

Number Percentage Area Percentage

A. 1980 Agricultural Census

1. All farms 4,070 100.00 47.09 100.00

2. Owner farms 2,227 54.72 24.53 52.09

3. Owner cum tenant 789 19.38 12.40 26.33

4. Tenant fars 1,054 25.90 10.16 21.58

B. 1990 Agricultural Census

1. All farms 5,071 100.00 47.32 100.00

2. Owner farms 3,491 68.84 30.73 64.94

3. Owner cum tenant 626 12.35 8.98 18.98

4. Tenant farms 954 18.81 7.61 16.08

Source: Pakistan (1983 and 1993).

126 Table A3.15: Employment profile of household heads and incidence of poverty, 1991

Urban Rural

Proportion Incidence Proportion Incidence Poor Poor of sample of poverty of sample of poverty (%) (%) (%) (%) (%) (%)

Agriculture 63.60 35.10 64.70

By land ownership

Tenant 36.60 30.20 32.00

Agricultural Labourer 13.60 43.80 17.30

Other Agriculture 7.00 56.00 11.40

Non-Agriculture Wage Earners 43.80 28.40 39.60 17.90 29.80 15.50

By type of job

White collar 14.20 22.1 10.00 6.50 26.30 5.00

Skilled/Semi-skilled 20.10 28.1 18.00 6.60 22.10 4.20

Casual/Manual 9.50 38.3 11.60 4.80 45.10 6.30

Self-Employed 36.30 34.00 39.30 15.20 36.30 16.00 Out-side Agriculture

By value of assets

Rs. 1,000 or less 9.30 51.20 15.20 4.30 46.30 5.80

Rs. 1,000 – 10,000 12.40 34.5 13.60 6.00 39.20 6.80

Rs. 10,000 or more 14.60 22.2 10.30 4.80 24.50 3.40

Other 19.90 33.7 21.40 3.40 41.10 4.10

Overall 100.00 31.40 100.00 100.00 34.50 100.00

Source: Gazdar, Howe and Zaidi (1994).1

1 The table is based on data from the 1991 Pakistan Integrated Household Survey. The identification of households was sequential, with priority given to the identification of agricultural households in rural areas, followed by wage earners outside agriculture and self-employed outside agriculture. Agricultural households were identified from their land ownership or operation status, ownership of other agricultural assets such as livestock, and reporting of earnings from agricultural labour. Of the remainder, if the household head reported any positive wage income and his/her occupation as employment, the household was classified as a non-agricultural wage earner. The residual households were classified as self-employed if the household head reported any positive income from self-employment, and as “other” if they could not be classified under any of the above categories, or were non-earners or unemployed. The category “other agriculture” includes those who did not report land ownership or operation, but did own other agricultural assets such as livestock. The poverty line used is Rs 296 per capita per month in 1991/92 rural prices.

127 1994-95 17.01 17.01 305.12 1993-94 15.68 17.10 269.98 1992-93 17.26 17.69 242.73 1991-92 17.35 18.01 220.69 1990-91 18.85 19.32 199.78 , 1989-90 17.21 17.63 177.33 1988-89 15.97 17.46 167.23 1987-88 17.38 16.07 151.49 1986-87 15.85 15.85 142.52 1985-86 15.28 15.56 137.57 Real wages for agriculture workers (average in Rs. per day) 1984-85 15.00 15.00 131.83 Employment and Wages in Pakistan: Recent Evidence Kharif Rabi CPI Table A3.16: Source: Monthly Statistical Bulletin (various issues), cited in M. Irfan:

128 CHAPTER FOUR

ANNEX 4: TABLES

Table A4.1: Capital stock ratios in large-scale manufacturing, 1990-91 (Rs million or %)

Net output Gross output Net Capital % of output per per Per worker Gross Capital Per unit worker worker output stock

Consumer goods 77.80 0.49 0.158 0.130 34.2 82 Food, geverages and tobacco 80.20 0.78 0.182 0.224 28.9 123 Of which: Sugar 423.30 0.50 0.256 0.203 40.7 7 Textiles, garments and footwear 76.90 0.38 0.156 0.100 25.3 62 Of which: Cotton yarn and cloth 236.70 0.39 0.188 0.109 28.0 58 Other consumer goods 73.40 0.58 0.104 0.126 21.8 121 Intermediate goods (cons.) 104.60 1.30 0.228 0.239 18.4 105 Cotton ginning 57.80 1.88 0.066 0.108 5.8 164 Industrial chemicals 168.20 1.13 0.477 0.379 33.4 79 Of which: Fertilizers 902.50 1.13 0.605 0.431 38.3 71 Petroleum refining 10122.30 13.50 0.809 0.960 7.1 119 Other cons-related inter. goods 63.80 0.68 0.146 0.184 26.8 125 Intermediate goods (invest.) 72.20 0.49 0.437 0.166 34.0 38 Non-metallic mineral products 99.60 0.57 0.436 0.261 46.2 60 Of which: Cement 582.90 0.86 0.655 0.428 49.8 65

129 Net output Gross output Net Capital % of output per per Per worker Gross Capital Per unit worker worker output stock

Iron and steel 116.90 0.50 0.537 0.134 27.0 25 Other inv-related inter. goods 15.40 0.28 0.084 0.062 22.3 75 Capital goods 49.70 0.53 0.125 0.131 24.7 105 Machinery (including electrical) 44.20 0.49 0.128 0.143 29.4 112 Transport equipment 111.80 0.78 0.141 0.142 18.3 101 Other capital goods 15.40 0.25 0.084 0.056 22.0 67 Total or average 78.20 0.60 0.202 0.149 24.8 74 Memo: “Big Four” a 307.40 0.47 0.249 0.160 34.2 64

Note: a “Big Four” refers to sugar, textiles (cotton yarn and cloth), cement and fertilizers. Source: Censuses of Manufacturing Industries.

Table A4.2: Ratio of fixed assets to employment

K/L ratio Major Industry 1988-87 1990-91

Food 183,045 177,905 Beverages 132,167 228,000 Tobacco 32,333 85,833 Textiles 93,327 151,172 Wearing apparels 39,417 46,050 Leather and products 49,833 104,733 Ginning, pressing and bailing - - Wood and products 303,000 203,333 Furniture and fixture - - Paper and products 153,222 207,875 Printing and publishing 60,583 121,000 Drugs and pharmaceutical products 86,267 120,889 Industrial chemicals 453,000 449,000 Other chemical products 80,364 110,889

130 Petroleum refining 1,176,500 984,000 Petroleum and coal products 77,000 92,500 Rubber products 94,875 103,875 Plastic products 95,000 133,200 Non-metallic mineral products 331,036 443,000 Iron and steel basic industries 612,667 546,614 Fabricated metal products 67,000 76,417 Non-electrical goods 101,947 95,960 Electrical machinery 74,250 152,684 Transport equipment 70,913 135,947 Measuring, photographic, optical goods 62,000 43,500 Sports and athletic goods 86,319,000 14,962,250 Others - -

131 Table A4.3: Capital output ratios wage – value added ratios

Capital output ratios Wage – value added ratios

1980- 1984- 1987- 1990- 1980- 1984- 1987- 1990- 81 85 88 91 81 85 88 91

All industries 1.7 1.89 1.421 1.350 0.417 0.355 0.253 0.285 Food manufacturing 1.3 1.34 0.746 1.169 0.229 0.273 0.207 0.251 Beverage industries 1.4 2.13 0.776 1.103 0.374 0.510 0.159 0.184 Tobacco manufacturing 0.4 0.75 0.056 0.079 0.325 0.313 0.031 0.032 Textile 1.8 1.70 1.538 1.576 0.551 0.373 0.290 0.322 Wearing apparel 0.8 1.14 0.665 1.086 0.313 0.694 0.398 0.754 Leather and leather products 0.7 0.53 4.203 1.891 0.181 0.217 0.991 0.452 Foot-wear except rubber or plastic 0.3 0.88 0.633 1.404 0.338 0.323 0.480 0.870 Ginning and bailing of fibres 0.5 0.76 0.623 0.435 0.183 0.266 0.347 0.325 Furniture and fixtures, not metal 0.8 5.12 3.192 1.022 0.387 0.373 0.449 0.347 Other paper products 1.6 2.11 1.959 1.491 0.535 0.440 0.319 0.229 Printing and publishing 2.1 1.57 1.388 0.420 0.558 0.506 0.606 0.166 Drugs and pharmaceutical products 0.4 1.14 0.875 0.798 0.236 0.385 0.478 0.479 Industrial chemicals 4.2 2.10 1.725 1.259 0.332 0.269 0.224 0.220 Other chemical products 1.0 0.55 0.501 0.497 0.395 0.233 0.194 0.217 Petroleum refining na 4.59 0.508 0.843 na 0.183 0.043 0.116 Rubber products 0.6 1.66 1.558 0.972 0.345 0.489 0.433 0.388 Plastic products 2.4 1.43 1.484 0.095 0.784 0.362 0.424 0.376 Pottery, china and earthenware 2.2 2.42 1.415 3.011 0.538 0.478 0.411 0.424 Other non-metallic mineral products 7.9 1.81 1.492 na 0.938 0.303 0.156 7.622 Glass and glass products 2.3 4.49 2.010 1.609 na 0.604 0.344 5.740 Iron and steel 1.0 1.40 5.784 4.019 0.863 na 0.422 0.543 Non-ferrous metal basic industries 1.4 1.12 0.470 2.662 0.756 0.403 0.722 0.676 Metal products, machinery, 1.8 1.10 1.036 0.955 0.595 0.419 0.418 0.381 equipment Non-electrical machinery 1.0 1.09 1.888 1.049 0.458 0.518 0.538 0.530 Transport-equipment 2.3 1.17 1.730 0.988 -na 0.319 0.676 0.414

132 Table A3.4: Determinants of labour productivity and employment in Pakistan OLS Regression results log V/L = 0.89 + 0.85 log K/L + 0.05t R2 = 0.99 D.W. 1.20 (0.41) (3.84) (12.32)

log V/L = -0.48 + 0.81 log K/L + 1.74 log V+ 0.040t R2 = .99 D.W. = 1.09 (0.16) (3.41) (0.69) (2.56) log V/L = -6.68 + 0.78 log K/L + 0.79 log V R2 = .98 D.W. = 0.53 (3.30) (2.79) (10.02)

log V/L = -1.15 + 0.99 log v R2 = .97 D.W. 1.15 (2.50) (23.85) log L = 6.99 - 0.58 log K/L - 0.01 t R2 = 0.22 D.W. 0.49 (2.41) (-1.96) (1.80)

log L = 0.48 + 0.83 log V - 0.81 log K/L - 0.04 t R2 = .57 D.W. 1.09 (-.20) (3.30) (3.41) (2.l56) Log L = 6.68 + 0.21 log V - 0.78 log K/L R2 = .36 D.W. = 1.5 (3.30) (2.67) (2.78)

Log L = 1.15 + 0.013Log V R2 = 0.06 D.W. = 1.15 (2.50) (0.31)

where: V = Value added in manufacturing K = Capital stock in manufacturing L = Labour in manufacturing t = time trend

Table A4.5: Productivity in different manufacturing industries in 1990-91 (Base=1982-83)

Total factor Labour productivity Capital productivity productivity Food 84.3 76.7 98.3 Textiles 257.1 151.3 103.1 Leather 57.2 53.2 94.9 Drugs and pharmaceutical 124.7 70.0 97.6 Industrial chemicals 139.4 196.0 104.2 Plastic products 109.1 106.0 100.2 Electrical machinery 175.0 103.9 100.7 Transport equipment 145.0 72.9 99.3 Cement 72.6 61.3 96.6

Source: DRI/PIDE Technology Study (1977).

133 Table A4.6: Labour productivity and capital intensity manufacturing (Rs. Mn)

1984-85 1985-86 1986-87 1987-88 1990-91

Labour productivity 0.104 0.109 0.127 0.144 0.178 (Value added/employment)

Capital intensity 0.099 0.123 0.166 0.168 0.192 (Value of fixed assets /employment)

Source: Economic Survey 1995-96.

Table A4.7: Investment in manufacturing industries

Investment in manufacturing Share of private as percentage of GDP investment in total manufacturing Private Public Total

1982-83 1.7 1.3 3.0 57.0 1983-84 2.9 1.2 3.1 60.0 1984-85 2.0 0.8 2.7 72.1 1985-86 2.2 0.8 3.0 72.6 1986-87 2.6 0.4 2.9 87.1 1987-88 2.5 0.4 2.9 86.5 1988-89 2.9 0.4 3.4 87.2 1989-90 3.3 0.5 3.7 88.0 1990-91 3.3 0.5 3.8 87.6 1991-92 4.3 0.5 4.8 89.8

1992-93 4.2 0.5 4.7 89.1 1993-94 4.2 0.5 4.7 87.7 1994-95 2.2 0.5 2.7 80.8 1995-96 2.3 0.6 2.9 80.9 1996-97 2.1 0.6 2.7 77.4

Source: Based on data obtained from Economic Survey, 1996-97 and previous issues.

134 Table A4.8: Composition of total investment in the manufacturing sector

Percentage share in investment

1982-83 1988-89 1992-93

Food, tobacco and beverages 14.30 18.90 26.40

Textiles 16.09 41.00 29.30

Leather, footwear and leather goods 1.50 3.70 2.30

Rubber and rubber products 3.60 0.80 1.20

Pulp and paper 5.50 4.30 4.60

Chemicals, pharmaceuticals and fertilizers 27.60 7.30 10.10

Cement and other non-metallic minerals 12.80 4.90 2.90 products

Basic metals 2.30 1.20 1.80

Metal products other than machinery 2.50 1.10 1.30 and transport equipment

Machinery other than electrical 2.40 1.10 1.30

Electrical machinery, appliances and fittings 3.20 3.20 2.70

Transport equipment 2.20 2.50 3.40

Services and miscellaneous industries 5.10 9.10 13.60

Source: National Accounts, 1988/89, and unpublished data from Federal Bureau of Statistics.

135 Table A4.9: Composition of industrial output in Pakistan

Percentage share in value added at factor cost Industries 1980-81 1985-86 1987-88 1990-91 1 Food Industries 24.21 15.69 15.49 14.24 2 Beverage Industries 0.90 1.52 0.61 1.27 3 Tobacco Manufacturing 3.00 2.87 5.38 7.49 4 Manufacturing of textiles 24.32 19.85 21.43 25.97 5 Manufacturing of wearing apparel except footwear 1.42 1.55 1.96 1.03 6 Manufacturing of leather and leather products, 1.62 2.34 1.60 0.73 leather substitutes and fur except wearing apparel 7 Manufacturing of footwear except vulcanized 1.29 0.29 0.99 0.38 molded rubber of plastic footwear 8 Ginning, pressing and baling of fibres 4.65 2.60 1.25 1.23 9 Manufacturing of wood and cork products 0.43 0.48 0.61 0.26 except furniture 10 Manufacturing of paper and paper products 2.06 1.26 1.32 1.69 11 Printing publishing and allied industries 1.15 1.54 1.33 2.57 12 Manufacturing of drugs and pharmaceutical 5.35 5.72 3.46 3.46 products 13 Manufacturing of Industrial chemicals 5.88 14.18 8.35 7.25 14 Manufacturing of other chemical products 1.99 3.62 3.11 2.31 15 Manufacturing of rubber products 1.26 1.86 0.70 0.86 16 Manufacturing of plastic products n.e.c. 0.24 0.75 0.51 0.55 17 Manufacturing of pottery, china and earthenware 0.32 0.32 0.42 0.25 18 Manufacturing of non-metallic mineral products 2.36 4.86 6.02 7.69 19 Iron and steel basic industries 6.61 5.32 8.26 6.34 20 Non-ferrous metal basic industries 0.06 0.02 0.02 0.03 21 Manufacturing of fabricated metal products 1.30 1.10 0.93 0.80 except machinery and equipment 22 Manufacturing of machinery except electrical 2.59 3.26 2.09 2.46 23 Manufacturing of electrical machinery apparatus, 4.25 4.06 3.53 4.21 appliances and supplies 24 Manufacturing of transport equipment 2.49 3.36 4.62 2.86 25 Manufacturing of scientific, precision and 0.29 0.17 0.40 0.14 measuring instruments and equipment 26 Manufacturing of photographic and optical goods 0.04 0.03 - - 27 Manufacturing of sports and athletic goods 0.10 0.17 0.25 0.32 28 Other manufacturing industries 0.36 0.29 5.00 1.27

Source: Census of Manufacturing Industries, 1980-81, 1985-86, 1987-88 and 1990-91.

136 Table A4.10: Industrial production – large-scale (percentage share)

Item 1988-89 1989-90 1990-91 1991-92 1992-93 1994-95 1995-96 1996-97

Food, beverage and 26.14 25.58 24.25 25.52 27.06 28.65 28.53 26.10 tobacco Food 18.89 18.76 18.83 19.57 19.59 21.68 20.73 18.34 Beverages 5.55 2.18 4.03 4.68 6.15 5.60 6.62 6.10 Cigarettes 1.70 1.64 1.30 1.27 1.32 1.37 1.18 1.66

Textile, apparel and 24.75 26.46 26.03 27.48 26.78 26.05 26.07 28.32 leather Textiles 16.13 18.11 17.17 17.50 19.62 19.93 20.03 21.39 Jute goods 1.36 1.22 1.22 1.16 1.04 0.79 0.67 0.69 Leather 1.84 1.83 1.73 1.58 1.39 1.29 1.23 1.15 Cotton (ginned) 5.41 5.30 5.91 7.24 4.73 4.04 4.14 5.09

Paper and board 2.29 2.16 1.87 1.99 2.75 2.69 2.99 2.84

Pharmaceuticals, 19.16 18.52 18.79 17.70 17.88 18.57 17.22 18.67 chemicals and rubber Pharmaceuticals 7.04 7.16 7.52 7.60 7.56 7.07 6.32 6.50 Chemicals 11.26 10.54 10.39 9.41 9.74 10.88 10.24 11.44 Rubber 0.86 0.82 0.88 0.69 0.59 0.62 0.66 0.74

Petroleum products 7.13 7.17 8.02 7.40 6.56 6.43 5.60 6.02

Non-metallic mineral 2.70 2.72 2.82 2.71 2.59 2.42 2.37 2.68 products

Basic metal industries 6.78 6.49 7.22 6.65 6.44 7.02 5.73 5.60

Metal products, 11.06 10.90 11.00 10.54 9.94 8.18 11.50 9.77 machinery Metal products 0.29 0.29 0.25 0.28 0.29 0.23 0.24 0.27 Machinery 1.33 1.05 0.78 0.56 0.84 0.52 0.47 0.44 Electrical machinery 4.98 4.85 5.15 4.85 4.57 4.55 4.75 5.02 Transport equipment 4.46 4.75 4.82 4.85 4.24 2.88 6.04 4.04

TOTAL 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00

Source: Unpublished National Accounts Data.

137 Table A4.11: Capacity utilization in major industries

1992-93 1993-94 1994-95 1995-96

Spinning 80.30 71.90 72.10 61.50

Weaving 42.90 42.90 35.70 42.90

Jute Goods - 50.70 44.70 47.30

Fertilizer 87.70 93.50 92.40 100.60

Cement 104.80 99.60 95.40 96.60

Sugar 99.10 102.20 95.40 69.50

Source: Planning and Development Division.

138 CHAPTER FIVE

ANNEX 5.12: THE SMALL-SCALE ENTERPRISE SECTOR IN MAIN DATA SOURCES

The data sources include National Income Accounts, Labour Force Surveys, the Economic Survey as well as major surveys done for this sector in Pakistan. These major surveys are: the Small Household and Manufacturing Industries (SHMI) 1983-84, 1988; the Census of Establishments 1987-88, the Household Integrated Economic Survey (HIES) 1987-88, 1990-91; the Integrated Survey of Service and Manufacturing Industries-Small, (ISSMI-Small), 1992.

Partial estimates of the output of the sector based on National Income Accounts (NIA) (table A5.1), suggest that its output share in manufacturing is around 30 per cent while its employment share is nearly 83 per cent (table A2). NIA, however calculate the size of the small-scale sector as a residual. In short, according to NIA we have a disproportionately high share of employment within manufacturing which goes to the SSE. Another characteristic of the SSE sector is its allegedly high growth rate. The combination of high employment absorption capacities and its supposedly high growth rate make this sector a focus of attention from an employment perspective.

Rates of growth

It is therefore important to estimate the growth rate of the sector as correctly as is possible, even if it is only in manufacturing. However, serious problems arise. Of the two methods of calculating growth rates of the SSE in Pakistan, one is based on National Income Accounts (NIA) and the other on inter-survey data on the SSE. National Income Accounts essentially calculate the growth rate between two residual categories (the estimate of the sector’s size is itself based on a residual); these calculations give a high growth rate for the sector. Inter-survey data on the other hand give a much lower rate of growth, although they have some problems of definition and comparability.

On NIA data, during the period 1980-81 to 1992-93, the manufacturing sector as a whole grew by 7.3 per cent, the large-scale sector is supposed to have grown by 7.1 per cent. This gives a residual growth rate of the SSE of 8.1 per cent (see table A5.3). If the period is extended up to 1996-97, the growth rate of the SSE become even higher at nearly 10 per cent. NIA data over the long run show, that during the 1950s and 1960s the large-scale sector was the leading sector in manufacturing. In the 1970s a reversal took place when the growth of the large-scale sector dropped (to around 4 per cent) and that of the small sector increased (to nearly 8 per cent)3. Over the 1980s , the period of high growth of the economy both sectors registered a growth of around 8 per cent. Since 1987-88, the trend in large-scale manufacturing growth is one of decline. However, a constant rate of growth of 8.4 per cent is estimated for the SSE for each subsequent year, up to 1997. This suggests that the estimate is likely to be ‘projection based’ and does not have a direct empirical basis (see table A5.4).

The growth of the SSE in manufacturing from the alternative survey sources give different growth figures. There are two sources here. First we have the Survey of Small Household-based Manufacturing Industries

2 See ILO-SAAT, Mahmood, M., 1997, mimeo for details.

3 This is sometimes attributed to the effect of the first PPP governments’ nationalization of some large-scale industries.

139 (SHMI) surveys for 1976-77, 1983-84 and 1988. Growth rates can be calculated from these, subject to modifications, due to differences in definitions and coverage of the SSEs in the three surveys, in order to make the basis of calculations consistent. There is also a fourth Integrated Survey of Service and Manufacturing Industries –Small (ISSMI-Small) for 1992-934 .

An input-output table for Pakistan has been used to make the SHMIs of 1976-77 and 1983-84 comparable (table A5.5) . This gives a growth rate of SSE between 1976-77 and 1983-84 of 4.4 per cent. Making the SHMIs of 1983-84 and 1988 comparable, a growth rate of 4.7 per cent is estimated. The final comparison is between the SHMI 1983-84 and ISSMI-Small 1992-93.5 This gives an even lower growth rate of 2.6 per cent.

Thus, NIA-based growth rates for the SSE sector in manufacturing are high, at around 8 per cent for the 1970s, 1980s and the 1990s. In contrast inter-survey growth rates for the 1970s and 1980s are much lower at 4.5 per cent and, for the last decade, up to 1992-93, even lower at 2.6 per cent. Even if we take an equivocal view on the data sources for the calculation of growth rates the SSE sector in manufacturing cannot be considered to have had unambiguously high growth rates during the 1970s, 1980s and 1990s. The likelihood is that growth rates were considerably lower, especially in the past decade. We now examine the profile of SSEs as it is revealed in the major surveys.

Broad characteristics

The SHMI

In 1988 there were 258,000 SSE units in manufacturing. They had fixed assets of Rs.5.6 billion; employed .6 million persons and produced a value added of Rs 9.9 billion.

4 The differences between the SHMI surveys and ISSMI-Small in definitions and coverage are the following: SHMI 1976/77: (a) Surveyed establishments; (b) With an investment of less than Rs. 2 million; (c) In urban areas only. SHMI 1983/84: (a) Surveyed establishments; (b) Which were not registered; (c) In both urban and rural areas. SHMI 1988: (a) Conducted a census of establishments; (b) Employing less than 10 workers; (c) In both urban and rural areas. ISSMI-Small 1992/93: (a) Surveyed establishments; (b) Which were neither listed on the stock exchange, nor registered with the Government, nor Government sponsored; (c) In both urban and rural areas.

5 To make the SHMIs for 1976/77 and 1983/84 comparable and to calculate the growth rate, Table A5.5 carries out a procedure detailed in Input Output Table for Pakistan, 1993. In essence the procedure is the following: for the SHMI 1983/84, it takes the Gross Value Added (GVA) revised downwards for 6 industries with estimation errors, per urban labourer. It then estimates the labour force in manufacturing for 1983/84 and subtracts the large-scale sectors share given in the Census of Manufacturing industries (CMI) for 1983/84. This gives an SSE labour force for both rural and urban areas. Then SSE employment multiplied by SSE GVA per labourer gives a total SSE GVA of Rs 12.8 billion. For the SHMI 1976/77 it follows a similar procedure to give a total SSE GVA of Rs 5.6 billion. These values for 1976/77 and 1983/84 are then indexed by wholesale prices. This procedure gives a growth rate for the inter-survey period of 1976/77 - 1983/84 of 4.4 per cent in Table A5.5. We have followed an additional procedure given in SHMI 1988, which makes urban SHMI 1983/84 comparable to urban SHMI 1988 [SHMI, 1988]. This involves subtracting units employing more than 10 workers from urban SHMI 1983/84. This procedure gives a growth rate for the inter-survey period of 1983/84 and 1988 of 4.7 per cent in Table A5.6.

The growth rates for value added per unit of labour are given in Table A5.7. Finally in Table A5.8 we have calculated growth rates for value added in the SSE sector for the most recent period possible, 1983/84 to 1992/93. This involves a comparison between the SHMI 1983/84, and the most recently conducted Integrated Survey of Service and Manufacturing Industries Small (ISSMI-Small) for 1992/93. There is some justification for making this comparison because, as the above definitions show, both the SHMI 1983/84 and ISSMI Small 1992/93 surveyed the unregistered sector. In Table A5.8 we have compared SHMI 1983/84 which is for manufacturing only, with ISSMI-Small 1992/93 for manufacturing. This gives an even lower growth rate for the SSE sector between 1983/84 and 1992/93 of 2.6 per cent p.a.

140 The value added per worker (labour productivity) of the sector was Rs. 18,000 in urban areas and Rs. 11,000 in rural areas (table A5.7). In contrast, large-scale sector labour productivity is 10 times greater on average. The capital-labour ratio, i.e. the capital intensity, for the SSE is around Rs. 9,000. The large-scale sectors value of capital per worker is Rs. 202,000 (not provided in a table here), which is greater by a factor of 22 in comparison to the SSE (table A5.9). The capital output ratio of the SSE is 1.8, which is also lower than 3.0 for large-scale sector. Clearly, both in terms of capital intensity and labour productivity the SSE sector is much lower than the large-scale sector.

In terms of value of assets the predominant SSE sub-sectors are food (31 per cent); followed by textiles (24 per cent); wood products (17 per cent) and fabricated metals (15 per cent). In employment, textiles have the largest share (42 per cent) followed by food (16 per cent); wood products (15 per cent) and fabricated metals (14 per cent). Textile again have the highest share in value added at 36 per cent, followed by food (18 per cent) and fabricated metals and wood with a 15 per cent share.

The significant industries within each major sub-sector can be determined on the basis of value added. In textiles, the largest industries are weaving (11 per cent share in total SSE manufacturing value added (TVA)) and carpets (7 per cent of TVA). In the second largest sub-sector, which is food products, the largest industry is wheat milling (8 per cent of TVA) and rice (2 per cent of TVA). In the third largest sub- sector of fabricated metals, the major industry is metal products (8 per cent of TVA) followed by non- electrical machines (3 per cent of TVA). In the fourth largest sub-sector, wood products, the most significant industry is furniture (6 per cent of TVA).

If we rank the industries on their own, weaving is the largest, followed by metal products, wheat milling, jewelry (a category on its own), furniture and non-electrical machinery.

The Census of Establishments (CE) 1987-88 and the Household Integrated Economic Survey 1990-91 (HIES)

The SHMI of an SSE employment of .63 million workers and 258,000 units is also partial as it excludes non-manufacturing sector. This SHMI estimate, however, is complemented well by a survey of income for the same year, the Census of Establishments (CE) 1987-88. The two together allow an estimate of the entire SSE sector.

The CE estimates of non-farm establishments using less than 10 workers are around 1.8 million, which employ 3.1 million workers. The share of manufacturing in employment from this data source is 0.65 million which is consistent with the SHMI data set, this is also the case with the sectoral compositions.

The total picture therefore gives an employment size of 2.45 million workers in non-manufacturing employment in 1987-88 (table A5.10). The largest share of employment is in trade (42 per cent of SSE employment), followed by services (28 per cent), textiles (9 per cent), catering (7 per cent), finance (2 per cent), transport (1 per cent), and fabricated metals and wood (around 3 per cent) each. The urban-rural employment split of the SSE is 69 per cent and 31 per cent respectively, although the ranking of the sub- sectors within them is the same.

The rural urban split is 31 to 69 per cent in favour of rural and the ranking of sub-sectors is the same for both.

141 Serious discrepancy in the manufacturing sector estimates

We need to note a very significant discrepancy between the employment estimates based on the SHMI and CE of 1987-88 and the Labour Force Surveys( LFS). The SHMI and CE data estimate the SSE employment in manufacturing to be roughly around 0.7 million. The LFS estimates the total employment in manufacturing in 1987-88 to be 4.1 million, of which the SSE’s share is 3 million and the large-scale manufacturing sectors share is .6 million.6 In other words the lower bound for SSE manufacturing employment is .7 million (SHMI and CE data) and the upper bound is 3 million (LFS data) for the year 1987-88. This poses a serious problem and we need to have some alternative estimates, to achieve perspective on the size of employment in the sector.

The Household Integrated Economic Survey (HIES) 1987–88 and 1990-91

The HIES 1990-91 gives a fairly good and recent estimate of the entire SSE (tables A5.10 an A5.11). The variable in the HIES is the number of units, 4.5 million in 1990-91. Trade is still the largest sub-sector (2.1 million units) followed by services (1.3 million), manufacturing (0.8 million) and catering (0.2 million). For all the units in the sector taken together and applying a constant ratio of employment per unit (1.72) the total employment for 1991 comes to 7.7 million persons. On the same assumption, manufacturing employment comes to 1.37 million, somewhere between the SHMI/CE estimate and the LFS estimate.

A striking characteristic brought out by the HIES 1990-91 is that of the 4.5 million units, 1.1 million are mobile, 0.5 from trade and another 0.5 from services.

A third important characteristic is that rural units are greater than urban ones. Of the 4.5 million, 2.5 million are in rural areas and 2 million in urban areas7. This is in contrast to the SHMI/CE estimates which suggest that the number of urban units to be higher in 1987-88, some three year prior to the date of the HIES.

Fourthly, mean income is clearly lower than that in the large-scale sector.

Our estimates of the SSE from the above discussion suggest that this sector could be employing between 3.1 and 7.7 million persons. Its mean income is lower than that in the large-scale sector and to that extent it is to a refuge sector. Manufacturing is a quarter of this sector in terms of value added, while trade and services account for around 70 per cent. Manufacturing in the SSE has a low capital-labour ratio and therefore a much lower labour productivity compared to the large-scale sector.

ISSMI-Small 1992-93

We have a wide range of size of employment in the sector, which we need to narrow down. Estimates based on Integrated Survey of Service an Manufacturing Industries-Small 1992-93 (ISSMI) allow for this possibility (tables A5.12-15). In 1992-93 the SSE comprised 1.9 million units which is consistent with the 1.8 units figure of the CE 1990-91 and much lower than the HIES 1990-91 figure of 4.5 million. Employment according to ISSMI is 4.4 million which lies between the lower bound given by CE of 3.1

6 LFS 4.1 million in the manufacturing sector should be equaled by [CMI Large-scale = 0.6m] + [SHMI Small- scale ] in 1988 but is not. Therefore, as a second-best estimate we can take SSE as a residue = [(4.1m) - (CMI's 0.6m)] = 3.7m. But this may be on the high side since CMI 0.6m is underestimated due to non-registration.

7 The density of units per 1,000 population is 55 for urban, 33 for rural areas and 40 for the whole sector. This suggests that the proliferation of the SSE sector is some function of population, even if it is not strictly proportional.

142 million and the upper bound of 7.7 million projected with HIES 1990-91. Of the value added contribution of Rs. 226 billion, the share of manufacturing is 26 billion, which is 17 per cent of the value added in the entire manufacturing sector according to ISSMI –Small and ISSMI- Large. The mean wage in the SSE is Rs 4000, which lies between that of a semiskilled and skilled worker. Capital stock data for ISSMI-Small are comparable to SHMI 1988 estimates shown above. Trade is ranked as the largest sub-sector on asset values, employment and value added. This is followed by services, textiles, food, hotels and metal fabrication. This is also in keeping with the SHMI 1988 data.

Therefore ISSMI-Small is not only consistent in many respects with other major surveys, it also arrives at a plausible middling figure for employment in the SSE sector which lies between the wide range of figures we get from different sources.

143 ANNEX 5.2: TABLES

Table A5.1: Estimated share of the small-scale sector in manufacturing 1992/93

GDP at current Total Large-scale Small-scale factor cost manufacturing

1990/91 908,374 158,840 112,204 46,636 (Rs. Million) % 100.00 17.49 12.35 5.13 % 100.00 70.64 29.36 1991/92 1,077,943 186,832 130,252 56,580 (Rs. Million) % 100.00 17.33 12.08 5.25

% 100.00 69.72 30.28

1992/93 1,200,129 207,273 142,206 65,267 (Rs. Million) % 100.00 17.27 1185.00 5.44 % 100.00 68.61 31.49 1996/97 2,245,904 378,647 256,164 122,483 (Rs. Million) % 100.00 16.86 11.40 5.45 % 100.00 67.65 32.36

Source: Calculated from the Economic Survey 1996-97.

144 17.10 82.90 100.00 % of Manu- facturing 2.09 10.14 12.23 % of 100.00 Manu- facturing 623,380 1990-91 3,024,584 3,647,964 29,828,000 17.40 82.60 % of 100.00 Manu- facturing (2.43) (11.57) (14.00) 720,000c 1987-88 3,423,900 4,143,900a 29,600,000 20.40 79.60 % of 100.00 Manu- facturing (2.74) (10.70) (13.44) 690,000 2,699,044 3,389,044 1982-83 25,220,000 19.50 80.50 % of 100.00 Manu- facturing (2.66) (10.98) 580,000 (13.640) 1977-78 2,398,928 2,978,928 21,840,000 21.00 79.00 % of 100.00 Manu- facturing (2.63) (9.89) (12.51) 480,000 1,806,150 2,286,150 1971-72 18,270,000 18.30 81.70 % of 100.00 Manu- facturing (2.49) (11.10) (13.60) 337,000 1960 1,501,000 1,838,000 Employment in the manufacturing sector 13,517,000 (a) Residual of total and large-scale manufacturing sector. (b) Domestic employed labour force. (c) For 1987-88 based on CMI and NMC Survey of large-scale manufacturing. ILO/ARTEP, employment and structural change in Pakistan, Bangkok, 1983 labour force surveys, CMI 1990-91. (a) Total Small-Scale Large-Scale Total labour Manufacturing Manufacturing Manufacturing Table A5.2: Note: Source:

145 (17.10) (46.90) (36.10) 623,380 (100.00) 1709,144 3,647,964 1,315,440 1990-91 (17.37) (47.06) (35.56) 720,000 (100.00) 4,143,900 1,950,275 1,473,625 1987-88 (19.47) (50.40) (30.13) 580,000 897,476 (100.00) 2,978,928 1,501,452 1977-78 51,366 (21.00) (56.68) (22.32) 480,000 (100.00) 2,286,150 1,295,814 1971-72 Employment in manufacturing, urban/rural Breakdown of Small-scale based on labour force survey. All Large-scale assumed in urban areas. % in brackets. (I) (II) ILO/ARTEP, employment and structural change in Pakistan, Bangkok, 1983 labour force surveys, CMI 1990-91. Total manufacturing Large-scale Small-scale rural Small-scale urban Table A5.2b: Note: Source:

146 Table A5.3: Growth rates in manufacturing (constant factor cost 1980/81, Rs million)

Value added

Total Small-scale Large-scale Small-scale manufacturing (%) share 1980-81 37,446 27,451 9,995 26.70 1992-93 89,889 63,577 26,312 29.10 Growth rate (%) 7.30 7.10 8.10 - 1980/81-1992/93 1996-97 104,381 68,051 33,330 31.90 Growth rate (%) 8.50 7.60 10.00 - 1980/81-1996-97

Source: Calculated from the Economic Survey 1996-97.

Table A5.4: Real growth in the manufacturing sector (% per annum)

Small-scale Large-scale Total manufacturing Period manufacturing manufacturing sector 1950-60 2.30 15.40 7.70 1960-70 2.90 13.90 9.90 1970-80 7.90 3.90 4.80 1980-89 8.40 8.30 8.40 1950-86 5.00 10.00 7.50 1986-87 8.40 7.20 7.50 1987-88 8.40 10.60 10.00 1988-89 8.40 2.40 4.00 1989-90 8.40 4.70 5.70 1990-91 8.40 5.40 6.30 1991-92 8.40 7.90 8.10 1992-93 8.40 4.10 5.40 1993-94 8.40 4.30 5.50 1994-95 8.40 1.50 3.60 1995-96 8.40 2.60 4.40 1996-97 8.40 -1.40 1.80

Source: Economic Surveys.

147 Table A5.5: Growth of SSE based on inter survey 1976/77 - 1983/84 growth rates

(Rs. million)

I. 1983/84 SHMI - Urban GVA (published) 8377.4 million Correction for 6 industries 1518.0 million SHMI Urban GVA revised 6895.4 million Employment SHMI Urban 555,497 Urban SHMI GVA/L Rs. 12,413

II. 1983/84 Estimates Employed labour force in manufacturing Pakistan Urban Rural by Pop. Census 1981 1.996 1.041 0.955 LFS % PA 1980/81-1983/84 1.23% Manuf. est. labour force 1983/84 2.071 1.08 0.991 Manuf. LSE (cm1 1983/84) -0.665 -0.484 -0.181 Manuf. SSE 1.406 million 0.596 0.81 GVA/L in SSE Rs. 12,413 Rs. 6,669 SSE GVA 1983/84 Rs. 12,808 million 7,410 million 5,398 million

III. 1976/77 Estimates Employed labour force in manuf. Pakistan Urban Rural by pop. Census 1981 1.996 million 1.041 0.955 LFS % PA 1976/77 - 1980/81 2.85% Manuf. Est. L Force 1976/77 1.784 0.931 0.853 Manuf. LSE (CM1 1976/77) -0.616 -0.462 -0.154 Manuf. SSE 1168 0.469 0.699 GVA/L in SSE Rs. 6,629 Rs. 3,561 SSE GVA 1976/77 Rs. 5,594 million 3104 2,490

IV. WPI 1976/77 (1975/76 = 100) = 112.4 WPI 1983/84 (1975/76 = 100) = 190.8

V. GVA SSE ave. PA growth rate 1976/77 - 1983/84 = 4.4%

Source: Input Output Table 1993.

148 Table A5.6: Inter survey growth in value added: Pakistan, 1976/77-1988 Value added (Rs.million)

Current (Rs. 1975/76) Constant % Growth Rate 1976-77 5,594 4,977 4.3a 1983-84 12,808 6,713 (URBAN) 1983-84 5,250 2,752 4.7b 1988 7,736 326

Notes: a From the Input Output Table 1993. SHMI 1976/77 made comparable to 1983/84. b From the SHMI 1988. SHMI 1983/84 made comparable to 1988.

Table A5.7: Inter survey growth in value added/labourer Value added/labourer (Rs.)

URBAN RURAL Years (Rs. (Rs. (Rs.) Growth (Rs.) Growth 1975/76) 1975/76) Current Rate Current Rate Constant Constant 1976-77 6,629 5,898 3,561 3,168 1.40 1.40 1983-84 12,413 6,506 6,669 3,495 4.80 6.60 1988 18,359 7,893 10,566 4,543

Source: Calculated from Input Output Table 1993, SHMI 1988.

Table A5.8: SSE manufacturing: Inter survey growth rates in value added 1983-84 - 1992/93

Real Current Constant Growth Year GVA WPI GVA Rate in (Rs. Million) (Rs. Million) GVA 1983/84 12,808.00 100.00 12,808.00

2.6% PA 1992/93 25,768.00 159.41 16,206.00

Source: Calculated from SMM1 1983/84 and ISSMI 1992/93.

149 8.0 1.6 1.0 6.8 5.9 3.6 1.6 3.7 0.7 1.2 8.2 3.3 1.4 0.8 0.3 0.7 0.3 8.9 6.7 0.9 18.0 35.6 11.3 14.6 14.9 100.0 9,903 (Rs.m) Value Added 8.9 0.5 0.5 8.8 6.5 2.2 1.3 3.2 1.3 0.6 8.0 2.6 0.8 0.6 0.3 0.5 0.3 7.8 5.3 1.3 15.9 41.6 14.2 15.0 13.7 ment (000) 627 100.0 Employ 1988 1.4 1.2 1.5 4.0 2.5 1.0 2.8 0.5 0.5 7.1 4.4 1.5 1.0 0.4 0.7 0.3 6.9 5.8 0.3 30.8 19.7 24.4 12.5 17.2 14.7 100.0 Fixed Assets (Rs.m) 5,597 RURAL AND URBAN 0.5 0.6 6.2 7.0 1.7 0.9 2.7 1.4 0.3 7.7 2.2 0.8 0.6 0.2 0.3 0.1 9.7 7.1 1.3 18.9 13.4 39.2 13.5 15.1 12.4 100.0 257,557 No of Units 7.9 3.2 0.9 7.0 1.8 4.8 1.9 0.8 8.7 1.1 4.7 8.8 4.2 1.8 1.3 0.2 0.4 0.3 8.7 6.7 0.6 20.2 32.0 12.7 15.4 100.0 Value Added (Rs.m) 9,369 7.5 1.7 0.6 4.4 5.2 1.3 0.5 6.7 1.9 2.4 3.2 1.2 1.1 0.2 0.3 0.2 7.1 5.3 0.5 22.0 35.3 10.7 12.9 14.5 10.1 ment (000) 946 100.0 Employ 1983/84 5.5 1.0 5.9 1.2 2.4 1.3 0.4 4.0 0.4 1.3 6.6 5.9 2.4 1.8 0.3 0.5 0.3 5.6 4.3 0.4 44.5 18.9 17.3 12.5 14.2 100.0 Fixed Assets (Rs.m) 6,736 RURAL AND URBAN 9.4 0.9 0.9 2.9 9.3 5.9 1.0 0.4 4.1 2.4 0.7 3.1 1.2 1.1 0.1 0.2 0.1 9.4 7.7 0.5 20.3 35.0 13.9 12.1 100.0 159.0 426,457 No of Units - 3.0 0.4 2.4 7.8 7.3 4.4 3.6 2.0 7.4 1.0 5.1 8.2 5.0 0.9 2.7 0.9 0.8 7.1 5.7 0.9 10 11.4 41.4 10.4 17.9 100.0 Value Added (Rs.m) - 2.4 0.3 1.1 5.5 4.2 2.9 1.6 1.6 7.4 7.9 4.5 0.5 2.6 0.8 0.8 7.4 5.8 0.8 11.1 41.6 19.2 10.0 10.0 16.1 ment (000) 380 100.0 Employ 1976/77 URBAN - 9.3 3.1 3.5 8.5 2.5 2.4 2.7 0.9 4.4 0.7 2.0 8.4 9.3 1.1 5.2 2.0 1.3 4.8 3.6 0.8 22.4 29.6 11.5 22.6 955 100.0 Fixed Assets (Rs.m) - 9.2 3.5 0.2 1.2 6.4 9.1 6.7 2.8 1.6 3.5 2.0 0.5 8.3 4.9 0.7 3.0 0.8 0.6 8.8 0.4 43.0 13.5 16.9 10.2 100.0 Units No of 108,642 SSE sectoral shares Calculated from SHMI: 1976/77, 1983/84, 1988. Total value Total Food, beverages tobacco Wheat milling Rice milling Oil extraction Textiles, leather Weaving Carpets Wood & products Furniture Chemicals, rubber Plastic products Minerals (non-iron) Pottery Bricks Fabricated metal Metal products Non electric machines Agricultural Machining Textiles Basic metals Iron foundries Other Jewelry Sports goods 1 2 3 4 5 7 8 Table A5.9: Source:

150 - 7.1 2.0 3.1 0.8 0.0 0.3 0.0 0.3 0.4 0.0 1.8 0.0 0.1 8.9 30.9 13.1 ment Employ- Rural - 5.8 2.0 2.3 0.7 0.0 0.2 0.0 0.3 0.4 0.0 1.7 0.0 0.1 38.6 18.6 12.4 No. Units 1.5 5.4 2.4 0.5 0.4 0.1 2.5 1.3 0.0 0.0 5.0 0.6 1.8 69.1 14.1 28.8 18.7 ment Employ- Urban 8.7 0.9 3.2 1.6 0.3 0.2 0.1 1.4 1.0 0.0 0.0 3.7 0.5 1.3 61.4 30.1 17.0 No. Units 3.5 8.6 3.2 0.5 0.7 0.1 2.8 1.6 0.0 0.0 6.7 0.7 1.9 21.2 41.9 27.5 100.0 ment Employ- Total 2.9 5.5 2.3 0.3 0.4 0.1 1.7 1.4 0.0 0.0 5.4 0.6 1.3 14.5 48.7 29.4 100.0 No. Units - 1.0 0.2 9.8 0.1 1.4 2.0 62.0 95.9 25.3 10.7 11.5 54.4 949.1 216.4 402.9 271.9 ment Employ- Rural (‘000) - 0.4 3.5 0.1 4.9 6.7 0.1 0.8 1.0 36.5 42.3 13.7 31.4 712.2 107.2 343.1 228.5 No. Units 3.9 1.3 1.6 45.9 74.4 15.8 12.3 76.2 38.9 18.7 55.8 434.2 166.9 882.9 152.0 573.0 ment 2,119.6 Employ- Urban 4.7 4.3 1.2 0.9 0.4 9.6 16.2 59.3 29.0 26.7 19.3 68.0 23.5 No. 160.7 555.7 314.0 Units 1,132.8 4.1 1.3 1.7 99.7 16.7 22.9 86.1 50.3 20.2 57.8 650.6 107.9 262.8 206.4 844.8 ment 3,068.7 1,285.6 Employ- Total 5.1 7.8 1.3 0.9 0.5 52.6 41.9 31.6 26.0 99.4 10.4 24.5 268.0 102.0 899.0 543.0 1,845.0 No. Units HIES 87/87 i.e. SSE in manufacturing and other sectors - estimate of establishments with less than 10 workers HIES 1987/88. Total Manufacturing Food beverage Textiles, leather Wood products Chemicals Minerals Metals Fabric metals Others industries Utilities Construction Trade Catering Transport, storage communication Finance Services Table A5.10: Source:

151 Table A5.11: HIES, Non agricultural micro enterprises, 1990/91 (number and %)

Services Total Manuf. Trade Hotels Total Manuf. Trade Hotels Services and others

No. All Units 4,475 818 2,134 207 1,316 100.0 18.2 47.6 4.6 29.4

Fixed 3,367 777 1,610 166 814 75.2 17.3 35.9 3.7 18.1

Mobile 1,108 41 524 40 502 24.7 0.9 11.7 0.9 11.2

Urban 1,962 321 925 123 593 43.8 7.1 20.6 2.7 13.2

Rural 2,513 496 1,209 84 723 56.1 11.0 27.0 1.8 16.1

Average monthly income (Rs)

All Units 2,025 1,706 2,254 2,213 1,821

Urban 2,481 2,243 2,743 2,416 2,214

Rural 1,668 1,358 1,881 1,916 1,498

Density (Units/1000 Pop)

All Units 39.6 7.2 18.9 1.8 11.6

Urban 54.5 8.9 25.7 3.4 16.5

Rural 32.6 6.5 15.7 1.1 9.4

% Income share from SSE:

All Units 61 54.4 63.8 79.7 57.6

Urban 63 55.9 65.9 78.7 59.6

Rural 58.8 52.8 61.5 81.6 55.4

% Share of SSE's with all loans

All Loans 26.0 34.7 22.4 18.9 27.4

Urban 22.6 26.2 19.6 23.5 25.1

Rural 28.7 40.2 24.6 12.1 29.4

% Share of SSE's with commercial loans only

All Units 1.5 0.9 2.4 0.0 0.7

Urban 1.6 0.6 2.1 0.0 1.6

Rural 1.5 1.1 2.6 0.0 0.0

Average outstanding loan (Rs) Commercial only

All Units 74,046 200,000 64,510 54,323

Urban 51,711 18,937 18,987 12,007 16,474

Rural 90,967 200,000 73,051

152 Services Total Manuf. Trade Hotels Total Manuf. Trade Hotels Services and others

Average outstanding loan (Rs) Non-commercial only

All Units 12,953 12,340 14,233 9,725 12,269

Urban 17,611 18,937 18,987 12,007 16,474

Rural 10,129 9,432 11,425 3,572 9,467

Average income of (Rs/pm) SSE without any loans

All Units 2,086 1,738 2,326 2,238 1,837

Urban 2,567 2,327 2,854 2,443 2,243

Rural 1,677 1,268 1,895 1,979 1,484

Average income of (Rs/pm) SSE with only commercial loans

All Units 2,627 3,067 2,435 3,240

Urban 2,537 1,406 2,279 3,240

Rural 2,724 3,725 2,559

Average income of (Rs/pm) SSE with only non-commercial loans

All Units 1,796 1,607 1,950 2,103 1,724

Urban 2,148 2,022 2,288 2,330 2,026

Rural 1,588 1,432 1,752 1,461 1,531

Average employment of SSE without any loan

All Units 1.5 1.9 1.4 2.0 1.4

Urban 1.8 2.4 1.6 2.5 1.5

Rural 1.3 1.6 1.3 1.3 1.4

Average employment of SSE with only commercial loan

All Units 2.1 5.4 1.8 0.0 1.3

Urban 1.9 6.0 1.9 0.0 1.3

Rural 2.2 5.2 1.7 0.0 0.0

Average employment of SSE with only non commercial loan

All Units 1.5 2.1 1.3 1.5 1.3

Urban 1.5 2.0 1.4 1.6 1.3

Rural 1.5 2.1 1.2 1.2 1.3

Source: HIES (1990/91).

153 152 1.41 4.33 1.28 0.36 0.31 1.14 0.04 1.60 0.96 2.82 0.07 1.44 8.46 11.43 75.77 100.00 Value Added Percentage 3.42 3.01 0.71 0.52 1.43 0.09 3.37 1.70 0.19 2.29 26.18 11.92 34.89 10.92 25.52 100.00 ment Employ- 5.12 7.32 4.16 0.82 0.87 0.89 0.12 4.23 1.18 2.11 0.17 3.02 24.70 39.91 30.09 Asset Value 100.00 2.89 8.46 2.62 0.48 0.32 0.70 0.05 2.41 1.87 7.33 0.10 2.09 No 19.75 41.65 29.23 Units 100.00 0.89 0.53 1.13 0.59 0.83 0.67 2.47 0.68 0.72 1.56 3.64 2.56 0.86 0.91 0.54 1.91 Y/K Y/L (Rs) 22,597 21,442 18,801 28,477 10,124 20,726 27,001 24,000 24,523 29,297 13,383 20,000 32,619 17,153 51,742 112,439 K/L (Rs) 5,232 25,510 40,543 16,592 37,306 31,387 46,818 16,887 35,500 33,938 18,797 30,931 23,214 35,664 31,854 27,023 96 809 692 168 3,195 9,777 2,897 2,586 3,605 2,168 6,384 3,257 (Y) 25,829 19,126 (Mrs) Value 171,246 226,010 Added Profits or (Rs) 6,171 4,170 6,782 4,905 8,304 8,455 8,666 6,688 1,701 2,694 2,808 3,561 9,925 3,912 4,095 Mean Wage 10,521 4,039 8,424 4,368 31,429 22,589 62,541 74,055 99,847 149,634 520,530 131,504 147,278 477,146 (Million) (L) 1,143,602 1,523,855 1,115,040 Employment 973 142 195 6,041 8,637 4,906 1,030 1,047 4,989 1,391 2,496 3,561 (K) 29,159 47,108 35,518 Asset Value 118,037 (M.Rs) 9 6 1 2 54 49 13 45 35 39 369 158 778 134 546 No (000) Units 1,868 Small and medium sector characteristics (ISSMI) 1992-93 ISSM1, 1992/93. Manufacturing Food Textiles Wood Paper Chemicals Minerals Metals Metal Products Other Trade Hotels Transport Finance Services All Sectors Table A5.12: Source:

153 8 17 > 10 51 101 5-9 95 354 3-4 No. of Employees 647 115 2 750 101 1 (000) 6 8 5 0 0 4 12 % 7 0 0 30 42 23 112 ship Partner- 0 94 92 88 95 89 100 % Type of Firm 2 0 339 687 127 486 1,719 dual Indivi- torship proprie- 6 4 0 0 2 0 2 3 3 7 0 0 33 17 31 100 % 0 1 9 0 0 0 34 92 20 11 15 41 550 181 169 169 Rural 1 5 2 1 0 0 0 3 2 7 0 0 15 48 29 100 % 9 5 5 1 2 0 19 66 29 34 20 93 188 618 377 1,279 No. of Units Urban 3 8 3 0 0 1 0 2 2 7 0 0 20 42 29 100 % 9 6 1 2 0 54 49 13 45 35 369 158 778 134 546 1,829 Total Estimates of the medium and small-scale non-agricultural sector 1992-93, (ISSM1) ISSM1 (1992-93). All sectors Manufacturing Food Textiles Wood Paper Chemicals Minerals Metals Metal products Other Trade Hotels Transport Finance Services Table A5.13: Source:

154 Table A5.14: SSE Sector characteristics (ISSMI, 1992/93) (000)

Characteristics All sectors Manufacturing

Vintage 551

90's 205

Late 80's 113

Early 80's 93

Late 70's 58

Early 70's 21

60's 45

50's 12

Pre 1947 4

Period Worked 1,279

Full Year 1,264

Type of Work 1,868

Subcontracting Only 0

Asset Size (Rs.) 369

> 1000 85

1 - < 10,000 106

10,000 - < 50,000 73

50,000 - < 100,000 44

100,000 - <500,000 51

>500,000 11

Obtaining loans 23

Outstanding Value Rs.2,286M

Sources: Private 32

Landlord/Shopkeeper 22

Commercial Bank/Institution 18

Provincial Government 6

Source: ISSM1 (1992-93).

155 25,510 17,821 21,777 19,178 34,135 42,432 14,416 24,536 K/l (rs.) 0.023 0.022 0.016 0.020 0.027 0.034 0.025 0.021 Profit/ Labour (M.Rs.) 0.880 1.240 0.730 1.030 0.790 0.790 1.730 0.874 Profit/ Capital 0.060 0.020 0.030 0.070 0.200 0.400 1.800 0.060 Unit Profit/ (M.Rs.) 2,481 3,789 6,453 8,889 2,960 1,194 Value 25,768 21,614 Added (M.Rs.) Profit or 723 6,170 1,819 5,025 8,333 5,433 Mean 10,042 13,409 Wage (Rs.) 88,201 47,850 112,167 238,328 325,640 331,414 1,143,602 1,007,551 Employment 692 1,996 5,183 6,252 3,734 29,159 11,299 24,733 (M. Rs.) Asset Value 7 1 95 51 369 101 115 362 (000) Units No of. Small and medium sector characteristics by size, (ISSM1), 1992/93 ISSM1 (1992/93). Employment size (persons engaged) All Manufacturing 1 2 3-4 5-9 36456 >25 <10 Table A5.15: Source:

156 0.3 0.3 0.1 0.1 0.1 0.1 Joint Investment 2.6 0.4 0.3 0.5 1.5 0.5 1.3 0.6 0.1 Non-Banks Institutions 0.6 0.4 0.2 0.3 0.1 0.2 Coop Banks 0.1 0.1 0.1 Shares Banks Foreign Loans from financial institutions 0.7 1.2 1.9 1.0 7.7 9.8 0.9 0.8 0.1 0.5 0.3 12.5 Banks Pakistani 1.1 1.5 2.9 0.0 1.0 9.7 2.4 1.5 0.1 0.0 0.0 0.8 0.5 1.0 16.1 10.7 Total 8.2 9.9 0.4 1.3 2.6 3.9 0.4 8.5 24.1 18.7 80.5 11.2 16.7 10.4 144.7 100.8 Individuals 8.6 28.3 52.7 84.6 10.6 97.5 90.5 182.5 259.5 539.4 519.4 335.3 486.3 234.1 235.4 1,536.4 From Savings 9.0 30.6 55.5 88.5 11.0 191.7 269.8 566.5 629.8 364.8 569.2 247.1 252.9 108.3 100.0 Total Investment 1,697.3 Total (Rs. M) Investment Credit for the SSE sector All industries Land Buildings Plant Transport Other fixed assets Weaving Food, Beverage, tobacco Textiles, leather Wood and products Chemicals, rubber Minerals (non iron) Basic metals Fabricated metals Others All industries Table A5.16:

157 Table A5.17: Vintage of industries

No. of Units (000) % of Units Total Total units Pre- 1970- 1980- units Pre- 1970- 1980- 1970 1979 1988 1970 1979 1988

Total 1,844.9 263.1 256.4 1,325.4 100 14.3 13.9 71.8

Manufacturing 267.9 27.1 37.9 202.9 100 10.1 14.1 75.7

Food, beverages 52.6 6.4 10.5 35.7 100 12.2 20.0 67.9

Textile, leather 101.6 9.7 14.0 77.9 100 9.5 13.8 76.7

Wood 41.9 3.4 5.3 33.2 100 8.1 12.6 79.2

Chemicals 5.1 0.2 0.4 4.5 100 3.9 7.8 88.2

Minerals 7.8 2.2 1.4 4.2 100 28.2 17.9 53.8

Metals 1.3 0.1 0.1 1.1 100 7.7 7.7 84.6

Fabric metals 31.6 2.2 2.9 26.5 100 7.0 9.2 83.9

Other industries 26.0 2.9 3.3 19.8 100 11.2 12.7 76.2

Utilities 0.9 0.1 0.2 0.6 100 11.1 22.2 66.7

Constructions 0.5 0.0 0.1 0.4 100 0.0 0.2 0.8

Trade 898.7 80.5 134.2 684.0 100 9.0 14.9 76.1

Catering 99.4 7.7 12.5 79.2 100 7.7 12.5 79.2

Transport, storage 10.4 0.8 1.5 8.1 100 7.7 14.4 77.9

Finance 24.5 2.1 4.4 18.0 100 8.6 18.0 73.5

Services 542.5 144.7 65.5 332.3 100 26.7 12.1 61.3

Source: HIES (1987/88).

158 96.3 64.7 88.5 75.1 27.6 69.0 32.8 85.7 789.2 155.4 676.9 583.3 355.5 160.1 369.5 119.6 815.9 134.2 877.4 662.8 9,902.8 1,784.6 3,523.4 1,118.3 1,445.6 1,477.9 Value Added (Rs.m) 3.5 3.5 8.0 8.3 4.0 5.0 4.0 2.0 3.0 2.0 8.0 56.0 55.0 89.0 94.0 14.0 86.0 50.0 49.0 33.0 20.0 627.0 100.0 261.0 415.0 131.2 (000) Employment 1987/1988 79.0 68.1 85.9 57.8 27.8 26.1 81.2 54.1 20.6 37.6 18.4 17.7 700.7 962.9 224.7 139.5 155.0 822.8 397.6 400.6 387.4 324.9 Fixed 5,597.0 1,728.2 1,100.6 1,363.7 Assets (Rs.M.) 48.8 257.6 673.0 391.4 569.0 813.0 384.0 1,169.0 1,444.0 4,282.0 2,228.0 7,012.0 3,713.0 2,057.0 1,528.0 3,359.0 34,389.0 16,082.0 34,705.0 38,897.0 17,957.0 31,903.0 19,848.0 25,015.0 18,159.0 100,867.0 No. Units 82.3 74.5 21.3 41.3 23.5 53.1 739.1 308.4 659.6 171.6 446.2 179.5 813.5 107.5 441.5 823.7 248.0 165.1 117.5 818.7 627.0 9,368.9 1,894.2 2,993.8 1,187.8 1,440.2 Value Added (Rs.M.) 6.6 5.0 2.0 3.0 2.0 5.0 71.0 42.0 12.0 63.0 18.0 23.0 96.0 11.0 10.0 67.0 50.0 946.0 208.0 167.0 334.0 101.0 122.0 492.0 137.0 324.7 (000) Employment 1983/1984 67.1 81.8 88.0 26.7 29.9 85.8 16.0 18.3 35.2 17.0 30.2 372.9 398.3 841.8 160.8 272.5 958.2 441.7 161.9 121.6 374.4 287.5 6,736.2 3,000.5 1,271.4 1,165.5 Fixed Assets (Rs.M.) 39.8 25.0 575.0 928.0 500.0 229.4 3,751.0 4,450.0 1,844.0 3,022.0 5,758.0 5,196.0 4,913.0 86,774.0 40,149.0 12,466.0 39,861.0 59,186.0 17,807.0 10,432.0 67,927.0 51,530.0 40,297.0 32,830.0 426,457.0 149,088.0 No. Units - 9.5 76.7 62.4 94.0 51.2 25.4 30.0 24.4 69.5 23.1 19.7 24.0 296.5 202.8 190.0 269.1 113.6 191.5 131.3 465.3 212.4 183.3 148.4 2,599.6 Value Added 10,766.0 (Rs.M.) - 9.0 1.0 4.0 6.0 6.0 2.0 3.0 3.0 3.0 42.0 21.0 73.0 38.0 11.0 38.0 28.0 61.0 30.0 10.0 28.0 22.0 380.0 162.0 1,586.0 13,222.0 (000) Employment 1976/77 - 8.7 6.6 7.3 88.8 29.6 33.9 81.6 23.6 22.6 26.1 41.8 19.2 80.7 17.0 10.8 49.4 19.3 12.2 45.6 34.1 955.2 213.6 282.4 110.2 216.2 Fixed Assets (Rs.M.) - 108.6 201.0 589.0 771.0 851.0 628.0 480.0 3,793.0 1,317.0 6,965.0 9,833.0 7,284.0 3,070.0 1,688.0 3,832.0 2,123.0 9,060.0 5,305.0 3,312.0 9,611.0 10,042.0 46,709.0 14,643.0 18,395.0 11,100.0 No. Units SHMI Pakistan (rural and urban) The absolute values of the 3 surveys are not comparable because differing definitions Small-scale Mnufacturing for each. SHMI, (1976/77, 1983/84, 1988). Total value Food, beverage, tobacco Wheat milling Rice milling Oil expelling Textiles, leather Weavingstan Carpets Wood and products Furniture Chemicals, rubber Plastic products Minerals (non-metal) Pottery Bricks Fabricated metal Metal products Non electric machines Agricultural Machining Textiles Basic metals Iron found-aries Other Jewelry Sports goods share 1 2 3 4 5 6 7 8 Table A5.18: Note: Source:

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