Meeting International Targets in

Graham Eele, Joseph Semboja, Servacious Likwelile and Stephen Ackroyd*

This article considers the prospects for Tanzania in achieving the international development targets, especially those relating to reductions in absolute poverty. A key conclusion is that the analysis depends on how poverty is defined, in particular what poverty line is used and which data sets define the base line. There is no officially recognised Tanzanian poverty line and even the use of the international poverty line, of US$1 per person per day measured at purchasing power parities, presents difficulties because of the lack of recent reliable data on purchasing power parity. Despite substantial efforts in Tanzania in recent years to collect poverty-related data, the data sets are not directly comparable and there seem to be substantial inconsistencies in the methods used. Different surveys result in very different estimates of poverty levels and poverty growth elasticities. Considerable care is therefore required in interpreting the results of these surveys and further work is needed to improve the database before more precise statements can be made. Current best estimates suggest that sustained economic growth in the order of between 5 and 7% per year will be needed over the next 15 years if a 50% reduction in the numbers of people below the $1 per day poverty line is to be achieved. The key requirement is to reduce and this will require sustained investment in rural infrastructure and both intensification and diversification in agriculture. In terms of the other international development targets, the picture in Tanzania is mixed. There are reasonable prospects of reaching the targets, although there is concern about the quality of education. Gender disparities at the primary level have largely been eliminated already and progress is being made at higher levels. It is unlikely, however, that Tanzania will be able to achieve the targets for reductions in infant and child mortality. While there has been a reduction in mortality levels in the past twenty years, the rate of decline achieved so far is insufficient to reach the targets by 2015. Any increase in this rate of decline over the next 15 years will be difficult to achieve

*Graham Eele and Stephen Ackroyd are Senior Consultant and Economist, respectively, at Oxford Policy Management Ltd, Oxford, and Joseph Semboja and Servacius Likwelile are Director and Research and Training Coordinator, respectively, at Research on Poverty Alleviation (REPOA), Tanzania.

Development Policy Review Vol. 18 (2000), 63–83 © Overseas Development Institute 2000. Published by Blackwell Publishers, 108 Cowley Road, Oxford OX4 1JF, UK, and 350 Main Street, Malden, MA 02148, USA. 64 Development Policy Review especially in the light of the HIV/AIDS pandemic. While the detailed effect on mortality rates has still to be assessed, at the very least it will result in a slow- down in the rate of improvement.

Recent socio-economic record

By most indicators Tanzania is one of the poorest countries in the world. In 1999, it ranked 156 out of 174 countries in terms of overall human development (UNDP, 1999) and 172 in terms of real GDP per capita (1997 data, measured in purchasing power parity). Relatively, in Tanzania appears to be declining; for example, the ranking had dropped from 126 in 1992 to 144 by 1996 (see Table 1 for recent indicators).

Table 1 Recent indicators of human development in Tanzania

Indicators Overall Gender gaps Male Female Life expectancy at birth (1997) (years) 48 47 49 Adult literacy rate (1997) (%) 72 82 62 Gross enrolment ratio for all levels (1997) (%) 33 33 32 Net primary school enrolment rate (1997) (%) 47 46 48 Infant mortality rate (1996) (per 1,000 live 88 - - births) Under-five mortality (1996) (per 1,000 live 144 - - births) Maternal mortality rate (1996) (per 100,000) 592 - - Rural–urban gaps Rural Urban Population with access to safe water (1996) % 50 46 68 Population with access to services 38 22 98 (1996) %

Sources: UNDP (1999); Macro International (1996).

The period since independence can be conveniently divided into three phases: from independence in 1961 to 1979; an initial period of economic reforms from 1979 to 1986; and since 1986. These are discussed briefly below.

Policy environment and poverty post-Independence

Much of what came to characterise Tanzania’s policy environment in the immediate post-independence period stemmed from the Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 65 announced in 1967. The Declaration ushered in a new policy direction for the country, a break from the fairly orthodox economic policies followed during the first years of independence, with the emphasis being placed on the role of villages in rural development. The new policy also emphasised public ownership of the means of production. This meant that, in effect, individual initiatives and the role of the private sector were sidelined, placing responsibility for the country’s development in the hands of the public sector. Tanzania was thus to be guided by a socialist ideology, the main objective of which was to build an egalitarian society with the being driven by a strong public sector. Major initiatives were instituted, including widespread nationalisation of key economic sectors, relocation of the rural population through a villagisation programme launched in 1973, and administrative control of markets, including setting of pan-territorial prices at the producer level. These policies had important implications. Producer prices and the exchange rate were set at levels that involved high and rising implicit taxation of rural cash incomes. The suppression of private business both reduced the opportunities for peasants to diversify as producers and increased the prices they faced as consumers. The combination of price controls, import controls, and investment in industry led to increasingly severe shortages of non-agricultural consumer goods in the rural areas. Also notable was the fact that increases in crop prices on world markets were not passed on to farmers (Bevan et al., 1988). The policy environment also had an effect on the urban self-employed, although less directly than on the peasants. Government attempts to protect the living standards of urban wage earners led to the maintenance of real wages that were well above peasant incomes. As a result considerable rural-urban migration ensued, with a rapid growth of the informal sector and a corresponding fall in the incomes of the self-employed (Bevan et al., 1988). The expanded role of the state also led to higher government expenditure and attendant fiscal deficits. All these policy measures had implications for poverty. For one thing, the participation of peasants and the urban self-employed in income-generating activities was inhibited, with a consequent narrowing of the range of income sources having a negative impact on rural and urban agents’ scope for getting out of poverty. The current policy stance, following the reforms, acknowledges this weakness. The internal causes of poverty cited in the National Poverty Eradication Strategy (NPES) include mistakes in domestic policy (URT, 1998). The implementation of policies that failed to promote economic growth, gave insufficient support to the agricultural sector and rural industries and disrupted local institutions is acknowledged in the NPES as being one of the major factors behind the persistence of poverty in the country. The present stance is geared towards the enhancement of people’s participation in the management of the economy. 66 Development Policy Review

The initial period of reform and the reforms since 1986

Starting in the early 1970s Tanzania experienced a series of economic shocks, culminating in a crisis towards the end of the decade.1 Macroeconomic performance faltered, the social and physical infrastructure deteriorated rapidly and the delivery of social services was endangered. Between 1979 and 1985, therefore, a number of major policy initiatives were taken to address the economic decline, but in general these failed to deal with the deep-seated structural problems. The lack of policy agreement with the international financial institutions resulted in a substantial reduction in the flow of both investment and aid funds (Collier, 1991). The period since the mid-1980s has seen gradual, but fundamental, macroeconomic reforms, focusing on trade and exchange-rate liberalisation, the removal of restrictions on the activities of the private sector, reduction in the role of the state and price liberalisation. Subsequent stages of the reform process have given more attention to the impact on the poor and have laid particular emphasis on the delivery of basic social services (Semboja, 1995). This process has been accompanied by political changes, in particular the move to a multi- party democracy in 1995. The reform programme has registered positive results in the areas of growth, price stability and availability of consumption goods and services. In spite of these achievements, however, there are concerns that poverty is worsening (Ndulu and Wangwe, 1997).

The poverty situation

One of the features of the post-reform period has been the concern that poverty, in both urban and rural sectors, has increased. The debate within Tanzania is not conclusive, however. Analysis of some surveys suggests that there has been growth of average income and expenditure over the last decade and that the incidence of poverty has declined. There is, however, some conflicting evidence on the ultra-poor (Semboja and Bol, 1997; Wangwe, 1996). Structural problems and policy biases against the agricultural sector have had an effect on the rural poor, the rural population being estimated to constitute the majority (about 92%) of the poor (Globevnik, 1997). Most recent data seem to suggest a slight increase in urban poverty (from 1993 to 1995), both proportionally and with regard to absolute numbers; the figures are below those

1. A series of adverse events took place including: the budget mini-crisis in 1971–72; the first world oil price shock in 1973–4; major drought in 1974–6; villagisation disruptions to the economy in 1974–6; the break-up of the East African Community (EAC) in 1977; the second oil shock in 1978–9; the war with in 1979-80; and the world recession in 1979–82 that depressed export prices for Tanzanian exports while raising import prices. The coffee price boom of 1976–7 was short-lived and insufficient to promote any significant sustained recovery. Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 67 of 1991, however (Semboja and Bol, 1997). Although food (consumption) poverty and lack of access to social infrastructure are important in urban areas, studies document that rural Tanzania performs significantly worse than its urban counterpart with respect to income and social indicators (Globevnik, 1997), something which makes the rural sector a priority for poverty-targeting purposes. Overall, however, recent poverty studies show the level of poverty to be low in the 1990s compared with the early 1980s. The trend has not been unidirectional (Semboja and Bol, 1997; Ferreira and Goodhart, 1995). Demery and Squire (1996) show that the share of the population in poverty (headcount index) fell by 14.1 percentage points in the eight years 1983–91. They attribute this change to the joint impact of changes in mean income (inequality held constant) and in inequality (mean income held constant). There has, however, been a decline in the spending of the poorest of the poor, suggesting that the poorest 10% of the population were noticeably worse-off in 1991 than in 1983. Much needs to be done in terms of research and analysis to unravel the puzzles surrounding the poverty situation in the country. This is predicated on having in place high quality data, namely data based on actual observation of individuals drawn from household surveys, representative samples covering all of the population and comprehensive coverage of different income sources as well as population groups (Deininger and Squire, 1996).

Local and international development targets

The government of Tanzania subscribes fully to the global goals of eradicating poverty and alleviating the social conditions of the poor in terms of health, education, gender balance and preservation of the environment. The country participated in the various international meetings at which goals were agreed and, amongst other initiatives, the government has issued The National Poverty Eradication Strategy, a policy document which spells out ways and approaches to poverty eradication (URT, 1998). The NPES sets a national target of reducing absolute poverty by 50% by 2015 and eliminating it completely by 2025, although it does not formally define what is meant by absolute poverty. Universal primary education is another long-established policy goal, for both boys and girls. A key issue recently has been the perceived quality of education received by children in the public system and value for money since the introduction of cost-sharing. Formal targets have not been set for health, although Tanzania is a signatory to targets established by various international conferences. In relation to , a National Environmental Policy was promulgated in 1997, preceded by a National Environment Action Plan (NEAP) prepared in 1994. That there are not fully articulated national targets in all the areas identified 68 Development Policy Review under the IDTs does not imply that the government and other elements of society are unconcerned about poverty and human development issues. Rather, the concerns and specific targets are set in the context of what is important in Tanzania. Even though the government has participated in international conferences where targets were agreed, it is inevitable that local concerns should predominate. The value of the targets, therefore, lies more in helping to focus attention on issues and on facilitating comparison with other countries rather than including them formally as part of national policy. Tanzania’s national priorities differ in a number of ways, although is a key concern. In relation to the human development targets, other issues are given prominence including AIDS, and child nutrition. Gender equality is seen as a broader concern than simply access to primary and secondary education.

Feasibility of achieving the poverty targets

Data availability

Despite considerable information in Tanzania for assessing progress and future prospects for the various IDTs, detailed analysis is hampered by the lack of consistent time series data. This is particularly problematic in the estimation of elasticities and rates of change, and places significant limitations on the calculation of trends. Forecasting is also constrained by the fact that most parts of the economy have undergone fundamental structural change over the past ten to fifteen years.2 It is questionable, therefore, even if reliable and consistent time series data were available, whether key coefficients and elasticities based upon these data could be considered as valid and robust for predicting the future. For most targets, especially those on poverty, mortality rates and reproductive health, the main sources of data have been household surveys carried out on an ad hoc basis. Where data are thought to be consistent over time, or at least derived from surveys using the same design, average annual rates of change have been calculated. Elsewhere, key elasticities have been calculated analytically from separate surveys. Simple simulation models have then been used to illustrate the effect of alternative assumptions about growth in economic output and incomes and other independent variables. The analysis identifies the levels of change required in the key determinants in order to achieve the targets by 2015. These changes are then used to determine average annual rates of change, which can be compared with recent experience and may

2. The main changes have been in the role of government and the liberalisation of both internal and external markets. Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 69 be related to specific policy choices. Information on poverty and incomes in Tanzania can be derived from the data collected from seven different household surveys carried out between 1983 and 1999.3 Comparison between surveys, however, is complicated by the differing methodologies, definitions and populations covered. For some surveys only the summary results are available, for others household-level data have been accessed. Because of measurement problems, as well as theoretical considerations (Deaton, 1997), much of the earlier analysis has concentrated on using total household expenditure to look at poverty. This is the approach that has been followed here. Particular problems occur in Tanzania in estimating total expenditure, because of the relative importance of non-monetary transactions, especially in rural areas where a substantial proportion of the household expenditure results from non-monetary transactions.4

Comparing survey results

Table 2 summarises results from the different surveys and illustrates the considerable variation between the surveys, for example in terms of mean incomes per adult equivalent, and in measures of inequality and the poverty lines used. A further problem relates to the small sample size used for all but the CBS 1991/2 and 1993 surveys. While sample sizes of at least 5,000 are required for the disaggregation of national data by region, smaller

3. a) A 1983 rural household survey involving just over 500 (World Bank, 1996). b) A 1991 household survey of 1,100 households in mainland Tanzania carried out jointly by the Cornell Food and Nutrition Policy Programme and the Economic Research Bureau (ERB) of the University of (Tinios et al., 1993). c) National household budget surveys (HBS) of over 5,000 households carried out by the Central Bureau of Statistics (CBS) in 1976 (published) and 1991/92 (unpublished). d) A World Bank Human Resources Development (HRD) survey of over 5,000 households carried out in 1993 (World Bank, 1996). e) 1995 World Bank Social Capital and Poverty Survey: a participatory assessment of poverty resulting in the publication, Voices of the Poor. While this study concentrated on finding out what the perceptions of the poor were on their own condition, it did also collect some quantitative information using the same methods as the HRD survey. f) Two separate household budget surveys carried out by REPOA in 1998, the first of 150 households in the peri-urban areas around Dar es Salaam; the second of 649 households from the regions in rural mainland Tanzania. These surveys used the same data collection methods as the 1993 HRD survey. Both data sets were available for analysis. 4. To be complete, and to ensure comparability between households, total expenditure should include: a) the imputed value of own production consumed in the household; b) the imputed value of transfers received in kind; and c) the imputed value of other items received in kind (e.g. in barter). 70 Development Policy Review sizes are reasonable for national estimates of variables such as mean income or expenditure. However, as none of the published results include any estimates of sampling error, it is necessary to view the results with caution.

Table 2 Summary poverty measures derived from various household surveys

Source World Cornell – CBS World World REPOA Bank ERB Bank Bank Date 1983 1991 1991/92 1993 1995 1998 Coverage Rural Mainland Mainland Tanzania Rural Rural & Peri-urban DSM Sample size 498 1,041 4,862 5,184 768 797 (Households) Mean income per 225,382 391,693 815,600 household (Tsh) Mean income per 62,932 77,240 183,162 177,742 adult (Tsh) 0.52 0.43 0.62 0.41 0.52 0.45 Ratio of income 24.9 6.2 10.1 accruing to top and bottom quintiles Proportion of 2.7% 5.0% income accruing to bottom quintile Proportion of 67.0% 45.4% 50.6% income accruing to top quintile Poverty line 2,491 23,039 25,431 35,181 95,168 (Tsh) (US$1 PPP) Poverty line 3,801 35,159 38,810 53,688 145,232 (Tsh) (REPOA/CBS)

Notes: (i) Mean income and poverty lines are calculated using current prices (ii) Poverty lines are in Tsh per adult equivalent per month.

For the two surveys where household level data are available, namely, the 1991/2 CBS household budget survey and the 1998 REPOA survey, there appear to be important differences in measures of inequality and of mean incomes. For the purposes of this study the 1998 REPOA surveys were used, with particular attention being given to the rural sample as poverty in Tanzania is primarily rural (World Bank, 1996). Preference for the REPOA surveys, aside from their being the most recent, relates to their methodology, which is the same as that used for the 1993 HRD survey and the household survey component of Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 71 the 1995 Social Capital and Poverty Survey. Care should be used in interpreting the results from the REPOA surveys, however, both because of the small sample size and hence larger sampling errors and because the rural survey covered only three regions. It is difficult to assess the reliability of the 1991/2 CBS survey; however, a priori its results do not appear consistent with those of other surveys, particularly the estimates of inequality which seem too high to be seriously credible. More work is required to review the data from this survey.

Poverty lines

A key issue for poverty analysis is the choice of a poverty line. Studies have derived a variety of alternative poverty lines for Tanzania (the Cornell-ERB study derived a value of 46,173 Tsh in 1991 prices; the 1999 World Bank study used 73,877 Tsh in 1993 prices; an earlier ILO study used a figure of 31,000 Tsh in 1991 prices — equivalent to 63,240 Tsh in 1994). The methodology by which these poverty lines have been derived, while not always clear, generally derives from different choices of commodities for a basic needs basket and by differences in pricing. Within Tanzania there is, as yet, no official poverty line, although REPOA have recently carried out some analysis based on the data from the 1991/2 survey (REPOA, 1998). This is based on the estimation of the cost, nationally, of a basic food basket, using the consumption patterns of the lower income groups. In 1994, this procedure led to a poverty line of 71,426 Tsh per adult equivalent per year, which has been used in the present study, using the consumer price index as published by CBS to deflate prices where required. Although this poverty line has yet to be adopted officially by the Tanzanian Government, it is increasingly being used in official documents and in the analysis of national poverty targets. This is largely because of clearer understanding and agreement on how the study’s poverty line has been derived (as opposed to the earlier poverty lines), and because it has been developed locally. To ensure comparability with the global component of the study, the present analysis includes a poverty line equivalent to US$1 per adult equivalent per day in 1985 prices using purchasing power parities (PPP). However, price data to calculate PPPs are not available for all the years for which there are survey data. Two sources of PPP conversion factors were identified: the World Bank database (Deininger and Squire, 1996) and the Penn World Tables (Heston and Summers, 1991). The former provides a single conversion factor from Tanzanian shillings to US dollars for 1993. The latter provides percentages of official exchange rates for 1985, 1986 and 1987. PPP conversion factors for other years are derived by a Tanzanian deflation factor based on the consumer price index and by estimated US dollar inflation for the appropriate periods. In relation to the World Bank database, while Tanzania participated in the 72 Development Policy Review

International Comparisons Project (ICP) during the 1980s and early 1990s, and purchasing power parities were calculated for all the main components of the national accounts for 1993, time did not permit a full reconciliation of the ICP data with the PPP conversion factors provided in the database. The Penn World Table rate for 1985 is based on the PPP for private consumption as set out in the national accounts. While it is assumed that the World Bank figure for 1993 is derived similarly, the database is not sufficiently documented to confirm this. For these reasons, the present analysis uses the Penn World Table data as the best comparison with the REPOA findings (see Table 3).

Table 3 Estimated poverty lines in Tsh per adult equivalent per year

REPOA/ CBS US$1 PPP (1994) (Penn, 1991) 1985 6,810 5,877 1990 27,319 23,575 1991 35,159 30,341 1992 42,840 36,969 1993 53,688 46,331 1994 71,426 61,638 1995 91,698 79,131 1996 110,940 95,737 1997 128,757 111,112 1998 145,232 125,330

Trends in poverty and inequality

Because of problems in reconciling results from different household surveys, it is difficult to identify trends in the incidence of poverty or in the level of inequality in Tanzania. Table 4 reproduces data extracted from Table 2, giving estimates of the Gini coefficient and the poverty headcount ratio, based on surveys from 1983, 1991 and 1998. The results from 1983 and 1991 are reported by the World Bank (1996) and are the same as those reported by Demery and Squire (1997). The 1998 results were calculated directly from the household data using the rural component of the REPOA sample. These data appear to indicate that the level of poverty as measured using the poverty headcount ratio has declined over a fifteen-year period from 0.65 in 1983 to 0.43 in 1998, representing a one-third reduction in the incidence of poverty. This is offset, however, by annual population growth of 2.8% over the same period (Bureau of Statistics), which suggests that the number of people Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 73 living below the poverty line in 1998 was very much the same as in 1983.

Table 4 Trends in poverty and inequality

World Bank World Bank REPOA 1983 1991 1998 (Rural) (All Tanzania) (Rural) Gini Coefficient 0.52 0.41 0.46

Poverty Headcount Ratio (P0) 0.65 0.51 0.43

The data also suggest that there has been some change in the level of inequality as measured by the Gini coefficient, with the coefficient declining from 0.52 to 0.41 between 1983 and 1991. This means that, over this period, Tanzania moved from being a high inequality country to a low inequality country (using the classification from the global study, Hanmer and Naschold in this volume). This trend was also identified by the World Bank in its 1996 study. More recently, however, the data show a worsening in the level of inequality, with the Gini coefficient increasing to 0.46 in 1998. The earlier period represents a time of economic stagnation in Tanzania, when incomes were severely constrained, which supports the conclusion that inequality declined. More recently, however, under the influence of reform and structural change, the economy has begun to grow again, albeit slowly. Given limited access by the poor to the benefits of these reforms (FSG, 1993), it is plausible that inequality has subsequently increased. For the purposes of the IDT for poverty, the level of poverty in Tanzania in 1991 represents the base line from which the headcount ratio should be reduced by 50% by 2015. Using the results from the Cornell-ERB survey as the baseline, since there are no direct data for 1990, this implies that the level of poverty should be reduced from 51% to about 25%. The higher REPOA/CBS poverty line results in a headcount ratio of 56% for 1998, implying a target ratio of less than 30% by 2015.

Poverty elasticities

Changes over time in the level of poverty can be broken down into changes in average incomes and changes in the distribution of these incomes (Ravallion, 1997). In line with the global study, therefore, we estimate elasticities of poverty (as measured by the headcount ratio) with respect to changes in mean income and in the Gini coefficient. Because of the lack of consistent time series data, it is not possible to estimate elasticities econometrically. Instead, the two elasticities are calculated directly from the survey data. Mean income poverty elasticities are calculated from the 1998 data set using two methods of calculation. The first uses household-level data to calculate the 74 Development Policy Review elasticity directly from the cumulative distribution function (CDF) of per capita incomes.5 The second uses the World Bank POVCAL programme on 20 equal groups with 5% of households in each. The results from this exercise are shown in Table 5, which also includes some elasticities calculated by the World Bank from the earlier surveys.

Table 5 Poverty elasticities with respect to changes in mean income

REPOA 1998 Rural Survey

World Bank US$1 (REPOA) REPOA/CBS 1993 HRD Survey Direct POVCAL Direct POVCAL Poverty line 73,877 125,330 125,330 145,232 145,232 (Tsh) Headcount 40 61 55 68 64 ratio (%) Elasticity -2.3 -0.87 -1.09 -0.53 -0.89

Poverty elasticities vary depending on the shape of the CDF. The elasticity derived from the World Bank 1993 HRD survey is because of the low poverty line, which is located close to where the CDF slope is greatest. At the higher poverty lines (REPOA, 1998), the CDF slope is much less and consequently the elasticities are relatively smaller. The elasticities derived from the higher poverty lines are of the same order of magnitude as those estimated from the global study for sub-Saharan Africa. There is also some variation between the elasticities calculated directly from the household data and those derived by POVCAL from the grouped data. It is not clear exactly why this might be the case, but, a priori, since the household data estimates are based on more information, they may be considered to be more reliable. The POVCAL estimates appear to reduce the effect of changing the poverty line as the range of elasticities for the different lines is much less than for the direct calculations.6 Table 6 shows the elasticity of the headcount ratio with respect to changes in income distribution as measured by the Gini coefficient. The World Bank 1993 HRD survey reports an elasticity in excess of 3. For the REPOA 1998 rural

5. The elasticity is a function of the slope of the CDF. This was estimated by fitting a quadratic function to the curve in the neighbourhood of the poverty line. 6. Curiously, this effect seems to be reversed for the headcount ratio. Elasticities calculated by POVCAL are more sensitive to changes in the poverty line than those estimated directly from household data. Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 75 survey, the estimates vary with the poverty line chosen, but are less than 1. For the highest poverty line, the elasticity is very close to zero. This means that as the majority of people are classified as poor using this line, changes in income distribution have little or no impact upon poverty levels.

Table 6 Poverty elasticities with respect to changes in income distribution

REPOA 1998 Rural Survey World Bank 1993 US$1 (REPOA) REPOA/CBS HRD Survey Poverty line (Tsh) 73,877 125,330 145,232 Gini coefficient (%) 41 45 45 Elasticity 3.5 0.24 0.05

Prospects for reductions in poverty by 2015

Our analysis estimates expected levels of poverty in 2015, with alternative rates of growth in average incomes starting from different positions, based on the different poverty lines and different estimates of the poverty elasticities. The analysis is based on growth in incomes alone and assumes no change in income distribution. The four alternative starting positions are derived from the two different poverty lines and the two poverty elasticities calculated from the household and the grouped data respectively (Table 7).

Table 7 Expected poverty levels in 2015 with alternative simulations and different growth rates in average per capita incomes

Simulations Av. annual growth rates in per capita income 0.5% 1.0% 1.5% 2.0% 2.5%

US$1 (Penn) poverty line, 56.0% 50.9% 45.5% 39.5% 33.1% elasticity -0.87, target rate of 33 % by 2015 US$1 (Penn) poverty line, 49.6% 43.9% 37.7% 30.9% 23.7% elasticity -1.09, target rate of 30 % by 2015 REPOA/CBS poverty line, 64.3% 60.9% 57.2% 53.1% 48.8% elasticity -0.53, target rate of 38 % by 2015 REPOA/CBS poverty line, 58.5% 53.1% 47.2% 40.9% 34.0% elasticity -0.89, target rate of 35 % by 2015 76 Development Policy Review

Prospects for meeting the IDTs in Tanzania depend crucially on the poverty line chosen and the elasticity of poverty incidence with respect to changes in mean incomes. With the lower poverty line and the higher elasticity (simulation 2), growth of just 2% per year in per capita incomes would be sufficient to meet the target. With the higher poverty line and the lower elasticity (simulation 3), growth of 2.5% per year in real per capita incomes would not be sufficient to meet the target. In this case, per capita growth of almost 4% per year would be required (not shown in the table). Depending on the poverty line chosen, therefore, real growth would need to be between 2% and 4% per capita per year to achieve the poverty target. The second part of the analysis examines the effects of changing income distribution, keeping average incomes constant (Table 8). Since the distribution elasticities are absolutely less than those for mean income, the impact of relatively small changes on poverty outcomes is limited. The table shows the effect of an increase in the Gini coefficient (a worsening of inequality) as well as the effect of a decrease.

Table 8 Expected poverty levels in 2015 given different changes in income distribution

Simulation Annual percentage change in Gini coefficient 1.0% 0.5% 0.0% -0.5% -1.0% -1.5% -2.0% US$1 (Penn) 57.3% 56.0% 54.9% 53.8% 52.8% 51.9% 51.1% poverty line REPOA/CBS 64.1% 63.8% 63.5% 63.2% 63.0% 62.8% 62.6% poverty line

The final part of the analysis is to combine the two effects into a single model (Table 9). Here, we estimate the level of growth in mean incomes required to reduce absolute poverty by 50% by 2015, given different scenarios for the starting position and changes in income distribution. The different scenarios are as follows: 1. Starting from the US$1 (Penn) poverty line and the larger elasticity estimate, combined with a 1% year decrease in the Gini coefficient (this implies a decline in the Gini coefficient from 0.46 to 0.39). 2. As for 1., but using the lower elasticity estimate. 3. Starting from the REPOA/CBS poverty line and the higher elasticity estimate, combined with a 2% per year decrease in the Gini coefficient (this implies a decline in the Gini coefficient from 0.46 to 0.32). 4. As for 3., but using the lower elasticity estimate. Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 77

Table 9 Level of annual growth in average per capita incomes required to reduce poverty by 50% by 2015 from different starting scenarios

Scenario Annual change in Annual per capita Gini coefficient income growth required to meet poverty target 1. US$1 (Penn) poverty -1.0% 2.5% line, elasticity –1.09, target rate of 30 % by 2015 2. US$1 (Penn) poverty -1.0% 2.6% line, elasticity –0.87, target rate of 33 % by 2015 3. REPOA/CBS poverty -2.0% 2.7% line, elasticity –0.89, target rate of 35 % by 2015 4. REPOA/CBS poverty -2.0% 3.9% line, elasticity –0.53, target rate of 38 % by 2015

Reaching the human development goals

The current rate of primary school enrolment is low, with a net enrolment ratio of 57% in 1997, although gross enrolment ratios are much higher (Lawson et al., 1999). In order to meet the goal of universal primary education, enrolment will need to increase by 5% per year. This is achievable, provided there are increased real levels of expenditure. In terms of gender equality in education, at least in enrolment, Tanzania has already met or is very close to meeting the targets. A key issue for education, however, concerns the maintenance of quality as well as quantity. There are indications that low enrolment ratios reflect a perception of falling standards and growing disenchantment with the quality of the public education system. It is thought unlikely that Tanzania will meet the goals on infant, child and maternal mortality. If present trends can be maintained, infant and child mortality may be expected to decline by about a third by 2015. The main concern is the future progress of the HIV/AIDS pandemic. Any major increase in infection and in AIDS cases is likely to result in a slowing down of this decline. Progress is being made on access to reproductive health care for both men and women. It is expected that demand for contraceptive services will be met by 2015. More action is needed, however, to improve the coverage of maternity services. 78 Development Policy Review

Prospects for poverty reduction in Tanzania

Achieving the international poverty target requires annual per capita income growth of between 2.5 and 3.9 %. With the population in Tanzania expected to increase annually by 2.8 %, the economy will need to grow on average by between 5.3 and 6.7% per year for the next 17 years. This is substantially higher than has been achieved over the past 15 years, although since this period has been one of structural change it may not be representative of what will happen in the future. Between 1995 and 1997 the economy grew at a rate of about 3.7%, which is 1.6 % less than the lowest level that will need to be sustained in the future. A key issue in looking at prospects for sustained growth in Tanzania is the extent to which the economy is vulnerable to negative exogenous shocks (Clay and Benson, 1998). Past experience suggests that, over a seventeen-year period, Tanzania may expect two or three severe shocks to the economy, from exogenous effects such as climatic events (primarily drought, but also floods and severe storms) and rapid changes in world markets especially for coffee and minerals. The effects of these shocks may be limited in duration, but substantial in any given year. To examine the impact of such shocks on projected growth, it is assumed that there are two major shocks to the economy that have the effect of reducing growth to zero in the year of impact and halving the growth rate the following year (Table 10). While it is technically possible for the to grow by 6 % per year or more, the major question is whether this can be sustained. In recent years, few countries in sub-Saharan Africa have been able to grow at this rate, the major exceptions being Botswana and Uganda.

Table 10 Required average rate of growth in the ‘normal’ years to achieve the poverty target

Required Average Growth Growth Rate Needed in Rate Normal Years 3.0 % 3.7% 4.0 % 4.9% 5.0 % 6.1% 6.0 % 7.3% Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 79

Growth prospects and policy choices

The analysis described above indicates that economic growth, and, in particular, growth in average household incomes, is the main driving force for poverty reduction. Although the evidence on the size of the poverty/growth elasticity is mixed, the data for Tanzania suggest that growth in incomes results in a larger impact on poverty than similar sized changes in income distribution. This does not imply that inequality is of no consequence, but rather that substantial levels of real per capita growth, sustained over a fifteen-year period, are needed if absolute poverty in Tanzania is to be addressed. In making any assessment of the prospects for sustained growth between now and 2015, it must be recognised that between 1985 and 1999 per capita GDP only increased at an average 0.4 % per year. While historic rates of growth will clearly be insufficient to meet the international poverty target, even with large reductions in income inequality it has to be recognised that this period includes very different policy environments. The principal issues concerning poverty reduction in Tanzania are therefore the policy framework required to stimulate and sustain historically high levels of growth and how growth can be structured in order to achieve the greatest impact on poverty levels. The global study (Hanmer and Naschold in this volume) suggests that, for a given level of income, poverty should be lower where: inequality is lower; the economy is more open; investment grows faster than the labour force; capital is used more efficiently; and productivity in agriculture rises faster than in the modern sector. In relation to these policy conditions, the prospects for sustained economic growth in Tanzania are better now than for some considerable time past. The process of economic reform and adjustment has resulted in a more stable and conducive macroeconomic environment; internal imbalances have been addressed, inflation is under control and the budget deficit is at manageable levels. By most measures the Tanzanian economy is already fairly open, restrictions on foreign exchange have been removed and the exchange rate is market-determined. Administrative regulation of imports and exports has been largely replaced by tariffs and Tanzania is committed to a gradual reduction in tariff levels. Growth and poverty reduction will depend on the country's capacity to attract both aid flows and private direct investment. Mobilisation of domestic savings is hampered by the underdeveloped state of the financial institutions and the lack of financial markets in rural areas. Given the scarcity of capital, it is important that it should be employed as efficiently as possible. In general terms this means that investment should be used to complement labour-intensive production techniques. Since by far the greatest amount of poverty is located in the rural areas, there is a need to prioritise capital spending towards linking rural communities with markets through the development of rural infrastructure 80 Development Policy Review and communications networks. The World Bank (1996) identified in particular the importance of the interaction between investment in education, especially for women and girls, and improved infrastructure. Given that most poverty is rural-based, that growth in rural incomes has a much greater impact on poverty than similar growth in urban areas, and that most rural communities depend on agricultural activity for their livelihoods, it seems clear that effective poverty reduction must involve increases in agricultural productivity. There is considerable potential for both diversification and intensification of agriculture in many areas (FSG, 1993), but it is essential that any strategy for agricultural development should take into account the immense variation in resource endowment and agro-ecological conditions from area to area. In some areas, for example, the potential for agricultural-led growth is limited by poor soils, lack of water, a fragile resource base and inadequate communications. For many people in these circumstances the only feasible option is migration in order to seek employment elsewhere. It is important therefore that emphasis should continue to be placed on employment creation and actions to strengthen the working of the labour market. There is some evidence that, even when average incomes have increased, especially poor and disadvantaged groups have been unable to benefit. It will be important to ensure that policies are in place to provide an adequate safety- net for such people. Finally, growth and investment will need to be maintained, given Tanzania’s vulnerability to exogenous shocks. All institutions will need to develop the capacity to anticipate and manage change, rather than reacting to crises. In particular, it will be important to strengthen financial organisations to provide private sector mechanisms for sharing risk and smoothing income and consumption flows.

Conclusions

The extent to which poverty in Tanzania can be halved by 2015 depends on the initial choice of poverty line and the prospects for future growth in incomes. Analysis suggests that growth in average incomes of between 2 and 4% per capita per year over the period since 1998 would result in a halving of absolute poverty by 2015. Conditions for sustained growth are moderately good, but will depend on continued flows of aid and private investment and action to reduce debt. Effective poverty reduction will require broad-based growth in the rural areas. Although a number of household surveys have been completed in recent years, detailed analysis is hampered by inconsistencies in data collection techniques, coverage and definitions. It is recommended that some effort be expended to see if the differences between the major surveys carried out in recent years can be reconciled. If possible, a database of survey data with Eele, Semboja, Likwelile and Ackroyd, Meeting Poverty Targets in Tanzania 81 information at the household level should be developed.7 To a large extent, the Tanzania case study supports the main conclusions of the global study, especially the results of the models derived for sub-Saharan Africa. There are, however, some important caveats. First, the global data set often masks shortcomings with the cross-sectional modelling. For many countries — and Tanzania is no exception here — reliable time series data are largely lacking. The global data sets contain information that is partial, inconsistent and based on incomplete information. It is important, therefore, to interpret the results from these models with considerable care in order to ensure that what is being reported is not just an artifice of the data, or perhaps reflects the assumptions made in collecting the data set. Secondly, Tanzania has a unique growth path, which has been determined by its resource endowment, previous political and economic experience and unique processes of economic reform and . Cross-section analysis may be misleading in this respect as it assumes that countries are simply at different points on the same growth path. This is a particular problem in sub- Saharan Africa where many countries have been through, or are still in the midst of, a process of structural transformation. Thirdly, the variables included in the global model need to be interpreted with care. At the national level, microeconomic relationships and structures are often as important as the macroeconomic environment in determining the achievement of development targets. At the global level it has not been possible to build this level of detail into the model, but this does not mean that it is unimportant. In Tanzania, for example, a key factor inhibiting growth is the undeveloped financial sector; investment, especially in the rural areas, is hampered by the lack of processes for mobilising savings and investment and for managing shocks. Fourthly, the global models assume a process of linear change. Tanzania, in common with many other small, open , is vulnerable to exogenous shocks. Any projection should be made in the light of known risks and should take account of the effect of these shocks.

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