4706066

IFPRI Discussion Paper 01747

August 2018

Agricultural Growth, Efficiency, and Family in

Alejandro Nin-Pratt

Environment and Production Technology Division INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE The International Food Policy Research Institute (IFPRI), established in 1975, provides research-based policy solutions to sustainably reduce poverty and end hunger and malnutrition. IFPRI’s strategic research aims to foster a climate-resilient and sustainable food supply; promote healthy diets and nutrition for all; build inclusive and efficient markets, trade systems, and food industries; transform agricultural and rural economies; and strengthen institutions and governance. Gender is integrated in all the Institute’s work. Partnerships, communications, capacity strengthening, and data and knowledge management are essential components to translate IFPRI’s research from action to impact. The Institute’s regional and country programs play a critical role in responding to demand for food policy research and in delivering holistic support for country-led development. IFPRI collaborates with partners around the world.

AUTHORS Alejandro Nin-Pratt ([email protected]) is a senior research fellow in the Environment and Production Technology Division of the International Food Policy Research Institute, Washington, D.C.

Notices

1 IFPRI Discussion Papers contain preliminary material and research results and are circulated in order to stimulate discussion and critical comment. They have not been subject to a formal external review via IFPRI’s Publications Review Committee. Any opinions stated herein are those of the author(s) and are not necessarily representative of or endorsed by IFPRI.

2 The boundaries and names shown and the designations used on the map(s) herein do not imply official endorsement or acceptance by the International Food Policy Research Institute (IFPRI) or its partners and contributors.

3 Copyright remains with the authors. The authors are free to proceed, without further IFPRI permission, to publish this paper, or any revised version of it, in outlets such as journals, books, and other publications.

Contents

TABLES iii FIGURES iv ABSTRACT vi 1. INTRODUCTION 1 2. POLICY ENVIRONMENT AND ECONOMIC GROWTH 3 3. AGRICULTURE IN PARAGUAY 16 4. FAMILY AGRICULTURE 26 5. MEASURES OF ECONOMIC AND TECHNICAL EFFICIENCY 35 6. AGRICULTURAL GROWTH AND EFFICIENCY 42 7. SUMMARY AND CONCLUSIONS 55 REFERENCES 58

Tables

2.1– Paraguay in the region (average values 2010-2015) 4 2.2– Contribution of sectoral productivity growth and of reallocation of employment between sectors to economy-wide labor productivity growth, 1995-2014 15 3.1– Changes in output composition and output growth, 1988/1990 – 2010/2013 17 3.2– Changes in agricultural export composition and export growth, 1988/1990 – 2010/2013 17 3.3– Distribution of farms, farm area, and land use by region, agroecological zone and departamento, 2008 19 4.1– Number of farms, agricultural area, household family members and hired workers across strata of farm size, 2008. 28 4.2– Share of FA and commercial farms in total farm area in four departamentos, 1991 and 2008 36 4.3– Share of FA and commercial farms in total, crop and output in four departamentos, 1991 and 2008. 36 4.4– Changes in the mix of outputs in four departamentos, measured as changes in shares of different agricultural activities in total output, between 1991 and 2008. 37 6.1– Classification of FA households in groups of revenue efficiency, departamento of San Pedro, 1997 and 2008. 43 6.2– Classification of commercial farms in groups of revenue efficiency, departamento of San Pedro, 1997 and 2008. 45 6.3– Revenue efficiency decomposition for FA production in San Pedro, 1997 and 2008. 46 6.4– Revenue efficiency decomposition for FA production in San Pedro, 1997 and 2008. 47 6.5– Classification of family agriculture farms in groups of revenue efficiency, departamento of Caaguazu, 1997 and 2008. 48 6.6– Classification of commercial farms in groups of revenue efficiency, departamento of Caaguazu, 1997 and 2008. 49 6.7– Classification of family agriculture farms in groups of revenue efficiency, departamento of Alto Parana, 1997 and 2008. 51 6.8– Classification of commercial farms in groups of revenue efficiency, departamento of Alto Parana, 1997 and 2008. 52

iii

Figures

2.1–Trends in GDP and GDP growth rates 3 2.2– Annual inflation rate, consumer prices 1981-2013 5 2.3– Index of exchange rate undervaluation 5 2.4– Exports and imports of goods and services, 1991-2015 6 2.5– Trends in GDP per capita (in 2010 constant US$) 7 2.6– Poverty trends 2003-2015 in percentage of population 8 2.7- Trends in the share of value added and employment of different economic sectors in Paraguay 12 2.8–Sectoral contribution to total labor productivity 13 3.1– Political and administrative map of Paraguay 20 3.2– Share of selected departamentos in the country’s total number of farms, farm area, cultivated area and area of pasture, 2008 21 3.3– Evolution of TFP output, input per worker, 1961-2012 23 3.4– Contribution of input per worker and TFP to total growth in output per worker 24 3.5– Trends in land and labor productivity 24 3.6– Trends in the use of inputs per worker, 1989-2012. 25 4.1– Share of FA in total cultivated area of different crops, 2008. 29 4.2– Production trends of agricultural activities produced by commercial farms and by family agriculture, 1975-2013 30 4.3–Number of farms, farm area, number family household members in agriculture and number of hired workers in 2008 measured relative to their value in 1991 (index = 100 in 1991) 32 4.4– Area of traditional FA crops and crops that expanded under commercial farming, 2008 values measured relative to their value in 1991 (index = 100 in 1991) 32 4.5– Output and input levels in 2008 compared to levels in 1997 (levels in 1997=100). Aggregated values for four departamentos: San Pedro, Caaguazu, Itapua and Alto Parana. 33 4.6– Average output composition in family and commercial farms, 1997 and 2008. Aggregated values for four departamentos: San Pedro, Caaguazu, Itapua and Alto Parana. 34

iv

ABSTRACT

Between 2001 and 2012, Latin America and the ’s (LAC) agriculture saw its best performance of the last 30 years. What were the implications of this growth for family agriculture (FA) in the region? This study contributes to answer this question by looking at the case of Paraguay, a country with one of the fastest growing agricultural sectors in the region during this period. At the center of the development challenges faced by this country is the debate on the role of family agriculture and smallholders in a future growth strategy. Between 1991 and 2008 the number of family workers in agriculture decreased significantly, while the total area of FA crops decreased to only 48 percent of its level in 1991. As some authors argued in the past, the 2000s represent a turning point for FA development in Paraguay, given that until 2002, the total area of farms of less than 20 hectares was still increasing, a trend that reversed after this year. Are these changes, part of a process of impoverishment of the rural population resulting from displacement of FA by the commercial sector as is normally assumed in previous studies? Evidence from this study shows that rural poverty decreased almost by half between 2003 and 2015; that the reduction of output of crops traditionally produced by FA was not the result of competition with the commercial sector, but mostly a consequence of the collapse of production, a failure of a government program for FA; and that in regions with high proportion of FA, commercial crop production expanded by displacing inefficient extensive livestock farmers and not FA agriculture. We conclude that the situation of FA in Paraguay is much more diverse and complex than the simple claims of decomposition and disappearance as the result of the expansion of capitalist farmers. In this context, there are options for the government to promote the development of FA with the goal of increasing employment opportunities in rural areas while achieving a much-needed diversification of agricultural production and exports.

Keywords: agriculture, efficiency, family agriculture, Latin America and the Caribbean, productivity

v

ACKNOWLEDGMENTS

This study was undertaken as part of the work of the analytical component of the Agricultural Science and Technology Indicators (ASTI) led by the International Food Policy Research Institute (IFPRI), in collaboration with the Environment and Natural Disasters Division of the Inter-American Development Bank (IDB). Special recognition goes to Cesar Falconi, Principal Economist in the Environment and Natural Disasters Division of the IDB until 2016, at present the IDB Representative in Surinam. As our counterpart in the IDB, he made this study possible. The author gratefully acknowledges the financial support of the IDB, and very much appreciates the support and insights of Alvaro Garcia Negro in the IDB office in Asuncion, suggesting names of experts for the interviews and introducing us to some of the major policy issues and trends of agriculture in the country. Our trip to Paraguay wouldn’t have been possible without the support of IDB’s administrative staff in Asuncion who arranged all interviews and managed our agenda during our visit. Special thanks go to Dionisio Borda, Jose Brunstein, Blas Cristaldo, Manuel Ferreira, Luis Galeano, Mario León Frutos, Fernando Masi, and Henry Moriya, who kindly shared their expert opinion and insights on different aspects of Paraguay’s agriculture, providing key inputs for the study. Finally, special thanks to Sandra Perez for efficiently managing all the activities of the project and contributing to the outcome by actively participating in al interviews and discussions in Paraguay. This paper has not gone through IFPRI’s standard peer-review procedure. The opinions of the author expressed herein do not necessarily state or reflect those of IFPRI, CGIAR or IDB. All errors and interpretations are, as usual, the sole responsibility of the author.

vi

1. INTRODUCTION

Paraguay’s economy has seen remarkable growth in the last 20 years. Driving this growth is a strong performance of the agricultural sector with an average annual growth of 5.7 percent between 2003 and

2015. Agriculture accounts for 30 percent of the gross domestic product (GDP) and 40 percent of exports.

Approximately 57 percent of agricultural growth during this period is explained by growth in production. Despite the improved performance of its economy in the last 15 years, sustained growth in the future is challenged by structural characteristics of agriculture and its economy and vulnerabilities of its development model. First, among these vulnerabilities is the country’s strong dependence on just a handful of commodities, which makes the economy particularly vulnerable to exogenous climate and market shocks. A second weakness is the dual nature of the agricultural sector. Growth, historically, has been driven by a dynamic commercial agricultural sector that is natural-resource and capital intensive but does not create many jobs. Production tends to concentrate on large extensions of land, leading to potential conflict with traditional forms of family agriculture (FA) production and organization. Figures for 2008 show that small family farmers (260,000 in number) represent 91 percent of total agricultural producers but use only 6 percent of total agricultural land.

At present, family agriculture in Paraguay is going through significant changes: i) from mainly subsistence and self-sufficient production units with no access to markets, to increased integration into commercial value chains driven by private firms that link family farms to domestic and international markets, and; ii) from cotton production supported by government plans to traditional production of and , livestock production and attempts to develop new crops like sesame. Farmers integrated to value chains have increased and diversified their incomes, but those without access to the new production systems are falling behind. Furthermore, since Paraguay is undergoing demographic transition, a growing young working-age population, seems to be a challenge rather than an opportunity (“demographic dividend”) given the low rate of job creation of its natural resource-based economy.

1

Despite these challenges, Paraguay has an enormous potential for natural resource-based production due to its abundant stock of natural resources, including highly strategic aquifer, mineral, and energy resources. At the center of its development strategy is the challenge of job creation and the dual nature of the agricultural sector.

This study analyzes the impact that fast agricultural growth in recent years had on the traditional production system of family farms in Paraguay and the different strategies followed by this sector in different geographic areas. This is done by looking at economic and technical efficiency of agricultural producers, and to how production systems of efficient and inefficient producers changed between 1991 and 2008, a period of fast growth in agricultural production. The goals of the efficiency analysis are first, to determine the combination of inputs and outputs associated to most efficient farmers in the group of family farms and commercial farmers, respectively; second, to compare efficient systems in 1991 and

2008 and look at their evolution in different regions after 17 years of sustained agricultural growth; and finally, compare changes in efficient systems of those departamentos showing low commercial development in 1991 (San Pedro and Caaguazu) with those in Itapua and Alto Parana which were already producing commercially in 1991. This approach allows us to identify efficient strategies and assess likely future paths for different types of producers.

The study is organized as follows. The next section presents an overview of the policy changes behind the improved performance of Paraguay’s economy. This is followed by a characterization of agriculture in Paraguay and its performance in the last two decades, while section 4 takes a closer look to family agriculture in Paraguay. Section 5 presents the methodological underpinnings behind the methodology used to analyze efficiency of agriculture and section 6 discusses results of the efficiency analysis. The last section concludes.

2

2. POLICY ENVIRONMENT AND ECONOMIC GROWTH

After President Alfredo Stroessner, Paraguay's dictator for nearly 35 years, was overthrown on February

3, 1989, Paraguay, like other countries in the region after the debt crisis of the 1980s, implemented new policies that resulted in a more open economy. At the start, these changes came with several problems, reflected in the volatility and decreasing trend of the GDP growth rate. According to a special report by

Deloitte (2015), the policy changes included the elimination of multiple exchange rates, reduction of the fiscal deficit and a rapid liberalization of interest rates. However, the economy was not prepared for this rapid liberalization as it did not have the regulations in place, nor the capacity to supervise financial markets. The consequence of an unregulated massive capital inflow was a series of financial crisis that recurrently affected the economy from 1995 until 2000. The impact of these policies on the economy are shown in Figure 2.1. Between 1990 and 2002, the Paraguayan economy grew at an average rate of 2.1 percent, but the impact of the financial crises was reflected not in the average growth but in the trend of the growth rate, that went from 6.0 percent in 1990 to almost -1.0 percent in 2002. The slowing down of the economy was accompanied by a growing and unsustainable fiscal deficit and external debt, and a negative regional context caused by the financial crisis in in 1989 and the Argentinian crisis of

2001-2002.

The economy emerged from the 1989-2002 crisis after the implementation of new policy measures that reduced the fiscal deficit and regulated financial markets. Most importantly, the economy benefited from the implementation of a new development strategy that focused on developing agribusinesses, attracting capital investment and developing the country’s infrastructure. The new policies were successful in accelerating growth and stabilizing the economy as can be seen in Figure 2.1 and discussed in Deloitte (2015). GDP growth after 2002 was on average 4.7 percent despite the 2008 global financial crisis and negative weather shocks to agriculture in 2009 and in 2012. The overall economy and the agricultural sector have grown consistently since 2003, growth that is explained in part by the continuity of Paraguay’s economic policy despite government changes.

3

Figure 2.1–Trends in GDP and GDP growth rates

Source: World Bank (2016)

Figure 2.2 shows how improved macroeconomic policies are reflected in the evolution of the inflation rate. After reaching an annual rate of 35 percent in 1990, inflation was reduced to one-digit levels, going below 5 percent in recent years. During the period of macroeconomic mismanagement, the country experienced a high undervaluation of its currency, which was corrected by the policy changes implemented in the 1990s, a measure that contributed to the enhanced macroeconomic environment, given that as Rodrik (2008) argued, poorly managed exchange rates are disastrous for economic growth

(Figure 2.3).

4

Figure 2.2– Annual inflation rate, consumer prices 1981-2013.

40

35

30

25

20

15

Annualrate (percentage) 10

5

0 1989 1994 1999 2004 2009 2014

Source: Elaborated by authors based on World Bank (2016)

Figure 2.3– Index of exchange rate undervaluation

Source: Authors based on World Bank (2016). Note: Calculated following Rodrik (2008). It is calculated as the log of the ratio of the exchange rate and purchasing power parity (PPP) conversion factors. When the index is greater than 1 it indicates that the value of the currency is lower (more depreciated) than indicated by PPP. This ratio is corrected for the Balassa-Samuelson effect, that is, non-traded goods are cheaper in poorer countries.

5

Figure 2.4 shows the evolution of total exports and imports between 1991 and 2015. Paraguay’s trade performance also reflects the impact of macroeconomic policies and stability, with a sharp decrease of trade after 1996 and recovery with accelerated growth after 2001.

Figure 2.4– Exports and imports of goods and services, 1991-2015

Source: Authors based on World Bank (2016).

Sustained growth in the last 15 years resulted in rapid growth in average income as measured by GDP per capita. Average income in 2003 measured in 2010 US$ was 2,633, the same value observed in 1989.

Sustained growth after 2003 brought average income to 3,825 dollars, an increase of 45 percent relative to its level in 2003.

6

Figure 2.5– Trends in GDP per capita (in 2010 constant US$)

Source: Authors based on World Bank (2016).

Growth in average income had a significant effect on reducing poverty as shown in Figure 2.6. The proportion of people living in poverty fell from 44 percent in 2003 to 22 percent in 2015 — a 50 percent reduction in 12 years. Extreme poverty followed a similar trend, decreasing from 21 percent in 2003 to 10 percent in 2015. Poverty is prevalent in rural areas, where more than half of the population was poor in

2003, compared to a share of 24 percent in urban areas. Poverty reduction was remarkable also in rural areas, decreasing from 52 percent in 2003 to 33 percent in 2015, while rural extreme poverty reached 18 percent in 2015, compared to 31 percent in 2003.

7

Figure 2.6– Poverty trends 2003-2015 in percentage of population

Source: Authors based on Dirección General de Estadística, Encuestas y Censos (2015)

8

Labor productivity and economic transformation

Development entails structural change, which is defined as the reallocation of economic activity across the three broad sectors (agriculture, industry and services) that accompanies the process of modern economic growth (Herrendorf, Rogerson and Valentinyi 2013). Countries that manage to pull out of poverty and get richer are those that can diversify away from agriculture and other traditional products.

As labor and other resources move from agriculture into more productive activities, overall productivity rises and income expands. The speed with which this structural transformation takes place is the key factor that differentiates successful countries from unsuccessful ones (McMillan, Rodrik and Verduzco-

Gallo, 2014). These changes are usually accompanied by an increasing degree of urbanization, as the economy’s center shifts from rural to urban areas, and rural to urban migration rises (Kuznets, 1966).

Developing economies are characterized by large productivity gaps between different sectors of the economy. McMillan and Rodrik (2012) identify three factors that help determine whether (and the extent to which) structural transformation goes in the “right” direction and contributes to overall productivity growth. First, economies with revealed comparative advantage in primary products are at a disadvantage.

The larger the share of natural resources in exports, the smaller the scope of productivity-enhancing structural change because even though they can achieve high levels of labor productivity, they usually cannot absorb the surplus labor from agriculture as is the case with light manufacturing industries and related services. Second, countries with competitive (or undervalued) currencies tend to experience more growth-enhancing structural change than those countries with overvalued exchange rates. And third, countries with more flexible labor markets tend to experience greater growth-enhancing structural change.

The three most common measures of economic activity at the sectoral level to measure structural transformation are: employment shares, value added shares, and final consumption expenditure shares

(Herrendorf et al., 2013). The first two are measures from the production side, while the third measures transformation from the consumption side of the economy.

9

Table 2.1 presents a classification of LAC countries based on income and gives an overview of the situation of Paraguay in a regional context. Countries have been classified based on GDP per capita in three groups: “higher income countries” (HI), “medium income countries” (MI) and “lower income countries” (LI).1 Paraguay shows an average GDP per capita that is above the average value in the LI group ($7,866 compared to $5,660, respectively). Other differences between Paraguay and countries in the LI group are that Paraguay has one of the lowest population densities in LAC, 16 people per square kilometer compared with an average of 152 in LI countries; it shows a high comparative advantage in agriculture and a low share of total employment in agriculture (25 percent compared to an average of 34 in the LI group); a high share of employment in services (57 compared to 48 in the LI group); a relatively high share of agriculture in GDP; and a low share of services in GDP. A relatively low level of employment in agriculture and a high share of agriculture in GDP means that labor productivity in agriculture is high compared to similar countries in the region, which is reflected in the high level of

RCA2. On the other hand, the high share of employment in services relative to service’s small share in

GDP implies relatively low productivity of the service sector. This could become a major problem for future growth if workers leaving agriculture are employed in low labor productivity activities.

1 The terms high, middle and low income are only relative to differences in GDP per capita between countries in the region. Note: Group 1: Trinidad and Tobago, Bahamas, , Argentina, , Panama, Venezuela and ; Group 2: Suriname, Brazil, Costa Rica, , Dominican Republic, , Ecuador, Jamaica, and Belize; Group 3: Paraguay, El Salvador, Guatemala, Guyana, Bolivia, Honduras and Haiti. 2 The numerator of the index of revealed comparative advantage (RCA) defined by Balassa (1965) represents the percentage share of agriculture in Paraguay’s exports and the denominator represents the average percentage share of agriculture in exports of countries in the rest of the world. An RCA=1 means that the percentage share of agriculture in a country is the same as that of the world average. If the RCA is above 1 the country is said to be specialized in agriculture relative to the rest of the world, and if the RCA is below 1 it is said not to be specialized.

10

Table 2.1– Paraguay in the region (average values 2010-2015)

Income Group HI MI LI Paraguay GDP per capita ($2011 PPP) 17,810 13,808 5,660 7,866 Natural resource rents (% GDP) 11 7 7 5 Population growth (%) 1.4 1.3 1.7 1.7 Urban population (%) 83 81 57 59 Population density (people/square Km) 47 38 152 16 Revealed comparative advantage in agriculture (RCA) 2.0 3.3 4.1 7.3 Share in total employment (%) - Agriculture 10 15 34 25 - Industry 23 22 18 18 - Services 66 65 48 57

Share in GDP (%) - Agriculture 4 6 16 22 - Industry 32 25 23 17 - Manufacture 18 16 16 12 - Services 64 69 61 49

Source: Elaborated by authors based on World Bank (2016). Note: Group 1: Trinidad and Tobago, Bahamas, Chile, Argentina, Uruguay, Panama, Venezuela and Mexico; Group 2: Suriname, Brazil, Costa Rica, Colombia, Dominican Republic, Peru, Ecuador, Jamaica, and Belize; Group 3: Paraguay, El Salvador, Guatemala, Guyana, Bolivia, Honduras and Haiti. RCAi= %Ag Exports(i)/%Ag Exports(world)

Figure 2.7 presents trends in the share of economic sectors in total GDP and employment in

Paraguay. The decreasing share of agriculture in total employment occurred simultaneously with rapid growth and has resulted in increased labor productivity (Figure 2.7A). On the other hand, industry’s value added shrink after the regional crisis of 2003, however, the share of industry in employment has remained just below 20 percent since 1995. The consequence of these changes was a sharp reduction in industry’s labor productivity.

The most interesting case is that of services. There was a large increase in employment in services in the early 1990s and then again a clear positive trend in employment after 2004. Despite these changes, the sector has been able to keep stable values of labor productivity, even showing some growth by the end of the period. Notice also that labor productivity in agriculture was only $2,000 in 1995, increasing to

$6,000 in 2013, a similar value to labor productivity in industry and services.

11

Figure 2.7- Trends in the share of value added and employment of different economic sectors in Paraguay

Source: Elaborated by authors based on World Bank (2016), ILO (2016) and UN (2016).

12

What were the implications of the trends observed in Figure 2.7 for overall labor productivity? Figure

2.8 shows the contribution of sectoral labor productivity to total labor productivity. Overall labor productivity increased by nearly 30 percent between 1995 and 2014, equivalent to annual growth of 1.3 percent. Agriculture was the only driver of productivity, increasing by almost 300 percent between 1995 and 2014, equivalent to an average annual growth rate of 5.6 percent. In contrast, labor productivity in industry decreased at a rate of -3.3 percent while productivity in services remained almost unchanged, with an average annual growth of 0.11 percent.

Figure 2.8–Sectoral contribution to total labor productivity

Source: Elaborated by authors based on World Bank (2016),

We present further evidence on sectoral contribution to productivity growth by decomposing economy-wide growth in labor productivity following McMillan, Rodrik and Verduzco-Gallo (2014):

푑푌푡 = ∑푗=푚 훽푗,푡−푠푑푦푗,푡 + ∑푗=푚 푦푗,푡푑훽푗푡 (2.1)

13

Equation 2.1 shows the decomposition of changes (d) in economy-wide labor productivity (Yt) into changes in sectoral productivity (yjt) weighted by the initial share of employment in each sector (βjt), and changes in sectoral employment weighted by productivity levels, where j is the sector and t the period.

The first term in the equation is the weighted sum of productivity growth within sectors, what McMillan,

Rodrik and Verduzco-Gallo (2014) call the “within” component of labor productivity growth. The second term is the structural change effect and it captures the productivity effect of labor reallocations across different sectors, calculated as the change in the labor share weighted by the productivity level of each sector. When changes in employment shares are positively correlated, for example, when the labor share of the sector with the highest productivity increases and the labor share of the sector with the lowest productivity decreases, the second term in equation (2.1) is positive, and structural change increases economy-wide labor productivity.

Productivity growth rates and its decomposition into the within and structural change effects for

Paraguay during the period 1996-2014 are shown in Table 2.2. The first column represents the “within” component of total productivity, the contribution of productivity growth within each sector. The second column is the structural transformation component or changes in productivity that result from reallocation of workers across sectors.

Table 2.2 shows that Paraguay’s 30 percent growth in labor productivity between 1994 and 2014 is the result of increased productivity within sectors. There was no contribution of structural change in labor productivity (-1 percent in total change) which is the result of reduced labor productivity in industry and convergence of productivity of all three sectors.

14

Table 2.2– Contribution of sectoral productivity growth and of reallocation of employment between sectors to economy-wide labor productivity growth, 1995-2014. Within Structural change Total 1996 109 -9 100 1997 114 -14 100 1998 100 0 100 1999 98 2 100 2000 99 1 100 2001 100 0 100 2002 106 -6 100 2003 76 24 100 2004 95 5 100 2005 105 -5 100 2006 102 -2 100 2007 71 29 100 2008 118 -18 100 2009 89 11 100 2010 107 -7 100 2011 110 -10 100 2012 97 3 100 2013 115 -15 100 2014 107 -7 100 Average 101 -1 100 Source: Elaborated by authors based on World Bank (2016), ILO (2016). Note: Sectoral productivity (“within”) component is the contribution of sectoral productivity growth weighted by the initial share of sectoral labor in total employment; the contribution from change in employment is the “structural change” component, the change in the sectoral employment share weighted by the level of sectoral labor productivity.

15

3. AGRICULTURE IN PARAGUAY

Table 3.1 shows the composition of output after the end of Stroessner’s rule in 1989 and its composition in 2010-2013 after the period of fast growth that started in 2003. The last column in Table 3.1 shows annual average growth rate of production of each commodity and the total for agriculture (last row). The improved performance of Paraguay’s agriculture in the past 15 years was driven by growth in soybean and beef production. The share in total output of these commodities almost doubled from 33 percent in

1988-1990 to 56 percent in 2011-2013. Fast growth in , and production also contributed significantly to output growth, with the total share of these three crops increasing from 5.5 percent in

1988-1990 to 17 percent by the end of the period. On the other hand, the importance of traditional staples like cassava and of cotton, a major export crop during the 1990s, significantly decreased their importance in total output. Cassava, with a share of 17 percent, and cotton with a share of 10 percent in total output in

1988-1990 reduced their share to 5 and 0.3 percent, respectively.

Table 3.2 shows that the most dynamic activities in recent years were export-oriented activities, some of them like soybeans and beef already important export commodities at the beginning of the period, while others like maize, wheat, sugar and rice significantly increased their share in total exports, mostly replacing cotton which represented 38 percent of total exports in 1988-1990 and shrink down to only 0.5 percent of total exports by the end of the period.

16

Table 3.1– Changes in output composition and output growth, 1988/1990 – 2010/2013 Output composition in two periods 1988-1990 2011-2013 Annual growth rate Soybeans 16.8 37.9 8.0 Beef 15.5 18.7 4.8 Maize 2.0 9.5 11.8 Cassava 16.8 4.6 -2.3 Pig 7.2 5.0 2.1 Wheat 2.4 4.5 6.9 Sugar cane 3.8 3.1 3.0 Rice 1.1 2.5 8.2 2.6 3.1 4.6 Poultry 2.6 2.7 6.8 Oranges 1.5 0.8 1.2 1.4 0.5 -1.1 Sunflower 0.3 0.5 7.6 Cotton 9.7 0.3 -11.6 Other 16.4 6.3 -0.7 100 100 3.9 Source: Authors using data from FAO (2016).

Table 3.2– Changes in agricultural export composition and export growth, 1988/1990 – 2010/2013 1988-1990 2011-2013 Annual growth rate Soybeans and soybean products 29.2 51.0 11.4 Beef and beef preparations 22.3 27.0 9.6 Cotton lint 37.7 0.5 -9.9 Maize 0.0 7.9 42.1 Wheat 0.8 4.0 16.5 Raw sugar 0.6 1.4 12.5 Rice 0.0 2.1 30.2 Other 9.3 6.0 6.6 Total 100 100 8.7 Source: Authors based on data from FAO (2016).

17

Table 3.3 shows the spatial distribution of farms, total farm area and land use by region, agroecological zone and departamento in 2008, the year of the last agricultural census. The country is divided in two major regions: Oriental (Eastern Region) and Occidental (Western Region) and 17 departamentos (not including the capital Asuncion), of which 14 are in the Region Oriental. Total agricultural area is divided in eight agroecological zones: North, Central, Central-East, Central-South,

South, South-West, East and . The Región Oriental is the traditional agricultural production region, where 97 percent of all farms are located and where 99 percent of total cultivated area can be found. The average farm size in this region was 48 hectares in 2008. The Chaco is at present the agricultural frontier, a semi-arid region with a very low population density, consisting of more than 60 percent of Paraguay´s land area and 80 percent of its total area under natural and cultivated forests, but where less than 2 percent of the population is located. The average farm area in this region is 2,155 hectares.

18

Table 3.3–Distribution of farms, farm area, and land use by region, agroecological zone and departamento, 2008 Natural Average and Agroecological Number Farm farm Cultivated cultivated Other zone Departamento of farms area area land Pasture forests uses (%) (%) (Ha.) (%) (%) (%) (%) Region Oriental 97 43 48 99 40 23 56 Concepcion 6 5 93 2 7 3 4 North San Pedro 16 6 38 10 5 4 10 Amambay 2 4 254 4 5 3 2 Cordillera 6 1 23 1 2 0 2 Central Paraguarí 8 2 29 2 3 1 3 Central 2 0 17 0 0 0 1 Guairá 6 1 13 2 1 0 1 Central-East Caaguazú 13 4 29 13 2 2 5 Caazapá 8 2 34 5 2 1 4 Central-South Misiones 3 3 89 2 4 0 5 South Itapúa 12 4 33 18 2 2 3 Southwest Ñeembucú 3 3 130 0 4 1 9 Alto Parana 7 4 58 24 1 2 3 East Canindeyu 5 4 88 17 3 3 3 Region Occidental 3 57 2,155 1 60 77 44 Presidente Hayes 2 21 1,481 0 24 25 17 Chaco Alto Paraguay 0 17 5,625 0 19 24 14 Boquerón 1 18 2,044 0 18 28 14 Total 100 100 107 100 100 100 100 Source: Authors based on Ministerio de Agricultura y Ganadería. 2014 and MGA-DCA (2009)

Figure 3.1 shows the administrative map of Paraguay with departamentos and major cities. The

Paraguay river divides the country in the two major regions shown in Table 3.3: Region Occidental

(Chaco) located to the west of the Paraguay river, and the Region Oriental, to the east.

19

Figure 3.1– Political and administrative map of Paraguay

Source: Vidiani.com. Available at: http://www.vidiani.com/detailed-administrative-map-of-paraguay/

Figure 3.2 shows the distribution of farms and land between selected departamentos and other regions. The departamentos are San Pedro, Caaguazú, Itapúa and Alto Paraná. The analysis in this study will focus in these departamentos because of detailed data availability for at least two periods (1997 and

2008) and because these departamentos received a large number of families during the so called “March to the East,” the exodus from Paraguay's central zone to the eastern border region that began in the 1960s

20

(Hanratty and Meditz 1988). However, the path followed by San Pedro and Caaguazú on the one hand and Itapúa and Alto Parana on the other, was quite different. Alto Parana, with border with Brazil, received many Brazilian producers that transformed agriculture in the departamento, with an early expansion of soybean and cereal production. A similar process occurred in Itapúa where mostly

Argentinian producers play a central role in the development of commercial agriculture. The expansion of commercial agriculture in San Pedro and Caaguazú only started much later. In these departmentos, large farms were specialized until recently in livestock mostly under Paraguayan producers. Particularly,

Caaguazú was central to the development of cotton production that had its peak in 1991and had virtually disappeared in the mid-2000s. Because of the large number of smallholders, San Pedro and Caaguazú have the highest number of farms (almost 30 percent of all farms in Paraguay) and 23 percent of cultivated area. In contrast, the number of farms in Itapúa and Alto Parana is below 20 percent, but because of early development of commercial agriculture, they cultivated more than 40 percent of the country’s crop area in 2008.

Figure 3.2– Share of selected departamentos in the country’s total number of farms, farm area, cultivated area and area of pasture, 2008

Source: Author’s calculations based on MGA-DCA (2009)

21

Trends and changes in output, inputs and productivity

Agricultural production in Paraguay has been growing steadily after the economy emerged from the 1989-

2002 crisis with the implementation of a new development strategy and new policy measures to reduce the fiscal deficit and to regulate financial markets. We use here data from the Food and Agriculture

Organization of the United Nations (FAO 2016), which provides national time-series data from 1961 to

2013 for the total quantity of different agricultural inputs and output. Total agricultural output is the value of gross agricultural production expressed in constant 2004–2006 US dollars including crop and livestock production. Inputs include labor, measured as total economically active population in agriculture, fertilizer (metric tons of nitrogen, potash, and phosphates used measured in nutrient-equivalent terms), and a measure of capital stock that includes the value of the animal stock, permanent crops, machinery and farm improvements, calculated by FAO at average 2005 prices.

TFP estimates are obtained by defining and index that uses a fix aggregator function for all possible binary comparisons which satisfies transitivity. O’Donnell (2008) refers to this index as a Lowe index which is spatially and temporally transitive and can be used to make multilateral firm comparisons of TFP and efficiency. This means that a direct comparison of TFP measures of two different periods should yield the same estimate of TFP change as the total change in TFP in sub-periods between these periods;

푄푖 = 푝′표푞푖 and 푋푖 = 푤′표푥푖, where po and wo are representative price vectors. Elasticities from econometric estimates of a Cobb-Douglas production function are used to aggregate inputs (Nin-Pratt et al. 2015), while domestic prices are used to aggregate outputs.

Figure 3.3 shows that agricultural output per worker increased 45 percent between 1989 and 2012

(from a level of 100 to 145 as measured by the output index). The figure also shows a high correlation between output growth and TFP, while total input shows a positive trend although at a much lower rate than output and TFP. Figure 3.4 complements the previous figure showing the contribution of input per worker and TFP to total growth in output per worker. We observe the best agricultural performance after

2002, with an average annual growth of 3.4 percent in output per worker. Notice that during the transition

22 period of policy changes between 1989 and 2002, yearly TFP growth was only 0.7 percent or 22 percent of total growth in output per worker, which reached an average value of 1.4 percent during that period.

Figure 3.3– Evolution of TFP output, input per worker, 1961-2012

Source: Elaborated by authors based on FAO (2016)

23

Figure 3.4– Contribution of input per worker and TFP to total growth in output per worker

4.00

3.50

3.00

2.50

2.00

1.50 87% 22% 1.00 76%

0.50 78% 13% 24% 0.00 1989-2002 2003-2012 1989-2012

Input TFP

Source; Elaborated by authors based on FAO (2016). Figure 3.5 shows the evolution of partial factor productivity measures (PFP): land and labor productivity. The patterns observed are like those of output and TFP. Notice that land productivity has increased faster (5.2 percent) than labor productivity (3.6 percent) in the last ten years.

Figure 3.5– Trends in land and labor productivity

Source; Elaborated by authors based on FAO (2016).

24

On the input side (Figure 3.6), the major observable change is the large increase in the use of fertilizer per worker, twelve times larger in 2012 than in 1989. This, together with the increase in capital per worker, which reached its lowest value in 2002 (90) and recovered to a value of 108 in 2012, are changes that reflect the growing importance of commercial agriculture.

Figure 3.6– Trends in the use of inputs per worker, 1989-2012.

Source; Elaborated by authors based on FAO (2016).

In sum, TFP growth and the improved performance of agriculture in the past 15 years in Paraguay is the result of rapid growth in commercial farming of soybeans, maize, wheat, rice and . These changes resulted in rapid growth in TFP, output per hectare and output per worker. The country produces more beans, groundnuts, sugar cane, rice and cattle (milk and beef) and practically eliminated cotton production, an important export crop in the past. These changes in the production matrix have been supplemented by a reduction in the use of fertilizer and feed per worker and an increase in the use of capital and land, a change that is likely linked to the expansion of the agricultural frontier and an increase in the importance of extensive livestock production.

25

4. FAMILY AGRICULTURE

The law No 2419 that creates the National Institute of Rural Development and Land in 2004 defines

“family agriculture” as the rural production activity that uses family labor as the main factor of production and uses less than 50 hectares of land in the Eastern region and less than 500 hectares in the Western region. Family agriculture in Paraguay differs from commercial agriculture by its lower levels of investment and intensive use of family labor, significant share of production for household consumption and less access to markets. Galeano (2012) distinguishes three different types of FA. The first type includes those rural households with no access to land and producers using less than 10 hectares of land.

These farmers combine agricultural production, in most cases for self-consumption, with off-farm employment in other activities. According to Galeano (2012), self-sufficient producers are those with land areas between 10 and 20 hectares. These producers rely on agricultural production as their main source of income and constitute what Galeano (2012) defines as peasant agriculture. Producers in the 20 to50 hectares’ stratum and those in the 50 to100 hectares’ stratum constitute the group of capitalized FA, described as “farmers” by Galeano (2012). In what follows, we present some of the main characteristics of FA in Paraguay and how these features changed during the period of fast agricultural growth after

2003.

Table 4.1 summarizes information from the 2008 National Agricultural Census (CAN), showing total number of farms and the distribution of area, household family members and hired workers across strata of farm area. There was a total of 289 thousand households producing agriculture in 31 million hectares in

2008. Almost 10 percent of this area was under crop cultivation (including temporary and permanent crops), while 17.8 million hectares were under pastures. The total number of family members in agricultural households was 1.08 million, with 40 percent of them between the ages of 15 and 44 years old. During that year, these households hired 320 thousand workers.

The FA farms are more than 90 percent of total farms as per the census of 2008, but only occupy 6 percent of total farm area. In view of its low share in total area, FA cultivates a proportionally large area

26 under crops (23 percent), but most pasture land is under commercial farmers (97 percent). Notice that most labor is allocated across FA producers, including two-thirds of all hired workers.

FA has historically specialized in the production of staple crops, mainly cassava, beans and maize; like and pineapple; and tomato. They also had a significant share in total production of mate and more recently of sesame production. Cotton is a special case because it was one of

Paraguay’s major export crops until the early 1990s and almost exclusively produced by family farmers.

Promoted by the government as part of a development plan for FA, cotton farming experienced extremely rapid growth in the 1970s and 1980s, reaching 386 thousand hectares in 1985 from only 47 thousand hectares in 1970. Those figures had dropped to only 66 thousand hectares in 2008 as the result of low yields, lack of adequate technology and wide price fluctuations. On the other hand, commercial agriculture has seen a rapid growth in the last 15 years by specializing in the production of soybeans, maize, wheat and beef.

27

Table 4.1– Number of farms, agricultural area, household family members and hired workers across strata of farm size, 2008.

Number of Area in 1000s hectares household family Number Hired members of farms 15-44 workers Other Family years’ Area Crops Pastures uses members old Less than 10 hectares 183 655 348 98 208 721 248 122 10-20 hectares 58 685 246 183 257 240 98 61 20-50 hectares 23 620 183 254 183 79 32 32 Total FA 264 1,960 777 535 648 1,039 378 215 50-500 hectares 17 2,759 855 1,373 531 34 14 43 +500 hectares 7 26,367 1,733 15,929 8,705 4 2 63 Commercial farms 25 29,127 2,588 17,303 9,236 38 16 106 Total 289 31,087 3,365 17,838 9,884 1,078 395 320 Percentage Less than 10 hectares 64 2 10 1 2 67 63 38 10-20 hectares 20 2 7 1 3 22 25 19 20-50 hectares 8 2 5 1 2 7 8 10 Total FA 91 6 23 3 7 96 96 67 50-500 hectares 6 9 25 8 5 3 4 13 +500 hectares 3 85 51 89 88 0 0 20 Commercial farms 9 94 77 97 93 4 4 33 Total 100 100 100 100 100 100 100 100 Source: Authors based on data from MGA-DCA (2009)

Figure 4.1 shows the share of FA in different agricultural activities according to figures from the 2008 agricultural census. Traditionally, the main family farming crops were white maize, beans, and cassava for auto consumption, and cotton, sesame, sugar cane, soybeans and cassava for selling in the market. On the other hand, and pineapple were the main permanent crops, while animals are kept as a savings strategy and from the productive standpoint, for milk production. As of 2008, more than 90 percent of the total area of pineapple, tomato, cassava, beans, mate and cotton was cultivated by FA, and in most cases at least 48 percent of total area was cultivated by farmers with less than 10 hectares. Banana, sesame orange and groundnuts were also cultivated in large proportions by FA. With the expansion of commercial agriculture, large production units cultivate most of the land under soybeans (94 percent), wheat (90 percent), sunflower, rice (96 percent) and maize (74 percent).

28

Figure 4.1– Share of FA in total cultivated area of different crops, 2008.

Source: Authors based on data from MGA-DCA (2009).

Figure 4.2 presents a long-term perspective of the changes in the output mix in Paraguay, showing trends of the activities that expanded under commercial farming after 1989 (soybeans, maize, wheat, beef, sunflower and rice) and all other activities produced in the country which we label FA crops/activities.

The two groups of activities were growing at similar pace between 1975 and 1985 but after that year, growth rates of commercial crops remained at 5 percent per year while other crops averaged zero growth in the 1990s. In the 2000s, growth rates of commercial crops show high variability but within a range of values between 3 to 16 percent. FA crops show similar variability in growth rates, but the range of growth rate changes was between -6 and 6 percent.

29

Figure 4.2– Production trends of agricultural activities produced by commercial farms and by family agriculture, 1975-2013

Source: Authors based on data from MGA-DCA (2009). Note: Commercial crops include soybean, maize, rice, wheat, sunflower and beef

Decline of family agriculture

Riquelme (2014) argues that the 2000s represent a turning point for agricultural development in Paraguay.

Until then, and after the end of Stroessner’s government, FA organizations were gaining momentum on the struggle for access to land, with increased agricultural land under FA during the 1990s. For example, and according to Riquelme (2014), total area of farms of less than 20 hectares increased from 122 thousand hectares in 1991 to approximately 160 thousand in 2002. This year marks, according to

Riqueleme (2014), the start of the decline of FA in the country. This decline is reflected in figures 4.3 and

4.4, showing changes in the number of farms, farm area, workers and area of FA’s main crops. The only variable showing growth between 1991 and 2008 in Figure 4.3 is total farm area (131 in 2008 compared to 100 in 1991). This expansion of the agricultural area was driven by commercial farms and growth in cultivated area of soybeans, maize, wheat, rice and pastures. On the other hand, a reduction in the number of farms (6 percent), on the number of family members in agricultural households (from 100 in 1991 to

30

67 in 2008), an even larger reduction in the number of family members of ages 15 to 44 years (from 100 to 60), and the collapse in the number of hired workers from 100 in 1991 to 31 in 2008, are all indicators of the impact that changes in the agricultural sector after 2002 had on FA.

We observe similar signals of the decline of FA on the output side. Figure 4.3 shows an index of the cultivated area of seven crops traditionally produced by FA (pineapple, tomato, cassava, beans, cotton, banana and orange), and four crops mostly produced by the commercial sector (maize, wheat, soybean and rice). Total area of the FA crops in 2008 shrink to only 48 percent of its level in 1991. The collapse of cotton production explains a significant part of this decline, but crops like banana and orange also show significant reductions in area. On the other hand, the area of pineapple, tomato and beans increased during the same period (85, 17 and 18 percent, respectively), while the area of cassava did not change.

Commercial crops show a very different picture, with total area in 2008 being 4 times bigger than in

1991. In this context, soybean shows the highest increase (4.5 times its level in 1991), but there are also high increases in production of all other crops: 353 percent growth in maize area, 316 percent in rice area and 248 percent in wheat.

31

Figure 4.3–Number of farms, farm area, number of family household members in agriculture and number of hired workers in 2008 measured relative to their value in 1991 (index = 100 in 1991)

Source: Authors based on data from MGA-DCA (2009). Figure 4.4–Area of traditional FA crops and crops that expanded under commercial farming, 2008 values measured relative to their value in 1991 (index = 100 in 1991)

Source: Authors based on data from MGA-DCA (2009).

32

Family agriculture in San Pedro, Caaguazu, Itapua and Alto Parana

We take a closer look at the impact that changes in agriculture after 2002 had on FA in the departamentos of San Pedro, Caaguazú, Itapúa and Alto Parana.3 Figures 4.5 and 4.6 show changes in inputs and in the composition of output calculated from aggregated values of the four departamentos. These results show a similar pattern than the results calculated at the national level. Total agricultural output of FA decreased in absolute values to only 68 percent of its level in 1991, while output of commercial farms increased by

460 percent. Changes in output in FA and commercial agriculture did not occur as the result of a proportional change in inputs, which might reflect the changes in the specialization of each group of farms between 1991 and 2008. For example, FA increased its farm area (27 percent), labor use (12 percent) and its capital in machinery (41 percent), which means that the reduction of output results from a reduction in the use of materials (fertilizer, feed, seed, pesticides) and in the stock of livestock capital, a consequence of a change in output specialization.

Figure 4.5– Output and input levels in 2008 compared to levels in 1997 (levels in 1997=100). Aggregated values for four departamentos: San Pedro, Caaguazu, Itapua and Alto Parana.

Source: Elaborated by authors

3 Using data from the Encuesta Permanente de Hogares of the Dirección General de Estadística, Encuestas y Censos, Asunción, Paraguay.

33

Changes in output composition are presented in Figure 4.6. The major change observed in the composition of output in FA is the diminished importance of and production, which represented almost 40 percent of total output in 1997 and decreased to only 12 percent in 2008. At the same time, FA households increased production of oil crops, cash crops, cereals and poultry meat. These changes in the output and input mix show that FA households in these departamentos adopted a more extensive production system in 2008 that uses more land, labor and machinery and a reduced amount of materials and animal stock to produce grain, roots and tubers and cash crops.

Figure 4.6– Average output composition in family and commercial farms, 1997 and 2008. Aggregated values for four departamentos: San Pedro, Caaguazu, Itapua and Alto Parana.

Source: Elaborated by authors

34

Aggregated results obtained for the four departamentos do not reflect the heterogeneity in production systems and the relative importance of FA and commercial farmers in 1997. In what follows we look at the impact that changes in agriculture between 1997 and 2008 had in each of the departamentos. In particular, we highlight differences between San Pedro and Caaguazú on the one hand, and Itapúa and

Alto Parana on the other. In the first two departamentos, FA was still producing almost all output in 1997.

In contrast with this situation, Itapua and Alto Parana already showed a significant expansion of commercial agriculture in 1997.

Table 4.2 shows shares of FA and commercial agriculture in total farm area in 1997 and 2008. As mentioned above, the importance of commercial agriculture was very different in San Pedro and

Caaguazu compared to its importance in Itapua and Alto Parana. In the case of San Pedro, the farm area of FA and commercial agriculture was about the same (54 and 46 percent of total area, respectively). In

Caaguazu, almost all land was under FA (80 percent). The importance of FA in San Pedro and Caaguazu in 1991 is larger when the comparison is made using total output instead of land (Table 4.3). FA in San

Pedro and in Caaguazu was producing almost all output in 1991 (99 percent).

In Itapua and Alto Parana, the importance of commercial agriculture is much higher in 1991 than in the other two departamentos: 62 and 77 percent of total farm area, respectively as shown in Table 4.2.

When comparing levels of output in Table 4.3, commercial farmers in Itapua were already producing 40 percent of total output in 1991, 50 percent of crop production and 16 percent of livestock production. In

Alto Parana, differences are even larger, with commercial farmers producing 56 and 77 percent of livestock and crop output, respectively.

35

Table 4.2– Share of FA and commercial farms in total farm area in four departamentos, 1991 and 2008 Departamento Year FA Commercial Total 1997 54 46 100 San Pedro 2008 30 70 100 1997 81 19 100 Caaguazú 2008 46 54 100 1997 38 62 100 Itapúa 2008 15 85 100 1997 23 77 100 Alto Parana 2008 11 89 100 1997 44 56 400 Total 2008 26 74 400 Source: Elaborated by authors using data from the Dirección General de Estadística, Encuestas y Censos. Encuesta Permanente de Hogares. Asunción, Paraguay.

Table 4.3– Share of FA and commercial farms in total, crop and livestock output in four departamentos, 1991 and 2008 1997 2008 FA Commercial Total FA Commercial Total Total 99 1 100 47 53 100 San Pedro Crop 100 0 100 43 57 100 Livestock 96 4 100 59 41 100 Total 98 2 100 59 41 100 Caaguazú Crop 99 1 100 46 54 100 Livestock 98 2 100 79 21 100 Total 60 40 100 28 72 100 Itapúa Crop 50 50 100 24 76 100 Livestock 84 16 100 71 29 100 Total 44 56 100 19 81 100 Alto Parana Crop 23 77 100 15 85 100 Livestock 84 16 100 52 48 100 Source: Elaborated by authors using data from the Dirección General de Estadística, Encuestas y Censos. Encuesta Permanente de Hogares. Asunción, Paraguay.

By 2008, the situation of FA in all departamentos had changed significantly but most importantly so in San Pedro and Caaguazú. In the case of San Pedro, the share of FA in total land area is 30 percent in

2008, down from 54 percent in 1991 while in Caaguazú, this share decreased from 81 to 46 percent. In

36

Itapúa and Alto Parana, there seems to be a similar negative impact of the expansion of commercial agriculture in total land under FA, going from 38 to 15 percent of total area in Itapúa and from 23 to 11 percent in Alto Parana.

The observed changes in the share of FA and of commercial farms in total land area and output were accompanied by significant changes in the output mix in FA, and most interestingly in the commercial sector in San Pedro and Caaguazú. These changes are presented in Table 4.4. We look first at changes in commercial agriculture. In the case of San Pedro, we observe a reduction of 62 percentage points in the share of beef production in total output and an increase of almost the same size in the share of oil crops.

Something similar happened among commercial farmers in Caaguazú, the only difference being that in that case, the change is from milk production instead of beef, to oil crops. These results indicate that in

1991, farmers with 50 hectares or more in San Pedro and Caaguazú were specialized livestock producers.

The transformation of agriculture in this departamentos resulted in a change in commercial agriculture from livestock producers to specialized oil crop producers. In Itapúa and Alto Parana, commercial farmers were already producing oil crops in 1991. Changes observed in these departamentos only meant an increased share of cereals and a reduction of oil crops in total output.

Table– 4.4–Changes in the mix of outputs in four departamentos, measured as changes in shares of different agricultural activities in total output, between 1991 and 2008. San Pedro Caaguazu Itapua Alto Parana FA Commercial FA Commercial FA Commercial FA Commercial Cash crops 3 -5 3 -4 16 1 -1 0 Cereals 3 4 -1 17 2 23 12 22 Oil crops 19 64 2 57 -3 -13 21 -18 Fruits & veg. -43 2 1 -3 2 0 2 0 Milk 2 2 -10 -50 -2 -3 -39 -4 Beef 0 -62 -5 8 0 -1 3 2 Poultry 7 -1 10 -15 -10 -3 -4 -1 Other 8 -3 -1 -11 -4 -4 6 -1 Total 0 0 0 0 0 0 0 0 Source: Elaborated by authors using data from the Dirección General de Estadística, encuestas y Censos. Encuesta Permanente de Hogares. Asunción, Paraguay. In the case of FA, we observe that the collapse of fruit and vegetable production mentioned above occurred in San Pedro. There, FA increased production of oil crops, poultry and cereals to partially

37 replace the decrease in production of fruits and vegetables. In Caaguazú, FA households did not increase production of oil crops which increased its share by only 2 percentage points in total output. The major change seems to be an increase in poultry production replacing milk production. In Itapúa, the major observed change in FA is the increase in the share of cash crops (16 points) and the reduction of the share of poultry by 10 percentage points. Finally, FA milk producers in Alto Parana practically disappeared (-

39 percentage points) and were replaced by increased output of oil crops and cereals (21 and 12 percentage points, respectively).

38

5. MEASURES OF ECONOMIC AND TECHNICAL EFFICIENCY

We use the framework proposed by Tone (2002) to measure technical and revenue efficiency at the household level, which builds on the definition of the revenue-based production possibility set:

푃푐 = {(푥, 푦̅)|푥 ≥ 푋흀, 푦̅ ≤ 푌̅흀, 흀 ≥ 0} (5.1) where x is a vector of inputs of a particular farm, X is vector of inputs of all farms, lambda is the intensity

푇 factor (weights inputs and outputs in final solution), 푌̅ = (푦̅1, … . , 푦̅푚), and 푦̅푗 = (푝1푗푦1푗, … . , 푝푚푗푦푚푗) , with y a vector of m outputs and pj the unit price for output j. For the analysis in this study, revenue efficiency is determined as if households make decisions on the combination of outputs to produce given their endowments on labor, land, capital and materials. Based on this, two linear programming (LP) problems are used to evaluate technical and revenue efficiency:

LP problem 1: 푇퐸표 = max 휃 (5.2)

푥표 ≥ X 휆 (5.3)

휃푦̅표 ≤ Y̅ 휆 (5.4) 휆 ≥ 0 (5.5) LP problem 2:

∗ 푒푦̅표 = max 푒푦̅ (5.6)

푥표 ≥ X 휆 (5.7) 푦̅ ≤ Y̅ 휆 (5.8) 휆 ≥ 0 (5.9) where e is a vector of 1s, xo represents inputs of a production unit (o), TEo is the measure of technical efficiency of production unit (o) and the revenue efficiency is calculated using the optimal value from LP

2 as follows:

∗ 푒푦̅표 푅퐸 = ∗ (5.10) 푒푦표

Revenue efficiency can then be decomposed into technical efficiency and allocative efficiency:

39

푅퐸∗ = 휃̅∗ × 퐴퐸∗ (5.11)

Technical efficiency in equation (5.11) can be further decomposed into scale efficiency (SE) and a measure of “pure” technical efficiency. To accommodate variable returns to scale (VRS) in the calculation of technical efficiency we introduce an extra equation in LP 1 (see Tone 2002, 1229):

e휆 = 1 (5.12)

Imposing this constraint in PL 1 we obtain TEvrs, a measure of technical efficiency with VRS. Scale efficiency is then calculated as follows:

푇퐸 푆퐸 = (5.13) 푇퐸푣푟푠

The final decomposition of revenue efficiency is then expressed as:

∗ ∗ 4 푅퐸 = 푇퐸푉푅푆 × 푆퐸 × 퐴퐸 (5.14)

where TEVRS×SE=TECRS.

Data for the analysis came from the Encuesta Permanente de Hograes of the Dirección General de

Estadística, Encuestas y Censos. We categorized data on animals into six groups: cattle, pigs, sheep and goat, poultry, equine, and other (fish, hives, rabbit). We classify crop commodities into the following groups: (i) cereals; (ii) cash crops (, cotton, sugar, , ); (iii) roots and tubers; (iv) fruits and vegetables; (v) oil crops; (vi) pulses; (vii) other (herbs, floriculture, non-identified crops) and aggregated the data by these groups.

The animal stock was converted into cow-equivalent units. Feed was calculated as value of crop production used as animal feed and feed purchases. Total farm area was calculated as the sum of total areas of different crops, cultivated and natural pasture, forestry and other land uses. Capital stock of

4 In the analysis in the next section we refer to TEVRS simply as TE

40 machinery includes the total value of tractor and milking machine as well as the total value of machinery/equipment (across all types). Quantity and value of purchased inputs were grouped into the following categories: (i) seed, fertilizer, pesticide (insecticide/fungicide), feed products (mineral supplements, “balanceados”, maize), veterinary products (vaccines/veterinary products). Labor data is reported in terms of total labor cost and there is no differentiation made on the type of labor. To obtain values of labor “quantities” we calculate the share of each household in total labor in each departamento and then use these shares to allocate census data on number of workers and other sources to each household.

41

6. AGRICULTURAL GROWTH AND EFFICIENCY

We now turn to the discussion of the results of the efficiency analysis. Comparisons were conducted separately for the four departamentos. Households in each departamento were grouped by type in FA households (less than 50 hectares) and commercial producers (more than 50 hectares). Each of these two groups was then sub-divided in three groups: a) Efficient households, those with revenue efficiency (RE) greater than 0.8; b) inefficient households which are those with RE≤0.40; and c) average households, those with RE>0.4 and RE≤0.8. Average values of farm size, input use and output mix are presented for each of the six groups in each departamento and year.

San Pedro

Table 6.1, presents production indicators of efficiency groups of FA producers in San Pedro. The first three collumns of the table show values of input use and of the mix of outputs produced by the three groups of efficiency in 1997. The results clearly show that in that year, efficient FA households were specialized in the production of fruits and vegetables (92 percent of total output value). The share of fruits and vegetables in the average group is still high but smaller than that of efficient producers (80 percent), while fruits and vegetables represent only 12 percent of total output value in the group of inefficient producers. Notice that efficient farms produced with relatively high levels of capital per worker, which is mostly capital in permanent crops. None of the farms in the three efficiency groups uses fertilizer, and the use of machinery is low (capital in machinery per worker). The inefficient group of farmers is a group of livestock producers, with a share of 70 percent of livestock products in total output.

The last three columns of Table 6.1 present the output and input mix of FA farmers in the three efficiency groups in 2008. Major changes occurred between 1991 and 2008. First is the significant increase in the average farm area of the three groups. The average area of an efficient FA producer in San

Pedro in 2008 was 7.4 hectares, up from 2.7 in 1991. Efficient farmers have also diversified away from fruits and vegetables into livestock and cash crops (28 and 21 percent of total output, respectively),

42 although fruits and vegetables still represent a large component of total output (35 percent). The group of average producers has also diversified away from fruits and vegetables which in 2008 represented only 5 percent of total output. Notice that oil crops and cereals contribute only with 13 to 20 percent of total output, with their highest contribution in the most inefficient group of farmers. On the input side, efficient farmers still produce with higher levels of capital per worker but in 2008 the use of machinery increased

(1.3 per worker compared to 0.4 in 1991).

Table 6.1–Classification of FA households in groups of revenue efficiency, departamento of San Pedro, 1997 and 2008. 1997 2008 Efficient Average Inefficient Efficient Average Inefficient Inputs Farm area 2.7 3.9 4.9 7.4 6.8 10.7 Land/worker 3.6 4.5 3.6 7.5 6.2 5.7 Capital/worker 23.3 12.7 2.0 3.3 1.1 0.9 Fertilizer/worker 0.0 0.0 0.0 0.0 0.0 0.1 Machinery/worker 0.4 0.4 0.3 1.3 0.9 0.7 Animal stock/worker 1.5 1.5 1.7 1.1 0.7 0.6 Output mix (%) Crops 93.0 84.9 30.3 71.7 55.9 44.2 Livestock 7.0 15.1 69.7 28.3 44.1 55.8 Fruits and veg. 92.1 79.7 12.2 34.7 5.0 3.7 Cash crops 0.6 3.1 7.2 21.0 23.6 12.1 Roots and tubers 0.1 1.1 4.8 2.6 10.1 7.4 Oil crops 0.1 0.4 2.1 11.2 13.3 15.7 Cereals 0.1 0.5 2.6 1.9 3.1 3.9 Pulses 0.0 0.1 1.4 0.3 0.8 1.2 Beef 4.3 8.4 44.7 19.8 19.6 28.8 Milk 0.5 2.8 10.8 3.5 13.6 13.1 Other livestock 2.2 3.9 14.2 5.1 10.9 14.0 Source: Author’s calculations based on data from MGA-DCA (2009)

Table 6.2 presents results of the efficiency grouping of commercial farmers in San Pedro in 1991 and

2008. The first thing to notice is that the number of commercial farms in San Pedro in 1991 was very small, with an average area of 560 hectares. These producers were specialized in extensive livestock production with a share of milk production in total output of 74 percent and only 17 percent share of

43 crops in total output. This extensive producers were highly inefficient when compared to smaller producers, which explains why all commercial farmers in 1991 are included in the group of inefficient producers.

In 2008, commercial agriculture in San Pedro has been completely transformed. The extensive livestock production has lost its importance and we observe now mixed crop-livestock production systems with average farm areas in all groups of about 200 hectares, and where fruits and vegetables contribute with about 20 percent of total output in all efficiency groups. The average farm size of efficient commercial farmers in 2008 was 193 hectares, representing 100 hectares per worker, and with relatively high levels of capital, machinery and fertilizer use per worker when compared to FA efficient farms. Most importantly, crops produced by commercial farms were roots and tubers, fruits and vegetables and cash crops. The major difference between most efficient producers and other producers is that efficient farmers specialized in crop production with only 13 percent share of livestock in total output. Livestock contributes with 44 percent of total output among inefficient farmers. Soybean and cereal production did not have a major impact in San Pedro during the analyzed period. In this departamento, the total cultivated area of soybeans in 2008 was only 185 thousand hectares, with a total area in Paraguay for tha same year of 2.5 million hectares. In 2012, soybean cultivated area in San Pedro increased to 289 thousand hectares. With updated data on household production we might be observing further changes in output composition and production among efficent farmers at present.

44

Table 6.2–Classification of commercial farms in groups of revenue efficiency, departamento of San Pedro, 1997 and 2008. 1997 2008 Inefficient Efficient Average Inefficient Inputs Farm area 559.8 192.8 204.5 173.6 Land/worker 34.1 99.7 135.0 81.3 Capital/worker 6.6 15.7 9.4 12.1 Fertilizer/worker 0.0 12.8 1.1 0.0 Machinery/worker 5.0 12.1 4.1 9.1 Animal stock/worker 1.7 4.4 5.7 5.5 Output mix (%) Crops 17.3 84.8 57.3 53.2 Livestock 81.6 13.1 41.2 43.4 Fruits and veg. 8.9 22.9 23.8 21.3 Cash crops 5.2 17.7 6.1 5.8 Roots and tubers 0.7 38.6 23.4 19.8 Oil crops - 0.0 0.6 0.8 Cereals 2.5 0.7 3.2 4.4 Pulses - 4.9 0.3 1.2 Beef 5.9 8.6 16.0 14.1 Milk 74.2 4.3 21.8 21.3 Other livestock 2.6 2.2 4.9 11.3 Source: Author’s calculations based on data from MGA-DCA (2009)

Tables 6.3 and 6.4 show the results of the calculated revenue efficient indicator and its components, allocative efficiency (price efficiency), technical and scale efficient.The first four rows of Table 6.3 present the efficieny values for all indicators for the three groups of efficiency in 1997 and 2008. The comparison of efficiency across groups is not relevant as households are grouped by value of RE, so differences between groups result from the classification defined a priori. More interesting is to look at the RE decomposition and then look at the components that explain differences between groups. For example, RE of the average group in 1997 is 0.59 and that of the inefficient group is 0.15, but looking at the other indicators we find that most of the differences between the average and the efficient group is caused by low allocative efficiency (AE=0.68), which means that the average group is using the wrong mix of outputs given output prices. Why is RE in the inefficient group only 0.15? The problem of allocative inefficiency in this group is even bigger than in the average group (0.46 compared to 0.68 and

45

0.94 in the average and efficient groups, respectively). Adding to this, there is also a low value of technical efficiency (0.49), much lower than the 0.89 value of the average group.

The bottom-half of Table 6.3 presents the efficiency decomposition of the different groups compared to the values in the most efficient group. For the year 1997, the difference in RE between the efficient and the average group is explained as follows: 71 percent of the difference is the result of allocative inefficiency in the average group, and 25 percent is attributed to technical inefficiency (TE). Only 4 percent of the difference results from scale inefficiency. In the case of the inefficient group, TE is the most important source of inefficiency. Fifty percent of the difference between the inefficient and the efficient groups result from TE, 40 percent from AE and 10 percent from SE. The results of the decompsition for 2008 are similar to those of 1997.

Table 6.3–Revenue efficiency decomposition for FA production in San Pedro, 1997 and 2008. 1997 2008 Efficient Average Inefficient Efficient Average Inefficient RE 0.93 0.59 0.15 0.94 0.54 0.15 TE 1.00 0.89 0.40 1.00 0.88 0.43 SE 0.99 0.98 0.83 1.00 0.95 0.84 AE 0.94 0.68 0.46 0.94 0.65 0.41 Difference with most efficient Average Inefficient Average Inefficient RE - 100 100 100 100 TE - 25 50 23 46 SE - 4 10 9 9 AE - 71 40 68 45 Source: Author’s calculations based on data from MGA-DCA (2009)

Table 6.4 shows the same results but for the group of commercial farmers. Technical efficiency (TE) is the major source of inefficiency in the inefficient group (59 percent), while AE explains 56 percent of the difference in efficiency between the average and the efficient group.

46

Table 6.4–Revenue efficiency decomposition for FA production in San Pedro, 1997 and 2008. 1997 2008 Inefficient Efficient Average Inefficient RE 0.01 1.00 0.55 0.11 TE 0.22 1.00 0.85 0.28 SE 0.64 1.00 0.90 0.88 AE 0.10 1.00 0.72 0.45 Difference with most efficient Average Inefficient RE - - 100 100 TE - - 27 59 SE - - 18 6 AE - - 56 36 Source: Author’s calculations based on data from MGA-DCA (2009)

Caaguazu

The case of Caaguazu presents a contrasting case with that of San Pedro. This departamento was a major cotton producer mostly under FA farms, but in recent years it has seen a fast expansion of commercial agriculture and of soybean production, which reached 319 thousand hectared in 2008 and 400 thousand hectares in 2012. In 1991, the average efficient producer had 4.2 hectares of farm area and was a livestock producer (70 percent of total output), also producing fruits and vegetables. This changed in 2008, and we observe that efficient producers have reduced the share of livestock products in total output, increasing the crop share to 60 percent. The share of fruits and vegetables in total output was reduced to 5 percent and cash crops and soybean increased their share in total output to 40 and 10 percent respectively.

47

Table 6.5– Classification of family agriculture farms in groups of revenue efficiency, departamento of Caaguazu, 1997 and 2008.. year 1997 2008 type Efficient Average Inefficient Efficient Average Inefficient Inputs Farm area 4.2 2.8 6.5 4.3 6.9 10.0 Land/worker 4.0 2.7 3.7 7.9 8.7 5.9 Capital/worker 3.1 1.0 1.7 2.0 1.3 1.1 Fertilizer/worker 0.0 0.1 0.1 0.3 0.3 0.0 Machinery/worker 0.5 0.1 0.4 3.1 0.9 0.7 Animal stock/worker 2.5 0.6 1.3 0.8 0.8 0.6 Output mix (%) Crops 28.7 38.2 24.3 59.4 34.6 35.6 Livestock 68.5 59.8 71.2 39.1 62.7 57.4 Fruits and veg. 26.4 15.9 5.7 5.0 7.9 5.9 Cash crops 1.2 11.1 7.0 40.1 10.2 11.3 Roots & tubers 0.7 8.3 5.8 3.2 6.6 10.6 Cereals 0.4 1.8 3.7 0.8 2.4 4.4 Oil crops - 0.3 1.1 10.0 6.7 1.9 Pulses - 0.7 0.9 0.4 0.8 1.6 Beef 28.8 37.6 42.3 31.5 38.3 31.3 Milk 36.1 12.9 12.8 3.3 16.4 13.8 Other livestock 6.5 11.3 20.6 5.7 10.7 19.3 Source: Author’s calculations based on data from MGA-DCA (2009)

A major transformation occurred among commercial farmers in Caaguazu as shown in Table 6.6. As in the case of San Pedro, large farmers in 1991 were mostly livestock producers. In Caaguazu, these farmers worked an average area of 252 hectares, with 68 percent of total output being livestock. They also produced a small proportion of cash crops, cereals and fruits and vegetables. These large farms were a very small proportion of the total number of farms in Caaguazu, and were mostly inefficient compared to other production units.

By 2008, the most efficient commercial producer in Caaguazu was a farmer with an average area of almost 300 hectares, specialized in oil crops (74 percent of total output) and also producing cereals (14 percent of total output) and beef and milk (10 percent). The average producer in 2008 is even more specialized in oil crop production (77 percent) and cereals (18 percent of total output), but its lowest efficiency compared to that of the efficient group could be related to a higher level of capital in machinery

48 per worker, probably needed to produced at this specialized level. Inefficient producers, on the other hand, have smaller farms (90 hectares) and are more diversified into livestock production (63 percent of total output). Results of the efficiency decomposition for Caaguazu producers are similar to those of San

Pedro and can be found in the Appendix.

Table 6.6– Classification of commercial farms in groups of revenue efficiency, departamento of Caaguazu, 1997 and 2008. 1997 2008 Inefficient Efficient Average Inefficient Inputs Farm area 252.3 298.8 235.4 90.2 Land/worker 15.8 49.7 74.7 55.3 Capital/worker 9.9 7.1 17.7 9.1 Fertilizer/worker - 2.8 4.2 5.6 Machinery/worker 6.2 8.6 17.1 10.0 Animal stock/worker 3.7 1.5 0.6 3.1 Output mix (%) Crops 36.9 88.5 95.8 31.7 Livestock 58.1 11.2 3.3 63.3 Fruits and veg. 7.2 0.0 0.2 1.1 Cash crops 12.4 0.8 0.0 8.4 Roots & tubers 7.0 0.1 0.4 6.8 Cereals 9.8 13.8 18.3 12.9 Oil crops 0.5 73.8 76.9 0.8 Pulses - - - 1.6 Beef - 7.6 - 16.3 Milk 37.1 3.4 2.3 11.9 Other livestock 26.0 0.4 1.9 40.1 Source: Author’s calculations based on data from MGA-DCA (2009)

Alto Parana

This departamento was part of the agricultural frontier during the “move to the east” to incorporate new lands to production. Among the farmers obtaining lands were experienced producers from the neighboring Brazil, and large areas of the departamento are cultivated by Brazilian farmers

49

(Braziguayos). Per Galeano (2012), 55 percent of land owners in Alto Parana in 2008 were Brazilians and only 38 percent were Paraguayans.

Table 6.7 shows main characteristics of FA households in the three efficiency groups in Alto Parana.

In 1997 the efficient FA producer used 1.6 hectares to produce cash crops, roots and tubers and milk (52 percent of crops and 37 percent of livestock in total output). Low values of land and capital per worker indicate that this was mostly labor-intensive production. With significantly large farm areas, the average group (12.7 hectares) and the inefficient group (7.5 hectares) were producing oil crops and livestock. To do this they used higher levels of capital and machinery per worker.

How do average efficiency groups of FA look in 2008? This is shown in the last three columns of

Table 6.7. The area of efficient farms is now even smaller than in 1997 (1.1 hectares), and the average and inefficient groups show smaller farm areas than in 1991, with the largest average farm size in the inefficient group (5.2 hectares). Capital per worker has also decreased in all groups compared to farms in

1991, except in the inefficient group. The efficient and average groups are now specialized in soybean production (60 and 90 percent of output value, respectively). In contrast, inefficient producers are not producing oil crops but more than half of the value of output in these groups comes from roots and tubers

(55 percent), and they also produce cash crops (26 percent) and cereals (10 percent).

50

Table 6.7– Classification of family agriculture farms in groups of revenue efficiency, departamento of Alto Parana, 1997 and 2008. 1997 2008 Efficient Average Inefficient Efficient Average Inefficient Inputs Farm area 1.6 12.7 7.5 1.1 2.2 5.2 Land/worker 2.8 7.5 3.6 3.1 3.9 4.0 Capital/worker 2.1 6.1 3.1 1.6 1.4 5.7 Fertilizer/worker - 0.3 0.1 3.6 2.6 0.5 Machinery/worker 0.6 4.2 2.2 0.1 1.9 7.4 Animal stock/worker 1.6 1.9 1.0 1.8 0.9 0.9 Output mix Crops 52.0 54.1 29.9 74.2 95.1 92.1 Livestock 37.2 41.6 65.8 24.3 4.1 6.1 Cash crops 18.9 6.5 3.5 1.4 26.4 Cereals 4.2 1.1 3.3 12.2 6.2 10.2 Oil crops 9.9 26.2 18.4 59.2 89.0 - Pulses 1.3 13.4 1.0 - - Roots and tubers 16.4 3.4 3.0 1.4 - 55.5 Fruits and veg. 1.4 3.4 0.7 - - - Milk 30.2 16.6 11.8 8.9 3.4 - Beef 18.8 43.4 9.6 - - Other livestock 7.0 6.3 10.6 5.7 0.7 6.1 Source: Author’s calculations based on data from MGA-DCA (2009)

Table 6.8 characterizes commercial farmers in Alto Parana, presenting average figures of input use and output mix in the three efficiency groups. All farms show high levels of capitalization (capital per worker), which has increased further between 1991 and 2008 among efficient producers. Land area of efficient producers has also increased from 121 hectares in 1991 to 290 hectares in 2008. Main crops for all farmers are oil crops and cereals and the only major change observed in the output mix between 1991 and 2008 is the increased share of livestock production in total output among most efficient farmers, which is also probably related to the increase in farm area and new technologies using rotations with cultivated pastures.

51

Table 6.8– Classification of commercial farms in groups of revenue efficiency, departamento of Alto Parana, 1997 and 2008. 1997 2008 Efficient Average Inefficient Efficient Average Inefficient Inputs Farm area 121.0 119.1 60.2 290.3 64.3 124.9 Land/worker 147.0 74.4 92.4 241.6 52.0 89.0 Capital/worker 55.7 48.9 82.5 80.4 44.7 55.7 Fertilizer/worker 3.7 1.8 6.0 14.6 1.5 Machinery/worker 45.0 46.9 31.1 61.3 42.5 41.0 Animal stock/worker 11.5 2.0 51.3 19.0 2.1 14.7 Output mix Crops 84.0 61.3 59.2 75.9 99.6 92.1 Livestock 15.3 37.4 38.7 23.9 0.4 6.9 Cash crops 4.4 4.6 1.2 Cereals 0.9 8.5 10.1 18.0 17.4 30.8 Oil crops 81.0 39.8 35.5 56.4 81.7 60.5 Pulses 0.5 1.4 0.8 0.1 Roots and tubers 1.0 6.6 4.8 0.0 0.1 0.8 Fruits and veg. 0.6 0.6 3.4 0.1 0.4 Milk 11.0 18.5 16.9 1.8 1.6 Beef 2.5 15.6 13.6 21.9 3.0 Other livestock 1.9 3.3 8.3 0.2 0.4 2.2 Source: Author’s calculations based on data from MGA-DCA (2009)

In summary, the evidence from the analysis of production efficiency and the changes that occurred between 1991 and 2008 shows considerable heterogeneity in the impact of agricultural growth in FA and commercial farms in Paraguay. In San Pedro and Caaguazu, departamentos with high concentration of FA households, efficient FA producers in 1991 were specialized in crop production with a large share of fruits and vegetables in total output. Changes in 2008 brought a significant increase in the average farm area of the three groups with efficient farmers diversifying away from fruits and vegetables into livestock and cash crops and still with small incidence of oil crops in total output, while efficient FA producers increased the use of machinery and capital per worker.

In the case of San Pedro, commercial farmers in 1997 were few and mostly extensive livestock producers. By 2008, the extensive livestock production has virtually disappeared and we observe mixed crop-livestock production systems with average farm areas of around 200 hectares in all groups. In all

52 cases, fruits and vegetables contributed with about 20 percent of total output, and households were using relatively high levels of capital, machinery and fertilizer per worker. Soybean and cereal production did not have a major impact in San Pedro during the analyzed period.

The case of Caaguazu has some different characteristics from that of San Pedro. This departamento was a major cotton producer mostly under FA production, but in recent years it has seen a fast expansion of commercial agriculture and of soybean production, which reached 319 thousand hectares in 2008 and

400 thousand hectares in 2012. What happened to FA agriculture in this context? In 1991, the average FA efficient producer was a livestock producer, also producing fruits and vegetables. In 2008, the average efficient farmer was relying less in production of livestock and fruits and vegetables, which were replaced by cash and oil crops. A major transformation occurred also among commercial farmers in Caaguazu where as in the case of San Pedro, large farmers in 1991 were mostly livestock producers. By 2008, the average efficient commercial producer was a farmer with an average area of 300 hectares specialized in oil crops and producing cereals, beef and milk.

Alto Parana saw the expansion of commercial agriculture as part of the shift of the agricultural frontier to the east. In Alto Parana, the farm area of an average FA producer was the smallest among all cases presented here, and decreased further between 1991 and 2008, with capital per worker also decreasing, in what seems to be a process of reduced share of agricultural income in total household income. At the same time, commercial farmers have increased farm area and continue to expand soybean and cereal production with increased share of livestock in total output.

We conclude that the situation of FA in Paraguay is much more diverse and complex than the simple claims of decomposition and disappearance as the result of the expansion of capitalist farmers. In San

Pedro and Caaguazu the evidence until 2008 shows that average area of efficient farmers increased, expanding production of mixed systems that include fruits and vegetables, cash crops and livestock. There is no evidence showing that expansion of commercial agriculture between 1991 and 2008 in San Pedro and Caaguazu had played a major role displacing FA. What the evidence seems to be showing is that this expansion displaced inefficient extensive livestock production, bringing more efficient and capitalized

53 farms. FA households that did not move out from agriculture were able to increase average farm area and resources. The situation of FA in Alto Parana is different, first because this region has seen a rapid expansion of commercial farming since it was incorporated to the agricultural frontier, and smallholders could never compete with efficient producers during the expansion of soybean production using a technology that gets its best result by saving on labor and incorporating large land areas to production.

54

7. SUMMARY AND CONCLUSIONS

This study looked at the recent performance of Paraguay’s agriculture and the challenges the country faces to sustain growth. At the center of these challenges is the debate on the role of family agriculture and smallholders in a future growth strategy. A sector traditionally supported by the government when the country was a producer and exporter of cotton, FA has been shrinking since 2002 and at present, does not seem to have a clear path for growth. There are two main factors explaining the reduction in the number of FA producers. The first is the result of fast growth experienced by the Paraguayan economy in the past two decades, which has accelerated the reallocation of labor from agriculture to other sectors, mainly to services. Economic growth generates opportunities for workers within agriculture and in other sectors,

“pulling” workers out from agricultural family production. This is potentially a desirable effect when is part of the process of development as it results in increased labor productivity and income. The second factor contributing to the reduction in the number of smallholders, in their share in total output and in the use of factors is competition with commercial agriculture. This could be a negative effect (for FA and eventually for the economy), one that “pushes” smallholders out of agriculture and it is not necessarily related to the creation of new employment opportunities.

Between 1991 and 2008 the number of family workers in agriculture decreased significantly, reaching in 2008, 67 percent of the total number observed in 1991. At the same time, total area of the FA crops in

2008 decreased to only 48 percent of its level in 1991. As some authors argued in the past, the 2000s represent a turning point for FA development in Paraguay, given that until 2002, the total area of farms of less than 20 hectares was still increasing, a trend that reversed after this year. Are these changes necessarily a bad outcome, part of a process of impoverishment of the rural population resulting from displacement of FA by the commercial sector as is normally assumed in previous studies? This is not necessarily the case.

There is evidence showing that agricultural growth between 2002 and 2008 had positive effects on the rural population, despite (because of) the decline of family agriculture. First, as shown in this study, rural

55 poverty between 2003 and 2015 decreased from more than 50 percent to 30 percent. This shows that the decline of FA was not merely the result of displacement by the commercial sector but mostly a consequence of better opportunities for workers, a pull rather than a push effect of growth. Second, the reduction of output of crops traditionally produced by FA was not the result of competition with the commercial sector, but mostly a consequence of the collapse of cotton production due to highly degraded land and low productivity because of inadequate practices and the lack of adapted varieties, a failure of a government program for FA. Third, when looking at changes in departamentos with diverse initial conditions, the results show a much-varied outcome of changes in agriculture. For example, in San Pedro and Caaguazu, the evidence shows that efficient FA households increased average farm area from 2.4 in

1991 to 7.4 hectares in 2008. These farmers, producing with relatively high levels of capital per worker, diversified away from fruits and vegetables into livestock and cash crops, although fruits and vegetables still represented a large component of total output, and they. Furthermore, there is no evidence showing that expansion of commercial agriculture between 1991 and 2008 in San Pedro and Caaguazu had played a major role displacing FA. What the evidence seems to be showing is that this expansion displaced inefficient extensive livestock production, bringing more efficient and capitalized farms.

In contrast, in Alto Parana, already with many commercial farms in the 1990s, the farm area of an average FA producer was the smallest among all cases presented here, and decreased further between

1991 and 2008, with capital per worker also decreasing, in what seems to be a process of reduced share of agricultural income in total household income in FA. At the same time, commercial farmers increased farm area and continue to expand soybean and cereal production with increased share of livestock in total output, which indicates that the possibility of FA to compete in this highly specialized commercial agricultural region is low.

We conclude that the situation of FA in Paraguay is much more diverse and complex than the simple claims of decomposition and disappearance as the result of the expansion of capitalist farmers. Our results show that there are opportunities for FA in the context of a growing and more efficient agricultural sector, at least in some areas and in particular production systems. However, it will be difficult for FA farmers to

56 take advantage of these opportunities without more favorable policies and support from the government.

What are the options then for FA in Paraguay? If the reallocation of labor away from agriculture continues and even accelerates in the coming years as part of the process of economic development, given that commercial agriculture continues to grow together with the development of infrastructure, the energy sector, transportation and related services, the country could face reduced opportunities of productive employment in non-agriculture. In this context, one of the options for the government is to promote the development of other promising agricultural activities with the goal of increasing employment opportunities in rural areas while achieving a much-needed diversification of agricultural production and exports. One neglected role of the government so far has been the investment in agricultural R&D. The experience with cotton ended with highly degraded land and low productivity because of inadequate practices and lack of technologies, while new opportunities have been lost because of the lack of adapted technologies (for example, sesame exports).

One of the limitations of this study is that the analysis of the effects of agricultural growth focused on the period 1991-2008, due to lack of reliable data for more recent years. An analysis of the changes in FA in the last ten years could give a new perspective of the future of FA in Paraguay.

57

REFERENCES

Altieri, M. A., and Koohafkan, P. (2008). Enduring farms: climate change, smallholders and traditional farming communities (Vol. 6). Third World Network (TWN).

Avila, A. and Evenson, R.E. (2005). “Crescimento da Produtividade Total dos Fatores. O Papel do Capital Tecnológico”. Revista de Política Agrícola 2, 89-109.

Balassa, B. (1965) “Trade Liberalisation and Revealed Comparative Advantage” The Manchester School of Economics and Social Studies, no.33, May

Deloitte. 2015. La economía paraguaya en los últimos 20 años. Por Desarrollo En Democracia (DENDE) Available at: https://www2.deloitte.com/py/es/pages/about-deloitte/articles/la-economia- paraguaya-en-los-ultimos-20-anos.html

Dirección General de Estadística, Encuestas y Censos. 2015. Principales Resultados de Pobreza y Distribución del Ingreso. Asuncion, Paraguay.

Dirección General de Estadística, Encuestas y Censos. Encuesta Permanente de Hogares. Asunción, Paraguay.

FAO. 2013. “Pobreza rural y políticas públicas en América Latina y el Caribe.” FAO – Santiago, Chile, 013. 308 pg.

FAO (Food and Agriculture Organization of the United Nations). FAOSTAT Statistics Database. [Rome] FAO: accessed Jun 2016.

Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 253-290.

Galeano, L. A. 2012. El caso de Paraguay, in: M. Vega, JR Molinas Vega, J.R., Machado, A.S., Zegarra Méndez, E., Phillips, J., Reydon, B.P., Thurner, M., Stringer, R., Shearer, E.B., S Mesbah, D. and Dunn, E.G., eds. Dinámicas del mercado de la tierra en América Latina y el Caribe: concentración y extranjerización (No. E14-319). FAO, Roma (Italia), pgs: 407-552

Hanratty, D. M. and S. W Meditz. 1988. "Paraguay: A Country Study: Land reform and land policy". Library of Congress, Washington D.C.

International Labor Organization (ILO). 2016. ILOSTATS. Geneva, ILO. https://www.ilo.org/ilostat/faces/ilostat-home/home?_adf.ctrl- state=iytffkvgu_4&_afrLoop=371012627881074#!.

Kuznets, S.. 1965. Economic growth and structure. New York: W. W. Norton.

McMillan, M., D. Rodrik and I. Verduzco-Gallo. 2014. Globalization, Structural Change, and Productivity Growth, with an Update on Africa, World Development, 63: 11–32.

Ministerio de Agricultura y Ganadería, Dirección de Censos y Estadísticas Agropecuarias. 2009. Censo Agropecuario Nacional 2008. San Lorenzo, Paraguay. Available at: http://www.mag.gov.py/Censo/Book%201.pdf

58

Ministerio de Agricultura y Ganadería. 2014. Zonificación Agroecológica de Rubros Agropecuarios del Paraguay. Dirección General de Planificación, Unidad de Estudios Agroeconómicos. Available at: http://www.mag.gov.py/Censo/Book%201.pdf

Nin-Pratt, A., P. Martel, C. E. Ludeña and C. Falconi. (2015). Productivity and the Performance of Agriculture in Latin America and the Caribbean: From the Lost Decade to the Commodity Boom. Inter-American Development Bank.

O'Donnell, C. J. (2008). An aggregate quantity-price framework for measuring and decomposing productivity and profitability change (No. WP072008). School of Economics, University of Queensland, Australia.

O'Donnell, C. J., and Fallah-Fini, S. (2011). Comparing Firm Performance Using Transitive Productivity Index Numbers in a Meta-frontier Framework (No. WP082011). School of Economics, University of Queensland, Australia.

Riquelme, Q. 2014. Agricultura Campesina y Desarrollo Sustentable. Déficits y carencias de una Política Pública Integral. Revista Paraguay Debate. Available at: http://paraguaydebate.org.py/?p=2136

Rodrik, D. (2008). The real exchange rate and economic growth. Brookings papers on economic activity, 2008 (2), pp.365-412.

Tone, K. (2002). “A Strange Case of the Cost and Allocative Efficiencies in DEA.” Journal of the Operational Research Society, 53: 1225-1231.

World Bank. 2016. World Development Indicators 2017. Washington, DC. © World Bank. https://data.worldbank.org/products/wdi”

59

ALL IFPRI DISCUSSION PAPERS

All discussion papers are available here They can be downloaded free of charge

INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE www.ifpri.org

IFPRI HEADQUARTERS 1201 Eye Street, NW Washington, DC 20005 USA Tel.: +1-202-862-5600 Fax: +1-202-862-5606 Email: [email protected]