Farm Size and Productivity

Transcription

1 Farm Size and Productivity Lessons from Recent Literature Douglas Gollin Oxford University FAO, IFAD, ISPC/CGIAR, and the World Bank Expert Consultation: Focusing Agricultural and Rural Development Research and Investment on Achieving SDGs 1 and 2 11 January 2018 D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 1 / 42

2 I. Introduction D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 2 / 42

3 Introduction Issues of farm size and productivity recur in discussions of agricultural development. Questions relate to development strategy and growth. What determines the size of farms? Are large farms more productive than small? Are small farms more productive than large? How much is farm size distorted by policies and by missing markets? Should we care about farm size for development strategy? Specic questions about smallholder agriculture: To what extent should development strategies prioritize smallholder agriculture? D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 3 / 42

4 Current Policy Issues Farm size is at the heart of current policy debates over issues such as: land grabbing (or FDI in agriculture, if you prefer!) land reform the degree of emphasis on smallholders in development strategies Equity issues related to farm size Poverty issues related to farm size D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 4 / 42

5 Why Do We Care about Farm Size and Productivity? Farm size in developing countries is very small, on average. Is this ecient? Or does it reect land market failures (which are very much in evidence)? If smallholder agriculture is highly productive, then: Trade-os between equity and eciency may not be very important. Land market failures may not be very signicant in explaining low levels of agricultural productivity. Targeting smallholder systems will also help to solve other development problems. If smallholder agriculture is unproductive, then these issues all need to be revisited. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 5 / 42

6 Conceptualization Issues: Farms and Farm Size Farms are dicult to conceptualize. When does a home garden become a farm? When does a part-time agricultural activity become a farm? These conceptual questions matter for identifying farms and for thinking about farm size. Farm size can be measured in many ways: Land area Value of output Value of sales Value of prots Employment Dierent denitions will lead to dierent conclusions about farm size distribution. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 6 / 42

7 Measurement Challenges: Productivity Productivity estimates depend on accurate measurement of inputs and outputs. Measurement is hard! Land: area, observable quality, unobservable quality Labour: quantity, skill, eort, task, timing Capital: type and vintage Intermediate goods: quantity, quality Prices: needed for comparisons across space and time D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 7 / 42

8 Dierent Productivity Measures Output per unit land (crop yield): Pro: fairly easy to calculated; comparable across locations Con: not very useful for animal agriculture and some crop commodities; fails to account for multiple uses of a crop (e.g., stover) Output per unit labour (average labour productivity): Pro: fairly easy to calculate; potential relationship to income Con: labour inputs are very dicult to measure in developing country contexts Total Factor Productivity (TFP) Pro: rich and useful measure of productivity dierences in a world with multiple inputs. Con: hard to measure and sensitive to assumptions about how inputs are combined. Productivity measurement is hard! D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 8 / 42

9 II. Descriptive Data on Farm Size D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 9 / 42

10 Background on Farm Size Most of the world's farms are small very small. Most of the world's farms are family managed... True also in the U.S. and Europe. Both US and EU dene farms in ways that allow for many small farms. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 10 / 42

11 US Smallholdings 20 percent of farms report < $1,000 in sales. Smallest 75% of US farms accounted for < 6% of gross sales, 25% of farmed area Largest 10% of farms accounted for > 75% of gross sales, > 40% of farmed area D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 11 / 42

12 EU Smallholdings Similarly, in the EU, there are large numbers of smallholdings. Very small farms accounted for: 47% of the holdings 39% of the regular farm workers and 23% of the total farm labour. But... only 7% of the farmed area, 2.5% of the total livestock units, 1.6% of the gross value. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 12 / 42

13 Average Farm Size across Countries Wide dispersion in farm size, but many developing countries have much smaller farm size and rely more heavily on small farms: Malawi: only 8% of holdings 2 ha or larger. Rwanda: only 6% of holdings 2 ha or larger Mozambique: 95% of holdings smaller than 4 ha EU-12: average farm size 6.0 ha EU-15: average farm size 22.0 ha EU-27: average farm size 12.6 ha United Kingdom (53.8 ha) France (52.1 ha) Germany (45.7 ha) Netherlands (25.0 ha) Spain (23.9 ha) US (169 ha) D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 13 / 42

14 III. Productivity Dierences across Countries D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 14 / 42

15 Labour Productivity in Agriculture Dierences across countries in average labour productivity are very large. These dierences are bigger for agriculture than for other sectors. Average labour productivity dierences in agriculture are arithmetically important in explaining the cross-country dispersion of income per capita; see Caselli (2005). Examine data to see what we can learn from cross-country patterns. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 15 / 42

16 Labour Productivity Data from FAO Numerator: gross agricultural output at international prices - at common set of prices of agricultural goods - no adjustment for intermediate usage Denominator: economically active population in agriculture D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 16 / 42

17 Agricultural Productivity Dierences Across Countries Ratio Richest Ten Percent over Poorest Ten Percent 50.1 Richest Quarter over Poorest Quarter 29.9 These are very large dierences in comparison to GDP per worker. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 17 / 42

18 Decomposing Agricultural Output per Worker Output per worker in agriculture: output worker = output land land worker output/land - i.e. yield, widely measured in both micro and macro studies land/worker - also widely measured in both micro and macro studies D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 18 / 42

19 Decomposing Agricultural Output per Worker Output per worker in agriculture: output worker = output land land worker output/land - i.e. yield, widely measured in both micro and macro studies land/worker - also widely measured in both micro and macro studies Where do the big dierences in output per worker come from? D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 18 / 42

20 FAO Estimates of Output per Unit Land Table: Tons Produced per Hectare of Staple Grains by Country Group Maize Rice Wheat Richest Ten Percent of Countries Richest Quarter Poorest Quarter Poorest Ten Percent of Countries Ratio of Top to Bottom Ten Percent Ratio of Top to Bottom Quarter D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 19 / 42

21 Output per Unit Land: Comments Substantial dierences between rich and poor countries. Richest countries produce at least twice as much grain per hectare as poorest. Clearly a signicant source of dierences across countries in agricultural productivity. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 20 / 42

22 Output per Unit Land: Comments Substantial dierences between rich and poor countries. Richest countries produce at least twice as much grain per hectare as poorest. Clearly a signicant source of dierences across countries in agricultural productivity. What about land per worker? D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 20 / 42

23 FAO Estimates of Land per Worker Arable Cropland (ha) / Agricultural Labour Fource Richest Ten Percent of Countries 44.6 Top Quarter 23.9 Bottom Quarter 1.3 Poorest Ten Percent of Countries 1.4 Ratio of Top to Bottom Ten Percent 31.2 Ratio of Top to Bottom Quarter 18.0 D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 21 / 42

24 Micro Estimates of Land Per Worker Are the cross-country data accurate? Independent estimates from Living Standards Measurement Surveys (LSMS) Measure: hectares per worker; rural households D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 22 / 42

25 Land per Worker: Some Micro Estimates from LSMS Malawi, 2010: 0.4 hectares / worker Ethiopia, 2011: 0.3 hectares / worker Tanzania, 2010: 0.3 hectares / worker Guatemala, 2003: 1.9 hectares / worker Nigeria, 2010: 0.5 hectares / worker D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 23 / 42

26 Direct Micro Measures of Output per Worker Some micro studies compute not only yield but also labor. Allows for direct comparisons of output per unit of labor. Data show very large dierences across agricultural production systems. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 24 / 42

27 Output per Unit of Labor, Maize Maize Country Year Yield Hours Output / Hour Source Kenya kg/acre Kg/Hr Suri (2011) Kenya kg/acre Kg/Hr Suri (2011) Malawi kg/ha Kg/Hr Smale (1995) South Africa kg/ha Kg/Hr Gouse et al. (2006) USA kg/acre Kg/Hr Foreman (2006) USA (Iowa) kg/acre Kg/Hr Iowa State D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 25 / 42

28 Output per Unit of Labor, Rice Rice Country Year Yield (kg/ha) Hours Output (kg) / Hour Java Java Java Java Burma 1930s Thailand 1960s Sri Lanka Philippines Taiwan Nigeria (Semi Irrigated) California USA D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 26 / 42

29 Output per Unit of Labor, Rice - Time Series Rice Country Year Yield (kg/ha) Hours Output (kg) / Hour USA Japan Japan Japan Korea (local vars) Korea (HYVs) Korea Korea Korea Japan (per 10a) Taiwan (Central) Taiwan (Central) Taiwan (Central) Taiwan (National) D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 27 / 42

30 Summary Points on Productivity Data Huge dierences across countries in output per unit of labour. Output per hour varies across contexts by an order of magnitude more than yield. Perhaps the focus should be on labour productivity dierences, not yield dierences! Dierences in output per unit of land are substantial but small in comparison to dispersion in land per unit of labor. Hours per hectare vary by enormous amounts across settings. Output per unit of labour is much higher in contexts where farm size is large. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 28 / 42

31 IV. The Inverse Relationship? D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 29 / 42

32 Farm Size and Measured Productivity A large literature has tested for yield dierences across farm size. Frequent nding: an inverse relationship between farm size and measured productivity. Typical approach regress an outcome measure (usually yield) on farm size, with a number of controls. A negative and signicant coecient is seen as evidence for the inverse relationship. Typical conclusion: small farms are highly productive. Consistent with a story dating back to Chayanov (1966) and characterized by Sen (1962)... Small farms self-exploit labor. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 30 / 42

33 Empirical Diculties Farm size is a choice; farms are typically smaller in more fertile areas. Much of the literature also compares small farms with slightly larger farms, rather than small with very large... Small farms are highly productive precisely because of failures in labor and capital markets. Not necessarily the case that they are technologically more productive. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 31 / 42

34 Measurement Issues Perhaps the inverse relationship simply reects measurement error. Small farms may underestimate land area or large farms may overestimate their area, systematically... No; the opposite may be true; but the inverse relationship holds even with GPS estimates of area instead of farmer reported area. [Carletto, Gourlay, and Winters (2015)]. Small farms may systematically over-report crop output. Yes, possibly. [Gourlay, Kilic, and Lobell (2017)]. Other measurement errors are also present; e.g., dierences in land quality. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 32 / 42

35 Inverse Relationship: A Summary Recent evidence casts some doubt on the inverse relationship. Even if it is present, farm size is a relatively weak variable in explaining output per unit of land. Much farm-level variation in yield is not explained by observable characteristics of farms or households [Gollin and Udry (2017)]. Production shocks, measurement error and heterogeneity in input quality are important. Even where the inverse relationship holds for yields, output per unit labour may be higher on large farms. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 33 / 42

36 V. Policy Issues D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 34 / 42

37 Policies Aecting Farm Size Many countries pursue policies intended to inuence farm size. Some seek to promote consolidation; e.g., through land market reforms intended to facilitate rental and transaction. Land titling and registry Direct support for investors seeking to assemble large tracts of land Growth corridors Other countries aim to limit consolidation Restrictions on sale or rental of land Legally determined limits on maximum farm size; e.g., through land redistribution or limits on land holdings. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 35 / 42

38 Do Policies Induce Misallocation Some striking evidence from macro analyses suggests that policies limiting land markets can lead to quantitatively important misallocation Examples: Adamopoulos, Brandt, Leight, and Restuccia (2017); Restuccia and Santaeulalia-Llopis (2017); Adamopoulos and Restuccia (2015) Land market restrictions may reduce sector output value by two-thirds or more! Potential methodological caveats discussed in Gollin and Udry (2017), but no doubt that land market failures are important for development. Look hard at policies restricting land markets or limiting farm size. But land distribution has important implications for equity and poverty. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 36 / 42

39 VI. Conclusions D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 37 / 42

40 Conclusions (1) All countries seem to have a large number of small, often part-time farms. Productivity per unit of land may be quite high. Productivity per unit of labor is often very low. Income from these farms is low. Small farms may produce higher output per unit of land than large farms, although measurement problems may aect this nding. However, large farms typically have higher output per unit of labour. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 38 / 42

41 Conclusions (2) Small farms are ubiquitous and will persist in developing countries (as they do in developed countries). In many developing countries, average farm size will continue to shrink due to demographic trends and limited availability of land. Many reasons to work towards making these smallholder systems productive. Equity Poverty Food security Nutrition Employment Promote sustainable management of natural resources But we should be realistic about the potential of small farms to generate income. Limits to what value / income can be produced on farms of 1-2 ha, even if yields are at the world frontier. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 39 / 42

42 Conclusions (3) Some smallholders will win the geographic lottery: Locations with access to lucrative markets Locations allowing for production of high-value commodities that cannot be produced in many places Locations permitting easy access to o-farm labour opportunities But many (most?) smallholders will nd that their farms cannot yield a middle class income, leading to an eventual (decades-long) process of labour exiting agriculture. Not necessarily movement out of rural areas; some will move into rural non-farm economy. Some into part-time farming (and part-time or full-time o-farm work) Roles for policy: Try to create more winners of the geographic lottery. Reduce frictions that limit movements out of agriculture. Plan and manage urban growth. D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 40 / 42

43 VII. References D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 41 / 42

44 References Adamopoulos, T., L. Brandt, J. Leight, and D. Restuccia (2017): Misallocation, selection and productivity: A quantitative analysis with panel data from China, Discussion paper, National Bureau of Economic Research. Adamopoulos, T., and D. Restuccia (2015): Land Reform and Productivity: A Quantitative Analysis with Micro Data,. Carletto, C., S. Gourlay, and P. Winters (2015): From Guesstimates to GPStimates: Land Area Measurement and Implications for Agricultural Analysis, Journal of African Economies, 24(5), Caselli, F. (2005): Accounting for cross-country income dierences, Handbook of economic growth, 1, Chayanov, A. V. (1966): The theory of peasant economy. Irwin, New York. Gollin, D., and C. Udry (2017): Heterogeneity, Measurement Error, and Misallocation: Evidence from African Agriculture,. Gourlay, S., T. Kilic, and D. Lobell (2017): Could the debate be over? errors in farmer-reported production and their implications for the inverse scale-productivity relationship in Uganda,. Restuccia, D., and R. Santaeulalia-Llopis (2017): Land misallocation and productivity, Discussion paper, National Bureau of Economic Research. Sen, A. K. (1962): An aspect of Indian agriculture, Economic Weekly, 14(4-6), D. Gollin (2018) Farm Size and Productivity FAO Expert Consultation 42 / 42