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Inputs, Productivity and Agricultural Growth in Sub-Saharan Africa

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Productivity and Efficiency Analysis

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

Abstract

This study employs a growth accounting approach to revisit past performance of agriculture in sub-Saharan Africa (SSA) and to analyze the relationship between the input mix used by SSA countries and productivity levels observed in the region. Findings show that improved technical efficiency has been the main driver of growth in recent years benefiting poorer, low labor productivity countries. Countries with higher output and input per worker have benefited much more from technological progress than poorer countries, suggesting that technical change has done little to reduce the gap in labor productivity between countries. Results also show that the levels of input per worker used in SSA agriculture at present are extremely low and associated with less productive technologies, and that technical change has shifted the world technological frontier unevenly, increasing the distance between SSA countries and those countries with the “right” input mix.

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Notes

  1. 1.

    Results of estimates and tests for all models are available from authors upon request.

References

  • Acemoglu D, Zilibotti F (2001) Productivity differences. Q J Econ 116(2):563–606

    Article  Google Scholar 

  • Alene AD (2010) Productivity growth and the effects of R&D in African agriculture. Agric Econ 41(3‐4):223–238

    Article  Google Scholar 

  • Arnade C (1998) Using a programming approach to measure international agricultural efficiency and productivity. J Agric Econ 49:67–84

    Article  Google Scholar 

  • Barro RJ, Sala-i-Martin X (1991) Convergence across states and regions. Brook Pap Econ Act 1991(1):107–182

    Article  Google Scholar 

  • Basu S, Weil DN (1998) Appropriate technology and growth. Q J Econ 113(4):1025–54

    Article  Google Scholar 

  • Block SA (1995) The recovery of agricultural productivity in Sub-Saharan Africa. Food Policy 20:385–405

    Article  Google Scholar 

  • Block S (2010) The decline and rise of agricultural productivity in sub-Saharan Africa since 1961 (No. w16481). National Bureau of Economic Research, Cambridge

    Book  Google Scholar 

  • Bravo-Ortega C, Lederman D (2004) Agricultural productivity and its determinants: revisiting international experiences. Estud Econ 31(2):133–163

    Google Scholar 

  • Bureau C, Färe R, Grosskopf S (1995) A comparison of three nonparametric measures of productivity growth in European and United States Agriculture. J Agric Econ 45:309–26

    Article  Google Scholar 

  • Caves DW, Christensen LR, Diewert WE (1982) The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica 50:1393–414

    Article  Google Scholar 

  • Cermeno R, Maddala G, Trueblood M (2003) Modelling technology as a dynamic error components process: the case of the inter-country agricultural production function. Econ Rev 22:289–306

    Article  Google Scholar 

  • Chavas JP (2001) An international analysis of agricultural productivity. In: Zepeda L (ed) Agricultural investment and productivity in develo** countries. Food and Agriculture Organization, Rome

    Google Scholar 

  • Coakley JA, Fuertes M, Smith RP (2006) Unobserved heterogeneity in panel time series models. Comput Stat Data Anal 50(9):2361–2380

    Article  Google Scholar 

  • Craig BJ, Pardey PG, Roseboom J (1997) International productivity patterns: accounting for input quality, infrastructure, and research. Am J Agric Econ 79(4):1064–1076

    Article  Google Scholar 

  • Eberhardt M (2012) Estimating panel time-series models with heterogeneous slopes. Stata J 12(1):61–71

    Google Scholar 

  • Eberhardt M, Bond S (2009) Cross-section dependence in nonstationary panel models: a novel estimator. MPRA Paper 17692 University Library of Munich. http://mpra.ub.uni-muenchen.de/17692/1/MPRA paper 17692.pdf. Accessed 15 February 2014

  • Eberhardt M, Teal F (2013) No mangoes in the tundra: spatial heterogeneity in agricultural productivity analysis. Oxf Bull Econ Stat 75:914–939

    Article  Google Scholar 

  • FAO (Food and Agriculture Organization of the United Nations) (2014) FAOSTAT database. http://www.fao.org/. Accessed 20 Jan 2014

  • Fuglie KO (2011) Agricultural productivity in Sub-Saharan Africa. In: Lee DL (ed) The food and financial crisis in Africa. Commonwealth Agricultural Bureau International, Wallingford

    Google Scholar 

  • Fuglie KO, Rada N (2012) Constraints to raising agricultural productivity in Sub-Saharan Africa. In: Fuglie KO, Wang SL, Ball VE (eds) Productivity growth in agriculture: an international perspective. Commonwealth Agricultural Bureau International, Wallingford

    Chapter  Google Scholar 

  • Fulginiti L, Perrin RK (1997) LDC agriculture: nonparameric Malmquist productivity indexes. JDev Econ 53:373–90

    Google Scholar 

  • Fulginiti L, Perrin RK (1999) Have price policies damaged LDC agricultural productivity? Contemp Econ Policy 17:469–75

    Article  Google Scholar 

  • Fulginiti LE, Perrin RK, Yu B (2004) Institutions and agricultural productivity in Sub-Saharan Africa. Agric Econ 4:169–80

    Article  Google Scholar 

  • Griliches Z (1964) Research expenditures, education, and the aggregate agricultural production function. Am Econ Rev 6:961–74

    Google Scholar 

  • Grossman G, Helpman E (1991) Innovation and growth in the global economy. MIT Press, Cambridge

    Google Scholar 

  • Growiec J (2012) The world technology frontier: what can we learn from the US states? Oxf Bull Econ Stat 74(6):777–807

    Article  Google Scholar 

  • Hayami Y, Ruttan V (1985) Agricultural development: an international perspective. Johns Hopkins University Press, Baltimore

    Google Scholar 

  • Jaffe A (1986) Technological opportunity and spillovers of R&D: evidence from firms’ patents, profits and market value. Am Econ Rev 76(5):984–1001, NBER Working Paper Series No. 1815

    Google Scholar 

  • Jerzmanowski M (2007) Total factor productivity differences: appropriate technology vs. efficiency. Eur Econ Rev 51:2080–2110

    Article  Google Scholar 

  • Kumar S, Russell RR (2002) Technological change, technological catch-up, and capital deepening: relative contributions to growth and convergence. Am Econ Rev 92(3):527–548

    Article  Google Scholar 

  • Lee HL, Hertel TH, Sohngen B, Ramankutty R (2005) Towards an integrated land use data base for assessing the potential for greenhouse gas mitigation. GTAP Technical Papers, 26

    Google Scholar 

  • Ludena CE, Hertel TW, Preckel PV, Foster K, Nin A (2007) Productivity growth and convergence in crop, ruminant, and non-ruminant production: measurement and forecasts. Agric Econ 37(1):1–17

    Article  Google Scholar 

  • Lusigi A, Thirtle C (1997) Total factor productivity and the effects of R&D in African agriculture. J Int Dev 9:529–38

    Article  Google Scholar 

  • Maddala GS, Wu S (1999) A comparative study of unit root tests with panel data and a new simple test. Oxf Bull Econ Stat 61(Special Issue):631–652

    Article  Google Scholar 

  • Nin A, Arndt C, Preckel PV (2003) Is agricultural productivity in develo** countries really shrinking? New evidence using a modified non-parametric approach. J Dev Econ 71:395–415

    Article  Google Scholar 

  • Nin-Pratt A, Yu B (2012) Agricultural productivity and policy changes in Sub-Saharan Africa. In: Fuglie KO, Wang SL, Ball VE (eds) Productivity growth in agriculture: an international perspective. Commonwealth Agricultural Bureau International, Wallingford

    Google Scholar 

  • Parente SL, Prescott EC (1994) Barriers to technology adoption and development. J Polit Econ 102(2):298–321

    Article  Google Scholar 

  • Pesaran MH (2004) General diagnostic tests for cross section dependence in panels. CESifo Working Paper 1229; IZA Discussion Paper 1240. University of Cambridge

    Google Scholar 

  • Pesaran MH (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74(4):967–1012

    Article  Google Scholar 

  • Pesaran MH (2007) A simple panel unit root test in the presence of cross-section dependence. JAppl Econ 22(2):265–312

    Google Scholar 

  • Pesaran MH, Smith RP (1995) Estimating long-run relationships from dynamic heterogeneous panels. J Econ 68(1):79–113

    Article  Google Scholar 

  • Prasada Rao DS, Coelli TJ (1998) Catch-up and convergence in global agricultural productivity, 1980–1995. CEPA Working Papers 4/98, Department of Econometrics, University of New England, Armidale

    Google Scholar 

  • Rambaldi AN, Prasada Rao DS, Dolan D (2007) Measuring productivity growth performance using meta-frontiers with applications to regional productivity growth analysis in a global context. Australasian Meeting of the Econometric Society, 3–6 July. Brisbane

    Google Scholar 

  • Segerstrom PS, Anant TCA, Dinapoulos E (1990) A Schumpeterian model of the product life cycle. Am Econ Rev 80:1077–1092

    Google Scholar 

  • Suhariyanto K, Thirtle C (2001) Asian agricultural productivity and convergence. J Agric Econ 52:96–110

    Article  Google Scholar 

  • Suhariyanto K, Lusigi L, Thirtle C (2001) Productivity growth and convergence in Asian and African agriculture. In: Lawrence P, Thirtle C (eds) Asia and Africa in comparative economic perspective. Palgrave, London

    Google Scholar 

  • Trueblood MA, Coggins J (2003) Intercountry agricultural efficiency and productivity: aMalmquist index approach. Mimeo. World Bank, Washington, DC

    Google Scholar 

  • USDA (United States Department of Agriculture) (2014). Economic research service: dataset on international agricultural productivity. http://www.ers.usda.gov/data-products/international-agricultural-productivity.aspx. Accessed 12 Aug 2014

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Acknowledgments

This work was undertaken as part of the Agricultural Science and Technology Indicators (ASTI) and the CGIAR Research Program on Policies, Institutions, and Markets (PIM) led by the International Food Policy Research Institute (IFPRI). Funding support for this study was provided by the Bill & Melinda Gates Foundation, the Canada Department of Foreign Affairs, and PIM. I thank Markus Eberhardt for sharing STATA code he developed and I adapted and used in the econometric analysis of this study. Any errors are my own responsibility. The opinions expressed here belong to the author, and do not necessarily reflect those of PIM, IFPRI, or CGIAR.

Author information

Authors and Affiliations

  1. Enviornment and Production Technology Division, International Food Policy Research Institute, 2033 K Street NW, Washington, DC, 20006, USA

    Alejandro Nin-Pratt

Authors
  1. Alejandro Nin-Pratt
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Correspondence to Alejandro Nin-Pratt .

Editor information

Editors and Affiliations

  1. Stern School of Business, New York University, New York, New York, USA

    William H. Greene

  2. Department of Economics, Carleton University, Ottawa, Ontario, Canada

    Lynda Khalaf

  3. Department of Economics, Rice University, Houston, Texas, USA

    Robin Sickles

  4. Department of Economics, McMaster University, Hamilton, Ontario, Canada

    Michael Veall

  5. Department of Economics, Carleton University, Ottawa, Ontario, Canada

    Marcel-Cristian Voia

Appendix

Appendix

Countries in our sample were grouped by agroecological zone (AEZ). These zones were defined based on data from Lee et~al. (2005). Table 11.5 presents the country classification by AEZ.

Table 11.5 Classification of SSA countries by agroecology
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Nin-Pratt, A. (2016). Inputs, Productivity and Agricultural Growth in Sub-Saharan Africa. In: Greene, W., Khalaf, L., Sickles, R., Veall, M., Voia, MC. (eds) Productivity and Efficiency Analysis. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-23228-7_11

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