Is climate variability subversive for agricultural total factor productivity growth? Long-run evidence from sub-Saharan Africa

Bannor, Frank and Dikgang, Johane and Gelo, Dambala (2021): Is climate variability subversive for agricultural total factor productivity growth? Long-run evidence from sub-Saharan Africa.

Abstract

It is expected that production in the agricultural sector will be significantly affected by climate change. Therefore, it is projected that countries with extreme climatic conditions will suffer a long-term decline in agricultural productivity beyond the short-term loss of production. Given the gross domestic product (GDP) value of agriculture in many sub-Saharan African (SSA) countries, the effects of climate change on agriculture are likely to permeate their economies. The long- and short-run effects of climate variability on agricultural total factor productivity (TFP) growth in 14 SSA countries are examined using panel data from 1995 to 2016. We employ a twofold approach. First, we use the Data Envelopment Approach (DEA) to calculate the Malmquist Index of Maize Productivity growth. Second, we apply a fully modified ordinary least square estimator and the Granger causality test in heterogeneous mixed panels to evaluate the long- and short-run impacts of climate variability on agricultural TFP development. The empirical results from the long-run analysis show that maize agricultural TFP is negatively associated with climate variability for only five countries. In the short run, our empirical estimation indicates no evidence of causality effect. To mitigate the negative long-run effects – and given that spending on R&D is found to produce negative effects in some of those five countries – policymakers should take immediate action to provide farmers with adequate and expeditious irrigation facilities, including the construction of dams to harvest and store rainfall water for future use.

• Item Type: MPRA Paper
• Language: English
• Keywords: total factor productivity; climate variability; data envelope approach; fully modified ordinary least square; heterogeneous mixed panel.
• Subjects: Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q16 - R&D ; Agricultural Technology ; Biofuels ; Agricultural Extension Services; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q18 - Agricultural Policy ; Food Policy; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q54 - Climate ; Natural Disasters and Their Management ; Global Warming

References

Abdelaziz, A. G., and Cashman, A. (2016). A methodology to assess the impact of climate variability and change on water resources, food security, and economic welfare. Agricultural Systems. https://doi.org/10.1016/j.agsy.2016.05.008.

Alam, S., Dulal, M. M., Hammoudeh, S. and Tiwarid, A. (2018). The nexus between access to electricity and labor productivity in developing countries. Energy Policy 122, 715-726. https://doi.org/10.1016/j.enpol.2018.08.009.

Alene, A. D. (2010). Productivity growth and the effects of R&D in African agriculture. Agricultural Economics 41, 223-238.

Algarini, A. (2017). The effect of human capital on total factor productivity growth in the Arab Gulf Cooperation Council countries. Doctoral dissertation, Colorado State University. CSU Libraries.

Antle, J. (2010). Adaptation of agriculture and the food system to climate change. Policy Issues Issue Brief 10-3, Washington, DC.

Badu-Apraku, B. and Fakorede, M. A. B. (2017). Advances in Genetic Enhancement of Early and Extra-Early Maize for Sub-Saharan Africa. Springer International Publishing AG. DOI 10.1007/978-3-319-64852-1_1.

Balk, B. M. and Zofío, J. L., (2018). The many decompositions of total factor productivity change. ERIM Report Series Research in Management. Erasmus Research Institute of Management, Erasmus University. No. ERS-2018-003-LIS.

Barrios, S., Ouattara, B. and Strobl, E. (2008). The impact of climatic change on agricultural production: Is it different for Africa? Food Policy 33, 287-298.

Bezabih, M., Chambwera, M. and Stage, J. (2011). Climate change and total factor productivity in the Tanzanian economy. Climate Policy, 11(6), 1289-1302, DOI: 10.1080/14693062.2011.57930.

Bilgic-Alpaslan, I. (2015). Three essays on estimation and determinants of productivity. Doctoral dissertation. Brandeis University International Business School.

Barnwal, P. and Kotani, K. (2013). Climatic impacts across agricultural crop yield distributions: An application of quantile regression on rice crops in Andhra Pradesh, India. Ecological Economics 87, 95-109.

Campbell, B. M., Thornton, P., Zougmoré, R., Van Asten, P. and Lipper, L. (2014). Sustainable intensification: What is its role in climate-smart agriculture? Current Opinion in Environmental Sustainability 8, 39-43.

Cooper, P. J. M., Dimes, J., Rao, K. P. C., Shapiro, B., Shiferaw, B. and Twomlow, S. (2008). Coping better with current climatic variability in the rain-fed farming systems of sub-Saharan Africa: An essential first step in adapting to future climate change? Agriculture, Ecosystems and Environment 126, 24-35.

Dell, M., Jones, B. F., Olken, B. A. (2012). Temperature shocks and economic growth: Evidence from the last half-century: dataset. Am. Econ. J. Macroecon. 4(3), 66-95.

Dercon, S. (2002). Income risk, coping strategies, and safety nets. World Bank Res Obs 17(2), 141-166.

Deressa, T., Hassan, R. and Poonyth, D. (2005). Measuring the impact of climate change on South African agriculture: the case of sugar cane growing regions. Agrekon 44(4), 524-542.

Dietz, S., Stern, N. (2015). Endogenous growth, the convexity of damage and climate risk: How Nordhaus' framework supports deep cuts in carbon emissions. Econ. J. 125, 574-620.

Deschenes, O. and Greenstone, M. (2007). The economic impacts of climate change: Evidence from agricultural output and random fluctuations in weather, The American Economic Review 97(1), 354-385.

Dickey, D. A., and Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49, 1057-1079.

Ding, L, Zheng, H and Zhao, X. (2018). The efficiency of the Chinese ocean economy within a governance framework using an improved Malmquist-Luenberger index. Journal of Coastal Research, 34(2), 272-281.

Emirmahmutoglu, F. and Kose, N. (2011). Testing for Granger causality in heterogeneous mixed panels. Economic Modelling 28, 870-876.

Espoir, K. D. and Ngepah, N. (2020). The effects of inequality on total factor productivity across districts in South Africa: A spatial econometric analysis. GeoJournal. https://doi.org/10.1007/s10708-020-10215-2.

Espoir, K. D. and Ngepah, N. (2021). Income distribution and total factor productivity: a cross-country panel cointegration analysis. International Economics and Economic Policy. https://doi.org/10.1007/s10368-021-00494-26.

Etwire, P. M., Fielding, D. and Kahui, V. (2018). Climate change, crop selection, and agricultural revenue in Ghana: A structural Ricardian analysis. Journal of Agricultural Economics, Vol. 70, No. 2, 2019, 488–506.

Exenberger, A. and Pondorfer, A. (2011). Rain, temperature and agricultural production: The impact of climate change in sub-Saharan Africa, 1961-2009. Working Papers in Economics and Statistics No. 2011-26, University of Innsbruck, Research Platform Empirical and Experimental Economics, Innsbruck.

Färe, R. and Grosskopf, S. (1990). Theory and calculation of productivity indexes: Revisited." Discussion Paper No. 90-8, Southern Illinois University, September 1990.

Färe, R., Grosskopf, S., Lindgren, B. and Roos, P. (1992). Productivity changes in Swedish pharmacies 1980-1989: A non-parametric Malmquist approach. Springer.

Färe, R., Grosskopf, S., Morris, M. and Zhongyang, Z. (1994). Productivity growth, technical progress, and efficiency in industrialized countries. American Economic Review 84(1), 66-82.

Fulginiti, L. E., Perrin, R. K. and Yu, B. (2004). Institutions and agricultural productivity in sub-Saharan Africa. Agricultural Economics 31(2-3), 169-180.

Gregory, A. and Hansen, B. (1996). Residual-based tests for cointegration in models with regime shifts. Journal of Econometrics 70(1), 99-126.

Hall, R. E., and Jones, C. I. (1999). Why do some countries produce so much more output per worker than others? The Quarterly Journal of Economics 114(1), 83-116.

Herzer, D. and Vollmer, S. (2012). Inequality and growth: Evidence from panel cointegration. J Econ. Inequal. 10, 489-503. DOI: 10.1007/s10888-011-9171-6.

Herzer, D., Nowak-Lehmann D., F. and Siliverstovs, B. (2006). Export-led growth in Chile: Assessing the role of export composition in productivity growth. The Developing Economies 44(3).

IPCC (2014). Climate change synthesis report. Working groups I, II, and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Geneva: IPCC; 2014. p. 151.

Johansen, S. (2000). Modeling of cointegration in the vector autoregressive model. Econ. Model. 17, 359-373.

Kalio, A. M., Mutenyo, M. J. and Owuor, G. (2012). Analysis of economic growth in Kenya: Growth accounting and total factor productivity. Journal of Business Management and Applied Economics 6, 1-22.

Kumar, K. R., Kumar, R. G., Ashrit, N. R. and Hansen, D. J. W. (2004). Climate impacts on Indian agriculture. Int. J. Climatol. 24, 1375-1393.

Letta, M. and Tol, R. (2019). Weather, climate, and total factor productivity. Environmental and Resource Economics 73(1), 283-305. ISSN 0924-6460.

Maudos, J., Pastor, J. and Serrano, S. (1999). Total factor productivity measurement and human capital in OECD countries. Economics Letters 63, 39-44.

Pedroni, P. (2000). Fully Modified OLS for Heterogeneous Cointegrated Panels, No 2000-03, Department of Economics Working Papers, Department of Economics, Williams College, https://EconPapers.repec.org/RePEc:wil:wileco:2000-03.

Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica 57, 1361-1401.

Persyn, D. and Westerlund, J. (2008). Error-correction-based cointegration tests for panel data. Stata J. 8, 232-241.

Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Discussion Paper No. 1240. The University of Cambridge, USC, and IZA Bonn.

Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics 22, 265-312. DOI: 10.1002/jae.951.

Phillips, P. (1995). Fully modified least squares and vector autoregression. Econometrica 63(5), 1023-1078. https://EconPapers.repec.org/RePEc:ecm:emetrp:v:63:y:1995:i:5:p:1023-78.

Sachs, J., Panatayou, T., Peterson, A. (1999). Developing Countries and the Control of Climate Change: A Theoretical Perspective and Policy Implications, CAER II Discussion Paper No. 44, Harvard Institute for International Development, Cambridge, MA.

Saad, W. (2017). Economic growth and total factor productivity in Lebanon. International Journal of Economics and Finance, 9(2), 159-171.

Schlenker, W. and Lobell, D. B. (2010). Robust negative impacts of climate change on African agriculture. Environmental Research Letters. DOI:10.1088/1748-9326/5/1/014010.

Stern, N. (2013). The structure of economic modeling of the potential impacts of climate change: Grafting gross underestimation of risk onto already narrow science models. J. Econ. Lit. 51(3), 838-859.

Toda, H. Y. and Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics 66, 225-250.

Westerlund, J. (2007). Testing for error correction in panel data. Oxf. Bull. Econ. Stat. 69, 709-748.

Yoji, K., Toshichika, I., Masayuki, Y. (2014). Is long-term climate change beneficial or harmful for rice total factor productivity in Japan: Evidence from a panel data analysis. Paddy Water Environ. 12(Supp. 2), S213-S225.

Zimmerman F. J. and Carter, M. R. (2003). Asset smoothing, consumption smoothing, and the reproduction of inequality under risk and subsistence constraints. J. Dev. Econ. 71:233-260.

Zivot, E. and Andrews, D. (1992). Further evidence of the great crash, the oil price shock, and the unit root hypothesis. Journal of Business and Economic Statistics 10, 251-270.

Zougmoré, R., Partey, S., Ouédraogo, M., Omitoyin, B. and Thomas, T. (2016). Toward climate-smart agriculture in West Africa: A review of climate change impacts, adaptation strategies and policy developments for the livestock, fishery, and crop production sectors. Agriculture and Food Security 5(1), 26.