The Effect of Climate Change on Agricultural Crop Returns in Uganda
The study examined the effect of climate change on agricultural crop returns in Uganda using the Ricardian Panel Tobit technique and the World Bank Living Standards Measurement Survey (LSMS) data, climate data from Uganda National Meteorological Authority (UNMA) and global weather data. The findings showed that climate related risks account for over 67 percent of agricultural risks and less than 2 percent of the farming households practise irrigation. Farmers that practised irrigation earned higher agricultural returns nationally than their counterparts did. The findings show that the output elasticities with respect to temperature range from -2.02 percent to 0.543 percent. This implies that for the average temperature increase by 1 percent, maize farm returns decreased by 2.02 percent, banana by 1.7 percent, cassava by 1.50 percent and beans by 1.01 percent. While 1 percent increases in rainfall, lowered banana returns by 0.02 percent, beans by 0.08 percent, cassava by 0.035 percent, maize by 0.025 percent except for groundnuts’ returns increased by 0.115 percent. Apart from climate factors, non-climate factors such as capital, labour, farm size, fertilizers and soil quality are equally important inputs and significantly impact on agricultural farm returns. The study proposes that due to unrelenting adverse climate change effects in Uganda, adoption of multi-pronged approaches such as extensive irrigation, agro-insurance, diversification of agricultural activities, use of food cribs during bumper harvests would be the breath of life for Ugandan farmers.
Adams, R. M., Hurd, B. H., Lenhart, S. & Leary, N. (1998). Effects of global climate change on agriculture:an interpretative review. Climate Research, 11, 19–30.
Ajwad, M. I., Kurukulasuriya, P., Basist, A., Dinar, A., Kogan, F., Mendelsohn, R. & Williams, C. (2004). Cross-sectional Analyses of Climate Change Impacts. The World Bank.
Akaike, H. (1973). Information Theory and the Maximum Likelihood Principle. In B.N Petrov and F.Csaki (Ed.), In 2nd International Symposium on Information Theory, (pp. 267-281). Budapest: Akailseoniai-Kiudo.
Angélil, O., Stone, D., Wehner, M., Paciorek, C. J., Krishnan, H. & Collins, W. (2017). An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events. Journal of Climate, 30, 5-16.
Appiah, D. O. (2017). Climate Policy Ambivalence in Sub-Saharan Africa. ICCG Reflection No.60.
Asseng, S., Foster, I. A. N. & Turner, N. C. (2011). The Impact of Temperature Variability on Wheat Yields. Global Change Biology, 17(2), 997-1012.
Ater, P. I. & Aye, G. C. (2012). Economic Impact of Climate Change on Nigerian Maize Sector: A Ricardian Analysis. WIT Transactions on Ecology and the Environment, 162.
Ayinde, O. E., Ajewole, O. O., Ogunlade, I. & Adewumi, M. O. (2010). Empirical Analysis of Agricultural Production and Climate Change: A case Study of Nigeria. Journal of Sustainable Development in Africa, 12(6), 275-283.
Bacha, D., Namara, R., Bogale, A. & Tesfaye, A. (2011). Impact of Small?scale Irrigation on Household Poverty: Empirical Evidence from the Ambo District in Ethiopia. Irrigation and Drainage, 60(1), 1-10.
Baltagi, B. (2008). Econometric Analysis of Panel Data. (Fourth ed.). John Wiley & Sons.
Barrios, S., Ouattara, B. & Strobl, E. (2008). The Impact of Climatic Change on Agricultural Production: Is it different for Africa? Food Policy, 33(4), 278-298.
Benin, S. (2015). Returns to Agricultural Public Spending in Africa South of the Sahara (Vol. 1491). Intl Food Policy Res Inst.
Bezabih, M., Falco, S. D. & Mekonnen, A. (2014). On the Impact of Weather Variability and Climate Change on Agriculture: Evidence from Ethiopia. Environment for Development Discussion Paper-Resources for the Future (RFF), (14-15).
BoU. (2018). Bank of Uganda State of the Economy. Kampala.
Caffrey, P., Finan, T., Trzaska, S., Miller, D., Laker-Ojok, R. & Huston, S. (2013). Uganda Climate Change Vulnerability Assessment Report. Kampala. USAID. ARCC.
Calzolari, G., Magazzini, L. & Mealli, F. (2001). Simulation-based Estimation of Tobit Model with Random. Econometric Studies: A Festschrift in Honour of Joachim Frohn, 8(349), 344-369.
Cameron, A. C. & Trivedi, P. K. (2005). Microeconometrics: Methods and Applications. Cambridge University press.
Chang, E. H., Wang, C. H., Chen, C. L. & Chung, R. S. (2014). Effects of Long-term Treatments of Different Organic Fertilizers Complemented with Chemical N Fertilizer on the Chemical and Biological Properties of Soils. Soil science and plant nutrition, 6. Soil Science and Plant Nutrition, 60(4), 499-511.
Dell, M., Jones, B. F. & Olken, B. A. (2009). Temperature and Income: Reconciling New Cross-sectional and Panel Estimates. American Economic Review, 99(2), 198-204.
Deschenes, O. & Greenstone, M. (2006). The Economic Impacts of Climate Change : Evidence from Agricultural Profits and Random Fluctuations of Weather, (131). MIT Joint Program on the Science and Policy of Global Change.
Dunne, J. P., Stouffer, R. J. & John, J. G. (2013). Reductions in Labour Capacity from Heat Stress under Climate Warming. Nature Climate Change, 3(6), 563.
Easterling, W. E., Crosson, P. R., Rosenberg, N. J., McKenney, M. S., Katz, L. A. & Lemon, K. M. (1993). Paper 2. Agricultural Impacts of and Responses to Climate Change in the Missouri-Iowa-Nebraska-Kansas (MINK) Region. Climatic Change, 24(1-2), 23-61.
Etwire, P. M., Fielding, D. & Kahui, V. (2019). Climate Change, Crop Selection and Agricultural Revenue in Ghana: A Structural Ricardian Analysis. Journal of Agricultural Economics, 70(2), 488-506.
Exenberger, A., Pondorfer, A. & Wolters, M. H. (2014). Estimating the Impact of Climate Change on Agricultural Production: Accounting for Technology Heterogeneity Across Countries. eeecon Working Paper. 2014-16.
Fang, S., Su, H., Liu, W., Tan, K. & Ren, S. (2013). Infrared Warming Reduced Winter Wheat Yields and some Physiological Parameters, which were Mitigated by Irrigation and Worsened by Delayed Sowing. . PLoS One, 8(7), e67518.
Fezzi, C. & Bateman, I. (2012). Non-linear Effects and Aggregation Bias in Ricardian Models of Climate Change. Centre for Social and Economic Research on the Global Environment. Working Paper 2012-02.
Fezzi, C. & Bateman, I. (2015). The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Biasin Ricardian Models of Farmland Values, 2(1), 57-92.
Friedman, M. & FRIEDMAN, M. (1953). Essays in Positive Economics. University of Chicago Press.
Gasper, R., Blohm, A. & Ruth, M. (2011). Social and Economic Impacts of Climate Change on the Urban Environment. Current Opinion in Environmental Sustainability, 3(3), 150-157.
GoU. (2013). The Uganda National Land Policy. Ministry of Lands, Housing and Urban Development. Republic of Uganda.
GoU. (2015). Second National Development Plan - Uganda. National Planning Authority Uganda. Retrieved from http://npa.ug/wp-content/uploads/NDPII-Final.pdf on 15/3/2019
GoU. (2016). National Fertiliser Policy. Kampala: Ministry of Agriculture Animal Industry and Fisheries. Republic of Uganda.
GoU. (2017). Policy Statement for the Ministry of Agriculture, Animal Industry and Fisheries FY 2016/17. Ministry of Agriculture, Animal Industry and Fisheries.
Granados, R., Soria, J. & Cortina, M. (2017). Rainfall Variability, Rainfed Agriculture and Degree of Human Marginality in North Guanajuato, Mexico. Singapore Journal of Tropical Geography, 38(2), 153-166.
Guloba, M. (2014). EFD. Retrieved from Analysis of Adaptation to Climate Variability And Change in Uganda.
Han, S. H., An, J. Y., Hwang, J., Kim, S. B. & Park, B. B. (2016). The Effects of Organic Manure and Chemical Fertilizer on the Growth and Nutrient Concentrations of Yellow Poplar (Liriodendron tulipifera Lin.) in a Nursery System . Forest science and Technology, 12(3), 137-143.
Hanjra, M. A. & Qureshi, M. E. (2010). Global water crisis and future food security in an era of climate change. Food policy, 35(5), 365-377.
Hansen, J., Sato, M., Ruedy, R., Schmidt, G. A. & Lo, K. (2019). Global Temperature in 2018 and Beyond.
Hou, R., Ouyang, Z., Li, Y., Wilson, G. V. & Li, H. (2012). Is the Change of Winter Wheat Yield under Warming Caused by Shortened Reproductive Period? Ecology and Evolution, 2(12), 2999-3008.
IPCC. (2013). Climate change 2013: The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. (F. T. Stocker, D. Qin, ..., & L. L. White , Eds.) Cambridge University Press.Cambridge,United Kingdom.
IPCC. (2014). Climate Change 2014: Impacts, Adaptation and Vulnerability: Regional Aspects. (C. B. Field, D. J. Barros, ..., & M. P. Midgley , Eds.) Cambridge University Press.Cambridge, United kingdom.
Jasso, G. (2004). The Tripartite Structure of Social Science Analysis. Sociological Theory, 22(3), 401-431.
Kabubo-Mariara, J. & Kabara, M. (2018). Climate change and food security in Kenya. In Agricultural Adaptation to Climate Change in Africa, 55-80.
Kabubo-Mariara, J., Mulwa, R. & Falco S. D. (2016). The impact of Climate Change on Food Calorie Production and Nutritional Poverty: Evidence from Kenya. Environment for Development Discussion Paper - Resources for the Future (RFF), 35.
Kurukulasuriya, P. & Ajwad, M. I. (2007). Application of the Ricardian technique to estimate the impact of climate change on smallholder farming in Sri Lanka. Climatic Change, 81, 39–59.
Kurukulasuriya, P. & Mendelsohn, R. (2008). A Ricardian analysis of the impact of climate change on African cropland. AfJARE, 2(1).
Lang, G. (2007). Where are Germany’s gains from Kyoto? Estimating the effects of global warming on agriculture. Climatic Change, 84, 423-439.
Lippert, C., Krimly, T. & Aurbacher, J. (2009). A Ricardian analysis of the impact of climate change on agriculture in Germany. Climate Change, 97, 593-610.
Maganga, A. & Malakini, M. (2015). Agrarian Impact of Climate Change in Malawi: A Quantile Ricardian Analysis (No. 1008-2016-79992).
Mall, R. K., Singh, R., Gupta, A., Srinivasan, G. & Rathore, L. S. (2006). Impact of Climate Change on Indian Agriculture: A Review. Climatic Change, 78(2-4), 445-478.
Massetti, E. & Mendelsohn. (2011). Estimating Ricardian Models with Panel Data. National Bureau of Economic Research, Working Paper No.17101.
Matovu, J. M. (2013). Productivity , Growth and Welfare Effects of Climate Change : Analysis Using a Dynamic CGE model for Uganda.
McDonald, J. F. & Moffitt, R. A. (1980). The Uses of Tobit Analysis. The Review of Economics and Statistics, 62(2), 318-321.
Mendelsohn, R., Arellano-Gonzalez, J. & Christensen, P. (2010). A Ricardian Analysis of Mexican Farms. Environment and Development Economics, 15(2), 153-171.
Mendelsohn, Robert, Nordhaus, W. D. & Shaw, D. (1994). The Impact of Global Warning on Agriculture: A Ricardian Analysis. American Economic Review, 84(4), 753-771.
Nielsen, J. Ø. & Vigh, H. (2012). Adaptive Lives. Navigating the Global Food Crisis in a Changing Climate. Global Environmental Change, 22(3), 659-669.
Nyuor, B. A., Donkor, E., Aidoo, R., Saaka Buah, S., Naab, J., Nutsugah, S. & Zougmoré, R. (2016). Economic impacts of climate change on cereal production: implications for sustainable agriculture in Northern Ghana. Sustainability, 8(8), 724.
Odhiambo, W., Nyangito, H. O. & Nzuma, J. (2004). Sources and Determinants of Agricultural Growth and Productivity in Kenya (No. 34). Kenya Institute for Public Policy Research and Analysis.
Peña-López, I. (2009). World Development Report 2010: Development and Climate Change.
Raza, J. & Siddiqui, W. (2014). Determinants of Agricultural Output in Pakistan: A Johansen Co-integration Approach. Academic Research International, 5(4), 30.
Rosenzweig, C. & Parry, M. L. (1994). Potential Impact of Climate Change on World Food Supply. Nature, 367(6459), 133.
Rowhani, P., Lobell, D. B., Linderman, M. & Ramankutty, N. (2011). Climate Variability and Crop Production in Tanzania. Agricultural and Forest Meteorology, 151(4), 449-460.
Salami, A., Kamara, A. B. & Brixiova, Z. (2010). Smallholder Agriculture in East Africa: Trends, Constraints and Opportunities. Tunis: African Development Bank.
Salvo M. D., Begalli D. & Signorello, G. (2014). The Ricardian Analysis Twenty Years after the Original Model : Evolution , Unresolved Issues and Empirical Problems. Journal of Development and Agricultural, 6(3), 124–131.
Sanghi, A., Mendelsohn, R. & Dinar, A. (1998). The Climate Sensitivity of Indian Agriculture: In Measuring the Impact of Climate Change on Indian Agriculture. World Bank Technical paper. World Bank, Washington, DC.
Schlenker, W. & Roberts, M. J. (2008). Estimating the Impact of Climate Change on Crop Yields: The Importance of Non-Linear Temperature Effects. National Bureau of Economic Research, Working Paper No. 13799.
Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461-464.
Sharma, U., Paliyal, S. S., Sharma, S. P. & Sharma, G. D. (2014). Effects of Continuous Use of Chemical Fertilizers and Manure on Soil Fertility and Productivity of Maize–wheat under Rainfed Conditions of the Western Himalayas. Communications in Soil science and Plant Analysis, 45(20), 2647-2659.
Shephard, R. W. (1970). Proof of the Law of Diminishing Returns. Zeitschrift für Nationalökonomie, 30(1-2), 7-34.
Skonhoft, A. (2008). Sheep as Capital Goods and Farmers as Portfolio Managers: A Bioeconomic Model of Scandinavian Sheep Farming. Agricultural Economics, 38(2), 193-200.
Skoufias, E. (2012). The Poverty and Welfare Impacts of Climate Change: Quantifying the Effects, Identifying the Adaptation Strategies. The World Bank.
Splett, N. S., Barry, P. J., Dixon, B. L. & Ellinger, P. N. (1994). A joint Experience and Statistical Approach to Credit Scoring. Agricultural Finance Review (USA).
Sy, A. (2016). Africa: Financing Adaptation and Mitigation in the World’s Most Vulnerable Region. Africa: Brookings Institution, Africa Growth Initiative.
Teixeira, E. I., Fischer, G., Van Velthuizen, H., Walter, C. & Ewert, F. (2013). Global Hot-spots of Heat Stress on Agricultural Crops due to Climate Change. Agricultural and Forest Meteorology, 170, 206-215.
Thomson, K. J. (2010). Climate Change and Agriculture: An Economic Analysis of Global Impacts, Adaptation and Distributional Effects. By R. Mendelsohn and A. Dinar. Cheltenham, UK: Edward Elgar (2009), pp. 256,£ 53.96 (online discount price). ISBN 978-1-84720-670-1. Experimental Agriculture, 46(2), 259-259.
Thurlow, J., Zhu, T. & Diao, X. (2012). Current Climate Variability and Future Climate Change: Estimated Growth and Poverty Impacts for Zambia. Review of Development Economics, 16(3), 394-411.
Tian, Y., Zheng, C., Chen, J., Chen, C., Deng, A., Song, Z. & Zhang, W. (2014). Climatic Warming Increases Winter Wheat Yield but Reduces Grain Nitrogen Concentration in East China. PloS one, 9(4), e95108.
Tobin, J. (1958). Estimation of Relationships for Limited Dependent Variables. Econometrica: journal of the Econometric Society, 24-36.
Tokunaga, S., Okiyama, M. & Ikegawa, M. (2015). Dynamic Panel Data Analysis of the Impacts of Climate Change on Agricultural Production in Japan. Japan Agricultural Research Quarterly: JARQ, 49(2), 149-157.
UBOS. (2009a). The Uganda National Panel Survey ( UNPS ) 2009-Documentation. Uganda Bureau of Statistics.
UBOS. (2009b). Statistical Abstract. Uganda Bureau of Statistics.
UBOS. (2010). Uganda National Panel Survey Manual Instructions for Agriculture Questionnaire. Uganda Bureau of Statistics .
UBOS. (2013). Uganda National Panel Survey 2011/2012 .Wave iii Report. Uganda Bureau of Statistics.
UBOS. (2015). The Uganda National Panel Survey ( UNPS ) 2013 /14 Basic Information Document. Uganda Bureau of Statistics.
Union, A. (2003). Comprehensive Africa Agriculture Development Programme. Midrand, South Africa: NEPAD.
Wang, J., Mendelsohn, R., Dinar, A., Huang, J., Rozelle, S. & Zhang, L. (2008). Can China Continue Feeding Itself? The impact of Climate Change on Agriculture. World Bank.
White, E. B. (2007). Charlotte ’ s Web, 1–157 . Retrieved 3 15, 2019, from https://lost-contact.mit.edu/afs/adrake.org/usr/rkh/Books/books/Charlotte%27s%20Web.pdf
World Bank. (2010). Worl Bank Development Indicators 2010. Washington, D.C, USA.
World Bank. (2011). World Bank Data Team. Living Standard Measurement Study : When Data Collection is Intrepid:. Retrieved from https://blogs.worldbank.org/opendata/living-standard-measurement-study-when-data-collection-intrepid on 4/4/2019
World Bank. (2011). World Bank Data Team: Living Standard Measurement Study . When Data Collection is Intrepid. Retrieved from L: https://blogs.worldbank.org/opendata/living-standard-measurement-study-when-data-collection-intrepid
Zivin, G. J. & Neidell, M. (2014). Temperature and the Allocation of Time: Implications for Climate Change. Journal of Labor Economics, 32(1), 1-26.
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