Asymmetric effects of rainfall on food crop prices: evidence from Rwanda

  • Received September 11, 2017;
    Accepted October 12, 2017;
    Published October 20, 2017
  • Author(s)
    ResearcherID: B-4548-2018
    Aimable Nsabimana
    ORCID , Olivier Habimana
  • DOI
    http://dx.doi.org/10.21511/ee.08(3-1).2017.06
  • Article Info
    Volume 8 2017, Issue #3, pp. 137-149
  • TO CITE АНОТАЦІЯ
  • Cited by
    5 articles
  • 986 Views
  • 324 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

This study examined the effects of the likely change in rainfall on food crop prices in Rwanda, a landlocked country where agriculture is mainly rain-fed. The empirical investigation is based on nonlinear autoregressive distributed lag cointegration framework, which incorporates an error correction mechanism and allows estimation of asymmetric long-run and short-run dynamic coefficients. The results suggest that food crop prices are vulnerable to rainfall shocks and that the effect is asymmetric in both the short and long run. Moreover, there was evidence of seasonal differences, with prices falling during harvest season and rising thereafter. Considering the ongoing threat of global climate change, and in order to cope with rainfall shortage and uncertainty, increase food affordability and ultimately ensure food security throughout the year, there is a need to develop and distribute food crop varieties and crop technologies that reduce the vulnerability of farming to rainfall shocks.

view full abstract hide full abstract
    • Fig. 1. Monthly average nominal price of the staple crops cassava roots, beans and potatoes in Rwanda, 20002015
    • Fig. 2. Distribution of mean monthly rainfall (mm) in Rwanda, 20002012
    • Fig. 3. Dynamic multipliers. Effect of rainfall on cassava root prices
    • Fig. 4. Dynamic multipliers. Effect of rainfall on bean prices
    • Fig. 5. Dynamic multipliers. Effect of rainfall on potato prices
    • Table 1. Descriptive statistics on key variables of interest in the study (real prices are expressed in Rwandan Francs; rainfall is in millimetres)
    • Table 2. Unit root tests
    • Table 3. Dynamic asymmetries in the price of beans, potatoes and cassava roots
    • Table 4. Asymmetric statistics on rainfall effects of food prices
    • Baez, J. E., Lucchetti, L., Genoni, M. E., & Salazar, M. (2015). Gone with the storm: rainfall shocks and household well-being in Guatemala World Bank Policy Research Working Paper, 7177.
    • Barrett, C. B. (2013). Food security and sociopolitical stability. OUP Oxford.
    • Baulch, B., & Hoddinott, J. (2000). Economic mobility and poverty dynamics in developing countries. The Journal of Development Studies, 36(6), 1-24.
    • Bellemare, M. F., Barrett, C. B., & Just, D. R. (2013). The welfare impacts of commodity price volatility: evidence from rural Ethiopia. American Journal of Agricultural Economics, 95(4), 877-899.
    • Benhin, J. K. (2008). South African crop farming and climate change: An economic assessment of impacts. Global Environmental Change, 18(4), 666-678.
    • Blanc, E. (2012). The Impact of Climate Change on Crop Yields in Sub-Saharan Africa. American Journal of Climate Change, (01)01, 13.
    • Burke, M., & Emerick, K. (2012). Adaptation to climate change: Evidence from US agriculture.
    • Burke, M., Hsiang, S. M., & Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527(7577), 235-239.
    • De la Paix, M. J., Anming, B., Lanhai, L., Ge, J., & Habiyaremye, G. (2011). Effects of climate change on Rwandan smallholder agriculture. African Journal of Agricultural Research, 6(13), 3217-3219.
    • Deaton, A., & Laroque, G. (1992). On the behavior of commodity prices. The Review of Economic Studies, 59(1), 1-23.
    • Dell, M., Jones, B. F., & Olken, B. A. (2014). What do we learn from the weather? The new climate–economy literature. Journal of Economic Literature, 52(3), 740-798.
    • Deressa, T., Hassan, R., & Poonyth, D. (2005). Measuring the impact of climate change on south african agriculture: The case of sugarcane growing regions. Agrekon, 44(4), 524-542.
    • Dillon, B. M., & Barrett, C. B. (2015). Global oil prices and local food prices: Evidence from east africa. American Journal of Agricultural Economics.
    • Elliot, B., Rothenberg, T., & Stock, J. (1996). Efficient tests of the unit root hypothesis. Econometrica, 64(8), 13-36.
    • Enfors, E. I., & Gordon, L. J. (2008). Dealing with drought: The challenge of using water system technologies to break dryland poverty traps. Global Environmental Change, 18(4), 607-616.
    • Ericksen, P. J., Ingram, J. S., & Liverman, D. M. (2009). Food security and global environmental change: emerging challenges. Environmental Science & Policy, 12(4), 373-377.
    • Field, C. B., Barros, V., Stocker, T. F., Qin, D., Dokken, D., Ebi, K. L., Mastrandrea, M. D., Mach, K. J., Plattner, G.-K., Allen, S., Tignor, M., Midgley, P.M. (Editors). (2012). Managing the risks of extreme events and disasters to advance climate change adaptation: Summary for policymakers. IPCC Report, 1-19.
    • Hill, R. V., & Porter, C. (2017). Vulnerability to drought and food price shocks: Evidence from Ethiopia. World Development, 96, 65-77.
    • Ivanic, M., & Martin, W. (2008). Implications of higher global food prices for poverty in low‐income countries. Agricultural economics, 39(s1), 405-416.
    • Jarvis, A., Lau, C., Cook, S., Wollenberg, E., Hansen, J., Bonilla, O., & Challinor, A. (2011). An integrated adaptation and mitigation framework for developing agricultural research: synergies and trade-offs. Experimental Agriculture, 47(2), 185.
    • Jones, P. G., & Thornton, P. K. (2003). The potential impacts of climate change on maize production in Africa and Latin America in 2055. Global environmental change, 13(1), 51-59.
    • Kassie, G. T., Abdulai, A., Greene, W. H., Shiferaw, B., Abate, T., Tarekegne, A., & Sutcliffe, C. (2017). Modeling Preference and Willingness to Pay for Drought Tolerance (DT) in Maize in Rural Zimbabwe. World Development, 94, 465-477.
    • Kouyate, C., von Cramon-Taubadel, S., & Fofana, I. (2016). Proximity and price co-movement in West African rice markets. African Journal of Agricultural and Resource Economics, 11(3), 167-182.
    • Kseniia Mikova, Enock Makupa, & Kayumba, J. (2015). Effect of Climate Change on Crop Production in Rwanda. Earth Sciences, 4(3), 120-128.
    • Lobell, D. B., Schlenker, W., & Costa-Roberts, J. (2011). Climate trends and global crop production since 1980. Science, 333(6042), 616-620.
    • Ma, J., & Maystadt, J.-F. (2017). The impact of weather variations on maize yields and household income: income diversification as adaptation in rural China. Global Environmental Change, 42, 93-106.
    • Mawejje, J. (2016). Food prices, energy and climate shocks in Uganda. Agricultural and Food Economics, 4(1), 4.
    • Mitra, S. K. (2014). Nonlinear impact of rain on foodgrain production in India. Applied Economics Letters, 21(14), 1001-1005.
    • Nelson, G. C., Rosegrant, M. W., Koo, J., Robertson, R., Sulser, T., Zhu, T., . . . Batka, M. (2009). Impact on agriculture and costs of adaptation. Food Policy Report. International Food Policy Research Institute, Washington DC.
    • Pesaran, H., & Shin, Y. (1999). An Autoregressive Distributed Lag Modelling Approach to Cointegration “chapter 11. Paper presented at the Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch Centennial Symposium.
    • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of applied econometrics, 16(3), 289-326.
    • Poulton, C., Kydd, J., Wiggins, S., & Dorward, A. (2006). State intervention for food price stabilisation in Africa: Can it work?Food Policy, 31(4), 342-356.
    • Santeramo, F. G., & von Cramon-Taubadel, S. (2016). On perishability and Vertical Price Transmission: empirical evidences from Italy. Bio-based and Applied Economics, 5(2), 199-214.
    • Sassi, M., & Cardaci, A. (2013). Impact of rainfall pattern on cereal market and food security in Sudan: Stochastic approach and CGE model. Food Policy, 43, 321-331.
    • Schmidhuber, J., & Tubiello, F. N. (2007). Global food security under climate change. Proceedings of the National Academy of Sciences, 104(50), 19703-19708.
    • Scholes, R. J., & Biggs, R. (2004). Ecosystem services in southern Africa: a regional assessment. Millennium Ecosystem Assessment.
    • Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in Honor of Peter Schmidt (pp. 281-314). Springer.
    • Tifaoui, S., & von Cramon-Taubadel, S. (2017). Temporary Sales Prices and Asymmetric Price Transmission. Agribusiness, 33(1), 85-97.
    • Tol, R. S. J. (2010). The economic impact of climate change. Perspektiven der Wirtschaftspolitik, 11(s1), 13-37.
    • Wang, J., Mendelsohn, R., Dinar, A., Huang, J., Rozelle, S., & Zhang, L. (2009). The impact of climate change on China’s agriculture. Agricultural Economics, 40(3), 323-337.
    • Watson, R. T., Zinyowera, M. C., & Moss, R. H. (1998). The regional impacts of climate change: an assessment of vulnerability. Cambridge University Press.
    • Von Cramon-Taubadel, S. (1998). Estimating asymmetric price transmission with the error correction representation: An application to the German pork market. European review of agricultural economics, 25(1), 1-18.
    • Von Cramon-Taubadel, S. (2017). The analysis of market integration and price transmission–results and implications in an African context. Agrekon, 1-14.
    • Wood, S. A., Jina, A. S., Jain, M., Kristjanson, P., & DeFries, R. S. (2014). Smallholder farmer cropping decisions related to climate variability across multiple regions. Global Environmental Change, 25, 163-172.
    • World Bank. (2011). Rwanda Economic Update: seeds for higher growth (country report, spring edition).
    • World Bank. (2015). Managing Uncertainty for Growth and Poverty Reduction: With a Special Focus on Agricultural Sector Risk Assessment. Country report, 7(Special issue).
    • Zivot, E., & Andrews, D. W. K. (2002). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of business & economic statistics, 20(1), 25-44
Related Articles

  • Existing situation and prospects of green economy: evidence from Bangladesh

    Muhammad Mahboob Ali doi: http://dx.doi.org/10.21511/ee.09(2).2018.01
    Environmental Economics Volume 9, 2018         Issue #2         pp. 7-21 Views: 2132 Downloads: 164 TO CITE АНОТАЦІЯ

    Economy for green is currently becoming a “buzz word” among producers, suppliers and consumers, which is also receiving impetus in Bangladesh. Based on the literature review, a number of theoretical relationships were empirically tested. An investigative query is: to what extent the green economy is flourishing with a via to extend sustainability of the state with competitive advantage? Structured questionnaire was deliberated in order to find the relationships between the demographic variables and the green ecosystem. Time period of the research was October 1, 2017 to March 31, 2018. It was empirically observed that the relationship between the respondents of both genders and usability of green production in the country exists; the connection between business type and sensitivity of any green product is easily obtainable; the linkage between business type and awareness of any green product is accessible in the market; the linkage between type of institution and encouraging goods and services of any “Green Product” in Bangladesh occurs; the relationship between different types of institutes and use of Green Product consumption is applicable in the country. Economy for Green can possibly reduce the magnitude of the worst shock of natural disasters which increasingly occur as regular variation in addition to severe problems on human being and non-human assets. Consumers and producers are essential by conscious of green concept. Green Investment Bank in Bangladesh may be established to accomplish a broad range of economic support for innovative green projects and technologies leading to increasing capacity and sustainable connections.

  • Green bonds of supranational financial institutions: On the road to sustainable development

    Nataliia VersalORCID Researcher ID, Antonina SholoikoORCID Researcher ID doi: http://dx.doi.org/10.21511/imfi.19(1).2022.07
    Investment Management and Financial Innovations Volume 19, 2022         Issue #1         pp. 91-105 Views: 1168 Downloads: 384 TO CITE АНОТАЦІЯ

    The move to sustainable development and building a carbon-low economy needs funding. In this regard, a new direction in finance – green (sustainable) finance – has emerged. One of the green finance instruments is green bonds, first issued by supranational financial institutions. This paper aims to identify the features of green bond issues and implemented green projects by the World Bank (the WB) and the European Bank for Reconstruction and Development (the EBRD). Data were obtained from databases and reports of the WB, the EBRD, and the Climate Bonds Initiative. Data analysis was provided using statistical methods, particularly descriptive and comparative statistics. A positive trend in the issue of green bonds in the volumes and timing of the WB and the EBRD was revealed, despite the shift in emphasis caused by COVID-19. Renewable energy, energy efficiency, and clean transportation remain the primary directions of the WB, and the EBRD green projects amounted to more than 60% of total projects funding. The geography of green projects financed through the WB and the EBRD green bonds indicates that green projects are receiving significant funding from countries facing environmental challenges and demonstrating intent to green transition (the WB – China and India, the EBRD – Turkey, Poland, and Egypt). Supranational financial institutions were the first to come to the forefront of sustainable development funding and are now spearheading the creation of new financial instruments aimed at financing both green and social projects, leading to the emergence of sustainability bonds.

    Acknowledgment(s)
    The authors would like to thank the participants of the 1st International Conference on Sustainable Development (SDL 2021) for providing the valuable remarks and a fruitful discussion. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

  • Climate change adaptation challenges confronting small-scale farmers

    Davison Mugiya , Costa Hofisi doi: http://dx.doi.org/10.21511/ee.08(1).2017.06
    Environmental Economics Volume 8, 2017         Issue #1         pp. 57-65 Views: 1067 Downloads: 372 TO CITE АНОТАЦІЯ

    Climate change adaptation issues have recently gained attention for the past few years in Zimbabwe. However, little has been done to explore the challenges, associated with climate change in the country. Therefore, this article explores the challenges affecting small-scale farmers in the Zvishavane District of Zimbabwe in coping with climate change vulnerability. The qualitative research methodology encompassing semi-structured interviews was used to collect data from small-scale farmers and other key informants in the study area. The study portrays that small-scale farmers are struggling to cope with climate change due to resource constraints, lack of access to credit and inputs, aid bottlenecks coupled with contradiction of programs among other critical issues.

Download Preview
Close
Environmental Economics
Environmental Economics