Predicting the Impact of Climate Conditions on the Economic Production of Iranian Provinces with The Approach of Random Forest Algorithm

Document Type : Research Paper

Authors

1 Ph.D. Candidate in Economics, Ferdowsi University of Mashhad

2 Associate Professor of Economics, Ferdowsi University of Mashhad

Abstract

Climate change is among the vital phenomena related to human societies, and its consequences have been demonstrated, particularly in recent decades, with varying intensity in many regions of the world. The importance of climate as one of the fundamental aspects of human life has never been as significant as it is today in macroeconomic and social issues. Analyzing climate change's economic impacts necessitates precise national and local analyses. Although numerous global studies examine the economic effects of climate change, limited research has been conducted at local levels within countries, especially concerning Iran. This article attempts to provide a comprehensive analysis of the susceptibility of the country's provincial economic production to climate change by utilizing a new dataset of weather conditions in the provinces from 2000 to 2020 through the random forest algorithm of machine learning subsets. Studies indicate a significant relationship between weather and sectors beyond agriculture, forestry, food security, tourism, health, fisheries, livestock, mining, and energy. Weather conditions can directly or indirectly impact various economic sectors, and their effect on economic activities is inevitable. However, research results regarding the impact of weather fluctuations face varied findings. Drought, with a higher recurrence than floods, poses more significant challenges to the economy on scales beyond local levels.

Keywords

Main Subjects

References

  1. Abidoye, B. O., & Odusola, A. F. (2015). Climate change and economic growth in Africa: an econometric analysis. Journal of African Economies, 24(2), 277-301.‏
  2. Acemoglu, D., Johnson, S., & Robinson, J. A. (2001). The colonial origins of comparative development: An empirical investigation. American economic review, 91(5), 1369-1401.‏
  3. Acemoglu, D., Johnson, S., & Robinson, J. A. (2005). Institutions as a fundamental cause of long-run growth. Handbook of economic growth, 1, 385-472.‏
  4. Adams, R. M., Rosenzweig, C., Peart, R. M., Ritchie, J. T., McCarl, B. A., Glyer, J. D., ... & Allen Jr, L. H. (1990). Global climate change and US agriculture. Nature, 345(6272), 219-224.‏
  5. Ali, S. (2012). Climate change and economic growth in a rain-fed economy: how much does rainfall variability cost Ethiopia?. Available at SSRN 2018233.‏
  6. Athey, S., & Imbens, G. W. (2019). Machine learning methods that economists should know about. Annual Review of Economics, 11, 685-725.‏
  7. Auffhammer, M. (2018). Quantifying economic damages from climate change. Journal of Economic Perspectives, 32(4), 33-52.‏
  8. Auffhammer, M., & Mansur, E. T. (2014). Measuring climatic impacts on energy consumption: A review of the empirical literature. Energy Economics, 46, 522-530.‏
  9. Auffhammer, M., & Schlenker, W. (2014). Empirical studies on agricultural impacts and adaptation. Energy Economics, 46, 555-561.‏
  10. Babatunde, M. A., & Adefabi, R. A. (2005, November). Long run relationship between education and economic growth in Nigeria: Evidence from the Johansen’s cointegration approach. In regional conference on education in West Africa (pp. 1-2).‏
  11. Barro, R.J., Sala-i Martin, X., (2003). Economic Growth, vol. 1. MIT Press Books.
  12. Bhuiyan, M. A., Dinçer, H., Yüksel, S., Mikhaylov, A., Danish, M. S. S., Pinter, G., ... & Stepanova, D. (2022). Economic indicators and bioenergy supply in developed economies: QROF-DEMATEL and random forest models. Energy Reports, 8, 561-570.‏
  13. Biau, O. (2010). Euro area gdp forecast using large survey dataset-a random forest approach (No. 259600029). EcoMod.‏
  14. Breiman, L. (2002). Manual on setting up, using, and understanding random forests. Berkeley: Statistics Department University of California Berkeley.‏
  15. Burke, M., Hsiang, S. M., & Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527(7577), 235-239.‏
  16. Burke, M., & Tanutama, V. (2019). Climatic constraints on aggregate economic output (No. w25779). National Bureau of Economic Research.‏
  17. Callaway, J. M., Markovska, N., Cukaliev, O., Causevski, A., Gjoshevski, D., Taseska, V., & Nikolova, S. (2011). Assessing the Economic Impact of Climate Change: National Case studies.‏
  18. Carleton, T. A., & Hsiang, S. M. (2016). Social and economic impacts of climate. Science, 353(6304), aad9837.‏
  19. Chakraborty, C., & Joseph, A. (2017). Machine learning at central banks.‏
  20. Chang, C. C. (2002). The potential impact of climate change on Taiwan's agriculture. Agricultural Economics, 27(1), 51-64.‏
  21. Chapman, J. T., & Desai, A. (2023). Macroeconomic predictions using payments data and machine learning. Forecasting, 5(4), 652-683.‏
  22. Chen, J. C., Dunn, A., Hood, K., Driessen, A., & Batch, A. (2019). Off to the races: A comparison of machine learning and alternative data for predicting economic indicators. In Big data for 21st century economic statistics. University of Chicago Press.‏
  23. Colacito, R., Hoffman, B., & Phan, T. (2014). Temperatures and Growth: a Panel Analysis of the US. University of North Carolinal.‏
  24. Crane-Droesch, A. (2018). Machine learning methods for crop yield prediction and climate change impact assessment in agriculture. Environmental Research Letters, 13(11), 114003.‏
  25. Dasgupta, S., Bosello, F., De Cian, E., & Mistry, M. (2022). Global temperature effects on economic activity and equity: a spatial analysis. Italy: European Institute on Economics and the Environment.‏
  26. Dell, M., Jones, B. F., & Olken, B. A. (2008). Climate change and economic growth: Evidence from the last half century (No. w14132). National Bureau of Economic Research.‏
  27. Dell, M., Jones, B. F., & Olken, B. A. (2012). Temperature shocks and economic growth: Evidence from the last half century. American Economic Journal: Macroeconomics, 4(3), 66-95.‏
  28. 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.‏
  29. Deschênes, O., & Greenstone, M. (2007). The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. American economic review, 97(1), 354-385.‏
  30. Elshennawy, A., Robinson, S., & Willenbockel, D. (2016). Climate change and economic growth: An intertemporal general equilibrium analysis for Egypt. Economic Modelling, 52, 681-689.‏
  31. Fankhauser, S., & Tol, R. S. (2005). On climate change and economic growth. Resource and Energy Economics, 27(1), 1-17.‏
  32. Guiteras, R., (2009). The impact of climate change on Indian agriculture. Manuscript, Department of Economics, University of Maryland, College Park, Maryland.
  33. Hadero, T. (2014). The impact of climate change on economic growth: time series evidence from Ethiopia (Doctoral dissertation, Doctoral dissertation, Jimma University).‏
  34. Hastie, T., Tibshirani, R., & Wainwright, M. (2015). Statistical learning with sparsity. Monographs on statistics and applied probability, 143(143), 8.‏
  35. Hsiang, S. (2016). Climate econometrics. Annual Review of Resource Economics, 8, 43-75.‏
  36. (2014). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects, Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.IPCC, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
  37. Kalkuhl, M., & Wenz, L. (2020). The impact of climate conditions on economic production. Evidence from a global panel of regions. Journal of Environmental Economics and Management, 103, 102360.‏
  38. Kolstad, C. D., & Moore, F. C. (2020). Estimating the economic impacts of climate change using weather observations. Review of Environmental Economics and Policy.‏
  39. Lal, R. (2009). Sequestering atmospheric carbon dioxide. Critical Reviews in Plant Science, 28(3), 90-96.‏
  40. Leimbach, M., Kriegler, E., Roming, N., & Schwanitz, J. (2017). Future growth patterns of world regions–A GDP scenario approach. Global Environmental Change, 42, 215-225.‏
  41. Malakoti-Khah, Z., & Farajzadeh, Z. (2020). The Impact of Climate Change on Economic Growth in Iran. Journal of Economics and Agricultural Development, 34 (2), 223-238 (In Persian).
  42. Masters, W. A., & McMillan, M. S. (2001). Climate and scale in economic growth. Journal of Economic growth, 6, 167-186.‏
  43. McKeown, A., & Gardner, G. (2009). Climate change reference guide.‏
  44. Mendelsohn, R., Dinar, A., & Sanghi, A. (2001). The effect of development on the climate sensitivity of agriculture. Environment and Development Economics, 6(1), 85-101.‏
  45. Muller, M. (2022). Inflation forecasting with Random Forest a Machine Learning approach to macroeconomic forecasting. Lund University, Department of Economics.
  46. Newell, R. G., Prest, B. C., & Sexton, S. E. (2021). The GDP-temperature relationship: implications for climate change damages. Journal of Environmental Economics and Management, 108, 102445.‏
  47. Nordhaus, W. D. (2006). Geography and macroeconomics: New data and new findings. Proceedings of the National Academy of Sciences, 103(10), 3510-3517.‏
  48. North, D. C. (1987). Institutions, transaction costs and economic growth. Economic inquiry, 25(3), 419-428.‏
  49. Nyangena, O., & Ruigu, G. M. (2018). Linking weather variability and economic growth in the east african region: a semi-parametric smooth coefficient approach. Journal of Scientific and Engineering Research, 5(6), 326-332.‏
  50. Olper, A., Maugeri, M., Manara, V., & Raimondi, V. (2021). Weather, climate and economic outcomes: Evidence from Italy. Ecological Economics, 189, 107156.‏
  51. Panaahi, H., & Ismaeili Darjani, N. (2020). Investigating the Impacts of Global Warming and Climate Change on Economic Growth: A Case Study of Iranian Provinces during the Period 2011-2001. Journal of Environmental Science and Technology, 22(1), 79-88 (In Persian).
  52. Pretis, F., Schwarz, M., Tang, K., Haustein, K., & Allen, M. R. (2018). Uncertain impacts on economic growth when stabilizing global temperatures at 1.5 C or 2 C warming. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2119), 20160460.‏
  53. Rodrik, D., Subramanian, A., & Trebbi, F. (2004). Institutions rule: the primacy of institutions over geography and integration in economic development. Journal of economic growth, 9, 131-165.‏
  54. Sachs, J. D., & Warner, A. M. (1997). Fundamental sources of long-run growth. The American economic review, 87(2), 184-188.‏
  55. 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. Journal of Economic Literature, 51(3), 838-859.‏
  56. Tebaldi, E., & Beaudin, L. (2016). Climate change and economic growth in Brazil. Applied Economics Letters, 23(5), 377-381.‏
  57. Woloszko, N. (2020). Adaptive Trees: a new approach to economic forecasting.‏
  58. Yoon, J. (2021). Forecasting of real GDP growth using machine learning models: Gradient boosting and random forest approach. Computational Economics, 57(1), 247-265.

Files

Share

How to cite

Statistics