Abstract: In this paper we test international migration from China and India to some important destinations from Organisation for Economic Cooperation and Development. The purpose is to see if, besides economic factors, climate migration has a significant impact on labour migration. Empirical estimation is done by running a Poisson Pseudo Maximum Likelihood Estimator with fixed effects on a balanced panel data. The data are collected for the period of time 1995-2018. Results show that Chinese people are more likely to migrate if carbon dioxide emissions and natural disasters are lower in destination countries. This implies that people migrate due to pull factors rather than push factors in the case of China. For India, no significance neither in origin nor in destinations is obtained for both proxies of climate change. The value of the paper comes from choosing these two countries in particular, which according to World Population Review (2020) and EM-DAT (2018) are the most affected of climate change countries from Asia. The originality comes from including climate change proxies alongside with economic factors and also from adding dummy variable such as common spoken language which in every case is obtained as being positive and significant. Based on our results, we are able to draw some practical implications of our research. Governments should implement more efficient programs for offering better living conditions for people from areas exposed to a high level of carbon dioxide emissions or high number of natural disasters in order to prevent their emigration. In case of sudden disasters, governments should involve in providing support for resettlements.

Keywords: gravity model of migration, climate change, China, India, PPML, fixed effects

JEL codes: F22, Q59, C23

DOI: ...