The Impact of Climate Change on Land Rent and Revenue, major Agricultural crops and Migration: A case Study of Pakistan

Abstract

This dissertation covers the impact of environmental degradation on agricultural crops, land revenue, land rent for Pakistan and migration in context of global and Pakistan scenarios. Environmental degradation is a phenomenon in which climatic changes become worsen and create impact on our daily life and means of living. This study contains the different questions like, how do fundamental and corporate features integrally related with the net migration and its significance to concerned economies. To explain the need and importance environmental degradation impact on agricultural sector in Pakistan, four models are to investigate the impact of climatic index, agricultural accessories index and dummy variables on four different crops (dependent Variables), one model each for land rent and land revenue with same independent variables. A panel date approach is incorporated to examine the impact of environmental degradation on agricultural crops land rent and land revenue. This study propose the proper measures against climatic changes to enhance the land revenue, land rent and crops production to save the future of the nation. In global prospect push and pull factors along climatic variables are incorporated to capture the impact on migration flows from Asia to Europe. There are fifteen (15) countries of origins and fourteen (14) European countries of destination. The origin countries which consist of Asian countries are further divided into three origins, such as Eastern Asian Countries (China, Hong Kong, Japan and Korea Republic),Southern Asian Countries (Bangladesh, India , Iran ,Pakistan and Sri lanka), and South-Eastern Asian Countries (Indonesia, Malaysia, Philippine, Thailand, Vietnam and Singapore). The result indicate that all Asian regions have negative net migration, distance is negative with the dependent variable, environmental variable creating pressure on migration and immigrant flow is positive towards those destination where language constraint does not exist. At a disaggregate level, rank and regression was used across all four provinces of Pakistan. The result of provincial analysis shows that no province stands equally at high or low level in all three ranks. Regression analysis proved that fundamental and corporate features are significant and positively responsible for out migration. For each province of Pakistan net migration is negative, which means out migration of Pakistan is greater than inward migration in Pakistan. This study also suggests that each province has to make serious efforts to improve the fundamental and corporate qualities; otherwise brain drain can never be stopped.