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A Structural Ricardian Valuation of Climate Change Impacts on Agriculture in Pakistan


Mirza Nomman Ahmed

This book presents the economic analysis of the impacts of climate change on agriculture in Pakistan. Particular emphasis is laid on the magnitude of implicit adaptations in overall climate impact assessment and the analysis of selected adaptation options. Using a hedonic pricing model and a revealed choice approach, this study identifies the impacts of climate change on agricultural incomes, depicts the spatial patterns and seasonality of the impacts, and models the future adaptation behavior of farmers in the crop sector. A high sensitivity of farming in Pakistan to climate change is confirmed. With a changing climate and income in mind, farmers in Pakistan are more likely to choose rice, vegetables and maize, whereas they move away from wheat, sugarcane, cotton and fruits.


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7 Structural Ricardian Model for theeconomic impact assessment of Climate Change


211 7 Structural Ricardian Model for the economic impact assessment of Climate Change The upcoming deliberations present the Structural Ricardian Model which serves as a remedy for the black box of adaptations implicit in the standard Ricardian approach. Instead of land value, the Structural model uses net revenues on the farm scale as the dependent variable, in this way an observed preference model is constructed, unveiling specific adaptations that farmer’s make to adapt to climatic change. Another difference is that the Structural model uses farm level data as opposed to aggregated data. The results of both models can be compared and supplemented to understand the economic impacts of climate change on agriculture in Pakistan. Multinomial logit models are nonlinear and include many parameters, which makes the interpretation of the output difficult. In following the empirical strategy is explained and results are presented alongside deliberations on model fit and testing. This is followed by the interpretation of the results. The theoretical considerations are based on the extensive review on models for categorical outcomes by LONG AND FREESE (2006). 7.1 Dataset and Study Area A large dataset is constructed by combining the detailed farm-household level information from the Pakistan Living Standards Measurement Survey (PSLM) 2007-2008 (FBS, 2009) with climate and soil data which was used for the land value model (Annex I). The PSLM survey covered 106 administrative districts (4 provinces) in the country between 2007 and 2008. Farming households in the sample were administered a detailed farm production (input and output)...

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