Economic dynamics of movement: Envrionmental changes and spatial spillover
Abstract
Interactions between socio-economic and environmental systems are at the core of environmental and resource economics as well as various social sciences, including different subfields of applied economics. In this dissertation, I investigate the spatial aspects of environmental-economic systems, using various economic theories and methods. In the three essays of this dissertation I explore three different topics regarding the spatial dimensions of the interplay between ecological and economic processes. The first essay deals with ecosystem services of pest management, the second with micro-economic forced migration, and the third essay covers spatial correlation in weather in relation to crop yields. The first essay captures agro-ecosystem management of crop pest by the provision of conservation practices. The Stochastic Space-Time Natural Enemy-adjusted Economic Threshold (SST-NEET) integer program is developed and solved to find the optimal cost efficient pest density required to be sprayed, incorporating ecosystem complexities such as prey-predator biophysical processes, stochasticity, spatial heterogeneity and spatial spillovers, and repeated decision processes. Two key findings emerge from the simulation-based experiments. First, increasing landscape heterogeneity is more important than increasing the size of the natural area itself when considering non-crop habitat management, e.g., conservation practices by the United States Department of Agriculture (USDA). Second, implementing non-crop habitat management should take priority in areas with relatively limited natural area. In the second essay, a micro-economic model of post-disaster behavioral responses (moving versus staying) and income consequences is presented. Post-disaster responses are conceptualized as outcome of two forces: the severity of the disaster's damage and the individual's resilience. Three types of responses (voluntary movers, stayers, and forced movers) in the context of extreme weather events are discerned from the micro-economic foundation of expected utility theory and the net gain model. Adopting a quasi-experimental design with the endogenous switching regression, I empirically argue find evidence for a substantial amount of forced migration following the 2005 hurricanes Katrina and Rita. Moreover, the results suggest that movers in the disaster area encountered double victimization: they were forced to move and their income declined. Moreover, I find that the low income households were more severely affected than the population as a whole. The third essay contributes to the environmental and spatial econometric literature by proposing various spatial econometric model specifications based on panel estimation, linking weather fluctuations and extremes to a climate change interpretation. I show that the main source of spatial correlation between weather variables is due to biases associated with spatial aggregation rather than to (potentially) omitted weather variables. By incorporating different motivations for spatial correlation in the crop yield response function, we develop six model specifications. These model specifications are based on four motivations for spatial correlation: aggregation bias, omitted socio-economic variables, omitted weather variables, and biophysical processes of weather variables. In a prediction performance analysis I show that the choice of predictor needs to be motivated by the purpose of the model rather than by the smallest prediction error, because the statistical differences between the competing model specifications are generally small. I also show that omitted socio-economic variables are not a serious econometric concern in the context of crop yield response functions incorporating weather variables.
Degree
Ph.D.
Advisors
Florax, Purdue University.
Subject Area
Environmental economics|Economics|Agricultural economics
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