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The appropriate use of disaggregated economic data not only improves the accuracy and robustness of economic analyses, but also extends the existing economic models to address new aspects of the issue. This dissertation consists of three essays: two essays use disaggregated economic-engineering data to address spatial heterogeneity in economic losses and regional interdependencies for Tsunami impact assessment and resilience planning in State of Oregon. The third essay uses disaggregated retail-store data to address the issues of estimation biasness using aggregated annual household purchase data in fresh fruit demand analysis.
The first essay presents an integrated engineering-economic impact assessment of a potential major Cascadia Subduction Zone (CSZ) Tsunami event on Clatsop County, a coastal county in State of Oregon. The model addresses spatial heterogeneities of physical damages and economic activities by integrating an engineering simulation using Method of Splitting Tsunami (MOST) with a computable general equilibrium (CGE) model. I find the integrated model predicts different economic losses and rankings of vulnerable sectors comparing to non-integrated model. The differences in economic impact assessment will lead to different allocation of disaster-relief resources and prioritization of vulnerable industry sectors in the regional disaster resilience plan.
The second essay develops an algorithm to spatially disaggregate the county-level transaction data into two sub-county regions, one of which is spatially aligned with the irregular spatial extent of the potential damage from natural disasters. Using the derived sub-county regional transaction data as the input, a Sub-County, Multi-regional CGE model is built to address spatially concentrated risks and cross-regional interdependencies within the jurisdictional boundaries. Comparing to County CGE model, Multi-Regional CGE predicts less economic losses in energy sector but more losses in health sector, due to imbalanced cross-regional trades within jurisdictional boundaries. To support the design of Oregon Resilience Plan, a case study of evaluating impacts of relocating a major health service facility out of inundation zone is also carried out using the multi-regional model.
The third essay performs a demand analysis of both conventional and organic fruit at the retail level, using a disaggregated store-level retail data. The study address the issues of estimation biasness using home-scan data due to annual aggregation of household purchases, inconsistent consumption bundles and missing price information of zero purchases. Comparing to home-scan demand analysis, this estimation shows more consistent results in cross-price elasticity between conventional and organic fresh fruits. The retail-store data also provides insights on the effects of marketing strategy and seasonal preference on fresh fruit demand.
Available online from the National Sea Grant Library