Essays on farmland values: a spatial econometrics perspective - Pinto Padilla, Allan (Kansas State University, 2023)
This dissertation seeks to evaluate the suitability of current statistical methods for identifying explosive unit root processes and to explore the spread of farmland values in a system influenced by temporal and cross-sectional interdependencies. The primary focus of the study is to examine the impact of agricultural and non-agricultural variables on farmland values at both the county level and in adjacent areas. The study focuses on the analysis of farmland values in the 99 counties of Iowa from 1969 to 2014. It explores the influence of population density and income on those values. The econometric procedures developed by Ciccarelli and Elhorst (2018) are employed to examine the dynamics of farmland values in the region. The study reveals a positive relationship between population density and farmland values in Iowa. An increase in population contributes to higher farmland values due to increased alternative uses for farmland. Using the multi-step procedure proposed by Aquaro, Bailey and Pesaran (2021), this study applies a heterogeneous spatial autoregressive model to analyze the Iowa farmland market, taking into account regional heterogeneity. The spatial parameters yield results that challenge prevailing economic theories of spatial dependence. A comprehensive framework is developed to capture the heterogeneous nature of farmland value spillovers, while simultaneously considering common factors in a manner that maintains generality. The study also investigates the direct and indirect effects of income per capita and population density. Through this analysis, insights are gained regarding the influence of changes in neighboring population density and income per capita on farmland values within a particular county over a specified time period. The findings emphasize a dominant area ripple effect and core-periphery spillovers in urbanized areas. This dissertation makes a significant contribution by evaluating farmland dynamics and network effects in accordance with theories of new economic geography and spatial dependence. Finally, this dissertation introduces and explains the “Kansas Property Tax Estimation Tool”, including several illustrative examples. The tool is designed to enhance and streamline tax planning processes. Legislators, taxing districts, and land managers can utilize the Estimator to run various “what if” scenarios promptly, on any device. The tool offers sufficient flexibility to cater to the needs of taxing districts throughout the entire state, regardless of the device used (mobile or desktop).
Keywords: Farmland values; Spatial autocorrelation; Dynamic; Spatial econometrics