Use of panel time-series data with cross-section dependence in evaluating farmland valuation: a cautionary note

The note highlights how misspecification of cross-section dependence structure in panel time-series data can lead to erroneous conclusions on farmland valuation. Combining the sample information from time-series and cross-section dimensions by using panel time-series data can improve inference on the net present value hypothesis for farmland. However, cross-section dependence must be addressed to take advantage of the additional information from this type of data. We consider three classes of panel unit root models that account for cross-section dependence through (1) common factor extraction, (2) block bootstrapping and (3) spatial dependence to explore whether farmland values can be explained by their economic fundamentals, given that the appropriate cross-section specification is implemented in testing. Results show that only spatial dependence approach accurately characterizes cross-section dependence in the Iowa panel time-series data, highlighting the importance of model selection when using data with cross-section dependence. Once the econometric model is specified with the underlying spatial cross-section dependence structure, the market valuation of Iowa farmland is mainly determined by fundamentals as predicted by the net present value model.