2022/11/29 by Ioannis Skevas · 13 citations
Agricultural and Biological Sciences · Decision Sciences · Economics, Econometrics and Finance · #Agricultural Economics and Policy #Ecology #Econometrics #Economic and Environmental Valuation #Economics #Efficiency Analysis Using DEA #Frontier #Geography #Identification (biology) #Inefficiency #Macroeconomics #Microeconomics #Productivity #Total factor productivity
paper · pdf · doi:10.1111/ajae.12360
published in American Journal of Agricultural Economics 105(4), 1221-1247 (Wiley)
openalex publication_date 2022/11/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
Abstract This article presents a novel modeling framework that quantifies spatial spillovers on firm total factor productivity (TFP) growth and its components in a single‐stage setting. A random parameters frontier model is specified to measure firm efficiency and calculate TFP growth and its components while allowing for the random parameters and the inefficiency term to be functions of individuals' and neighbors' characteristics. In this manner, the dependence of TFP growth and its components on these characteristics is built into the model, and the corresponding marginal effects are calculated. The empirical application concerns specialized Dutch dairy farms observed over the 2009–2016 period. Apart from the conventional input–output quantities, information on farms' latitudes and longitudes is available, thus allowing the identification of neighboring producers and testing for the existence of spatial spillovers. The empirical findings suggest that farms surrounded by more intensive neighbors experience faster technical progress and TFP growth, which highlights the existence of positive spatial spillovers in Dutch dairy farming.