2020/02/10 by Anna Gloria Billé, Billè, Anna Gloria, Marco Rogna +1
Economics, Econometrics and Finance · Environmental Science · Agricultural and Biological Sciences · #Spatial and Panel Data Analysis #Land Use and Ecosystem Services #Agricultural Economics and Policy
paper · pdf · doi:10.48550/arxiv.2002.03922
Given the extreme dependence of agriculture on weather conditions, this paper\nanalyses the effect of climatic variations on this economic sector, by\nconsidering both a huge dataset and a flexible spatio-temporal model\nspecification. In particular, we study the response of N-fertilizer application\nto abnormal weather conditions, while accounting for other relevant control\nvariables. The dataset consists of gridded data spanning over 21 years\n(1993-2013), while the methodological strategy makes use of a spatial dynamic\npanel data (SDPD) model that accounts for both space and time fixed effects,\nbesides dealing with both space and time dependences. Time-invariant short and\nlong term effects, as well as time-varying marginal effects are also properly\ndefined, revealing interesting results on the impact of both GDP and weather\nconditions on fertilizer utilizations. The analysis considers four\nmacro-regions -- Europe, South America, South-East Asia and Africa -- to allow\nfor comparisons among different socio-economic societies. In addition to\nfinding both spatial (in the form of knowledge spillover effects) and temporal\ndependences as well as a good support for the existence of an environmental\nKuznets curve for fertilizer application, the paper shows peculiar responses of\nN-fertilization to deviations from normal weather conditions of moisture for\neach selected region, calling for ad hoc policy interventions.\n