Given the extreme dependence of agriculture on weather conditions, this paper analyses the effect of climatic variations on this economic sector, by considering both a huge dataset and a flexible spatio-temporal model specification. In particular, we study the response of N-fertilizer application to abnormal weather conditions, while accounting for GDP as a control variable. The dataset consists of gridded data spanning over 21 years (1993-2013), while the methodological strategy makes use of a spatial dynamic panel data (SDPD) model that accounts for both space and time fixed effects, besides dealing with both space and time dependences. Time-invariant short and long term effects, as well as time-varying marginal effects are also properly defined, revealing interesting results on the impact of both GDP and weather conditions on fertilizer utilizations. The analysis considers four macro-regions - Europe, South America, South-East Asia and Africa - to allow for comparisons among different socio-economic societies. In addition to finding both spatial (in the form of knowledge spillover effects) and temporal dependences as well as a good support for the existence of an environmental Kuznets curve for fertilizer application, the paper shows peculiar responses of N-fertilization to deviations from normal weather conditions of moisture for each selected region, calling for ad hoc policy interventions.

The Effect of Weather Conditions on Fertilizer Applications: A Spatial Dynamic Panel Data Analysis / Anna Gloria Billé; Marco Rogna. - In: JOURNAL OF THE ROYAL STATISTICAL SOCIETY. SERIES A, STATISTICS IN SOCIETY. - ISSN 1467-985X. - ELETTRONICO. - 185:1 (January)(2022), pp. 3-36. [10.1111/rssa.12709]

The Effect of Weather Conditions on Fertilizer Applications: A Spatial Dynamic Panel Data Analysis

Anna Gloria Billé
Primo
;
2022

Abstract

Given the extreme dependence of agriculture on weather conditions, this paper analyses the effect of climatic variations on this economic sector, by considering both a huge dataset and a flexible spatio-temporal model specification. In particular, we study the response of N-fertilizer application to abnormal weather conditions, while accounting for GDP as a control variable. The dataset consists of gridded data spanning over 21 years (1993-2013), while the methodological strategy makes use of a spatial dynamic panel data (SDPD) model that accounts for both space and time fixed effects, besides dealing with both space and time dependences. Time-invariant short and long term effects, as well as time-varying marginal effects are also properly defined, revealing interesting results on the impact of both GDP and weather conditions on fertilizer utilizations. The analysis considers four macro-regions - Europe, South America, South-East Asia and Africa - to allow for comparisons among different socio-economic societies. In addition to finding both spatial (in the form of knowledge spillover effects) and temporal dependences as well as a good support for the existence of an environmental Kuznets curve for fertilizer application, the paper shows peculiar responses of N-fertilization to deviations from normal weather conditions of moisture for each selected region, calling for ad hoc policy interventions.
2022
The Effect of Weather Conditions on Fertilizer Applications: A Spatial Dynamic Panel Data Analysis / Anna Gloria Billé; Marco Rogna. - In: JOURNAL OF THE ROYAL STATISTICAL SOCIETY. SERIES A, STATISTICS IN SOCIETY. - ISSN 1467-985X. - ELETTRONICO. - 185:1 (January)(2022), pp. 3-36. [10.1111/rssa.12709]
Anna Gloria Billé; Marco Rogna
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