Does agricultural subsidies foster Italian southern farms? A Spatial Quantile Regression Approach

TL;DR

This paper investigates how agricultural subsidies influence farm performance in Southern Italy using a novel spatial quantile regression approach, revealing varying effects across performance levels and significant spatial spillovers.

Contribution

It introduces a micro-founded spatial quantile regression model to analyze the heterogeneous impact of subsidies on farm performance across different performance quantiles.

Findings

Subsidies have a positive impact on higher-performing farms.

Spatial spillovers significantly affect farm performance.

Impact of subsidies varies across the performance distribution.

Abstract

During the last decades, public policies become a central pillar in supporting and stabilising agricultural sector. In 1962, EU policy-makers developed the so-called Common Agricultural Policy (CAP) to ensure competitiveness and a common market organisation for agricultural products, while 2003 reform decouple the CAP from the production to focus only on income stabilization and the sustainability of agricultural sector. Notwithstanding farmers are highly dependent to public support, literature on the role played by the CAP in fostering agricultural performances is still scarce and fragmented. Actual CAP policies increases performance differentials between Northern Central EU countries and peripheral regions. This paper aims to evaluate the effectiveness of CAP in stimulate performances by focusing on Italian lagged Regions. Moreover, agricultural sector is deeply rooted in place-based production processes. In this sense, economic analysis which omit the presence of spatial dependence produce biased estimates of the performances. Therefore, this paper, using data on subsidies and economic results of farms from the RICA dataset which is part of the Farm Accountancy Data Network (FADN), proposes a spatial Augmented Cobb-Douglas Production Function to evaluate the effects of subsidies on farm's performances. The major innovation in this paper is the implementation of a micro-founded quantile version of a spatial lag model to examine how the impact of the subsidies may vary across the conditional distribution of agricultural performances. Results show an increasing shape which switch from negative to positive at the median and becomes statistical significant for higher quantiles. Additionally, spatial autocorrelation parameter is positive and significant across all the conditional distribution, suggesting the presence of significant spatial spillovers in agricultural performances.