The paper aims to investigate the relationship between distributive trade (wholesale and retail trade) and productivity growth across Italian provinces. In most studies, the potential determinants of productivity in the distributive trade have been investigated, while the impact of these activities on economic growth of the whole system has received less attention. By using panel data during the time period 2000–2013, the paper tests if the increase in the share of employees in distributive trade over the given period has promoted the productivity growth. This study applies both a random-effects model and, among the dynamic panel data estimators, a generalized method of moments estimator (GMM). In order to control both the issue of endogeneity, due to the presence of some potentially endogenous variables among the explanatory variables, and the problem of instrument proliferation, the GMM estimator is implemented together with a statistical method, which reduces the number of instruments when the set of endogenous variables is wide. The findings show that the distributive trade has a strong positive impact on the productivity growth. Moreover, this link is reinforced when we control the potential endogeneity. The results also support the idea that distributive trade can promote provincial convergence.

Distributive trade and regional productivity growth

DI BERARDINO, CLAUDIO;D'INGIULLO, DARIO;SARRA, Alessandro
2017-01-01

Abstract

The paper aims to investigate the relationship between distributive trade (wholesale and retail trade) and productivity growth across Italian provinces. In most studies, the potential determinants of productivity in the distributive trade have been investigated, while the impact of these activities on economic growth of the whole system has received less attention. By using panel data during the time period 2000–2013, the paper tests if the increase in the share of employees in distributive trade over the given period has promoted the productivity growth. This study applies both a random-effects model and, among the dynamic panel data estimators, a generalized method of moments estimator (GMM). In order to control both the issue of endogeneity, due to the presence of some potentially endogenous variables among the explanatory variables, and the problem of instrument proliferation, the GMM estimator is implemented together with a statistical method, which reduces the number of instruments when the set of endogenous variables is wide. The findings show that the distributive trade has a strong positive impact on the productivity growth. Moreover, this link is reinforced when we control the potential endogeneity. The results also support the idea that distributive trade can promote provincial convergence.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/671581
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