Spatial wage differentials and agglomeration externalities: Evidence from Indonesian microdata

Abstract

This paper aims to examine sources of labor wage differentials and to investigate human capital externalities across Indonesian districts. Our study attempts to fill the gap in the standard literature, which mainly asserts the key role of labor market characteristics in explaining the disparities. Based on microdata on individual workers from 2006-2015, we found that not only individual (labor) characteristics play a role in explaining the wage variations, but also regional endowments and agglomeration forces. The latter mainly results from spatial proximity of firms to other firms, from labor market pooling, and from knowledge spillovers. In addition, we also found strong evidence of positive human capital externalities, particularly in agglomerated regions. All in all, these findings may suggest the importance of skills and agglomeration for policymakers in boosting local productivity vis-à-vis reducing income/wage inequality.

Regional Wage Differences and Agglomeration Externalities: Micro Evidence from Thai Manufacturing Workers

“…Following Groot et al (2014), the spatial residuals at the provincial level shown in Figure 6 are interpreted as an average regional wage (after controlling for the observed worker characteristics and sectoral composition). Alternatively, the provincial average spatial residual could also be recognized as a regional wage premium (Ridhwan 2021). To simplify the interpretation, the nationwide average value was used for normalizing the spatial residuals.…”

“…Following Groot et al (2014) and Ridhwan (2021), the two-stage estimation technique was applied to identify the sources of regional wage disparity. The first-stage regression relates workers' wages to their various characteristics based on the Mincer earnings function, which includes education level, age, gender, industry, province, and year (see Mincer (1974)).…”

“…The combination of fixed effects (or industry-region-year fixed effects (γ ind,r,t )) are the so-called spatial residuals. In particular, these residual terms could be interpreted as regional productivity after correcting for workers' characteristics, industrial composition, location, and time (Combes et al 2008;Groot et al 2014;Ridhwan 2021).…”

“…Meanwhile, localization economies represent the positive externalities induced by industrial specialization in a specific boundary. Following the approaches introduced by Groot et al (2014) and Ridhwan (2021), the measurements of urbanization and localization economies were constructed using microdata from both IC and geospatial data.…”

“…Hence, this study identifies the source of regional wage differences in Thailand. A two-stage estimation method was applied to distinguish the effects of labor productivity from regional characteristics (Combes et al 2008;Groot et al 2014;Ridhwan 2021).…”