The increasing availability of employer-employee matched data linking workers and firms has provided opportunities to explore issues around productivity dispersion and wage inequality at the firm level in higher-income countries. However, such data is rare for lower-income countries. This project fills this gap by generating a novel dataset matching employers and employees in Senegal. This dataset will be used to explore determinants of productivity and how it varies between industries and regions, sorting between workers and firms, and how firm productivity and other factors determine wage gaps.
Two administrative data sources from the National Statistics Office and Revenue Agency will be linked to construct the Senegalese Employer-Employee Database (SEED). These data sources cover over 13,000 formal firms and over 800,000 workers distributed across Senegal. The SEED will include firm-level and worker-level data collected between 2008 and 2018 and will be used to study a variety of issues by the research team before being made available for other researchers. Primarily, a group of semi-parametric methods (Olley and Pakes, 1996; Levinshohn and Levin, 2003; and Ackerberg, Caves, and Frazer, 2015) will be used to estimate firm productivity. The best alternative within these semi-parametric estimators will be selected before exploring the geographical dispersion of productivity. In addition, the researchers will apply the AKM model (Abowd, Kramarz and Margolis, 1999) to estimate the wage premium of firms and analyse the assortative matching between employers and workers.
This project will produce empirical work addressing the question of why firms differ in their measured productivity levels and how workers self-select into jobs. Identifying how the quality of matching can be improved will help in the design of labour market policy. Further, the results of this research will help design appropriate policies to promote employment of young new workers entering the labour market, improve industrial policy through better identification of promising sectors, and propose regulations to tailor tax policy to the spatial dispersion of firms.
