There is extensive evidence that private firms in developing economies face larger barriers to expanding than firms in advanced economies and that differences in barriers to firm growth manifest in aggregate productivity differences. It is conceivable, however, that productivity differences also result from the lower quality of human capital employed by firms in less developed economies, as suggested by the theoretical analysis in Jones (2014). Distinguishing between resource misallocation and skill deficits is of paramount importance for policy, as interventions that would address one problem may not be successful in tackling the other, but progress in this direction has been halted by the lack of suitable data.
This project is therefore implemented in two steps. First, design and collection of a novel worker-level dataset on occupational skills in low- and middle-income countries, that is fully comparable with analogous data sources in high-income countries and is accompanied by firm-level data on production, capital, and intermediate inputs. Second, quantification of the productivity losses that result from differences in the skill content of jobs and from differences in the efficiency of labour allocations across countries, using our novel dataset to inform a general equilibrium model with human capital and frictional labour markets.
Management practices in developing economies are often based on tradition or otherwise obsolete information, and uncertainty is a significant obstacle to firm expansion (Bloom et al., 2013). Access to high-quality data can improve firm-level operational efficiency in LICs. This project responds precisely to the need for accurate and reliable information for improved decision-making in LICs. The researchers will provide access to reliable skill data and complement the data with detailed statistical and economic analysis to enhance human resource management, training, and hiring practices by both private and public decision-makers.
