In an influential study, Bender et al (2018) document consistent relationships between management practices, productivity, and workforce composition using administrative data from German firms matched to ratings of their practices from the World Management Survey. We replicate and extend their analysis using comparable data from Brazil. The main conclusions from their study are supported in ours, strengthening the view that more structured practices affect organizational performance through workforce selection across different institutional settings. However, we find more structured management practices are linked to greater wage inequality in Brazil, relative to greater wage compression in Germany, suggesting that some of the consequences of adopting structured practices are tied to the local context.
Understanding how differences in management “best practices’’ affect organizational outcomes has been a focus of both theoretical and empirical work in the fields of management, sociology, economics and public policy. The World Management Survey (WMS) project was born almost two decades ago with the main goal of developing a new systematic measure of management practices being used in organisations. The WMS has contributed to a body of knowledge around how managerial structures, not just managerial talent, relates to organizational performance. Over 18 years of research, a set of consistent patterns have emerged and spurred new questions. We will present a brief overview of what we have learned in terms of measuring and understanding management practices and condense the implications of these findings for policy. We end with an outline of what we see as the path forward for both research and policy implications of this research programme.
International Data on Measuring Management Practices, 2016. American Economic Association – Papers & Proceedings
with N Bloom, R Lemos, R Sadun and J Van Reenen
Rapid advances in computer power and increased openness of national statistical agencies have led to unprecedented availability of large datasets. Consider three types of firm datasets. First, governments collect administrative data on firms: information on jobs, investment and output has long been collected to calculate national, industrial and regional statistics. Second, there has been an explosion of Big Data – various forms of data typically created for business purposes. Products like ORBIS contain over 50 million firms from almost every country in the world and can be used to address many questions. Another example is Compustat, which contains extensive data for about 6,000 listed US firms but excludes the other 99% of private firms. We focus on a third type of international firm data, which is collected from surveys. In an age of rich administrative and Big Data why bother with such surveys?
Over the last decade the World Management Survey (WMS) has collected firm-level management practices data across multiple sectors and countries. We developed the survey to try to explain the large and persistent total factor productivity (TFP) differences across firms and countries. This review paper discusses what has been learned empirically and theoretically from the WMS and other recent work on management practices. Our preliminary results suggest that about a quarter of cross-country and within-country TFP gaps can be accounted for by management practices. Management seems to matter both qualitatively and quantitatively for performance at the level of the firm and the nation. Competition, governance, human capital, and informational frictions help account for the variation in management. We make some suggestions for both policy and future research.