Aggregate Uncertainty And Sectoral Productivity Growth

We show that an increase in aggregate uncertainty—measured by stock market volatility—reduces productivity growth more in industries that depend heavily on external finance. This effect is larger during recessions, when financing constraints are more likely to be binding, than during expansions. Our statistical method—a difference-in-difference approach using productivity growth for 25 industries for 18 advanced economies over the period 1985-2010—mitigates concerns with omitted variable bias and reverse causality. The results are robust to the inclusion of other sources of interaction effects, such as financial development (Rajan and Zingales, 1998) and counter-cyclical fiscal policy (Aghion et al., 2014). The results also hold if economic policy uncertainty (Baker et al., 2015) is used instead of stock market volatility as the measure of aggregate uncertainty.

We study the role of uncertainty shocks in explaining unemployment dynamics, separating out the role of aggregate and sectoral channels. Using S&P500 data from the first quarter of 1957 to third quarter of 2014, we construct separate indices to measure aggregate and sectoral uncertainty and compare their effects on the unemployment rate in a standard macroeconomic vector autoregressive (VAR) model. We find that aggregate uncertainty leads to an immediate increase in unemployment, with the impact dissipating within a year. In contrast, sectoral uncertainty has a long-lived impact on unemployment, with the peak impact occurring after two years. The results are consistent with a view that the impact of aggregate uncertainty occurs through a “wait-and-see” mechanism while increased sectoral uncertainty raises unemployment by requiring greater reallocation across sectors.

China’s growth potential has become a hotly debated topic as the economy has reached an income level susceptible to the “middle-income trap” and financial vulnerabilities are mounting after years of rapid credit expansion. However, the existing literature has largely focused on macro level aggregates, which are ill suited to understanding China’s significant structural transformation and its impact on economic growth. To fill the gap, this paper takes a deep dive into China’s convergence progress in 38 industrial sectors and 11 services sectors, examines past sectoral transitions, and predicts future shifts. We find that China’s productivity convergence remains at an early stage, with the industrial sector more advanced than services. Large variations exist among subsectors, with high-tech industrial sectors, in particular the ICT sector, lagging low-tech sectors. Going forward, ample room remains for further convergence, but the shrinking distance to the frontier, the structural shift from industry to services, and demographic changes will put sustained downward pressure on growth, which could slow to 5 percent by 2025 and 4 percent by 2030. Digitalization, SOE reform, and services sector opening up could be three major forces boosting future growth, while the risks of a financial crisis and a reversal in global integration in trade and technology could slow the pace of convergence.

These classic studies of the history of economic change in 19th- and 20th-century United States, Canada, and British West Indies examine national product; capital stock and wealth; and fertility, health, and mortality. "A 'must have' in the library of the serious economic historian."—Samuel Bostaph, Southern Economic Journal

The COVID-19 pandemic struck the global economy after a decade that featured a broad-based slowdown in productivity growth. Global Productivity: Trends, Drivers, and Policies presents the first comprehensive analysis of the evolution and drivers of productivity growth, examines the effects of COVID-19 on productivity, and discusses a wide range of policies needed to rekindle productivity growth. The book also provides a far-reaching data set of multiple measures of productivity for up to 164 advanced economies and emerging market and developing economies, and it introduces a new sectoral database of productivity. The World Bank has created an extraordinary book on productivity, covering a large group of countries and using a wide variety of data sources. There is an emphasis on emerging and developing economies, whereas the prior literature has concentrated on developed economies. The book seeks to understand growth patterns and quantify the role of (among other things) the reallocation of factors, technological change, and the impact of natural disasters, including the COVID-19 pandemic. This book is must-reading for specialists in emerging economies but also provides deep insights for anyone interested in economic growth and productivity. Martin Neil Baily Senior Fellow, The Brookings Institution Former Chair, U.S. President’s Council of Economic Advisers This is an important book at a critical time. As the book notes, global productivity growth had already been slowing prior to the COVID-19 pandemic and collapses with the pandemic. If we want an effective recovery, we have to understand what was driving these long-run trends. The book presents a novel global approach to examining the levels, growth rates, and drivers of productivity growth. For anyone wanting to understand or influence productivity growth, this is an essential read. Nicholas Bloom William D. Eberle Professor of Economics, Stanford University The COVID-19 pandemic hit a global economy that was already struggling with an adverse pre-existing condition—slow productivity growth. This extraordinarily valuable and timely book brings considerable new evidence that shows the broad-based, long-standing nature of the slowdown. It is comprehensive, with an exceptional focus on emerging market and developing economies. Importantly, it shows how severe disasters (of which COVID-19 is just the latest) typically harm productivity. There are no silver bullets, but the book suggests sensible strategies to improve growth prospects. John Fernald Schroders Chaired Professor of European Competitiveness and Reform and Professor of Economics, INSEAD

Central bankers often assert that low inflation and anchoring of inflation expectations are good for economic growth (Bernanke 2007, Plosser 2007). We test this claim using panel data on sectoral growth for 22 manufacturing industries for 36 advanced and emerging market economies over the period 1990-2014. Inflation anchoring in each country is measured as the response of inflation expectations to inflation surprises (Levin et al., 2004). We find that credit constrained industries—those characterized by high external financial dependence and R&D intensity and low asset tangibility—tend to grow faster in countries with well-anchored inflation expectations. The results are robust to controlling for the interaction between these characteristics and a broad set of macroeconomic variables over the sample period, such as financial development, inflation, the size of government, overall economic growth, monetary policy counter-cyclicality and the level of inflation. Importantly, the results suggest that it is inflation anchoring and not the level of inflation per se that has a significant effect on average industry growth. Finally, the results are robust to IV techniques, using as instruments indicators of monetary policy transparency and independence.