Okun's (1962) seminal paper is an important study on economic growth and unemployment but a detailed exploration of the effect of productivity growth on unemployment has been left aside. Yet, the relationship between productivity growth and unemployment has been debated since long. In this paper we present stylized facts on the link between productivity growth and unemployment for the short and long run, and present model variants that demonstrate that in the short run productivity growth can have a negative effect on employment - or may even increase unemployment - while in the long run the relationship between productivity growth and employment are likely to co-vary positively. Using US data, empirically we decompose the time series of unemployment rate and productivity growth into long run and short run components and show empirical evidence that the long run and short run components co-vary as predicted by some theories.
We propose a theory of low-frequency movements in unemployment based on asymmetric real wage rigidities. The theory generates two main predictions: long-run unemployment increases with (i) a fall in long-run productivity growth and (ii) a rise in the variance of productivity growth. Evidence based on U.S. time series and on an international panel strongly supports these predictions. The empirical specifications featuring the variance of productivity growth can account for two U.S. episodes which a linear model based only on long-run productivity growth cannot fully explain. These are the decline in long-run unemployment over the 1980s and its rise during the late 2000s.
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.
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
Traditionally, economic growth and business cycles have been treated independently. However, the dependence of GDP levels on its history of shocks, what economists refer to as “hysteresis,” argues for unifying the analysis of growth and cycles. In this paper, we review the recent empirical and theoretical literature that motivate this paradigm shift. The renewed interest in hysteresis has been sparked by the persistence of the Global Financial Crisis and fears of a slow recovery from the Covid-19 crisis. The findings of the recent literature have far-reaching conceptual and policy implications. In recessions, monetary and fiscal policies need to be more active to avoid the permanent scars of a downturn. And in good times, running a high-pressure economy could have permanent positive effects.
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