Uncertainty appears to jump up after major shocks like the Cuban Missile crisis, the assassination of JFK, the OPEC I oil-price shock, and the 9/11 terrorist attacks. This paper offers a structural framework to analyze the impact of these uncertainty shocks. I build a model with a time-varying second moment, which is numerically solved and estimated using firm-level data. The parameterized model is then used to simulate a macro uncertainty shock, which produces a rapid drop and rebound in aggregate output and employment. This occurs because higher uncertainty causes firms to temporarily pause their investment and hiring. Productivity growth also falls because this pause in activity freezes reallocation across units. In the medium term the increased volatility from the shock induces an overshoot in output, employment, and productivity. Thus, uncertainty shocks generate short sharp recessions and recoveries. This simulated impact of an uncertainty shock is compared to vector autoregression estimations on actual data, showing a good match in both magnitude and timing. The paper also jointly estimates labor and capital adjustment costs (both convex and nonconvex). Ignoring capital adjustment costs is shown to lead to substantial bias, while ignoring labor adjustment costs does not. Copyright 2009 The Econometric Society.

We examine the impact of Chinese import competition on broad measures of technical change—patenting, IT, and TFP—using new panel data across twelve European countries from 1996 to 2007. In particular, we establish that the absolute volume of innovation increases within the firms most affected by Chinese imports in their output markets. We correct for endogeneity using the removal of product-specific quotas following China's entry into the World Trade Organization in 2001. Chinese import competition led to increased technical change within firms and reallocated employment between firms towards more technologically advanced firms. These within and between effects were about equal in magnitude, and account for 14% of European technology upgrading over 2000–7 (and even more when we allow for offshoring to China). Rising Chinese import competition also led to falls in employment and the share of unskilled workers. In contrast to low-wage nations like China, developed countries had no significant effect on innovation.

The last three decades have witnessed an explosion of theoretical work on the organization of firms (Robert Gibbons and John Roberts forthcoming). In parallel, there has been a massive increase in access to microdata which has revealed huge dispersions in productivity. For example, within narrow industries like cement, oak flooring, and block-ice the total factor productivity of plants at the ninetieth percentile is about twice that of those at the tenth percentile (Lucia Foster, John Haltiwanger, and Chad Syversson 2008). Unfortunately, analyzing to what extent this heterogeneity in productivity is due to management and organizational practices, unmeasured inputs, or other technologies has been held back by a lack of data. National statistical agencies do not usually collect data on the internal organization of companies, nor do firms report this in their accounts. Recently, however, social scientists have been starting to fill this gap by working closely with small numbers of individual firms (e.g., the “Insider Econometrics” approach described in Kathryn Shaw 2009) or covering wide cross-sections of firms (e.g., Nicholas Bloom, Raffaella Sadun, and John Van Reenen 2009). In this paper we describe some of the tools of this research, particularly Bloom and Van Reenen (2007)—henceforth BVR— for measuring management and organizational practices. 1

Abstract We argue that social capital as proxied by trust increases aggregate productivity by affecting the organization of firms. To do this we collect new data on the decentralization of investment, hiring, production, and sales decisions from corporate headquarters to local plant managers in almost 4,000 firms in the United States, Europe, and Asia. We find that firms headquartered in high-trust regions are significantly more likely to decentralize. To help identify causal effects, we look within multinational firms and show that higher levels of bilateral trust between the multinational’s country of origin and subsidiary’s country of location increases decentralization, even after instrumenting trust using religious similarities between the countries. Finally, we show evidence suggesting that trust raises aggregate productivity by facilitating reallocation between firms and allowing more efficient firms to grow, as CEOs can decentralize more decisions.

The impact of R&D on growth through spillovers has been a major topic of economic research over the last thirty years. A central problem in the literature is that firm performance is affected by two countervailing “spillovers” : a positive effect from technology (knowledge) spillovers and a negative business stealing effects from product market rivals. We develop a general framework incorporating these two types of spillovers and implement this model using measures of a firm's position in technology space and productmarket space. Using panel data on U.S. firms, we show that technology spillovers quantitatively dominate, so that the gross social returns to R&D are at least twice as high as the private returns. We identify the causal effect of R&D spillovers by using changes in federal and state tax incentives for R&D. We also find that smaller firms generate lower social returns to R&D because they operate more in technological niches. Finally, we detail the desirable properties of an ideal spillover measure and how existing approaches, including our new Mahalanobis measure, compare to these criteria.

Abstract No previous infectious disease outbreak, including the Spanish Flu, has affected the stock market as forcefully as the COVID-19 pandemic. In fact, previous pandemics left only mild traces on the U.S. stock market. We use text-based methods to develop these points with respect to large daily stock market moves back to 1900 and with respect to overall stock market volatility back to 1985. We also evaluate potential explanations for the unprecedented stock market reaction to the COVID-19 pandemic. The evidence we amass suggests that government restrictions on commercial activity and voluntary social distancing, operating with powerful effects in a service-oriented economy, are the main reasons the U.S. stock market reacted so much more forcefully to COVID-19 than to previous pandemics in 1918–1919, 1957–1958, and 1968.

Many Americans continued some forms of social distancing after the pandemic. This phenomenon is stronger among older persons, less educated individuals, and those who interact daily with persons at high risk from infectious diseases. Regression models fit to individual-level data suggest that social distancing lowered labor force participation by 2.4 percentage points in 2022, 1.2 points on an earnings-weighted basis. When combined with simple equilibrium models, our results imply that the social distancing drag on participation reduced US output by $205 billion in 2022, shrank the college wage premium by 2.1 percentage points, and modestly steepened the cross-sectional age-wage profile.

We show how real and financial frictions amplify, prolong, and propagate the negative impact of uncertainty shocks. We use a novel instrumentation strategy to address endogeneity in estimating the impact of uncertainty by exploiting differential firm exposure to exchange rate, policy, and energy price volatility. We show that financially constrained firms cut investment more than unconstrained firms following an uncertainty shock. We then build a general equilibrium heterogeneous firms model with real and financial frictions, finding that financial frictions (i) amplify uncertainty shocks by doubling their impact on output; (ii) increase persistence by doubling the duration of the drop; and (iii) propagate uncertainty shocks by spreading their impact onto financial variables.

Abstract A rising share of employees now regularly engage in working from home (WFH), but there are concerns this can lead to “shirking from home.” We report the results of a WFH experiment at Ctrip, a 16,000-employee, NASDAQ-listed Chinese travel agency. Call center employees who volunteered to WFH were randomly assigned either to work from home or in the office for nine months. Home working led to a 13% performance increase, of which 9% was from working more minutes per shift (fewer breaks and sick days) and 4% from more calls per minute (attributed to a quieter and more convenient working environment). Home workers also reported improved work satisfaction, and their attrition rate halved, but their promotion rate conditional on performance fell. Due to the success of the experiment, Ctrip rolled out the option to WFH to the whole firm and allowed the experimental employees to reselect between the home and office. Interestingly, over half of them switched, which led to the gains from WFH almost doubling to 22%. This highlights the benefits of learning and selection effects when adopting modern management practices like WFH.

Using an innovative survey measure of management practices on over 15,000 firms, we find private equity firms are better managed than government, family, and privately owned firms, and have similar management to publicly listed firms. This is true both in developed and developing countries. Looking at management practices in detail we find that private equity owned firms have strong people management practices (hiring, firing, pay, and promotions), but even stronger monitoring management practices (lean manufacturing, continuous improvement, and monitoring). Plant managers working in private equity owned firms also report greater autonomy from headquarters over sales, marketing, and new product introduction.