Economists have shown that large and persistent differences in productivity levels across businesses are ubiquitous. This finding has shaped research agendas in a number of fields, including (but not limited to) macroeconomics, industrial organization, labor, and trade. This paper surveys and evaluates recent empirical work addressing the question of why businesses differ in their measured productivity levels. The causes are manifold, and differ depending on the particular setting. They include elements sourced in production practices -- and therefore over which producers have some direct control, at least in theory -- as well as from producers' external operating environments. After evaluating the current state of knowledge, I lay out what I see are the major questions that research in the area should address going forward. (JEL D24, G31, L11, M10, O30, O47)

There is considerable evidence that producer-level churning contributes substantially to aggregate (industry) productivity growth, as more productive businesses displace less productive ones. However, this research has been limited by the fact that producer-level prices are typically unobserved; thus within-industry price differences are embodied in productivity measures. If prices reflect idiosyncratic demand or market power shifts, high "productivity" businesses may not be particularly efficient, and the literature's findings might be better interpreted as evidence of entering businesses displacing less profitable, but not necessarily less productive, exiting businesses. In this paper, we investigate the nature of selection and productivity growth using data from industries where we observe producer-level quantities and prices separately. We show there are important differences between revenue and physical productivity. A key dissimilarity is that physical productivity is inversely correlated with plant-level prices while revenue productivity is positively correlated with prices. This implies that previous work linking (revenue-based) productivity to survival has confounded the separate and opposing effects of technical efficiency and demand on survival, understating the true impacts of both. We further show that young producers charge lower prices than incumbents, and as such the literature understates the productivity advantage of new producers and the contribution of entry to aggregate productivity growth.

A pervasive finding in the burgeoning literature using business microdata is that firm turnover is high and that this churning process contributes substantially to aggregate (industry) productivity growth, as more productive entrants appear to displace less productive exiting businesses. A limitation of this research is that establishment-level prices are typically unobserved, resulting in within-industry price differences being embodied in productivity measures. If prices reflect idiosyncratic demand shifts or market power variation, high "productivity" businesses may not be particularly efficient. In this case, the literature's findings might be better interpreted as evidence of entering businesses displacing less profitable, but not necessarily less productive, exiting businesses. This distinction is important not only for the sake of understanding the positive features of selection, but the normative ones as well; whether selection is driven by efficiency or market power differences has important welfare implications. In this paper, we investigate the nature of selection using data from industries where we observe both establishment-level quantities and prices. We find that, as has been found in the preceding literature for revenue-based TFP measures, physical productivity and prices also exhibit considerable within-industry variation. We also show that while physical productivity shares common traits with revenue-based measures, there are important differences. These involve the productivity levels of entrants relative to incumbents and the size of the impact of net entry on productivity aggregates. Furthermore, we characterize the dimension(s) of selection and show that both idiosyncratic productivity and demand (price) conditions affect businesses' survival probabilities.

Many studies have documented large and persistent productivity differences across producers, even within narrowly defined industries. This paper both extends and departs from the past literature, which focused on technological explanations for these differences, by proposing that demand-side features also play a role in creating the observed productivity variation. The specific mechanism investigated here is the effect of spatial substitutability in the product market. When producers are densely clustered in a market, it is easier for consumers to switch between suppliers (making the market in a certain sense more competitive). Relatively inefficient producers find it more difficult to operate profitably as a result. Substitutability increases truncate the productivity distribution from below, resulting in higher minimum and average productivity levels as well as less productivity dispersion. The paper presents a model that makes this process explicit and empirically tests it using data from U.S. ready-mixed concrete plants, taking advantage of geographic variation in substitutability created by the industry's high transport costs. The results support the model's predictions and appear robust.Markets with high demand density for ready-mixed concrete-and thus high concrete plant densities-have higher lower-bound and average productivity levels and exhibit less productivity dispersion among their producers.

Economists have shown that large and persistent differences in productivity levels across businesses are ubiquitous. This finding has shaped research agendas in a number of fields, including (but not limited to) macroeconomics, industrial organization, labor, and trade. This paper surveys and evaluates recent empirical work addressing the question of why businesses differ in their measured productivity levels. The causes are manifold, and differ depending on the particular setting. They include elements sourced in production practices-and therefore over which producers have some direct control, at least in theory-as well as from producers' external operating environments. After evaluating the current state of knowledge, I lay out what I see are the major questions that research in the area should address going forward.

Agents are often better informed than the clients who hire them and may exploit this informational advantage. Real estate agents have an incentive to convince clients to sell their houses too cheaply and too quickly. We test these predictions by comparing home sales in which real estate agents are hired to when an agent sells his own home. Consistent with the theory, we find homes owned by real estate agents sell for 3.7% more than other houses and stay on the market 9.5 days longer, controlling for observables. Greater information asymmetry leads to larger distortions. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Tratjenberg, and numerous participants at the NBER Workshop on AI and Economics in September, 2017. In particular, Rebecca Henderson provided detailed and very helpful comments on an earlier draft and Larry Summers suggested the analogy to the J-Curve. Generous funding for this research was provided in part by the MIT Initiative on the Digital Economy. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We would like to thank seminar participants at the University of Chicago for their comments and SafeGraph, Inc. for making their data available for academic COVID research. We thank Roxanne Nesbitt and, especially, Nicole Bei Luo for superb research assistance and the Initiative on Global Markets for financial assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.