This paper studies whether removing barriers to trade induces efficiency gains for producers. Like almost all empirical work which relies on a production function to recover productivity measures, I do not observe physical output at the firm level. Therefore, it is imperative to control for unobserved prices and demand shocks. I develop an empirical model that combines a demand system with a production function to generate estimates of productivity. I rely on my framework to identify the productivity effects from reduced trade protection in the Belgian textile market. This trade liberalization provides me with observed demand shifters that are used to separate out the associated price, scale, and productivity effects. Using a matched plant–product level data set and detailed quota data, I find that correcting for unobserved prices leads to substantially lower productivity gains. More specifically, abolishing all quota protections increases firm-level productivity by only 2 percent as opposed to 8 percent when relying on standard measures of productivity. My results beg for a serious reevaluation of a long list of empirical studies that document productivity responses to major industry shocks and, in particular, to opening up to trade. My findings imply the need to study the impact of changes in the operating environment on productivity together with market power and prices in one integrated framework. The suggested method and identification strategy are quite general and can be applied whenever it is important to distinguish between revenue productivity and physical productivity.

We measure the impact of a drastic new technology for producing steel—the minimill—on industry-wide productivity in the US steel industry, using unique plant-level data between 1963 and 2002. The sharp increase in the industry's productivity is linked to this new technology through two distinct mechanisms: (i ) the mere displacement of the older technology (vertically integrated producers) was responsible for a third of the increase in the industry's productivity, and (ii ) increased competition, due the minimill expansion, drove a productivity resurgence at the surviving vertical integrated producers and, consequently, the productivity of the industry as a whole.

We compare and combine two distinct approaches to estimating market power in the US brewing industry—one based on production data, the other on demand. Both methods produce similar estimates of average markups and reveal a recent upward trend. We then combine the two approaches in two ways. First, we replace conventional instruments in demand estimation with a moment involving a production-based markup estimate, yielding similar results. We then evaluate the common (but controversial) assumption that retail markets operate competitively, finding that demand-based markups recovered with the assumption of competitive retail markets align with production-based estimates, as long as downstream costs are accounted for.

In this paper, we develop a method to estimate markups using plant-level production data. Our approach relies on cost-minimizing producers and the existence of at least one variable input of production. The suggested empirical framework relies on the estimation of a production function and provides estimates of plant-level mark-ups without specifying how firms compete in the product market. We rely on our method to explore the relationship between markups and export behavior. We find that markups are estimated significantly higher when controlling for unobserved productivity; that exporters charge, on average, higher markups and that markups increase upon export entry.

Manager pay has increased considerably since 1980, and so has inequality in manager pay. Over the same period, there has been a sharp rise in market power. We start from the premise that the role of managers is to increase firm productivity. When markets are imperfectly competitive, productivity not only helps firm grow in size, productivity also affects market power. We model how imperfect competition in product markets affects manager pay, and break down the contributions of firm size and market power to compensation. We find that market power, on average, accounts for 45.2% of total manager pay. Notably, there is substantial variation across managers. Top managers are disproportionately employed by firms with market power, and they benefit from it: in 2019, 80.3% of top manager pay is attributable to market power. Our main conclusion is that rise of market power explains half of the increase in average manager pay, and nearly all of the increase in manager pay inequality.

We document the evolution of market power based on firm-level data for the U.S. economy since 1955. We measure both markups and profitability. In 1980, aggregate markups start to rise from 21% above marginal cost to 61% now. The increase is driven mainly by the upper tail of the markup distribution: the upper percentiles have increased sharply. Quite strikingly, the median is unchanged. In addition to the fattening upper tail of the markup distribution, there is reallocation of market share from low- to high-markup firms. This rise occurs mostly within industry. We also find an increase in the average profit rate from 1% to 8%. Although there is also an increase in overhead costs, the markup increase is in excess of overhead. We discuss the macroeconomic implications of an increase in average market power, which can account for a number of secular trends in the past four decades, most notably the declining labor and capital shares as well as the decrease in labor market dynamism.

We propose an approach to measuring the misallocation of production in a market that compares actual industry cost curves to undistorted (counterfactual ) supply curves. As compared to traditional, TFPR-based, misallocation measures, this approach leverages cost data, such that results are readily mapped to welfare metrics. As an application, we analyze global crude oil extraction and quantify the extent of misallocation therein, together with the proportion attributable to market power. From 1970 to 2014, we find substantial misallocation, in the order of US$744 billion, 14.1 percent to 21.9 percent of which is attributable to market power.

We investigate the role of dynamic production inputs and their associated adjustment costs in shaping the dispersion of static measures of capital misallocation within industries (and countries). Across nine data sets spanning 40 countries, we find that industries exhibiting greater time-series volatility of productivity have greater cross-sectional dispersion of the marginal revenue product of capital. We use a standard investment model with adjustment costs to show that variation in the volatility of productivity across these industries and economies can explain a large share (80–90 percent) of the cross-industry (and cross-country) variation in the dispersion of the marginal revenue product of capital.

status: Published