Jan De Loecker

Product Differentiation, Multiproduct Firms, and Estimating the Impact of Trade Liberalization on Productivity

In this paper I analyze the productivity gains from trade liberalization in the Belgian textile industry. So far, empirical research has established a strong relationship between opening up to trade and productivity, relying almost entirely on deflated sales to proxy for output in the production function. The latter implies that the resulting productivity estimates still capture price and demand shocks which are most likely to be correlated with the change in the operating environment, which invalidate the evaluation of the welfare implications. In order to get at the true productivity gains I propose a simple methodology to estimate a production function controlling for unobserved prices by introducing an explicit demand system. I combine a unique data set containing matched plant-level and product-level information with detailed product-level quota protection information to recover estimates for productivity as well as parameters of the demand side (markups). I find that when correcting for unobserved prices and demand shocks, the estimated productivity gains from relaxing protection are only half (from 8 to only 4 percent) of those obtained with standard techniques.

Dynamic Inputs and Resource (Mis)Allocation

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.

Estimating Market Power: Evidence from the US Brewing Industry

While inferring markups from demand data is common practice, estimation relies on difficult-to-test assumptions, including a specific model of how firms compete. Alternatively, markups can be inferred from production data, again relying on a set of difficult-to-test assumptions, but a wholly different set, including the assumption that firms minimize costs using a variable input. Relying on data from the US brewing industry, we directly compare markup estimates from the two approaches. After implementing each approach for a broad set of assumptions and specifications, we find that both approaches provide similar and plausible markup estimates in most cases. The results illustrate how using the two strategies together can allow researchers to evaluate structural models and identify problematic assumptions.