This paper proposes a technique for obtaining more precise estimates of demand and supply curves when one is constrained to market-level data. The technique allows one to augment market share data with information relating consumer demographics to the characteristics of the products they purchase. This extra information plays the same role as consumer-level data, allowing estimated substitution patterns and (thus) welfare to directly reflect demographic-driven differences in tastes for observed characteristics. I apply the technique to the automobile market, estimating the economic effects of the introduction of the minivan. I show that models estimated without micro data yield much larger welfare numbers than the model using them, primarily because the micro data appear to free the model from a heavy dependence on the idiosyncratic logit "taste" error. I complete the welfare picture by measuring the extent of first-mover advantage and profit cannibalization both initially by the innovator and later by the imitators. My results support a story in which large improvements in consumers' standard of living arise from competition as firms cannibalize each other's profits by seeking new goods that give them some temporary market power.

We add to the methods for conditioning out serially correlated unobserved shocks to the production technology. We build on ideas first developed in They show how to use investment to control for correlation between input levels and the unobserved firm-specific productivity process. We show that intermediate inputs (those inputs which are typically subtracted out in a value-added production function) can also solve this simultaneity problem. We discuss some theoretical benefits of extending the proxy choice set in this direction and our empirical results suggest these benefits can be important.

This paper examines direct broadcast satellites (DBS) as a competitor to cable. We first estimate a structural consumer level demand system for satellite, basic cable, premium cable and local antenna using micro data on almost 30000 households in 317 markets, including extensive controls for unobserved product quality and allowing the distribution of unobserved tastes to follow a fully flexible multivariate normal distribution. The estimated elasticity of expanded basic is about -15, with the demand for premium cable and DBS more elastic. The results identify strong correlations in the taste for different products not captured in conventional logit models. Estimates of the supply response of cable suggest that without DBS entry cable prices would be about 15 percent higher and cable quality would fall. We find a welfare gain of between $127 and $190 per year (aggregate $2.5 billion) for satellite buyers, and about $50 (aggregate $3 billion) for cable subscribers.

We propose a new measure of allocative efficiency based on unrealized increases in aggregate productivity growth. We show that the difference in the value of the marginal product of an input and its marginal cost at any plant—the plant-input gap—is exactly equal to the change in aggregate output that would occur if that plant changed that input's use by one unit. We show how to estimate this gap using plant-level data for 1982 to 1994 from Chilean manufacturing. We find the gaps for blue- and white-collar labor are quite large in absolute value, and these gaps (unlike for materials and electricity) are increasing over time. The timing of the sharpest increases in the labor gaps suggests that they may be related to increases in severance pay.

In the U.S. Census Bureau’s 2002 and 2007 Censuses of Manufactures, 79% and 73% of observations, respectively, have imputed data for at least one variable used to compute total factor productivity (TFP). The bureau primarily imputes for missing values using mean-imputation methods, which can reduce the underlying variance of the imputed variables. For five variables entering TFP, we show that dispersion is significantly smaller in the Census mean-imputed versus the nonimputed data. We use classification and regression trees (CART) to produce multiple imputations with observed data for similar plants. For 90% of the 473 industries in 2002 and 84% of the 471 industries in 2007, we find that TFP dispersion increases as we move from Census mean-imputed data to nonimputed data to the CART-imputed data.