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.

This paper exploits policy discontinuities at U.S. state borders to examine the effect of R&D investments on innovative projects. We examine the Small Business Innovation Research (SBIR) State Match program, which offers noncompetitive grants to federally awarded SBIR Phase I projects that are eligible to compete for Phase II. Results from SBIR activity (2002–2010) indicate heterogeneous treatment effects. Notably, the positive differential effects are moderated by firms within the science and health fields and with less previous SBIR success. The State Match effectively stabilized Phase II trends in contrast to neighboring states that experienced greater declines from the concurrent recession.

Despite unprecedented vertical growth in large cities, the economics of skyscrapers remain understudied. We combine data on tall buildings with a panel of land prices covering 140 years to analyze the determinants of urban heights. We provide estimates of the land price elasticity of height, the height elasticity of construction cost, and the elasticity of substitution between land and capital for tall buildings. The land price elasticity of height increased substantially over time, and it is larger for commercial than for residential buildings, which suggests that the supply side helps to produce the typical segregation of urban land uses.

We document how imperfect information generates heterogeneous effects in information treatments with personalized high-frequency feedback and peer comparisons. In our field experiment in retail electricity, we find that high- and low-energy users symmetrically underestimate and overestimate their relative energy use pretreatment. Responses to personalized feedback, however, are asymmetric. Households that overestimate their relative use and low users both respond by consuming more. These boomerang effects provide evidence that peer-comparison information programs, even those coupled with normative comparisons, are not guaranteed to lead to increases in prosocial behavior.