Imputation in U.S. manufacturing data and its implications for productivity dispersion

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • White, KK; Reiter, JP; Petrin, A

Published Date

  • July 1, 2018

Published In

Volume / Issue

  • 100 / 3

Start / End Page

  • 502 - 509

Electronic International Standard Serial Number (EISSN)

  • 1530-9142

International Standard Serial Number (ISSN)

  • 0034-6535

Digital Object Identifier (DOI)

  • 10.1162/rest_a_00678

Citation Source

  • Scopus