TY - JOUR
T1 - Imputation in U.S. manufacturing data and its implications for productivity dispersion
AU - White, Kirk K.
AU - Reiter, Jerome P.
AU - Petrin, Amil
N1 - Funding Information:
National Science Foundation grant NSF SES 1131897.
PY - 2018/7/1
Y1 - 2018/7/1
N2 - 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.
AB - 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.
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U2 - 10.1162/rest_a_00678
DO - 10.1162/rest_a_00678
M3 - Article
AN - SCOPUS:85049799100
SN - 0034-6535
VL - 100
SP - 502
EP - 509
JO - Review of Economics and Statistics
JF - Review of Economics and Statistics
IS - 3
ER -