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. The Bureau primarily imputes for missing values using mean-imputation methods which can reduce the...

We build up from the plant level an “aggregate(d) Solow residual" by estimating every U.S. manufacturing plant's contribution to the change in aggregate final demand between 1976 and 1996. We decompose these contributions into plant-level resource reallocations and plant-level technical...

Within-industry differences in measured plant-level productivity are large. A large literature has been devoted to explaining the causes and consequences of these differences. In the U.S. Census Bureau's manufacturing data, the Bureau imputes for missing values using methods known to result in...

We build up from the plant level an "aggregate(d)" Solow residual by estimating every U.S. manufacturing plant's contribution to the change in aggregate final demand between 1976 and 1996. Our framework uses the Petrin and Levinsohn (2010) definition of aggregate productivity growth, which...

Data stewards seeking to provide access to large-scale social science data face a difficult challenge. They have to share data in ways that protect privacy and confidentiality, are informative for many analyses and purposes, and are relatively straightforward to use by data analysts. We present...