I discuss reasons why manufacturing productivity statistics should be interpreted with caution in light of the recent growth of domestic and foreign outsourcing and offshoring. First, outsourcing and offshoring are poorly measured in U.S. statistics, and poor measurement may impart a significant bias to manufacturing and, where offshoring is involved, aggregate productivity statistics. Second, companies often outsource or offshore work to take advantage of cheap (relative to their output) labor, and such cost savings are counted as productivity gains, even in multifactor productivity calculations. This fact has potentially important implications for the interpretation of productivity statistics. Whether, for instance, productivity growth derives from a better-educated, more efficient U.S. workforce, from investment in capital equipment in U.S. establishments, or from the use of cheap foreign labor affects how productivity gains are distributed among workers and firms in the short term and undoubtedly matters for U.S. industrial competitiveness and living standards in the long term. Although it is impossible to fully assess the impact that mismeasurement and cost savings from outsourcing and offshoring have had on measured productivity growth in manufacturing, I point to several pieces of evidence that suggest it is significant, and I argue that these issues warrant serious attention. I am grateful to Katharine Abraham, Mike Harper, Peter Meyer, Anne Polivka, Ken Ryder, Larry Summers, Lisa Usher, Robert Yuskavage, and seminar participants at the Federal Reserve Bank– Chicago for comments on an earlier draft of this paper, and to Mary Streitweisser and James Franklin for supplying detailed information on the construction of BEA’s input-output estimates and their use in productivity calculations. Lillian Vesic-Petroic provided excellent research assistance. Any remaining errors as well as the views expressed in this piece are my own.