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Project Citation: 

Flaaen, Aaron, Kamal, Fariha, Lee, Eunhee, and Yi, Kei-Mu. Data and Code: Aggregation Bias in the Measurement of U.S. Global Value Chains. Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-05-13.

Project Description

Summary:  View help for Summary This paper analyzes aggregation bias in measuring global value chain (GVC) activity -- the bias arising when an entire industry is essentially treated as a single establishment -- by employing novel U.S. Census microdata. We find negative aggregation bias that has worsened between 2002 and 2012. Unlike with industry-level measures, we see little slowdown in GVC integration by U.S. manufacturers during this period. A decomposition reveals most of the increase in the bias is from within establishments with high export and import intensities. Such granular-level measures of GVC will provide further understanding into how economies adjust to increasingly prevalent shocks

Scope of Project

Subject Terms:  View help for Subject Terms international trade; supply chains
JEL Classification:  View help for JEL Classification
      F00 International Economics: General
      F14 Empirical Studies of Trade
Geographic Coverage:  View help for Geographic Coverage USA
Time Period(s):  View help for Time Period(s) 2002 – 2012
Universe:  View help for Universe U.S. Manufacturing Sector
Data Type(s):  View help for Data Type(s) administrative records data; census/enumeration data

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