Replication Data for: Global Competition, Local Unions, and Political Representation: Disentangling Mechanisms (doi:10.7910/DVN/OPXLWV)

View:

Part 1: Document Description
Part 2: Study Description
Part 5: Other Study-Related Materials
Entire Codebook

Replication Data for: Global Competition, Local Unions, and Political Representation: Disentangling Mechanisms

doi:10.7910/DVN/OPXLWV

Harvard Dataverse

2025-03-26

1

Stegmueller, Daniel; Becher, Michael, 2025, "Replication Data for: Global Competition, Local Unions, and Political Representation: Disentangling Mechanisms", https://doi.org/10.7910/DVN/OPXLWV, Harvard Dataverse, V1

Replication Data for: Global Competition, Local Unions, and Political Representation: Disentangling Mechanisms

doi:10.7910/DVN/OPXLWV

Stegmueller, Daniel (Duke University)

Becher, Michael (IE University)

Becher, Michael

Stegmueller, Daniel

Harvard Dataverse

Stegmueller, Daniel

Becher, Michael

Stegmueller, Daniel

2025-02-15

https://doi.org/10.7910/DVN/OPXLWV

Social Sciences, Democratic Representation, Trade, Labor Unions, Mediation

While recent scholarship has demonstrated multiple political effects of international trade, less attention has been paid to unbundling the mechanisms through which import competition affects democratic politics. One mechanism, in theory, works through labor unions as domestic countervailing powers shaping legislative responses on compensation and trade votes. We assess the relevance of unions as a mediating variable in the US Congress. For identification, we leverage two distinct sources of exogenous variation, one instrument for import exposure and another for unionization, and combine them in a semiparametric estimator. We find that (i) import competition lowers district-level unionization, (ii) weaker unions lead to less legislative support for compensating economic losers and less opposition to trade deregulation, and (iii) the union mechanism represents a large fraction of the overall effect of import exposure on legislative votes. The results help explain weak compensation and further trade liberalization in the face of rising global competition.

This dataset underwent an independent verification process, complying with the AJPS Verification Policy updated June 2023, which replicated the tables and figures in the primary article. For the supplementary materials, verification was performed solely for the successful execution of the code. The verification process was carried out by the Cornell Center for Social Sciences at Cornell University. <br></br> The associated article has been awarded the Open Materials Badge. Learn more about the Open Practice Badges from the <a href="https://www.cos.io/">Center for Open Science</a>. <br></br> <img src="https://socialsciences.cornell.edu/sites/default/files/2024-04/materials_large_color.png" alt="Open Materials Badge " width="60" height="60"> <br></br> Open Materials Badge <br></br> Replication materials.: Please see the included README.txt file for details on software requirements and how to run all code (batch / shell scripts are included).

Autor, David H., David Dorn, and Gordon H. Hanson. 2013. "The China syndrome: Local labor market effects of import competition in the United States." American Economic Review 103(6): 2121-2168. <br></br> Autor, David H, David Dorn, and Gordon H Hanson. 2015. “Untangling trade and technology: Evidence from local labour markets.” The Economic Journal 125(584): 621–646. <br></br> Becher, Michael, Daniel Stegmueller, and Konstantin Kaeppner. 2018. "Local Union Organization and Law Making in the US Congress." Journal of Politics 80(2): 39–554. <br></br> Bonica, Adam. 2014. “Mapping the Ideological Marketplace.” American Journal of Political Science, 58: 367-386. <br></br> Bureau of Labor Statistics. 2019. “Foreign Direct Investment (FDI) State-County Employment and Wage Estimates.” [dataset] U.S. Bureau of Labor Statistics and U.S. Bureau of Economic Analysis. Retrieved from: https://www.bls.gov/fdi/tables/ <br></br> Flood, Sarah, Miriam King, Renae Rodgers, Steven Ruggles, J. Robert Warren, Daniel Backman, Annie Chen, Grace Cooper, Stephanie Richards, Megan Schouweiler, and Michael Westberry. IPUMS CPS: Version 12.0 [dataset]. Minneapolis, MN: IPUMS, 2024. https://doi.org/10.18128/D030.V12.0 <br></br> Greenland, Andrew, John Lopresti, and Peter McHenry. 2019. "Import competition and internal migration." Review of Economics and Statistics 101(1): 44–59. <br></br> Kernell, Georgia. 2009. “Giving Order to Districts: Estimating Voter Distributions with National Election Returns.” Political Analysis 17(3): 215–35. <br></br> Lewis, Jeffrey B., Keith Poole, Howard Rosenthal, Adam Boche, Aaron Rudkin, and Luke Sonnet. 2024. Voteview: Congressional Roll-Call Votes Database. https://voteview.com/ <br></br> Manson, Steven, Jonathan Schroeder, David Van Riper, Katherine Knowles, Tracy Kugler, Finn Roberts, and Steven Ruggles. IPUMS National Historical Geographic Information System: Version 19.0 [dataset]. Minneapolis, MN: IPUMS. 2024. http://doi.org/10.18128/D050.V19.0 <br></br> Ruggles, Steven. Sarah Flood, Matthew Sobek, Daniel Backman, Annie Chen, Grace Cooper, Stephanie Richards, Renae Rodgers, and Megan Schouweiler. IPUMS USA: Version 15.0 [dataset]. Minneapolis, MN: IPUMS, 2024. https://doi.org/10.18128/D010.V15.0 <br></br> Rupasingha, Anil, Stephan J. Goetz, and David Freshwater, D. 2006 (with updates). The production of social capital in US counties. Journal of Socio-Economics, 35, 83-101. Data are available from Northeast Regional Center for Rural Development at the Pennsylvania State University, PA: https://nercrd.psu.edu/data-resources/county-level-measure-of-social-capital/ <br></br> More details on which variables relate to these sources are available in the codebook PDFs.

The <i>American Journal of Political Science</i> and the Cornell Center for Social Sciences are not responsible for the accuracy or quality of data uploaded within the <i>AJPS</i> Dataverse, for the use of those data, or for interpretations or conclusions based on their use.

Label:

CODE.zip

Text:

R code to replicate all tables and figures. Contains data sets [in Rdata format] as well as PDF codebooks.

application/zip

Label:

README.txt

Text:

Readme first! This file contains instructions on how to replicate all results reported in the paper. It also lists details of the exact computing environment used to create these results. Furthermore, it contains instructions on how to install the necessary software and libraries/packages. Finally, it contains an index of all files and a description of their function.

text/plain

Label:

TABLES.zip

Text:

[Optional] Rnw files to knit well-formatted latex tables from results in the Code folder

application/zip