Getting Rich(er) in Office? Corruption and Wealth Accumulation in Congress

28 Pages Posted: 13 Aug 2009 Last revised: 7 Sep 2009

Gabriel S. Lenz

University of California, Berkeley - Charles and Louise Travers Department of Political Science

Kevin Lim

Massachusetts Institute of Technology (MIT)

Date Written: 2009

Abstract

How corrupt is Congress? We provide an indirect test by comparing wealth accumulation among U.S. House members and the public. Using wealth data from representatives’ Personal Financial Disclosure forms and from the Panel Study of Income Dynamics, we examine whether representatives accumulate wealth faster than expected. To do so, we first use difference-in-differences, least squares regression, and median regression estimators, conditioning on variables such as the value of households’ stock, cash, business, and land assets, their debts, and demographic variables. These estimators find representatives accumulating wealth about 50 percent faster than expected. Next, we employ matching. Unlike these estimators, matching finds an almost identical rate of wealth accumulation in both groups. Matching may yield such a different finding because it reduces bias from modeling errors. Since the distribution of wealth has a complex shape that is difficult to parameterize, such errors are likely. We thus conclude that representatives report accumulating wealth at a rate consistent with similar non-representatives, potentially suggesting that corruption in Congress is not widespread.

Suggested Citation

Lenz, Gabriel S. and Lim, Kevin, Getting Rich(er) in Office? Corruption and Wealth Accumulation in Congress (2009). APSA 2009 Toronto Meeting Paper. Available at SSRN: https://ssrn.com/abstract=1450077

Gabriel S. Lenz (Contact Author)

University of California, Berkeley - Charles and Louise Travers Department of Political Science ( email )

210 Barrows Hall
Berkeley, CA 94720
United States

HOME PAGE: http://polisci.berkeley.edu/people/faculty/person_detail.php?person=378

Kevin Lim

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

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