IDEAS home Printed from https://ideas.repec.org/a/bla/ecinqu/v58y2020i4p1628-1642.html
   My bibliography  Save this article

Which Communities Complain To Policymakers? Evidence From Consumer Sentinel

Author

Listed:
  • Devesh Raval

Abstract

Consumer complaints provide a signal of the problems that different American communities face. I use a large database of millions of complaints to examine how per capita complaint rates vary across communities, as well as heterogeneity in who complains to different agencies and about different consumer protection issues. I find higher complaint rates in more heavily Black, more educated, higher income, older, and more urban communities and lower complaint rates in more heavily Hispanic and higher household size communities. The demographics of complaints are quite different for the Consumer Financial Protection Bureau, with much higher rates of complaints from Black and college educated areas compared to the Federal Trade Commission or Better Business Bureaus. I also find much higher rates of finance related complaints from Black communities across all reporting agencies. (JEL D18, H50, J10)

Suggested Citation

  • Devesh Raval, 2020. "Which Communities Complain To Policymakers? Evidence From Consumer Sentinel," Economic Inquiry, Western Economic Association International, vol. 58(4), pages 1628-1642, October.
    • Handle: RePEc:bla:ecinqu:v:58:y:2020:i:4:p:1628-1642
    DOI: 10.1111/ecin.12838
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ecin.12838
    Download Restriction: no
    File URL: https://libkey.io/10.1111/ecin.12838?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521586115.
    2. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643.
    3. Papke, Leslie E & Wooldridge, Jeffrey M, 1996. "Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 619-632, Nov.-Dec..
    4. Oster, Sharon, 1980. "The Determinants of Consumer Complaints," The Review of Economics and Statistics, MIT Press, vol. 62(4), pages 603-609, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dou, Yiwei & Hung, Mingyi & She, Guoman & Wang, Lynn Linghuan, 2024. "Learning from peers: Evidence from disclosure of consumer complaints," Journal of Accounting and Economics, Elsevier, vol. 77(2).
    2. H. Lim & J. C. Letkiewicz, 2023. "Consumer Experience of Mistreatment and Fraud in Financial Services: Implications from an Integrative Consumer Vulnerability Framework," Journal of Consumer Policy, Springer, vol. 46(2), pages 109-135, June.
    3. Andrew Sweeting & David J. Balan & Nicholas Kreisle & Matthew T. Panhans & Devesh Raval, 2020. "Economics at the FTC: Fertilizer, Consumer Complaints, and Private Label Cereal," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 57(4), pages 751-781, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rainer Winkelmann & Lin Xu, 2022. "Testing the binomial fixed effects logit model, with an application to female labour supply," Empirical Economics, Springer, vol. 62(2), pages 679-708, February.
    2. repec:spo:wpmain:info:hdl:2441/7182 is not listed on IDEAS
    3. Sebastian Weber, 2009. "European Financial Market Integration: A Closer Look at Government Bonds in Eurozone Countries," Working Paper / FINESS 1.1b, DIW Berlin, German Institute for Economic Research.
    4. Harding, Don & Pagan, Adrian, 2011. "An Econometric Analysis of Some Models for Constructed Binary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 86-95.
    5. Menzel, Konrad, 2014. "Consistent estimation with many moment inequalities," Journal of Econometrics, Elsevier, vol. 182(2), pages 329-350.
    6. Ural Marchand, Beyza, 2012. "Tariff pass-through and the distributional effects of trade liberalization," Journal of Development Economics, Elsevier, vol. 99(2), pages 265-281.
    7. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    8. Daniel Buncic, 2012. "Understanding forecast failure of ESTAR models of real exchange rates," Empirical Economics, Springer, vol. 43(1), pages 399-426, August.
    9. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    10. David Fairris & Gurleen Popli & Eduardo Zepeda, 2008. "Minimum Wages and the Wage Structure in Mexico," Review of Social Economy, Taylor & Francis Journals, vol. 66(2), pages 181-208.
    11. Javier Parada Gómez Urquiza & Alejandro López-Feldman, 2013. "Poverty dynamics in rural Mexico: What does the future hold?," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 55-74, November.
    12. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    13. Joseph G. Altonji & Rosa L. Matzkin, 2001. "Panel Data Estimators for Nonseparable Models with Endogenous Regressors," NBER Technical Working Papers 0267, National Bureau of Economic Research, Inc.
    14. Inanoglu, Hulusi & Jacobs, Michael, Jr. & Liu, Junrong & Sickles, Robin, 2015. "Analyzing Bank Efficiency: Are "Too-Big-to-Fail" Banks Efficient?," Working Papers 15-016, Rice University, Department of Economics.
    15. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Robert Breunig & Alison Stegman, 2005. "Testing For Regime Switching In Singaporean Business Cycles," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 50(01), pages 25-34.
    17. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    18. George Kapetanios, 2002. "Measuring Conditional Persistence in Time Series," Working Papers 474, Queen Mary University of London, School of Economics and Finance.
    19. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    20. Martins-Filho, Carlos & Yao, Feng & Torero, Maximo, 2018. "Nonparametric Estimation Of Conditional Value-At-Risk And Expected Shortfall Based On Extreme Value Theory," Econometric Theory, Cambridge University Press, vol. 34(1), pages 23-67, February.
    21. Théophile T. Azomahou & Jalal El Ouardighi & Phu Nguyen Van & Thi Kim Cuong Pham, 2006. "Estimation semi-paramétrique de la convergence des régions européennes," Economie & Prévision, La Documentation Française, vol. 0(2), pages 97-110.

    More about this item

    JEL classification:

    • D18 - Microeconomics - - Household Behavior - - - Consumer Protection
    • H50 - Public Economics - - National Government Expenditures and Related Policies - - - General
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:ecinqu:v:58:y:2020:i:4:p:1628-1642. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/weaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.