IDEAS home Printed from https://ideas.repec.org/p/uct/uconnp/2017-11.html
   My bibliography  Save this paper

Partisan Conflict and Income Distribution in the United States: A Nonparametric Causality-in-Quantiles Approach

Author

Listed:
  • Mehmet Balcilar

    (Eastern Mediterranean University)

  • Seyi Saint Akadiri

    (Montpellier Business School)

  • Rangan Gupta

    (University of Pretoria)

  • Stephen M. Miller

    (University of Nevada, Las Vegas)

Abstract

This study examines the predictive power of a partisan conflict index on income inequality. Our study adds to the existing literature by using the newly introduced nonparametric causality-in-quantile testing approach to examine how political polarization in the Unites States affects several measures of income inequality and distribution overtime. The study uses annual time-series data from 1917-2013. We find evidence of a causal relationship running from partisan conflict to income inequality, except at the upper end of the quantiles. The study suggests that a reduction in partisan conflict will lead to a more equal income distribution.

Suggested Citation

  • Mehmet Balcilar & Seyi Saint Akadiri & Rangan Gupta & Stephen M. Miller, 2017. "Partisan Conflict and Income Distribution in the United States: A Nonparametric Causality-in-Quantiles Approach," Working papers 2017-11, University of Connecticut, Department of Economics.
    • Handle: RePEc:uct:uconnp:2017-11
    Note: Stephen Miller is the corresponding author
    as

    Download full text from publisher

    File URL: https://media.economics.uconn.edu/working/2017-11.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Shinhye Chang & Rangan Gupta & Stephen M. Miller, 2018. "Causality Between Per Capita Real GDP and Income Inequality in the U.S.: Evidence from a Wavelet Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 269-289, January.
    2. Racine, Jeff & Li, Qi, 2004. "Nonparametric estimation of regression functions with both categorical and continuous data," Journal of Econometrics, Elsevier, vol. 119(1), pages 99-130, March.
    3. Azzimonti, Marina, 2018. "Partisan conflict and private investment," Journal of Monetary Economics, Elsevier, vol. 93(C), pages 114-131.
    4. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Fernández-Val, Iván, 2019. "Conditional quantile processes based on series or many regressors," Journal of Econometrics, Elsevier, vol. 213(1), pages 4-29.
    5. Marina Azzimonti-Renzo, 2014. "Partisan conflict," Working Papers 14-19, Federal Reserve Bank of Philadelphia.
    6. Periklis Gogas & Rangan Gupta & Stephen M. Miller & Theophilos Papadimitriou & Georgios Antonios Sarantitis, 2015. "Income Inequality: A State-by-State Complex Network Analysis," Working Papers 201534, University of Pretoria, Department of Economics.
    7. Andrew Gelman & Lane Kenworthy & Yu-Sung Su, 2010. "Income Inequality and Partisan Voting in the United States," Social Science Quarterly, Southwestern Social Science Association, vol. 91(s1), pages 1203-1219.
    8. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
    9. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    10. Brian Burgoon, 2013. "Inequality and anti-globalization backlash by political parties," European Union Politics, , vol. 14(3), pages 408-435, September.
    11. Jeong, Kiho & Härdle, Wolfgang K. & Song, Song, 2012. "A Consistent Nonparametric Test For Causality In Quantile," Econometric Theory, Cambridge University Press, vol. 28(4), pages 861-887, August.
    12. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    13. Alesina, Alberto & Drazen, Allan, 1991. "Why Are Stabilizations Delayed?," American Economic Review, American Economic Association, vol. 81(5), pages 1170-1188, December.
    14. Nishiyama, Yoshihiko & Hitomi, Kohtaro & Kawasaki, Yoshinori & Jeong, Kiho, 2011. "A consistent nonparametric test for nonlinear causality—Specification in time series regression," Journal of Econometrics, Elsevier, vol. 165(1), pages 112-127.
    15. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    16. Thomas Piketty & Emmanuel Saez, 2003. "Income Inequality in the United States, 1913–1998," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 1-41.
    17. Atkinson, A B, 1997. "Bringing Income Distribution in from the Cold," Economic Journal, Royal Economic Society, vol. 107(441), pages 297-321, March.
    18. Andrew Gelman & Lane Kenworthy & Yu‐Sung Su, 2010. "Income Inequality and Partisan Voting in the United States," Social Science Quarterly, Southwestern Social Science Association, vol. 91(5), pages 1203-1219, December.
    19. Claudia Goldin & Robert A. Margo, 1992. "The Great Compression: The Wage Structure in the United States at Mid-Century," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(1), pages 1-34.
    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. Cai, Yifei & Wu, Yanrui, 2019. "Time-varied causality between US partisan conflict shock and crude oil return," Energy Economics, Elsevier, vol. 84(C).
    2. Seyi Saint Akadiri & Ada Chigozie Akadiri, 2018. "Growth and Inequality in Africa: Reconsideration," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 4(3), pages 76-86, September.
    3. Christian Pierdzioch & Rangan Gupta & Hossein Hassani & Emmanuel Silva, 2018. "Forecasting Changes of Economic Inequality: A Boosting Approach," Working Papers 201868, University of Pretoria, Department of Economics.

    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. Mehmet Balcilar & Seyi Saint Akadiri & Rangan Gupta & Stephen M. Miller, 2019. "Partisan Conflict and Income Inequality in the United States: A Nonparametric Causality-in-Quantiles Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(1), pages 65-82, February.
    2. Bos, Martijn & Demirer, Riza & Gupta, Rangan & Tiwari, Aviral Kumar, 2018. "Oil returns and volatility: The role of mergers and acquisitions," Energy Economics, Elsevier, vol. 71(C), pages 62-69.
    3. Gupta, Rangan & Risse, Marian & Volkman, David A. & Wohar, Mark E., 2019. "The role of term spread and pattern changes in predicting stock returns and volatility of the United Kingdom: Evidence from a nonparametric causality-in-quantiles test using over 250 years of data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 391-405.
    4. Shahbaz, Muhammad & Balcilar, Mehmet & Abidin Ozdemir, Zeynel, 2017. "Does oil predict gold? A nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 52(C), pages 257-265.
    5. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "The role of time‐varying rare disaster risks in predicting bond returns and volatility," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 327-340, July.
    6. Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
    7. Ahdi Noomen Ajmi & Roula Inglesi-Lotz, 2021. "Revisiting the Kuznets Curve Hypothesis for Tunisia: Carbon Dioxide vs. Ecological Footprint," Working Papers 202171, University of Pretoria, Department of Economics.
    8. Mehmet Balcilar & Deven Bathia & Riza Demirer & Rangan Gupta, 2017. "Credit Ratings and Predictability of Stock Returns and Volatility of the BRICS and the PIIGS: Evidence from a Nonparametric Causality-in-Quantiles Approach," Working Papers 201719, University of Pretoria, Department of Economics.
    9. Jiang, Yong & Ren, Yi-Shuai & Ma, Chao-Qun & Liu, Jiang-Long & Sharp, Basil, 2020. "Does the price of strategic commodities respond to U.S. partisan conflict?," Resources Policy, Elsevier, vol. 66(C).
    10. Demirer, Riza & Gupta, Rangan & Suleman, Tahir & Wohar, Mark E., 2018. "Time-varying rare disaster risks, oil returns and volatility," Energy Economics, Elsevier, vol. 75(C), pages 239-248.
    11. Bahloul, Walid & Balcilar, Mehmet & Cunado, Juncal & Gupta, Rangan, 2018. "The role of economic and financial uncertainties in predicting commodity futures returns and volatility: Evidence from a nonparametric causality-in-quantiles test," Journal of Multinational Financial Management, Elsevier, vol. 45(C), pages 52-71.
    12. Yong Jiang & Yi-Shuai Ren & Chao-Qun Ma & Jiang-Long Liu & Basil Sharp, 2018. "Does the price of strategic commodities respond to U.S. Partisan Conflict?," Papers 1810.08396, arXiv.org, revised Feb 2020.
    13. Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018. "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers 201866, University of Pretoria, Department of Economics.
    14. Gupta, Rangan & Yoon, Seong-Min, 2018. "OPEC news and predictability of oil futures returns and volatility: Evidence from a nonparametric causality-in-quantiles approach," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 206-214.
    15. Maghyereh, Aktham & Abdoh, Hussein, 2020. "The tail dependence structure between investor sentiment and commodity markets," Resources Policy, Elsevier, vol. 68(C).
    16. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "Exchange rate returns and volatility: the role of time-varying rare disaster risks," The European Journal of Finance, Taylor & Francis Journals, vol. 25(2), pages 190-203, January.
    17. Bathia, Deven & Demirer, Riza & Ferrer, Román & Raheem, Ibrahim D., 2023. "Cross-border capital flows and information spillovers across the equity and currency markets in emerging economies," Journal of International Money and Finance, Elsevier, vol. 139(C).
    18. Massimiliano Caporin & Petre Caraiani & Oguzhan Cepni & Rangan Gupta, 2024. "Predicting the Conditional Distribution of US Stock Market Systemic Stress: The Role of Climate Risks," Working Papers 202407, University of Pretoria, Department of Economics.
    19. Riza Demirer & Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2020. "Effect of Rare Disaster Risks on Crude Oil: Evidence from El Nino from Over 140 Years of Data," Working Papers 2020104, University of Pretoria, Department of Economics.
    20. Demirer, Riza & Gabauer, David & Gupta, Rangan & Nielsen, Joshua, 2024. "Gold, platinum and the predictability of bubbles in global stock markets," Resources Policy, Elsevier, vol. 90(C).

    More about this item

    Keywords

    Partisan Conflict; Income Distribution; Quantile Causality;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:uct:uconnp:2017-11. 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: Mark McConnel (email available below). General contact details of provider: https://edirc.repec.org/data/deuctus.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.