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Bayesian Inference for Comparative Research

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  • Western, Bruce
  • Jackman, Simon

Abstract

Regression analysis in comparative research suffers from two distinct problems of statistical inference. First, because the data constitute all the available observations from a population, conventional inference based on the long-run behavior of a repeatable data mechanism is not appropriate. Second, the small and collinear data sets of comparative research yield imprecise estimates of the effects of explanatory variables. We describe a Bayesian approach to statistical inference that provides a unified solution to these two problems. This approach is illustrated in a comparative analysis of unionization.

Suggested Citation

  • Western, Bruce & Jackman, Simon, 1994. "Bayesian Inference for Comparative Research," American Political Science Review, Cambridge University Press, vol. 88(2), pages 412-423, June.
    • Handle: RePEc:cup:apsrev:v:88:y:1994:i:02:p:412-423_09
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    Cited by:

    1. José Alemán, 2008. "Labor Market Deregulation and Industrial Conflict in New Democracies: A Cross‐National Analysis," Political Studies, Political Studies Association, vol. 56(4), pages 830-856, December.
    2. Scott R. Eliason & Robin Stryker, 2009. "Goodness-of-Fit Tests and Descriptive Measures in Fuzzy-Set Analysis," Sociological Methods & Research, , vol. 38(1), pages 102-146, August.
    3. Theo S. Eicher & Chris Papageorgiou & Adrian E. Raftery, 2011. "Default priors and predictive performance in Bayesian model averaging, with application to growth determinants," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 30-55, January/F.
    4. Hix, Simon & Hoyland, Bjorn & Vivyan, Nick, 2007. "From doves to hawks: a spatial analysis of voting in the Monetary Policy Committee of the Bank of England, 1997-2007," LSE Research Online Documents on Economics 25199, London School of Economics and Political Science, LSE Library.
    5. Schneider, Jesper W., 2013. "Caveats for using statistical significance tests in research assessments," Journal of Informetrics, Elsevier, vol. 7(1), pages 50-62.
    6. Meseguer Yebra, Covadonga, 2000. "Learning and economic policy choices with an application to IMF agreements," ISER Working Paper Series 2000-02, Institute for Social and Economic Research.
    7. Benjamin T. Skinner, 2019. "Making the Connection: Broadband Access and Online Course Enrollment at Public Open Admissions Institutions," Research in Higher Education, Springer;Association for Institutional Research, vol. 60(7), pages 960-999, November.
    8. Germà Bel & Óscar Gasulla & Ferran A. Mazaira-Font, 2020. "The effect of health and economic costs on governments' policy responses to COVID-19 crisis, under incomplete information," IREA Working Papers 202008, University of Barcelona, Research Institute of Applied Economics, revised Jun 2020.
    9. Broscheid, Andreas & Gschwend, Thomas, 2003. "Augäpfel, Murmeltiere und Bayes: Zur Auswertung stochastischer Daten aus Vollerhebungen," MPIfG Working Paper 03/7, Max Planck Institute for the Study of Societies.
    10. Ameer Megahed & Brian Aldridge & James Lowe, 2019. "Comparative study on the efficacy of sodium hypochlorite, aqueous ozone, and peracetic acid in the elimination of Salmonella from cattle manure contaminated various surfaces supported by Bayesian anal," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-15, May.
    11. William Reed, 2003. "Information and Economic Interdependence," Journal of Conflict Resolution, Peace Science Society (International), vol. 47(1), pages 54-71, February.
    12. Ballinger, Clint, 2011. "Why inferential statistics are inappropriate for development studies and how the same data can be better used," MPRA Paper 29780, University Library of Munich, Germany.
    13. Cai, Zhen & Xie, Yi & Aguilar, Francisco X., 2017. "Eco-label credibility and retailer effects on green product purchasing intentions," Forest Policy and Economics, Elsevier, vol. 80(C), pages 200-208.
    14. Anastasia Dimiski, 2020. "Factors that affect Students’ performance in Science: An application using Gini-BMA methodology in PISA 2015 dataset," Working Papers 2004, University of Guelph, Department of Economics and Finance.
    15. Ilya Lokshin, 2015. "Whatever Explains Whatever: The Duhem-Quine Thesis And Conventional Quantitative Methods In Political Science," HSE Working papers WP BRP 23/PS/2015, National Research University Higher School of Economics.
    16. Andrew D. Martin, 2003. "Bayesian Inference for Heterogeneous Event Counts," Sociological Methods & Research, , vol. 32(1), pages 30-63, August.
    17. Xiaoyong Li & Giuseppe T. Cirella & Yali Wen & Yi Xie, 2020. "Farmers’ Intentions to Lease Forestland: Evidence from Rural China," Land, MDPI, vol. 9(3), pages 1-18, March.
    18. Meseguer, Covadonga, 2006. "Learning and economic policy choices," European Journal of Political Economy, Elsevier, vol. 22(1), pages 156-178, March.
    19. Engsted, Tom & Schneider, Jesper W., 2023. "Non-Experimental Data, Hypothesis Testing, and the Likelihood Principle: A Social Science Perspective," SocArXiv nztk8, Center for Open Science.

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