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Unifying the Study of Asymmetric Hypotheses

Published online by Cambridge University Press:  18 July 2017

Andrew S. Rosenberg ,
Austin J. Knuppe  and
Bear F. Braumoeller
Andrew S. Rosenberg*
Affiliation:
Department of Political Science, The Ohio State University, Columbus, USA. Email: rosenberg.1108@osu.edu
Austin J. Knuppe
Affiliation:
Department of Political Science, The Ohio State University, Columbus, USA. Email: rosenberg.1108@osu.edu
Bear F. Braumoeller
Affiliation:
Department of Political Science, The Ohio State University, Columbus, USA. Email: rosenberg.1108@osu.edu
*
*Email: rosenberg.1108@osu.edu
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Abstract

This article presents a conceptual clarification of asymmetric hypotheses and a discussion of methodologies available to test them. Despite the existence of a litany of theories that posit asymmetric hypotheses, most empirical studies fail to capture their core insight: boundaries separating zones of data from areas that lack data are substantively interesting. We discuss existing set-theoretic and large-N approaches to the study of asymmetric hypotheses, introduce new ones from the literatures on stochastic frontier and data envelopment analysis, evaluate their relative merits, and give three examples of how asymmetric hypotheses can be studied with this suite of tools.

Type
Articles
Information
Political Analysis , Volume 25 , Issue 3 , July 2017 , pp. 381 - 401
Copyright
Copyright © The Author(s) 2017. Published by Cambridge University Press on behalf of the Society for Political Methodology. 

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Footnotes

Authors’ note: The authors are grateful to Jose Fortou, Christopher Gelpi, Oul Han, Marcus Kurtz, Adam Lauretig, Richard McAlexander, William Minozzi, Anna Meyerrose, Jason Morgan, Adam Ramey, Gregory Smith, Avery White, and the participants in our panel at the 2015 American Political Science Association conference for feedback and comments on previous drafts. Replication materials are available at doi:10.7910/DVN/9NXGHP. These techniques are implemented in the open-source software asymmetric, which can be downloaded at https://github.com/asrosenberg/asymmetric-package. Further examples and resources can be found at https://www.asrosenberg.com/asymmetric-package/.

Contributing Editor: Jonathan N. Katz

References

Abbott, Andrew. 1988. Transcending general linear reality. Sociological Theory 6(2):169–186.Google Scholar
Aigner, Dennis, Knox Lovell, C. A., and Schmidt, Peter. 1977. Formulation and estimation of stochastic frontier production function models. Journal of Econometrics 6(1):21–37.Google Scholar
Almanidis, Pavlos, and Sickles, Robin C.. 2011. The skewness issue in stochastic frontiers models: Fact or fiction? In Exploring research frontiers in contemporary statistics and econometrics . Heidelberg: Springer, pp. 201–227.Google Scholar
Angrist, Joshua D., and Pischke, Jörn-Steffen. 2008. Mostly harmless econometrics: An Empiricist’s companion . Princeton, NJ: Princeton University Press.Google Scholar
Bergh, Andreas, and Nilsson, Therese. 2010. Good for Living? On the relationship between globalization and life expectancy. World Development 38(9):1191–1203.Google Scholar
Braumoeller, Bear F. 2015. Guarding against false positives in qualitative comparative analysis. Political Analysis 23(4):471–487.Google Scholar
Braumoeller, Bear F., and Goertz, Gary. 2000. The methodology of necessary conditions. American Journal of Political Science 44(4):844–858.Google Scholar
Bueno de Mesquita, Bruce. 1983. The war trap . New Haven, CT: Yale University Press.Google Scholar
Bueno de Mesquita, Bruce, Morrow, James D., Siverson, Randolph M., and Smith, Alastair. 1999. An institutional explanation of the democratic peace. American Political Science Review 93(4):791–807.Google Scholar
Charnes, Abraham, Cooper, William W., and Rhodes, Edwardo. 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2(6):429–444.Google Scholar
Clark, William Roberts, Gilligan, Michael J., and Golder, Matt. 2006. A simple multivariate test for asymmetric hypotheses. Political Analysis 14(3):311–331.Google Scholar
Daouia, Abdelaati, Noh, Hohsuk, and Park, Byeong U.. 2016. Data envelope fitting with constrained polynomial splines. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 78(1):3–30.Google Scholar
Daouia, Abdelaati, and Gijbels, Irène. 2011. Robustness and inference in nonparametric partial frontier modeling. Journal of Econometrics 161(2):147–165.Google Scholar
Daouia, Abdelaati, Florens, Jean-Pierre, and Simar, Léopold. 2012. Regularization of nonparametric frontier estimators. Journal of Econometrics 168(2):285–299.Google Scholar
Daouia, Abdelaati, Florens, Jean-Pierre, and Simar, Léopold. 2010. Frontier estimation and extreme value theory. Bernoulli 16(4):1039–1063.Google Scholar
Debreu, Gerard. 1951. The coefficient of resource utilization. Econometrica: Journal of the Econometric Society 19(3):273–292.Google Scholar
Dekkers, Arnold L. M., Einmahl, John H. J., and De Haan, Laurens. 1989. A moment estimator for the index of an extreme-value distribution. The Annals of Statistics 17(4):1833–1855.Google Scholar
Deprins, D., Simar, L., and Tulkens, H.. 1984. Measuring labor inefficiency in post offices. In The performance of public enterprises: Concepts and measurements , ed. Marchand, M., Pestieau, P., and Tulkens, H.. North-Holland, pp. 243–267.Google Scholar
Dion, Douglas. 1998. Evidence and inference in the comparative case study. Comparative Politics 30(2):127–145.Google Scholar
Dul, Jan. 2016. Necessary condition analysis (NCA) logic and methodology of “necessary but not sufficient” causality. Organizational Research Methods 19(1):10–52.Google Scholar
Duverger, Maurice. 1963. Political parties: Their organization and activity in the modern state . New York: Wiley.Google Scholar
Farrell, Michael James. 1957. The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General) 120(3):253–290.Google Scholar
Fenn, Paul, Vencappa, Dev, Diacon, Stephen, Klumpes, Paul, and O’Brien, Chris. 2008. Market structure and the efficiency of european insurance companies: A stochastic frontier analysis. Journal of Banking and Finance 32(1):86–100.Google Scholar
Gartzke, Erik. 1998. Kant We all just get along? Opportunity, willingness, and the origins of the democratic peace. American Journal of Political Science 42:1–27.Google Scholar
George, Alexander L., and Bennett, Andrew. 2005. Case studies and theory development in the social sciences . Boston, MA: MIT Press.Google Scholar
Gijbels, Irène, and Peng, L.. 2000. Estimation of a support curve via order statistics. Extremes 3(3):251–277.Google Scholar
Goertz, Gary, Hak, Tony, and Dul, Jan. 2013. Ceilings and floors where are there no observations? Sociological Methods and Research 42(1):3–40.Google Scholar
Greene, William H. 2008. The econometric approach to efficiency analysis. In The measurement of productive efficiency and productivity growth , ed. Fried, Harold O., Knox, C. A., Shelton, Lovell, and Schmidt, S.. New York: Oxford University Press, pp. 92–250.Google Scholar
Hall, Peter, and Park, Byeong U.. 2004. Bandwidth choice for local polynomial estimation of smooth boundaries. Journal of Multivariate Analysis 91(2):240–261.Google Scholar
Hall, Peter, Park, Byeong U., and Stern, Steven E.. 1998. On polynomial estimators of frontiers and boundaries. Journal of Multivariate Analysis 66(1):71–98.Google Scholar
Hall, Peter, and Simar, Léopold. 2002. Estimating a changepoint, boundary, or frontier in the presence of observation error. Journal of the American Statistical Association 97(458):523–534.Google Scholar
Hug, Simon. 2013. Qualitative comparative analysis: How inductive use and measurement error lead to problematic inference. Political Analysis 21(2):252–265.Google Scholar
Kaufman, Stuart J., Little, Richard, and Wohlforth, William C.. 2007. The balance of power in world history . New York, NY: Palgrave Macmillan.Google Scholar
Koenig-Archibugi, Mathias. 2004. Explaining government preferences for institutional change in EU foreign and security policy. International Organization 58(1):137–174.Google Scholar
Koenker, Roger. 2005. Quantile regression . New York, NY: Cambridge University Press.Google Scholar
Koopmans, Tjalling C. 1951. Efficient allocation of resources. Econometrica: Journal of the Econometric Society 19(4):455–465.Google Scholar
Krasner, Stephen D. 1983. International regimes . Ithaca, NY: Cornell University Press.Google Scholar
Krogslund, C., Choi, D. D., and Poertner, M.. 2015. Fuzzy sets on shaky ground: Parameter sensitivity and confirmation bias in fsQCA. Political Analysis 23(1):21–41.Google Scholar
Li, Yuhui, and Shugart, Matthew S.. 2016. The seat product model of the effective number of parties: A case for applied political science. Electoral Studies 41:23–34.Google Scholar
Lieberson, Stanley. 1985. Making it count: The improvement of social research and theory . Berkeley, CA: University of California Press.Google Scholar
Lijphart, Arend. 1990. The political consequences of electoral laws, 1945–85. American Political Science Review 84(02):481–496.Google Scholar
Lupia, Arthur, and McCubbins, Mathew D.. 1998. The democratic dilemma: Can citizens learn what they need to know? New York: Cambridge University Press.Google Scholar
Maoz, Zeev, and Russett, Bruce. 1993. Normative and structural causes of democratic peace, 1946–1986. American Political Science Review 87(3):624–638.Google Scholar
Meeusen, Wim, and Van Den Broeck, Julien. 1977. Efficiency estimation from Cobb–Douglas production functions with composed error. International Economic Review 18(2):435–444.Google Scholar
Mercer, Jonathan. 1996. Reputation and international politics . Ithaca, NY: Cornell University Press.Google Scholar
Moore, Barrington. 1966. Social origins of dictatorship and democracy: Lord and peasant in the making of the modern world . Boston: Beacon Press.Google Scholar
Morgan, Stephen L., and Winship, Christopher. 2014. Counterfactuals and causal inference . 2 ed. New York: Cambridge University Press.Google Scholar
Neto, Octavio Amorim, and Cox, Gary W.. 1997. Electoral institutions, cleavage structures, and the number of parties. American Journal of Political Science 41(2):149–174.Google Scholar
Noh, Hohsuk. 2014. Frontier estimation using kernel smoothing estimators with data transformation. Journal of the Korean Statistical Society 43(4):503–512.Google Scholar
Poitier, Kerry R. 2010. True efficient frontiers in production performance assessment using machine learning and data envelopment analysis . Miami, FL: University of Miami.Google Scholar
Poitier, Kerry, and Cho, Sohyung. 2011. Estimation of true efficient frontier of organisational performance using data envelopment analysis and support vector machine learning. International Journal of Information and Decision Sciences 3(2):148–172.Google Scholar
Ragin, Charles C. 1987. The comparative method: moving beyond qualitative and quantitative strategies . Berkeley, CA: University of California Press.Google Scholar
Ragin, Charles C. 2000. Fuzzy-set social science . Chicago, IL: University of Chicago Press.Google Scholar
Ragin, Charles C. 2008. Redesigning social inquiry: Fuzzy sets and beyond . Chicago, IL: University of Chicago Press.Google Scholar
Ray, Subhash C., Kumbhakar, Subal C., and Dua, Pami. 2015. Benchmarking for performance evaluation: A production frontier approach . New York, NY: Springer.Google Scholar
Richani, Nazih. 2013. Systems of violence: The political economy of war and peace in colombia . New York: Suny Press.Google Scholar
Rosenberg, Andrew S., Knuppe, Austin J., and Braumoeller, Bear F.. 2017. Replication data for: Unifying the study of asymmetric hypotheses. Harvard Dataverse. http://dx.doi.org/0.7910/DVN/9NXGHP.Google Scholar
Russett, Bruce. 1994. Grasping the democratic peace: Principles for a post-cold war world . Princeton, NJ: Princeton University Press.Google Scholar
Russett, Bruce, Layne, Christopher, Spiro, David E., and Doyle, Michael W.. 1995. Correspondance: The democratic peace. International Security 19(4):164–184.Google Scholar
Schimmelfennig, Frank. 2001. The community trap: Liberal norms, rhetorical action, and the eastern enlargement of the European union. International Organization 55(1):47–80.Google Scholar
Seawright, Jason. 2005. Assumptions, causal inference, and the goals of QCA. Studies in Comparative International Development 40(1):39–42.Google Scholar
Seawright, Jason. 2016. Multi-method social science: Combining qualitative and quantitative tools . New York, NY: Cambridge University Press.Google Scholar
Seiford, Lawrence M. 1996. Data envelopment analysis: The evolution of the state of the art (1978–1995). Journal of Productivity Analysis 7(2–3):99–137.Google Scholar
Simar, Léopold. 2007. How to improve the performances of DEA/FDH estimators in the presence of noise? Journal of Productivity Analysis 28(3):183–201.Google Scholar
Simar, Léopold, and Wilson, Paul W.. 2013. Estimation and inference in nonparametric frontier models: Recent developments and perspectives . Boston, MA: Now Publishers.Google Scholar
Simar, Léopold, and Zelenyuk, Valentin. 2011. Stochastic FDH/DEA estimators for frontier analysis. Journal of Productivity Analysis 36(1):1–20.Google Scholar
Taagepera, Rein, and Shugart, Matthew Soberg. 1993. Predicting the number of parties: A quantitative model of Duverger’s mechanical effect. American Political Science Review 87(2):455–464.Google Scholar
Talmadge, Caitlin. 2015. The Dictator’s army: Battlefield effectiveness in authoritarian regimes . Ithaca, NY: Cornell University Press.Google Scholar
Thiem, Alrik, Baumgartner, Michael, and Bol, Damien. 2016. Still lost in translation! A correction of three misunderstandings between configurational comparativists and regressional analysts. Comparative Political Studies 59:742–774.Google Scholar
Tsebelis, George. 1999. Veto players and law production in parliamentary democracies: An empirical analysis. American Political Science Review 93(03):591–608.Google Scholar
Whitehead, Laurence. 1981. Miners as voters: The electoral process in Bolivia’s mining camps. Journal of Latin American Studies 13(2):313–346.Google Scholar
Wimmer, Andreas. 2014. Nation building. A long-term perspective and global analysis. European Sociological Review 31(1):30–47.Google Scholar
Yu, Keming, and Moyeed, Rana A.. 2001. Bayesian quantile regression. Statistics and Probability Letters 54(4):437–447.Google Scholar