Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Measuring the Wellbeing of Groups Read chapter Read first chapter

2019 | OriginalPaper | Chapter

5. Comparing Latent Subgroups

Author : Gordon Anderson

Published in: Multilateral Wellbeing Comparison in a Many Dimensioned World

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Frequently, the groupings of interest in a society are not directly observed; they are latent and unknown in number. In this chapter, a technique for determining the number of groups and partially determining an agents’ group membership is explored. The determination is partial in the sense that only the probability of an individual’s membership of a group can be determined. The technique is based upon mixture distributions, for which a good reference is McLachlan and Peel (Finite Mixture Models. Wiley, New York, 2000). After outlining the nature of mixture distributions, estimation, calculation of the probability of class membership and determining the optimal number of classes are discussed. Ultimately, possibilities for examining the determinants of group membership are outlined.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Partial Orderings
next chapter Ambiguity, Comparability, Segmentation and All That
Footnotes
1
Examples of disputed boundaries are not hard to find; determining the poor has probably been the most contentious (e.g. Sen 1982; Foster 1998). Things are not different when the focus of the analysis is on the middle or rich class (Atkinson and Brandolini 2013; Banerjee and Duflo 2008; Easterly 2001; Saez and Veall 2005). The most recent disputation as to the value of this type of classification argues that “wellness” is in general a many dimensioned concept so that income of itself is but a reflection of societal wellness (Stiglitz et al. 2010). Sen and others (e.g. papers in Grusky and Kanbur, 2006; Kakwani and Silber 2008; Nussbaum, 1997 2011; Alkire and Foster 2011) have forcibly argued that limitations to individual’s functionings and capabilities should be considered the determining factors in her/his poorness or wellness, again implying that an individual’s income will only partially reflect her/his poverty status.
 
2
Indeed, this is generally assumed in practice in elementary wellbeing measurement.
 
3
The law is basically a central limit theorem (see Chap.​ 2) using the idea that averages of things will be normally distributed in the limit.
 
Literature
Akaike, H. (1972). Information Theory and an Extension of the Maximum Likelihood Principle. Proceedings of the 2nd International Symposium on Information Theory to Problems of Control and Information Theory, Budapest, 267–281.
Alkire, S., & Foster, J. E. (2011). Counting and Multidimensional Poverty Measurement. Journal of Public Economics, 95, 476–487.CrossRef
Anderson, G. J., Crawford, I., & Leicester, A. (2011). Welfare Rankings From Multivariate Data, a Nonparametric Approach. Journal of Public Economics, 95, 247–252.CrossRef
Anderson, G., Linton, O., & Whang, Y.-J. (2012). Nonparametric estimation and inference about the overlap of two distributions. Journal of Econometrics, 171(1), 1–23.CrossRef
Anderson, G., Linton, O., & Thomas, J. (2017). Similarity, Dissimilarity and Exceptionality: Generalizing Gini’s Transvariation to Measure ‘Differentness’ in Many Distributions. Metron, 75, 161–180.CrossRef
Anderson, G. J., Farcomeni, A., Pittau, M. G., & Zelli, R. (2016). A New Approach to Measuring and Studying the Characteristics of Class Membership: Examining Poverty, Inequality and Polarization in Urban China. Journal of Econometrics, 191(2), 348–359.CrossRef
Andrews, R. A., & Currim, I. S. (2003). A Comparison of Segment Retention Criteria for Finite Mixture Logit’s Models. Journal of Marketing Research, XL, 235–243.CrossRef
Atkinson, A. B., & Brandolini, A. (2013). On the Identification of the Middle Class. In J. C. Gornick & M. Jaantti (Eds.), Income Inequality (pp. 77–100). Stanford: Stanford University Press.CrossRef
Banerjee, A. V., & Duflo, E. (2008). What is middle class about the middle classes around the world? Journal of Economic Perspectives, 22(2), 3–28.
Battistin, E., Blundell, R., & Lewbel, A. (2009). Why Is Consumption More LogNormal Than Income? Gibrat’s Law Revisited. Journal of Political Economy, 117(6), 1140–1154.CrossRef
Blundell, R., & Preston, I. (1998). Consumption Inequality and Income Uncertainty. The Quarterly Journal of Economics, 113(2), 603–640.CrossRef
Browning, M., & Lusardi, A. (1996). Household Saving: Micro Theories and Micro Facts. Journal of Economic Literature, 34(4), 1797–1855.
Chen, X., Hong, H., & Nekipelov, D. (2011). Nonlinear Models of Measurement Errors. Journal of Economic Literature, 49, 901–937.CrossRef
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum Likelihood from Incomplete Data via EM Algorithm. Journal of the Royal Statistical Society, B, 69, 1–38.
Eckstein, Z., & Wolpin, K. (1990). Estimating a Market Equilibrium Search Model from Panel Data on Individuals. Econometrica, 58, 783–808.CrossRef
Easterly, W. (2001). The Middle Class Consensus and Economic Development. Journal of Economic Growth, 6(4), 317–335.CrossRef
Foster, J. (1998). Absolute Versus Relative Poverty. The American Economic Review, 88(2), 335–341.
Friedman, M. (1957). A Theory of the Consumption Function. Princeton: Princeton University Press.
Gabaix, X. (1999). Zipf’s Law for Cities an Explanation. Quarterly Journal of Economics, 111, 739–767.CrossRef
Gibrat, R. (1931). Les Inegalites Economiques. Paris: Librairie du Recueil Sirey.
Gini, C. (1916). Il Concetto di Transvariazione e le sue Prime Applicazioni. In C. Gini (Ed.), Transvariazione. Libreria Goliardica (pp. 1–55).
Grusky, D. B., & Kanbur, R. (2006). Poverty and Inequality: Studies in Social Inequality. Stanford: Stanford University Press.
Hall, R. E. (1978). Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence. Journal of Political Economy, 86(6), 971–987.CrossRef
Kaufman, L., & Rousseeuw, P. J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis. New York: Wiley.CrossRef
Keane, M., & Wolpin, K. (1997). The Career Decisions of Young Men. Journal of Political Economy, 105, 473–522.CrossRef
Keribin, S. (2000). Consistent Estimation of the Order of Mixture Model. Sankhya, 62, 49–66.
Kakwani, N., & Silber, J. (2008). Quantitative Approaches to Multidimensional Poverty Measurement. London: Palgrave Macmillan.CrossRef
Kim, C. J., & Nelson, C. (1999). State-Space Models with Regime-Switching: Classical and Gibbs-Sampling Approaches with Applications. Cambridge: MIT Press.
Leroux, B. G. (1992). Maximum Likelihood Estimation for Hidden Markov Models. Stochastic Processes and their Applications, 40, 127–143.CrossRef
Lewbel, A. (2007). Estimation of Average Treatment Effects with Misclassification. Econometrica, 75, 537–551.CrossRef
Marron, J. S., & Wand, M. P. (1992). Exact Mean Integrated Squarred Error. Annals of Statistics, 20, 712–736.CrossRef
Modigliani, F., & Brumberg, R. (1954). Utility Analysis and the Consumption Function: An Interpretation of Cross Section Data. In K. K. Kurihara (Ed.), Post Keynesian Economics (pp. 388–436). London: Routledge.
Nussbaum, M. C. (1997). Capabilities and Human Rights. Fordham Law Review, 66, 273–300.
Nussbaum, M. C. (2011). Creating Capabilities: The Human Development Approach. Cambridge, MA: Harvard University Press.CrossRef
Reed, W. J. (2001). The Pareto, Zipf and Other Power Laws. Economics Letters, 74, 15–19.CrossRef
Rossi, P. E. (2014). Bayesian Non and Semi-Parametric Methods and Applications. Princeton/Oxford: Princeton University Press.
Saez, E., & Veall, M. R. (2005). The Evolution of High Incomes in Northern America: Lessons from Canadian evidence. American Economic Review, 95(3), 831–849.CrossRef
Sen, A. (1982). Choice, Welfare and Measurement. Cambridge, MA: MIT Press.
Stiglitz, J. E., Sen A., & J.P. Fitoussi (2010). Mis-measuring Our Lives: Why GDP Doesn’t Add Up. The Report of the Commission on the Measurement of Economic Performance and Social Progress. New York/London: The New Press
Sutton, J. (1997). Gibrat’s Legacy. Journal of Economic Literature, 35(1), 40–59.
Metadata
Title
Comparing Latent Subgroups
Author
Gordon Anderson
Copyright Year
2019
Book
Multilateral Wellbeing Comparison in a Many Dimensioned World

Print ISBN: 978-3-030-21129-5

Electronic ISBN: 978-3-030-21130-1

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-21130-1_5

Premium Partner

    Image Credits