nep-ltv New Economics Papers
on Unemployment, Inequality and Poverty
Issue of 2009‒09‒19
five papers chosen by
Maximo Rossi
University of the Republic

  1. Moral Judgments in Social Dilemmas: How Bad is Free Riding? By Robin Cubitt; Michalis Drouvelis; Simon Gaechter; Ruslan Kabalin
  2. Rating scale analysis By Michael Glencross
  3. Decomposition of inequality change into pro-poor growth and mobility components: -dsginideco- By Stephen P. Jenkins; Philippe Van Kerm
  4. Caste and punishment : the legacy of caste culture in norm enforcement By Hoff, Karla; Kshetramade, Mayuresh; Fehr, Ernst
  5. Marry for What? Caste and Mate Selection in Modern India By Abhijit Banerjee; Esther Duflo; Maitreesh Ghatak; Jeanne Lafortune

  1. By: Robin Cubitt (University of Nottingham); Michalis Drouvelis (University of York); Simon Gaechter (University of Nottingham); Ruslan Kabalin (University of Nottingham)
    Abstract: In the last thirty years economists and other social scientists investigated people’s normative views on principles of distributive justice. Here we study people’s normative views in social dilemmas, which underlie many situations of economic and social significance. Using insights from moral philosophy and psychology we provide an analysis of the morality of free riding. We use experimental survey methods to investigate people’s moral judgments empirically. We vary others’ contributions, the framing (“give-some” vs. “take-some”) and whether contributions are simultaneous or sequential. We find that moral judgments depend strongly on others’ behaviour; and that failing to give is condemned more strongly than withdrawing all support.
    Keywords: moral judgments, framing effects, public goods experiments, free riding
    Date: 2009–08
  2. By: Michael Glencross (Community Agency for Social Enquiry, Johannesburg)
    Abstract: In many research studies, respondents' beliefs and opinions about various concepts are often measured by means of five, six and seven point scales. The widely used five point scale is commonly known as a Likert scale (Likert, (1932) "A technique for the measurement of attitudes", Archives of Psychology, 22, No. 140). In such situations, it is desirable to have a test statistic that provides a measure of the amount of agreement or disagreement in the sample, that is, whether or not a particular item 'pole' is characteristic of the respondents. This is preferable to making arbitrary decisions about the extremeness or otherwise of the sample responses. A suitable test for this purpose was designed by Cooper (1976), "An exact probability test for use with Likert-type scales, Educational and Psychological Measurement, 36, pp. 647-655. (Cooper z), with modifications suggested by Whitney (1978), "An alternative test for use with Likert-type scales", Educational and Psychological Measurement, 38, pp. 15-19 (Whitney t). Cooper showed that for large samples, the Cooper z statistic has a sample distribution that is approximately normal. The alternative Whitney t statistic has a sample distribution that is approximately t with (n-1) degrees of freedom and is suitable for small samples. Between them, these two statistics, although rarely used, provide a quick and straightforward way of analysing rating scales in an objective way. This presentation will describe the Stata syntax used to calculate the Cooper z and Whitney t statistics and create the related bar graphs. An illustrative example will be used to demonstrate their use in a survey.
    Date: 2009–09–16
  3. By: Stephen P. Jenkins (University of Essex); Philippe Van Kerm (CEPS/INSTEAD, Luxembourg)
    Abstract: This short talk describes the module -dsginideco- which decomposes the change in income inequality between two time periods into two components, one representing the progressivity (pro-poorness) of income growth, and the other representing reranking. Inequality is measured using the generalized Gini coefficient, also known as the S-Gini, G(v). This is a distributionally-sensitive inequality index, with larger values of v placing greater weight on inequality differences among poorer (lower ranked) observations. The conventional Gini coefficient corresponds to thecase v = 2. The decomposition is of the form: final-period inequality - initial-period inequality = R - P where R is a measure of reranking, and P is a measure of the progressivity of income growth. For full details of the decomposition and an application, see S.P. Jenkins and P. Van Kerm (2006), "Trends in income inequality, pro-poor income growth and income mobility", Oxford Economic Papers, 58(3): 531-548.
    Date: 2009–09–16
  4. By: Hoff, Karla; Kshetramade, Mayuresh; Fehr, Ernst
    Abstract: Well-functioning groups enforce social norms that restrain opportunism, but the social structure of a society may encourage or inhibit norm enforcement. This paper studies how the exogenous assignment to different positions in an extreme social hierarchy - the caste system - affects individuals'willingness to punish violations of a cooperation norm. Although the analysis controls for individual wealth, education, and political participation, low-caste individuals exhibit a much lower willingness to punish norm violations that hurt members of their own caste, suggesting a cultural difference across caste status in the concern for members of one’s own community. The lower willingness to punish may inhibit the low caste’s ability to sustain collective action and so may contribute to its economic vulnerability.
    Keywords: Gender and Social Development,Corruption&Anitcorruption Law,Anthropology,Access to Finance,Social Inclusion&Institutions
    Date: 2009–09–01
  5. By: Abhijit Banerjee; Esther Duflo; Maitreesh Ghatak; Jeanne Lafortune
    Abstract: This paper studies the role played by caste, education and other social and economicattributes in arranged marriages among middle-class Indians. We use a unique dataset on individuals who placed matrimonial advertisements in a major newspaper,the responses they received, how they ranked them, and the eventual matches. Weestimate the preferences for caste, education, beauty, and other attributes. We thencompute a set of stable matches, which we compare to the actual matches that weobserve in the data. We find the stable matches to be quite similar to the actualmatches, suggesting a relatively frictionless marriage market. One of our keyempirical findings is that there is a very strong preference for within-caste marriage.However, because both sides of the market share this preference and because thegroups are fairly homogeneous in terms of the distribution of other attributes, inequilibrium, the cost of wanting to marry within-caste is low. This allows caste toremain a persistent feature of the Indian marriage market
    Date: 2009–05

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