When information dominates comparison: Learning from Russian subjective panel data
Introduction
How does income distribution affect individual utility? In a seminal paper, Hirschman (1973) suggested that individuals could derive positive flows of utility from observing other people's faster progression if they interpret this evolution as a sign that their turn will come soon (for instance if the other lane of cars starts progressing towards the exit while their lane is still immobile during a traffic jam inside a tunnel). Dubbed the “tunnel effect” after the metaphor used by the author, this suggests that rising inequality may increase welfare, even for the poor, if it is interpreted as a positive signal with respect to likely future outcomes. This is at odds with the vision of Thurow (1971) who indicated that people may dislike inequality as such because they have quasi-aesthetic preferences for more equal distributions of wealth.
The same opposition exists regarding the interpretation of the income of one's reference group, which can be defined as the set of “relevant others” (e.g. peers, neighbors, colleagues, former schoolmates, etc.). On the one hand, the notion that utility is relative dates back to Veblen (1909) and Duesenberry (1949) and implies that individual utility depends on comparison to a reference level. This comparison effect has been documented empirically since then, e.g. van de Stadt et al., 1985, Clark and Oswald, 1996; a consequence is that reference group income should affect individual utility negatively. On the other hand, Hirschman's conjecture suggests that an individual can use the observation of his reference group's income as a source of information about his own perspectives (see also Levy-Garboua and Montmarquette, 2001), and hence derive positive utility from it. In summary, income distribution may affect subjective welfare in at least two ways: either as a direct argument in individual utility, or as a piece of information used to form expectations about future variables1. Our purpose is to try to disentangle these two aspects, focusing on the notion of the reference level of income. We analyze life satisfaction, using five rounds (1994–2000) of the representative household-level Russian longitudinal monitoring survey (RLMS). We concentrate on the longitudinal nature of the data in order to analyze intra-individual variations in satisfaction.
Our interpretation considers transition in Russia as a natural experiment characterized by an unusually high variance in absolute and relative incomes. Transition countries have effectively witnessed large movements in the distribution of wealth, income and labor market status, since the early 1990s, due to the transformation of the coordination system, the productive structure and relative prices in the economy. These evolutions have been associated with a high degree of uncertainty both at the individual level (employment and income perspectives) and at the aggregate level (macroeconomic and regulatory environment). Rising income inequality has been an important part of this evolution2. In the particular case of Russia, the presence of mineral and energy resources, and their privatization through the 1995 “loans for share” program, has led to a sharp increase in the income gap. Swings in macroeconomic policy have also hit the population's income, from the years of high inflation 1992–1995, through a period of monetary austerity and exchange rate stability, until the 1998 devaluation and the following resumption of growth (see Lokshin and Ravallion, 2000). Russia is thus an ideal case to test Hirschman's conjecture, as it enshrines all the necessary ingredients: uncertainty, growing inequality and prospects for development.
Ravallion and Lokshin (2000) have already advocated the presence of such a “tunnel effect” in Russia, based on the analysis of the demand for income redistribution in 1996. Analyzing the answers to the question “do you agree that the government should restrict the income of the rich?”, they show that individuals who agree are not necessarily those who are poorer, but rather those whose perspectives are more uncertain. This is consistent with the conjecture that it is not inequality per se that affects individual utility. We pursue the exploration of this issue, concentrating on the notion of the reference level of income. We show that in the very volatile Russian environment, individuals react favorably to a rise in their reference group's income, suggesting that the informational effect dominates the comparison effect.
As an illustration, consider the fate of the agriculture and government administration workers across five rounds of the RLMS (Table 1). It is striking that their individual satisfaction moves with the average income of their professional group rather than with their individual income.
The remainder of this paper explores this finding more systematically, i.e. controlling for the other determinants of life satisfaction. The next section presents the empirical strategy, while Section 3 discusses the results and Section 4 concludes.
Section snippets
Empirical strategy
We use rounds 5–9 of the RLMS representative household survey, running from December 1994 to October 20003. As the survey is based on a stratified sample of dwelling units, attrition is due to households or
Results
We first present the general socio-demographic correlates of life satisfaction, we then discuss the role of reference group income; lastly, we turn to the influence of inequality.
Conclusion
This study has revealed unusual findings. Although basic socio-demographic variables are correlated in a quite standard way with individual satisfaction, social comparison indicators are not. Reference group income exerts a positive influence on individual satisfaction, which contrasts with other studies on the subject. This is particularly true of categories of the population who experience high income volatility and feelings of uncertainty. Inequality indices do not seem to matter although
Acknowledgements
I thank Jean-Marc Robin for his precious advice, Pierre-Emmanuel Coralet and Marta Menendez for technical support, Jean-Oliver Harrault, Thomas Picketty and Andrew Clark for helpful comments. I am grateful to Klara Sabirianova, from the William Davidson Institute, who provided me with the data on industry codes. This paper has also benefited from the remarks of the participants at the 2002 European Economic Association Annual Congress, the 2002 CEPR/WDI Annual International Conference on
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