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An Ex-Post View of Inequality of Opportunity in France and its Regions

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Abstract

This paper proposes an ex-post measure of inequality of opportunity in France and its regions by assessing the inequality between individuals exerting the same effort. To this end, we define a fair income that fulfils ex-post equality of opportunity requirements. Unfairness is measured by an unfair Gini based on the distance between the actual income and the fair income. Our findings reveal that the measures of ex-post inequality of opportunity largely vary across regions, and that this is due to differences in reward schemes and in the impact of the non responsibility factors of income. We find that most regions have actual incomes closer to fair incomes than to average income, excepted Ile de France where the actual income looks poorly related to effort variables. Finally, we find that income inequality and inequality of opportunity are positively correlated among regions.

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Notes

  1. Obviously, this residual includes effort as well as circumstance variables and it is impossible to disentangle between both determinants. Like other papers that use earnings equations, we include the residual into the circumstance set (Almas et al. 2011; Bourguignon et al. 2007). We think this is also more appropriate in the context of our study because we study to which extent individuals who exert the same effort obtain the same outcome with a direct measure of effort.

  2. Bjorklund et al.’s decomposition is based on the following formulas:

    $$\begin {array}{rll} Var\left (\epsilon _{i}|X^{C}\right ) &=& \sigma _{c}^{2} \\ \epsilon _{i} &=& \epsilon _{i}-\epsilon _{i}/\sigma _{c}+\epsilon _{i}/\sigma _{c} \\ \epsilon _{i} &=& \tilde {\epsilon }^{c}_{i} + u_{i}\\ u_{i} &=& \epsilon _{i}/\sigma _{c} \\ log(y_{i}) &=& f\left (X^{E}_{i}, X^{C}_{i}\right )+ \tilde {\epsilon }^{c}_{i} + u_{i}\end {array}$$

    We find no significant effects in our data.

  3. All the categorical variables are binary in this research paper, since we transformed the multicategorial ones into dummy variables.

  4. The generalized proportionality allocation has been characterized as a compromise solution in the first best by Bossert (1995).

  5. The properties of the index are available in the paper by Almas et al. (2011). It is worth noting that while the Gini index satisfies full symmetry, the unfair Gini satisfies partial symmetry.

  6. This constraint could bias our result if job mobility is correlated with effort but the sign of the correlation is not clear. On the one hand, individuals, the youngest in particular often progress by changing jobs. On the other hand, those who exert less effort are more likely to change jobs in order to benefit from unemployment benefits and are more likely to lose their job. Therefore, to the extent that the sign of the bias is not clearly identifiable, we maintain this choice.

  7. The regression estimated to purge the effort variables from their correlation with circumstances is made on a national, instead of regional, basis due to data limitations.

  8. Results are not reported but available upon request.

  9. Changing the sector of reference does not change the empirical results.

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Correspondence to Jean-François Carpantier.

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The authors thank the participants of the FUSL CEREC seminar in Brussels and UAB workshop in Barcelona (project ECO2010-21668-C03-02, financed by the Ministry of Economy and Competitiveness), as well as Professors Xavier Ramos, Francisco Ferreira, Juan Gabriel Rodriguez and especially Dirk Van de Gaer for their helpful comments and suggestions. The usual disclaimers apply.

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Carpantier, JF., Sapata, C. An Ex-Post View of Inequality of Opportunity in France and its Regions. J Labor Res 34, 281–311 (2013). https://doi.org/10.1007/s12122-013-9161-5

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