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Implications on the Proposed Basic Income Reform

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A Feasible Basic Income Scheme for Germany

Part of the book series: Contributions to Economics ((CE))

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Abstract

This chapter covers the estimated effects of the basic income proposal in Germany. By comparing the observed labor supply of the year 2010 with the estimated labor supply values of each individual after the policy reform, it is possible to identify and quantify the fiscal effects of the reform as well as the impact on income distribution. The implications of the proposed NIT-scheme for Germany are analyzed using a micro-simulation algorithm to mirror the German tax-and-transfer system. The chapter starts by introducing and discussing the GSOEP database that is used for the analysis. As information on income of the currently unemployed is necessary to simulate alternatives, their expected wage rates are estimated using a Heckman sample selection model. The data is then used to estimate multinomial logit regression models for singles and couples. The chapter continues by presenting the second-order effects with respect to labor supply that were triggered by the reform. This also includes a discussion about the feasibility of the approach. Afterwards, the attention shifts to the reform’s impact on social indicators especially on income poverty and income inequality with regard to different types of households. It ends with critical remarks of this procedure as well as of the limits of this study.

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Notes

  1. 1.

    For more information on the GSOEP, see Wagner et al. (2007). Regarding general documentation, see Haisken-DeNew and Frick (2005) and http://www.diw.de/en/soep (June 2014).

  2. 2.

    During the course of the survey different instruments have been tested to support the personal interview such as pen-and-pencil personal interview of computer-assisted personal interview (Haisken-DeNew and Frick 2005, p. 157).

  3. 3.

    Individual-related transfers especially those related to social insurances are collected in the person questionnaire (e.g. unemployment pay, pension) while information on transfers related to the total income of the community of needs is obtained by the household questionnaire (unemployment pay II, social welfare, etc.).

  4. 4.

    Only every 5 years (wave 2002/2007) an additional wealth module is included in the survey. For a discussion about the related problem of item-non-responses, see Frick et al. (2007). Wave 2012 was not available at the time of conducting this analysis.

  5. 5.

    The GSOEP assigns each wave to a character starting with ‘a’ in 1984. Wave ‘bb’ (2011) was released in 2013.

  6. 6.

    This corresponds to the setting of the analyses in Chap. 4

  7. 7.

    All questionnaires are available at http://panel.gsoep.de/soepinfo2011 (June 2014) in German and English.

  8. 8.

    The term household in this context is used as being equal to a community of need (German: Bedarfsgemeinschaft).

  9. 9.

    The weighting methodology of the GSOEP is very complex and beyond the scope of this work. For more information see (Haisken-DeNew and Frick 2005, pp. 37–41; 153–186) and Pischner (2007).

  10. 10.

    https://www.destatis.de/EN/PressServices/Press/pr/2012/07/PE12_255_12411.html (June 2014).

  11. 11.

    Regarding the case of faked or fraudulent interviews in the GSOEP, see Schäfer et al. (2004).

  12. 12.

    For more information of the imputation of PUNR, see Frick et al. (2010).

  13. 13.

    See Grabka and Frick (2003) and Frick and Grabka (2007) for detailed information on the imputation of INR in the GSOEP.

  14. 14.

    The reference to a common budget supports the joint-budget-approach established in Chap. 5

  15. 15.

    Figures 6.1 and 6.2 represent household data. The data is weighted, but not corrected with regard to the number of household members. Hence, these figures display the observed gross respectively disposable income instead of the equivalent household income.

  16. 16.

    This distribution (without households with zero income) can be approximated by a log-normal distribution with \(\ln (\mu ) = 10.1399\) and \(\ln (\sigma ) = 0.901\).

  17. 17.

    Similar to Fig. 6.1, the distribution in Fig. 6.2 can be approximated by a log-normal distribution with \(\ln (\mu ) = 10.0756\) and \(\ln (\sigma ) = 0.5791\).

  18. 18.

    The Lorenz curve was originally applied to wealth distributions (Lorenz 1905). For detailed explanation, see Gastwirth (1971) and Allison (1978) among others.

  19. 19.

    Altering the value of TE in a reasonable range has no influence on the estimated parameters (van Soest 1995, p. 67; Steiner and Wrohlich 2008, p. 10).

  20. 20.

    In order to estimate the central probability equation \(P(y = 1\vert x) = G(\beta _{0} + x\beta )\), probit regressions use the features of the normal distribution as transforming function, so that \(G(z) = \Phi (z) =\int _{ -\infty }^{z}\phi (v)dv\) with \(\phi (z) = \left (2\pi \right )^{-\frac{1} {2} }e^{-\frac{z^{2}} {2} }\) (Wooldridge 2009, pp. 575f).

  21. 21.

    The inverse Mills ratio λ is defined as \(\lambda = \frac{\phi (\alpha )} {1-\Phi (\alpha )}\) with ϕ(α) being the standard normal density, \(\Phi (\alpha )\) the distribution function of the standard normal distribution, and \(\alpha = - \frac{X_{2}\beta _{2}} {(\sigma _{22})^{\frac{1} {2} }}\) (Heckman 1976, p. 478).

  22. 22.

    The OLS regression of the Heckman sample selection model is a Mincer income function (sometimes Mincer earnings function) where wage rates are explained by socio-cultural and -demographic input vectors following human capital theory. The logarithm of each wage rate is used to linearize the model. Assuming that each input factor x generates a constant and small return r for each additional unit/year, the observed wage rate ω ∗ can be approximated by \(\omega ^{{\ast}} =\omega _{0}e^{\sum r_{i}x_{i}}\) (Mincer 1958, 1974; Berndt 1991, pp. 150–192).

  23. 23.

    See Appendix D for descriptive statistics.

  24. 24.

    The McFadden R 2 (which belongs to the class of Pseudo R-squares) is defined as \(1 -\frac{lnL_{1}} {lnL_{0}}\) where L 0 represents the estimate likelihood of the model without predictors and L 1 the likelihood of the model that includes predictors (McFadden 1974, p. 121).

  25. 25.

    Regarding single-households, working time categories are ordered since category 1 (0 hours) involves lower working time respectively income than category 2 (1–40 hours) or 3 ( > 40 hours).

  26. 26.

    Hence, the second column of Tables 6.11 respectively 6.12 and the second column of Tables 6.13 and 6.14 are identical.

  27. 27.

    This refers to the annual costs of a reform and not so much to the costs of the administrative changing process.

  28. 28.

    An increase of the child allowance by 10 per month results in, given 14.5 million children that are entitled to child allowances as of 2010 (Data: Destatis, 2010) to an increase of transfer payments by 1.7 billion per year.

  29. 29.

    For more information on the reasons of non-availment of social transfers, see Riphahn (2001).

  30. 30.

    For a discussion about direct (using consumption) and indirect (using income) measures of poverty, see e.g. Ringen (1988) and Halleroed (1995).

  31. 31.

    The OECD uses multiple poverty lines (at 40/50/60 % median equivalent income). However, 60 % is commonly used to measure poverty in industrialized countries.

  32. 32.

    http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Glossary:Equivalised_income (April 2013).

  33. 33.

    Calculation: 1 (head of household) + 0.5 (partner) + 0.5 (child’s age ≥ 14) + 0.3 (child’s age ¡ 14) = 2.3.

  34. 34.

    The Foster-Greer-Thorbecke index is based on four axioms that are (i) the monotonicity axiom, (ii) the transfer axiom, (iii) the transfer sensitivity axiom, and (iv) the subgroup monotonicity axiom. The monotonicity axiom requires that the overall poverty measure increases if the income of a household below the poverty line is reduced ceteris paribus. The transfer axiom states that a pure transfer of income from one household to another that is both poorer and below the poverty line will decrease the applied poverty measure and vice versa. This axiom is specified further by the transfer sensitivity axiom. If money is redistributed between household below the poverty line, but from a richer to a poorer household, then the value of the poverty measure will obviously decrease. However, the axiom also states that the magnitude of decrease increases the lower the income of both households (the distance in income between the two is constant). Hence, a redistribution of money for households far away from the poverty line has a stronger impact on poverty than for those close to it. At last, the subgroup monotonicity axiom states that if the poverty of a subgroup of the total population changes while poverty measures of the remaining subgroups are constant, overall poverty changes in the same direction (Kakwani 1980; Foster et al. 1984, pp. 762–764). For a general overview of poverty axioms, see Bellú and Liberati (2005). A formal analysis of poverty measures and axioms is provided in Zheng (2002).

  35. 35.

    In a continuous notation the FGT-index is expressed as \(FGT_{\alpha } =\int _{ 0}^{z}\left [\left (1 -\frac{y} {z}\right )^{\alpha }f(y)dy\right ]\) where f(y) is the density function of the income (Atkinson 1987, pp. 754f).

  36. 36.

    For a detailed survey of studies using the FGT-index or even extending it, see Foster et al. (2010).

  37. 37.

    For a comparison of different income inequality measures, see e.g. (Faik 1995, pp. 312f).

  38. 38.

    Measures of income inequality are based on an axiom-system consisting of five axioms in general. First, the Principle of Anonymity states that only income and no other socio-economic characteristics are decisive for the order of different income distributions. Secondly, the Pigou-Dalton Transfer Principle constitutes that any transfer from the rich to the poor reduces the inequality measure and vice versa (see Pigou 1912/2012; Dalton 1920). Thirdly, Principle of Population states that the inequality measure is unchanged if the population is replicated with the same distribution. Fourthly, Decomposability indicates that any index should be decomposable to different subgroups and that the overall measure is related to changes in subgroups. At last, Income Scale Independence states that the inequality measure does not change if all individual incomes are altered with the same proportion. The measure is then invariant to uniform proportional changes. For detailed information on inequality measure axioms, see (Faik 1995, pp. 295–297) or (Hartmann 1985, pp. 78–86) among others.

  39. 39.

    This is closely related to the concept of constant relative risk aversion that is used in finance. See (Cuthbertson and Nitzsche 2004, pp. 14–19, 383–386) for more information on this topic.

  40. 40.

    See Sect. C.3 for the calculation of the constant relative inequality aversion.

  41. 41.

    In addition, the transfer-principle does not hold for negative values of ε (Hartmann 1985, p. 138).

  42. 42.

    For ε = 1, the Atkinson-index is sometimes expressed as \(A_{\epsilon =1} = 1 -\frac{1} {\mu } e^{\frac{\sum lny_{i}} {N} }\) (Hartmann 1985, p. 138).

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    Maximilian Sommer

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Sommer, M. (2016). Implications on the Proposed Basic Income Reform. In: A Feasible Basic Income Scheme for Germany. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-24064-0_6

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