Abstract
This paper is the first to analyze the impact of family background on permanent earnings based on sibling correlations in Germany and to provide a cross-country comparison of Germany, Denmark, and USA. The main findings are that family and community background has a stronger influence on permanent earnings in Germany than in Denmark, and a comparable influence is found in USA. This holds true for both male and female siblings. A deeper analysis of Germany shows that family background also plays an important role in explaining variations in family income, wages, education, and risk attitudes.
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Notes
In addition to parental income, these include parental education, parents’ social networks, but also parental attitudes and parenting styles.
Two examples would be the neighborhood and the quality of the available schools.
For details, see next section.
There is a discussion in the literature on whether the model should be estimated allowing for serial correlation of the transitory individual component. As gaps of different lengths in the series of yearly earnings observations are common especially in the survey data, I did not incorporate a serial correlations model. If serial correlation was a problem, the correlations presented in this paper would be downwardly biased. Björklund et al. (2002) showed that accounting for autocorrelated errors in the Danish data changed the brother correlation only slightly from 0.25 to 0.29. Mazumder (2008) argued that estimating the model allowing for serial correlation has no effect on his estimates for the USA. Nevertheless, if there were a problem with serial correlations, the corrected German estimates would be even higher than those presented in this paper. This would leave the main results unaffected.
Most authors have focused on brother pairs and sister pairs. Given the differences in labor market attachment between brothers and sisters, allowing for mixed sibling pairs would lead to estimates that depend heavily on how many brother–sister pairs are observed in each family.
Comi (2010) calculated sibling correlations in early career earnings for seven European countries including Germany. The results are not listed in Table 1 as they focus exclusively on early career outcomes and therefore cannot be seen as a proxy for equality of opportunity. Schnitzlein (2012) presented brother correlations in permanent earnings for different ethnic groups in Denmark. As the results in Table 1 do not distinguish between ethnic groups, these results are also not included. Björklund and Jäntti (2012) presented brother and sister correlations in earnings in Fig. 1 in their article. The results are very similar to the results in Björklund et al. (2002, 2004).
The corresponding brother correlation in income was 0.34.
See, for example, Corak (2006).
I used SOEP version SOEPv25.
See http://www.human.cornell.edu/pam/research/centers-programs/german-panel/cnef.cfm for an overview of the available data and Frick et al. (2007) for additional information.
In an earlier version of this article, I presented robustness tests including different alternative definitions on whom to count as siblings (Schnitzlein 2011). As the results remained virtually unchanged, I focus on this strict definition here.
Unfortunately, there is no English documentation available. An English description of the database can be found in Timmermans (2010).
I will provide a robustness test to show that the established international ranking is robust to variations in this restriction.
Note that women’s labor market participation rates clearly differ across countries. In 2010, 71.1 % of Danish women aged between 15 and 64 were employed. The corresponding rates were 66.1 % in Germany and 62.4 % in USA (OECD 2012). The women reporting positive earnings in my sample, therefore, might be a more homogeneous group in USA and Germany than in Denmark. To test the reliability of the results, estimates were made using family income instead of labor earnings for Germany (presented in Tables 5 and A.3). The observed pattern of estimates for women being lower than the estimates for brothers remains stable.
As stated in the note to Table 3, the average number of yearly individual earnings observations varies among the countries. In Denmark and Germany, the average numbers are very similar as follows: 4.5/4.8 years for brothers and 4.6/4.2 years for sisters. Due to the biannual rhythm of the PSID, the corresponding numbers for USA are 3.2 years. This difference can lead to downwardly biased estimates for USA (for a discussion, see Solon et al. 1991). While this supports the finding that there is a significant difference between Denmark and USA, it is unclear what would happen to the difference between Germany and the US. As a robustness check, I reestimated the model for the US using additional years from the CNEF data back to 1994. This specification contains 4.5 individual yearly earnings observations for US brothers and sisters. The sibling correlations in this specification remain largely unaffected (brothers 0.44/sisters 0.29). As I wanted to ensure that the data cover a comparable period in time in all three countries, I did not include the additional years in the main analysis. The full results from this specification are available from the author upon request.
Table A2 in the electronic appendix contains the associated number of observations, individuals, and families.
In an earlier version of this article, I presented additional robustness tests including different age restrictions. These can be found in Schnitzlein (2011).
The main difference between the samples in Tables 3 and 5 is not the inclusion or the exclusion of individuals with missing information for one of the outcomes, but the restriction that for each individual, only years with full information on all three outcomes were considered. Thus the biggest difference is found in the number of observations and not in the number of families or individuals. The results from an unbalanced panel can be found in Table A3 in the electronic appendix.
Included were all individuals that are at least 25 years of age. For each individual, the most recent level of education achieved was included. As there is no yearly variation on the level of the individual, the model was only estimated with two levels. Therefore, the number of observations and individuals is identical in Table 6 for education.
A similar result for USA is found by Mazumder (2008).
An overview of the literature on education and family background can be found in Björklund and Salvanes (2010).
Respondents are asked to answer the question Are you generally a person who is fully prepared to take risks or do you try to avoid taking risks? On an 11-point scale ranging from 0 (risk averse) to 10 (f ully prepared to take risks). This question has been included in the SOEP questionnaire in 2004, 2006, and 2008. See also discussion in Dohmen et al. (2011).
References
Becker GS, Tomes N (1979) An equilibrium theory of the distribution of income and intergenerational mobility. J Polit Econ 87(6):1153–1189
Becker GS, Tomes N (1986) Human capital and the rise and fall of families. J Labor Econ 4(3):1–39
Björklund A, Eriksson T, Jäntti M, Raaum O, Österbacka E (2002) Brother correlations in earnings in Denmark, Finland, Norway and Sweden compared to the United States. J Popul Econ 15(4):757– 772
Björklund A, Jäntti M (2009) Intergenerational income mobility and the role of family background. In: Nolan B, Smeeding TM (eds) Salverda W. Oxford handbook of economic inequality. Oxford University Press, New York, pp 491–521
Björklund A, Jäntti M (2012) How important is family background for labor-economic outcomes. Labour Econ 19(4):465–474
Björklund A, Jäntti M, Lindquist MJ (2007) Family background and income during the rise of the welfare state: brother correlations in income for Swedish men born 1932–1968. IZA Discussion Paper 3000, IZA Bonn
Björklund A, Jäntti M, Lindquist MJ (2009) Family background and income during the rise of the welfare state: brother correlations in income for Swedish men born 1932–1968. J Public Econ 93(5–6):671–680
Björklund A, Jäntti M, Raaum O, Österbacka E, Eriksson T (2004) Family structure and labor market success: the influence of siblings and birth order on the earnings of young adults in Norway, Finland, and Sweden. In: Corak M (ed)Generational mobility in North America and Europe. Cambridge University Press, Cambridge, pp 208–225
Björklund A, Lindahl L, Lindquist MJ (2010) What more than parental income, education and occupation? An exploration of what Swedish siblings get from their parents. BE J Econ Anal Policy (Contributions) 10:102
Björklund A, Salvanes KG (2010) Education and family background: mechanisms and policies. In: Hanushek EA, Machin S, Wößmann L (eds) Handbook in the economics of education, vol 3. North-Holland, Amsterdam, pp 201–247
Black SE, Devereux P (2011) Recent developments in intergenerational mobility. In: Ashenfelter O, Card D (eds) Handbook of labor economics, vol 4B. Elsevier, Amsterdam, pp 1487–1542
Comi SL (2010) Family influence on early career outcomes in seven European countries. Econ Bull 30(3):2054–2062
Corak M (2006) Do poor children become poor adults? Lessons from a cross-country comparison of generational earnings mobility. Res Econ Inequal 13(1):143–188
Couch KA, Dunn TA (1997) Intergenerational correlations in labor market status—a comparison of the United States and Germany. J Hum Resour 32(1):210–232
Dohmen T, Falk A, Huffman D, Sunde U, Schupp J, Wagner GG (2011) Individual risk attitudes: measurement, determinants and behavioral consequences. J Eur Econ Assoc 9(3):522–550
Dohmen T, Falk A, Huffman D, Sunde U (2012) The intergenerational transmission of risk and trust attitudes. Rev Econ Stud 79(2):645–677
Eisenhauer P, Pfeiffer F (2008) Assessing intergenerational earnings persistence among German workers. J Labour Mark Res 41(2&3):119–137
Eriksson T, Zhang Y (2012) The role of family background for earnings in rural China. Front Econ China 7(3):465–477
Frick JR, Jenkins SP, Lillard DR, Lipps O, Wooden M (2007) The cross-national equivalent file (CNEF) and its member country household panel studies. Schmollers Jahrb 127(4):627–654
Grawe ND (2004) Intergenerational mobility for whom? The experience of high- and low-earning sons in international perspective. In: Corak M (ed) Generational income mobility in North America and Europe. Cambridge University Press, Cambridge, pp 58–89
Haider S, Solon G (2006) Life-cycle variation in the association between current and lifetime earnings. Am Econ Rev 96(4):1308–1320
Hauser RM, Wong R (1989) Sibling resemblance and intersibling effects in educational attainment. Sociol Educ 62(3):149–171
Levine DI, Mazumder B (2007) The growing importance of family: evidence from brothers’ earnings. Ind Relat 46(1):7–21
Mazumder B (2008) Sibling similarities and economic inequality in the US. J Popul Econ 21(3):685–701
Mazumder B (2011) Family and community influences on health and socioeconomic status: sibling correlations over the life course. BE J Econ Anal Policy (Contributions) 11(3):1
OECD (2012) OECD Factbook 2011–2012: economic, environmental and social statistics. OECD Publishing
Österbacka E (2001) Family background and economic status in Finland. Scand J Econ 103(3):467–484
Schnitzlein DD (2009) Structure and extent of intergenerational mobility in Germany (Struktur und Ausmaß der intergenerationalen Einkommensmobilität in Deutschland). J Econ Stat (Jahrbücher für Nationalökonomie und Statistik) 229(4):450–466
Schnitzlein DD (2011) How important is the family? Evidence from sibling correlations in permanent earnings in the US, Germany and Denmark. SOEP papers 365, DIW Berlin
Schnitzlein DD (2012) How important is cultural background for the level of intergenerational mobility. Econ Lett 114(3):335–337
Sieben I, Huinink J, de Graaf PM (2001) Family background and sibling resemblance in educational attainment: trends in the former FRG , the former GDR and the Netherlands. Eur Sociol Rev 17(4):401–430
Solon G (1989) Biases in the estimation of intergenerational earnings correlations. Rev Econ Stat 71(1):172–174
Solon G (1992) Intergenerational income mobility in the United States. Am Econ Rev 82(3):393–408
Solon G (1999) Intergenerational mobility in the labor market. In: Ashenfelter O, Card D (eds) Handbook of labor economics, vol 3A. Elsevier, Amsterdam, pp 1761–1800
Solon G (2004) A model of intergenerational mobility variation over time and place. In: Corak M (ed) Generational income mobility in North America and Europe. Cambridge University Press, Cambridge, pp 38–47
Solon G, Corcoran M, Gordon R, Laren D (1991) A longitudinal analysis of sibling correlations in economic status. J Hum Resour 26(3):509–534
Timmermans B (2010) The Danish integrated database for labor market research: towards demystification for the English speaking audience. DRUID Working Paper 10–16, Danish Research Unit for Industrial Dynamics
Vogel T (2006) Reassessing intergenerational mobility in Germany and the United States: the impact of differences in lifecycle earnings patterns. SFB 649 Discussion Paper 2006–055, Humboldt University of Berlin
Wagner GG, Frick JR, Schupp J (2007) The German socio-economic panel study (SOEP): scope, evolution and enhancements. Schmollers Jahrb 127(1):139–169
Wiegand J (1997) Four essays on applied welfare measurement and income distribution dynamics in Germany 1985–1995. University College London, London
Yuksel M (2009) Intergenerational mobility of immigrants in Germany: moving with natives or stuck in their neighborhoods? IZA Discussion Paper 4677. IZA Bonn
Acknowledgments
I thank Regina T. Riphahn, Anders Björklund, Guido Heineck, Olaf Groh-Samberg, the editor, and two anonymous referees as well as conference and seminar participants in Perth (GB), Philadelphia, Nuremberg, Limerick, Borkop, Delmenhorst, Hangzhou, and Berlin for their helpful comments and suggestions. Part of this research was carried out during a research visit to the Aarhus School of Business. I am particularly grateful to Tor Eriksson for his helpful comments and valuable support during my stay. This project was part of a dissertation funded by the Institute for Employment Research (IAB) in Nuremberg, Germany
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Schnitzlein, D.D. How important is the family? Evidence from sibling correlations in permanent earnings in the USA, Germany, and Denmark. J Popul Econ 27, 69–89 (2014). https://doi.org/10.1007/s00148-013-0468-6
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DOI: https://doi.org/10.1007/s00148-013-0468-6