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\title{The Intergenerational Dynamics of Social Inequality-Empirical Evidence from Europe and the United States}
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             \author[1]{Veronika V.  Eberharter}

             \affil[1]{  University of Innsbruck}

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\date{\small \em Received: 6 December 2013 Accepted: 1 January 2014 Published: 15 January 2014}

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\begin{abstract}
        


Based on nationally representative data from the German Socio-Economic Panel (SOEP), the Panel Study of Income Dynamics (PSID), and the British Household Panel Survey (BHPS) we analyze the intergenerational transmission of economic and social (dis-)advantages in Germany, the United States and Great Britain. We test with the hypotheses that the extent and the determinants of intergenerational income mobility and the relative risk of poverty differ with respect to the existing welfare state regime, family role patterns, and social policy design. The empirical results indicate a higher intergenerational income elasticity in the United States than in Germany and Great Britain, and country differences concerning the influence of individual and parental socio-economic characteristics, and social exclusion attributes on intergenerational income mobility and the relative risk of poverty.

\end{abstract}


\keywords{social and economic inequality; intergenerational income mobility; poverty, social exclusion.}

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\section[{Introduction}]{Introduction}\par
ost of the industrialized countries are confronted by changing social and economic structure, increasing economic and social inequalities, low income and social isolation. The negative relation between income inequality and intergenerational income mobility suggests that children growing up in lowincome households can only escape the poverty trap if intergenerational income mobility compensates economic and social inequality \hyperref[b56]{(Mayer and Lopoo 2005)}. From the socio-political point of view, the research of the determinants of intergenerational income mobility and poverty persistence is essential to design effective social policy measures. Though focused on alleviating social and economic inequalities, the social policy of a country reproduces "stratification" in terms of power, class and other forms of inequality. The policy instruments and transfer packages tell a great deal about the working of a country's welfare state regime. The welfare state regime defines a complex of legal and organizational properties, the role of the state interacting alongside the market, the civil society, and the family in the provision of welfare \hyperref[b75]{(Therborn 1995}\hyperref[b20]{, de Swaan 1988}\hyperref[b2]{, Arts and Gelissen 2002)}. The existing topologies of welfare state regimes are based on various dimensions, as social insurance and poverty policy \hyperref[b49]{(Leibfried 1992}, Korpi and Palme 1998), welfare expenditures, benefit equality, and taxes \hyperref[b14]{(Castles and Mitchell 1993}\hyperref[b11]{, Bonoli 1997} {\ref , Kauto 2002)}, female work desirability \hyperref[b69]{(Siaroff 1994)}, political tradition \hyperref[b62]{(Navarro and Shi 2001)}, or decommodification and stratification (Esping-Andersen 1990, Esping-Andersen 1994, Esping-Andersen 1999).\par
The Esping-Anderson welfare state regime typology clusters democratic industrial societies into liberal, conservative, and social democratic welfare state regimes. The liberal welfare state regime (United States, Great Britain, Canada, Australia, New Zealand) is characterized by low decommodification and strong individualistic self-reliance. The public philosophy is grounded on the idea of opportunity reflecting individual efforts, which indicates an open, liberal and dynamic social system. The distributional consequences of the market forces are accepted. A relatively unregulated labor market fosters the creation of low-paid jobs, large wage dispersions, and small differences in the jobs performed by women and men. Labor market policies offer less protection for workers and do little to ameliorate market-based risks. The market rather than the state is promoted in guaranteeing the welfare needs of the citizens. These countries are characterized in terms of minimal assistance to allow the worker the opportunity to gain entry back into the market should circumstances dictate a temporary departure. The state reacts only in case of social failures and limits the help to special groups. The transfers are modest and the rules for entitlement are very strict. The principle of stratification leads to low-income state dependents, and people not able to afford social insurance plans. The education systems are less stratified and standardized which may induce a higher social mobility. At the other hand, privately financed higher education suggests intergenerational social immobility  {\ref (} The conservative-corporatist welfare state regime (Germany, Austria, France, Italy) is typified by a modest level of decommodification. Government policies ensure against market-based risks and protect those who are unable to succeed in the market place.\par
The direct influence of the state is restricted to the provision of income maintenance benefits. The labor market institutions and labor market policies ensure employment stability. Health care, welfare, social insurance, national assistance, and old age pensions are provided at government expense. Social policy is designed to guarantee income equality. Family policies facilitate the incorporation of women into the labor force (e.g. child care, paid maternity leave, job return guarantees) and support the transition from the traditional male bread-winner model to the adult worker model. At the other hand tax policy (e.g. tax splitting) favor men as breadwinner and women foremost as mothers, which reinforce the preservation of traditional family role patterns concerning the allocation of time into paid work \hyperref[b16]{(Charles et al. 2001}\hyperref[b52]{, Lewis 2006}). The education system is formal and coordinated, and higher education is publicly provided. In Germany, the vocation-oriented educational "dual system" relies on occupation-specific credentials, and results in socially stratified and sex segregated outcomes. The federal states have the primary responsibility for organizing the educational system, which results in a high level of standardization, and constitutes the mechanisms for perpetuating social inequalities \hyperref[b61]{(Mortimer and} {\ref Krüger 2000, OECD 2012)}.\par
The social democratic approach to welfare and social policy (Scandinavian countries) is especially committed to create equal opportunity, to reduce social risks, and to diminish social divisions. The level of decommodification is high, and stratification is directed to achieve a system of highly distributive benefits. These countries advocate full employment and promote equality including the provision of a safety net that no one should be allowed to fall through. Social policy aims at maximizing the capacities of individual independence. Women are encouraged to participate in the labor market.\par
The paper aims to analyze the influence of the individual and parental socio-economic mapping, and social exclusion characteristics on the intergenerational income mobility and the relative risk of poverty in countries with different welfare state regimes, labor market institutions, family role patterns, and social policy design. The paper focuses on the situation in Germany, the United States, and Great Britain. We test the hypotheses that the link between social stratification, intergenerational income mobility, and poverty persistence works differently according to the existing welfare state regime, family role patterns, and the social policy: -In the United States and Great Britain we expect a higher income inequality which is associated with lower intergenerational income mobility than in Germany. Due to high individualism and selfrelience in the society we expect that the impact of -In Germany, social policy is designed to focusing on a higher social permeability of the society. We expect a higher intergenerational income mobility at the bottom of the income distribution compared to the United States and Great Britain. -In all the countries, we suppose that instable family structures, non-employment, and disability boost the relative risk of poverty.\par
To analyze the determinants of the intergenerational income mobility we employ a regression approach on the permanent postgovernment income variables of children and parents including a set of individual and family background controls \hyperref[b71]{(Solon 1999}\hyperref[b9]{, Björklund and Jäntti 2000}\hyperref[b43]{, Hertz 2004}\hyperref[b19]{, Couch and Lillard 2004}\hyperref[b38]{, Grawe 2004}). We apply quintile transition matrices and the Bartholomew mobility index (Bartholomew 1982, \hyperref[b21]{Dearden et al. 1997}) to evaluate the intergenerational mobility for different income positions. To analyze the determinants of the relative poverty risk we employ a binomial logit model  {\ref (Mc Fadden 1973}\hyperref[b53]{, Maddala 1983}\hyperref[b41]{, Heckman 1981}). The explanatory variables contain a set of individual and family background socio-economic resources, and social exclusion attributes.\par
The paper is organized in 5 sections: section 2 focuses on the theoretical background of the intergenerational transmission of social and economic disadvantages, section 3 reports the data and sample organization, section 4 outlines the methodology to analyze the intergenerational income mobility and the relative risk of poverty conditional to individual and family background characteristics, and social exclusion attributes. Section 5 presents the empirical results and section 6 concludes with a summary of findings and discussion of some stylized facts about the intergenerational heritage of economic and social disadvantages to derive policy implications and directions for further research. 
\section[{II.}]{II.} 
\section[{Theoretical Background}]{Theoretical Background}\par
Poverty and social exclusion are dynamic processes limiting a person's future prospects \hyperref[b4]{(Atkinson 1998)}. Social exclusion is a multi-dimensional phenomenon, affecting both the quality of life of individuals and the equity and cohesion of society as a whole \hyperref[b51]{(Levitas et al. 2007}). It reflects a combination of inter-related factors resulting from a lack of capabilities \hyperref[b66]{(Sen 1985}\hyperref[b67]{, Sen 1992)}   \hyperref[b76]{(Townsend 1979} {\ref , United Nations 1995}\hyperref[b22]{, Duffy 1995} {\ref , Walker and Walker 1997}\hyperref[b13]{, Burchard et al. 2002)} or the inability to do things, that are in some sense considered normal by the society as a whole \hyperref[b44]{(Howarth et al. 1998)}, or the insufficiency of different attributes of well-being (e.g. housing, literacy, health, provision of public good, income, etc.), then both the concepts become very close \hyperref[b12]{(Bourguignon and Chakravarty 2003)}.\par
There are two major theories concerning the mechanisms of the intergenerational transmission of advantages and disadvantages. According to the family resource model it is not a lack of economic resources, but other characteristics of the parents that are correlated with economic status that influence the parental abilities to provide stimulating environments for their children to have economic success. Low-income parents more likely possess disadvantageous characteristics, and therefore they fail to provide stimulating environments for the better-off of their children \hyperref[b55]{(Mayer 1997}). According to the neoclassical human capital approach \hyperref[b7]{(Becker 1964}\hyperref[b60]{, Mincer 1974}) the economic status of the parents is transmitted to their children. The structural hypothesis of intergenerational economic and social mobility emphasizes the view that limited parental resources during childhood restrict the social and economic status of the children as adults  {\ref (Blanden et al. 2005, Mayer and}\hyperref[b56]{Lopoo 2005)}. The parental investments increase the children´s human capital, which in turn positively affects their earnings capacity \hyperref[b8]{(Becker and Tomes 1986}\hyperref[b70]{, Solon 1992}\hyperref[b71]{, Solon 1999}\hyperref[b72]{, Solon 2002}\hyperref[b15]{, Chadwick and Solon 2002}\hyperref[b58]{, Mazumdar 2005)}, their ability to gain non-labor income, and even their success in the marriage market \hyperref[b65]{(Pencavel 1998}). Among the endowment conditions parental education, employment behavior, occupational choice, family role patterns, as well as social capital environment are of importance  {\ref (Stevens 1999, Finnie and}\hyperref[b29]{Sweetman 2003)}. At the other side, gaps in the parents' investment abilities impede the economic success of the offspring \hyperref[b1]{(Acemoglu and Pischke 2000)}.\par
The first generation of the studies on intergenerational income mobility \hyperref[b8]{(Becker and Tomes 1986)} found an intergenerational correlation of about .20 for the United States, implying that the parental status does not strongly affect the children's economic and social position. Using multi-year income variables and correcting for measurement errors the second generation of analyses \hyperref[b70]{(Solon 1992}\hyperref[b71]{, Solon 1999}\hyperref[b72]{, Solon 2002)} found empirical evidence of intergenerational income elasticity ranging between 0.20 and 0.60. The analysis of the dynamics of the intergenerational income mobility  {\ref (Corcoran 2001, Mayer and} {\ref Lopoo 2002)} reveals a decreasing effect of the parental income status on the income and social position of the children. 
\section[{III. Data Base and Sample Organization}]{III. Data Base and Sample Organization}\par
The empirical analysis is based on data from the German Socio-Economic Panel (SOEP), the British Household Panel Survey (BHPS), and the US Panel Study of Income Dynamics (PSID), which were made available to us by the Cross-National Equivalent File (CNEF) project at the College of Human Ecology at Cornell University, Ithaca, N.Y.. 1 The PSID started in 1980 and contains a nationally representative unbalanced panel of about 40,000 individuals in the United States. From 1997 on the PSID data are available bi-yearly. The SOEP started in 1984 and contains a representative sample of about 29,000 German individuals that includes households in the former East Germany since 1990 \hyperref[b77]{(Wagner et al. 2007}). The BHSP started in 1991. The first wave consists of some 5,500 households and 10,300 individuals drawn from 250 areas of Great Britain. Additional samples of 1,500 households in each of Scotland and Wales were added in 1999, and in 2001 a sample of 2,000 households was added in Northern Ireland, making the panel suitable for UK-wide research. The surveys track the socioeconomic variables of a given household, and each household member is asked detailed questions about age, gender, marital status, educational level, labor market participation, working hours, employment status, occupational position, economic situation of the members of a given family over time, as well as household size and composition. The income variables are measured on an annual basis and refer to the prior calendar year. The data allow monitoring the employment and occupational status, the earnings situation, and the socio-economic characteristics of the individuals.\par
The data do not provide a sufficiently long time horizon to observe parents and children at identical life cycle situations, but cover an adequately long period to allow monitoring socioeconomic characteristics, employment and occupational status, and earnings situation of children living in the parental household and when becoming members of other family units. In this way the data allow to draw inferences about the effects of being exposed to different life situations in the parental household on the economic and social situation as young adults. The sample is restricted to persons aged 14 to 20 years, and co-resident with their parents in four consecutive years  {\ref (United States (1987} {\ref -1991)}, Germany  {\ref (1988)} {\ref (1989)} {\ref (1990)} {\ref (1991)} {\ref (1992)}, and Great Britain  {\ref (1991)} {\ref (1992)} {\ref (1993)} {\ref (1994)} {\ref (1995)}. The data base does not allow identifying parents -children relations exactly, therefore we define 'parents' as adults, whose marital status is 'married', or 'living with partner' and who are living in households with persons indicated as 'children'. We use family (household) identifiers and relationship codes to match sons and daughters to their fathers and mothers within each data set. We allow families to contribute as many parent-child pairs to each data set as meet our screening rules: the number of the parent-child pairs equals the number of the children in the parental households. The young adults are at least 24 years old when we observe the economic and social status in 2005-2009 (Germany) or 2003-2007 (USA), and in 2004-2008 (GB) when living in their own households. We focus on persons participating in the labor market, and exclude persons in full-time education. We do not consider the former East Germans, for they are not included in the SOEP sampling frame before 1990. We analyze the intergenerational economic and social mobility of persons in Great Britain because other regions are not included in the first waves of the British Household Panel Survey. The selection process leads to a sample of 2,128 German women and men, the US sample covers 2,585 persons, and the British sample includes 1,840 women and men.\par
The paper follows the standard conventions and assumes that income is shared within families and thus household income is arguably a better measure of the economic and social status than individual income variables \hyperref[b58]{(Mazumdar 2005}). The study is based on the equivalent post-government household income, which equals the pre-government household income plus household public transfers (social benefits: dwellings, child or family allowances, unemployment compensation, assistance, and other welfare benefits), plus household social security pensions (age, disability, widowhood), deducting household total family taxes (mandatory social security contributions, income taxes, or mandatory employee contributions). We use the referred income variables from the data base, thus the results make not allowance for the bias of imputed values on income inequality and income mobility \hyperref[b33]{(Frick and Grabka 2005)}. To consider the family structure we calculate the permanent household income per adult equivalent. We employ the 'old' OECD-equivalence scale (OECD 1982) made available by the data base, which assigns a value of one to the first adult household member, a value of 0.7 to each additional adult, and a value of 0.5 to each child \hyperref[b63]{(OECD 1982}\hyperref[b39]{, Hagenaars et al. 1994}). The household income variables are deflated with the national CPI (2001=100) to reflect constant prices. To exclude transitory income shocks and cross-section measurement errors we use 5-year moving averages of the real equivalent post-government household income. The parental household socio-economic mapping is captured either by the characteristics of the father or the mother. In "double"-parent families the characteristics of the father are employed, in "single"-parents families the characteristics of the mother or the father are introduced in the analysis.\par
A major factor that will lead to changes in the quality of mobility data is that response rates tend to decline over time and so the representativeness of mobility tables derived from survey data may worsen. As the income variables highly determine survey-attrition we follow \hyperref[b30]{Fitzgerald et al. (1998a;}\hyperref[b31]{1998b)} to construct a set of sample specific weights to address to the nonrandom sample attrition bias, that do not account for attrition in general, but for attrition among the particular groups under study We estimate a probit equation that predicts retention in the sample (i.e being observed as an adult) as a function of pre-determined variables measured during childhood. Presuming that the samples are representative when the children are still children we construct a set of weights1 Pr( 0 , ) ( , ) Pr( 0 ) A z x w z x A x ? ? ? = = ? ? = ? ? ? ?\textbf{(1)}\par
where x denotes the parental income as primary regressor, and z is a vector of covariates to predict attrition, indicated by A=1. Thus w(z,x) will take higher values for people whose characteristics z make them more likely to exit the panel before their adult income can be measured. The variables considered in z are the gender, and the parental age and educational attainment as well as their squares. We suppose these variables to affect the attrition propensities, to be endogenous to the outcome, that is to have an effect on the children's income as adults conditional on the parental income. The weights w(x,z) are multiplied with the parental household weights, which yields a set of weights that apply to the household of the children as adults. The parental household weights are assumed to capture the attrition effects and the weights, w(z,x), compensate for subsequent non-random attrition. The most common approach to quantify how economic (dis)advantages are transmitted across generations is to estimate the intergenerational income elasticity applying ordinary least squares (OLS) to the regression of a logarithmic measure of the children's income variable ( c y ) on a logarithmic measure of the income variable of the parental household ( p y ), and a set of control variables) ( c X 0 1 2 n c p c c c c y ß ß y ß X ? = = + + + ? .\textbf{(2)}\par
In model specification (a) we regress the logarithm of the average equivalent post-government income (2001=100) of the children's generation on the logarithm of the average equivalent post-government income (2001=100) of the parental household. The constant term ß 0 represents the change in the economic status common to the children's generation. The slope coefficient, 1 ? , is used as a measure of intergenerational mobility and expresses the elasticity of the children's income variable with respect to the parents' income situation. The larger 1 ? the more likely a person will inhabit the same income position as her parents, which implies a greater persistence of the intergenerational economic status.  to account for the indirect effects of the parental income on the children's income. To the extent that these variables lower the coefficient ß 1 these other effects "account for" the raw intergenerational income elasticity. The gender dummy (GEN) takes the value 1 for men and the value 0 for women and controls for gender differences on intergenerational income elasticity. We include the years of education of the individual (EDUC) to capture the human capital level. In the case of missing values the educational attainment is set equal to the amount reported in the previous year. We include the average schooling years of the parents (EDUC P ) to capture the correlation between educational attainment of the parents and their ability to invest in education of the children, which in turn affects the income of the children as adults. The number of children (CHILD) in the household considers the effects of care requirements on the disposable household income. We consider the parental employment status and introduce the variable "parental unemployment" (UNEMP P ) which takes the value 1 if one of the parents is employed less than half the observation period, and 0 else. We include four occupational dummies to capture the effect of the social status of the parents (OCC p ) on the income situation in adulthood. The empirical specification of the occupational status is oriented at the ISCO-88 (International Standard Classification of Occupations). ISCO-88 aggregates the occupations into broadly similar categories in an hierarchical framework according to the degree of complexity of constituent tasks and skill specialization, and essentially the field of knowledge required for competent performance of these tasks. ISCO-88 uses four skill levels, which are partly operationalized in terms of the International Standard Classification of Education (ISCED) and partly in terms of the job-related formal training which may be used to develop the skill level by persons who will carry out such jobs  {\ref (ILO 1990}). This classification rather than one based more closely on the years of education is motivated by the concept of Roy  {\ref (1951)}, that occupations require different types of or combinations of abilities and skills, and educational attainment (Goldthorpe 1987, Erikson and Goldthorpe 1992a, Erikson and Goldthorpe 1992b, \hyperref[b36]{Goldthorpe 2000)}. There is a distinctive ranking of the occupational dimensions: lower-numbered categories offer a higher prestige and a higher social status. This is particularly true for countries, where economic and social hierarchies are salient. We rearrange the 2-digit occupational categories provided by the database into 7 categories. In the analysis we consider four occupational groups "1 academic/ scientific professions/managers", "2 professionals/ technicians/ associate professionals", "3 trade/personal services", and "7 elementary occupations".\par
The regression model in specification (c) considers social exclusion characteristics that are expected to have adverse effects on a person's social and economic status. We include two dummy variables for family disruption, which take the value 1 if the marital status of the person (DISRUPT), respectively of one of her parents (DISRUPT P ) is "widowed", "divorced", or "separated", and 0 else. The disability status dummy variable takes the value 1 if the person (DISABIL) or on of her parents (DISABIL P ) is disabled, and 0 else. The health status dummy variable (SATHEALTH P ) takes the value 1, if one of the person's parents are in good health, and 0 else. 
\section[{b) Intergenerational income transitions}]{b) Intergenerational income transitions}\par
The intergenerational income elasticity indicates the average income mobility but does not shed light on the probability of the intergenerational movement relative income positions which is one of the key issues from a welfare point of view \hyperref[b41]{(Heckman 1981}). To evaluate the intergenerational persistence of income positions we employ a transition matrix of the logarithms of the permanent real equivalent household income [2001=100] of the parents and children. Both the income variables are allocated to five equally populated ranked income groups indexed by i and j. The elements 0 ij p ? of the transition matrix indicate the probability (in percent) that a person belongs to the j th quintile of the income distribution given that she belongs to the i th quintile of the income distribution of the parental household with1 ij ij j i p p = =\par
? ? \hyperref[b32]{(Formby et al. 2004}). The elements on the diagonal ( ii p ) represent the stayers and the off-diagonal terms ( ij p ) represent the movers concerning the intergenerational income position. The difference between the subscripts represents the distance from the main diagonal, the further away from the diagonal, the greater is the intergenerational mobility of the income positions. If the incomes of parents and children are equally distributed across the income quintiles, elements of the transition matrix are .2.\par
To quantify the dimension of the intergenerational income mobility we employ the Bartholomew index (Bartholomew 1982, \hyperref[b21]{Dearden et al. 1997)}, which expresses the mobility in terms of average income boundaries crossed over the observation period. The Bartholemew index sums up the moves across the income classes, i.e. outside the main diagonal1 1 1 m m ij i j B p i j m = = = ? ?? ,\textbf{(3)}\par
with ij p the proportion of children in income class j having parents in the income class i. The further the distance between the children's and the parents' income classes the greater the weight assigned to it. In the case of no mobility the Bartholomew index takes the value zero. The Bartholomew index is not independent from the order of the transition matrix, the index value based on a matrix of five groups will be different from that based on a matrix consisting of ten groups. Hence, the Bartholomew index is not comparable across countries based on transition matrices of different orders (Börklund and Jäntti 2000). 
\section[{a) Relative risk of poverty}]{a) Relative risk of poverty}\par
To evaluate the determinants of the probability to count among the poor we employ a binomial logit model  {\ref (Mc Fadden 1973;}\hyperref[b41]{Heckman 1981;}\hyperref[b53]{Maddala 1983}). The dependent variable (pov) takes the value 1 if the household income is below the poverty threshold, which is the third decile of the real (2001=100) equivalent post government household income, and zero else. The probability that a person is potentially poor then is estimated to beZ Z e e pov P + = = 1 ) 1 ( . (\textbf{4})\par
and B c the regression coefficients. In general, a probability greater than .5 predicts poverty, and a probability less than 0.5 predicts that the individual is better off. The interpretation of the regression coefficients B c is based on the odds, that is the ratio of the probability that the person is in a poverty situation and the probability that the person is well off. \par
The exp(B c ) are the factors by which the odds change when the c-th independent variable increases by one unit, e.g. this value expresses the relative risk ratio of poverty or social exclusion with a one-unit change in the c-th independent variable. The variables in ) ( c X contain a set of individual and family background characteristics and social exclusion attributes. These variables are the same for all alternatives, but their effects on the probability are allowed to differ for each alternative income quintile. (Table \hyperref[tab_1]{1)} V. 
\section[{Empirical Results}]{Empirical Results}\par
Table \hyperref[tab_1]{1} presents descriptive statistics of the non-weighted variables. The countries do not significantly differ concerning the real post-government household income and the educational attainment of the young adults and their parents. Country differences occur concerning the occupational distributions: In the United States the proportion of professional occupations (19.2\%) of the young adults is significantly lower than in Germany (25.38\%), and in Great Britain (28.26\%). On the other hand, the proportion of trade and service occupations (22.11\%) is significantly higher than in Germany (10.3\%), and in Great Britain (11.0\%). In the United States the parents' occupational distribution shows a significant higher proportion of elementary occupations (23.9\%) than in Germany (15.7\%), and in Great Britain (18.2\%). Due to the generational effect, family disruption is more expressed in the parental households than in the children's. The proportion of fathers or mothers who are dissatisfied with their health is significantly higher in Germany (16.9\%) and the United States (13.6\%) than in Great Britain (8.0\%).   
\section[{The Z characterizes the linear combination}]{The Z characterizes the linear combination} 
\section[{a) Intergenerational Income Mobility}]{a) Intergenerational Income Mobility}\par
The regression of the logarithm of the real equivalent post-government household income of the children's generation on the logarithm of the real equivalent post-government household income of the parents' generation reveal a higher intergenerational income elasticity in the United States (.678) than in Great Britain (.504), and in Germany (.484). The results corroborate the findings of various studies reporting a range of intergenerational income elasticity of 0. The inclusion of a set of individual and family background characteristics accentuates the country differences of intergenerational income mobility patterns. In all countries, individual and family background variables considerably affect the intergenerational income mobility, but in varying amount. In the United States, the individual and family background characteristics contribute more than 21 percentage points to the "raw" intergenerational income elasticity, the ß 1 coefficient decreases from .678 to .465. In Germany, these variables lower the intergenerational income elasticity by about 10 percentage points to .377. In Great Britain, the individual and family background attributes increase intergenerational income mobility by about 8 percentage points. The results confirm the hypothesis that economic success relates to a higher extent on individual and family background resources in the United States than in Germany and Great Britain. In Germany, social and family policy is obviously more successful to alleviate individual and family based social mobility barriers than in the United States.\par
In all countries, living with children in the household significantly reduces intergenerational income mobility. In Germany and the United States, women experience lower intergenerational income mobility, and higher education significantly increases the intergenerational income mobility which corroborates the human capital hypothesis. The parents' educational attainment does not significantly contribute to the children's economic success. Social origin matters: in Germany and Great Britain parents with academic or professional occupations significantly improves the chances to get better off in adulthood.\par
The contribution of social exclusion attributes to intergenerational income mobility is of little account, and reveals country differences concerning the effectiveness of welfare policy to guarantee social and economic mobility, and to alleviate individual and family disadvantages. In the United States, social exclusion characteristics have a significant higher impact on intergenerational income mobility than in Germany and Great Britain, and lower the ß 1 coefficient by 8 percentage points. In Germany, social exclusion attributes contribute .3 percentage points to the intergenerational income mobility, and in Great Britain these variables lower the 'raw' intergenerational income elasticity by 2.6 percentage points. In Germany and the United States, family disruption has a significant negative effect on the intergenerational income mobility. To live with disabled parents in childhood (Germany) or to be disabled as adult (United States) significantly increases the intergenerational income elasticity. (Table \hyperref[tab_2]{2})   The Bartholomew index documents higher intergenerational income mobility for Germany compared with Great Britain and the United States. The higher intergenerational income mobility at the lower end of the income distribution in Germany than in Great Britain and the United States documents that German social policy, institutional labor market settings, and the public financed educational system are more effective to guarantee higher social permeability in the society. In the United States, the intergenerational immobility on the top of the income distribution is more pronounced than in Germany and Great Britain. The higher correlation between the children's economic success and the parental economic resources corroborates that high income parents are able to invest in the human capital of their children, which guarantees their economic and social advancement. However, the degree of immobility at the top and at the bottom of the income distribution might be exaggerated, for upward mobility is not possible for those performing the highest income category, and downward mobility is not possible for persons in the lowest income category \hyperref[b50]{(Lentz et al. 1989}\hyperref[b58]{, Mazumdar 2005}) (Table \hyperref[tab_4]{3}).   {\ref (B c} )) and the significance level for each of the explanatory variables X c of the binomial logit model. In Germany and the United States women experience a significant higher probability to count among the poor than men. In all the countries, each additional child living in the household as living with well-educated parents significantly reduces the relative risk of poverty. In Germany and Great Britain, to hold an academic or a professional occupation significantly lowers one's relative risk of poverty. Persons engaged in trade and service Pearson Chi2(16)=163.99 (Germany), 248.63 (USA), 235.71 (GB) Pr=0.000 (Germany, USA, GB) Source : SOEP-BHPS-PSID 1980-2010, author's calculations occupations experience a significantly higher probability to count among the poor. The significant effect of the parental occupational status on the relative poverty risk underlines the intergenerational class persistence \hyperref[b50]{(Lentz and} {\ref Laband 1989, Hellerstein and}\hyperref[b42]{Sandler Morill 2011)}. In Germany and the United States persons whose parents are engaged in professional occupations have a significantly lower relative risk to be poor and persons with parents in elementary professions experience a significantly higher relative risk of poverty. In Germany, parental unemployment and health dissatisfaction significantly increase the relative poverty risk. In the United States and Great Britain marital status matters: divorce and separation increase the relative poverty risk. Volume XIV Issue I Version I 102 ( E ) 
\section[{Conclusions}]{Conclusions}\par
We analyzed the extent of and the determinants of intergenerational income mobility and the relative risk of poverty in Germany, the United States and Great Britain. We tested the hypotheses that country differences concerning welfare-state regimes, family role patterns, institutional settings of the labor markets, and social policy design induce different working of the individual and parental socio-economic resources and social exclusion attributes on intergenerational income mobility and the relative risk of poverty. The empirical findings partly support these hypotheses:\par
-Though similar in their welfare state regime, the United States and Great Britain differ concerning the average intergenerational income elasticity, the intergenerational transition of income positions, the impact of individual and family background characteristics and social exclusion attributes on the intergenerational income mobility, and the relative risk of poverty. -In the United States the intergenerational correlation of social and economic status is higher than in Germany and Great Britain, which contradicts the hypothesis of a mobile society, and a high permeability of the social system. The intergenerational income elasticity is higher than in Great Britain and Germany. The inclusion of individual and family background variables lower the 'raw' intergenerational income elasticity by about one third, compared to about one fourth in Germany, and about 15 percent in Great Britain. The inclusion of social exclusion attributes (family disruption, disability and health dissatisfaction) lower the "raw intergenerational income elasticity to a higher extent than in Germany and Great Britain. -In all the countries, the highest intergenerational income persistence is evident in the tails of the income distribution which corroborates the results of previous studies \hyperref[b3]{(Atkinson et. al. 1983}\hyperref[b21]{, Dearden et. al. 1997}\hyperref[b17]{, Corcoran 2001)}. In Germany, the results reveal the highest intergenerational income mobility in the lower tail of the income distribution, indicating that social policy more effectively alleviates the intergenerational transmission of social and economic disadvantages than in the United States and in Great Britain. In the United States, the transition matrix indicates the highest income persistence at the upper tail of the income distribution which corroborates that low income parents cannot sufficiently contribute to the well-off of their children. The intergenerational immobility in the tails of the income distribution results to an increasing intergenerational transmission of poverty and social exclusion, a deepening of economic and social inequality across generation, and produces economic inefficiencies imposing economic and social costs. Growing up in low income or in social exclusion environment negatively affects a person's future social and economic position and life chances. The social and welfare policies of a country are forced to design efficient policy measures to break the intergenerational transmission of disadvantages, and to prevent the development of a self-replicating underclass. Regardless of a country's welfare state regime, it is necessary to recognize the potential of education, and to encourage human capital accumulation to be means to advance the social ladder. However, the results call for broader analysis of the mechanisms how families, labor markets and social policy interact in determining the intergenerational transmission of economic and social (dis-)advantages in further research.\par
VII.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
       \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.85\textwidth}}
Year 2014\\
101\\
Volume XIV Issue I Version I\\
E )\\
(\\
Global Journal of Human Social Science\end{longtable} \par
  {\small\itshape [Note: © 2014 Global Journals Inc. (US) -]} 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.1643646408839779\textwidth}P{0.1044889502762431\textwidth}P{0.17023480662983423\textwidth}P{0.08922651933701657\textwidth}P{0.14323204419889504\textwidth}P{0.08922651933701657\textwidth}P{0.08922651933701657\textwidth}}
\tabcellsep \tabcellsep \multicolumn{4}{l}{Income position parental household}\tabcellsep \\
\multicolumn{2}{l}{income position}\tabcellsep 1\tabcellsep 2\tabcellsep 3\tabcellsep 4\tabcellsep 5\\
Germany\tabcellsep 1\tabcellsep .3370\tabcellsep .2935\tabcellsep .1359\tabcellsep .1685\tabcellsep .0652\\
USA\tabcellsep 1\tabcellsep .3705\tabcellsep .3125\tabcellsep .1339\tabcellsep .1295\tabcellsep .0536\\
\multicolumn{2}{l}{Great Britain 1}\tabcellsep .4752\tabcellsep .2178\tabcellsep .1386\tabcellsep .1188\tabcellsep .0495\\
Germany\tabcellsep 2\tabcellsep .1522\tabcellsep .2283\tabcellsep .3152\tabcellsep .1467\tabcellsep .1576\\
USA\tabcellsep 2\tabcellsep .2063\tabcellsep .2332\tabcellsep .2422\tabcellsep .1659\tabcellsep .1525\\
\multicolumn{2}{l}{Great Britain 2}\tabcellsep .2157\tabcellsep .2647\tabcellsep .2108\tabcellsep .2157\tabcellsep .0974\\
Germany\tabcellsep 3\tabcellsep .1196\tabcellsep .1576\tabcellsep .2228\tabcellsep .2609\tabcellsep .2391\\
USA\tabcellsep 3\tabcellsep .1222\tabcellsep .2262\tabcellsep .1765\tabcellsep .2398\tabcellsep .2353\\
\multicolumn{2}{l}{Great Britain 3}\tabcellsep .1139\tabcellsep .1782\tabcellsep .2525\tabcellsep .2475\tabcellsep .2079\\
Germany\tabcellsep 4\tabcellsep .0924\tabcellsep .1087\tabcellsep .1793\tabcellsep .2880\tabcellsep .3315\\
USA\tabcellsep 4\tabcellsep .0876\tabcellsep .1106\tabcellsep .2120\tabcellsep .3318\tabcellsep .2581\\
\multicolumn{2}{l}{Great Britain 4}\tabcellsep .0637\tabcellsep .1650\tabcellsep .2549\tabcellsep .2647\tabcellsep .2549\\
Germany\tabcellsep 5\tabcellsep .0656\tabcellsep .1093\tabcellsep .1858\tabcellsep .2459\tabcellsep .3934\\
USA\tabcellsep 5\tabcellsep .0246\tabcellsep .1034\tabcellsep .1478\tabcellsep .2611\tabcellsep .4631\\
\multicolumn{2}{l}{Great Britain 5}\tabcellsep .0446\tabcellsep .1634\tabcellsep .1634\tabcellsep .2723\tabcellsep .3564\\
\tabcellsep \tabcellsep \multicolumn{2}{l}{Bartholemew-}\tabcellsep \multicolumn{2}{l}{Percentage off the}\tabcellsep \\
\tabcellsep \tabcellsep Index\tabcellsep \tabcellsep \multicolumn{2}{l}{main diagonal}\tabcellsep \\
\tabcellsep Germany\tabcellsep \multicolumn{2}{l}{1.1828}\tabcellsep .7062\tabcellsep \tabcellsep \\
\tabcellsep USA\tabcellsep \multicolumn{2}{l}{1.1252}\tabcellsep .6875\tabcellsep \tabcellsep \\
\tabcellsep Great Britain\tabcellsep \multicolumn{2}{l}{1.1189}\tabcellsep .6775\tabcellsep \tabcellsep \\
\tabcellsep \multicolumn{5}{l}{Source: SOEP-BHPS-PSID 1980-2010, author's calculations.}\tabcellsep \end{longtable} \par
  {\small\itshape [Note: c) Relative Risk of PovertyTable4presents the relative risk ratios (exp]} 
\caption{\label{tab_4}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.49583333333333335\textwidth}P{0.2125\textwidth}P{0.14166666666666666\textwidth}}
Germany\tabcellsep USA\tabcellsep GB\end{longtable} \par
  {\small\itshape [Note: Source : SOEP-BHPS-PSID 1980-2010, author's calculations. NOTE: * p<0.05; ** p<0.01; *** p<0.001 VI.]} 
\caption{\label{tab_5}Table 4 :}\end{figure}
 			\footnote{The Intergenerational Dynamics of Social Inequality-Empirical Evidence from Europe and the United States} 		 		\backmatter   			 
\subsection[{Acknowledgements}]{Acknowledgements}\par
The author wishes to thank the participants of the 5 th ECINEQ Meeting in Bari, Italy, July 22-24, 2013, for valuable comments and discussions. The shortcomings and errors remain the author's as usual. 			  			  				\begin{bibitemlist}{1}
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\end{document}
