The Effects of Endogamous Marriage on Family Outcomes: Evidence from Exogenous Variation in Immigrant Flows During 1900-1930 in the United States

Home , Endogamy

THE EFFECTS OF ENDOGAMOUS MARRIAGE ON FAMILY OUTCOMES: EVIDENCE FROM EXOGENOUS VARIATION IN IMMIGRANT FLOWS DURING 1900-1930 IN THE UNITED STATES

Ho-Po Crystal Wong1 29 September 2014

Abstract. Positive assortative matching in terms of traits like ethnicity, race and personality has been prevalent in marital formation. One possible explanation for this is that husbands and wives in endogamous marriages have complementary skills and tastes that increase marital surplus. This paper aims to estimate the eects of ethnic assortative matching on a variety of household outcomes by using the exogenous variation in immigrant ows in the United States during the period 1900-1930 to disentangle the selection eect of partners. The major nding is that the complementarities in home production from same ethnic marriage enhances investment in household public goods such as childrearing and home ownership and reduces the market labor supply of wives. OLS and Logit estimates of this eect appear to be substantially biased downward, indicating positive selection into intermarriage in terms of unobservable traits that increase marital surplus.

JEL Classication: D13, J12, J13, J15, J16

Key Words: endogamous marriage, assortative matching, immigrants, intermarriage, labor supply, children, household public goods

1Department of Economics, West Virginia University. 1601 University Ave., Morgantown, WV26506, USA. Email: [email protected]. I thank Shelly Lundberg for her valuable suggestions.All errors are my own. 1. Introduction and related literature

Mate selection is not a random process and it is a well-documented stylized fact that in marriage individuals tend to sort on traits such as ethnicity and race. Sociologists refer marriages of the same type as endogamy (see for instance, Kalmijn 1998).Studies show that racially and ethnically mixed couples tend to experience less stable marriage: their divorce rates are higher and the duration of marriages tends to be shorter (see Jones, 1996; Kalmijn et al. 2005). As proposed in the seminal work of Becker (1973), one primary economic reason for marital sorting is the complementarity or substitution eects for certain traits of couples in marital production. Conceivably ethnicity is one important complement in marital production. Coordination in household production and decision making can be easier when spouses speak the same language and share a similar cultural background (Kalmijn et al. 2005). Couples from the same ethnic group in general have more similar tastes for food and common interests, which would enhance the complementarity in leisure as well as the utility from public goods sharing and consequently the gain to marriage. Divergent cultural norms of ethnically mixed couples could hinder coordination and might give rise to more conicts and disagreement in households.

While there is a solid theoretical foundation for assortative matching, empirically it is complicated to estimate the causal eect of assortative matching on marital outcomes due to the selection problem in union formation (see Adserà & Ferrer (2014)). Spouse selections are determined by many characteristics unobserved to the researcher and yet might play a central role in household outcomes.Without a proper instrument it is extremely dicult to isolate this selection eect and disentangle the causal impact of endogamous marriage on family outcomes. Qian (1997) found that among interracially married couples, men and women from lower status racial groups but with high education levels tend to marry spouses from a higher status racial group with low education levels. As a result of the possible language barrier and cultural dierences that exist between spouses in intermarriage, couples that intermarry might be compensated for their dierences by other positive attributes of their partners. Intermarried couples also tend to be matched positively by the educational dimension. For instance, Chiswick & Houseworth (2011) suggested that the probability of intermarriage is positively related to the similarity in education level. Conceivably apart from education, there are qualities attributable to intermarriage or endogamous marriage that cannot be observed in the data. This would give rise to substantial bias in estimating the eect of endogamous marriage using simple OLS or logit models. In the same spirit as this paper, Halla (2013) estimated the eect of assortative mating on marital stability in

2 Austria by performing Cox proportional hazard models. One dimension of assortative mating he investigated is ethnicity. He found no evidence that the decrease in assortative mating by ethnicity is associated with the increased risk of divorce in Austria. But again, in his estimations, the non-random mate selection has not been accounted for, which potentially could confound his ndings. Higher levels of education could enhance cultural assimilation and facilitate the interaction with people of dierent ethnic backgrounds (Pagnini & Mor- gan,1990; Qian, 1990; Qian et al., 2001).One can easily imagine that two individuals having dierent ethnic backgrounds might form a union because each of them possesses some positive attributes in spouse selection unobserved by the researchers but might have a role to play in a variety of family outcomes. For instance, they might both be physically attractive or possess personality traits favorable to marriage (Lundberg 2010). Same ethnic couples in contrast might be less selective in these unobservable traits as they have additional benets from mating of likes compared to their intermarried counterparts.

The existing literature on intermarriage and endogamous marriage by race or ethnicity has been mostly descriptive. These studies primarily focus on examining the factors related to endogamous marriage over time and the extent to which ethnic groups dier in terms of the trends in endogamy and intermarriage. One major lesson we have learnt from these works is that individuals have a tendency to match themselves by ethnicity throughout human history and such trends are aected by factors such as education attainment of dierent ethnic groups, their sizes in the population and the composition of local marriage market over time ( Kalmijin 1998; Gilbertson et al. 1996; Qian 1997). Yet, the question of the extent to which ethnic assortative matching aects household outcomes has remained largely unexplored. Given such human regularity, examining the causal impact of ethnic endogamous marriage on household outcomes is important in understanding why it persists in societies.

This paper contributes to an understanding of the persistence of ethnic endogamy by in- vestigating its eect on family outcomes after taking into account the selection bias at play in partner selection by making use of the great migration period of the United States from 1900-1930 to identify the causal eect of same-ethnic marriage on a variety of household outcomes. I examine the causal eect of ethnic assortative matching on household behavior by using an instrumental variables (IV) strategy based on exogenous variation in immigrant ows primarily driven by warfare and the changes in immigration policy in the United States. Table 1 presents the variation of immigrant ows during the period under study. The number of immigrant arrivals increased sharply at the beginning of the First World War and dropped dramatically subsequently. The inux of immigrants resumed to a normal level after the end of First World War but was articially suppressed in the mid-1920s due to 3 the passage of a variety of quota acts on immigrations. Angrist (2002) used this exogenous variation in immigrant ows to instrument for the sex ratios of ethnic groups. One major nding is that higher sex ratios are associated with higher marriage rates for the second generation women. I use the immigrant ows of dierent ethnic groups as instruments for endogamous marriages. This allows for estimation of the eect of endogamous marriage on household outcomes inclduing home ownership, childbearing as well as spousal labor supply.

Most of the economic studies related to endogamous marriage only take the preference for same-ethnic marriage as the starting point of their analysis. Few attention has been directed toward understanding the favorable family outcomes resulted from endogamy For instance, Angrist (2002) addressed the question of how sex ratios of ethnic groups aect the marriage and labor market given the preference for endogamous marriage by ethnicity. Lafortune (2013) explored how a gender's scarcity within the same ethnic group aects educational investments based on the empirical fact that a large fraction of second-generation Americans tend to marry within their own ethnicity. This paper contributes to this line of literature by providing the economic basis for such preference in terms of the family outcomes favorable to marriage caused by ethnic assortative matching. Also, interethnic marriage rates have often been conceived as a proxy for the degree of assimilation of the ethnic groups involved (see Pagnini & Morgan 1990; Qian & Lichter 2007; Furtado & Trejo 2012). Assortative matching by ethnicity potentially could play an important role in the labor supply, fertility and other investments in household public goods of households. Understanding the economic impact of ethnically endogamous marriages thus provides additional insights into the economic factors that might aect the process of social assimilation and adaptation of immigrants to the host country.

Another strand of literature concentrates on marriages between the natives and immigrants. Furtado and Trejo (2012) reviewed the literature on the economic eects of intermarriages. Most studies found that immigrants that marry natives tend to have better economic outcomes than those who marry within their ethnicity. But as they pointed out, these estimates are subject to the same selection problem as aforementioned, which makes it dicult to interpret the relationship found. Meng & Gregory (2005) adopted a two-stage least square (2SLS) and non-linear two-stage least square (NSLS) model to estimate the wage premium for intermarriage. In the rst stage, they make use of the local sex ratio of immigrants to predict the probability of intermarriage between natives and immigrants. They found that intermarried immigrants earn signicantly higher than endogamously married immigrants (i.e. immigrants marrying immigrants). In the same spirit as Meng & Gregory (2005), I provide in the 2SLS and NSLS estimates of the eect of endogamous marriage in ethnicity 4 among immigrants by using instruments based on the variation in immigration ows during the mass migration period from 1900-1930 to predict the likelihood of endogamous marriage.

Research that attempts to understand the reasons behind the vulnerability of intermarriage mostly comes from the sociology literature (Jones 1994; Dalmage 2000; Chito & Childs 2005; Bratter & King 2008). The most popular hypothesis is the exogamy hypothesis, which suggests that the dissimilarity in values and norms from divergent cultures, lack of social support from family and friends and the social stigma attached to intermarriages are the main reasons for which these marriages are relatively more fragile than their endogamous counterparts (see Kalmijn et al. 2005; Dribe & Lundh 2012 and Milewski & Kulu 2013). However, none of these works examine the linkage between the family outcomes associated with endogamous marriages and marital stability.

Although cutltural proximity and social distance between ethnic groups are important consideration in social assimilation, this paper primarily investigates the average eect of endogamous marriage, given the dierences across ethnic groups. Studies relate cultural proximity of couples to marital outcomes can be found in Kalmijn et al. (2005) and Dribe & Lundh (2012). However the main results of this paper are unaected by exclusion of ethnic groups that are conceived to have a larger social distance from groups of European ancestry as shown in the robustness tests in Section 6.The nding of this paper is relevant to a wide range of sociocultural setting where divergent cultural norms across dierent ethnic groups prevail. It also contributes to a better understanding of the eect of assortative matching on family structure generally. For instance positive assortative matching in terms of traits like personality might have similar eects on household outcomes (see Lundberg 2010). These matching mechanisms play an increasingly central role in contemporary marriage given the decline in gender-based division of labor in households over recent decades.

I nd that overall marrying within the same ethnic group generates profound eects on investment in household public goods in terms of childrearing and home ownership and might have enhanced household specialization as indicated by the lower labor force participation of endogamously married women. This is consistent with the hypothesis that ethnic assortative matching increases marital surplus and thus encourages investment in household public goods and household division of labor. These ndings provide a possible economic explanation why endgamous marriage tends to be more stable. The OLS and Logit results appear to substantially underestimate the eect of endogamous marriage. This implies that intermarried couples select positively into marriage in terms of other unobservable traits in mating that generate marital surplus, consistent with the empirical ndings in the sociology 5 literature.The results highlight the importance in addressing the selection issues in marital formation in estimating the causal eect of assortative matching on household outcomes.

2. Theoretical Framework

Under Becker (1973)'s assortative mating framework, holding other things equal, mating of likes is implied if such pairings maximize marital output. Suppose that the marital output function takes the form: f(x, y) where x and y stand for a trait of men and women and let it be ethnicity and assume the function is twice dierentiable. For simplicity consider that there are only two ethnic groups: a and b. If a type xa man and a type ya woman match with each other and a type xb manor a type yb woman match with each other, endogamous marriage happens. Endogamous marriage is optimal if

(2.1) f(xa, ya) + f(xb, yb) > f(xb, ya) + f(xa, yb)

This occurs when ∂2f(x,y) , i.e. when the arguments in the marital production function ∂x∂y > 0 are complements. Arguably, ethnicity is one form of complements in marital production. Lifestyles of individuals are undoubtedly aected by the cultures they are brought up with. For example, people from the same ethnic group are likely to have more common interests, same religious belief and similar tastes for food.They are more likely to agree on each other in terms of parenting practices All these would enhance the gain to marriage. Theoretically, the extra marital surplus to marriage in the above is purely driven by the positive (or negative) assortative matching itself and such gain would not occur had spouses been matched dierently. Therefore holding other things constant, any individual in the marriage market would prefer a mate from the same ethnic group.

Yet in reality, the occurrence of same-ethnic marriage (i.e. endogamous marriage) depends on the availability of same-ethnic mates in the marriage market. Individuals would search for a same-ethnic mate until the marginal cost of such search exceeds its marginal benet. When same-ethnic partners are relatively scare in the marriage market due to for instance, a large inux of immigrants that are dominated by one sex for a certain ethnicity; the search cost for getting a same ethnic mate will be higher, which would give rise to more marriages across ethnic lines.

6 In addition, as a result for the higher marital surplus for endogamously married couples over their intermarried equivalents, endogamous marriages are likely to be more stable (see Jones 1994, 1996; Bratter & King 2008 for empirical support). This will enhance household specialization of labor.If the wives expect that there is a higher probability for their marriage to dissolve, they will reduce their specialization in home production, which is traditionally largely shouldered by the wives, and at the same time participate more actively in the paid workforce to nancially protect themselves against marital dissolution (see Johnson & Skin- ner 1986; Parkman 1992; England and Folbre 1999).

3. Model Specification

I restrict my analysis to foreign and second generation households headed by men aged 20-45. Men from this age group is exposed to relatively higher marriage risks and their mate selection is more likely to be inuenced by the inux of new immigrants. This restriction increases the likelihood of appropriately assigning the immigration ows to marriages at the time of their formation. To isolate the potential eects of assimilation and American nativity on family outcomes (Baker and Benjamin 1997; Meng and Gregory 2005), which might confound the sorting eect of immigrants; I exclude natives in my sample, who are dened to be individuals that were born in the United States with American born parents). Also, practically it is impossible to identify the ethnicity of natives from the data.

The below 2SLS regression models are used to estimate the eect of endogamous marriage on a variety of household outcomes. Consider the following regression model:

(3.1) 0 Yi = Xiβ + αEi + αs + σt + µj + i where Yi is some outcome variable of household i including the number of children in the household, home ownership and spousal labor force participation. Xi is a vector of control variables including the age and age squared of household heads and wives, dummies for literacy level for the husband, dummies for years in the United Stated for the household heads, a dummy variable that indicates the grandparents reside in the households and a dummy variable that indicates urban residence. Ei is a dummy variable that takes the value one if the marriage of household i is endogamous and zero otherwise. γs , σt and µj capture the state, year and ethnicity eects respectively and iis an i.i.d. noise term.

Hypothetically, α > 0 if endogamous marriage facilitates outcomes such as fertility, home ownership and labor force participation of the household head. And if endogamous marriage 7 encourages household specialization of labor, the labor supply of endogamously married wife will fall.

The rst stage regression is the following:

(3.2) 0 0 Ei = Xiπ1 + netj,tEthnic τ 1 + θ1s + ω1t + ρ1j + φ1i

where netj,t is the number of female adults minus the number of male adults over the male population of ethnic group j in year t. This term aims to capture the net supply of female immigrants in a particular ethnic group to the marriage market as a percentage of the ethnic male population. Therefore it is the net ow of female immigrants as a percentage of the male stock. An increase in female immigrants as a proportion of the male foreign stock in the same ethnic group should increase the likelihood for a man to marry endogamously. Ethnic

is a vector of dummies for the ethnic groups to which the household head belongs. θ1s, ω1t andρ1j capture the state, year and ethnic group xed eects respectively in the rst stage regression and φ1i is the noise term.

Alternatively, using another set of instruments, the rst stage regression is given by:

(3.3) 0 0 Ei = Xiπ1 + Immigrantj,tEthnic τ 2 + θ2s + ω2t + ρ2j + φ2i

where immigrantj,t denotes the total number of immigrants divided by the total population of ethnic group j in year t. Instead of focusing on the supply of women in the marriage market, this captures the ow of immigrants as a percentage of the foreign stock in a given ethnic group. A larger immigrant ow as a percentage of the foreign stock in the country should increase the supply of mates. However if sex-biased migration prevails, it might in-

crease the competition in the marriage market for endogamous mates.θ2s, ω2t and ρ2j capture the state, year and ethnic group xed eects in specication 2.φ2i is the noise term. The impact the immigrant ows imposes on ethnically endogamous marriages depend on the age, sex and marital status composition of the local ethnic groups as well as those of the immigrants. Since detailed information on the demographic composition of the immigrants are not available, the interaction of the instruments with the ethnic group dummies allow for group specic eects for these instruments.

The rst stage equation (3.2) or (3.3) can be estimated with ordinary least squares (OLS) or Logit model. The second state is estimated by ordinary least squares (OLS) , which gives the 2SLS and NSLS estimates respectively. The rst stage and second stage estimates are

8 presented in Tables 6-7. Estimates using simple OLS and Logit models are also included to examine the direction and magnitude of the bias.

The justication for the validity of these instruments is that the variation in the immigrant ows over time and across ethnic groups is primarily driven by conditions outside the United States and a set of immigration policies uncorrelated with the family outcomes of the immigrants. For instance, the large scale migration of Italians to the United States during this period is mainly a result of the poor land management and disease in South Italy (see Foerster 1924). Secondly the immigrants from Europe dramatically decreased when the United States entered the rst World War (see Figure 1), which is an exogenous political event. Finally a variety of Immigration Acts set forth in the 1920's imposing quotas on immigrants based on their country of origin. For example, the rst per centum immigration quota law went into eect in 1921. With an aim to reduce the number of immigrants from Southern and Eastern Europe, the law restricted the admission of aliens in any one year to 3 percent of the number of foreign-born persons of each nationality residing in the United States in 1910, as determined by the 1910 census in which most of the immigrants came from Northern and Western Europe. The 1924 National Origins Act further reduced the annual quota of admissible aliens from 3 to 2 per cent (see Bloch 1929).2 Also the quota limit law imposed a more severe restriction on immigrants from countries of South and East Europe and East Asia, but less on North and West Europe (see the Annual Report of the Commissioner General of Immigration in the scal year ended June 30, 1924). Immigrants from the Western Hemisphere such as those born in Mexico were exempted from the quota laws. This legislation thus gave rise to a substantial change in the ethnic composition of immigrants entering the United States. As shown clearly in Figure 1, the two quota acts drastically reduced the number of Italian, English and Spanish immigrants subsequent to the passage of these two quota acts. The eects of these restrictive immigration legislation are most strongly felt a year after its implementation in 1920 and 1924. These changes in immigration law provide excellent exogenous variation of the immigrant ows to the United States, which no doubt produced profound impact on the local marriage market condition and the occurrence of endogamous marriages.

4. Data

The data for this study come from the 1910,1920 and 1930 Census IPUMS, one percent sample. The data contain information regarding the birthplaces of the respondents and their

2Also the quota limit law put a more severe restriction of immigrants from coutnries of South and East Europe and East Asia, but less on North and West Europe (see the Annual Report of the Commissioner General of Immigration in the scal year ended June 30, 1924). 9 parents as well as the number of years they have resided in the United States if they are immigrants. It also provides basic information with respect to the work status of the respondents including their employment status. The information on the number of children in the household and home ownership is also recorded. I match the data on the immigration ows of dierent ethnic groups come from the Annual Report of the Commissioner General of Immigration from 1900-1929 prepared by the Department of Commerce and Labor to the Census data.3 These are administrative records for the number of immigrants from dierent origins. The data on the foreign born population of ethnic groups based on country of birth are from the Historical Census Statistics on Country of Birth of the Foreign-Born Popu- lation. Details on grouping and dening the ethnicity are provided in Appendix A. Table 2 and Figure 1 present the immigration ows and population of dierent ethnic groups in the United States during 1900-1930. They show clearly that the immigrants from Europe dropped sharply during the First World War and subsequently in the mid-1920s as a result of the quota law. The immigration trends of the Mexican and Japanese are less aected by the First World War and the quota acts which aim to limit the number of immigrants in mid-1920s from Europe, particularly Eastern Europe. Table 4a displays the summary statistics by generation of immigrants. Overall the second generation population is associated with a higher literacy and home ownership rate but they tend to have fewer children. Table 5 illustrates the overall decline in endogamous marriage over time. These trends suggest that it is highly possible that the First World War and the quota act aected the marriage market in the United States through an exogenous reduction in the supply of foreign mates that could potentially match with the second generation immigrants.

One drawback of using these historical data is that the demographic variables in Census IPUMS in the period under study are rather limited. The dependent variables in this study consist of household public goods variables namely home ownership and the number of residing children as well as spousal labor supply. Several measures are used to capture the socioeconomic characteristics of the households in the sample. The quadratics in ages for both spouses are used to capture the life cycle eect on household outcomes. The presence of grandparents in the households might aect household outcomes: for instance, they can take care of the children in the households that might aect the labor supply of the wife. I control for this by using a dummy variable that indicates the presence of parents of the spouses. In addition, I take into account whether households' location is urban. Households

3During 1895-1903, the data was collected by the Bureau of Immigration in the Department of Treasury. It was then transferred to the Bureau of Immigration and Naturalization in the Department of Commerce and Labor between 1906-1913 and subsequently became the Bureau of Immigration in the Department of Labor. 10 residing in rural areas tend to have more children and a higher home ownership rate. Wild- smith et al. (2003) suggest that rural push toward intermarriage can be found in the Irish and Italian groups. I also create eight dummy groups for rst generation household heads' having resided in the United States for one to ve years, six to ten years and so on as well as a dummy variable that indicates the household head being a second generation immigrants. Foreign born men that have resided in the United States for a longer period or second generation immigrants have a higher likelihood to marry outside of their own ethnicity as they have been more exposed to the local culture and are more likely to have a better English ability that could facilitate intermarriage and cultural assimilation. Since education level of individuals is not available in the sample period, the literacy level of spouses is included to account for its eect on household outcomes and labor supply. The literacy skills are coded as a series of mutually exclusive dummy variables that include illiterate (cannot read or write), cannot read, can write, cannot write, can read and literate (read and write).

To account for the time trend and the permanent state eect on the outcome variables, I add year and state dummies in my estimation. The ethnicity of household heads is used to capture for the dierences in marital and market behavior that vary across ethnic groups. The analysis comprises seventeen ethnic groups: Dutch, English, Finnish, Former Austro-Hungarian, French, German. Greek, Italian, Japanese, Mexican, Polish, Portuguese, Romanian, Russian,Scandinavian, Spanish and Turkish.The groupings are based on geographic proximity and languages of countries.4

The next section presents the estimates of the rst-stage and second-stage regressions using alternative econometric models. Section 6 provides robustness checks for alternative specications and examines whether the results are sensitive to exclusion of ethnic groups that might raise concern for the estimates. Overall I nd substantial underestimation of the magnitude of the eects of endogamous marriage without accounting for selection into inter-marriage and the ndings are robust to alternative specications and sampling.

5. The Results

Table 6 presents the rst stage results using dierent sets of instruments. The rst two and last two columns are estimates using the instruments in equation (3.2) and (3.3) respectively. Conjecturally the instruments in equation (3.2) would be better instruments

4The changes in national boundaries during the First World War make it impossible to consistently separate the ethnic groups from the former Austria-Hungary. In the robustness check, I show that the results are insentive to exclusion of the Former Austro-Hungarian group. 11 for endogamous marriage as they directly capture the net ow of women available to the stock of men in each ethnic group while those in equation (3.3) captures the eect of an increase in the size of mates of each ethnic group on endogamous marriage. I denote the two sets of instruments as IV(1) and IV(2) respectively. For the two-stage least squares (2SLS) estimations, the F-statistics for the instruments in both specications are above 10 indicating that they are strong instruments. The Chi-square tests of the two Logit models also indicate that the instruments are jointly signicantly dierent from zero. Consistent with the above conjecture, the instruments in (3.2) perform slightly better as indicated by the higher value in the F-statistics and Chi-squared test. It is noteworthy that the eect of the immigration ow as a percentage of the local ethnic population (IV(2)) on endogamous marriage of each group appear to be quite dierent from the net ow of women as a percentage of the male population (IV(1)). One conjecture is the direction of how the inux of immigrants aects endogamous marriage largely depends on the composition of the gender. Its eect on endogamous marriage could be either positive or negative eects if sex-biased migration prevails.Suppose that the local ethnic population is dominated by males and the inux of immigrants consist mostly of males, then the new immigrants will become competitors for endogamous mates and will therefore lower the probability of endogamous marriage.Wildsmith et al. (2003) also found that states with large proportion of men in the ethnic population led to exogamy for men. Table 3 displays the number of single immigrants by gender and the sex ratios of singles by nativity during the period 1910-1919 and 1920-1929.5 A comparison of these statistics with the results from Table 6 is in concert with the above conjecture. Overall the sex ratios for most immigrant groups have been high meaning that there are more single male immigrants than female immigrants migrating to the United States in the period under study. So on the net, the number of immigrants as a percentage of the male population imposes a negative eect on endogamous marriage as the new male immigrants compete with the existing immigrants and the second generation for same-ethnic mates. On the other hand, the net ow of female immigrants as a percentage of the male population produces a positive eect for the majority of ethnic groups. The likelihood of endogamous marriage for the German immigrant group is unresponsive to the change in the immigrant ow as a percentage of the German population but it responds negatively to the change in net supply of women. This result is somewhat puzzling and might be related to that the female immigrants from Germany might be mostly married so that they might not contribute to the net supply of women in the marriage market and the German immigrant group might be culturally compatible with the rest of the old immigrant groups, which explain for its unresponsiveness for the instrument set IV(2).

5This information is unavailable for the period 1900-1909. 12 An examination of Table 4b indicates that the mating criteria and family outcomes for endogamous and exogamous couples are quite dierent. Even before taking into account the selection eect, an endogamous household on average has 0.59 more children in the family. The wife in an intermarried household is 10.9 percentage point more likely to be able to read and write and 7.2 percentage point for the husband in a mixed-ethnic marriage. This is not unexpected given that a higher level of literacy can facilitate communication with other ethnic groups. The above suggests that without properly dealing with the selection problem in marital formation, the estimated eects of endogamous marriage is likely to be biased due to the existence of unobserved attributes the researchers cannot account for such as physical appearance, the respondents' ability to adapt to dierent cultures and in our study the exact education level of spouses.

Table 7 provides estimates of the eect of endogamous marriage on a variety of household outcomes using the instruments in equation (2) and (3) based on a variety of econometric models. The discussion that follows are primarily based on the results in NL2S(1) as IV(1) are stronger instruments compared to IV(2). The direction of the bias is the same using alternative sets of instruments. Overall, the OLS and standard Logit or Poisson estimates provide very similar results.

Panel A of Table 7 shows the OLS, Poisson, Two-Stage Least Square and Poisson IV estimates of the eect of endogamous marriage on a variety of household outcomes in the full sample using the instruments in equation (2) and (3). For the number of children in household which is non-negative interger-valued, I perform Poisson and Poisson IV regression. The latter is a Generalized Method of Moments Estimator (GMM) that allows for endogenous variables. Based on the Poisson IV(1) estimate, endogamously married couples on average bear 1.68 more children. The estimate using Poisson regression (0.121) appears to substantially underestimate the eect of ethnic assortative matching on childbearing.

Panel B of Table 7 illustrates that as predicted, the OLS and Logit regressions substantially underestimate the magnitude of the eect of endogamous marriage on home ownership, which is one form of public goods in marriage. This suggests that intermarried spouses in- deed select positively into marriages in terms of wealth and other unobservable attributes that enhance marital surplus. After accounting for this selection eect of intermarried couples into marriage, the 2SLS estimate suggests that endogamously married couples are 32.2 percent more likely to own a house and 26.2 percent for the NL2S estimate. Both estimates are substantially higher than the OLS and Logit estimates (ranging from 3.2-3.5 percent).

13 Endogamous marriage does not appear to have any signicant eect on husbands' labor supply. For the endogamously married wives however, they are much less likely to participate in the labor market (-24.6 percent using 2SLS(1) and -12.2 percent using NSLS(1)). Both estimates are remarkably lower than the OLS estimate. These results are consistent with that endogamous marriage might have enhanced household specialization of labor due to its higher marital surplus generated, holding other things constant. The higher marital surplus makes endogamous marriage more stable and thus increases the incentives for wives to specialize in home production. In addition, the fact that the estimated coecients in the OLS and Logit models are substantially biased downward suggests that the intermarried spouses are possibly matched based on unobservable traits that might discourage the labor force participation of wives. For instance, a wealthy man marries a physically attractive woman or one who possesses very high homemaking skills from another ethnic group. Al- ternatively, couples that marry endogamously can more eciently perform gender division of labor within the family.

6. Robustness Checks

To examine if the estimates are sensitive to the groupings and alternative specications, I perform a variety of robustness checks as presented in Table 8. I provide NL2S(1) estimates for home ownership, labor force participation of the husbands and wives and Poisson IV(1) estimates for the number of children. Specication (1) connes the sample to ethnic groups that are of European ancestry by excluding the Japanese and Mexican group. Intermarries across Europeans are subject to less cultural dierence and so one would expect that the eect of endogamous marriage to be weaker when non-Europeans are excluded. The empirical results partially conrm this hypothesis. A comparison between the estimates in Table 7 and Table 8 suggests that inter-marriages that occur among the European ancestry categories produce a much weaker eect on fertility (1.026 compared to 1.68 in the full sample). European women in endogamy are found to reduce their market labor supply compared to those that marry across ethnic lines (-0.11), but the magnitude is smaller compared with estimates using the full sample (-0.22). The likelihood to own homes for endogamous couples is very similar in the two samples. Taken together, this implies that inter-marriages that possibly involved European and non-European spouses are less complementary in marital production. This result provides some economic justication for the strong separation in marriage along the European and non-European dividing line, possibly because of the larger cultural dierence across this line.

14 Dening Austro-Hungarian as one ethnic group raises some concern as the former emperor actually contains numerous ethnic groups that speak dierent languages such as German, Hungarian, Czech, Slovak and Italian. As a result of the territorial changes during the First World War, it is not possible to consistently separate the ethnic groups belonging to the former Austria-Hungary in the data. Potentially the inclusion of this large group in the analysis might confound some results.Specication (2) in Table 8 excludes the Austro- Hungarian group from the sample. It is reassuring to nd that the estimates are insensitive to exclusion of the Austro-Hungarian groups. The estimates are very similar to those using the full sample. The eect of endogamous marriage on the likelihood of home ownership becomes weaker but it is still at a substantial 21.4 percent.

Specication (3) further restricts the sample to households headed by men aged 20-40 as the partner selection of older men are less likely to be aected by the immigrant ows. The estimates of the number of children in households and the likelihood of home ownership drops but they estimates are still substaintiallly lower than the Possion and OLS estimates in Table 7. It is not surprising that the estimates become lower as fertility and wealth tend to increase with the age of the household heads. However the estimate of the eect on female labor supply is not substantially aected by the sub-sampling.

Conceptually the immigrant ows could aect family and economic outcomes through two channels: Firstly, they could change the prospect in the marriage market of opposite sexes in the same ethnic group through changing the ethnic sex ratio. For instance, more immigrant men could enhance the bargaining power of women in the same ethnic group (Grossbard- Shechtman 1985, 1993; Angrist 2012). Secondly, increasing the number of mates of the same ethnic group would increase the probability of endogamous marriage, which is also the subject of study in this paper. Specication (4) includes the sex ratio for individuals aged 16-45 in each ethnic group constructed by the Census data. This measure is based on the stock of immigrants in the country. Similar to the nding in Kalmijn & Van Tubergen (2010), I nd that the ethnic sex ratio itself produces no eect of endogamous marriage. This specication allows us to investigate to what extent the results of the eect of endogamous marriage could potentially be driven by variation in ethnic sex ratios instead of endogamy. A comparison of the results in Tables 7 and 8 shows that the eects of endogamous marriage after con- trolling for ethnic sex ratio are somewhat weaker for number of children in households and female labor force participation. The eect on home ownership is very similar using both specications. Overall, the magnitude of all the estimates remain much stronger than the OLS and Possion estimates except for the estimated eect on husbands' labor supply, which

15 is statistically insignicant.

As suggested by Angrist (2012), sex ratios based on the foreign stock could be endogenous to family outcomes. I use the sex ratio of the immigrant ows to predict the ethnic sex ratios of the immigrant stock. In specication (5), the predicted values of the sex ratios are included in the regressions.6 The estimates are not sharply dierent from specication (4). In particular, the estimates for the eect on the number of children in households and labor force participation of wives are actually closer to the estimates provided in the main results using the imputed sex ratios. The robustness checks show that the pattern of the results: stronger eects of endogmous marriage when it is instrumented for, is not altered by alternative specications.

7. Concluding Remarks

I create instruments based on the exogenous variation of immigrant ows from dierent countries to the United States during the great migration period to estimate the eect of endogamous marriage (i.e. marriage of the same ethnicity) on a variety of household outcomes. The results in this paper provide a robust and convincing nding that marrying within the same ethnic group alters a number of family outcomes that are found to be benecial to marriage and this relationship is causual. As proposed by Becker (1973), the mechanism for the linkage between ethnic assortative matching and these favorable family outcomes is that ethnic assortative matching enhances marital surplus as same ethnicity is one form of complements in marital output. As a result of such complementarity, couples invest more in household public goods such as home ownership and childrearing. Wives who marry endogamously are also found to have lower labor force participation. This might indicate that sexual division of labor within the family is more pronounced for endogamous couples. Such economic eects of assortative matching have been largely overlooked in the literature. Conceivably this result can be extended to matching of the likes for traits such as personality. After all, the benets of endogamous marriage mostly come from the fact that these couples share similar cultural backgrounds which facilitate household co-ordination and the complementarity in leisure as well as public goods sharing. Similar eects can be applied to couples that share similar interests and lifestyle.

The results provide important insights for mating of the likes which complement the existing literature on endogamous and inter-ethnic marriage that is mostly descriptive. The substantial bias present in the OLS and Logit estimates indicates that couples that marry within the same ethnic group might have paid less eort in marital search and that some

6The control variables in this OLS include ethnic and year dummies. 16 unobserved positive traits are possibly present for intermarried couples. Such nding is consistently with the ndings in Qian (1997) and Chiswick & Houseworth (2011).The ndings portray a very clear picture that without accounting for the selection problem in mating, the eect of endogamous marriages are heavily underestimated and that the positive eect arising out of matching of the likes are largely present in marriage. One important lesson from this analysis is that it is necessary to account for the selection problem in order to draw casual inference about the eect of endogamous marriage on marital outcomes.

In addition, the ndings of this paper provide a possible economic reason why ethnically mixed couples are more vulnerable to marital disruption (Bratter& King 2008; Jones 1994): holding other attributes of mates constant, same-ethnic couples could generate more marital surplus for the same amount of input into marital production and this will lower the likelihood of dissolution. Becker et al. (1977) found that discrepancies between intelligence, social background, religion or race raise the probability of marital dissolution. They also found a very strong positive eect of racially endogamous marriage on fertility. In their study, racially mixed couples tend to have one less child than other couples. Note that they have not accounted for the selection problem in their estimation and so it is likely that the true eect of racially endogamous marriage is larger than their estimate. In my analysis, the eect of endogamous marriage on the number of children in households is highly underestimated using simple OLS and Poisson regressions. An interesting implication from the results is that the immigration quota acts of 1924 which gave rise to a dramatic increase in intermarriage rates might have contributed to the increase in marital breakdown in the United States. The increasing trend of marital instability that had been observed in the United States might have been in part the cost the society paid for cultural assimilation. Such eect has been over-looked in the literature and deserves further investigation.

17 References

[1] Adserà, A., & Ferrer, A. M. (2013). The fertility of recent immigrants to Canada (No. 7289). Discussion Paper Series, Forschungsinstitut zur Zukunft der Arbeit. [2] Adserà, A., & Ferrer, A. (2014). Immigrants and Demography: Marriage, Divorce, and Fertility (No. 7982). IZA Discussion Paper. [3] Alba, R.D. & Golden, R.M. (1986). Patterns of Ethnic Marriage in the United States. Social Forces, vol.65(1), 202-223. [4] Angrist, J. (2002). How Do Sex Ratios Aect Marriage and Labor Markets? Evidence from America's Second Generation. Quarterly Journal of Economics, vol.117(3), 997-1038. [5] Baer, J.A. (2001). Women in American Law: The Struggle Toward Equality from the New Deal to the Present. New York/London: Holmes & Meier Publishers. [6] Baker, M. & Benjamin, D. (1996). The Role of Family in Immigrants' Labor-Market Activity: An Evaluation of Alternative Explanations. American Economic Review, vol.87(4), 705-727. [7] Becker, G.S. (1973). A Theory of Marriage: Part I. Journal of Political Economy, vol.81(4), 813-846. [8] Becker, G.S. (1981). A Treatise on the Family. Cambridge, MA: Harvard University Press. [9] Becker, G.S., Landes E.M. & Michael R.T. (1977). An Economic Analysis of Marital Instability. Journal of Political Economy, vol.85(6), 1141-1187. [10] Bisin, A. & Verdier, T. (2000). Beyond the Melting Pot: Cultural Transmission, Marriage, and the Evolution of Ethnic and Religious Traits. Quarterly Journal of Economics.vol.115(3), 955-988. [11] Bloch, L. (1929). Facts about Mexican Immigration Before and Since the Quota Restriction Laws. Journal of the American Statistical Association, vol.24(165), 50-60. [12] Bodnar, J. (1985). The Transplanted: A History of Immigrants in Urban America. Indiana: Indiana University Press. [13] Bratter, J.L. & Eschbach, K. (2006). `What about the Couple?' Interracial Marriage and Psychological Distress. Social Science Research, vol.35(4), 1025-1047. [14] Bratter, J. L., & King, R. B. (2008). But Will It Last?: Marital Instability Among Interracial and Same-Race Couples. Family Relations, vol.57(2), 160-171. [15] Bratter, J.L. & Zuberi K. (2007). The Demography of Dierence: Shifting Trends of Racial Diversity and Interracial Marriage 1960-1990. Race and Society ,vol.4(2), 133-148. [16] Celikaksoy, A., Nielsen, H. S., & Verner, M. (2006). Marriage Migration: Just Another Case of Positive Assortative Matching? Review of Economics of the Household, vol.4(3), 253-275. [17] Chiswick, B.R. & Houseworth, C. (2011). Ethnic Intermarriage among Immigrants: Human Capital and Assortative Mating. Review of Economics of the Household, vol.9(2), 149-180. [18] England, P. & Folbre, N. (1999) .The Cost of Caring. Annals of the American Academy of Political and Social Science, vol.561(1), 39-51 [19] Foerster, R.F. (1924). Italian Emigration of Our Times. Cambridge, MA: Harvard University Press. [20] Frimmel, W., Halla, M. & Winter-Ebmer, R. (2013). Assortative Mating and Divorce: Evidence from Austrian Resigster Data. Journal of the Royal Statistical Society: Series A (Statistics in Society), vol.176(4), 907-929. [21] Furtado, D. & Theodoropoulos, N. (2007). Interethnic Marriage Decisions: A Choice between Ethnic and Educational Similarities. CReAM Discussion Paper 16/07.

18 [22] Gilbertson, G.A., Fitzpatrick, J.P. & Lijun, Y. (1996).Hispanic Intermarriage in New York City: New Evidence from 1991. International Migration Review, vol.30(2), 445-59. [23] Gibson, C.J. & Lennon E. (1999).Historical Census Statistics on the Foreign-born Population of the United States: 1850-1990.U.S. Bureau of the Census: Population Division Working Paper No.29. [24] Grossbard-Shechtman, S. (1985). Marriage Squeezes and the Marriage Market, in Kingsley Davis and Amyra Grossbard-Shechtman, eds., Contemporary Marriage: Comparative Perspectives on a Changing Institution.New York: Russell Sage Publication. [25] Grossbard-Shechtman, S. (1993). On the Economics of Marriage: A Theory of Marriage, Labor, and Divorce. Boulder: Westview Press. [26] Haines, M.R. (1996). Long-Term Marriage Patterns in the United States from Colonial Times to Present. History of the Family, vol.1(1), 15-39. [27] Hutchinson, E.P. (1956). Immigrants and Their Children, 1850-1950. New York: John Wiley & Sons. [28] Johnson, W. R. & Skinner, J. (1986). Labor Supply and Marital Separation. American Economic Review, vol.76(3), 455-469. [29] Jones, F. L. (1994). Are marriages that cross ethnic boundaries more likely to end in divorce?. Journal of the Australian Population Association,vol.11(2), 115-132. [30] Jones, F. L. (1996). Convergence and divergence in ethnic divorce patterns: A research note. Journal of Marriage and the Family, vol.58(1), 213-218. [31] Kalmijn,M.(1998). Intermarriage and Homogamy: Causes, Patterns, Trends. Annual Review of Sociol- ogy, vol.24, 395-421. [32] Kalmijn, M., de Graaf, P. M., & Janssen, J. P. (2005). Intermarriage and the risk of divorce in the Nether- lands: The eects of dierences in religion and in nationality, 197494. Population studies, vol.59(1), 71-85. [33] Kalmijn, M. & van Tubergen, F. (2010). A Comparative Perspective on Intermarriage: Explaining Dierences Among National-Origin Groups in the United States. Demography, vol.47(2), 459-479. [34] Lafortune, J. (2013). Making Yourself Attractive: Pre-Marital Investments and the Returns to Education in the Marriage Market. American Economic Journal: Applied Economics, vol.5(2), 158-178. [35] Lunderg, S. (2010). Personality and Marital Surplus. Discussion Paper. [36] Massey, D.S. (1995). The New Immigration and Ethnicity in the United States. Population and Devel- opment Review, vol. 21(3), 631-652. [37] Meng X. & Gregory R.G. (2005). Intermarriage and the Economic Assimilation of Immigrants. Journal of Labor Economics, vol.23(1), 135-175. [38] Ng, E., & Nault, F. (1997). Fertility among recent immigrant women to Canada, 1991: An examination of the disruption hypothesis. International Migration, vol.35(4), 559-580. [39] Pagnini, D.L. & Morgan S.P. (1990). Intermarriage and Social Distance among U.S. Immigrants at the Turn of the Century. American Journal of Sociology, vol.26(2), 405-432. [40] Parkman, A.M. (1992). Unilateral Divorce and the Labor Force Participation Rate of Married Women, Revisited. American Economic Review, vol.82(3), 671-678. [41] Qian, Z. (1997). Breaking the Racial Barriers: Variations in Interracial Marriage between 1980 and 1990. Demography, vol.34(2), 263-276. [42] Qian, Z., Blair, S. L., & Ruf, S. D. (2001). Asian American Interracial and Interethnic Marriages: Dierences by Education and Nativity. International Migration Review, vol.35(2), 557586.

19 [43] Schoen, R., & Wooldredge, J. (1989). Marriage choices in North Carolina and Virginia, 1969-71 and 1979-81. Journal of Marriage and the Family, vol.51(2), 465-481. [44] Wildsmith, E., Myron, P. G. & Gratton, B. (2003). Assimilation and Intermarriage for U.S. Immigrant Groups, 1880-1990. History of the Family, vol.8(4), 563-584. [45] U.S. Census Bureu (2010). Overview of Race and Hispanic Origin: 2010. [46] Willcox, W.F. (1931). Immigration into the United States, Chapter II in W.F. Willcox, ed., Interna- tional Migrations, Volume II: Interpretations. New York: National Bureau of Economic Research.

20 Figure 1. Great Migration of the United States: 1900-1930

Data: Annual Report of the Commissioner General of Immigration, Department of Labor [1900, 1930].

21 Table 1: Annual Arrivals of Immigrants 1890-1928

Fiscal year Arrivals Fiscal year Arrivals Fiscal year Arrivals 1890 364,086 1904 606,019 1918 55,191 1891 448,403 1905 809,847 1919 62,306 1892 445,987 1906 925,011 1920 334,310 1893 343,422 1907 1,123,842 1921 652,909 1894 219,046 1908 689,474 1922 279,598 1895 190,928 1909 733,267 1923 391,316 1896 263,709 1910 912,026 1924 421,785 1897 180,556 1911 749,642 1925 241,319 1898 178,748 1912 726,040 1926 271,371 1899 242,573 1913 1,044,457 1927 300,136 1900 341,712 1914 1,008,750 1928 294,088 1901 388,931 1915 243,370 Total 18,018,759 1902 565,983 1916 176,611 1903 631,885 1917 160,105 Reproduced from Annual Report of the Commissioner General of Immigration Fiscal Year Ended June 30 1928, Department of Labor.

22 Table 2: By Ethnicity: Number of Immigration and Population during 1900-1930

1900-1909 1910-1919 1920-1929

Percent Percent Populat- Percent Number of Population of Im- Number of Population of Im- Number of Population of Imm- Ethnicity immigrants in 1910 migrants immigrants in 1920 migrants immigrants in 1930 migrants Dutch 72,786 120,063 60.62 88,328 131,766 67.03 57,209 133,133 42.97 English 841,028 2,573,534 32.68 857,327 2,172,714 39.46 1,089,374 2,147,733 50.72 Finnish 129,941 129,680 100.2 75,600 149,824 50.46 18,038 142,478 12.66 Former Austro- Hungarian 1,037,390 1,670,582 62.01 525,236 1335348 39.33 164525 1,137,002 14.47 French 92,398 117,418 78.69 172,436 153,072 112.7 240,260 135,592 177.2 German 656,363 1,137,002 57.73 409,725 1,686,108 24.30 482,810 1,608,814 30.01 Greek 175,432 101,282 173.21 263,560 175,976 149.8 69,280 174,526 39.70 Italian 1,982,418 1,343,125 147.6 1,290,899 1,610,113 80.17 539,178 179,0429 30.11 Japanese 142,536 67,744 210.4 77,257 81,502 94.79 40,207 70,993 56.64 Mexican 23,991 221,915 10.81 173,663 486,418 35.70 480,804 641,462 74.95 Polish 792,250 937,884 84.47 600,055 1,139,979 52.64 79,706 1,268,583 6.280 Portuguese 63,144 59,360 106.4 78,413 69,981 112.1 46,421 73,164 63.45 Romanian 68,409 87,434 78.24 68,279 102,823 66.40 13,454 146,393 9.190 Russian 328,233 1,602,782 20.48 419,308 1,400,495 29.94 43,590 1,153,628 3.780 Scandinavian 511,020 1,250,733 40.86 284,440 1,148,602 24.76 228,185 1,125,340 20.28 Spanish 44,218 22,108 200.0 85,197 49,535 172.0 64,201 59,308 108.3 Turkish 11,643 91,959 12.66 9,230 16,303 56.62 1,606 48,911 3.280

23 Table 3: By Ethnicity and Gender: Single Immigrants during 1910-1919 and 1920-1929

1910-1919 1920-1929 Single Sex ratio Single Sex ratio Single male female of single Single male female of single Ethnicity immigrants immigrants immigrants7 immigrants immigrants immigrants Dutch 37,453 17,127 2.19 20,381 12,767 1.60 English 108,573 99,208 1.09 141,665 133,666 1.06 Finnish 34,837 21,729 1.60 5,621 6,892 0.82 Former Austro- Hungarian 34,044 33,008 1.03 10,157 10,321 0.98 French 63,452 44,361 1.43 93,348 66,365 1.41 German 153,054 110,539 1.38 192,189 152,699 1.26 Greek 151,881 19,040 7.98 22,334 14,672 1.52 Italian 87,643 28,422 3.08 31,847 15,430 2.06 Japanese 18,722 4,824 3.88 9,540 3,998 2.39 Mexican 64,360 33,819 1.90 193,826 73,906 2.62 Polish 231,868 159,075 1.46 21,632 24,990 0.87 Portuguese 28,304 18,448 1.53 19,807 7,493 2.64 Romanian 14,626 4,788 3.05 4,227 3,328 1.27 Russian 69,963 14,604 4.79 10,132 5,504 1.84 Scandinavian 150,925 81,853 1.84 118,594 60,761 1.95 Spanish 45,217 8,273 5.47 33,107 5,828 5.68 Turkish 5,294 271 19.54 663 254 2.61

Notes: Data are from Annual Report of the Commissioner General of Immigration, Department of Labor [1910, 1929].

7The sex-ratio is dened as the number of male individuals divided by the number of female individuals. 24 Table 4a: Summary Statistics: By Generation of Immigrants

Husbands Wives Foreign Second Foreign Second All households born generation born generation in sample Age 35.7 34.5 32.3 31.1 (6.00) (56.3) (6.43) (6.52) N 54,690 30,274 48,963 36,001 Number of children in household 2.54 1.96 2.57 2.01 2.33 (1.98) (1.77) (1.99) (1.79) (1.93) N 54,690 30,274 48,963 36,001 84,964 In the labor force 0.990 0.989 0.072 0.052 (0.100) (0.104) (0.258) (0.223) N 54,690 30,274 48,963 36,001 66,491 Own house 0.319 0.385 0.308 0.389 0.342 (0.466) (0.487) (0.461) (0.488) (0.474) N 54,386 30,180 48,678 35,888 84,556 Can read and write 0.878 0.990 0.809 0.9878 (0.326) (0.101) (0.393) (0.110) N 54,690 30,274 48,963 36,001 Grannies in household 0.049 0.080 0.045 0.080 0.060 (0.215) (0.272) (0.207) (0.272) (0.237) 54,690 30,274 48,963 36,001 84,964 Urban dummy 0.792 0.674 0.796 0.6878 0.750 (0.405) (0.469) (0.403) (0.463) (0.433) N 54,690 30,274 48,963 36,001 84,964 Standard error in bracket. Data source: Data source: 1910, 1920 and 1930 Census of Population, Public Use Microdata Sample, one percent sample.

25 Table 4b: Summary Statistics: By Endogamous and Exogamous Marriages

Endogamous Exogamous Endogamous Exogamous Marriages Marriages Marriages Marriages Age of husband 35.4 34.7 Own house 0.344 0.334 (4.94) (4.97) (0.475) (0.472) N 70,113 14,851N 69,766 14,800 Age of wife 31.9 31.3 Husband can read and write 0.905 0.979 (6.52) (6.39) (0.293) (0.145) N 70,113 14,851N 70,113 14,851 Number of children Wife can read and in household 2.44 1.85 write 0.866 0.975 (1.96) (1.70) (0.341) (0.157) N 70,113 14,851N 70,113 14,851 Husband in the labor force 0.99 0.99 Grannies in household 0.057 0.073 (0.10) (0.10) (0.232) (0.260) N 70,113 14,851N 70,113 14,851 Wife in the labor force 0.063 0.064 Urban dummy 0.744 0.782 (0.244) (0.245) (0.437) (0.413) N 70,113 14,851N 70,113 14,851 Notes: Standard error in bracket; data source: Data source: 1910, 1920 and 1930 Census of Population, Public Use Microdata Sample, one percent sample.

26 Table 5: Percentage of Endogamous Marriage for First and Second Generation Men Men Marrying Non-natives

First Generation Second Generation Ethnicity 1910N 1920N 1930N 1910N 1920N 1930N Dutch 33.33 55.69 0.006 50.02 39.3 28 25.0 12 English 91.7 2590 89.2 1850 88.5 1679 74.2 3051 66.0 2428 60.6 2297 Finnish 95.5 222 92.4 290 94.8 192 85.77 95.0 20 75.0 84 Former Austro- Hungarian 93.9 3107 89.2 2779 85.7 1915 71.8 294 67.7 594 63.4 1070 French 73.0 115 63.9 144 58.1 117 11.4 105 16.2 154 14.6 137 German 88.7 3066 76.5 1339 81.4 1247 80.0 4425 70.4 3646 66.3 3678 Greek 69.4 36 76.4 208 73.4 354-0 0.004 0.004 Italian 97.4 2302 96.7 3574 94.9 4035 67.1 82 67.6 250 77.0 897 Japanese 97.1 139 99.0 311 99.1 226-0 1002 100 28 Mexican 99.3 269 99.2 654 99.0 982 97.7 88 95.1 82 97.3 184 Polish 87.7 171 90.5 2981 87.3 2744 47.6 21 71.7 499 75.5 878 Portuguese 97.0 133 97.3 226 92.9 210 66.7 18 72.9 48 74.0 104 Romanian 74.7 91 63.9 233 62.3 263 0.002 28.67 29.5 44 Russian 91.4 3190 87.4 3527 80.5 2895 78.0 127 72.5 403 69.2 1099 Scandinavian 89.4 1676 86.0 1276 85.2 1002 76.5 665 72.2 1178 64.7 1532 Spanish 69.6 23 82.4 57 70.8 106 0.006 0.003 20.0 15 Turkish 93.2 73 75.0 32 77.7 121-0-0 1001 Total 17,206 19,490 18,094 8,893 9,346 12,064 Author's calculation. Data source: 1910, 1920 and 1930 Census of Population,Public Use Microdata Sample, one percent sample Public Use Microdata Sample, one percent sample.

27 Table 6: First Stage Regression Results: Estimate of Equation (2)

Coecients Coecients Coecients Coecients of IV(1) of IV(1) of IV(2) of IV(2) OLS Logit OLS Logit Independent Variables8 (1) (2) (3) (4) Dutch -1.065* (0.578) -0.594 (0.408) 0.941* (0.521) 0.519 (0.373) English 0.319 (0.366) 0.077 (0.245) 0.039 (0.061) 0.079* (0.048) Finnish 0.165*** (0.043) 0.081 (0.069) -0.133*** (0.027) -0.076* (0.043) Former Austro-Hungarian 0.028 (0.021) 0.012 (0.019) -0.087*** (0.023) -0.062*** (0.022) French 0.003 (0.132) -0.046 (0.071) 0.030 (0.040) 0.043* (0.021) German -1.506*** (0.015) -0.931*** (0.019) 0.137 (0.193) 0.215 (0.137) Greek 0.036 (0.026) 0.042*** (0.016) -0.054* (0.031) -0.060 (0.020) Italian 0.085*** (0.007) 0.040*** (0.011) -0.110*** (0.008) -0.061*** (0.012) Turkish 0.083*** (0.123) 0.074 (0.082) 0.030 (0.040) -0.118 (0.103) Spanish 0.073 (0.103) 0.084 (0.057) -0.082** (0.081) -0.087** (0.044) Polish 0.165*** (0.032) 0.150*** (0.031) -0.121*** (0.020) -0.108*** (0.020) Portuguese -0.476*** (0.184) 0.443 (0.330) -0.103** (0.048) -0.010*** (0.063) Romanian -0.003 (0.132) 0.044* (0.023) -0.028 (0.060) -0.084*** (0.032) Russian 0.036 (0.040) 0.074** (0.032) -0.089** (0.039) -0.118*** (0.034) Scandinavian 0.215 (0.171) 0.145 (0.146) -0.185*** (0.056) -0.149*** (0.048) Japanese 0.086*** (0.009) 0.165 (0.042) -0.147*** (0.012) -0.234*** (0.053) Mexican -1.866*** (0.019) -0.140 (0.100) 0.194*** (0.018) 0.142* (0.082) N 84,964 84,964 84,964 84,964 F-statistics (OLS)/ 26.32 105.9 26.07 83.84

χ2test (Logit) for inclusion of instruments

Notes:*** variable is statistically signicant at 1 % level;**variable is statistically signicant at 5 % level; a variable is statistically

signicant at 10 % level; The Logit estimates are marginal eects evaluated at sample means. Robust standard errors clustered at

the ethicity-year level are in brackets. Additional regressors for all equations include quadratics in age for both the wife and hus-

band, an urban indicator, literacy level of the wife and husband, a dummy indicates the wife and husband are second generation,

years of residence of the husband in the US, indicator of residence with parents of either he wife or the husband ethnicity and oc-

cupation indicators for the husband, state dummies and census year dummies. The coecients for the Logit models provide the

marginal eects of the instruments at the means of the independent variables.

8 The results for the rst 15 independent variables represent estimates for the vectorτ1 in equation 2 and 3. 28 Table 7: Estimates for Equation (1): All Sample Panel A Eects of Endogamous Marriage OLS Poisson Possion Possion IV(1) IV(2) Dependent Variable (1) (2) (3) (4)N Number of children in household 0.230*** 0.121*** 1.680*** 3.38 84,964 (0.035) (0.016) (0.453) (2.30)

Panel B Eects of Endogamous Marriage OLS Logit 2SLS(1) NL2S(1) 2SLS(2) NL2S(2) Dependent Variables (1) (2) (3) (4) (5) (6)N Home ownership 0.032*** 0.035*** 0.322* 0.262*** 0.367* 0.279*** 84,566 (0.007) (0.007) (0.167) (0.063) (0.211) (0.069) Labor force participation of husband 0.001* 0.001* 0.0035 -0.003 0.007 -0.003 84,964 (0.0008) (0.0008) (0.013) (0.009) (0.015) (0.009) Labor force participation of wife -0.007** -0.007** -0.246*** -0.122*** -0.387*** -0.130*** 84,964 (0.003) (0.003) (0.091) (0.044) (0.109) (0.045)

Notes: ***variable is statistically signicant at 1% level; **variable is statistically signicant at 5% level; *variable is statistically signicant at 10% level. Robust standard errors clustered at the ethicity-year level are in brackets. The logit estimates are marginal eects evaluated at the sample mean.

29 Table 8: Robustness Checks Panel A Eect of Endogamous Marriage Possion IV(1) European Excluding Household Including Including Only Austro- heads ethnic ethnic Hungarian age 20-40 sex ratio predicted only age 16-45 sex ratio age 16-45

Dependent Variables (1) (2) (3) (4) (5) Number of children 1.026*** 1.658*** 1.020*** 1.246*** 1.361*** in household (0.268) (0.556) (0.261) (0.349) (0.380)

N 81,965 73,192 65,055 84,964 84,964

30 Panel B Eect of Endogamous Marriage NL2S(1) European Excluding Household Including Including Only Austro- heads ethnic predicted Hungarian age 20-40 sex ratio ethnic only age 16-45 sex ratio age 16-45 Dependent Variables (1) (2) (3) (4) (5) Home ownership 0.267*** 0.214*** 0.197*** 0.264*** 0.251*** (0.072) (0.071) (0.053) (0.063) (0.063) N 81,588 72,883 64,733 84,566 84,566 Labor force participation of husband -0.013 -0.007 -0.001 -0.003 -0.002 (0.008) (0.010) (0.010) (0.009) (0.009) N 81,965 73,192 65,055 84,964 84,964 Labor force participation of wife -0.110** -0.125** -0.135*** -0.094** -0.112*** (0.043) (0.052) (0.047) (0.042) (0.042) N 81,965 73,192 65,055 84,964 84,964

Notes: ***variable is statistically signicant at 1% level; **variable is statistically signicant at 5% level;

*variable is statistically signicant at 10% level. Robust standard errors clustered at the ethicity-year level are in brackets. The Logit estimates are marginal eects evaluated at the sample mean.

31 Appendix A: Grouping of Ethnicity Ethnicity is recoded into 17 categories.Individuals are grouped by their place of birth or the place of birth of their parents in the Census data. If the individual was native born and both his parents are foreigners, he would be categorized into the ethnic group of his mother as second generation.The followings are the places of birth in Census that can be merged with the ethnic groups with the data on the immigration ows from the Annual Report of the Commissioner General of Immigration.

Classication for Ethnicity of Immigrants from the Annual Report of the Commissioner General of Immigration: By Race/People Race/People Ethnicity Bohemian and Moravian (Czech) Former Austro-Hungarian Croatian and Slovenian Former Austro-Hungarian Dalmatian, Bosnian, Herzegovinian Former Austro-Hungarian Dutch and Flemish Dutch English English (Anglophone) Finnish Finnish French French German German Greek Greek Irish English (Anglophone) Italian North Italian Italian South Italian Japanese Japanese Lithuanian Russian Magyar Former Austro-Hungarian Mexican Mexican Polish Polish Portuguese Portuguese Rumanian Romanian Russian Russian Ruthenia Russian Scandinavian Scandinavian Scotch English (Anglophone) Spanish Spanish Turkish Turkish Welsh English (Anglophone) 32 Classication for Ethnicity of Immigrants from Historical Census Statistics: By Country of Birth of the Foreign-Born Population Country Ethnicity Country Ethnicity England English (Anglophone) Mexico Mexican Scotland English (Anglophone) Lithuania Russian Wales English (Anglophone) Russia Russian Northern Ireland English (Anglophone) Denmark Scandinavian Irish Free State English (Anglophone) Finland Finnish Netherlands Dutch Iceland Scandinavian Austria Former Austro-Hungarian Norway Scandinavian Hungary Former Austro-Hungarian Sweden Scandinavian Poland Polish Portugal Portuguese Rumania Romanian Spain Spanish France French Greece Greek Germany German Turkey Turkish Italy Italian Japan Japanese

33 Classication for Ethnicity from IPUMS Census Data: By Country of Birth Country Country Code Code in Census Country Ethnicity in Census Country Ethnicity 200 Mexico Mexican 436 Portugal Portuguese 400 Denmark Scandinavian 438 Spain Spanish 401 Finland Finnish 450 Austria Former Austro-Hungarian 402 Iceland Scandinavian 452 Czechsolovakia Former Austro-Hungarian 404 Norway Scandinavian 453 Germany German 405 Sweden Scandinavian 454 Hungary Former Austro-Hungarian 410 England English (Anglophone) 455 Poland Polish 411 Scotland English (Anglophone) 456 Romania Romanian 412 Wales English (Anglophone) 455 Poland Polish 413 United Kingdom English (Anglophone) 456 Romania Romanian 414 Ireland English (Anglophone) 462 Lithuania Russian 421 France French 465 Russia Russian 425 Netherlands Dutch 501 Japan Japanese 433 Greece Greek 542 Turkey Turkish 434 Italy Italian