1 / 58

A Nation of Immigrants: Assimilation and Economic Outcomes in the Age of Mass Migration

A Nation of Immigrants: Assimilation and Economic Outcomes in the Age of Mass Migration. Larger project: age of mass migration (1850-1913). We construct large panel datasets to analyze economic decisions & outcomes of trans-Atlantic migrants Linking migrants across population censuses

qamar
Download Presentation

A Nation of Immigrants: Assimilation and Economic Outcomes in the Age of Mass Migration

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A Nation of Immigrants:Assimilation and Economic Outcomes in the Age of Mass Migration

  2. Larger project: age of mass migration (1850-1913) • We construct large panel datasets to analyze economic decisions & outcomes of trans-Atlantic migrants • Linking migrants across population censuses • Possible with historical censuses: “72-year rule” allows to link people by name, age, birthplace • Origin (Europe : Norway): compare migrants with stayers • Identifying selection of migrants using sibling-pairs • Role of childhood environment in migration • Destination (US): compare migrants and 2nd generation migrants from 16 European countries with US natives • Today’s paper: migrants’ performance in US

  3. Why focus on this period? • Mass migration episode: European countries lost quarter of their population through mass migration. In 1910, 22% of US labor force was foreign born • Large enough to affect labor supply and economic development on both sides of the Atlantic • US open border policy allows us to focus on migrant decisions, free of immigrant selection policies

  4. Question 1: How did European immigrants perform relative to US natives? • How did migrants perform in labor markets upon first arrival? Did migrants converge to natives? • Convergence: a migrant starts below natives & catches up over time • How did their children fare in the US labor market? • Economic outcome is occupation. We match occupation to median earnings [details later] • Limitation: only capture convergence in occupations, not within-occupation income convergence

  5. Question 2: How were return migrants selected from migrant pool? • Were return migrants positively or negatively selected from the migrant pool? • Important because over 25% of migrants returned home (Gould, 1980; Bandiera, Rasul & Viarengo, 2010) • Conceptually, nature of selection of return migrants is ambiguous • Negatively selected: If migrants who were not successful in US returned home • Positively selected: If migrants intended to go back home, and more productive migrants reached “saving targets” faster

  6. Why challenging to address these basic questions? • Because of a lack of historical panel dataset • Previous literature mostly relies on cross-sectional data • Inferring convergence from a cross section raises well-known biases (Borjas 1985, Duleep & Dowhan 2002, Lubotsky 2007) • We construct panel of 24,000 men from 16 sending countries in 1900-1920 using census manuscripts (in Ancestry, then digitizing)

  7. Paper in a nutshell: Inferring convergence from the data Data Wage 25 years Panel A A A 100 B 80 Repeated cross-section Cross-section Same immigrationcohort 60 D C 40 5 years Year 1900 1920 1895 1915 Immigrants A and Barrived in 1895 and stayed Immigrants C and Darrived in 1915 and stayed Convergence Wage A A 100 Decline in cohortquality Negatively selectedreturn migration Panel 90 A,B A,B RCS CS 50 C,D 25 Years in US 5

  8. Rest of the talk A word on historical context Building a panel dataset, 1900-20 Results for full immigrant population Results by country of origin Mechanisms Outcomes of the 2nd generation Assimilation through marriage

  9. “New immigrants” and assimilation Big concerns in US at the time about migrants Migrants have low natural intelligence Poverty in immigrant neighborhoods and low levels of school attendance of immigrant children Nativist view: new arrivals would not be able to assimilate Progressive reformer view: immigrant behavior could be changed Initiated public legislation, including child labor laws and schooling requirements to aid immigrant communities

  10. Assimilation and temporary migration Immigration Commission (1911) concluded that migrants (especially from Southern/Eastern Europe) would not be able to assimilate Concluded that immigration was a threat to economic and social fabric of the US Temporary migration in part to blame “If an immigrant intends to remain permanently in the US and become an American citizen, he naturally begins at once… to fit himself for the conditions of his new life…If, on the other hand, he intends his sojourn in this country to be short… acquisition of the English language will be of little consequence… The chief aim of a person with this intention is to put money in his purse… not for investment here but for investment in his home country.” -- Jenks and Lauck, Dillingham Commission investigators (1922) Provided fuel for literacy test (1917) & quotas (1924)

  11. Building panel dataset • Panel of 24,000 native and immigrant men from 16 sending countries • Ages 18-35 in 1900; immigrants arrived before 1900; exclude US south • We use iterative procedure to match individuals by name, age and place of birth from 1900 to 1910/20 • Note: need to be able to search complete 1910/20 censuses for procedure (use Ancestry, then digitize) • Match rates: 19% of natives, 13% foreign-born (to both 1910 & 1920) • Illustrating our matching procedure • Is matched sample representative of population? [details]

  12. Estimating migrant-native convergence • Estimate age-earnings profiles using cross-sections, repeated cross-sections, panel • Outcome = occupation score. Occupation-based earnings, expressed in 2010 dollars. 125 occupations [details] • Occupation score = f(age, Census yr, country-of-origin and…) • Years in the US indicators aggregated to 5-yr intervals • Arrival cohort indicator (before/after 1890) j = country of origin; m = year of arrival; t = Census year; t-m = years spent in US • Regressions: Tables

  13. Figure 2: Convergence in occupation score between immigrants and native-born workers by years spent in the US Years in the US

  14. Figure 2: Convergence in occupation score between immigrants and native-born workers by years spent in the US Years in the US Cohort quality

  15. Figure 2: Convergence in occupation score between immigrants and native-born workers by years spent in the US Negatively selected return migration Years in the US Cohort quality

  16. Alternative specifications [details] • Concern: other sources of selective attrition [details] • Drop immigrants who arrived as children • Interact country FE * arrival cohort dummies • Match occupations to 1900 earnings [details] • Subdivide into finer arrival cohorts • Robustness to farmers’ earnings • Add state FE and state FE * urban area (endogenous, but can shed light on mechanism) • Compare earning distributions of migrants and natives • Log(occupation-based earnings) instead of occupation-based earnings

  17. Heterogeneity across countries • Permanent immigrants from five countries held higher-paid occupations than US natives upon first arrival • English-speaking countries: England, Scotland, Wales, plus Russia and France • Permanent migrants from six countries held lower-paid occupations than US natives • Permanent migrants from most sending countries appear to experience occupational upgrading over time similar to natives • Heterogeneity by country is important to consider…

  18. Figure 3: Occupation-based earning gap, permanent immigrants upon first arrival (0-5 years in US) vs. natives by country of origin. Panel data

  19. Figure 3: Occupation-based earning gap, permanent immigrants vs. natives upon first arrival (0-5 years in US) and after 30+ years, by country of origin. Panel data

  20. Selection of return migrants by country • We infer selection of return migrants by comparing convergence in panel and repeated C-S • Significantly negatively selected return to five countries (England, Italy, Norway, Russia and Switzerland) • Significantly positively selected return to one country (Finland) • Adjust for (small) differences in return rates: multiply each coefficient by the ratio of the average migration rate to the country’s actual migration rate • Magnitudes do not change • Exception: even more negative selection to Russia

  21. Figure 5: Implied selection of return migrants, by country of origin. Difference between estimated convergence in panel and repeated cross-section data

  22. Direct evidence on return migration to Norway • 1910 Norwegian census added supplement: return migrants were asked when they moved to US, when they returned, and occupation held in US • We compare US occupational distribution in 1910 of Norwegian migrants who stayed in US vs. returned • Migrants who returned had occupations paying $1,659 less on average • Remarkably similar to indirect inference from comparing panel and repeated cross section (-$1,757)

  23. Explaining cross-country variation in immigrant performance[details] • Regress country coefficients on country characteristics • Note: Only 16 countries and no exogenous variation, so these relationships are merely suggestive • Migrant countries that fared better in US: • had higher real wages in 1880 • had more similar culture, language and religious • Low correlation between countries performance in US and: • population pressure (rates of natural population increase) • health conditions (measured by infant mortality)

  24. 2nd generation migrants • How do 2nd generation migrants perform in US labor markets? • Convergence may take more than one generation • 2nd generation migrants educated in US: likely fluent in English and possibly exposed to US norms and culture • Differences can persist over generations: if lived in migrant enclaves or inherited occupational skills from parents • We find persistence over generations: if 1st generation out- (under-)performs natives, so does 2nd generation

  25. Assimilation of 2nd generation migrants

  26. Assimilation of 2nd generation migrants

  27. Assimilation of 2nd generation migrants

  28. Assimilation of 2nd generation migrants

  29. Difference in predicted occupational score between migrants (1st and 2nd generation) and natives Predicted values are for males aged 35 in 1910 and who immigrated in 1890 (for 1st generation)

  30. Assimilation through marriage [details] • What about cultural assimilation of immigrants? Look at inter-marriage between immigrants and US natives • Endogamy could reflect preferences or constraints • We find strong endogamy among 1st generation immigrants; less endogamy among 2nd generation • Strong cross-country persistence of in-group marriage rates across generations • Migrants from countries with better-paid occupations somewhat less likely to marry within same country

  31. Conclusions • Contrary to conventional wisdom, in early 20th century, long term migrants: • didn’t hold lower-paid occupations than US natives • experienced similar occupational upgrading over time • Apparent convergence in CS data between immigrants and natives driven by: • lower occupational quality of later immigrant cohorts • lower occupational quality of temporary/return migrants • Substantial variation by country • Persistence in labor & marriage patterns over generations

  32. Other sources of selective attrition Any form of selective attrition of migrants vs. natives could drive assimilation-pattern differences between panel and repeated CS: Selective mortality: Quantitatively less important than return migration For natives, repeated cross sections are similar to panel, implying selective mortality is non-issue for them Direct data on mortality by country of origin and by occupation (from death registries)

  33. Other sources of selective attrition [back] • Selective name changes: • Name changes that occurred upon entry to US (before we first observe migrants) are non-issue • Men who changed name between censuses would not be in panel but stay in repeated CS before & after name change • Foreign-born men in panel have slightly more “foreign” names than their foreign-born counterparts in the CS • An indication they may have changed name • Difference in the “foreignness” index is associated with only a $60 difference in occupation-based earnings

  34. Other sources of selective attrition [back] • The “foreignness” index: first calculating probability of being foreign born conditional on having a given first name (and, separately, a given last name) in the 1900-20 IPUMS samples • The “foreignness” index is then the sum of the two probabilities; the index varies between zero and two. Foreign-born men in the cross-section (panel sample) have an index value of 1.13 (1.23)

  35. Matching procedure • Potential 1900 population to be matched: • Men aged 18-35 • Small sending countries: find all migrants who moved to US between 1880-1900 • Big sending countries and natives: start with all migrants in 5% Integrated Public Use Microdata Series (IPUMS) sample

  36. Matching procedure STEP 1: Standardize first and last names of men in 1900 sample to address orthographic differences between phonetically equivalent names • using the NYSIIS algorithm (Atack & Bateman,1992) • Men who are unique by first and last name, birth year, and place of birth (state or country) in 1900 become candidates for our matching procedure

  37. Matching procedure STEP 2: Identify potential matches in 1910 and 1920 • by searching for all men in our 1900 sample in the 1910 and 1920 Census manuscripts • For small sending countries, we compile complete populations of men with relevant sample characteristics in 1910 and 1920 • For large sending countries and native born, we use the (expansive) Ancestry.com algorithm to search for candidate matches in 1910 and 1920; this search returns many potential matches for each case, which we cull using the iterative match procedure described in the next step

  38. STEP 3. Iterative matching procedure • We start by looking for a match by first name, last name, place of birth (state or country) and reported birth year • Three possibilities: • If find a unique match, stop and consider the observation “matched” • If find multiple matches for same birth year, observation is thrown out • If do not find a match, we try matching first within a one-year band (older and younger) and then with a two-year band around the reported birth year; only accepts unique matches • If these attempts do not produce a match, observation is thrown out

  39. Table 1: Match rates by country [back]

  40. Occupation-based earnings • No individual information about wages or income in 1900-20 Census; only occupation is observed • We collect occupation string by hand from the historical manuscripts on Ancestry.com • How to use occupations meaningfully? • Assign individuals median income in their reported occupation from 1950 income distribution (“OCCSCORE” variable) • Other ways: social class, education required, etc

  41. Occupation-based earnings [back] • Reliance on occupation-based earnings in 1950 is a concern. The decades of the 1940s and 1950s were a period of wage compression (Goldin and Margo, 1992) • For example, if immigrants were clustered in low-paying occupations, the occupation score variable may understate both their initial earnings penalty and the convergence implied by moving up the occupational ladder  • To address this concern, we match our occupations to the 1901 Cost of Living survey (which has several disadvantages). We get larger initial penalty, but otherwise similar results

  42. Table 2: Common occupations for natives and foreign-born in matched samples, 1920 [back]

  43. Is matched sample representative of population? Men in both panel and repeated CS must have survived and remained in US until 1920 By 1920, up to sampling error: any difference between cross-section and panel (given age 38-55; arrive by 1900) due to imperfect matching Concern: men with uncommon names and consistent age reporting are more likely to be successfully linked between Censuses. Both may be correlated with socio-economic status

  44. Table 3: Comparing matched samples with the population, 1920 [back]

  45. [back]

  46. [back]

  47. Alexander James in 1900

  48. Alexander James in 1910

  49. Alexander James in 1920 [back]

  50. Mass migration from Europe 1850-1913 [back]

More Related