1. Turmunkh Zorigt ‘18 Isaac Tucker-Rasbury ‘18
Professor Fernando Lozano
Pomona College
To understand the success of immigrants in a host economy, Economists have highlighted the importance of differentiating between
years in the host economy (tenure) and year of migration (cohort). The year of migration remains a crucial source of information, since its
availability allows one to account for cohort effects. Groups of migrants from distinct sets of years have different assimilation
characteristics, and consequently calculating them as separate inputs is needed to create a more accurate model by using year of
immigration. Unfortunately, most data sets for countries other than the U.S. do not provide information on this. We use cross sectional
microdata from the host country of immigrants in the United States to estimate when migrants moved into Brazil and South Africa. By
utilizing ordinary least squares, this methodology allows for comparing immigrant economic assimilation across different
countries. Future applications of this methodology could allow comparisons across various additional countries.
Estimating
Year
of
Immigration
of
People
in
Brazil
and
South
Africa
Results:
Main idea:
Intro:
The model overestimates the years of immigration in both
countries. In order to create a better model, one could
include more variables to regress or apply a more accurate
econometric tool that would not be susceptible to the
necessary assumptions of using ordinary least squares.
Conclusion:
Our aim is to create a model that predicts when immigrants
came to Brazil and South Africa. We are concerned with
Brazil and South Africa because there exists a lack of
economic research on the immigrants of these countries.
We calculated ordinary least squares in Stata to predict the
people’s year of migration based on gender, education,
marital status, birthplace, and age. We assume that push
factors of immigrants in the US are the same as immigrants
in Brazil and South Africa. Additionally, we include spousal
birthplace and education because one’s welfare is
correlated to his or her spouse’s welfare. For each of these
variables, we use a dummy variable.
Our basic OLS regression equation is as follows:
𝑦 = 𝛽0 + 𝑋1 ∗ 𝛽1 + … + 𝑋 𝑘 ∗ 𝛽 𝑘 + 𝜀
Where
X represents
the
dummy
variables,
k is
the
number
of
variables,
y is
the
year
of
immigration,
and
ε is
the
error
term.
We
had
a
total
of
k
=
34
variables.
Our microdata was provided by IPUMS.
Significance:
This research project represents the beginning of the cohort analysis conducted by George Borjas’ in his 1985 paper Assimilation,
Changes in Cohort Quality, and the Earnings of Immigrants. In this paper, Borjas proves that Chiswick’s use of cross sectional analysis
in his 1978 paper The Effect of Americanization on the Earnings of Foreign-born Men significantly overestimates figures. He did this by
showing that one must use cohort analysis instead and take into account for out migration and the fact that different cohorts of
immigrants can have different qualities.
Figure 1: Brazil Immigrant Model Accuracy
Figure 2: South Africa Immigrant Model Accuracy