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APPENDIX E
Multivariate Analysis of the Determinants of
Financial Air] Given to ]-l Visa Holders by the
Chinese Government and American Universities
Tables E-1 and E-2 give the results of the multivariate analyses of the
determinants of financial aid from American universities and the Chi-
nese government for ]-1 visa holders. The first column in each table lists
the factors found to be significant determinants of the amount of money
given each visa holder. The second column indicates the weight given to
each factor. Because the dependent variable is the number of dollars
provided per year, the "B" (Beta) coefficients in this column can be
interpreted as the dollar amounts that should be added to or subtracted
from the intercept given at the bottom of the table in order to derive an
estimate of the amount of money a student with certain characteristics
would be expected to receive. The third column shows t-statistics that
indicate whether the coefficient in column 2 is significant. T-statistics
larger than 1.96 indicate that the probability of obtaining a coefficient
that large by chance is less than 5 percent. Since; all the t-statistics
shown are greater than 1.96, all factors listed are highly significant.
When a sample is very large, as in the case N = 19,859, statistical
significance is more frequently obtained.
The R2 shown at the bottom of the table indicates the proportion of
the variation in the amount of money received that could be explained
by the available factors. For the analysis of the financial aid from the
Chinese government, this was 13 percent; for the universities, it was 17
percent. This leaves a significant portion of the variation unexplained.
However, given that the unit of analysis frequently was zero, and given
the limited number of independent variables, these are quite satisfac-
tory results.
Following are two specific examples of how characteristics of individ-
uals would affect the amount of money each would have been expected
to receive from an American university or the Chinese government.
These examples are intended to show how the same individual would
have been evaluated differently for funding by the Chinese government
227
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228
APPENDIX E
and a U.S. university based on the data available to CSCPRC staff for
1979 to 1983.
Example 1: A new research scholar came to the United States to study
engineering in 1981. He is 25 years old and has just gradu-
atedfrom a university in China.
The intercept is given, followed by addition or subtraction of
amounts based on the applicant's characteristics. As shown below, the
applicant is expected to receive more money from the Chinese govern-
ment than from the U. S. university.
Chinese Government U.S. University
Intercept $2,981.67 $224.73
1981 -895.94 1,540.82
Age -833.74
Research scholar 1,973.28 1,130.42
Engineering 2,313.86 - 461.04
Expected level of funding 5,539.12 2,454.93
Example 2: A female university professor in China is a continuing
student studying law on a J-1 visa. She is 38 years old,
and is applying for funding in 1980.
As shown below, this student would be expected to receive some support
from a U.S. university, but nothing from the Chinese government. In
fact, the predicted amount from the PRC is negative. (Anyone who
would receive a negative estimated amount of funding would be very
unlikely to have received any support from that particular source of
funds.)
Intercept
1980
Continuing
Age
Female
Student
Law
University professor
Expected level of funding
Chinese Government '' ~ ''
$2,981.67
-775.88
-631.09
- 1,267.30
-637.49
1,357.37
-1,053.18
-25.90
up.. university
$224.73
996.73
287.50
209.27
3,239.27
1,280.97
-1,243.15
4,995.32
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APPENDIX E
229
TABLE E-1 Determinants of the Yearly Amount of Money Given to a
]-1 Student or Scholar by a U.S. University, 1979 Through 1983
Independent Variable Estimate of B t-statistic
Year
1980 996.73 5.17
1981 1,540.82 8.80
1982 1,754.02 10.10
1983 1,703.61 9.83
Continuing student or scholar 287.50 4.29
Female 209.27 2.38
Category
Student 3,239.27 20.24
Professor 2,610.27 12.14
Teacher 1,420.59 3.49
Research scholar 1,130.42 7.63
Field of study
A g r i c u 1 t u r e —967.61 - 4.61
Architecture —1,631.91 - 3.17
Computer science —879.72 —4.50
E n g i n e e r i n g —461.04 - 3.72
Health sciences 1,508.57 10.17
Law 1,280.97 3.36
Life sciences 2,017.43 13.55
Mathematics 1,415.81 7.56
Physical sciences 2,208.23 17.64
Social sciences 643.89 3.49
Occupation
Government official - 1,434.54 -9.92
University professor —1,243.15 - 11.37
Secondary teacher - 1,756.63 - -4.98
Media —1,323.87 - 2.82
Business management - 1,705.98 -6.09
Other organization - 1,607.84 - 10.89
Intercept 224.73 0.52
R2 = .167
Adjusted R2 = .166, N = 19,859
NOTE: Variables not found to be significant are not included.
SOURCE: USIA data tape.
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230
APPENDIX E
TABLE E-2 Determinants of the Yearly Amount of Money Given to a
J-1 Student or Scholar by the Chinese Government, 1979 Through 1983
Independent Variable Estimate of B t-statistic
Year
1980 -775.88 -5.35
1981 -895.94 -6.60
1982 - 1,086.54 -8.08
1983 -792.19 -5.90
Continuing student or scholar -631.09 - 12.17
Age in years -33.35 - 12.07
Female -637.49 -9.49
Category
Student 1,357.37 10.88
Professor 1,247.59 7.46
Teacher 1,957.77 6.26
Research scholar 1,973.28 17.07
Field of study
Agriculture 1,569.54 9.69
American studies - 1,537.77 -2.27
Architecture 2,275.32 5.80
Computer science 1,721.11 13.05
Engineering 2,313.86 39.88
Humanities 343.68 2.29
Law - 1,053.18 -3.69
Library science 981.48 2.17
Occupation
Agricultural worker - 2,205.72 - 6.98
Intercept 2,981.67 14.90
R2= 126
Adjusted R2 = .125, N = 19,859
NOTE: Variables not found to be significant are not included.
SOURCE: USIA data tape.
Representative terms from entire chapter:
research scholar
