Transcript National Replication vs. Regional Replication: How

National Replication vs. Regional Replication
---- How Reliable is the OLS-Based Evidence of College Wage Premium?
38% of the world’s tertiary graduates
33% of the world’s GDP in 2011
huge diversities within the 2 nations
HaogenYao, Steve Simpson
Teachers College, Columbia University
Sui Yang, Shi Li
Beijing Normal University
The Studies Replicated
The Race between Education and
Technology (Goldin and Katz, 2008)
Universal high school and mass higher
education (Wang, 2009)
Summary: Apply the basic regression and
aggregated indicators (yearly-national
level) to find that the relative lag of
college graduate supply is the main
reason of expanding wage premium.
Summary: Use extended Mincer earning
function and the Chinese Census data to
find a very high marginal return to
higher education for both urban and
rural populations.
Problem statement: We know OLS is problematic. Before applying advance
methods like IV and RD, maybe we should firstly ask HOW reliable (unreliable) the
OLS-based evidences are? Here is a straightforward answer relying on large-scale
datasets: regional replication.
The Implementation
Goldin and Katz (2008)
Wang (2009)
Data. Yearly CPS and Census (when
available) data, 1915-2005
Method. Regress the college-high
school wage premium (log ratio) on
relative supply, with institutional
factors and time trends controlled
Data. 1% sample of the 2005 Chinese
Census
Method. Includes variables indicating
the lengths of 4 levels of education,
with individual characteristics and
provincial dummies controlled
Our Replication
Our Replication
Data. Same for national replication, but
1976-2010 CPS for regional replication
b/c previous data are inappropriate
Method. while the original one weighed
data by gender, race and experience, we
use personal weight but control these 3
factors in regression/ Use the national
equation to predict regional premium
Data. 20% resampling of the 1% sample
Method. The same regression with the
same set of variables/ But not sure if
they are constructed in identical way/
Replication for the nation and the six
administrative divisions
The United State
Result from Goldin and Katz (2008)
.4
.3
Our Result
.5
.6
.7
.8
Figure 1. College Wage Premium for the US
1920
1940
Actual Premium
1960
year
1980
Predicted Premium
2000
.5
.5
.6
.6
.7
.7
.8
Wage Premium for Middle Atlantic
.8
Wage Premium for East North Central
.3
.3
.8
.4
.4
Figure 5. Wage Premium for West North Central
1980
1990
2000
2010
1970
1980
1990
2000
2010
.7
1970
.6
The Model Works for 52% of
the US Population
Wage Premium for Mountain
.3
.4
.4
.4
.6
.6
.5
.8
.8
Wage Premium for Pacific
1970
1980
1980
1990
2000
2010
1990
year
Actual Premium for the US
Predicted Premium for the Region
2000
.2
.2
1970
1970
2010
1980
1990
Actual Premium for the Region
2000
2010
.8
Wage Premium for West North Central
.7
THE DIFFERENCE
.5
.6
Relatively optimistic actual
premiums evolutions for WNC
and SA, and the predicted ones
are even more optimistic
.3
.4
Figure 5. Wage Premium for West North Central
1980
1990
2000
2010
Wage Premium for South Atlantic
.9
WHY
.7
.8
Variable Construction?
.6
Omitted Variable?
1990
year
Actual Premium for the US
Predicted Premium for the Region
2000
2010
.5
1980
Actual Premium for the Region
.4
1970
1970
1970
1980
1990
2000
2010
THE DIFFERENCE: Quite obvious…
.8
Wage Premium for New England
WHY
.7
.2
.8
.4
.6
The quality of “supply” variable? Industrial
structure? Path dependency? SES?
Figure 5. Wage Premium for West North Central
Yes fixed-effect can close the gap between
lines, but it gives an elasticity of substitution
between skilled and unskilled as high as 9, much
1970
1980
higher than the suggested one of 1.4
2000
2010
.6
1990
Wage Premium for West South Central
.4
.3
.6
.6
.4
.8
.8
.5
1
1
Wage Premium for East South Central
.4
1970
1970
1980
1980
1990
2000
2010
1990
year
Actual Premium for the US
Predicted Premium for the Region
2000
1970
2010
1980
1990
Actual Premium for the Region
2000
2010
China
Return to Education in China (%) by Wang
0
20
40
60
80
Our data does not allow for a strict
classification of rural/urban population.
Our urban group contains rural residents
that may drag the estimates down
LowerS
UpperS
Return to Education in China (%) by Replication
Lower marginal
return of higher
education, BUT still
can tell it is big
20
Larger gap of return
to higher education
0
lower estimates
40
60
Pretty high marginal
return of higher
education
Higher
80
Primary
Primary
LowerS
UpperS
Attainment (assuming the same yearly return within a level)
Urban Accumulated
Urban Marginal
Rural Accumulated
Rural Marginal
Higher
20
40
60
80
East
0
South Central
Primary
LowerS
UpperS
Higher
UpperS
Higher
Primary
LowerS
Urban Accumulated
Urban Marginal
UpperS
Rural Accumulated
Rural Marginal
60
40
20
Higher
0
Similar shapes are found
for East and South Central.
About 57% of the Chinese
population live in these
two regions.
80
South Central
Primary
LowerS
20
20
40
40
60
60
80
Northeast
80
North
Primary
LowerS
UpperS
Higher
Primary
LowerS
UpperS
60
80
0
0
South Central
THE DIFFERENCE
WHY
40
Low overall returns
Upper secondary education looks too
“risky” to the rural Northeast: Those
entered college gain big, while losers
swallow the pain of 3-years cost with
no human capital accumulation.
Industrial Structure?
20
Market openness?
0
Over college-oriented high
school education?
Primary
LowerS
Urban Accumulated
Urban Marginal
UpperS
Rural Accumulated
Rural Marginal
Higher
Higher
Northwest
60
THE DIFFERENCE
20
40
No strong marginal return to
higher education.
And it seems for Northwest
the priority should be lower
secondary education
LowerS
UpperS
Higher
60
Primary
80
0
South Central
These are the real
RURAL China
0
20
20
60
Hint
40
40
80
Southwest
0
Primary
Primary
LowerS
UpperS
Higher
LowerS
Urban Accumulated
Urban Marginal
UpperS
Rural Accumulated
Rural Marginal
Marginal Returns (%) for Urban China
0
-1
0
2
1
4
2
6
3
4
8
Marginal Return (%) for China
Primary
Primary
LowerS
Urban (Wang)
Urban (Replication)
UpperS
Higher
Rural (Wang)
Rural (Replication)
North
East
Southwest
LowerS
UpperS
Northeast
South Central
Northwest
4
Marginal Returns (%) for Rural China
2
Closer look at the marginal returns
-2
0
The low return to upper secondary
education is as eye-popping as the
high return to higher education
Primary
North
East
Southwest
LowerS
UpperS
Northeast
South Central
Northwest
Higher
Higher
To Sum Up
 The study is simple and straightforward-- Firstly have a national replication to
make sure we get results similar to the original study’s, then compare them to
regional results. By looking at the nation-region disparities, we are able to assess
the OLS-based evidence of college wage premium.
 GK(2008) and Wang(2009) advocate mess higher education, but our replications
caution on this suggestion. Even assuming the OLS results are enough for causal
identification, mess higher education may only benefit half of the population for
both countries. Since we are unable to perfectly replicate the two studies, the
best way to clear up the worry is regional replication from the authors.