Hello,
I need to use the Wald estimator method of fitting straight lines. For this data, the estimator computes the return to education as the ratio of the difference in earnings by quarter of birth to the difference in years of education by quarter of birth. I am comparing individuals from quarter 1 to individuals the individuals born in the last 3 quarters.
So basically I need to
I attached a sample of the data below. Any solutions?
The data bellow is: Quarter of Birth (qob), Year of Birth (yob), Years of education (education), Log of Weekly Wage (logwage)
qob yob education logwage
1 1933 12 6.245846
4 1933 12 5.847161
1 1930 12 6.645516
1 1933 16 6.706133
4 1937 14 6.357876
4 1935 12 5.441835
1 1938 12 6.39066
1 1930 12 4.607667
3 1939 12 6.553961
2 1936 7 7.017041
3 1934 14 6.39066
4 1934 13 6.935289
4 1935 16 6.533516
3 1937 12 6.030926
1 1937 10 6.252533
4 1935 20 7.313221
1 1938 12 6.594229
1 1933 13 6.088502
2 1937 12 6.32398
3 1936 12 6.725576
1 1938 12 5.522127
4 1931 12 4.643836
2 1936 9 5.790019
3 1936 1 4.903136
3 1930 6 5.259596
1 1934 1 5.259596
1 1939 6 4.998381
4 1939 14 6.175587
1 1934 8 5.847161
4 1931 6 5.434904
3 1932 9 6.190276
1 1939 7 2.144956
3 1937 11 5.154292
2 1930 12 5.729413
4 1934 6 5.076735
1 1936 10 4.829082
4 1939 11 5.824032
3 1934 6 5.216794
1 1939 7 4.973191
2 1935 9 4.86191
4 1936 12 5.441835
1 1939 8 5.561051
4 1935 12 4.1905284
1 1931 13 5.691204
2 1934 8 5.847161
2 1936 13 6.254921
3 1935 14 5.036578
1 1932 12 4.526169
1 1933 14 5.48264
2 1934 11 5.886382
2 1936 6 4.895349
1 1938 11 5.426651
4 1937 11 5.259596
4 1931 6 4.771743
1 1934 16 6.175587
4 1935 14 6.092223
3 1931 18 5.693662
4 1935 12 5.664895
2 1938 18 6.115849
3 1937 13 5.595926
4 1937 10 5.108855
2 1935 16 6.134774
2 1938 9 6.195386
2 1937 12 4.701389
2 1931 17 6.033475
3 1931 16 4.3075624
3 1939 12 4.972081
4 1936 15 4.607667
2 1931 12 5.154292
3 1934 10 4.0539565
4 1935 14 5.162243
2 1931 14 5.906462
3 1936 14 5.952494
2 1934 12 5.729413
3 1936 12 5.465704
1 1937 11 5.259596
4 1934 9 1.920874
4 1932 11 5.259596
1 1933 18 5.812119
3 1939 7 4.566949
4 1930 16 5.559572
2 1933 12 -2.3418057
3 1931 7 4.202202
3 1939 12 4.958667
3 1932 18 6.483019
1 1936 6 5.331882
3 1930 10 4.838264
4 1935 9 7.46365
1 1931 12 5.683383
2 1939 12 5.095193
4 1933 4 4.4616995
2 1934 16 6.357876
2 1933 12 5.927342
3 1934 6 2.961499
3 1933 10 4.972081
1 1933 6 4.749104
4 1939 12 5.635147
1 1939 10 5.481056
1 1935 10 5.496143
2 1938 9 5.664895
I need to use the Wald estimator method of fitting straight lines. For this data, the estimator computes the return to education as the ratio of the difference in earnings by quarter of birth to the difference in years of education by quarter of birth. I am comparing individuals from quarter 1 to individuals the individuals born in the last 3 quarters.
So basically I need to
I attached a sample of the data below. Any solutions?
The data bellow is: Quarter of Birth (qob), Year of Birth (yob), Years of education (education), Log of Weekly Wage (logwage)
qob yob education logwage
1 1933 12 6.245846
4 1933 12 5.847161
1 1930 12 6.645516
1 1933 16 6.706133
4 1937 14 6.357876
4 1935 12 5.441835
1 1938 12 6.39066
1 1930 12 4.607667
3 1939 12 6.553961
2 1936 7 7.017041
3 1934 14 6.39066
4 1934 13 6.935289
4 1935 16 6.533516
3 1937 12 6.030926
1 1937 10 6.252533
4 1935 20 7.313221
1 1938 12 6.594229
1 1933 13 6.088502
2 1937 12 6.32398
3 1936 12 6.725576
1 1938 12 5.522127
4 1931 12 4.643836
2 1936 9 5.790019
3 1936 1 4.903136
3 1930 6 5.259596
1 1934 1 5.259596
1 1939 6 4.998381
4 1939 14 6.175587
1 1934 8 5.847161
4 1931 6 5.434904
3 1932 9 6.190276
1 1939 7 2.144956
3 1937 11 5.154292
2 1930 12 5.729413
4 1934 6 5.076735
1 1936 10 4.829082
4 1939 11 5.824032
3 1934 6 5.216794
1 1939 7 4.973191
2 1935 9 4.86191
4 1936 12 5.441835
1 1939 8 5.561051
4 1935 12 4.1905284
1 1931 13 5.691204
2 1934 8 5.847161
2 1936 13 6.254921
3 1935 14 5.036578
1 1932 12 4.526169
1 1933 14 5.48264
2 1934 11 5.886382
2 1936 6 4.895349
1 1938 11 5.426651
4 1937 11 5.259596
4 1931 6 4.771743
1 1934 16 6.175587
4 1935 14 6.092223
3 1931 18 5.693662
4 1935 12 5.664895
2 1938 18 6.115849
3 1937 13 5.595926
4 1937 10 5.108855
2 1935 16 6.134774
2 1938 9 6.195386
2 1937 12 4.701389
2 1931 17 6.033475
3 1931 16 4.3075624
3 1939 12 4.972081
4 1936 15 4.607667
2 1931 12 5.154292
3 1934 10 4.0539565
4 1935 14 5.162243
2 1931 14 5.906462
3 1936 14 5.952494
2 1934 12 5.729413
3 1936 12 5.465704
1 1937 11 5.259596
4 1934 9 1.920874
4 1932 11 5.259596
1 1933 18 5.812119
3 1939 7 4.566949
4 1930 16 5.559572
2 1933 12 -2.3418057
3 1931 7 4.202202
3 1939 12 4.958667
3 1932 18 6.483019
1 1936 6 5.331882
3 1930 10 4.838264
4 1935 9 7.46365
1 1931 12 5.683383
2 1939 12 5.095193
4 1933 4 4.4616995
2 1934 16 6.357876
2 1933 12 5.927342
3 1934 6 2.961499
3 1933 10 4.972081
1 1933 6 4.749104
4 1939 12 5.635147
1 1939 10 5.481056
1 1935 10 5.496143
2 1938 9 5.664895
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