Example 29.1 Klein’s Model I Estimated with LIML and 3SLS
This example uses PROC SYSLIN to estimate the classic Klein Model I. For a discussion of this model, see Theil (1971). The following statements read the data.
*---------------------------Klein's Model I----------------------------*
| By L.R. Klein, Economic Fluctuations in the United States, 1921-1941 |
| (1950), NY: John Wiley. A macro-economic model of the U.S. with |
| three behavioral equations, and several identities. See Theil, p.456.|
*----------------------------------------------------------------------*;
data klein;
input year c p w i x wp g t k wsum;
date=mdy(1,1,year);
format date monyy.;
y =c+i+g-t;
yr =year-1931;
klag=lag(k);
plag=lag(p);
xlag=lag(x);
label year='Year'
date='Date'
c ='Consumption'
p ='Profits'
w ='Private Wage Bill'
i ='Investment'
k ='Capital Stock'
y ='National Income'
x ='Private Production'
wsum='Total Wage Bill'
wp ='Govt Wage Bill'
g ='Govt Demand'
i ='Taxes'
klag='Capital Stock Lagged'
plag='Profits Lagged'
xlag='Private Product Lagged'
yr ='YEAR-1931';
datalines;
1920 . 12.7 . . 44.9 . . . 182.8 .
1921 41.9 12.4 25.5 -0.2 45.6 2.7 3.9 7.7 182.6 28.2
1922 45.0 16.9 29.3 1.9 50.1 2.9 3.2 3.9 184.5 32.2
1923 49.2 18.4 34.1 5.2 57.2 2.9 2.8 4.7 189.7 37.0
1924 50.6 19.4 33.9 3.0 57.1 3.1 3.5 3.8 192.7 37.0
1925 52.6 20.1 35.4 5.1 61.0 3.2 3.3 5.5 197.8 38.6
1926 55.1 19.6 37.4 5.6 64.0 3.3 3.3 7.0 203.4 40.7
1927 56.2 19.8 37.9 4.2 64.4 3.6 4.0 6.7 207.6 41.5
1928 57.3 21.1 39.2 3.0 64.5 3.7 4.2 4.2 210.6 42.9
1929 57.8 21.7 41.3 5.1 67.0 4.0 4.1 4.0 215.7 45.3
... more lines ...
The following statements estimate the Klein model using the limited information maximum likelihood method. In addition, the parameter estimates are written to a SAS data set with the OUTEST= option.
proc syslin data=klein outest=b liml;
endogenous c p w i x wsum k y;
instruments klag plag xlag wp g t yr;
consume: model c = p plag wsum;
invest: model i = p plag klag;
labor: model w = x xlag yr;
run;
The PROC SYSLIN estimates are shown in Output 29.1.1 through Output 29.1.3.
Output 29.1.1
LIML Estimates for Consumption
The SYSLIN Procedure
Limited-Information Maximum Likelihood Estimation
3 |
854.3541 |
284.7847 |
118.42 |
<.0001 |
17 |
40.88419 |
2.404952 |
|
|
20 |
941.4295 |
|
|
|
1.55079 |
0.95433 |
53.99524 |
0.94627 |
2.87209 |
|
1 |
17.14765 |
2.045374 |
8.38 |
<.0001 |
Intercept |
1 |
-0.22251 |
0.224230 |
-0.99 |
0.3349 |
Profits |
1 |
0.396027 |
0.192943 |
2.05 |
0.0558 |
Profits Lagged |
1 |
0.822559 |
0.061549 |
13.36 |
<.0001 |
Total Wage Bill |
Output 29.1.2
LIML Estimates for Investments
The SYSLIN Procedure
Limited-Information Maximum Likelihood Estimation
3 |
210.3790 |
70.12634 |
34.06 |
<.0001 |
17 |
34.99649 |
2.058617 |
|
|
20 |
252.3267 |
|
|
|
1.43479 |
0.85738 |
1.26667 |
0.83221 |
113.27274 |
|
1 |
22.59083 |
9.498146 |
2.38 |
0.0294 |
Intercept |
1 |
0.075185 |
0.224712 |
0.33 |
0.7420 |
Profits |
1 |
0.680386 |
0.209145 |
3.25 |
0.0047 |
Profits Lagged |
1 |
-0.16826 |
0.045345 |
-3.71 |
0.0017 |
Capital Stock Lagged |
Output 29.1.3
LIML Estimates for Labor
The SYSLIN Procedure
Limited-Information Maximum Likelihood Estimation
LABOR |
w |
Private Wage Bill |
3 |
696.1485 |
232.0495 |
393.62 |
<.0001 |
17 |
10.02192 |
0.589525 |
|
|
20 |
794.9095 |
|
|
|
0.76781 |
0.98581 |
36.36190 |
0.98330 |
2.11156 |
|
1 |
1.526187 |
1.320838 |
1.16 |
0.2639 |
Intercept |
1 |
0.433941 |
0.075507 |
5.75 |
<.0001 |
Private Production |
1 |
0.151321 |
0.074527 |
2.03 |
0.0583 |
Private Product Lagged |
1 |
0.131593 |
0.035995 |
3.66 |
0.0020 |
YEAR-1931 |
The OUTEST= data set is shown in part in Output 29.1.4. Note that the data set contains the parameter estimates and root mean squared errors, _SIGMA_, for the first-stage instrumental regressions as well as the parameter estimates and for the LIML estimates for the three structural equations.
Output 29.1.4
The OUTEST= Data Set
LIML |
0 Converged |
CONSUME |
c |
1.55079 |
17.1477 |
. |
0.39603 |
. |
. |
. |
. |
. |
-1 |
-0.22251 |
. |
. |
. |
0.82256 |
. |
. |
LIML |
0 Converged |
INVEST |
i |
1.43479 |
22.5908 |
-0.16826 |
0.68039 |
. |
. |
. |
. |
. |
. |
0.07518 |
. |
-1 |
. |
. |
. |
. |
LIML |
0 Converged |
LABOR |
w |
0.76781 |
1.5262 |
. |
. |
0.15132 |
. |
. |
. |
0.13159 |
. |
. |
-1 |
. |
0.43394 |
. |
. |
. |
The following statements estimate the model using the 3SLS method. The reduced form estimates are produced by the REDUCED option; IDENTITY statements are used to make the model complete.
proc syslin data=klein 3sls reduced;
endogenous c p w i x wsum k y;
instruments klag plag xlag wp g t yr;
consume: model c = p plag wsum;
invest: model i = p plag klag;
labor: model w = x xlag yr;
product: identity x = c + i + g;
income: identity y = c + i + g - t;
profit: identity p = y - w;
stock: identity k = klag + i;
wage: identity wsum = w + wp;
run;
The preliminary 2SLS results and estimated cross-model covariance matrix are not shown. The 3SLS estimates are shown in Output 29.1.5 through Output 29.1.7. The reduced form estimates are shown in Output 29.1.8 through Output 29.1.11.
Output 29.1.5
3SLS Estimates for Consumption
The SYSLIN Procedure
Three-Stage Least Squares Estimation
1 |
16.44079 |
1.449925 |
11.34 |
<.0001 |
Intercept |
1 |
0.124890 |
0.120179 |
1.04 |
0.3133 |
Profits |
1 |
0.163144 |
0.111631 |
1.46 |
0.1621 |
Profits Lagged |
1 |
0.790081 |
0.042166 |
18.74 |
<.0001 |
Total Wage Bill |
Output 29.1.6
3SLS Estimates for Investments
1 |
28.17785 |
7.550853 |
3.73 |
0.0017 |
Intercept |
1 |
-0.01308 |
0.179938 |
-0.07 |
0.9429 |
Profits |
1 |
0.755724 |
0.169976 |
4.45 |
0.0004 |
Profits Lagged |
1 |
-0.19485 |
0.036156 |
-5.39 |
<.0001 |
Capital Stock Lagged |
Output 29.1.7
3SLS Estimates for Labor
LABOR |
w |
Private Wage Bill |
1 |
1.797218 |
1.240203 |
1.45 |
0.1655 |
Intercept |
1 |
0.400492 |
0.035359 |
11.33 |
<.0001 |
Private Production |
1 |
0.181291 |
0.037965 |
4.78 |
0.0002 |
Private Product Lagged |
1 |
0.149674 |
0.031048 |
4.82 |
0.0002 |
YEAR-1931 |
Output 29.1.8
Reduced Form Estimates
1 |
-0.12489 |
0 |
0 |
0 |
-0.79008 |
0 |
0 |
0 |
0.013079 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
-0.40049 |
0 |
0 |
0 |
-1 |
0 |
0 |
-1 |
1 |
0 |
0 |
0 |
-1 |
0 |
0 |
-1 |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
0 |
0 |
0 |
0 |
-1 |
0 |
0 |
0 |
-1 |
0 |
0 |
1 |
0 |
0 |
0 |
-1 |
0 |
0 |
1 |
0 |
0 |
Output 29.1.9
Reduced Form Estimates
16.44079 |
0.163144 |
0 |
0 |
0 |
0 |
0 |
0 |
28.17785 |
0.755724 |
-0.19485 |
0 |
0 |
0 |
0 |
0 |
1.797218 |
0 |
0 |
0.181291 |
0.149674 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
-1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
Output 29.1.10
Reduced Form Estimates
1.634654 |
0.634654 |
1.095657 |
0.438802 |
0.195852 |
0.195852 |
0 |
1.291509 |
0.972364 |
0.972364 |
-0.34048 |
-0.13636 |
1.108721 |
1.108721 |
0 |
0.768246 |
0.649572 |
0.649572 |
1.440585 |
0.576943 |
0.072629 |
0.072629 |
0 |
0.513215 |
-0.01272 |
0.987282 |
0.004453 |
0.001783 |
-0.0145 |
-0.0145 |
0 |
-0.01005 |
1.621936 |
1.621936 |
1.10011 |
1.440585 |
0.181351 |
0.181351 |
0 |
1.281461 |
0.649572 |
0.649572 |
1.440585 |
0.576943 |
0.072629 |
0.072629 |
0 |
1.513215 |
-0.01272 |
0.987282 |
0.004453 |
0.001783 |
-0.0145 |
-0.0145 |
1 |
-0.01005 |
1.621936 |
1.621936 |
1.10011 |
0.440585 |
1.181351 |
0.181351 |
0 |
1.281461 |
Output 29.1.11
Reduced Form Estimates
46.7273 |
0.746307 |
-0.12366 |
0.198633 |
0.163991 |
0.634654 |
-0.19585 |
1.291509 |
42.77363 |
0.893474 |
-0.18946 |
-0.06173 |
-0.05096 |
0.972364 |
-1.10872 |
0.768246 |
31.57207 |
0.596871 |
-0.12657 |
0.261165 |
0.215618 |
0.649572 |
-0.07263 |
0.513215 |
27.6184 |
0.744038 |
-0.19237 |
0.000807 |
0.000667 |
-0.01272 |
0.014501 |
-0.01005 |
74.3457 |
1.490345 |
-0.31603 |
0.19944 |
0.164658 |
1.621936 |
-0.18135 |
1.281461 |
31.57207 |
0.596871 |
-0.12657 |
0.261165 |
0.215618 |
0.649572 |
-0.07263 |
1.513215 |
27.6184 |
0.744038 |
0.80763 |
0.000807 |
0.000667 |
-0.01272 |
0.014501 |
-0.01005 |
74.3457 |
1.490345 |
-0.31603 |
0.19944 |
0.164658 |
1.621936 |
-1.18135 |
1.281461 |