I am trying to estimate a system of equations concerning the effect of FDI on Business cycle synchronisation.
The system is as follows.
(Business Synchronization) i j = (Trade Intensity)i j + (FDI Intensity)i j + (Structural Dissimilarity) + Z1i j + u i j
(FDI Intensity)i j = (Trade Intensity)i j +(Structural Dissimilarity)i j + Z2i j + u i j
(Trade Intensity) i j = (FDI Intensity)i j + (Structural Dissimilarity)i j +Z3 i j +u ij
(Structual Dissimilarity) i j = (FDI Intensity)i j +(Trade Intensity)i j + Z4 I J +u i j
Where i denotes country I . j denotes country j. Z Denotes exogenous determinants of the dependent variable for that equation
When I don't suppress the constant, here is the STATA output using three stage least squares estimator
Code:
Three-stage least-squares regression
----------------------------------------------------------------------
Equation Obs Parms RMSE "R-sq" chi2 P
----------------------------------------------------------------------
synch 183 4 .0233448 0.2415 111.42 0.0000
fdi 183 4 .0397629 0.2064 158.99 0.0000
trade 183 4 .024307 0.4589 446.22 0.0000
dissim 183 4 .1277664 0.4433 276.77 0.0000
----------------------------------------------------------------------
----------------------------------------------------------------------------------
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
synch |
trade | .3203797 .1389368 2.31 0.021 .0480685 .5926909
fdi | .1204827 .0971815 1.24 0.215 -.0699895 .3109549
dissim | .0359573 .0156557 2.30 0.022 .0052726 .066642
euro | .0305018 .0059332 5.14 0.000 .018873 .0421306
_cons | -.0918088 .0071617 -12.82 0.000 -.1058456 -.0777721
-----------------+----------------------------------------------------------------
fdi |
trade | 1.519969 .1435987 10.58 0.000 1.238521 1.801417
dissim | .0828209 .0245547 3.37 0.001 .0346944 .1309473
border | -.0434 .0120242 -3.61 0.000 -.0669669 -.019833
euro | -.0008237 .0042045 -0.20 0.845 -.0090643 .007417
_cons | -.0327858 .0113729 -2.88 0.004 -.0550763 -.0104953
-----------------+----------------------------------------------------------------
trade |
fdi | .5812198 .0360878 16.11 0.000 .5104889 .6519506
dissim | -.0639277 .0115948 -5.51 0.000 -.0866531 -.0412024
border | .025972 .0053825 4.83 0.000 .0154225 .0365215
logdistance | -.0068376 .0013158 -5.20 0.000 -.0094165 -.0042587
_cons | .0509309 .0066589 7.65 0.000 .0378797 .063982
-----------------+----------------------------------------------------------------
dissim |
trade | 1.568267 .9418691 1.67 0.096 -.2777621 3.414297
fdi | -2.857465 .9470738 -3.02 0.003 -4.713695 -1.001234
gdpgap | .2480874 .0182323 13.61 0.000 .2123528 .283822
loggdpcapitaprod | .4634245 .0879656 5.27 0.000 .291015 .635834
_cons | -4.171305 .8046478 -5.18 0.000 -5.748385 -2.594224
----------------------------------------------------------------------------------
Endogenous variables: synch trade fdi dissim
Exogenous variables: logdistance loggdpcapitaprod gdpgap loggdpprod euro
lang landlocked border logfreedom
------------------------------------------------------------------------------
When I suppress the constant here is the output.
Code:
----------------------------------------------------------------------
Equation Obs Parms RMSE "R-sq" chi2 P
----------------------------------------------------------------------
synch 183 4 .0475851 0.5097 552.74 0.0000
fdi 183 4 .0377404 0.5349 400.96 0.0000
trade 183 4 .0285063 0.5361 578.89 0.0000
dissim 183 4 .167015 0.8399 1957.54 0.0000
----------------------------------------------------------------------
----------------------------------------------------------------------------------
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
synch |
trade | -1.290544 .1589516 -8.12 0.000 -1.602084 -.979005
fdi | .9583024 .1368436 7.00 0.000 .6900939 1.226511
dissim | -.1607618 .0085147 -18.88 0.000 -.1774502 -.1440734
euro | .0361279 .0072658 4.97 0.000 .0218871 .0503687
-----------------+----------------------------------------------------------------
fdi |
trade | 1.202404 .0902235 13.33 0.000 1.025569 1.379239
dissim | .0144295 .0075185 1.92 0.055 -.0003066 .0291656
border | -.0109175 .0093866 -1.16 0.245 -.029315 .0074799
euro | .006046 .0043691 1.38 0.166 -.0025172 .0146093
-----------------+----------------------------------------------------------------
trade |
fdi | .7297148 .0377461 19.33 0.000 .6557339 .8036958
dissim | -.0347674 .0072208 -4.81 0.000 -.0489199 -.0206149
border | .0131548 .0052226 2.52 0.012 .0029188 .0233909
logdistance | .0036213 .0006443 5.62 0.000 .0023585 .0048842
-----------------+----------------------------------------------------------------
dissim |
trade | -5.162866 .5351785 -9.65 0.000 -6.211796 -4.113935
fdi | 3.246299 .435652 7.45 0.000 2.392437 4.100161
gdpgap | .1619648 .0152134 10.65 0.000 .1321472 .1917824
loggdpcapitaprod | .0181678 .0029277 6.21 0.000 .0124296 .023906
----------------------------------------------------------------------------------
Endogenous variables: synch trade fdi dissim
Exogenous variables: logdistance loggdpcapitaprod gdpgap loggdpprod euro
lang landlocked border logfreedom
------------------------------------------------------------------------------
As can be seen, when suppressing the constant for each equation, R squared seems to increase for each equation and a number of variables become more significant. However, the coefficient for trade becomes negative. This however goes against what economic theory predicts. Theory would predict that countries that have high trade intensity would be suspect to business cycle synchronisation.
Should I thus suppress the constant and go with the model with the higher r squared and more significant variables or should I go with what the theory predicts?
Thanks
Mark
0 Response to Change of sign on coefficient and and r squared when supressing constant. How to interpret the results?
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