help: lmcovsem dialog:

Title

lmcovsem: (SEM-FIML) Breusch-Pagan Diagonal Covariance Matrix LM Test

Table of Contents

Syntax

Description

Saved Results

References

*** Examples

Author

Syntax

lmcovsem

Description

- (SEM) Structural Equation Modeling Regressions sem for system of simultaneous equations.

- SEM Estimations assume:

1- Independence of the errors in each eqution or no correlations between different periods in the same equation.

2- no correlations between the errors for any of two equtions between two different periods, this is called "Intertemporal Correlation".

3- correlations may be exist between different two equations, but at the same period, and this is called "Contemporaneous Correlation".

4- SEM can be applied when there is correlations between different two equations at the same period, or if the independent variables are differnt from equation to equation.

5- If "Contemporaneous Correlation" does not exist, ordinary least squares (OLS) can be applied separately to each equation, the results are fully efficient and there is no need to estimate SEM.

Breusch-Pagan LM can test whether contemporaneous diagonal covariance matrix is 0. (Independence of the Errors), or correlated if at least one covariance is nonzero.

Ho: no Contemporaneous Correlation: Sig12 = Sig13 = Sig23 = ... = 0.

Ha: Contemporaneous Correlation: at least one Covariance is nonzero.

Saved Results

lmcovsem saves the following in r():

r(lmcov) LM Diagonal Covariance Matrix Test
r(lmcovp) LM Diagonal Covariance Matrix Test P-Value
r(lmcovdf) Chi2 Degrees of Freedom

References

Judge, Georege, R. Carter Hill, William . E. Griffiths, Helmut Lutkepohl, & Tsoung-Chao Lee (1988)
"Introduction To The Theory And Practice Of Econometrics",
2nd ed., John Wiley & Sons, Inc., New York, USA; 456-461.

Judge, Georege, W. E. Griffiths, R. Carter Hill, Helmut Lutkepohl, & Tsoung-Chao Lee(1985)
"The Theory and Practice of Econometrics",
2nd ed., John Wiley & Sons, Inc., New York, USA.

Examples

in this example FIML will be used as follows:

clear all

sysuse lmcovsem.dta , clear

sem (y1 <- y2 x1 x2) (y2 <- y1 x3 x4), cov(e.y1*e.y2)

lmcovsem

return list

* If you want to use dialog box: Press OK to compute lmcovsem

db lmcovsem

. clear all
. sysuse lmcovsem.dta , clear
. sem (y1 <- y2 x1 x2) (y2 <- y1 x3 x4), cov(e.y1*e.y2)

Structural equation model Number of obs = 17
Estimation method = ml
Log likelihood = -363.34588
------------------------------------------------------------------------------
| OIM
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Structural |
y1 <- |
y2 | .2425937 .2106232 1.15 0.249 -.1702201 .6554075
x1 | .2568409 .462485 0.56 0.579 -.649613 1.163295
x2 | -1.037016 .3154059 -3.29 0.001 -1.6552 -.4188317
_cons | 147.0826 54.4491 2.70 0.007 40.36431 253.8009
-----------+----------------------------------------------------------------
y2 <- |
y1 | -.6282929 .6148239 -1.02 0.307 -1.833326 .5767398
x3 | -.5226661 .3235637 -1.62 0.106 -1.156839 .1115071
x4 | 3.4208 1.440664 2.37 0.018 .5971513 6.244449
_cons | 62.44495 42.36071 1.47 0.140 -20.58052 145.4704
-------------+----------------------------------------------------------------
Variance |
e.y1 | 80.17577 28.99122 39.46865 162.8673
e.y2 | 142.4478 80.80501 46.86006 433.0208
-------------+----------------------------------------------------------------
Covariance |
e.y1 |
e.y2 | 25.62619 53.75243 0.48 0.634 -79.72665 130.979
------------------------------------------------------------------------------
LR test of model vs. saturated: chi2(2) = 0.12, Prob > chi2 = 0.9408

. lmcovsem
==============================================================================
* (SEM-FIML) Breusch-Pagan Diagonal Covariance Matrix LM Test - Method(ml)
==============================================================================
Ho: Diagonal Disturbance Covariance Matrix (Independent Equations)
Ho: Run OLS - Ha: Run SEM

Lagrange Multiplier Test = 0.97750
Degrees of Freedom = 1.0
P-Value > Chi2(1) = 0.32282
==============================================================================

Author

Emad Abd Elmessih Shehata
Professor (PhD Economics)
Agricultural Research Center - Agricultural Economics Research Institute - Egypt
Email: emadstat@hotmail.com
WebPage at IDEAS: http://ideas.repec.org/f/psh494.html
WebPage at EconPapers: http://econpapers.repec.org/RAS/psh494.htm

LMCOVSEM Citation

Shehata, Emad Abd Elmessih (2012)

LMCOVSEM: "Stata Module to Compute (SEM-FIML) Breusch-Pagan Diagonal Covariance Matrix LM Test"

http://ideas.repec.org/c/boc/bocode/s457435.html

http://econpapers.repec.org/software/bocbocode/s457435.htm

Online Help:

* Breusch-Pagan Diagonal Covariance Matrix Test:
lmcovnlsur (NL-SUR) Breusch-Pagan Diagonal Covariance Matrix Test
lmcovreg3 (3SLS-SUR) Breusch-Pagan Diagonal Covariance Matrix Test
lmcovsem (SEM-FIML) Breusch-Pagan Diagonal Covariance Matrix Test
lmcovvar (VAR) Breusch-Pagan Diagonal Covariance Matrix Test
lmcovxt Panel Data Breusch-Pagan Diagonal Covariance Matrix Test
---------------------------------------------------------------------------

* (1) (3SLS-SUR) * Simultaneous Equations:
lmareg3 (3SLS-SUR) Overall System Autocorrelation Tests
lmhreg3 (3SLS-SUR) Overall System Heteroscedasticity Tests
lmnreg3 (3SLS-SUR) Overall System Non Normality Tests
lmcovreg3 (3SLS-SUR) Breusch-Pagan Diagonal Covariance Matrix
r2reg3 (3SLS-SUR) Overall System R2, F-Test, and Chi2-Test
diagreg3 (3SLS-SUR) Overall System ModeL Selection Diagnostic Criteria
---------------------------------------------------------------------------
* (2) (SEM-FIML) * Structural Equation Modeling:
lmasem (SEM-FIML) Overall System Autocorrelation Tests
lmhsem (SEM-FIML) Overall System Heteroscedasticity Tests
lmnsem (SEM-FIML) Overall System Non Normality Tests
lmcovsem (SEM-FIML) Breusch-Pagan Diagonal Covariance Matrix Test
r2sem (SEM-FIML) Overall System R2, F-Test, and Chi2-Test
diagsem (SEM-FIML) Overall System ModeL Selection Diagnostic Criteria
---------------------------------------------------------------------------
* (3) (NL-SUR) * Non Linear Seemingly Unrelated Regression:
lmanlsur (NL-SUR) Overall System Autocorrelation Tests
lmhnlsur (NL-SUR) Overall System Heteroscedasticity Tests
lmnnlsur (NL-SUR) Overall System Non Normality Tests
lmcovnlsur (NL-SUR) Breusch-Pagan Diagonal Covariance Matrix Test
r2nlsur (NL-SUR) Overall System R2, F-Test, and Chi2-Test
diagnlsur (NL-SUR) Overall System ModeL Selection Diagnostic Criteria
---------------------------------------------------------------------------
* (4) (VAR) * Vector Autoregressive Model:
lmavar (VAR) Overall System Autocorrelation Tests
lmhvar (VAR) Overall System Heteroscedasticity Tests
lmnvar (VAR) Overall System Non Normality Tests
lmcovvar (VAR) Breusch-Pagan Diagonal Covariance Matrix Test
r2var (VAR) Overall System R2, F-Test, and Chi2-Test
diagvar (VAR) Overall System ModeL Selection Diagnostic Criteria
---------------------------------------------------------------------------