Object Reference : Object View and Procedure Reference : Pool
  
 
tsls
Two-stage least squares.
Syntax
pool_name.tsls(options) y [x1 x2 x3 ...] [@cxreg w1 w2 ...] [@perreg w3 w4 ...] [@inst z1 z2 ...] [@cxinst z3 z4 ...] [@perinst z5 z6 ...]
Type the name of the dependent variable followed by one or more lists of regressors. The first list should contain ordinary and pool series that are restricted to have the same coefficient across all members of the pool. The second list, if provided, should contain pool variables that have different coefficients for each cross-section member of the pool. If there is a cross-section specific regressor list, the two lists must be separated by “@CXREG”. The third list, if provided, should contain pool variables that have different coefficients for each period. The list should be separated from the previous lists by “@PERREG”.
You may include AR terms as regressors in either the common or cross-section specific lists. AR terms are, however, not allowed for some estimation methods. MA terms are not supported.
Instruments should be specified in one of three lists. The “@INST” list should contain instruments that are common across all cross-sections and periods. The “@CXINST” should contain instruments that differ across cross-sections, while the “@PERINST” list specifies instruments that differ across periods.
There must be at least as many instrumental variables as there are independent variables. All exogenous variables included in the regressor list should also be included in the corresponding instrument list. A constant is included in the common instrumental list if not explicitly specified.
Options
General options
 
m=integer
Set maximum number of iterations.
c=number
Set convergence criterion. The criterion is based upon the maximum of the percentage changes in the scaled coefficients. The criterion will be set to the nearest value between 1e-24 and 0.2.
numericderiv / ‑numericderiv
[Do / do not] use numeric derivatives only. If omitted, EViews will follow the global default.
fastderiv / ‑fastderiv
[Do / do not] use fast derivative computation. If omitted, EViews will follow the global default.
showopts / ‑showopts
[Do / do not] display the starting coefficient values and estimation options in the estimation output.
s
Use the current coefficient values in “C” as starting values for equations with AR or MA terms (see also param ).
s=number
Determine starting values for equations specified by list with AR or MA terms. Specify a number between zero and one representing the fraction of preliminary least squares estimates computed without AR or MA terms. Note that out of range values are set to “s=1”. Specifying “s=0” initializes coefficients to zero. By default, EViews uses “s=1”.
cx=arg
Cross-section effects. For fixed effects estimation, use “cx=f”; for random effects estimation, use “cx=r”.
per=arg
Period effects. For fixed effects estimation, use “cx=f”; for random effects estimation, use “cx=r”.
wgt=arg
GLS weighting: (default) none, cross-section system weights (“wgt=cxsur”), period system weights (“wgt=persur”), cross-section diagonal weighs (“wgt=cxdiag”), period diagonal weights (“wgt=perdiag”).
cov=arg
Coefficient covariance method: (default) ordinary, White cross-section system robust (“cov=cxwhite”), White period system robust (“cov=perwhite”), White heteroskedasticity robust (“cov=stackedwhite”), Cross-section system robust/PCSE (“cov=cxsur”), Period system robust/PCSE (“cov=persur”), Cross-section heteroskedasticity robust/PCSE (“cov=cxdiag”), Period heteroskedasticity robust (“cov=perdiag”).
keepwgts
Keep full set of GLS weights used in estimation with object, if applicable (by default, only small memory weights are saved).
rancalc=arg (default=“sa”)
Random component method: Swamy-Arora (“rancalc=sa”), Wansbeek-Kapteyn (“rancalc=wk”), Wallace-Hussain (“rancalc=wh”).
nodf
Do not perform degree of freedom corrections in computing coefficient covariance matrix. The default is to use degree of freedom corrections.
coef=arg
Specify the name of the coefficient vector (if specified by list); the default is to use the “C” coefficient vector.
iter=arg (default=“onec”)
Iteration control for GLS specifications: perform one weight iteration, then iterate coefficients to convergence (“iter=onec”), iterate weights and coefficients simultaneously to convergence (“iter=sim”), iterate weights and coefficients sequentially to convergence (“iter=seq”), perform one weight iteration, then one coefficient step (“iter=oneb”).
Note that random effects models currently do not permit weight iteration to convergence.
s
Use the current coefficient values in “C” as starting values for equations with AR or MA terms (see also param ).
s=number
Determine starting values for equations specified by list with AR terms. Specify a number between zero and one representing the fraction of preliminary least squares estimates computed without AR terms. Note that out of range values are set to “s=1”. Specifying “s=0” initializes coefficients to zero. By default, EViews uses “s=1”.
unbalsur
Compute SUR factorization in unbalanced data using the subset of available observations for a cluster.
prompt
Force the dialog to appear from within a program.
p
Print estimation results.
Examples
pool1.tsls y? c x? @inst z?
estimates TSLS on the pool specification using common instruments Z?
Cross-references
See “Two-stage Least Squares” and “Two-Stage Least Squares” for details on two-stage least squares estimation in single equations and systems, respectively.
“Instrumental Variables” discusses estimation using pool objects, while “Instrumental Variables Estimation” discusses estimation in panel structured workfiles.
See also Pool::ls.