Name

iv1 — instrumental variables

CALLING SEQUENCE

[rtsls]=iv1(y,y1,x1,xall)

PARAMETERS

Input

• y = dependent variable vector (nobs x 1)

• y1 = endogenous variables matrix (nobs x g) for this equation

• xexog = exogenous variables matrix for this equation

• xall = instruments for variables y1

Output

• rtsls = a structure tlist with

  - rtsls ('meth') = 'tsls'

  - rtsls ('nobs') = nobs

  - rtsls ('nendog') = # of endogenous

  - rtsls ('nexog') = # of exogenous

  - rtsls ('nvar') = # of endogenous + # of exogenous

  - rtsls ('y') = y data vector

  - rtsls ('beta') = bhat estimates

  - rtsls ('tstat') = t-statistics

  - rtsls ('yhat') = yhat predicted values

  - rtsls ('resid') = residuals

  - rtsls ('residtsls') = residuals calculated with the endogenous variables replaced by their regression from

• first stage estimation

  - rtsls ('sigu') = e'*e

  - rtsls ('sige') = e'*e/(n-k)

  - rtsls ('dw') = Durbin-Watson Statistic

  - rtsls ('prescte') = boolean indicating the presence or

• absence of a constant in the regression

  - rtsls ('rsqr') = rsquared

  - rtsls ('rbar') = rbar-squared

  - rtsls ('f') = F-stat for the nullity of coefficients

• other than the constant

  - rtsls ('pvaluef') = its significance level

  - rtsls ('grsqr') = generalized rsquared (that is which takes into account the endogeneity of some explicative variables)

DESCRIPTION

Produces instrumental variables estimation when all variables are in vector or matrix form.

EXAMPLE

x1 = rand(200,1,'n');
x2 = rand(200,1,'n');

y1 = zeros(200,1);
y2 = zeros(200,1);
evec = rand(200,1,'n');
//
// create simultaneously determined variables y1,y2
y1 = 1+x1+evec;
y2 = 1+y1+x2+evec;

riv=iv1(y2,y1,[ones(200,1) x2],[ones(200,1) x1 x2]) 
// provides and stores into a tlist the results of the estimation of the regression of y2 onto y1, x2 and a constant, using x1, x2 and the constant as intruments
               

AUTHOR

Eric Dubois 2002