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olsc

Cochrane-Orcutt estimation of an autocorrelated model

CALLING SEQUENCE

rolsc=olsc(namey, arg1,...,argn)

PARAMETERS

Input

* namey = a time series, a real (nx1) vector or a string equal to the name of a time series or a (nx1) real vector between quotes

* argi = an argument which can be:

  - a time series

  - a real (nx1) vector

  - a real (nxk) matrix

  - a string equal to the name of a time series or a (nxk) real vector or matrix between quotes

  - a list of such elements

  - the string 'noprint' if the user doesn't want to display the results of the regression

  - the string 'maxit=n' where n is the maximum number of iterations that can be performed (default = 100)

  - the string 'crit=n' where crit is the convergence criterion, used to assess if the difference between successive values of the autocorrelation coefficient is significant (default=sqrt(%eps))

 

Output

* rolsc = a results tlist with

  - rolsc('meth') = 'Cochrane-Orcutt'

  - rolsc('y') = y data vector

  - rolsc('x') = x data matrix

  - rolsc('nobs') = # observations

  - rolsc('nvar') = # variables

  - rolsc('beta') = bhat

  - rolsc('yhat') = yhat

  - rolsc('resid') = residuals

  - rolsc('vcovar') = estimated variance-covariance matrix of beta

  - rolsc('sige') = estimated variance of the residuals

  - rolsc('sigu') = sum of squared residuals

  - rolsc('ser') = standard error of the regression

  - rolsc('tstat') = t-stats

  - rolsc('pvalue') = pvalue of the betas

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

  - rolsc('condindex') = multicolinearity cond index

  - rolsc('prescte') = boolean indicating the presence or absence of a constant in the regression

  - rolsc('rsqr') = rsquared

  - rolsc('rbar') = rbar-squared

  - rolsc('f') = F-stat for the nullity of coefficients other than the constant

  - rolsc('pvaluef') = its significance level

  - rolsc('prests') = boolean indicating the presence or absence of a time series in the regression

  - rolsc('namey') = name of the y variable

  - rolsc('namex') = name of the x variables

  - rolsc('bounds') = if there is a timeseries in the regression, the bounds of the regression

  - rolsc('rho') = estimated first order autocorrelation of residuals

  - rolsc('trho') = its Student t

  - rolsc('iterout') = a (niter x 3) matrix giving for each

DESCRIPTION

Computes Cochrane-Orcutt ols regression for AR1 errors. Endogenous variable must be given first, as a vector, a ts, between quotes (if the user wants to keep the name of the variable in the tlist result and for the printings) or not. Exogenous variables are given after, in one of the formats authorized for the endogenous one, or in matrix format. The program displays on screen various results (coefficients, tstat, R², Durbin and Watson, first order autocorrelation of residuals,...) except if the user has entered the argument 'noprint' anywhere after the first argument.

EXAMPLE

load('grocer/bdexamples/bdhenderic.dat') ; bounds('1964q3','1989q2') ; rolsc=olsc('delts(lm1-lp)','delts(lp)','rnet','lagts(1,lm1-lp-ly)','cte')
// This example, taken from olsar1_d, shows the estimation of first order autocorrelated model on Hendry and Ericsson (1991) preferred specification
// from which the variable 'delts(lagts(1,lm1-lp-ly))' has been withdrawn.

AUTHOR

Eric Dubois 2002

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