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nwest

Estimation with Newey-West correction on standard errors

CALLING SEQUENCE

[rnwest]=nwest(namey,varargin)

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 'win=n' where n is the length of the Barlett window (default = floor(5*nobs^0.25))

 

Output

* rnwest = a results tlist with

  - rnwest('meth') = 'Newey-West''s'

  - rnwest('y') = y data vector

  - rnwest('x') = x data matrix

  - rnwest('nobs') = # observations

  - rnwest('nvar') = # variables

  - rnwest('beta') = bhat

  - rnwest('yhat') = yhat

  - rnwest('resid') = residuals

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

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

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

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

  - rnwest('tstat') = t-stats

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

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

  - rnwest('condindex') = multicolinearity cond index

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

  - rnwest('rsqr') = rsquared

  - rnwest('rbar') = rbar-squared

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

  - rnwest('pvaluef') = its significance level

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

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

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

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

DESCRIPTION

Computes Newey-West's adjusted heteroscedastic and autocorrelation consistent (HAC) Least-squares Regression

EXAMPLE

load('grocer/bdexamples/bdhenderic.dat') ; bounds('1964q3','1989q2') ; rnwest=nwest('del(lm1-lp)','del(lp)','rnet','lagts(1,lm1-lp-ly)','cte')
 
// Example taken from nwest1_d, applies the Newet-west correction to the Hendry and Ericsson (1991) preferred specification with a default Barlett window.

AUTHOR

Emmanuel Michaux 2004

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