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hwhitemod

White's adjusted heteroscedastic estimation for a model equation

CALLING SEQUENCE

[model2,rh1,...,rhn]=hwhitemod(model,tsmat,indeq,arg1,...,argn)

PARAMETERS

Input

* model = a model tlist

* tsmat = a tsmat containing all data needed for estimating the equation (should be the tsmat associated to the model, created by function create_dbmod)

* indeq = optional arguments which can be:

   - a string, the name of the equation to estimate or the keyword 'all' (to estimate all equations)

   - or an integer, the # of the equation in the model

* arg1,...,argn = optional arguments

   - 'noprint' if the user does not want to print the result (default: results are displayed on screen)

   - the string 'save=%t' if the user wants to save the estimated coefficients in the model tlist

Output

* model2 = the model tlist, with the estimated coefficients if the option save has been swtiched to %t

* rh1,...,rhn = a variable number of hwhite results tlists, each one corresponding to the results of the corresponding estimated equation

DESCRIPTION

Computes White's adjusted heteroscedastic consistent Least-squares Regression for equations of a model.

EXAMPLE

global GROCERDIR
// load the model small:
 load(GROCERDIR+'data\small.dat')
 // load the database small_db:
 load(GROCERDIR+'data\small_db.dat')
 // set the bounds:
 bounds('1980q1','2005q4');
// In the small model, estimate by ols the equation td_p3m_d1, with T-statistics corrected for heteroskedasticity by White's method.
// Save the estimated coefficients in the model tlist small
// and store into tlist rp3m_d1 the whole estimation results:
 [small,rp3m_d1]=hwhitemod(small,small_db,'td_p3m_d1','save=%t');
// In the small model, estimate by ols the equation td_p3m_d1, with T-statistics corrected for heteroskedasticity by White's method.

AUTHOR

Éric Dubois 2019

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