olsHALL.b: OLS regression model for consumption

In meboot: Maximum Entropy Bootstrap for Time Series

OLS regression model for consumption

Description

Compute OLS coefficients in a regression model for the consumption variable. See details.

Usage

    olsHALL.b (y, x)
  

Arguments

y	dependent variable (consumption).
x	regressor variable (disposable income).

Details

The regression model is: c(t) = b1 + b2*c(t) + b3*y(t-1) + u(t), where 'c' is consumption and 'y' is disposable income.

This function is intended to speed up the ME bootstrap procedure for inference. Instead of using the lm or dynlm interfaces the function calls directly to the Fortran procedure 'dqrls'.

Value

Coeffient estimates by OLS.

Examples

    data("USconsum")
    USconsum <- log(USconsum)

    # lm interface 
    lmcf1 <- lm(USconsum[-1,1] ~ USconsum[-51,1] + USconsum[-51,2])
    coefficients(lmcf1)
 
    # dynlm interface 
    library("dynlm")
    lmcf2 <- dynlm(consum ~ L(consum, 1) + L(dispinc, 1), data=USconsum)
    coefficients(lmcf2)

    # olsHALL.b
    olsHALL.b(y=USconsum[,1], x=USconsum[,2])
  

meboot documentation built on Aug. 23, 2023, 1:07 a.m.