Artificial Weak Instrument Data

Artificial data set to illustrate the problem of weak instruments.

Usage

data("WeakInstrument")

Format

A data frame containing 200 observations on 3 variables.

y

dependent variable.

x

regressor variable.

z

instrument variable.

Source

Online complements to Stock and Watson (2007).

References

Stock, J.H. and Watson, M.W. (2007). Introduction to Econometrics, 2nd ed. Boston: Addison Wesley.

See also

StockWatson2007

Examples

data("WeakInstrument")
fm <- ivreg(y ~ x | z, data = WeakInstrument)
summary(fm)
#> 
#> Call:
#> ivreg(formula = y ~ x | z, data = WeakInstrument)
#> 
#> Residuals:
#>      Min       1Q   Median       3Q      Max 
#> -2.97431 -0.53401 -0.02326  0.60138  1.92226 
#> 
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)   
#> (Intercept) -0.01422    0.06890  -0.206  0.83673   
#> x            1.15773    0.42691   2.712  0.00728 **
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> Residual standard error: 0.8687 on 198 degrees of freedom
#> Multiple R-Squared: 0.7795,	Adjusted R-squared: 0.7784 
#> Wald test: 7.354 on 1 and 198 DF,  p-value: 0.007279 
#>