Quarterly U.S. macroeconomic time series (1959Q1–2000Q4) used in Baum, Schaffer & Stillman (2007) to illustrate HAC standard errors, two-step GMM, and CUE estimation. Original source: Stock and Watson (2003).
Format
A data frame with 168 observations and 17 variables:
- year
Calendar year.
- quarter
Quarter (1–4).
- date
Stata quarterly date (0 = 1960Q1).
- UR
Unemployment rate (percent).
- CPI
Consumer Price Index.
- FFIR
Federal funds interest rate.
- TBILL
Treasury bill rate.
- TBON
Treasury bond rate.
- ER
Trade-weighted exchange rate.
- GDP
Nominal GDP (billions of dollars).
- inf
Annualized CPI inflation:
100 * log(CPI / L4.CPI).NAfor the first 4 observations.- ggdp
Annualized GDP growth:
100 * log(GDP / L4.GDP).NAfor the first 4 observations.- dinf
First difference of inflation (
inf - L.inf).NAfor the first 5 observations.- ggdp_2
Second lag of GDP growth (
L2.ggdp).- TBILL_1
First lag of Treasury bill rate (
L.TBILL).- ER_1
First lag of exchange rate (
L.ER).- TBON_1
First lag of Treasury bond rate (
L.TBON).
Source
Stock, J.H. and Watson, M.W. (2003). Introduction to Econometrics. Addison-Wesley.
Downloaded from http://fmwww.bc.edu/ec-p/data/stockwatson/macrodat.dta.
Redistribution basis: system.file("COPYRIGHTS", package = "ivreg2r").
Details
The derived variables inf, ggdp, dinf, and the lagged
instrument columns are pre-computed following Baum, Schaffer & Stillman
(2007, p. 474) so that
users can replicate their examples directly without time-series operators.
References
Baum, C.F., Schaffer, M.E. and Stillman, S. (2007). Enhanced routines for instrumental variables/generalized method of moments estimation and testing. The Stata Journal, 7(4), 465–506.
Examples
data(stockwatson)
# Baum, Schaffer & Stillman (2007), p. 475: 2SLS with IID errors
fit_iv <- ivreg2(dinf ~ 1 | UR | ggdp_2 + TBILL_1 + ER_1 + TBON_1,
data = stockwatson)
summary(fit_iv)
#>
#> 2SLS Estimation
#>
#> Call:
#> ivreg2(formula = dinf ~ 1 | UR | ggdp_2 + TBILL_1 + ER_1 + TBON_1,
#> data = stockwatson)
#>
#> Observations: 158
#> VCV type: Classical (iid)
#>
#> Coefficients:
#> Estimate Std. Error z value Pr(>|z|)
#> (Intercept) 0.93807 0.29420 3.189 0.00143 **
#> UR -0.15501 0.04833 -3.208 0.00134 **
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> ---
#> R-squared: 0.1914
#> Adj. R-squared: 0.1862
#> Wald chi2(1): 10.2 (p = 0.0017)
#> Root MSE: 0.5543
#>
#> Underidentification test (Anderson canon. corr. LM statistic):
#> Chi-sq(4) = 58.66 (p = 0.0000)
#>
#> Weak identification test:
#> Cragg-Donald Wald F: 22.58
#> Stock-Yogo critical values (IV size):
#> 10% maximal IV size 24.58
#> 15% maximal IV size 13.96
#> 20% maximal IV size 10.26
#> 25% maximal IV size 8.31
#> Stock-Yogo critical values (IV relative bias):
#> 5% maximal IV relative bias 16.85
#> 10% maximal IV relative bias 10.27
#> 20% maximal IV relative bias 6.71
#> 30% maximal IV relative bias 5.34
#>
#> Overidentification test (Sargan):
#> Chi-sq(3) = 5.85 (p = 0.1191)
#>
#> Weak-instrument-robust inference:
#> H0: B1=0 and orthogonality conditions are valid
#> Anderson-Rubin Wald F(4,153) = 3.44 (p = 0.0100)
#> Anderson-Rubin Wald Chi-sq(4) = 14.23 (p = 0.0066)
#> Stock-Wright LM S Chi-sq(4) = 13.05 (p = 0.0110)
#>
#> Endogeneity test:
#> Chi-sq(1) = 0.50 (p = 0.4783)
#> Tested: UR
#>
#> First-stage diagnostics:
#> Endogenous F-stat p-value Partial R2 Shea PR2 SW F AP F
#> UR 22.58 0.0000 0.3712 0.3712 22.58 22.58
#>
#> Instrumented: UR
#> Excluded instruments: ggdp_2, TBILL_1, ER_1, TBON_1
#>
# \donttest{
# Baum, Schaffer & Stillman (2007), p. 476: two-step GMM with HAC (Bartlett, bw=5)
fit_gmm <- ivreg2(dinf ~ 1 | UR | ggdp_2 + TBILL_1 + ER_1 + TBON_1,
data = stockwatson, method = "gmm2s",
vcov = "robust", kernel = "bartlett", bw = 5,
tvar = "date")
summary(fit_gmm)
#>
#> 2-Step GMM Estimation
#>
#> Call:
#> ivreg2(formula = dinf ~ 1 | UR | ggdp_2 + TBILL_1 + ER_1 + TBON_1,
#> data = stockwatson, vcov = "robust", method = "gmm2s", kernel = "bartlett",
#> bw = 5, tvar = "date")
#>
#> Observations: 158
#> VCV type: HAC (kernel=Bartlett; bandwidth=5)
#> Estimates efficient for arbitrary autocorrelation
#>
#> Coefficients:
#> Estimate Std. Error z value Pr(>|z|)
#> (Intercept) 0.58508 0.37240 1.571 0.116
#> UR -0.10024 0.06346 -1.580 0.114
#> ---
#> R-squared: 0.1548
#> Adj. R-squared: 0.1493
#> Wald chi2(1): 2.5 (p = 0.1185)
#> Root MSE: 0.5668
#>
#> Underidentification test (Kleibergen-Paap rk LM statistic):
#> Chi-sq(4) = 7.95 (p = 0.0933)
#>
#> Weak identification test:
#> Cragg-Donald Wald F: 22.58
#> Kleibergen-Paap rk Wald F: 7.36
#> (Stock-Yogo critical values are for iid errors)
#> Stock-Yogo critical values (IV size):
#> 10% maximal IV size 24.58
#> 15% maximal IV size 13.96
#> 20% maximal IV size 10.26
#> 25% maximal IV size 8.31
#> Stock-Yogo critical values (IV relative bias):
#> 5% maximal IV relative bias 16.85
#> 10% maximal IV relative bias 10.27
#> 20% maximal IV relative bias 6.71
#> 30% maximal IV relative bias 5.34
#>
#> Overidentification test (Hansen J):
#> Chi-sq(3) = 3.57 (p = 0.3119)
#>
#> Weak-instrument-robust inference:
#> H0: B1=0 and orthogonality conditions are valid
#> Anderson-Rubin Wald F(4,153) = 1.41 (p = 0.2343)
#> Anderson-Rubin Wald Chi-sq(4) = 5.81 (p = 0.2137)
#> Stock-Wright LM S Chi-sq(4) = 3.18 (p = 0.5278)
#>
#> Endogeneity test:
#> Chi-sq(1) = 1.03 (p = 0.3112)
#> Tested: UR
#>
#> First-stage diagnostics:
#> Endogenous F-stat p-value Partial R2 Shea PR2 SW F AP F
#> UR 7.36 0.0000 0.3712 0.3712 7.36 7.36
#>
#> Instrumented: UR
#> Excluded instruments: ggdp_2, TBILL_1, ER_1, TBON_1
#>
# }