Chapter 11
2024-12-12
library(wooldridge)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(stargazer)##
## Please cite as:## Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.## R package version 5.2.3. https://CRAN.R-project.org/package=stargazer# Load the data
data("minwage")
# Create lagged variables
minwage <- minwage %>%
mutate(gwage232_lag1 = lag(gwage232, 1),
gemp232_lag1 = lag(gemp232, 1))
# Handle missing values (e.g., by removing rows with missing values)
minwage <- na.omit(minwage)
# (i) First-order autocorrelation
acf(minwage$gwage232, lag.max = 1)
# (ii) Dynamic model estimation
model1 <- lm(gwage232 ~ gwage232_lag1 + gmwage + gcpi, data = minwage)
summary(model1)##
## Call:
## lm(formula = gwage232 ~ gwage232_lag1 + gmwage + gcpi, data = minwage)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.044649 -0.004114 -0.001262 0.004481 0.041568
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0023648 0.0004295 5.506 5.45e-08 ***
## gwage232_lag1 -0.0684816 0.0343986 -1.991 0.0470 *
## gmwage 0.1517511 0.0095115 15.955 < 2e-16 ***
## gcpi 0.2586795 0.0858602 3.013 0.0027 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.007775 on 595 degrees of freedom
## Multiple R-squared: 0.3068, Adjusted R-squared: 0.3033
## F-statistic: 87.79 on 3 and 595 DF, p-value: < 2.2e-16# (iii) Adding lagged employment
model2 <- lm(gwage232 ~ gwage232_lag1 + gmwage + gcpi + gemp232_lag1, data = minwage)
summary(model2)##
## Call:
## lm(formula = gwage232 ~ gwage232_lag1 + gmwage + gcpi + gemp232_lag1,
## data = minwage)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.043900 -0.004316 -0.000955 0.004255 0.042430
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0023960 0.0004254 5.633 2.74e-08 ***
## gwage232_lag1 -0.0656875 0.0340720 -1.928 0.054344 .
## gmwage 0.1525470 0.0094213 16.192 < 2e-16 ***
## gcpi 0.2536899 0.0850342 2.983 0.002968 **
## gemp232_lag1 0.0606620 0.0169691 3.575 0.000379 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.007699 on 594 degrees of freedom
## Multiple R-squared: 0.3214, Adjusted R-squared: 0.3169
## F-statistic: 70.34 on 4 and 594 DF, p-value: < 2.2e-16# (iv) Comparing models
stargazer(model1, model2, type = "text")##
## ===================================================================
## Dependent variable:
## -----------------------------------------------
## gwage232
## (1) (2)
## -------------------------------------------------------------------
## gwage232_lag1 -0.068** -0.066*
## (0.034) (0.034)
##
## gmwage 0.152*** 0.153***
## (0.010) (0.009)
##
## gcpi 0.259*** 0.254***
## (0.086) (0.085)
##
## gemp232_lag1 0.061***
## (0.017)
##
## Constant 0.002*** 0.002***
## (0.0004) (0.0004)
##
## -------------------------------------------------------------------
## Observations 599 599
## R2 0.307 0.321
## Adjusted R2 0.303 0.317
## Residual Std. Error 0.008 (df = 595) 0.008 (df = 594)
## F Statistic 87.792*** (df = 3; 595) 70.343*** (df = 4; 594)
## ===================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01# (v) Regression of gmwage on lagged variables
model3 <- lm(gmwage ~ gwage232_lag1 + gemp232_lag1, data = minwage)
summary(model3)##
## Call:
## lm(formula = gmwage ~ gwage232_lag1 + gemp232_lag1, data = minwage)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.01987 -0.00511 -0.00385 -0.00290 0.62191
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.003487 0.001465 2.380 0.0176 *
## gwage232_lag1 0.212051 0.146727 1.445 0.1489
## gemp232_lag1 -0.042776 0.073749 -0.580 0.5621
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03347 on 596 degrees of freedom
## Multiple R-squared: 0.004117, Adjusted R-squared: 0.0007754
## F-statistic: 1.232 on 2 and 596 DF, p-value: 0.2924R Markdown
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