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23 lines
1021 B
R
23 lines
1021 B
R
# Goals: Simulate a dataset from a "fixed effects" model, and
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# obtain "least squares dummy variable" (LSDV) estimates.
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#
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# We do this in the context of a familiar "earnings function" -
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# log earnings is quadratic in log experience, with parallel shifts by
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# education category.
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# Create an education factor with 4 levels --
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education <- factor(sample(1:4,1000, replace=TRUE),
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labels=c("none", "school", "college", "beyond"))
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# Simulate an experience variable with a plausible range --
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experience <- 30*runif(1000) # experience from 0 to 20 years
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# Make the intercept vary by education category between 4 given values --
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intercept <- c(0.5,1,1.5,2)[education]
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# Simulate the log earnings --
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log.earnings <- intercept +
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2*experience - 0.05*experience*experience + rnorm(1000)
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A <- data.frame(education, experience, e2=experience*experience, log.earnings)
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summary(A)
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# The OLS path to LSDV --
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summary(lm(log.earnings ~ -1 + education + experience + e2, A)) |