R: PSID Earnings Data 1982

PSID1982 {AER} | R Documentation

## PSID Earnings Data 1982

### Description

Cross-section data originating from the Panel Study on Income Dynamics, 1982.

### Usage

    data("PSID1982")

### Format

A data frame containing 595 observations on 12 variables.

experience

  Years of full-time work experience.

weeks

  Weeks worked.

occupation

  factor. Is the individual a white-collar (`"white"`) or blue-collar (`"blue"`) worker?

industry

  factor. Does the individual work in a manufacturing industry?

south

  factor. Does the individual reside in the South?

smsa

  factor. Does the individual reside in a SMSA (standard metropolitan statistical area)?

married

  factor. Is the individual married?

gender

  factor indicating gender.

union

  factor. Is the individual's wage set by a union contract?

education

  Years of education.

ethnicity

  factor indicating ethnicity. Is the individual African-American (`"afam"`) or not (`"other"`)?

wage

  Wage.

### Details

`PSID1982` is the cross-section for the year 1982 taken from a larger panel data set `PSID7682` for the years 1976–1982, originating from Cornwell and Rupert (1988). Baltagi (2002) just uses the 1982 cross-section; hence `PSID1982` is available as a standalone data set because it was included in AER prior to the availability of the full `PSID7682` panel version.

### Source

The data is from Baltagi (2002).

### References

Baltagi, B.H. (2002). Econometrics, 3rd ed. Berlin, Springer.

Cornwell, C., and Rupert, P. (1988). Efficient Estimation with Panel Data: An Empirical Comparison of Instrumental Variables Estimators. Journal of Applied Econometrics, 3, 149–155.

### See Also

`PSID7682`, `Baltagi2002`

### Examples

    data("PSID1982")
    plot(density(PSID1982$wage, bw = "SJ"))

    ## Baltagi (2002), Table 4.1
    earn_lm <- lm(log(wage) ~ . + I(experience^2), data = PSID1982)
    summary(earn_lm)

    ## Baltagi (2002), Table 13.1
    union_lpm <- lm(I(as.numeric(union) - 1) ~ . - wage, data = PSID1982)
    union_probit <- glm(union ~ . - wage, data = PSID1982, family = binomial(link = "probit"))
    union_logit <- glm(union ~ . - wage, data = PSID1982, family = binomial)
    ## probit OK, logit and LPM rather different.

[Package AER version 1.2-5 Index]