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Employment, wages, and capital stock for UK companies: an unbalanced annual panel over 1976–1984 (140 companies, 1,031 firm-year observations). This is the companion dataset to Arellano, M. and Bond, S. (1991), "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, 58(2), 277–297, shipped as distributed (levels plus the log transforms and year dummies used throughout the Stata literature).

Usage

abdata

Format

A data frame with 1,031 observations and 16 variables:

ind

Industry code.

year

Calendar year (1976–1984). The time variable: use as tvar.

emp

Employment.

wage

Real wage.

cap

Gross capital stock.

indoutpt

Industry output.

n

Log employment, log(emp).

w

Log real wage, log(wage).

k

Log gross capital stock, log(cap).

ys

Log industry output, log(indoutpt).

yr1980

Year dummy: 1 if year == 1980.

yr1981

Year dummy: 1 if year == 1981.

yr1982

Year dummy: 1 if year == 1982.

yr1983

Year dummy: 1 if year == 1983.

yr1984

Year dummy: 1 if year == 1984.

id

Firm identifier (140 distinct companies). Use as ivar.

Source

Arellano, M. and Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297.

Downloaded from http://fmwww.bc.edu/ec-p/data/macro/abdata.dta.

Redistribution basis: system.file("COPYRIGHTS", package = "ivreg2r").

Details

n, w, k, and ys are natural logs of emp, wage, cap, and indoutpt respectively. yr1980yr1984 are year-dummy indicators (1 in the named year, 0 otherwise).

See also

Examples

data(abdata)

# ivreg2 help file line 1558: one-way cluster on firm id
fit <- ivreg2(n ~ w + k, data = abdata, clusters = ~id)
summary(fit)
#> 
#> OLS Estimation
#> 
#> Call:
#> ivreg2(formula = n ~ w + k, data = abdata, clusters = ~id)
#> 
#> Observations: 1,031 
#> VCV type:     Cluster-robust 
#> Clusters:    140 (id)
#> 
#> Coefficients:
#>             Estimate Std. Error z value Pr(>|z|)    
#> (Intercept)  2.55693    0.67565   3.784 0.000154 ***
#> w           -0.36363    0.21596  -1.684 0.092230 .  
#> k            0.81085    0.03248  24.963  < 2e-16 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> ---
#> R-squared:      0.8345 
#> Adj. R-squared: 0.8342 
#> Wald chi2(2):  322.5 (p < 2.2e-16)
#> Root MSE:       0.5455 
#>