```
## Poisson models from Table I in Aghion et al. (2013)
## load data set
data("InstInnovation", package = "sandwich")
## log-scale variable
InstInnovation$lograndd <- log(InstInnovation$randd)
InstInnovation$lograndd[InstInnovation$lograndd == -Inf] <- 0
## regression formulas
f1 <- cites ~ institutions + log(capital/employment) + log(sales) + industry + year
f2 <- cites ~ institutions + log(capital/employment) + log(sales) +
industry + year + lograndd + drandd
f3 <- cites ~ institutions + log(capital/employment) + log(sales) +
industry + year + lograndd + drandd + dprecites + log(precites)
## Poisson models
tab_I_3_pois <- glm(f1, data = InstInnovation, family = poisson)
tab_I_4_pois <- glm(f2, data = InstInnovation, family = poisson)
tab_I_5_pois <- glm(f3, data = InstInnovation, family = poisson)
## one-way clustered covariances
vCL_I_3 <- vcovCL(tab_I_3_pois, cluster = ~ company)
vCL_I_4 <- vcovCL(tab_I_4_pois, cluster = ~ company)
vCL_I_5 <- vcovCL(tab_I_5_pois, cluster = ~ company)
## replication of columns 3 to 5 from Table I in Aghion et al. (2013)
cbind(coef(tab_I_3_pois), sqrt(diag(vCL_I_3)))[2:4, ]
cbind(coef(tab_I_4_pois), sqrt(diag(vCL_I_4)))[c(2:4, 148), ]
cbind(coef(tab_I_5_pois), sqrt(diag(vCL_I_5)))[c(2:4, 148), ]
```

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