(0.025) (0.022) Year 2013 0.366* 0.424* (0.025) (0.022) Year 2014 0.347* 0.430* (0.025) (0.022) Intercept 2.511* 1.431* 2.377* 1.421* (0.004) (0.043) (0.003) (0.038) Adj_R2 0.008 0.475 0.003 0.502 Observations 29939 29939 30621 30621 Notes: This table presents coefficients of OLS regressions taking log pay as the dependent variable. (1) and (3) are for models including the disabled groups only, (2) and (4) are for models including a wide range of characteristics. Each coefficient can be interpreted as a percentage pay gap and standard errors for the coefficients are shown in parenthesis on the line below. + Statistically significant at 5%; * Statistically significant at 1%.
(0.025) (0.022) Year 2013 0.366* 0.424* (0.025) (0.022) Year 2014 0.347* 0.430* (0.025) (0.022) Intercept 2.511* 1.431* 2.377* 1.421* (0.004) (0.043) (0.003) (0.038) Adj_R2 0.008 0.475 0.003 0.502 Observations 29939 29939 30621 30621 Notes: This table presents coefficients of OLS regressions taking log pay as the dependent variable. (1) and (3) are for models including the disabled groups only, (2) and (4) are for models including a wide range of characteristics. Each coefficient can be interpreted as a percentage pay gap and standard errors for the coefficients are shown in parenthesis on the line below. + Statistically significant at 5%; * Statistically significant at 1%.
research-report-107-the-disability-pay-gap.docx