Eestimated coefficient. t-value

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1 Table 1: Estimated wage curves for men, Dependent variable: log (real wage rate) Dependent variable: log real wage rate Men Men, Rendom-effect Fixed-effect z-vae t-vae Men GMM, One step result z-vae lag of log(hourly wage) L.logW *** log unemployment log u *** *** log u *** (Dummy for 91-01)*log D 91_01 *log u unemployment *** *** D 91_01 *log u *** (Dummy for 02-09)* log unemployment D 02_09 *log u *** *** D 02_09 *log u ** age40_59 log WA ** *** log WA Work force size log WS *** *** log WS *** firm size(over1000 employees) log FS *** *** log FS *** living costs for regions log LC ** ** log LC time trend Year *** *** Year *** Intercept *** *** *** Regressioin diagnostics observations Observations 1175 N of groups N of instruments 34 sigma_u sigma_e rho R-sq : within : between : overall Wald chi2 F test that all u_i=0 Wald chi2(8) = F(46, 1214) = Prob > F = Wald chi2(9) =

2 Table 2: Estimated wage curves for women, Dependent variable: log real wage rate Women, Women, Women, Rendom-effect Fixed-effect GMM z-vae t-vae z-vae lag of log(hourly wage) L.logW *** log unemployment log u *** *** log u *** (Dummy for 91-01)*log D 91_01 *log u unemployment *** *** D 91_01 *log u *** (Dummy for 02-09)* log unemployment D 02_09 *log u *** *** D 02_09 *log u *** age40_59 log WA *** *** log WA *** Work force size log WS *** ** log WS ** firm size(over1000 employees) log FS *** *** log FS *** living costs for regions log LC *** log LC time trend Year *** *** Year *** Intercept Intercept *** *** Intercept *** Regressioin diagnostics Observations Obzervations 1175 N of groups N of instruments 334 sigma_u sigma_e rho R-sq : within : between : overall Wald chi2 F test that all u_i=0 Hausman test F(46, 1214) = Prob > F = Chi2(8) = Wald chi2(8) = Wald chi2(9) =

3 Table 3: Estimated wage curves for both sexes, Dependent variable: log real wage rate Both sexes, Both sexes, Both sexes, Rendom-effect Fixed-effect GMM z-vae t-vae z-vae lag of log(hourly wage) L.logW *** log unemployment log u *** *** log u *** (Dummy for 91-01)*log D 91_01 *log u unemployment *** *** D 91_01 *log u *** (Dummy for 02-09)* log unemployment D 02_09 *log u *** *** D 02_09 *log u *** age40_59 log WA *** *** log WA Work force size log WS *** *** log WS *** firm size(over1000 employees) log FS *** *** log FS *** living costs for regions log LC log LC time trend Year *** *** Year *** Intercept Intercept *** *** Intercept *** Regressioin diagnostics Observations Obzervations 1175 N of groups N of instruments 334 sigma_u sigma_e rho R-sq : within : between : overall Wald chi2 Wald chi2(8) = Wald chi2(9) = F test that all u_i=0 Hausman test F(46, 1214) = Prob > F = Chi2(8) =

4 Notes for Tables 1 through 3 1. *, **, and *** refer to the statistical significance at the 1%, 5%, and 10% levels, respectively. 2. Observations are for 47 prefectures X 27 years. 3. Wage rates are defined as follows: {(monthly wages incding family and commuting allowances, overtime payments, etc.) X 12 + (annual bonuses)}/cpi 4. GMM estimation is corrected for heteroschedasticity Figure 2: Predicted log wage rate and log unemployment for men,

5 Figure 3: Predicted log wage rate and log unemployment for men, Figure 4 Predicted log wage rate and log unemployment for men,

6 Figure 5: Predicted log wage rate and log unemployment for women,

7 Figure 6: Predicted log wage rate and log unemployment for women, Figure 7: Predicted log wage rate and log unemployment for women,

8 Figure 8: Predicted log wage rate and log unemployment for both sexes, Figure 9: Predicted log wage rate and log unemployment for both sexes, Figure 10: Predicted log wage rate and log unemployment for both sexes,

9 Table 4: Instrumental variable results Dependent variable: log real wage rate Men, Women, Both sexes, IV IV IV z-vae z-vae z-vae log unemployment log u *** *** *** (Dummy for 91-01)*log D 91_0 1*log u *** *** *** (Dummy for 02-09)* log unemployment D 02_09 *log u *** *** *** age40_59 log WA ** ** ** Work force size log WS *** ** ** firm size(over1000 employees) log FS *** *** *** living costs for regions log LC *** * time trend Year *** *** *** Intercept Intercept *** *** *** Regressioin diagnostics Observations N of groups sigma_u sigma_e rho R-sq : within : between : overall Wald chi2 Wald chi2(8) = Wald chi2(8) = Wald chi2(8) = Notes: 1. The instrumental variables are as follows: Dummy for 91 01, Dummy for 02 09, log WA, log WS, log FS, log LC, ratio of active job openings, proportion of employees to total labour force.

10 2. *, **, and *** refer to the statistical significance at the 1%, 5%, and 10% levels, respectively. Appendix: Descriptive statistics Men Women Both sexes Variable Mean Std. Dev. Min Max Mean Std. Dev. Min Max wage income (1,000 yen) unemployment rate (%) log wage income log unemployment fixed hours of work overtime hours of work proportion of employees aged number of regular employees proportion of employees in firms with 1,000 or more regional cost of living

Panel A: Treated firm matched to one control firm. t + 1 t + 2 t + 3 Total CFO Compensation 5.03% 0.84% 10.27% [0.384] [0.892] [0.

Panel A: Treated firm matched to one control firm. t + 1 t + 2 t + 3 Total CFO Compensation 5.03% 0.84% 10.27% [0.384] [0.892] [0. Online Appendix 1 Table O1: Determinants of CMO Compensation: Selection based on both number of other firms in industry that have CMOs and number of other firms in industry with MBA educated executives