Appendix (Additional Materials for Electronic Media of the Journal) I. Variable Definition, Means and Standard Deviations

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1 1 Appendix (Additional Materials for Electronic Media of the Journal) I. Variable Definition, Means and Standard Deviations Table A1 provides the definition of variables, and the means and standard deviations for continuous variables used in the regression analysis. The dependent variable is log real wages in prices. The explanatory variables include potential experience, experience square, dummy variables for educational levels and an additional dummy variable to take into account any additional technical diploma or certificate obtained, dummy variables to capture type of employment (regular=1), sector (public=1), location of residence (rural =1), and control variables for region of residence and occupation. The 35 states and union territories of India were grouped into 6 regions North, North East, Central, West, East and South. Occupations are classified into nine one-digit level categories based on the National Occupational Classification (NOC), II. Ordinary Least Squares Estimates (OLS) of Male and Female Wage Functions By Gender, The OLS estimates of the male and female wage functions are given in columns 2 and 8 of the appendix tables A2-A5 for the years 1983, 1994, 2005 and 2012, respectively. The parameter estimates of the wage functions are also statistically significant at the 1% level and conform to the stylized facts. The log wage increases at a decreasing rate with potential experience and the returns to education increases as the level of education increases. An additional technical diploma or certificate fetches

2 2 higher reward in the labour market. The reward for women s secondary and above levels of education, including the additional technical diploma or certificate, is higher than men s. As expected wages in the rural labour market are much lower than in urban areas. Similarly, regular workers earn higher wages than casual workers in both rural and urban areas except females in III. Maximum Likelihood Estimates of Quantile Regression of Male and Female Wage Functions by Gender, The gender specific quantile regression estimates of the wage functions obtained using maximum likelihood method are also given in appendix tables A2-A5 for the years 1983, 1994; 2005 and Following the previous works, we also report the estimates at 5 points -10 th, 25 th, 50 th, 75 th and 90 th percentiles- of the wage distribution. The effects of the variables are in general in conformity with those observed using OLS, but the returns to human capital characteristics differ by gender at various points on the wage distribution. This provides justification for examining the gender wage gap across the wage distribution using the quantile regression approach. Examining the human capital factors namely experience and education, we find that the returns to experience declines across the distribution from lower (below median) to the upper (above median) percentiles for both men and women and is somewhat higher for males than for females, except at 90 th percentile for In general, the returns exhibit a tendency to rise and then fall at the upper tail for males while the coefficients of education in the female regression display a more or less monotonic increase as we move from the lower to the upper tail for all but higher

3 3 secondary and diploma levels where it declines at the top percentile. The return to women s graduate (both general and technical) education is higher than men s. The dummy variables regular and rural are included to capture the wage difference between regular and casual workers, and rural and urban labour markets. The coefficient of the regular dummy variable is positive and statistically significant at 1% level for both men and women in 1983 and 1994 and also for men in 2005 and 2012 except at the 10 th percentile. However, the premium enjoyed by regular female workers declines and it turns out to be negative for all percentiles except 90 th in The observed effect could be due to increasing casualization of work and females are pushed to such jobs because of career interruptions due to marriage, and child bearing and rearing. The coefficient of the dummy variable for rural residence is negative and statistically significant across the wage distribution in all the years, which is a clear indication of lower reward in rural labour markets. Note that the wages are adjusted for rural-urban differences in prices using location and state specific consumer price indices.

4 4 Table A1. Variable definition, means and standard deviations, Variable* Log daily wage (Rupees in price) (0.873) (0.879) (0.874) (0.848) Experience (years) (12.545) ( ) (12.431) ( ) (12.577) ( ) (12.720) ( ) Experience square (years) Dummy variables for Educational level: Illiterate & below primary Primary Middle Secondary Higher secondary & n.a Diploma/Certificate Graduate-general Graduate-technical ** Additional technical diploma/ certificate Regular/salaried worker(=1) Public sector(=1) n.a Rural areas(=1) Sex (male=1) # of observations 87,307 82,710 84,639 71,350 Note: * Additional control variables include dummy variables for 6 regions and 10 occupations. ** included with graduate-general due to small number of observations in certain segments of the labour market, n.a.: data not available.

5 Table A2. OLS and Quantile regression estimates of log daily wage functions for male and female wage workers, 1983 Explanatory variable Male Female OLS q(0.10) q(0.25) q(0,50) q(0.75) q(0.90) OLS q(0.10) q(0.25) q(0,50) q(0.75) q(0.90) Experience (years) (70.97) (43.37) (57.88) (57.52) (49.83) (32.37) (18.49) (9.3) (13.36) (13.11) (10.76) (8.37) Experience square (/1000) (-56.09) (-36.9) (-47.42) (-45.18) (-36.95) (-22.94) (-17.3) (-9.16) (-13.12) (-12.97) (-9.78) -0.2 (-6.7) Primary (32.65) (13.73) (21.21) (29.85) (30.11) (22.38) (10.28) (1.09) (4.17) (10.27) (13.01) (11.86) Middle (48.83) (22.77) (35.27) (43.56) (41.3) (27.98) (13.97) (3.96) (8.1) (14.68) (12.9) (9.61) Secondary (79.35) (40.47) (61.23) (70.2) (63.97) (42.75) (28.71) (16.11) (24.7) (30.55) (20.53) (13.7) Graduate & above (general & technical) (99.97) (51.78) (74.26) (85.71) (80.38) (56.3) (35.33) (21.96) (28.25) (33.21) (24.49) (18.68) Additional technical diploma/certificate (21.68) (14.12) (17.91) (18.42) (14.48) (8.81) (11.72) (10.1) (12.7) (8.78) (5.46) (1.92) Regular (37.96) (11.35) (26.98) (41.97) (41.74) (26.2) (21.61) (5.1) (16.73) (22.31) (22.45) (19.07) Rural (-63.71) (-34.1) (-49.1) (-55.24) (-52.01) (-37.43) (-22.75) (-11.91) (-17.13) (-21.28) (-19.33) (-13.54) Constant term (234.33) (95.08) (165.88) (214.09) (224.18) (167.88) (116.14) (51.85) (89.33) (120.08) (105.41) (80.36) Adjusted R 2 / Pseudo R 2 # of observations Note (i) t-statistics in parentheses. (ii) The set of explanatory variables includes 5 regional dummies and 9 occupation dummies in all the equations. 5

6 Table A3. OLS and quantile regression estimates of log daily wage functions for male and female wage workers, 1994 Explanatory Variable Male Female OLS q(0.10) Q(0.25) Q(,50) (q(.75) Q(.90) OLS q(0.10) Q(0.25) Q(,50) (q(.75) Q(.90) Experience (years) (67.97) (43.8) (56.84) (62.79) (58.08) (39.05) (26.63) (13.9) (17.87) (22.82) (20.45) (13.7) Experience square (/1000) (-51.72) (-35.8) (-44.97) (-47.83) (-42.24) (-26.02) (-23.09) (-12.66) (-15.92) (-20.22) (-17.3) (-11.37) Primary (24.55) (10.27) (16.71) (25.2) (27.26) (21.15) (7.26) (1.54) (3.89) (7.14) (8.9) (6.84) Middle (41.55) (18.74) (30.51) (42.61) (43.68) (34.04) (15.3) (3.8) (8.87) (14.39) (16.82) (12.52) Secondary (55.63) (25.51) (43.53) (57.57) (58.66) (41.76) (28.92) (9.3) (23.28) (27.87) (26.39) (16.38) Higher secondary & diploma /certificate (57.67) (28.6) (45.25) (58.1) (58.11) (41.83) (29.39) (13.77) (24.85) (26.5) (23.99) (14.99) Graduate-general (19.03) (14.07) (17.74) (19.48) (16.61) (11.21) (10.33) (2.97) (11.91) (9.22) (8.64) (5.01) Graduate-technical (81.63) (44.89) (67.19) (83.27) (84.1) (62.75) (40.24) (20.98) (35.64) (36.75) (34.76) (23.18) Additional technical diploma/certificate (51.69) (28.69) (42.82) (55.27) (55.51) (40.19) (25.34) (11.43) (21.22) (23.87) (23.2) (15.23) Regular (38.8) (13.39) (25.79) (42.23) (49.66) (37.26) (14.41) (5.53) (9.97) (11.13) (16.31) (15.07) Rural (-36.75) (-21.75) (-28.21) (-35.34) (-37.63) (-29.2) (-16.4) (-6.87) (-13.77) (-15.22) (-14.65) (-10.9) Constant term (206.19) (92.77) (149.81) (210.08) (232.69) (188.13) (109.08) (42.74) (88) (107.3) (112.2) (82.73) Adjusted R 2 / Pseudo R 2 # of observations Note (i) t-statistics in parentheses. (ii) The set of explanatory variables includes 5 regional dummies and 9 occupation dummies in all the equations. 6

7 Table A4. OLS and quantile regression estimates of log daily wage functions for male and female wage workers, 2005 Explanatory variable Male Female OLS q(0.10) q(0.25) q(0.50) q(0.75) q(0.90) OLS q(0.10) q(0.25) q(0.50) q(0.75) q(0.90) Experience (years) (81.62) (46.09) (59.85) (64.84) (54.07) (36.66) (39.43) (17.91) (24.4) (24.34) (24.57) (16.64) Experience square (/1000) (-57.23) (-35.64) (-44.85) (-45.96) (-35.25) (-20.66) (-32.7) (-15.29) (-20.47) (-20.49) (-20.34) (-13.07) Primary (26.15) (9.35) (14.95) (22.33) (24.18) (19.53) (10.91) (3.99) (5.46) (7.86) (9.50) (8.82) Middle (49.32) (18.29) (29.27) (41.64) (43.03) (35.06) (16.00) ) (9.43) (11.75) (12.97) (10.51) Secondary (61.63) (23.14) (36.45) (53.47) (54.38) (41.96) (27.54) (11.59) (14.4) (18.09) (23.41) (19.40) Higher Secondary (67.75) (26.29) (43.23) (59.17) (57.42) (43.77) (32.86) (13.97) (19.97) (27.21) (25.04) (19.95) Diploma (35.66) (14.29) (24.74) (31.66) (28.58) (21.67) (29.84) (19.05) (26.19) (27.36) (18.81) (14.20) Graduate-general (98.86) (45.42) (69.75) (86.04) (78.75) (62.31) (52.34) (30.23) (38.51) (42.47) (35.61) (27.23) Graduate-technical (81.75) (39.7) (58.62) (70.16) (64.07) (50.96) (45.13) (23.36) (35.74) (37.37) (30.08) (23.73) Additional technical diploma/certificate (7.09) (4.67) (4.52) (6.43) (5.66) (4.22) (2.99) (-4.1) (-3.29) (0.55) (3.26) (1.86) Regular (37.13) (7.98) (16.72) (31.71) (45.96) (46.98) (5.62) (-1.09) (1.23) (0.94) (7.65) (11.11) Rural (-11.99) (-9.86) (-9.55) (-8.71) (-8.06) (-8.31) (-9.40) (-2.08) (-5.96) (-8.9) (-7.27) (-6.03) Constant term (232.76) (105.71) (164.5) (212.92) (211.41) (180.53) (109.69) (67.32) (81.05) (91.18) (98.57) (85.69) Adj. R 2 / Pseudo R # of observations Note (i) t-statistics in parentheses. (ii) The set of explanatory variables includes 5 regional dummies and 9 occupation dummies in all the equations. 7

8 8 Table A5. OLS and quantile regression estimates of log daily wage functions for male and female wage workers, 2012 Explanatory variable Male Female OLS q(0.10) q(0.25) q(0.50) q(0.75) q(0.90) OLS q(0.10) q(0.25) q(0.50) q(0.75) q(0.90) Experience (years) (61.17) (31.48) (44.21) (49.84) (41.40) (33.67) (32.02) (14.17) (20.52) (23.25) (21.82) (16.74) Experience square (/1000) (-41.19) (-24.33) (-32.53) (-34.85) (-26.33) (-19.86) (-24.70) (-11.28) (-16.64) (-18.33) (-17.24) (-12.85) Primary (12.41) (2.97) (4.91) (9.67) (12.65) (11.95) (5.21) (1.64) (3.07) (3.31) (5.02) (4.73) Middle (29.59) (7.50) (14.75) (23.64) (27.17) (24.35) (11.66) (4.27) (6.18) (8.27) (9.28) (8.28) Secondary (41.98) (13.59) (21.42) (32.27) (36.86) (31.28) (18.80) (7.76) (9.81) (11.52) (14.79) (12.63) Higher secondary & diploma/ certificate (56.45) (19.06) (31.28) (47.12) (46.93) (39.77) (30.34) (11.64) (18.00) (24.08) (21.53) (16.47) Graduate-general (75.46) (29.72) (51.54) (62.55) (59.18) (48.58) (41.66) (20.09) (27.30) (35.72) (27.61) (21.83) Graduate-technical (64.13) (28.91) (46.46) (52.31) (47.00) (41.47) (37.70) (18.60) (27.26) (31.12) (23.78) (19.59) Additional technical diploma /certificate (11.34) (6.93) (9.82) (9.83) (7.30) (5.90) (5.10) (4.15) (3.84) (3.27) (1.18) (1.96) Regular (24.13) (-0.60) (4.61) (14.08) (31.08) (51.68) (-5.74) (-11.00) (-11.16) (-5.75) (-0.46) (9.29) Rural (-14.46) (-7.72) (-9.80) (-9.86) (-10.73) (-12.42) (-10.43) (-0.05) (-5.71) (-7.37) (-8.78) (-6.66) Constant term (220.18) (100.64) (155.55) (193.40) (185.76) (185.83) (80.87) (36.39) (54.05) (68.47) (77.95) (66.87) Adjusted R 2 / Pseudo R # of observations Note (i) t-statistics in parentheses. (ii) The set of explanatory variables includes 5 regional dummies and 9 occupation dummies in all the equations.