Managing Long Working Hours: Evidence from a Management Practice Survey

Mari Tanaka; Taisuke Kameda; Takuma Kawamoto; Shigeru Sugihara; Ryo Kambayashi

doi:10.3368/jhr.0421-11605R2

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Figure 1
Distribution of Overtime Hours by Changes in Management Scores
Notes: We divide the sample of establishments into two groups according to whether the change of the overall management scores from 2010 to 2015 is below (left panel) or above (right panel) the median of the changes in the sample. The figures show the histograms of overtime hours among male workers by two groups of establishments and by periods 2010–2011 (light gray) and 2015–2016 (transparent). All workers working for more than 50 hours are top-coded as above 50 hours.
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Figure 2
Complementarity of Bonus–Promotion and Monitoring–Targeting: Graphical Representation
Notes: The figure visualizes the results of Table 4. In Panel A, we plot the estimates of the marginal contribution of bonus and promotion score, defined by , where ΔBP_jt is one standard deviation of the change of the bonus and promotion score from 2010 to 2015. The panel depicts this value at three levels of the monitoring and targeting score (MT_jt): the tenth percentile, the sample average, and the 90th percentile in 2010. In Panel B, we plot the estimates of the marginal contribution of monitoring and targeting score, defined by , where ΔMT_jt is one standard deviation of the change of the monitoring and targeting score from 2010 to 2015. The panel depicts this value at three levels of the bonus and promotion score (BP_jt): the tenth percentile, the sample average, and the 90th percentile in 2010. The marginal contributions in the y-axis are shown in percentage terms of the mean of the dependent variable (that is, an indicator of working overtime above the hours shown on the x-axis).
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Figure 3
Quantile Regressions for Overtime Hours
Notes: The figure summarizes the results of quantile regressions for overtime hours. We first obtain the residuals after the mean regression of individual overtime hours on establishment fixed effects and the log of the total cost for intermediate goods. We then regress the residuals on the change in the management scores from 2010 to 2015, an indicator for observations in 2015 or 2016, and their interaction term using quantile regressions. As the management score, Panel A uses the overall management score, Panel B uses the bonuses and promotion score, Panel C uses the monitoring and targeting score, and Panel D uses the displacement score, respectively. The estimated coefficients of the interaction term are presented in the figure. The 95 percent confidence intervals were calculated based on standard errors estimated by bootstrapping with 500 replications. As the distributions of overtime hours are truncated at zero, nonzero changes at the lower percentiles of the distributions are observed only for a limited fraction of establishments. The gray areas indicate the magnitude of this issue by color. As shown in Online Appendix Figure A.5, (i) about three-quarters of the establishments have zero as the tenth percentile of the establishment’s distribution of overtime hours, (ii) about half of the establishments have zero as the 20th percentile of the distribution of overtime hours, and (iii) about a quarter of the establishments have zero as the 45th percentile of the distribution of overtime hours.

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Table 1

Average Overtime Hours and Management Practices

	Overtime Hours
	(1)	(2)	(3)
Overall management Score	2.553^***	−2.436
	(0.495)	(4.747)
Bonus–promotion			8.623^**
			(4.053)
Monitoring–targeting			−5.579
			(3.713)
Displacement			−1.228
			(2.323)
Observations	72,180	72,180	72,180
Worker attributes	Yes	Yes	Yes
Demand control	Yes	Yes	Yes
Year FE	Yes	Yes	Yes
Establishment FE	No	Yes	Yes
Mean dep. var.	18.07	18.07	18.07

Notes: Column 1 controls only for year fixed effects, worker attributes (age, age-squared, tenure, tenure-squared, female dummy, and three education dummies), and the log of intermediate input cost. Columns 2–3 additionally control for the establishment of fixed effects. Standard errors are clustered at the level of the establishment and are reported in parentheses. ^*p < 0.1, ^**p < 0.05, ^***p < 0.01.

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Table 2

Distribution of Overtime Hours and Management Practices

	Over 5 h	Over 10 h	Over 15 h	Over 20 h	Over 25 h	Over 30 h	Over 35 h	Over 40 h	Over 45 h	Over 50 h
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
Bonus–promotion	0.216^***	0.253^***	0.250^***	0.253^**	0.227^**	0.171^*	0.132^*	0.091	0.050	0.038
	(0.083)	(0.083)	(0.093)	(0.101)	(0.103)	(0.093)	(0.073)	(0.062)	(0.050)	(0.044)
Monitoring–targeting	−0.007	−0.027	−0.070	−0.115	−0.133	−0.133	−0.118^*	−0.097^*	−0.082^*	−0.071^*
	(0.071)	(0.078)	(0.089)	(0.096)	(0.095)	(0.085)	(0.068)	(0.058)	(0.048)	(0.040)
Displacement	−0.073	−0.042	−0.004	−0.015	−0.012	−0.016	−0.034	−0.028	−0.034	−0.021
	(0.057)	(0.055)	(0.055)	(0.051)	(0.050)	(0.046)	(0.040)	(0.036)	(0.032)	(0.030)
Observations	72,180	72,180	72,180	72,180	72,180	72,180	72,180	72,180	72,180	72,180
Mean dep. var.	0.634	0.536	0.457	0.380	0.309	0.249	0.195	0.149	0.106	0.0797

Notes: “Over a h” is defined by an indicator variable that takes one if the worker works more than a hours of overtime in the week, and zero otherwise. All regressions control for year fixed effects, establishment fixed effects, the log of intermediate input cost, and worker attributes (age, age-squared, tenure, tenure-squared, female dummy, and three education dummies). Standard errors are clustered at the level of the establishment and are reported in parentheses. ^*p < 0.1, ^**p < 0.05, ^***p < 0.01.

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Table 3

Distribution of Overtime Hours and Management Practices by Workers’ Characteristics

Panel A: Sample by Tenure
	Over 10 h		Over 45 h
	Junior	Senior	Junior	Senior
	(1)	(2)	(3)	(4)
Bonus–promotion	0.313^***	0.179^*	0.110^**	−0.007
	(0.093)	(0.096)	(0.056)	(0.067)
Monitoring–targeting	−0.025	−0.051	−0.106^**	−0.058
	(0.093)	(0.085)	(0.054)	(0.059)
Displacement	−0.065	−0.022	−0.055	−0.021
	(0.067)	(0.061)	(0.044)	(0.030)
Observations	35,268	36,906	35,268	36,906
Mean dep. var.	0.563	0.510	0.119	0.0926
Panel B: Sample by Gender
	Over 10 h		Over 45 h
	Male	Female	Male	Female
	(1)	(2)	(3)	(4)
Bonus–promotion	0.234^***	0.342^***	0.018	0.124^*
	(0.086)	(0.118)	(0.057)	(0.066)
Monitoring–targeting	−0.027	−0.056	−0.090	−0.058
	(0.079)	(0.128)	(0.056)	(0.058)
Displacement	−0.049	−0.009	−0.038	−0.022
	(0.056)	(0.081)	(0.039)	(0.035)
Observations	56,322	15,842	56,322	15,842
Mean dep. var.	0.587	0.356	0.124	0.0408
Panel C: Sample by Propensity
	Over 10 h		Over 45 h
	High P(10 h)	Low P(10 h)	High P(45 h)	Low P(45 h)
	(1)	(2)	(3)	(4)
Bonus–promotion	0.288^***	0.251^***	0.054	0.049
	(0.095)	(0.095)	(0.060)	(0.052)
Monitoring–targeting	0.013	−0.079	−0.111^*	−0.046
	(0.089)	(0.089)	(0.065)	(0.043)
Displacement	−0.084	−0.001	−0.047	−0.024
	(0.064)	(0.063)	(0.045)	(0.026)
Observations	36,383	35,791	36,243	35,931
Mean dep. var.	0.639	0.431	0.144	0.0672

Notes: In Panel A, columns labeled “Junior” use the sample of workers whose tenure is less than 11 years (median of tenure in the sample), and columns labeled “Senior” use the rest. In Panel B, columns labeled “Male” use the sample of male workers, and columns labeled “Female” use the female sample. In Panel C, the propensity function P(a h) is defined for each worker by Prob(Overtime hours ≥ a|X) for each a (= 10 and 45) and estimated using a probit model using the BSWS data in 2009 (see Online Appendix Table A.3 for the estimation result), where X is the set of workers’ attributes. Columns labeled “High P(a h)” use the sample of workers having above the median level of the estimated P(a h), and columns labeled “Low P(a h)” use the rest of the sample. All regressions control for year fixed effects, establishment fixed effects, the log of intermediate input cost, and female dummy (except for Panel B), tenure, tenure-squared, age, age-squared, and three education dummies. Standard errors are clustered at the level of the establishment and are reported in parentheses. ^*p < 0.1, ^**p < 0.05, ^***p < 0.01.

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Table 4

Testing Complementarity of Bonus–Promotion and Monitoring–Targeting

	Over 5 h	Over 10 h	Over 15 h	Over 20 h	Over 25 h	Over 30 h	Over 35 h	Over 40 h	Over 45 h	Over 50 h
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
Bonus–promotion	0.051	0.032	0.038	0.052	0.015	−0.086	−0.114	−0.156^*	−0.149^*	−0.142^*
	(0.157)	(0.131)	(0.137)	(0.142)	(0.142)	(0.133)	(0.110)	(0.094)	(0.081)	(0.076)
Monitoring–targeting	−0.235	−0.333^*	−0.363^*	−0.392^*	−0.424^**	−0.489^**	−0.458^***	−0.438^***	−0.357^***	−0.318^***
	(0.193)	(0.178)	(0.191)	(0.201)	(0.203)	(0.190)	(0.168)	(0.147)	(0.132)	(0.121)
Displacement	−0.070	−0.039	−0.000	−0.011	−0.009	−0.012	−0.030	−0.024	−0.031	−0.018
	(0.055)	(0.053)	(0.053)	(0.049)	(0.049)	(0.045)	(0.039)	(0.034)	(0.031)	(0.029)
Monitoring–targeting × Bonus–promotion	0.352	0.473^*	0.453^*	0.430^*	0.451^*	0.551^**	0.526^**	0.528^***	0.426^**	0.383^**
	(0.282)	(0.251)	(0.251)	(0.254)	(0.253)	(0.246)	(0.219)	(0.197)	(0.176)	(0.163)
Observations	72,180	72,180	72,180	72,180	72,180	72,180	72,180	72,180	72,180	72,180
Mean dep. var.	0.634	0.536	0.457	0.380	0.309	0.249	0.195	0.149	0.106	0.0797

Notes: This table shows the estimates of Equation 2 that adds the interaction term of the bonus–promotion and monitoring–targeting scores to the baseline specification in Table 2. Standard errors are clustered at the level of the establishment and are reported in parentheses. ^*p < 0.1, ^**p < 0.05, ^***p < 0.01.

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Table 5

Labor Turnover

	Hiring Rate		Separation Rate
	(1)	(2)	(3)	(4)
Bonus–promotion	−0.225	−0.205	0.080	0.095
	(0.155)	(0.156)	(0.158)	(0.163)
Monitoring–targeting	−0.068	−0.055	0.030	0.041
	(0.079)	(0.081)	(0.065)	(0.064)
Displacement	−0.040^*	−0.033	0.043	0.042
	(0.022)	(0.023)	(0.027)	(0.027)
Ln(Cost of intermediate inputs)	0.008		−0.008
	(0.008)		(0.006)
Ln(shipment)		−0.002		−0.017^**
		(0.008)		(0.009)
Observations	398	401	398	401
Mean dep. var.	0.110	0.111	0.101	0.102

Notes: This table uses the sample of the Survey of Employment Trends (2010, 2011, 2014, 2015) in the balanced panel of establishments that are matched to the JP-MOPS for at least one year in each period of 2010–2011 and 2014–2015 and have nonmissing observations for the establishment’s total cost of inputs. All regressions control for year fixed effects, establishment fixed effects, and either the log of intermediate input cost or the log of the shipment value of the year. “Hiring rate” is the number of full-time workers hired during the year divided by the number of full-time workers at the beginning of the year. “Separation rate” is the number of full-time workers that left their jobs during the year divided by the number of full-time workers at the beginning of the year. Standard errors are clustered at the level of the establishment and are reported in parentheses.

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Table 6

Distribution of Overtime Hours within Establishments

	Average Overtime Hours		Max.–Min. of Overtime Hours		95th–5th Percentile of Overtime Hours
	(1)	(2)	(3)	(4)	(5)	(6)
Overall management score	1.308		−9.955		−5.469
	(4.456)		(9.261)		(8.816)
Bonus–promotion		6.370^*		1.093		3.568
		(3.613)		(7.891)		(7.525)
Monitoring–targeting		−1.447		−7.199		−3.353
		(3.518)		(7.037)		(6.964)
Displacement		−1.667		−0.614		−2.110
		(2.342)		(5.508)		(4.816)
Observations	2,307	2,307	2,307	2,307	2,307	2,307
Mean dep. var.	17.26	17.26	49.05	49.05	41.29	41.29

Notes: This table uses the sample of the BSWS (in 2010–2011 and 2015–2016) aggregated at the level of establishment–year and matched to the JP-MOPS data on management practices in 2010 and 2015. All regressions control for year fixed effects, establishment fixed effects, and the log of intermediate input cost. “Average overtime hours” is the average of overtime hours in the establishment in the year. “Max. – min. of overtime hours” denotes the difference between the maximum and the minimum overtime hours in the establishment in the year. “95th – 5th percentile of overtime hours” denotes the difference between the 95th percentile and 5th percentile in the year. Standard errors are clustered at the level of establishments and are reported in parentheses. ^*p < 0.1, ^**p < 0.05, ^***p < 0.01.