Silviase/jgov_v1.4_full_ann huggingface dataset:
fines exceptions to the legal work hour standard. Overtime work hours under this agreement should be compensated by at least a 25-percent wage premium (Article 37). $ ^{4} $

The weekly legal work hours had been set at 48 per week until 1987 and then gradually declined to 40 by 1997. In response to diplomatic pressure to reduce the current account surplus, prior to the Tokyo summit of May 1986, the Japanese government established a clear policy goal to set a standard of 40 work hours per week. In accordance with this policy goal, the Labor Standard Law was revised in 1987 and implemented from April 1, 1988. Moratorium periods were given depending on industry and establishment size, and this transition is summarized in Appendix Table 1. The moratorium periods ended by March 1997, by which time the standard work hours had become 40 hours per week uniformly across industries and establishment sizes with a few exceptions. $ ^{5} $

Another important legal standard was set by the Temporary Act for the Promotion of Work Hour Reduction, which is often called Jitan Sokushin Ho, enacted on September 1, 1992. The law was effective for five years and offered three legal provisions. First, the law promoted the formation of an establishment-level committee, which consisted of employer and employee representatives, for work hour reduction. The agreement in the committee that is submitted to local labor standard office becomes a legally binding contact as a usual labor agreement (Roushi Kyoyaku). Second, the law provided the potential exemption from the Antitrust Law for the employers’ collusion in an effort to reduce work hours. This exemption was provided because establishments may exceedingly compete for quick service, and this excess competition may result in long working hours. Third, the law established a subsidy scheme that provided up to 3 million yen (about 30 thousand US dollars) to promote labor-saving capital investment for establishments that hired up to 300 regular employees. This paper abstracts from the effect of Jitan Sokushin Ho, but the law’s effect should be
absorbed by year dummy variables or the interaction terms of year and establishment size dummy variables.

## 3 Theory

This section discusses the effect of legal work hours on the actual hours worked and employment based on a simple static labor demand model, as in Calmfors and Hoel (1988) and Hunt (1999). Assume the firm produces output by using labor and capital and it faces an exogenous wage rate $ (w) $ , rental rate of capital $ (r) $ . The firm chooses the hours of work per worker $ (h) $ , employment $ (N) $ , and capital $ (K) $ given legal work hours $ (\bar{h}) $ , the overtime premium $ (p) $ , and the fixed cost of employment $ (f) $ . The firm produces output sold at a unit price using a given technology expressed as a production function $ g(h, N, K) $ . The firm solves the following profit maximization problem:

$$ \max_{h,N,K}g(h,N,K)-whN-fN-pw\max(0,(h-\bar{h}))N-rK. $$

The reduction of legal work hours $ \bar{h} $ increases the marginal cost of labor, and this reduces employment through the scale effect. In addition, the increase of the marginal cost of labor causes a substitution to capital. The isoquant and isocost curves on the hour and employment planes are drawn in Figure 2. This figure also indicates how the isocost curve changes when the number of legal work hours is reduced.

Figure 3 illustrates the results of comparative statics for the reduction of legal work hours. Case 1 considers the case in which the optimal hours are above the legal work hours before and after the legal work hour revision (i.e., $ h^{*} > \bar{h}_{0} > \bar{h}_{1} $ ) because of high fixed costs. The first-order conditions regarding labor inputs are given as:

$$ \begin{align*}g_{h}(h,N,K)&=MC_{h}=wN+pw,\\g_{N}(h,N,K)=MC_{N}&=wh+f+pw(h-\bar{h}).\end{align*} $$
The marginal cost of employment $ MC_{N} $ increases, while the marginal cost of hour $ MC_{h} $ does not change, in response to the reduction of legal work hours $ \bar{h} $ . This induces the substitution of employment to hour. Thus the reduction of legal work hours unambiguously reduces employment because of the scale effect and the substitution to hour (and capital). The effect on hour depends on whether the sum of the scale effect and the substitution effect to capital exceeds the substitution effect from employment.

By contrast, if the initial number of legal work hours does not bind but the number of revised legal work hours does (i.e. $ \bar{h}_{0} > h^{*} > \bar{h}_{1} $ , Figure 3 Case 2), the first-order conditions evaluated around the revised legal work hours becomes:

$$ \begin{aligned}g_{h}(h,N,K)&=MC_{h}&=wN if h\leq\bar{h}_{1},\\ &=wN(1+p)if h>\bar{h}_{1},\\ \end{aligned} $$

$$ \begin{aligned}g_{N}(h,N,K)&=MC_{N}&=wh+f if h\leq\bar{h}_{1},\\ &=wh+f+pw(h-\bar{h}_{1})if h>\bar{h}_{1}.\\ \end{aligned} $$

The discontinuities of the marginal costs of hour and employment at legal work hours create an incentive for a firm to set the actual hours at legal work hours. Thus, employment substitutes for hours of work. Because of the scale effect and substitution effect to capital, the hours of work unambiguously fall. The effect on employment depends on the relative size of the substitution effect between hours and employment, and the sum of the scale effect and the substitution effects to capital.

The analysis of the static model reveals that the reduction of legal work hours is more likely to reduce actual hours worked when 1. the fixed cost of employment is small (i.e., the legal work hour is initially not binding), 2. the scale effect is large (i.e., the labor cost share is large and product demand is price elastic), and 3. the capital substitution is large (i.e., the elasticity of substitution between labor and capital is large and capital supply is price elastic).
The dynamic structure of the legal work hour reduction adds another complexity to our analysis. The legal work hour reduction in Japan in the late 1980s and early 1990s took place gradually with moratorium periods, and the schedule of the legal work hour reduction was known in 1988. The adjustment cost of work hours could be high because it involves a reorganization of the work schedule and a full revision of the employment contract. If the cost of the work hour adjustment is sufficiently large, the employer is likely to reduce the actual work hours only once after the first reduction of legal work hours. Suppose that an employer experiences a 2-hour reduction in the legal work hours this year and expects an additional 2-hour reduction in 2 years. If the lump-sum adjustment cost is sufficiently high, the employer reduces the work hours by 4 hours so that the employer pays the adjustment cost only once, and not twice. In this situation, the steady state legal work hour, instead of the current legal work hour, affects the actual work hours once the employer experiences the legal work hour change.

## 4 Identification Strategies

The change in the actual hours of work in response to the change of legal work hours can be examined by estimating the following regression model, which was also employed by Hunt (1999).

$$ h_{i j s t}=\alpha\bar{h}_{j s t}+D_{j}+D_{s}+D_{t}+D_{j}D_{s}+D_{j}D_{t}+D_{s}D_{t}+u_{i j s t}, $$

where $ h_{ijst} $ is actual hours worked. The subscript i is for individual, j for industry, s for establishment size, and t for year. Legal work hours is denoted as $ \bar{h}_{jst} $ defined by industry, establishment size, and year. The dummy variables are included for industry, establishment size, and year to capture industry, establishment size, and year-specific macroeconomic shocks. In the actual implementation, we gradually add the dummy variables to examine which level of aggregate shock is the crucial determinant of work hours that is correlated with legal work hours.
Additional identification information can be obtained from the heterogeneity of the initial work hour distribution across industries and establishment sizes. The theory in the previous section predicts that the reduction of legal work hours reduces actual hours worked through the substitution effect when legal work hours are initially not binding but become binding after the revision. The data set does not allow us to directly test this prediction at the establishment level because it does not have a panel structure. We instead use the industry, establishment size, year-level fraction of workers for whom the work hour regulation was initially not binding but becomes binding after the revision.

The fraction of workers whose work hours are below the current legal work hours but above the revised legal work hours in industry j, establishment size s in year t is denoted as $ f a_{jst} $ . The estimation equation becomes:

$$ h_{ijst}=\alpha_{1}\bar{h}_{jst}+\alpha_{2}\bar{h}_{jst}\times fa_{jst-1}+\alpha_{3}fa_{jst-1}+dummy variables+u_{ijst}. $$

The theory predicts $ \alpha_{2}>0 $ through the substitution effect because the higher the fraction of affected workers, the more effective the work hour regulation is. If the reduction of work hours in response to the legal work hour reduction is mainly caused by the scale effect, $ \alpha_{1}>0 $ , but $ \alpha_{2}=0 $ holds.

We further consider the econometric model that takes a dynamic adjustment into consideration. The econometric model that allows for the lump-sum adjustment cost of work hours becomes:

$$ h_{i j s t}=\alpha\bar{h}_{j s t}^{a d j}+\mathrm{d u m m y~v a r i a b l e s}+u_{i j s t}, $$

where $ \bar{h}_{jst}^{adj} = 48 $ if the legal work hour is not yet revised and $ \bar{h}_{jst}^{adj} = 40 $ once the legal work hour is revised. $ ^{6} $ This specification embodies the theoretical prediction that the adjustment of work hours takes place at one time without a gradual adjustment.
## 5 Data

The data set used in this study is micro data from the Basic Survey on Wage Structure (BSWS), compiled annually by the Japanese government between 1989 and 1999. $ ^{7} $ This survey is conducted in June of every year and includes observations randomly chosen from almost all regions and industries in Japan except for agriculture. The annual number of observations is approximately 1.5 million workers from 60-70 thousand establishments. The sample includes all establishments with 10 or more employees in both private and public sectors and all establishments that belong to private firms with 5 to 9 employees.

The establishments in the sample are randomly chosen in proportion to the size of prefectures, industries, and number of employees from the Establishment and Enterprise Census (EEC hereafter), which lists all establishments in Japan. $ ^{8} $ The randomly selected establishments were asked to extract their workers’ information from their payroll records. $ ^{9} $ The establishment and individual files were merged using an establishment identification number.

The unit of analysis is an individual worker with relevant information from the establishment to which he/she belongs. Among the variables related to work hours, scheduled work hours and overtime work hours in June are available. Other variables include each worker's scheduled monthly payment in June, overtime payment in June, bonus payment of the previous calendar year, age, sex, educational attainment, full-time/part-time status, type of work or job, employment status (with or without permanent status), working days/hours, as well as the firm's attributes, including the number of permanent workers (Joyo Rodo Sha) $ ^{10} $ , firm
size, industry, and location.

Table 1 reports the descriptive statistics of the analysis data. The weighted average of legal work hours declined to 40 in 1999 from 47.21 in 1989. Weekly actual hours worked also decreased from 44.67 in 1989 to 40.33 in 1999. While hours worked declined during the period, monthly scheduled cash earnings and annual bonuses increased during the corresponding period. Accordingly, the imputed hourly wage rate increased from 1,645 yen to 2,345 yen between 1989 and 1999.

Figure 4 compares the distribution of actual hours worked (=scheduled work hours + overtime work hours) in 1989 and 1999. The distribution apparently shifts to the left and becomes less dispersed.

Figure 5 examines compliance to the overtime pay premium regulation. Labor standard law requires employers to pay a wage premium of between 25 and 50 percent to compensate for overtime. To examine compliance to this regulation, the overtime wage premium is calculated by the hourly wage for overtime (= unscheduled wage in June / unscheduled work hour in June) divided by the hourly wage for scheduled work hours (= (scheduled wage in June - legal allowances) / scheduled work hours in June). In this calculation, those workers in managerial-supervising positions who are exempted from the work hour regulation are not included in the sample because overtime work hours and wage payment are not recorded. The mode of the distribution is 1.25, but many workers do not receive the expected overtime premium. This is partly because the work hours exceeding scheduled work hours are not necessarily work hours exceeding the legal work hours, but a non-negligible portion may result from noncompliance to the law. The noncompliance to the law attenuates the effect of the legal work hour on actual work hours. By contrast, in a significant number of cases the overtime wage premium exceeds 25 percent. There are several reasons for this. First, employers must pay at least a 35-percent holiday wage premium for having workers work on
holidays. Second, at least a 25-percent wage premium should be paid for the work schedule that takes place between 10 p.m. and 5 a.m. as a midnight premium. A midnight premium should be added on to the usual overtime or holiday premium if the overtime or holiday work takes place during the aforementioned period, and thus the total of the legal premium goes up to 60 percent.

## 6 Results

Table 2 reports the results of the regressions of actual hours worked on legal work hours with several specifications. The estimated coefficient of 0.481 reported in Column 1 implies that a one-hour reduction of legal work hour reduces the actual work hour by about 30 minutes. This relationship is robust even after controlling for industry and establishment heterogeneity, as reported in Columns 2, 3, and 4.

However, once the year effects are allowed for, the coefficient dramatically drops to 0.140, as reported in Column 5. This implies that a one-hour reduction in the legal work hours reduces the actual hours worked by a mere 8.4 minutes ( $ =60 \times 0.140 $ ). This coefficient is rather stable after including year and industry interaction terms and industry and size interaction terms, as reported in Columns 6 and 7. The coefficient further drops to 0.093 after including size and year interaction dummy variables, but there is not much variation in legal work hour for this specification. If we take 0.140 as the causal effect, among 4 actual work hour reductions between 1989 and 1999, about a 1-hour reduction (480 minutes $ \times $ 0.140) was attained by the reduction of legal work hours.

The effect of the legal work hour reduction on actual hours worked should depend on the fraction of workers who are directly affected by the change of legal work hours, if the substitution effect is important. Table 3 reports the regression results that include the interaction terms of legal work hours and the lagged fraction of workers who are affected by the reduction of work hours. The results are mixed, but the results in Columns 5, 6, and 8 confirm the theoretical prediction that the effect is stronger in the industries and
establishment sizes where the fraction of workers who are affected by the change in legal work hour is high. However, the results are of weak statistical significance and rather suggestive for the importance of the substitution effect. By contrast, the straight effect of legal work hours on actual hours worked continues to be significant in a robust way, and this is suggestive for the relative importance of the scale effect.

Table 4 reports the regression results that allow for a specific form of adjustment for hours worked with dynamic consideration. The explanatory variable is “eventual legal work hours” that takes 48 hours before the legal work hour revision and 40 hours after the revision. If establishments adjust their work hours toward 40 hours once the reduction of legal work hour applies, this explanatory variable should pick up its effect. The estimated coefficients are similar to the ones reported in Table 2, but once the year dummy variables are included, the coefficient virtually becomes zero, as reported in Columns 5 through 8. The dynamic adjustment consideration does not seem to be an important explanation for why the estimated coefficients reported in Table 2 are small.

## 7 Effects on Wage and Employment

### 7.1 Effects on Monthly Wage

The theoretical analysis in the previous section assumed that the firms are wage takers operating in a perfectly competitive market. In the presence of friction in the labor market, however, firms and workers could potentially negotiate a package of total compensation and work hours.

Within this negotiation framework, Trejo (1991) points out that efficient negotiations between firms and workers nullify the work hour regulation because firms and workers continue to contract on the identical package of total compensation and work hours. He finds evidence for this in the US. In contrast, Hunt (1999) finds that monthly pay had not changed when actual hours declined in the mid 1980s in Germany and, as a result, the effective hourly wage
increased. Nymoen (1989) also found that, in the short run, the reduction of work hours increased hourly wage based on Norwegian time-series data. Pencavel and Holmlund (1988) finds a similar result based on Swedish data.

To examine the effect of the tighter work hour regulation on monthly total compensation, which is defined as scheduled wage and overtime wage in June plus bonus payments in the previous year/12, is regressed upon the legal work hours. The results of regressions for several specifications are reported in Table 5. The specifications without year effects render negative coefficients, but the specifications with year effects, reported in Columns 5 through 8, indicate that the tighter work hour regulation had decreased monthly total compensation, but the estimates are not statistically significant except for the specification reported in Column 7. The size of the coefficient, which is 0.004, is very small because when the legal work hour is reduced by one hour, which is a 2.5-percent reduction from 40 hours, monthly pay is reduced by 0.4 percent. The elasticity is about 0.16. Combined with the previous findings that the tighter work hour regulation reduced the actual hours worked, the reduction of the legal work hours resulted in an increase of the hourly wage rate.

To further investigate the reasons why monthly total compensation hardly changed in response to the reduction of the legal work hours, the monthly compensation is divided into regular monthly salary and bonus parts, using the following relationship:

$$ \ln(Scheduled\ Wage+Overtime\ Wage+Annual\ Bonus/12) $$

= $ \ln\{(\text{Scheduled Wage} + \text{Overtime Wage}) $

$$ \times(1+\frac{Annual Bonus/12}{Scheduled Wage+Overtime Wage})\} $$

$$ \simeq\ \ln(Scheduled\ Wage+Overtime\ Wage) $$

$$ Annual Bonus/12 $$

$$ ^{+}\overline{\mathrm{S c h e d u l e d~W a g e+O v e r t i m e~W a g e}}. $$

The approximation $ \ln(1+\rho)\simeq\rho $ is used to derive the third line.

The log of monthly cash earnings and the fraction of bonus to monthly wage are separately
regressed on the legal work hour to decompose the legal work hour’s effect on monthly total compensation.

Table 6 reports the results for the regressions of monthly wage, including overtime pay, on legal work hours. The specifications with year dummy variables report that the tighter legal hour restriction was associated with the reduction of monthly wage, but these estimates are not statistically significant, except for a specification in Column 7. Table 7 reports the results for the regressions of the fraction of bonus to monthly wage on legal work hours. All the estimated coefficients are almost zero.

Overall, neither monthly wage nor the bonus fraction responds to the change of the work hour resection in a significant way. Combined with evidence that the reduction in the legal work hour reduced the actual hours worked, the reduced legal work hour increases the hourly wage rate, or hourly labor cost.

### 7.2 Effects on Hiring New School Graduates

Increased hourly wage induced by the reduction in legal work hours may have reduced the number of employees. The Basic Survey of Wage Structure is not designed to provide panel data and basically cannot capture change in the number of employees over time. However, it includes information on the number of workers who are newly recruited from schools by types of schools (junior high school, senior high school, junior college (Tandai)/technical college (Kousen), four year college) at each establishment. These numbers are added up to obtain the total number of newly recruited workers from schools, and this total is divided by the total number of permanent employees to obtain the fraction of newly hired workers among permanent workers as an establishment-level variable. The fraction of workers who are newly hired from schools among permanent workers may vividly capture the labor input adjustment because this is the margin where the adjustment cost is presumably minimal.

Table 8 reports the regression results of the fraction of newly hired workers among permanent workers on legal work hours. All the estimated coefficients indicate that the reduction
of legal work hours reduces the fraction of newly hired workers. According to the specification that allows for straight industry, establishment size, and year effects indicates that a one-hour reduction in the legal work hour reduces the fraction of new hiring by 0.13 percentage point. The eight-hour reduction of legal work hours between 1988 and 1999 results in more than a one-percentage point reduction in the hiring of new graduates from schools. The accumulated effect is non-negligible, considering the fact that the fraction of newly hired workers among permanent workers is about 5 percent during the analysis period.

The Basic Survey of Wage Structure also records the total wage bill that went to newly hired workers from schools. Dividing this figure by the number of workers recruited from schools, the average monthly wage for newly hired workers is calculated. Average monthly wages of newly hired workers from schools by education groups are regressed on the legal work hour. Table 9 reports the results of the regression, and the estimated coefficients for the specifications with industry, establishment size, and year dummy variables imply that the reduced legal work hours had no impact on the monthly salary of newly recruited workers from schools. This nominal rigidity may well have amplified the quantity adjustment.

## 8 Conclusion

This paper examined the effect of the weekly legal work hour reduction on actual work hours through both theoretical and empirical analyses. The theoretical analysis with exogenous wage revealed that whether the reduction of the legal work hour reduces the actual work hours critically depends on production technology, including the fixed cost of employment and the elasticity of substitution between the hours of work and the number of workers.

The empirical examination exploited an unusual natural experiment in Japan; the number of legal work hours was reduced from 48 in 1988 to 40 in 1997. The analysis, based on micro data from the Basic Survey of Wage Structure, revealed that the reduction of legal work hours modestly reduced actual hours worked. The most preferred estimate implies that a one-hour reduction in the legal work hours reduced actual work hours by 0.14 hour, or 8.4.