تنظیم، بهره وری و نوسانات خروجی کار : ارزیابی یارانه تنظیم استخدام ژاپن

This paper provides a quantitative examination of the impact of Japan’s Employment Adjustment Subsidy, a major employment insurance policy since 1975, on labor adjustment, productivity and output fluctuation in the iron and steel sector. A partial equilibrium industry model with heterogeneous establishments and aggregate uncertainty shows that the EAS reduces steady-state labor productivity by encouraging labor hoarding, and in some cases, preventing the exit of least efficient establishments. The EAS also reduces job flows and increases average establishment-level employment. Although the impact on productivity is roughly proportional to the size of subsidized workers in most cases, the effects of the subsidy on output and employment volatility are more than proportional. First, the subsidy can lead to a sizable increase in output fluctuations over business cycles by symmetrically increasing the output response to shocks. This result is achieved through lower output via a subsidy during unfavorable times and higher output via less time and money spent on hiring during favorable times. Second, the subsidy meets its primary objective of reduced employment volatility. The reduction can be considerable when firing costs are high.

This paper examines the Employment Adjustment Subsidy (EAS), a core Japanese employment insurance policy since 1975. The EAS program allows establishments to reduce output during unfavorable business conditions without laying off workers by providing part of the costs of sustaining excess workers.1 The EAS policy has not yet been formally analyzed despite recent macroeconomic literature emphasizing job reallocation as a driving force behind business cycles. Therefore, the primary objective of this paper is to point out some of the key implications of the policy through the application of a theoretical framework of heterogeneous establishments with aggregate uncertainty. In particular, this paper investigates the impact of the EAS on average labor productivity, job flows and entry/exit rates at the steady-state. In addition, it examines the implications of the policy for the volatility of employment, output and productivity over business cycles. Between 1990 and 2002, more than 360 billion yen (over 3.6 billion US dollars) was spent on the EAS. On average between January 1991 and October 2001, about 170,000 establishments were eligible for the subsidy program.2 According to the 1996 Establishment Census, there were about 6.5 million establishments in Japan (excluding public service) with 770,000 in manufacturing. Thus, the average number of targeted establishments corresponds to 2.6% of the total number of establishments, or approximately 20% of manufacturing establishments. The number of targeted establishments peaked at 411,000 units in February 2000. The EAS recipients are heavily concentrated in the manufacturing sector, with the largest beneficiary being the iron and steel industry. The manufacturing sector and the iron and steel industry, respectively, received approximately 94% and 40% of the total subsidy bill between 1990 and 2002.3 Although the program in principle involves the entire economy, this paper focuses on the iron and steel industry due to the program’s high concentration in this industry. The calibrated industry model developed later will attempt to match key moments obtained from the data for this industry. Using longitudinal data sets in the US manufacturing sector, Davis and Haltiwanger, 1990, Davis and Haltiwanger, 1992, Davis and Haltiwanger, 1999 and Davis et al., 1996 exposed the importance of idiosyncratic differences across establishments in explaining business cycle dynamics. Many theoretical frameworks analyzing industry dynamics, such as Jovanovic, 1982, Hopenhayn, 1992, Hopenhayn and Rogerson, 1993, Ericson and Pakes, 1995 and Campbell and Fisher, 2004, also stressed the importance of heterogeneity across firms when characterizing firm’s production and entry/exit decisions. To the extent that the EAS interacts with such heterogeneity across establishments within an industry, the appropriate theoretical framework to analyze the effect of the policy must also encompass similar features. In addition, prior research concerning the implications of differing labor market institutions, particularly European employment policies, has shown that labor market policies have an important effect on equilibrium job flows, unemployment and productivity. Hopenhayn and Rogerson (1993), for instance, illustrate that high firing costs in Europe, which interfere with the process of job reallocation, lead to a sizable reduction in employment and a drop in average productivity. Others have stressed the interactions between a changing economic environment and labor market policy. Ljungqvist and Sargent (1998) explain that generous unemployment benefits increase unemployment rates when the skill mix demanded in the labor market is rapidly changing. Other studies have linked multiple labor market policies. Bertola and Rogerson (1997), for example, demonstrate that wage compression in Europe tends to generate more volatile employment flows, fostering a policy that restricts the firing of workers. They argue that these institutional differences can account for the similarities in job flows and differences in unemployment between Europe and the US. Some labor market institutions, namely labor adjustment costs and wage rigidities, are likely preconditions for the EAS, since the subsidy will not be used if labor adjustment is costless or if wages can perfectly absorb shocks. Although there are few quantitative studies that estimate the cost of firing workers in Japan, there is some legal evidence that suggests that firing workers in Japan is generally very difficult, more similar to the European than the US case.4 Moreover, the post-war tradition of life-time employment has encouraged firms to invest in building firm specific human capital.5 This evidence indicates that adjusting employment has been in general quite costly in Japan.6 Correspondingly, the EAS was designed in order to “assist establishments in their efforts to maintain employment in times of temporary unfavorable business conditions owing to economic recession or changes in the industrial structure of the Japanese economy, as well as to promote employment stability and prevent unemployment.”7 While there has not been a formal empirical study on the effect of the subsidy program primarily due to the unavailability of data, some existing studies suggest that the EAS distorts employment behavior. For instance, Hashimoto (1993) uses monthly aggregate manufacturing data and finds that, since the subsidy allows for adjustment through temporary business closures, employment became less sensitive, while work hours became more sensitive, to demand shocks after the subsidy program was enacted in 1975.8 While factors other than the EAS may be part of his results, the estimated elasticity of employment with respect to unanticipated demand shocks drops dramatically from .30 before to −.27 after the initiation of the EAS policy. He also points out that the treatment of temporarily laid off workers in Japanese statistics as ‘employed’ explains part of the difference in unemployment rates between Japan and the US. Another related yet unexplored empirical issue is that the presence of subsidized workers reduces measured productivity, since hoarded workers are not properly taken into account in employment statistics. This paper attempts to estimate the number of unutilized workers through the subsidy program in the iron and steel industry, as well as the reduction in productivity that can be accounted for by the inclusion of subsidized workers in employment statistics. These estimates will, in turn, be used for the calibration of the model. The model developed here offers insights beyond the direct effect of labor hoarding on productivity. The effects of the EAS on the cyclical dynamics of output and employment generate a wide set of empirical predictions, testable in future research as more data becomes available. The model exploits the theoretical framework of Hopenhayn, 1992 and Hopenhayn and Rogerson, 1993. The main advantage of using their framework is that, as previously mentioned, their model allows for a heterogeneity across establishments and thus allows us to evaluate the impact of the subsidy program on industry dynamics by explicitly modeling the equilibrium response of heterogeneous establishments. Unlike Hopenhayn and Rogerson, however, the consideration of labor supply decisions and hence the households’ problem will be omitted.9 Thus, the analysis will be a partial equilibrium estimate of the change in overall industry dynamics caused by the subsidy program. In addition, two-state aggregate uncertainty is introduced to the model, a feature that was not present in Hopenhayn and Rogerson (1993).10 In interpreting the impact of the subsidy on average labor productivity, a word of caution is in order: while establishments are heterogeneous in the model, workers are homogeneous in the sense that productivity does not increase with tenure. Although the subsidy could possibly increase average productivity if the heterogeneity of workers were added to the model, it was not done for simpler expositions of the key mechanism of the EAS. In my model, the difference between old and new workers is solely reflected in the hiring cost, which reduces output during the first period; the productivity of new and old workers is equalized afterwards. I show that the subsidy program reduces steady-state average productivity primarily by increasing the number of unutilized workers (labor hoarding effect). In some cases, the effect goes beyond a pure labor hoarding effect. For example, when firing costs are high, the subsidy program can also reduce the average labor productivity by preventing the least efficient businesses from exiting the market. The estimated impact of the subsidy on productivity through labor hoarding is small, as the estimated average fraction of subsidized workers in the iron and steel sector between 1990 and 2002 is only about 2.1%. The calibrated model shows that the EAS modestly increases the steady-state average establishment-level employment, while keeping the average establishment-level output roughly the same. The EAS also slightly reduces the steady-state exit/entry rate and the steady-state job turnover (destruction) rate. Nevertheless, the second moment features generated by my simulation exercises reveal that the subsidy program has a disproportionate impact on output and employment dynamics over the business cycle. In particular, output volatility can increase by roughly 2.7% even when the steady-state fraction of subsidized workers is around 1.4%. The intuitive reason for this result is that the subsidy increases the sensitivity of output to aggregate shocks symmetrically: following unfavorable shocks, the subsidy allows establishments to reduce production without laying off workers, while following favorable shocks, establishments are able to increase output without hiring new workers. On the other hand, the subsidy significantly reduces employment volatility. In some cases, the drop in employment volatility can be substantial, even when the fraction of subsidized workers is small: the volatility of employment falls by more than 25% when firing costs are high, even with only 2% of the workers being subsidized. The reduction in employment volatility is achieved by the reduced sensitivity of job creation and destruction to aggregate shocks over the business cycle. This paper proceeds as follows: Section 2 provides a brief background of the EAS as well as an overview of the employment and output trends obtained from the aggregate iron and steel industry data. I then calculate the direct impact of the EAS on TFP induced by labor hoarding, which later will be used for the calibration of the model. Section 3 lays out the theoretical framework of the industry model. Section 4 shows results from solving a stochastic version of the model through numerical dynamic programming. I present key statistical features obtained from the stationary distribution of the model as well as simulation exercises, and compare the subsidy case with the benchmark case that sets the subsidy to zero. Section 5 concludes.

This paper has examined the effects of the EAS, Japan’s major employment insurance program, on average productivity, employment, and the volatility of output and employment over the business cycle, through the examination of the iron and steel industry. The partial equilibrium model described in this paper shows that the subsidy reduces average productivity primarily by increasing the number of unutilized workers. The subsidy could further reduce average productivity by interfering with the process of job reallocation and preventing the exit of the least efficient establishments. Furthermore, simulation exercises reveal that the subsidy may have a much larger impact on the volatility of output and employment. In particular, when firing costs are high, the subsidy increases output volatility by 3% and reduces employment volatility by a quarter over the business cycles, even when the fraction of subsidized workers is about 2%. While measures such as productivity and employment/output volatility are often used to evaluate welfare, I do not intend to draw a normative conclusion on the welfare effect of the subsidy program. Nevertheless, I believe that the implications highlighted in this exercise are important ones, providing policymakers a better understanding of the program and allowing them to more successfully target their policy objectives. Here, I raise a couple of issues for a more complete welfare assessment. First, the paper predicts that the subsidy increases output volatility while reducing employment volatility. Consequently, an assessment of the policy requires an analysis of the cost of output volatility and the benefits of employment stability.49 Second, while some labor market imperfections are assumed for subsidy take-up to take place (i.e., firing restrictions and rigid wage), this paper does not address how the subsidy program may enhance or reduce labor market imperfections.50 The analysis presented here raises several additional issues for further investigation. First, since the quantitative impact of the subsidy on the volatility of output and employment is sensitive to the magnitude of labor adjustment costs, it will be important to quantify these costs accurately to evaluate the potential impact of the subsidy program. Second, the analysis treated the iron and steel industry as an independent economy with no interaction with other industries. New policy implications may arise if inter-industry interactions between high productivity sectors and low productivity sectors are present in the model.51 Third, it seems worthwhile to investigate why the subsidy was so heavily concentrated in the iron and steel sector. Finally, employment volatility during the severe recession of the 1990s was surprisingly mild in Japan compared to other industrial nations, despite the fact that EAS coverage was highly concentrated in certain sectors of the economy.52 It would be worthwhile to investigate other factors that contributed to the stability of employment.