Rising Wage Inequality Within Firms: Evidence from Japanese health insurance society data

Transcription

1 RIETI Discussion Paper Series 12-E-039 Risin Wae Inequality Within Firms: Evidence from Japanese health insurance society data SAITO Yukiko RIETI KOUNO Toshiaki Fujitsu Research Institute The Research Institute of Economy, Trade and Industry

2 RIETI Discussion Paper Series 12-E-039 June 2012 Risin Wae Inequality Within Firms: Evidence from Japanese health insurance society data SAITO Yukiko Umeno RIETI KOUNO Toshiaki Fujitsu Research Institute Abstract Usin a novel dataset compiled from Japanese health insurance societies coverin about 1,500 firms and 15 million employees in total, we examine wae inequality within and between firms. Employin the mean lo deviation approach to decompose wae inequality into within-firm and between-firm inequality, we find that it increased amon male employees durin the period we examined (FY ). Moreover, even after controllin for chanes in the compositional structure of firms employees, an increase in wae inequality within firms can be observed, reatly contributin to the increase in overall wae inequality, which likely reflects the rowin prevalence of performance-based wae systems. 1 Keywords: Wae inequality; Within-firm inequality; Performance-based wae JEL classification: J31, D31 RIETI Discussion Papers Series aims at widely disseminatin research results in the form of professional papers, thereby stimulatin lively discussion. The views expressed in the papers are solely those of the author(s), and do not represent those of the Research Institute of Economy, Trade and Industry. 1 The authors would like to thank Mitsuru Iwamura, Fumio Ohtake, Hidehiko Ichimura, Tomohiro Machikita, Daiji Kawauchi, Haruhisa Nishino, Masayuki Morikawa and other participants of the JEA meetin at Kwansei Gakuin University and of seminars at the Institute of Developin Economies, Japan External Trade Oranization, Hitotsubashi University and RIETI, for helpful comments. Saito started writin this paper when she was a researcher at Fujitsu Research Institute, Japan. She thanks various supports from the institute. She ratefully acknowledes financial support from the Japan Society for the Promotion of Science (# ) and a rant from the Japan Center for Economic Research. 1

3 1. Introduction Economic inequality is an issue that is attractin rowin public attention and has become a major focus of political debate worldwide. A considerable number of studies have attempted to measure chanes in economic inequality and examine the mechanisms underlyin such chanes. One of the most important factors in this context are chanes in firms wae systems and numerous researchers have hihlihted the increasin prevalence of performance-based wae systems and the role these play in wae inequality (e.., Lemieux et al. 2009; Tsuru et al. 2005; Uni 2008). A widely used approach to examine the mechanisms underlyin chanes in economic inequality has been to employ decomposition analysis. Specifically, followin the seminal studies by Shorrocks (1982, 1984) and Mookherjee and Shorrocks (1982), chanes in overall inequality are frequently decomposed into chanes in within-roup inequality and between-roup inequality usin the mean lo deviation (MLD) approach. Usin this approach, previous studies examinin economic inequality have frequently decomposed inequality by ae roup. Doin so is particularly useful in understandin how chanes in population structure, especially population ain, can play a role in overall economic inequality: since inequality amon the elderly tends to be reater than amon the youn, an increase in the share of the elderly in the population will increase economic inequality overall. For instance, lookin at wae inequality in Japan, Ohtake and Saito (1998) and Shinozaki (2006) find that the increase in wae inequality observed durin the 1990s is larely due to chanes in the ae structure of the population rather than chanes in inequality within the same ae roups. Studies such as Ohtake and Saito (1998) and Shinozaki (2006) on wae inequality are relatively straihtforward to conduct. Information to roup employees by their characteristics such as ae, ender and academic backround is easily obtainable from surveys on employees, 1 and there are a considerable number of studies oin back several decades that use employee characteristics for the analysis of wae inequality 2. In contrast, examinin wae inequality within firms is considerably more difficult. In Japan, the only relevant firm-level survey is the Basic Survey on Waes Structure (BSWS) by the Ministry of Health, Labour and Welfare (MHLW). However, the sample of employees 1 For instance, in Japan there are the Employment Status Survey and the Special Survey of the Labor Force Survey (both conducted by the Ministry of Internal Affairs and Communications) providin such information. 2 Examples include Blinder (1973), Katz and Revena (1989), Katz and Murphy (1992), Freeman and Katz (1994), Sasaki and Sakura (2005), Goldin and Katz (2007), and Kawauchi et al. (2008). 2

4 for each firm is very small, makin it difficult to reliably measure within-firm wae inequality. Reflectin this scarcity of adequate data not only in Japan but also elsewhere, most research on the implications of performance-based pay systems for overall wae inequality consists of anecdotal studies based on surveys of specific firms rather than empirical studies based on a comprehensive set of firm-level data spannin a lare number of firms. That bein said, there are a number of exceptions: studies that attempt to empirically capture inequality within firms usin indirect means. Tachibanaki (2006), for example, employin the BSWS, makes inferences about inequality within firms by roupin firms in terms of size and industry, while for the United States, Davis and Haltiwaner (1991) measure within-firm inequality implicitly as the residual between between-firm inequality and inequality overall. The only study that we are aware of that measures within-plant wae inequality explicitly is that by Skans et al. (2007), who construct an employer-employee dataset usin a Swedish database. In this study, we use a novel dataset compiled by the MHLW from health insurance societies (kenkou hoken kumiai) in order to explicitly measure inequality within firms. Details of this dataset will be provided in the next section. Usin this hue dataset allows us to capture the wae distribution within each individual firm and we decompose overall wae inequality into within-firm and between-firm inequalities usin the MLD approach. The dataset covers about 1,500 firms with a total of about 15 million employees at any particular time durin our observation period. 3 No other dataset covers such a lare number of employees and this is the first time that this dataset is used for the analysis of inequality. In addition to the lare number of employees covered in the dataset, another unique feature is that it makes it possible to measure the wae distribution for each individual firm includin all employees. Usin this data and the MLD approach, we find the followin. Overall inequality increased durin the observation period due to an increase in inequality within firms amon male employees, which as a result overtook that amon female employees. Moreover, even after controllin for chanes in the compositional structure of firms employees, an increase in wae inequality within firms can be observed, which reatly contributes to the increase in overall wae inequality. These findins are consistent with the increasin prevalence of performance-based pay systems in Japan. The remainder of the paper is oranized as follows. The next section provides a 3 In contrast, the number of observations in the BSWS is approximately 1 million and therefore considerably smaller than the number of insurants in our dataset. 3

5 detailed outline of our dataset, while Section 3 explains our methodoloy. Section 4 then presents our results on chanes in wae inequality within and between firms as well as the results of the decomposition of chanes in inequality. Finally, Section 5 concludes. 2. Data The data we use in this paper to measure wae inequality are compiled from Japan s health insurance societies (kenkou hoken kumiai, referred to as HIS hereafter), which form part of Japan s mandatory health insurance system. In Japan, all citizens have to join a health insurance scheme. All workers 4 are insured in the followin way. All overnment workers are insured throuh the mutual-aid associations (kyousai kumiai), while all non-overnment workers are insured throuh one of the followin three schemes; (a) the scheme manaed by the above mentioned HISs (the Society-manaed Health Insurance or kumiai kenpo), (b) the Association-manaed Health Insurance (kyoukai kenpo) 5 or (c) the National Health Insurance (kokuho). The type of scheme under which non-overnment workers are insured depends on the nature of their workplace. If their workplace is a plant of a corporate (houjin) firms or, under certain circumstances, a non-corporate firm, 6 employees have to be oranized throuh (a) the Society-manaed Health Insurance or (b) the Association-manaed Health Insurance. If their firms have established an HIS, the employees are insured throuh (a) the Society-manaed Health Insurance. Otherwise the employees are insured throuh (b) the Association-manaed Health Insurance. Employees fallin under one of these schemes are insured throuh (c) the National Health Insurance. In addition, employers of non-corporate firm are basically insured throuh (c) the National Health 4 Part-time workers workin more than three quarters of the time of full-time workers can be insured in the same way as full-time workers. Workers earnin an annual income of less than 1.3 million yen can be rearded as non-workin dependents and are basically insured throuh the same insurance scheme as their supportin family member. If such employees do not have a supportin family member, they are insured throuh the National Health Insurance. 5 The Government-manaed Health Insurance and the Seamen s insurance were mered into the Association-manaed Health Insurance in October, Even if the firm a plant belons to is not a corporate firm, any plant with five or more employees that does not belon to the food industry, the service industry, or the ariculture, forestry and fisheries industry has to oranize either of the two schemes. On the other hand, other plants not oblied to oranize one of the two schemes nevertheless can do so voluntarily at the manaement s discretion. 4

6 Insurance. Firms can establish an HIS if the number of insurants is no less than 700 or in collaboration with other firms if the total number of insurants is no less than 3,000. In both cases, the HIS must be authorized by the MHLW. Due to these requirements, most of those insured thouh an HIS are employees workin for lare firms or their roup firms. Based on the Health Insurance Law, all HISs have to submit monthly and yearly reports 7 to the MHLW. The monthly reports include the number of insurants for each wae rade, 8 where each wae rade corresponds to a certain wae bracket (Table 1). This means that, usin these HIS reports, which are accessible throuh a disclosure request to the MHLW, we can measure wae inequality within each HIS. Table1 In this paper, we assume that each HIS corresponds to a particular firm and use this data to measure wae inequality within each firm. Strictly speakin the boundaries of HISs and firms do not always exactly overlap since the way an HIS is oranized depends on the firm s manaement; however, plants of the same firm are usually oranized all into the same HIS. Moreover, even when this is the case, HISs are not necessary formed by a sinle firm. HISs can be formed jointly by firms belonin to the same business roup or by several smaller firms typically from the same industry and/or reion. They therefore are likely to have similar characteristics, so that we reard the HIS they form as akin to a virtual firm. Our dataset consists of approximately 1,500 HISs for each period. The data are available from April 2003 to March 2008 (FY2003 to FY2007), because the MHLW did not prepare data in an electronic format before April We exclude from our dataset HISs that were newly established or dissolved durin the observation period; that is, we focus only on HISs that existed throuh the entire period. Doin so, the number of sample HISs is 1,496 with about 15 million employees 9 in the HISs at any particular time. Accordin to the Employment Status Survey, the number of occupied persons was about 7 These reports are submitted in order for the MHLW to monitor HISs medical expenses and insurance premiums. In addition to the data on waes, the reports also include information related to medical expenses. 8 These rades refer to the standard monthly wae class and are based on the previous month s wae excludin bonus payments but includin overtime payments. The insurance premium each insurant pays is calculated based on this wae rade. 9 The number of male insurants is about 10 million and that of female insurants is about 5 million. 5

7 55 million. This means that our dataset covers about 27 percent of all employees. 10. We start our analysis by lookin at the wae distribution overall (Fiure 1). Specifically, the fiure shows the wae distribution of pooled observations in our dataset for the entire observation period. We find that for male employees, the distribution peaks at wae rade 23, which corresponds to a monthly wae of 410,000 yen. On the other hand, for female employees, the distribution peaks at wae rade 14, which corresponds to a monthly wae of 220,000 yen. Fiure 1 3. The MLD approach This section explains the mean lo deviation (MLD) approach, which we use to examine wae inequality. The MLD is defined as follows: MLD lo( x) lo( x), (1) where x n j x j n 1 n /, lo( x) lo( x ) / and x 1 j is the wae of person j. j j n The MLD approach is useful for decomposin inequality. It can be linearly decomposed into within-roup inequality and between-roup inequality as follow: MLD MLD in MLD bet, (2) where n MLDin, 1 MLD (3) n MLDbet lo( x) 1 lo( x ), (4) is the share of roup in the total population, MLD is the internal inequality of roup measured by the MLD approach, and x is a mean wae of roup. Within-roup inequality MLD in is defined as the mean of the each roup s internal inequality MLD weihted by the population share of roup. On the other hand, 10 While the number of employees insured throuh the mutual-aid associations is 4 million and that throuh the Association-manaed Health Insurance is 20 million, it is difficult to establish the number of employees insured throuh the National Health Insurance since it also contains non-workers. 6

8 between-roup inequality MLD bet is defined as the weihted difference between the mean wae overall and the mean wae within individual firms. Next, we turn to chanes in inequality over time, say, from time t to t t. The chane in overall inequality MLD is aain decomposed into the chane in within-roup inequality MLDin and the chane in between-roup inequality MLDbet as follows: MLD MLD in MLD bet (5) Note that it is necessary to take into account chanes in the compositional structure of the population when examinin chanes in within-roup inequality. Even thouh inequality within individual roups may remain unchaned, overall within-roup inequality may chane as a result of chanes in the weiht of certain roups. That is, an increase in the weiht of roups with hih internal inequality will lead to a rise in within-roup inequality overall. Then, chanes in within-roup inequality MLDin are linearly decomposed into the pure effect of chane in each roup s internal inequality MLD 1 and the effect n of chanes in compositional structure MLD 1 where, t t, t, n (, t, t t ) / 2, MLD MLD, t t MLD, t and MLD MLD MLD ) / 2. (, t, t t 4. Results 4.1 Chanes in the wae distribution and inequality overall We start our examination by lookin at chanes in the wae distribution and inequality overall. Because the wae distributions based on the monthly HIS reports display seasonality, we construct yearly data by calculatin the 12-month averae for each observation point. For example, the annual data for 2003 are calculated usin data from April 2003 to March Fiures 2 and 3 show the wae distribution for 2003 as well as the difference between 2003 and 2007 for male and for female employees, respectively. As already seen in Fiure 1, the peak for male employees is in wae rade 23, while that for female employees is in rade 14. Next, takin a closer look at Fiure 2 and the chane in the wae distribution 7

9 depicted by the broken line, we find increases in the number of employees on either side of the 2003 peak, suestin an increase in wae inequality amon male employees. On the other hand, in Fiure 3 for female employees, the shape of the difference distribution is quite similar to the 2003 distribution, with a small shift to the riht. Thus, the fiure does not provide any evidence of an in inequality, but instead hints at an increase in waes for female employees. Next, we examine the chanes in wae inequality usin inequality indices. Fiure 4 depicts the trend in wae inequality from 2003 to 2007 usin MLD. As can be seen, inequality amon male employees appears to have rown rapidly, while inequality amon female employees shows only a minimal increase. As a result, while inequality amon male employees was smaller than amon female employees in 2003, the reverse was the case in The same pattern is observed when usin the Gini index: while the index increased from to for male employees, it only rose from to for female employees. Fiures 2 to Inequality within firms Next, we calculate the inequality index for each individual firm and examine the distribution of the inequality index. In addition, we calculate within-firm inequality overall and examine its trend over time. Fiures 5 and 6 show the distribution of the MLD for individual firms for male and female employees, respectively. Comparin the distributions for 2003 and 2007, we find that for both male and female employees it shifts to the riht. In other words, we find that inequality within individual firms tended to increase durin this period. Similar patterns can be observed when usin Gini indices instead. Fiure 7 shows the chane in within-firm inequality usin the MLD method. Within-firm inequality is defined as the weihted mean of the inequality measured in individual firms, where firms share in the overall population of employees is used as weihts, as shown in Equation (3). We find that within-firm inequality for male employees is hiher than that for female employees. Furthermore, within-firm inequality for male employees increased rapidly durin this period. This chane in within-firm inequality overall is due to the chane in inequalities within individual firms seen in Fiures 5 and 6 and, as will be seen in the next sections, chane in the weiht of individual firms. 8

10 Fiures 5 to Decomposition of overall inequality The next step is to decompose chanes in equality overall into the contribution of chanes in within-firm inequality and chanes in between-firm inequality. Between-firm inequality is defined as the weihted difference between the mean wae overall and the mean waes within individual firms, as shown in Equation (4). The indices of between-firm inequality for male and female employees are shown in Fiure 8. We find that between-firm inequality is hiher for female employees than that for male employees. Moreover, a sliht increase in between-firm inequality can be observed for male employees, while for female employees it remained essentially unchaned. Aain, similar patterns can be found usin Gini indices instead. Fiure 8 The contribution of chanes in within-firm and between-firm inequality to chanes in inequality overall is shown in Fiure 9. We find that the contribution of chanes in within-firm inequality is substantial, especially for male employees. On the other hand, the contribution of chanes in between-firm inequality is also positive for male employees, but considerably smaller, while it is even slihtly neative for female employees. Thus, for male employees, the increase in within-firm inequality accounted for 82 percent of the increase in wae inequality overall. Given that the increase in within-firm inequality is responsible for the lion s share of the increase in inequality overall, we further decompose it into chanes in inequality within individual firms and chanes in the composition of firms. The results are presented in Fiure 10 and show that increases in inequality within individual firms make a lare positive contribution to within-firm inequality overall. On the other hand, while the contribution of chanes in the composition of firms is positive for male employees, thereby further exacerbatin overall within-firm inequality, it is neative for female employees, thus offsettin to a reat extent the role of increases in inequality within individual firms. The results imply that the share of men workin for firms with relatively lare internal inequality has increased, while the share of women workin for firms where internal inequality is relatively small has rown. Finally, we also decompose chanes in between-firm inequality into the contribution of chanes in differentials between firms mean waes and chanes in firms weihts. The 9

11 results are shown in Fiure 11 and indicate that, both for male and for female employees, differentials in firms mean waes made a neative contribution and compositional chanes a positive contribution. In other words, the means of firms waes were converin durin the observation period, but at the same time an increasin number of employees were workin for firms payin waes that were considerably hiher or lower than the mean. Fiures 9 to 11 The main reason for these diverin trends in the role of the composition of firms most likely is the lare increase in the number of insurants, especially female insurants, reistered with the HIS of temp aencies (jinzai haken kenko hoken kumiai), for both chanes in within-firm and between-firm inequalities. Internal inequality in the HIS of temp aencies is relatively small for female employees, but relatively lare for male employees, while mean waes are considerably lower than the overall means for both male and female employees. 4.4 Chanes in the ae structure of firms employee The discussion so far has inored the effects of chanes in the ae structure of the population. As hihlihted in previous studies that decompose overall inequality by ae roup, the rowin share of elderly employees is one potential reason for the increase in within-firm inequality. That is, because inequality amon older employees tends to be larer than amon youner employees within individual firms, an increase in share of older employees will lead to a rise in equality, even if within-ae roup inequality in individual firms remains unchaned. In contrast with the employment surveys typically used in precedin studies, our data are available on a firm-level basis only, and we therefore do not have information about the characteristics of individual employees such as their ae. However we do have some information on the employees ae, namely the mean ae of employees at an individual firm, which is included in the yearly HIS reports and which allows us to examine the ain of employees. Lookin at this information indicates that, in 68% of firms mean ae of male employees and in 85% of the mean ae of female employees increased durin the observation period. We therefore examine whether the increase in within-firm inequality is related to the ain of employees. We do so by calculatin the correlation between chanes in within-firm inequality and employees mean ae. By doin so, slihtly neative correlation (-0.07) is observed for male employee and the positive correlation 10

12 (0.11) is observed for female employees. Focusin on male employees, this result suests there are factors other than chanes in the ae structure of employee that is responsible for increase in within-firm inequality. 4.5 Bonus payments It is often said that the bonus system plays an important role in the introduction of performance-based pay (e.., Lemieux et al. 2009; Tsuru et al. 2005). In fact, the wae rades that we use in the analysis here to examine wae inequality do not include bonuses. If performance-based pay is likely introduced throuh the bonus system, the wae inequality that we measure here may be biased downward. Therefore, the actual increase in firm-internal wae inequality miht be even more pronounced than the result here suested if bonus payments were included. What is more, since the focus here is on monthly waes rather than bonus payments, the analysis suests that the increase in firm-internal wae inequality is not a temporary phenomenon (e.., due to inflated bonus payments) but reflects a loner-term trend. 4.6 Business cycle It has lon been said that wae inequality is stronly related with business cycle. Conventionally, wae inequality is thouht to rise durin recession and this countercyclical earnin volatility recently plays an important role in solvin some macroeconomic puzzles. Althouh the countercyclical earnin volatility is the important basis of economic theory, the question how wae inequality related with business cycle is controversial (e.. Goldin and Maro 1992; Barlevy and Tsiddon 2006). The observation period of our analysis is in economic recovery period. In order to identify the effect of business cycle on within-firm wae inequality, we divide the firms into two roups, i.e. one is constituted from firms in ood performance and the other is from those in bad performance. Each firm s performance is measured usin ratio of sum of bonus payments compared with sum of monthly base wae payments. If the ratio rows, we reard that the firm is in ood performance. If the ratio shrinks, we reard that the firm is in bad performance. We find that firm s internal wae inequality tends to row for both two firm roups. 5. Conclusion This paper examined chanes in within-firm and between-firm inequality in waes usin 11

13 data from health insurance societies for the period from FY2003 to FY2007. Wae inequality was measured usin the mean lo deviation (MLD) approach, where inequality overall is decomposed into within-firm and between-firm inequality. The main findin of this paper is that within-firm inequality increased reatly durin the period studied and contributed substantially to the chane in inequality overall, even after controllin for chanes in the weihtin of firms. Specifically, it was found that inequality overall rew rapidly amon male employees and overtook that amon female employees, which remained more or less unchaned. In contrary with earlier studies showin that overall inequality increased due to the rowin share of elderly employee, we found that firms in which internal inequality increased did not necessarily have an ain workforce. That is, even after takin employees ain into account, we still find an increase in firm-internal inequality, suestin that the reater prevalence of performance-based pay schemes rather than any composition effects are responsible for the observed increase in wae inequality. Other notable findins are as follows. Comparin male and female employees, we find that within-firm inequality is hiher for male than that for female employees, while the reverse is the case for between-firm inequality. A likely explanation for these results is that, compared with male waes, female waes are less determined by performance within the firm and instead to a lare extent depend on which firm women works for. Furthermore, despite the increase in firm-internal inequality, we find a decrease in the differentials between the means of firms waes both for male and female employees, which suests that the deree to which employees wae depends on their performance within the firm, rather than which firm they work for, is increasin. Another findin is that the rise of temp aencies durin the 2000s, throuh the rowin share in employment they account for, has had a considerable and interestin impact on inequality. While firm-internal wae inequality amon female employees at temp aencies is relatively small, that amon male employees is relatively lare. As a result, the increasin weiht of temp aencies has a neative (compressin) effect on inequality amon female employees, but a positive (enlarin) effect on inequality amon male employees. Furthermore, mean waes at temp aencies are relatively low both for male and female employees, so that the increase in the share of employees workin at temp aencies has a positive (enlarin) effect on between-firm wae inequality, which is defines as weihted difference between the mean wae overall and the mean wae within individual firms. 12

14 While our research has produced interestin new insihts on developments in wae inequality within firms in Japan, much remains to be explored. One important issue, for example, is the relationship between chanes in wae inequality within firms and firm characteristics such as their performance. If we assume that the observed increase in within-firm inequality is the result of the adoption of performance-based pay, we need to clarify under what circumstances firms adopt performance-based pay and how this affects firm performance. References Barlevy, G. and D. Tsiddon (2006) Earnins inequality and Business cycle, European Economic Review, Vol. 50, pp Bell, P. (1951). Cyclical variations and trend in occupational wae differentials in American industry since 1914, Review of Economics and Statistics, Vol. 33, No. 4, pp Blinder, A. S. (1973) Wae Discrimination: Reduced Form and Structural Estimates, Journal of Human Resources, Vol. 8, No. 4, pp Blinder, A. and H. Esaki (1978) Macroeconomic activity and income distribution in the postwar United States, Review of Economics and Statistics, Vol. 60, No. 4, pp Davis, S. J., J. Haltiwaner, L. F. Katz and R. Topel (1991) Wae Dispersion Between and Within U.S. Manufacturin Plants, , Brookins Papers on Economic Activity, Microeconomics, Vol. 1991, pp Freeman, R. B. and L. F. Katz (1994) Risin Wae Inequality: The United States vs. Other Advanced Countries, in R. B. Freeman, ed., Workin Under Different Rules, New York: Russell Sae Foundation. Goldin, C. and R. A. Maro (1992). The Great Compression: The U.S. Wae Structure at Mid-Century, Quarterly Journal of Economics, Vol. 107, pp Goldin, C. and L. F. Katz (2007) The Race Between Education and Technoloy: The Evolution of U.S. Educational Wae Differentials, 1890 to 2005, NBER Workin Paper, No Katz, L. F. and K. M. Murphy (1992) Chanes in Relative Waes, : Supply and Demand Factors, The Quarterly Journal of Economics, Vol. 107, No. 1, pp Katz, L. F. and A. L. Revena (1989) Chanes in the Structure of Waes: The United States vs Japan, Journal of the Japanese and International Economies, Vol. 3, Issue 4, pp Kawauchi, D., R. Kambayashi and I. Yokoyama (2008) Wae Distribution in Japan: 13

15 , Canadian Journal of Economics, Vol. 41, No. 4, pp Lemieux, T., W. B. MacLeod and D. Parent (2009) Performance Pay and Wae Inequality, Quarterly Journal of Economics, Vol. 124, No. 1, pp Mookherjee, D. and A. Shorrocks (1982) A Decomposition Analysis of the Trend in UK Income Inequality, The Economic Journal, Vol. 92, pp Ohtake, F. and M. Saito (1998) Population Ain and Consumption Inequality in Japan, The Review of Income and Wealth, Vol. 44, No. 3, pp Sasaki, H. and K. Sakura (2005) Chanes in the Demand for Skilled Labor within Japan s Manufacturin Sector: Effects of Skill-Biased Technoloical Chane and Globalization, Bank of Japan Workin Paper Series, No. 05-E-12. Shorrocks, A. F. (1982) Inequality Decomposition by Factor Components, Econometrica, Vol. 50, No. 1, pp Shorrocks, A. F. (1984) Inequality Decomposition by Population Subroups, Econometrica, Vol. 52, No. 6, pp Shinozaki, T. (2006) Wae Inequality in Japan, , Japan Labor Review, Vol. 3, No. 4, pp Skans, O. N., P. A. Edin and B. Holmlund (2007) Wae Dispersion Between and Within Plants: Sweden , NBER Workin Paper. No Tachibanaki, T. (2006) Kakusa Shakai, Nania Mondai Nanoka, Tokyo: Iwanami Shoten (in Japanese). Tsuru, T., M. Abe and K. Kubo (2005) Nihon Kiyou no Jinji Kaikaku, Jinji Deta niyoru Seikashui no Kensho, Nihon Roudou Kenkyuu Zasshi, Vol. 7, No. 2, pp (in Japanese). Uni, H.(2008) Chanes in Employment Structure and Rises in Wae Inequality in Japan, Proceedins of the International Conference on Public Employment Service Policies and Perspectives, pp

16 Table 1. Wae rades Grade Standard monthly wae (in yen) Monthly wae bracket (in yen) 1 98,000 Up to 101, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,000 and over Note: This table applies up to March From April 2007, the number of rades increased to 47. Specifically, rades 1 and 39 were each subdivided into five rades. In the analysis in the paper, however, we combined these rades aain to be able to make comparisons between 2003 and

17 Fiure 1. Wae distribution by standard monthly wae rade Share o of insurants Male Female All Wae rade Fiure 2. Chane in wae distribution for male employees No. of Insurants (1,000) (Left axis) (Riht axis) No. of insurants (1,000) Chane ( ) Wae rade 16

18 Fiure 3. Chane in wae distribution for female employees No. of Insurants (1,000) (Left axis) (Riht axis) No. of insurants (1,000) Chane ( ) Wae rade Fiure 4. Chane in wae inequality (MLD) MLD Male Female Year 17

19 Fiure 5. Distribution of MLD for male employees Share of HIS MLD Fiure 6. Distribution of MLD for female employees Share of HIS MLD 18

20 Fiure 7. Chane in within-firm MLD Within-firm MLD Male Female Year Fiure 8. Chane in between-firm MLD Between-firm MLD Male Female Year 19

21 Fiure 9. Decomposition of chanes ( ) in overall inequality Between-firm Within-firm Male Female Fiure 10. Decomposition of chanes ( ) in within-firm inequality Male Female Compositional Firm-internal

22 Fiure 11. Decomposition of chanes ( ) in between-firm inequality Male Female Compositional Pure-differential