Discussion Paper No. 602

TESTING THE MORALE THEORY OFNOMINAL WAGE RIGIDITY

Daiji Kawaguchi and Fumio Ohtake

April 2004

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

Testing the Morale Theory of Nominal Wage
Rigidity
Daiji Kawaguchi
Graduate School of Humanities and Social Sciences
University of Tsukuba
andFumio Ohtake1 2
Institute of Social and Economic Research
Osaka University
April 2004

1 Corresponding Author;

Address: Mihogaoka 6-1, Ibaraki, Osaka 567-0047,
Japan; Tel: (81)-6-6879-8572; Fax: (81)-6-6878-2766; E-Mail: ohtake@iser.osakau.ac.jp
2 We would like to thank Souichi Ohta and the participants of the 2003 Japan
Economics Association annual meeting for their helpful comments. The remaining
errors are, of course, our responsibility. We gratefully acknowledge the financial support from Suntory foundation, Grant-in-aid for scientific research (grant
number (B)(2)12124207 and (C)(2)14530109), and the 21st century COE program(Osaka University).

Abstract
This paper attempts to test the morale theory of nominal wage rigidity byidentifying the causal effect of pay cuts on workers’ income satisfaction andwork morale. This paper uses the current deflationary recession in Japan toestimate this causal effect. Our original survey of Japanese firms and theiremployees conducted in 2000 revealed that about 17 percent of our sample
experienced a nominal, annual income decline. These wage cuts severely
decreased income satisfaction and work morale. We consider several channels through which pay cuts deteriorate workers’ pay satisfaction and work
morale. We found that an income freeze demoralizes workers by reducing
workers’ trust in their firms, but an income decline decreases work moraleeven after controlling for this reduction of trust. Allowing for the firm fixed
effects does not alter the robust relationship between the income cut anddemoralization. Overall, our results consistently indicate the adverse effectof income cuts on workers’ pay satisfaction and morale. This evidence, obtained from a deflationary economy, supports Bewley (1999)’s morale theoryof nominal wage rigidity.

1Introduction

This paper tests the morale theory of nominal wage rigidity proposed by
Bewley (1999), using an original employer-employee survey conducted in the
middle of Japan’s ongoing deflationary recession. Downward nominal wage
rigidity has attracted economists’ interest, mainly due to its important implications for monetary policy. Recent studies based on panel data of workers
have indicated that there is a significant degree of downward nominal wage
rigidity. For example, McLaughlin (1994), Kahn (1997), Card and Hyslop (1997), Altonji and Devereux (2000) and McLaughlin (2000) examined
US micro data to find the existence and degree of nominal downward wage
rigidity. Smith (2000) examined British micro data and Kuroda and Yamamoto (2003a) and Kuroda and Yamamoto (2003b) examined Japanese
micro data.1 All of these studies have examined the distribution of nominal
wage change using panel data and have found an asymmetric distribution
skewed to the right, with a sharp spike at no nominal wage change. The
observed distributions are consistent with the existence of downward nominal wage rigidity. Few of the studies mentioned above have investigated thereasons why nominal wages do not fall, mainly because the data used did
not contain enough information on the workers’ workplace and the workers’
emotional reactions to wage cuts.
The reasons for downward nominal wage rigidity have been mainly in1

Based on the observed downward nominal wage rigidity among Japanese youth, Kondo(2003) considered the reasons why their wage is particularly downwardly rigid.

1

vestigated through interviews with employers, asking the reasons why they
do not cut wages, even during a recession. Bewley (1999) interviewed morethan 300 business executives and labor leaders in the Northeastern regionof the US during the recession of the early 1990s and found that employers avoided pay cuts because they expected that pay cuts would demoralize
workers and reduce workers’ effort. Similar findings have been reported in
Kaufman (1984) and Blinder and Choi (1990) based on smaller-scale employer interviews. Another line of research by Loewenstein and Sicherman(1991) and Frank and Hutchens (1993) offered evidence that workers prefer
an increasing wage profile, and in particular, Loewenstein and Sicherman(1991) introduced the popular survey responses that workers perceive wage
cuts as a sign that their employers do not appreciate their efforts. This evidence indirectly established the link between wage cuts and workers’ morale.
Few studies, however, have attempted to establish the direct, causal relationship between wage cuts and workers’ morale using a sample of workers
who actually experienced wage cuts. An exceptional study is that of Smith(2002), who examined the relationship between wage cuts and workers’ satisfaction with their wages. She used the British Household Panel Study to
examine the effect of wage cuts and freezes on workers’ self-reported satisfaction with their pay. She found that both wage cuts and freezes negatively
affect workers’ satisfaction with their pay by almost the same degree. Because the inflation rate was about 8 to 9 percent at the beginning of the
1990s and was about 2 to 3 percent after 1993, the nominal wage freeze in2the 1990s in the UK implied a real wage cut. From the finding that wage
freezes and cuts affect workers’ pay satisfaction in a similar fashion, Smith(2002) concluded that workers’ pay satisfaction is deteriorated by real wage
cuts rather than by nominal wage cuts.
The morale theory of nominal wage rigidity is powerfully tested in a
deflationary economy. Under inflation, nominal wage freezes imply real wage
cuts and distinguishing the effects of a nominal wage freeze and a nominal
wage decrease on workers’ morale is impossible if workers care about real
wages. At the same time, a nominal wage freeze implies a real wage increase
under deflation, and it is still possible to identify the effect of a nominal wage
decrease on workers’ morale, even if workers react to real change given the
degree of the nominal wage decline dominates the degree of deflation. In
this sense, we can test the effect of nominal wage decline on workers’ morale
without identifying whether workers are reacting to real or nominal changes
in a deflationary economy. In other words, using data on income change andwork morale from a deflationary economy, we can identify the reduced-form
relationship between nominal wage decline and work morale that we wish toaddress.
The discussion above indicates the importance of examining the effects
of nominal wage cuts on workers’ pay satisfaction or morale during a deflationary recession; however, the actual analysis has not been easy because theoccurrence of actual deflation has been quite rare. In this sense, the current
deflation in Japan offers an ideal ground for testing the morale theory of wage
3

rigidity by Bewley (1999). As evidenced in Figure 1, Japan has experienced
a general price decline since the beginning of 1998, and this trend continued
until at least the end of 2001.2 We use an original employer - employee survey
conducted in July 2000 in Japan to examine how workers’ pay satisfaction
and work morale are affected by nominal wage cuts/freezes.
The rest of this paper is organized as follows. Section 2 describes thedata used in this study. Section 3 analyzes the frequency of wage declines
and freezes and who experienced them. Section 4 analyzes the effect of wage
declines and freezes on workers’ satisfaction with their earnings. The lastsection concludes.

2

Data

The Institute of Industrial and Labor Policies, Chubu (Chubu Sansei Ken in
Japanese) conducted a survey covering 123 companies and their employees
in the Chubu area of Japan, which is the area around Nagoya including
Toyota: a well-known motor town. The companies include Toyota and its
subsidiary parts suppliers, Chubu electric power, Matsuzakaya department
store, Nagoya railway, and other companies.
The survey consists of a firm questionnaire and an employee questionnaire. Human resource departments were asked to complete the firm survey
questionnaire. The employee survey questionnaires were distributed and col2

An overview of the recent deflation in Japan is available in Ahearne, Gagnon, Haltmaier, and Kamin (2002).

4lected through labor unions in the case of unionized workers and throughhuman resource departments in the case of non-unionized workers. The employee questionnaires were collected in sealed envelopes to obtain the employees’ honest opinions and to guard their privacy. The questionnaires were
distributed July 5-7, 2000 and were collected at the end of the same month.
The Institute distributed 123 firm questionnaires and collected 83 of them;
the response rate was 67.5%. It randomly chose 2000 employees, distributed
the questionnaires, and collected 1823 of them, for a response rate of 91.2%.
The response rate was quite high for this type of survey, and the sample
presumably represents the population: all employees of the 123 firms in thiscase. Among these observations, we dropped the female observations and restricted our sample to observations for which all of the following information
was available: educational background, income, industry, occupation, andchanges in basic pay, bonuses, and annual income. This sample restriction
reduced the sample size to 1557.
The descriptive statistics of the respondents appear in Table 1. The
average age of workers was about 37 years old and the average tenure wasabout 17 years. As for educational background, the majority of the sample(51%) was high school graduates and 29% of the whole sample was college
graduates. Considering the distribution of years of education and age, theaverage job tenure was long, reflecting the long-term employment relationshiptypical in Japan, as articulated by Hart and Kawasaki (1999). More thanhalf of the sample earned between 5000 and 7990 thousand yen annually (One5

dollar was traded for 105 - 110 yen in July 2000). The earnings distribution
was skewed to the right, as in the usual earnings distribution. We also report
the comparable national figures taken from Japan Institute of Labour (2002)
in Column (2). Compared with these national average figures, workers in theanalysis sample had longer job tenure and a higher educational backgroundand enjoyed higher earnings. It is important to note that our sample basicallyis comprised of workers who are in “good jobs.”

3

Whose Wages Fall in Deflation?

The employee survey asked about the changes in i) basic pay, ii) bonus pay,
and iii) annual income from the previous year, and workers were asked tochoose one of the following three options: a) decreased, b) frozen, or c)increased. The responses to this question by age categories appear in Table
2. It is striking that about 17% of the workers in the sample experienced
an annual income decline. The distribution of changes shows that bonus
pay was more likely to be frozen or decreased than basic pay, and this may
reflect the fact that bonus pay is more vulnerable to a firm’s performance.
The age decomposition shows that basic pay/bonus decreases/freezes weremore likely to occur among older workers, particularly workers between ages
50 and 59.3
3

The high frequency of basic pay decline among workers in this particular age groupmay be partly due to the “position-retirement” that is a widely observed employment
custom in Japan. Since large firms in Japan tend to adopt up-or-out career systems
during the late stage of workers’ careers, those workers who are in administrative (whitecollar) or foreman (blue collar) positions but fail to be promoted to the higher position

6

Among workers between ages 40 and 49, 6.45% and 16.13% of workers
experienced a basic pay and bonus decline respectively. In total, 18.43% ofworkers in this age range experienced annual income decline. The proportionof workers who experienced annual income decline was 14.02% among workers
between ages 30 and 39 and 12.89% among workers between 20 and 30. A
comparison of these percentages reveals that an annual income decline wasmore prevalent among older workers. In particular, the decrease in basic pay
was relatively rare among workers between ages 20 and 30 compared witholder workers.
To examine the effect of age on the probability of experiencing an annual
income decline or freeze, holding educational background, income level, industry, and occupation constant, we estimate the multinomial logit model,
in which the dependent variable is a categorical variable corresponding toannual income 3. declined, 2. frozen, and 1. increased. The results ofthe estimation appear in Table 3. The results of the estimation show thatolder workers are less likely to experience an annual income increase evenafter controlling for covariates, as reported in Column (1), but once the effects of covariates are controlled for, age does not explain the annual income
decrease, as reported in Column (2). To check the appropriateness of thelinear specification with respect to age and tenure, the specification that includes the squared term of age and tenure is estimated and the results areare asked to leave the company with some premium on their retirement allowance. If aworker prefers to stay in the firm, he is asked to retire from his current position and workin a lower one; a basic pay cut is usually associated with this transition.

7

reported in Columns (3) and (4). Nonetheless, those two terms do not enter
the equation significantly, and the linear specification is sufficient to capture
the effect of age and tenure on annual income change. To conclude, after
conditioning on the covariates, including income level, older workers are lesslikely to experience an annual income increase, but they are not more likely
to experience income decrease. Thus we roughly conclude that workers in all
age ranges are equally likely to experience a wage decrease conditioned on
the covariates, including their current income level.

4

The Effect of Wage Cuts on Workers’ Satisfaction with Their Pay

This section analyzes how income decreases and freezes affected workers’
satisfaction with their pay. As a measure of workers’ satisfaction with theirwages, we analyzed responses to the following question: “Are you satisfied
with your current annual income? Please answer using a percentage, where
100 percent means that you are completely satisfied with your annual income.” We assume that the response to this question is determined byyi = β1 Increasei + β2 Decreasei + xi γ + ui ,(1)

where yi is the worker i’s satisfaction with his pay, Increasei and Decreasei
are the dummy variables that take one if the worker i experienced an income
increase and decrease respectively. The vector xi contains sets of covariatesthat can affect the workers’ pay satisfaction and can be correlated with the8event of a pay freeze or decline. Most importantly, xi contains income category dummy variables to control for the effect of income level on income
satisfaction.
The results of the estimation controlling for education, income class, industry, and occupation appear in Column (1) of Table 4. An income increase
boosts workers’ satisfaction with their annual income by 8.04 percentage
points while an income decrease diminishes the satisfaction by 3.13 percentage points, compared with the case of an income freeze.
Annual income decline may decrease workers’ satisfaction with their pay
through several channels. As Clark and Oswald (1996) discussed, relative
income, rather than absolute income, determines workers’ satisfaction. It
may be relative income decline compared with a reference group, rather thanincome decline itself, that negatively affects workers’ income satisfaction. To
address this possibility, we used a question asking workers’ perceived relative
position of their annual income compared with colleagues of the same sex,age, educational background, occupation, etc. Workers were asked to answer
this question with one of the following six response categories: 1. Upper(Above top 20 %), 2. Upper middle (from top 20% to top 40%), 3. Middle(top 40% to top 60%), 4. Lower middle (Bottom 20% to bottom 40%), 5.
Bottom (Below bottom 20%) and 6. Do not know. The estimation results ofthe model that includes dummy variables for each of these categories appear
in Column (2). This inclusion of relative income position dummy variables,
however, does not essentially change the results from Column (1).
9

If workers strongly attach to their firms by accumulating firm-specific human capital, they have good reason to care about their firms’ growth. Firms’
growth may affect workers’ satisfaction with their wages because workers withpoor future prospects may require higher current wages to compensate for
their future lower expected wages. Income declines and freezes may be correlated with firms’ growth, and the coefficient on the income decline or freeze
dummy variables may be subject to omitted variable bias. To deal with thisissue, we included firms’ sales growth between 1996 and 1999 (budget year)
and employment growth between 1997 and 2000 (calendar year) as proxyvariables for firms’ expected growth. The estimated results appear in Column (3) of Table 4. Although sales growth positively affected workers’ income
satisfaction, the coefficients for the income freeze or decline dummy variables
and their interaction with the age dummy variables did not essentially differ
from the results in Column (2).
According to Lazear’s long-term contract theory (Lazear (1979) and Lazear(1981)), young workers are paid below their marginal product and old workers are paid above their marginal product to induce workers’ effort when
workers’ effort is not perfectly observed by firms. As mentioned in Lazear’s
original work and formalized in Kanemoto and MacLeod (1992), this type oflong-term contract depends strongly on the workers’ trust that their firms
will repay the difference of wage and productivity when workers get old.
Thus, wage cuts may damage workers’ trust in their firms and reduce theirsatisfaction with their pay. Alternatively, as Bewley (1999) discussed, wage
10

cuts may directly destroy the workers’ trust in their firms and reduce workers’ satisfaction with their wages because workers no longer feel identified
with their firms. Both theories predict that wage cuts will reduce workers’
satisfaction with their wages via the reduction of their trust in their firms.
To evaluate these possibilities, we include several variables that presumably capture the transparency of each firm’s wage- determining mechanism
and workers’ trust in their firms. The firm survey asked whether each firm
publicized the following items to their workers: 1. wage schedule, 2. worker
evaluation sheet, 3. the standards for worker evaluation, 4. the mechanism ofwage and bonus determination based on worker evaluation, and 5. the mechanism of promotion determination based on worker evaluation. The firms
were allowed to choose one of the following three choices: 1. Yes, 2. No, 3.
We do not have one. We created the dummy variable indicating “yes” to eachquestion and included the dummy variables as explanatory variables in (1).
These dummy variables are supposed to capture the trust between firms andworkers created through the transparency of wage/bonus/promotion determination. In addition, answers for several questions in the employee survey
were included as explanatory variables. The first item used was the answer
to a question regarding whether an employee’s trust had increased or decreased in these three years. Employees were asked to answer the question
using the numbers between 1 (decreased very much) and 5 (increased verymuch). This index is directly included in the regression. The questions that
asked workers their perceptions of the firm’s fairness in promotion and wage
11

determination were also used. One question asked whether the respondent
felt that the firm’s promotional decisions were fair, and the respondent could
choose one of the following alternatives: 1. unfair, 2. rather unfair, 3. neither fair nor unfair, 4. rather fair, 5 fair. This response is directly introducedin the regression. The employee questionnaire also asked for each worker’s
subjective satisfaction with the firm’s evaluation of his work performance.
Each respondent was allowed to answer this question using a number between 0 and 100. This variable is also directly introduced in the regression.
The other question that is intended to capture each worker’s trust in his firmasks how workers express their work-related complaints. Respondents wereallowed to choose one from the following answers:
1. consult the labor union at your workplace, 2. consult colleagues atyour workplace, 3. consult a superior at your workplace, 4. tell people in
the human resource division, 5. file complaint to complaint bureau at yourworkplace, 6. complete an opinion survey administrated by your company,
7. consult an external organization dealing with labor issues, 8. consult alawyer, 9. do not tell anyone and try to be patient, 10. consider a job change,
11. rely on other methods (specify).
The dummy variables were created that take one if the respondent expressed his complaint through a labor union (i.e., the worker chose the alternative 1) and company (i.e., the worker chose at least one of the alternatives
between 3 and 6). Both dummy variables are included in the regression tocapture the worker’s trust in his labor union and firm.
12The regression results, including all of the variables explained above that
presumably capture each worker’s trust in his firm, appear in Column (4)of Table 3. The coefficients for income increase boost workers’ satisfaction
by 4.53 percentage points, while income decline diminishes the satisfaction
by 2.96 percentage points compared with the case of income freeze. Thus,
the speculation that income decline decreases workers’ income satisfaction
by destroying the trust between workers and firms is not strongly supportedby the data.
The results of a regression that includes both proxy variables representing
each firm’s growth and each worker’s trust appear in Column (5) of Table 3.
The results do not essentially change from the results reported in Column(4). Even after controlling for several factors, the negative effect of income
decline on income satisfaction is robust and stronger among younger workers.
As confirmed in Tables 2 and 3, older workers are less likely to experiencea wage increase. This could be so because the effect of an income freeze
on pay satisfaction may differ depending on workers’ age. To examine thispossibility, a specification that includes the interaction terms between income
increase or decrease dummy with age is estimated and the result is reported
in Column (6). The coefficient for the interaction term of income increase
and age is negative, which implies that an income increase brings less pay
satisfaction among older workers. Otherwise, this result can be interpreted
that younger workers’ pay satisfaction is more strongly deteriorated by a pay
freeze. This is probably because younger workers expect an income increase13

more strongly than older workers. An interesting result is the zero coefficientfor the interaction term between income decrease and age. This result implies
that an income decline negatively affects workers’ pay satisfaction by thesame degree, regardless of the workers’ age.
Thus far, the analysis neglects the firms’ heterogeneity, which could becorrelated with the event of an income increase or decrease. Neglecting firms’
heterogeneity could potentially bias the estimated coefficients for an income
decrease. On the one hand, those firms that cut workers’ income may be
experiencing financial hardship that is not captured by observed variables.
This financial hardship may create a bitter atmosphere among workers, which
may negatively affect workers’ pay satisfaction. Then the adverse effect of apay cut on workers’ pay satisfaction may operate through a worse workplaceatmosphere. On the other hand, if firms attempt to keep the number of
employment by adopting a pay cut, workers may react less negatively to theincome cut. In this case, the negative effect of income cut on pay satisfactionis under-estimated because we failed to hold firms’ employment policies constant. To deal with these possible biases, whose sign cannot be determineda priori, we adopt a firm-level fixed effects estimation. The result of the estimation appears in Column (7) of Table 4. The result is virtually identicalto the result reported in Column (6), and the effect of the heterogeneity bias
seems to be minimal.

14

5

The Effect of Wage Cuts on Workers’ Work
Motivation

In this section, we attempt to directly recover the causal relationship between
income change and the change of workers’ morale. The employee survey asked
about the change of the individual worker’s and workplace morale in the past
3 years. The question reads “How has your individual and your workplacemorale changed in the past 3 years?” and employees were asked to answer
this question by choosing one of the following choices as a description for his
own and workplace morale respectively; 1: Decreased, 2: Rather decreased,
3: Hard to tell, 4: Rather increased, 5: Increased. Using this question, we
relate the change of income and the change of the individual workers’ morale.
Using this question has two merits. First, the question directly asks
about individual workers’ morale and we can directly test the morale theory
by Bewley (1999). Second, the question asks about the change of workers’
morale instead of the level of workers’ morale. Thus we can avoid the interpersonal comparison of a subjective answer. In addition, we can relate thechange of income with the change of work morale. One drawback is thatthe income change question asked about the change over the previous year,
but the morale change question asked about the change over the past three
years.
The latent variable of the change of workers’ morale is specified as:m∗i = β1 Increasei + β2 Decreasei + xi γ + ui ,15

(2)

where all the notations except for m∗i are the same as for equation (1) whilem∗i is the latent variable of the change of workers’ morale. This latent variable
is linked to the observed response by the following equation:
if m∗i ≥ µ4 ,if µ4 > m∗i ≥ µ3 ,mi = 3 if µ3 > m∗i ≥ µ2 ,

2 if µ2 > m∗i ≥ µ1 ,

1 if µ1 > m∗i ,

5





4

(3)

where mi is a categorical variable indicating worker i’s response to the morale
question (1:“Decreased” - 5:“Increased”) and µk (k = 1, 2, 3, 4) are the thresholds of morale change that determine the answer for the morale question. The
result of the estimation with standard covariates appears in Column (1) of
Table 5. The result indicates that income increase stimulates work morale,
while income decrease demoralizes workers. Both effects are statistically significant.
The effect of income change on morale change can operate through several channels. To identify these channels, sets of covariates are added to themorale change equation gradually, as in the analysis of the previous section.
The first set of covariates is the workers’ perception of their relative income
position and the result of the estimation appears in Column (2) of Table 5.
The result is essentially identical to that of Column (1), except for the sizeof estimated coefficients. The second set of covariates is the proxy variables
for the firms’ growth: firms’ sales growth between 1996 and 1999 and employment growth between 1997 and 2000. The result of the estimation isreported in Column (3), and the result does not differ drastically from that16

of Column (2). The third set of covariates is the proxy variables for workers’
trust in their firms: transparency of firms’ wage policy, workers’ self-reportedchange in the trust toward their firm in the past three years, workers’ perceived fairness of promotion and wage determination, and to whom workers’
work-related complaints are directed. The inclusion of this set of covariates
drastically changes the estimated effect of income change on the change ofwork morale, as reported in Column (4). Income increase no longer pushes
up workers’ morale after conditioning on workers’ trust in their firms. Thischange of result implies that the positive effect of income increase on workers’ morale operates by fostering workers’ trust in their employers. To thecontrary, the adverse effect of income cut on workers’ morale is estimatedto be significant even after controlling for the change in workers’ trust in
their employers. The results of the estimation that includes the proxy forfirm growth in addition to the variables included in Column (4) appears inColumn (5). The addition of the proxy variables for firm growth does not
significantly change the estimation results.
Thus far, we have neglected the possible heterogeneous morale response
to income change depending on the workers’ age. To allow for this heterogeneity, the interaction term of age and dummy variables for income increase
and decrease are introduced into the specification. The result of the estimation is reported in Column (6). The coefficients for the interaction terms are
virtually zero and the morale responses are homogeneous across age groups.
Lastly, we consider firms’ unobserved heterogeneity that is potentially corre17

lated with the event of income increase or decrease. The existence of correlated heterogeneity could bias the coefficient for income decrease, either in an
upward or downward direction. The event of income decrease may be more
likely to occur in the firms that attempt to keep the number of employees
through pay cuts or in the firms that have a deteriorating workplace atmosphere. To address this possible heterogeneity bias, we introduced dummy
variables for each firm in the estimation. The result of estimation appears inColumn (7), and it is virtually unchanged from the result in Column (6).
The results reported in this section clearly indicate the negative effects ofincome cuts on workers’ morale, even after controlling for several factors that
could occur simultaneously with income change, such as a change in workers’
trust in their employers or employers’ unobserved heterogeneity. This result
supports Bewley (1999)’s morale theory of nominal wage rigidity.

6

Conclusion

Using a firm-employee survey of Japan conducted in 2000, this paper examined the effect of pay cuts on workers’ pay satisfaction and work morale
under deflation. The data show that about 17 percent of workers experienced
an annual, nominal income cut. Those workers who experienced income cuts
were less satisfied with their pay and had lower work morale than those who
did not experience an income cut. We found that an income increase positively affected workers’ morale by fostering workers’ trust in their firms. In
contrast, even after controlling for the workers’ trust in their firms, income
18

cuts negatively affected workers’ work morale. These findings are very robust,even after controlling for workers’ and employers’ heterogeneity by using therich information available in our survey.
Our results clearly indicate that workers are demoralized by nominal income cuts, even during the deflation. The results obtained in this paper
supports Bewley (1999)’ morale theory of wage rigidity, although whether
the wage cut was real or just nominal was indistinguishable because the exact amount of the nominal income cut was unknown in our survey. We offer
strong evidence that nominal wage decreases demoralize workers, while wage
freezes do not under deflation. This evidence explains why the nominal wage
is rigid in a downward direction and the distribution of wage change has spikeat zero even during a deflationary recession.

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22

Table 1: Descriptive Statistics
Variable
Age
TenureEducation (Category Dummies)
Junior High School
High School
Technical College
Tech. Coll. Attached to the Firm
Junior College
College (Humanities and Social Sciences)
College (Engineering and Natural Sciences)
Graduate School
Annual Income (10 Thousand Yen) (Category Dummies)-299
300-399
400-499500-599600-699700-799
800-899
900-999
1000-1099
1100-1199
1200-1299
1300-1399
1400-1499
1500N

(1)
Analysis
Sample37.49(7.34)
16.99(7.92)(2)
National Figures for Male
Workers
39.7

0.04
0.51
0.02
0.06
0.02
0.14
0.15
0.06

0.16
0.29

0.01
0.05
0.14
0.17
0.17
0.17
0.11
0.08
0.05
0.02
0.01
0.01
< 0.00< 0.001557

11.8} 0.08 (Technical Coll. +Junior Coll.)} 0.29 (College + Graduate
School)Average Annual Income(10 Thousand Yen)
College Graduates
522
Tech. Coll. + Junior College
382.8High School Graduates
448.3

Note: Age, education, and annual income are category variables. Means of the variables are reported
and standard errors are reported in parentheses. All national figures are taken from the Japan Instituteof Labour (2002). Average age and tenure of workers are based on Table 16 and figures are for 1999.
The distribution for educational background is based on Table 15 that contains figures for 1997.
Average annual income for each educational background is based on Table 38, which contains theamount of scheduled case earnings for 2000. We imputed annual income assuming that workers
receive 4 months salary as a bonus in a given year. Receiving a bonus equivalent to 4 months salary isroughly consistent with the national figures reported in Table 37.

23

Table 2: Descriptive Statistics of Wage or Income Decline (Employee Reported)
Age Group
Basic Pay
DecreaseFreezeIncrease

<30

30-39

40-49

50-59

Total

2.06
13.92
84.02

5.51
14.52
79.97

6.45
22.35
71.20

16.38
30.77
53.85

6.17
17.98
75.85

DecreaseFreezeIncrease

13.40
23.20
63.40

13.77
23.78
62.45

16.13
26.78
57.14

38.46
24.62
36.92

16.44
24.60
58.96

Annual Income
DecreaseFreezeIncrease

12.89
17.53
69.59

14.02
19.52
66.46

18.43
23.27
58.29

30.77
28.46
40.77

16.51
21.07
62.43

N

194

799

434

130

1557

Bonus

24

Table 3: Annual Income Change from the Previous Year (Employee Reported)
Method of Estimation: Multi-Nominal Logit
Dependent Variables: Increased, Frozen (Base Category), Declined
Dependent Variable
Age

Age2

Ten

Ten2

(1)
Increased-0.06(0.03)[-0.02]-(2)
Decreased
0.03(0.03)[0.01]--0.01(0.03)[<-0.00]-

0.02(0.03)[0.00]--0.11(0.41)
1.95(1.26)
0.29(0.46)
1.12(0.76)-0.19(0.67)-0.10(0.59)-0.08(0.61)
Yes-0.40(0.30)
2.05(1.15)
0.46(0.31)
0.33(0.71)-0.89(0.50)-0.26(0.40)-1.20(0.59)
YesHigh School
Tech. Coll.
Firm Tech.
Junior Coll.
Coll. (BA)
College (BS)Grad. School
Income, Industry, Occupation, Dummies
Observations

1557

(3)
(4)
Increased
Decreased
-0.07
-0.01
(0.03)(0.03)[-0.01][0.00]
0.00
0.00(<0.00)(<0.00)[<-0.00][<0.00]-0.03
0.10(0.09)(0.08)[-0.01][0.01]
0.00-0.00(<0.00)(<0.00)[<0.00][<0.00]-0.06-0.35(0.44)(0.29)
1.97
2.12(1.26)(1.17)
0.33
0.51(0.48)(0.33)
1.17
0.43(0.74)(0.70)-0.14-0.69(0.71)(0.50)-0.06-0.12(0.61)(0.44)-0.08-1.02(0.64)(0.67)
Yes
Yes
1557

Note: Firm-level clustering, robust standard errors are reported in parentheses. Marginal effects
evaluated at the sample mean are in brackets.

25

Table 4: OLS and Firm-level Fixed Effects Estimation of Satisfaction Determination
Dependent Variable: Satisfaction with Current Annual Income(Expressed in Percentage: Mean = 70.93)
Income Increase
Income Increase

(1)
8.04

(2)
6.62

(3)
7.35

(4)
4.53

(5)
5.11

(6)
5.34

(7)
5.25

(1.18)(1.13)(1.21)(1.13)(1.30)(1.08)(1.07)

-

-

-

-

-

-0.34

-0.32

(0.11)(0.14)* Age-Mean(Age)
-3.13

-3.45

-2.26

-2.96

-2.14

-2.32

-2.20

(1.35)(1.25)(1.18)(1.10)(1.08)(1.01)(1.39)

-

-

-

-

-

-0.00

0.02

(0.18)(0.17)

-0.14

0.02

-0.10

0.23

0.12

0.28

0.23

(0.25)(0.27)(0.25)(0.28)(0.25)(0.21)(0.21)

0.18

0.12

0.27

0.06

0.19

0.19

0.29

(0.22)(0.24)(0.22)(0.23)(0.20)(0.19)(0.19)

Education Dummies

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Income Dummies

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Ind. Occupation. Dummies

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Relative Inc.

No

Yes

Yes

Yes

Yes

Yes

Yes

Trust in Firm

No

No

No

Yes

Yes

Yes

Yes

Firm Growth

No

No

Yes

No

Yes

Yes

Yes

Firm Fixed Effects
Observations

No
1552

No
1552

No
1457

No
1524

No
1432

No
1432

Yes
1432

R-squared

0.22

0.26

0.28

0.39

0.40

0.40

-

Inc. Decline
Inc. Decline* Age-Mean(Age)AgeTen

Note: Firm-level clustering, robust standard errors are reported in parentheses for the OLS estimates.
Usual standard errors are in parentheses for the fixed effects estimates.

26

Table 5: Ordered Probit Estimation of the Determination of the Change of Workers’ Morale
Dependent Variable: The Change of Individual Works’ Morale from 3 Years Ago(1: Declined, 2: Rather Declined, 3: Hard to Tell, 4: Rather Increased, 5: Increased; Mean = 3.11)
Income Increase
Income Increase

(1)
0.19

(2)
0.14

(3)
0.12

(4)
-0.01

(5)
-0.02

(6)
-0.01

(7)
-0.01

(0.07)(0.07)(0.07)(0.09)(0.09)(0.10)(0.11)

-

-

-

-

-

0.00

-0.00

(0.01)(0.01)* Age-Mean(Age)Inc. Decline
Inc. Decline

-0.20

-0.22

-0.23

-0.15

-0.18

-0.16

-0.15

(0.07)(0.07)(0.07)(0.07)(0.07)(0.08)(0.09)

-

-

-

-

-

-0.01

-0.01

(0.01)(0.01)

-0.02

-0.01

-0.01

-0.01

-0.01

-0.01

-0.01

(0.01)(0.01)(0.01)(0.01)(0.01)(0.01)(0.01)

-0.00

-0.01

-0.01

-0.01

-0.01

-0.01

-0.01

(0.01)(0.01)(0.01)(0.01)(0.01)(0.01)(0.01)

-2.56

-2.32

-2.89

-2.59

-2.81

-2.75

-2.04

(0.51)(0.54)(0.51)(0.50)(0.50)(0.47)(0.52)* Age-Mean(Age)AgeTen
Cut Point 1
Cut Point 2

-1.62

-1.37

-1.92

-1.41

-1.63

-1.57

-0.82

(0.52)(0.54)(0.50)(0.51)(0.50)(0.45)(0.52)

-0.63

-0.37

-0.89

-0.25

-0.43

-0.37

0.40

(0.51)(0.53)(0.49)(0.50)(0.49)(0.44)(0.51)

0.69

0.97

0.48

1.30

1.15

1.21

2.00

(0.51)(0.53)(0.49)(0.50)(0.47)(0.42)(0.47)

Educ. Dummies

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Income Dummies

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Ind. Occ. Dum

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Relative Inc.

No

Yes

Yes

Yes

Yes

Yes

Yes

Trust in Firm

No

No

No

Yes

Yes

Yes

Yes

Firm Growth

No

No

Yes

No

Yes

Yes

Yes

Firm Fixed Effects
Observations

No
1553

No
1553

No
1456

No
1523

No
1430

No
1430

Yes
1430

Log Likelihood

-2100

-2082

-1917

-1816

-1681

-1681

-1654

Cut Point 3
Cut Point 4

Note: Standard errors are in parentheses. Firm-level clustering, robust standard errors are reported in
the parentheses for the specifications that do not include firm fixed effects.

27

19
97
0
19 1
97
0
19 3
97
0
19 5
97
0
19 7
97
0
19 9
97
1
19 1
98
0
19 1
98
0
19 3
98
0
19 5
98
0
19 7
98
0
19 9
98
1
19 1
99
0
19 1
99
0
19 3
99
0
19 5
99
0
19 7
99
0
19 9
99
1
20 1
00
0
20 1
00
0
20 3
00
0
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00
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00
0
20 9
00
1
20 1
01
0
20 1
01
0
20 3
01
0
20 5
01
0
20 7
01
09

Figure1: CPI of Japan (March 2000=100)

103

102

101

100

99
y = -0.0011x2 + 0.0259x + 100.8
R2 = 0.811

98

97Year Month