The Impact of Import Competition
on Japanese Manufacturing Employment

Eiichi Tomiura*

Research Institute for Economics and Business Administration, Kobe University,
2-1 Rokko-dai, Kobe City, 657-8501, Japan
E-mail: tomiura@rieb.kobe-u.ac.jp

April 2001
Abstract
Although previous studies of the effect of imports on Japanese employment relied on relatively
aggregate data, the variability among industries is substantial within each two-digit sector. This
paper exploits recently available longitudinal data of 390 manufacturing industries and controls
for industry-specific factors at the four-digit level. This paper finds the significant impact ofimport price changes on Japanese employment. The estimates suggest that substantial share of
average employment decline can be accounted for by the intensified import competition andthat the employment sensitivity increases with industry import share. All these findings are
significant especially for the yen appreciating recession years.
Journal of Economic Literature Classification Numbers: F14, F41.

*

I am grateful to Yukio Uchida for his excellent research assistance. Valuable comments from
Naoki Mitani are appreciated. All remaining errors are mine.

I. INTRODUCTION
The intensified import competition must have non-negligible impact on many decisionvariables of domestic firms in increasingly globalized economies. Among the variables ofconcern, employment is one of the most serious indicators for households and policy makers.
Despite the attention to the possibility of deindustrialization in Japan, there has been very little
formal research for the effect of foreign trade on Japanese employment. When we limit our
scope to papers in international academic journals published during the last decade, Dekle(1998), Rebick (1999) and Tachibanaki et al. (1998) are almost the sole contribution to thisissue.1 On the other hand, various studies, including Revenga (1992), since Branson and Love
(1988), have accumulated for the U.S. case to meet the challenges posed by the appreciating
dollar and high unemployment in the 1980s. One of the reasons for this lack of analyses ofJapanese experience may have been the relative stability of employment once assured by theJapanese traditional long-term employment practice, but the unemployment has now become aserious economic problem in Japan. Hence, the direct investigation of impact of international
competition on Japanese employment is required to respond to the needs both in academia
and in policy circles.
Previous studies of Japanese employment and imports, however, have been limited tothose using relatively aggregate data, although they succeeded in revealing important
regularities. Dekle (1998) found, by estimating the labor demand function, that yen fluctuations
have a sizable impact on Japanese employment. By decomposing Japanese demand into1

Even if we expand our scope to earlier literature on this issue, we can think of no directly relevant
papers other than Higuchi (1989) and Brunello (1990). Several authors are interested in the effect offoreign direct investment on employment or the effect of imports on wages in Japan. On the other
hand, Burgess and Knetter (1998) accomplish an international comparison of G-7 countries,
including Japan, on employment response to exchange rates.
2

components, Rebick (1999) detected that employment changes of men are strongly relatedwith export growth but import share changes have no noticeable effect on employmentchanges. Tachibanaki et al. (1998) reported, based on cross-section regressions of Japaneseindustries, that the relation between employment and imports has generally been weak while
the imports from China could have a strong effect on wages. All these findings are very
informative, carefully based on analytically elaborated methods and produced critical
implications, but, at the same time, are unfortunately constrained by the limitation of Japanese
import data concorded to a domestic industry basis. All previous empirical work on Japaneseemployment and trade, as far as the author knows, relied on broadly defined two-digit data.2
This contrasts with studies of the U.S. case since they have already extensively employedfour-digit data.
The level of data aggregation is beyond an issue of mere curiosity. As will be explained inthis paper, substantial variability is actually observed across four-digit industries within thesame two-digit sector in terms of import penetration and of employment growth in the case ofJapanese manufacturing. For example, the import share of industries ranges widely fromone-hundredth percent up to 98 percent in 1995 if industries are disaggregated into thefour-digit level, while the variation is at most around thirty percent among two-digit sectors.
Therefore, since the two-digit classification is obviously too broad for our purpose, we need tocontrol for various industry-specific factors at more disaggregated level.
To meet such a requirement, this paper exploits recently available four-digit longitudinal
data of 390 Japanese industries, based on the data concordance between import statistics andJapan’s Annual Survey of Manufacturers (Kogyou Tokei, in Japanese) established by2

For example, Rebick (1999) uses observation of 18 two-digit industries with five-year intervals.
Tachibanaki et al (1998) also depend on two-digit data of 22 industries, although they are annual.
The data set of Dekle (1998) consists of 12 two-digit industries.
3

Tomiura and Uchida (2001).3 The number of industries whose data are available, 390, ismuch larger than typical numbers in previous studies; i.e. around twenty. The impact of importcompetition on employment is examined by estimating the labor demand function in the open
economy, as in Dekle (1998).4 The instrumental variables are assigned to the wage, theimport price and the import share, because they are supposed to be endogenously determined.
The sample period in the data set, 1988-1995, is quite information rich, as it covers both theboom years with relatively stable exchange rate and the recession years after the burst of realestate and stock bubble with yen appreciation. 5 To examine the possible asymmetry in
employment response during these years, this paper splits the whole sample period into two
sub-periods.
To preview our results, this paper demonstrates, by controlling for the industry-specificeffect at the disaggregated level, that Japanese employment is significantly responsive to importprice changes and that substantial share of average employment decline can be explained by
the intensified import competition. This paper also finds that the employment sensitivity
increases with industry import share. All these three principal findings are significant in theyears of recession with yen appreciation after 1993.
The remainder of the paper is structured as follows. Section II explains the dataconcordance and documents the inter-industry variation at the four-digit level. Section III
formalizes our econometric specifications. Section IV reports the empirical results. Finally,
3

Tomiura and Uchida (2001) describe the data set in detail and apply it to the preliminary study ofgross job creation and destruction. Since their gross job flow data are available only twice in five
years, this paper is the first attempt to use this concorded data to the analysis of longitudinal datawith sufficient observations along the time dimension.
4
As will be explained, we cannot choose the approach by Rebick (1999) due to the data constraint
on the export side. The econometric models in Tachibanaki et al. (1988) are not formalized in an
optimization framework. On the other hand, the reduced-form estimation, as in Revenga (1992), isvulnerable to misspecifications of labor supply function.
5
The data before 1988 is not available because the import classification system was substantiallychanged in that year due to the adoption of the international harmonized system of tariff

4Section V concludes.

II. MATCHING IMPORT AND EMPLOYMENT DATA AT 4-DIGIT LEVEL
Whenever a researcher becomes interested in the impact of trade on employment andwages, the matching of import data to labor data has always been a substantial problem
because two statistics adopt different classification systems in many countries, including Japanand the U.S. Even if we trace import data back to nine-digit levels in the Harmonized System(HS) classification which identifies more than eight thousand products, some products cannot
be mapped to one particular domestic industry. 6
The availability of matched data, however, sharply varies depending on the countries
under investigation. For the U.S. case, a comprehensive data concordance has already been
established at NBER by Feenstra (1996) and been extensively used by many researchers.7
To evaluate the impact of import competition on Japanese employment or wages, on the other
hand, each researcher must establish own concordance table from scratch. Hampered mainlyby the lack of import data concorded to a domestic industry classification, previous studies ofJapanese data have been limited at two-digit sectors (e.g. Higuchi (1989), Brunello (1990),
Burgess and Knetter (1998), Deckle (1998), Tachibanaki et.al. (1998), and Rebick (1999)),
while U.S. industries have already been often explored at four-digit level (Revenga (1992), forexample). As will be explained later, the two-digit level classification is obviously too broad forstudying the impact of import on employment since the degree of import penetration
substantially varies among four-digit industries even within the same two-digit sector. Unlessclassifications. The data for 1995 is the most recent one at the time of data concordance research.
6
For example, many industries are classified in domestic industry classification by theirproduction/processing method, which is unknown for imports produced/processed outside of thecountry.
7
The data set constructed by Feenstra (1996) contains U.S. import data with many classifications
such as SIC, SITC, and HS.
5we trace back at least to four-digit level and control for industry-specific factors, we cannot
exclude the possibility that the aggregation effects could contaminate the results previously
obtained at two-digit Japanese data.
This paper employs the import and employment data matched by Tomiura and Uchida(2001), which is the most comprehensive data concordance to date for Japanese industries
available at the four-digit level.8 Since we believe the relation of employment with international
competition is a current serious concern, this paper is intended to be an early contribution to
the investigation of Japanese employment and import, by using this recently available data. The
number of industries of which the data are available in this data set, 390, is by far the larger
than those examined previously, i.e. from eight to twenty-four. The data set is also informativein that it includes, instead of a sub-sample of, all manufacturing industries, excluding only
non-tradables.9 Since the sample period of concorded data is from 1988 to 1995, we have alongitudinal data of 3120 observations (390 industries for 8 years). The use of this detailed
data set must contribute immensely to an understanding of Japanese response of employment
to import competition.
Before discussing formal models and estimations, brief overview of basic statistics will be
useful. Table I summarizes the import share data classified by two-digit sectors. The importshare kept rising in many sectors. What is most striking in Table I, however, is the tremendous
heterogeneity across four-digit industries within each two-digit sector. For example, in the8

For detailed information on this data set, see Tomiura and Uchida (2001). The import dataclassified according to the domestic industry classification and the complete listing of SIC codes ofindustries will be downloadable at the web site.
9
Out of 562, all four-digit domestic industries, 72 industries are excluded as nontradables. The SIC
codes for these industries are listed in Tomiura and Uchida (2001). Other 490 industries areaggregated into 390 industries, of which each of 334 industries has one-to-one direct
correspondence in import statistics. Although necessary to complete the analysis of impact ofinternational competition, we leave the study of export to future work since no data concordancetables are currently available at a comparably disaggregated level and since we believe import effectcan be examined separately from export effect.
6

electric machinery industry, the largest sector in Japan in terms of employment size, imported
products reached in 1995 to occupy nearly eight percent of the domestic market. The
variation within the sector, however, is substantial since there simultaneously exist an industry
with import share exceeding twenty percent (radio and television sets) and an industry withthat less than one-tenth percent (traffic signal control equipment).10 Besides, while the highest
import share observed at the two-digit level is at most around thirty percent, the same tablealso shows that imports actually dominate some industries with import share exceeding ninety
percent when we disaggregate industries into the four-digit level. We cannot neglect thus
considerable inter-industry variation.
Table II documents the basic descriptive statistics of related variables, including
employment and wages. The employment expanded in the first sub-period (1988−92) byaround one percent and declined by slightly less than three percent during the latter sub-period(1993−95) if we measure the changes as the unweighted average of employment growth rates
in 390 industries. The observation of such a mild employment fluctuation, however, should beviewed rather as an artifact of aggregation. The employment in industries with their growth
rates one standard deviation above mean increased by more than 26 percent during 1988−92,
while industries whose employment change rates lied one standard deviation below averageexperienced employment shrinkage of nearly twenty percent during 1992−95. Such a large
variation in employment growth is a good illustration of substantial inter-industry heterogeneityin many variables. In sum, as the figures in the table do demonstrate such wide variability
across industries during the same period, we must control for various industry-specific factors
in investigating labor demand.

10

The names and SIC codes of the four-digit industries with maximal and minimal importpenetration ratio are not shown in the table to save space, but are available upon request by theauthor.
7

III. MODEL AND SPECIFICATIONThis section aims to set out a simple theoretical framework and to discuss the methods
for estimation. First, the supply-side of the industry i (i=1, 2, …, N) at time t (t=1, 2, …, T)
can be summarized by the following standard cost function:

Cit = φit witγ 1 +1 c itγ 2 Qit(1),where w, c, and Q denote wage, non-labor input costs, and output quantity, respectively. The
factor markets are assumed to be perfectly competitive. Other cost shifters are captured by φ.
We naturally assume 0 < γ 1 + 1 < 1, 0 < γ 2 < 1 . By Shephard’s lemma, the labor demand isderived, suppressing the subscripts, as following;L=∂C= φ(γ 1 + 1) wγ 1 cγ 2 Q .
∂w(2)Next, consider the demand-side of the industry by introducing the following standard
demand function for the output: p 
Qi = A i*  epi 

−θ

y γ3

(3)

,with p i , pi* , y denoting the price of the i- th product which is supplied by the domestic
industry, the price of imported i-th product, and domestic income, respectively. All the8variables except for the import price p* are denominated in terms of home-country’s currency(yen, in the case of Japan), while p* is expressed in source-country’s currency ($, say). The
nominal exchange rate (¥/$, say) is referred to as e. We assume that the product produced in
the home country is an imperfect substitute for the imported product.11 Other factors shifting
demand are expressed by the term A. Both θ and γ3 are naturally assumed positive.
By plugging (3) into (2) and by replacing the endogenous own output price, we canderive the following labor demand function in the first-differenced logarithm form:

d ln L = δ0 + δ1 d ln w + δ2 d ln c + δ3 d ln y + θd ln ep * +ε(4),where ε denotes the error term with usual properties. The coefficient on wage, δ 1, should be
negative in the labor demand function. We expect the positive sign for the coefficient on theimport price, θ, since the import price fall intensifies competition and thus reduces demand forlabor in domestic industries. The estimate of the employment elasticity with respect to theimport price, θ, is the main target of this paper.
In addition to (4), the following specification that includes the interactive term of importprice with the import share MS will also be estimatedd ln L = δ0 + δ1 d ln w + δ2 d ln c + δ3 d ln y + θ0 d ln ep * +θ1 MSd ln ep * +ε

11

(5)

In evaluating the impact of imports on employment, this paper concentrates on the directcompetition between final products which are substitutes. It is true that import penetration also
affects employment through imported inputs into production. Analyzing these two effects within thesame model, however, is empirically difficult because both are often highly correlated and difficult
to distinguish without extensive dependence on input-output tables. Campa and Goldberg (1998)
limited themselves to the latter channel, although they distinguish two routes in their theoreticalmodel.
9because the sensitivity of employment to imports is likely to vary positively with the industry’s
exposure to imports. Naturally, we expect θ1 as well as θ0 be positive. Using the estimates, we
can calculate the industry-specific employment elasticity of the i-th industry θibyθi = θ0 + θ1 MS i .
In estimating the above equations (4) and (5), we will assign instrumental variables (IV)to the wage, to the import price and to the import share because all these variables aresupposed to be endogenously determined.12 The OLS estimation treating these variables as
exogenous will yield biased and inconsistent estimates. We will check this point by comparing
the result of IV estimation with that of OLS.

IV. EMPIRICAL RESULTS
The specifications derived in the previous section are adapted to the following empiricalcounterpart, taking account of the availability of data and the fitness of the model:

d ln Lit = αi + θ0 d ln Pitm + θ1 MS it d ln Pitm + βd ln wit + λd ln Li , t −1
+ γ 0 d ln cit + γ1 d ln ci ,t −1 + εit(6),where Pm denotes the import price in terms of domestic currency, yen. As in Revenga (1992),
the import price data employed here are actual transaction prices of importers derived from
WPI statistics, instead of the unit value indices.13 In calculating the import share, MS, of every

12

Dekle (1998) is the most closely related research with this paper in estimating the labor demand
function, since many other previous studies such as Burgess and Knetter (1998) and Revenga(1992) estimated the reduced-form equation derived from interaction with the labor supply function.
While he assigns instrumental variables to wage, Dekle (1998) differs from this paper in treating
import price and import share as exogenous.
13
The most closely corresponding category in WPI is assigned to each SIC industry. No
imputation was used. The concordance table is available upon request by the author.
10

four-digit industry, this paper utilizes the data concordance by Tomiura and Uchida (2001),
which combines import statistics and Annual Survey of Manufacturers.14 All other data areconsistently drawn from Annual Survey of Manufacturers.15 Price series are deflated.16
Similarly in Dekle (1998), the lagged employment is introduced to capture the effect of
employment adjustment costs. All the variables included in the regression (6) areindustry-specific. 17 The industry-specific dummy variables, α i, are included, while theyear-specific dummies are omitted just to improve the fitness.18 Let us turn next to theempirical results.
Table III presents the main estimation results.19 In all six specifications reported here,
the fixed-effect model (FE) is chosen as the Hausman specification test shows that the null
hypothesis of the random effect orthogonal to the explanatory variables is rejected at any
conventional confidence levels. The test statistics are reported in the table in the row headedby χ 2 .

14

We also calculated the import share in terms of deflated real values, but the ratio barely differsfrom the nominal ratio.
15
The wage is defined as the real average wage calculated as the deflated total wage payment
divided by the number of employees. The employment in this paper is measured in terms of thenumber of employees, not the total man-hours of work. Although it is due to the data limitation in
Annual Survey of Manufacturers, this choice does not seems to affect the main conclusion of thispaper since Rebick (1999) found that these two measures result in virtually the same estimates in
his model of the trade impact on Japanese wage differentials. The material and energy expenses areused as the non-labor costs.
16
The import price is deflated by aggregate domestic WPI, while the wage is deflated by aggregate
CPI.
17 As in Dekle (1998), the income variable, y, is omitted since real GDP turned out to be
insignificant and appears an incorrect proxy for business cycles in this context.
18
The dummy identifying two-digit sector is not included since variability within two-digit sector islarge.
19
The instruments for the wage variable are own one-period lag, current and one-period lagged
non-labor cost, and current and one-period lagged alternative wages. We choose wages in service
sector and in construction sector as the alternative wages. The data for these alternative wages arefrom Ministry of Labor Statistics. The instrumental variables assigned to the import price are own
one-period lag, current and one-period lagged real effective exchange rate of the yen (drawn fromIMF-IFS). The instruments for the import share interacted with the import price (first-differenced
logarithm) are own one-period lag, one-period lagged non-labor cost, and current and one-period
lagged real GDP (drawn from National Account by Economic Planning Agency).
11

The sign of wage coefficient β is significantly negative, as is appropriate in labordemand function, in all specifications using the instrumental variables (IV) (1) to (5). The OLS
estimation, which treats wage as exogenous, reported in the column (6), on the other hand,yields a quite different, wrong result, which shows that the wage is positively related to labordemand. This finding of importance of instrumenting the wage variable confirms the previous
result by Dekle (1998). The non-labor input cost factors are significant in all specifications.
The lagged employment is also strongly significant, suggesting that labor adjustment costs inJapanese manufacturing are substantial. This observation of sluggish labor adjustment due toadjustment costs appears consistent with existing evidence on Japanese employment. All thecoefficient estimates of these variables are quite similar and relatively robust to specification
changes across (1) to (5).
The coefficient on the import price, θ0, is significantly positive in all cases. The findingof the significant employment sensitivity to imports contrasts with the results from someprevious studies since they reported no discernible effect of imports on Japanese employment(Brunello (1990), for example).20 The finding of this paper, together especially with Dekle(1998), cast doubt on conventional wisdom that Japanese employment is isolated frominternational competition.
The import price interacted with import share, θ1, is statistically significant in no
specification except for that shown in column (4), which excludes the import price term
without interaction. We will discuss this insignificance problem in the next paragraphs.
This paper further provides richer information by splitting the whole sample period

20

Burgess and Knetter (1998) conclude that Japanese employment is less responsive to theexchange rate changes in the cross-country comparison context. Tachibanaki et al. (1998) foundthat the total import impact on employment is small. Higuchi (1989) found that the yen appreciation
exerts a restraining impact on Japanese wages only for senior/middle-aged workers. Rebick (1999)
detected negligible effect of import share on employment and wage differentials in Japan.
12based on the phase of business cycle. The impact of imports on employment may differ
depending on the period, since our sample period of 1988-95 can be divided into thefollowing two sub-periods: the earlier years of boom with the real estate and stock bubble
during the relatively stable exchange rate and the later years of recession after the burst of the
bubble and yen appreciation. The sharp contrast between these two sub-periods is obvious,
for example, from the figures depicted in Table II. To control this difference within our sample
period, we introduce the period dummy, D, which takes the value one until 1992 and zeroafter 1993, defined based on the sign of average employment change. The dummy isinteracted with the import price and with the import price term interacted with import share as
follows.21

d ln Lit= αi + (θ0 + η0 D )d ln Pitm + (θ1 + η1 D)MS it d ln Pitm + βd ln wit + λd ln Li , t −1(7)

+ γ 0 d ln cit + γ 1 d ln ci , t −1 + εit

The estimation results with thus defined period dummy are reported in Table IV. As
were in the regressions without the dummy, instrumental variables are assigned and FE modelis used for estimating the panel data. The estimates of coefficients of explanatory variables not
linked with the dummy appear basically robust to this modification.
All the coefficients, especially for the latter sub-period, are precisely estimated. Whatshould be emphasized most in Table IV is the impressive contrast in the employment response
across different sub-periods. First, as the coefficients with the period dummy and those

21

Dekle (1998) included the year-specific dummies not interacted with import price, but a similar
specifications of the period dummy in our case yielded estimates with wrong sign for the importprice.
13

without it are almost canceled out, both the import price and the interactive term with importshare have virtually no impact on employment in the first sub-period, while they are significant
for the latter sub-period in all cases reported in the table. Second, the introduction of theperiod dummy makes the interaction term with import share, which was insignificant in theprevious estimation, now significant for the latter sub-period. Hence, the sensitivity of
employment to imports increases with the degree of exposure to imports in the industry.
Evaluated at the average import share of 11.4%, the implied employment elasticity withrespect to import price is around 0.72 to 0.77 for the latter sub-period. The estimates for thelatter sub-period also indicate that employment elasticity in an industry with a 27% importpenetration ratio (one standard deviation above the mean) is larger than one, i.e. around 1.2 to
1.7. Consequently, by comparing the estimates shown in two tables, we can interpret that therelatively low elasticity estimate without the period dummy, 0.1−0.2, is a composite of
substantially higher elasticity in recent years and nearly zero response in earlier years.
The estimates of employment elasticity with respect to import price obtained in thispaper are in a comparable range with previous results, for example, 0.4−1.7 by Dekle (1998)
from a similar model at the Japanese two-digit level.22 Yet none of the differences in estimatedvalues should be exaggerated. Considering differences in data employed in each research, weshould emphasize that the principal conclusion revealing significant impact of imports on
employment is shared and confirmed.23

22

Branson and Love (1988) reported employment elasticity for each 2-digit U.S. industry fromnearly zero to about 0.65. Campa and Goldberg (1998) concluded that a ten percent permanent
dollar appreciation reduces overtime employment by around 0.46 percent, based on 2-digit U.S. data.
Revenga (1992) found the U.S. elasticity estimate of 0.1−0.4 for the pooled 38 four-digit industries.
23
If there exists non-negligible employment adjustment across four-digit industries within two-digit
sector, we expect lower estimate of employment elasticity at more aggregate levels. The higher
estimate by Dekle (1988) at two-digit level seems at odd with this prediction, but four-digit
industry’s labor share changes within two-digit sector is mostly less than one percent in our sample.
Thus, the interpretation attributing the difference in estimates to the difference in aggregation levels
does not work here. Alternatively, one can possibly explain the gap by different data used for real14

As for the import share, we detect that the employment elasticity increases
significantly with the industry import share during the latter sub-period, but the existing
evidence on the relation with import share is mixed. For example, Campa and Goldberg(1997) and Dekle (1998) reported no significant effect of import share on employment
sensitivity at the two-digit data for the U.S. and for Japan, respectively. 24 On the other hand,using the four-digit data, Revenga (1992) found that the responsiveness of U.S. employment
to import price changes varies positively with the degree of import penetration in the industry. 25
Although far from the decisive argument, at least in our case, the comparison of Table IV with
Table III suggests that significant linkage with industry import share might have been obscuredby the insufficient control for the asymmetry in employment response. The strongly positive
relation of employment response with the import share in each industry also confirms, in ourcontext, that the simultaneous observation of employment decrease and falling import prices
during the same period is not a mere superficial coincidence.
The estimated magnitude of employment elasticity cannot be neglected also incomparison with average employment fluctuation in whole manufacturing in Japan. The
estimates in Table IV indicate that import price fall of around three percent, observed during
1992-95, must have reduced labor demand by more than two percent, evaluated at the meanand held other factors constant. Since the actual employment decrease is less than three
percent in terms of the average of 390 industries, substantial share of average employment

import price series. Dekle (1988) constructed it from weighted-average of foreign prices, while wederived it from WPI.
24
Rebick (1999) also reported that import share changes have no significant effect on employmentchanges in Japan, but his conclusion is based on a different approach.
25
Since all the cited studies concluding insignificant effect of import share are based on two-digit
data, the irrelevance of import share might be the artifact of aggregation. The estimates in Table III
show, however, that mere disaggregation does not alter the conclusion. Dekle (1998) refers toJapanese regulation and long-term employment practices as the causes isolating the employment
adjustment from industry’s exposure to imports. We tried the regressions including the dummy for
regulated industry, but they perform poorly.
15

decline can be accounted for by the intensified import competition during the latter sub-period.
Thus, this paper reveals the substantial impact of competitive pressure from imports on
Japanese employment, although international effects have often been neglected in Japan amid
the financial troubles after the burst of the bubble. Although the asymmetric employment
response could be consistent with sunk costs associated with hiring and firing, the explorationof exact causes of this asymmetry is beyond the scope of this paper and should be left for
future research.

V. CONCLUDING REMARKSThe impact of imports on labor demand in 390 Japanese manufacturing industries has
been investigated. By assigning instrumental variables both to wage and to import variables,and by splitting the sample period based on the phase of business cycle, this paper has
revealed that Japanese employment is significantly responsive to import price changes and thatthe employment sensitivity varies positively depending on the industry import share, especiallyduring the period of declining employment after the burst of the bubble with falling importprices.
A brief overview of basic statistics clearly indicates the needs to take account of theconsiderable variability among industries when we evaluate the employment response toimports. Therefore, compared with previous studies of Japanese data at the two-digit level,
this paper, which exploits the recently available four-digit longitudinal data, could be especiallymarked as a substantial improvement in controlling for industry-specific factors.

16

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Branson, William H. and Love, James P. (1988), U.S. manufacturing and the realexchange rate, in “Misalignment of Exchange Rates: Effects on Trade andIndustry” (R.C. Marston, Ed.), pp.241-275.
Brunello, Giorgio (1990), Real exchange rate variability and Japanese industrial
employment, J. Japan. Int. Econ. 4, 121-138.
Burgess, Simon M. and Knetter, Michael (1998), An international comparison of
employment adjustment to exchange rate fluctuations, Rev. Int. Econ. 6(1),151-163.
Campa, Jose Manuel and Goldberg, Linda S. (1998), “Employment versus wage
adjustment and the U.S. dollar,” NBER Working Paper 6749.
Dekle, Robert (1998), The yen and Japanese manufacturing employment, J. Int. Money
Finance 17, 785-801.
Feenstra, Robert C. (1996), “U.S. imports, 1972-1994: Data and concordances,” NBER
Working Paper 5515.
Higuchi, Yoshio (1989), Japan’s changing wage structure: The impact of internal factors
and international competition, J. Japan. Int. Econ. 3, 480-499.
Rebick, Marcus E. (1999), Trade and the wage structure in the presence of pricedifferentials in the product market: The Japanese labor market 1965-1990,
J. Japan. Int. Econ. 13, 22-43.
Revenga, Ana L. (1992), Exporting jobs? The impact of import competition on
employment and wages in U.S. manufacturing, Quart. J. Econ. 107, 255-284.

17

Tachibanaki, Toshiaki, Morikawa, Masayuki, and Nishimura, Taro (1998), Economic
development in Asian countries, and the effect of trade in Asia on employment
and wages in Japan, Asian Econ. J. 12(2), 123-151.
Tomiura, Eiichi and Uchida, Yukio (2001), “The impact of import competition on gross
job creation and destruction: A study based on Japanese import-industry dataconcordance,” Discussion Paper #01-DOF-36, Research Institute of Economy,
Trade and Industry.

18

TABLE I
IMPORT SHARE AND VARIABILITY WITHIN 2-DIGIT SECTOR

INDUSTRY
ELECTRIC MACHINERY (30)
GENERAL MACHINERY (29)
FOOD MANUFACTURING (12)TRANSPORT EQUIPMENT (31)
METAL PRODUCTS (28)PRINTING & PUBLISHING (19)
PLASTIC PRODUCTS (22)TEXTILE MILL PRODUCTS (15)CHEMICAL PRODUCTS (20)APPAREL & OTHER FABRICS (14)
CERAMIC, STONE & CLAY (25)
PULP & PAPER (18)
IRON & STEEL (26)
LUMBER & WOOD PRODUCTS (16)MISCELLANEOUS MANUFCT (34)
PRECISION INSTRUMENTS (32)FURNITURE & FIXTURES (17)NONFERROUS METALS (27)
RUBBER PRODUCTS (23)
BEVERAGE & TABACCO (13)
LEATHR & FUR PRODUCTS (24)
COAL & OIL PRODUCTS (21)
ORDNANCE (33)

MS
1988

1991

3.17
2.57
9.07
2.40
1.00
0.51
1.16
12.01
7.88
10.84
2.29
5.13
3.95
12.19
13.60
7.19
3.63
24.75
5.21
3.01
14.87
14.87
14.00

4.27
2.95
11.12
3.08
1.30
0.57
1.31
15.01
8.17
11.62
2.82
4.35
3.97
15.32
14.62
9.25
4.84
21.32
6.32
4.72
20.52
13.75
9.58

1995
7.78
3.44
11.56
3.50
1.66
0.65
1.88
24.70
8.42
17.15
2.88
5.45
3.92
18.93
16.84
14.60
6.70
20.95
8.12
4.68
30.46
10.15
7.34

Within-sector
St.Dev MAX
MIN
5.29
22.09
0.09
3.02
13.62
0.09
11.60
36.58
0.08
11.80
34.87
0.28
6.16
26.29
0.39
1.08
2.06
0.01
1.89
6.19
0.24
20.07
78.63
6.61
16.31
91.58
0.82
20.46
95.42
0.50
11.04
57.56
0.10
22.81
83.24
0.01
10.78
31.99
0.04
22.60
72.08
0.05
17.17
51.97
0.41
20.28
97.90
0.21
8.62
24.69
0.70
19.83
56.50
0.10
12.01
40.17
0.14
19.00
60.40
0.04
22.77
84.43
14.69
12.55
32.26
0.21
-------------(NOTE) The import share (MS) is measured in percentage. The standard deviation, maximum andminimum are defined for import share across four-digit industries within each two-digit sector at
1995. The ordnance industry (33) is composed of only one four-digit industry (3311). The number
in parentheses following the abbreviated industry name is the two-digit SIC code for corresponding
industry. The industries are arrayed in descending order of the number of employees at 1995.

19

TABLE II
SUMMARY STATISTICSEMPLOYMENTAVERAGE
St. DEVMAX
MINREAL WAGE
AVERAGE
St. DEVMAX
MIN
NON-LABOR COSTSAVERAGE
St. DEVMAX
MINREAL IMPORT PRICEAVERAGE
St. DEVMAX
MINIMPORT SHAREAVERAGE
St. DEVMAX
MIN

1988-92

1993-95

1.344224.7359397.0686−46.2277−2.8125
15.3695
181.6488−70.4602

2.11984.731631.1196−21.4884

0.94444.932142.4596−26.5324−0.2058
6.113137.3988−33.2886−0.6383
6.000037.2249−35.9442−0.8005
7.086726.2283−25.3685−3.23546.859029.8366−21.9187

10.3987
15.1508
97.39370.001311.4020
15.4568
96.2997
0.0057(NOTE) All the figures in Table II, except the import share, are percent change rates from theprevious year, while the import share is in absolute level (%). Each figure is expressed in terms of
average, over the years during the period, of the cross-section unweighted average (standard
deviation, maximum, or minimum) of 390 industries in each year.

20TABLE III
ESTIMATION RESULTS (WHOLE PERIOD)
RHS
variables/
Statistics(1) IV(2) IV(3) IV(4) IV(5) IV(6) OLSd ln Lt −1−0.308(0.022)−0.243(0.168)
-----

-----

d ln ct −1

-----

R2
χ2

0.163
37.085−0.308(0.022)−0.291(0.173)0.097(0.084)1.830(1.235)0.242(0.043)0.314(0.045)0.186
37.374−0.307(0.022)−0.304(0.173)0.175(0.065)-----d ln ct−0.316(0.022)−0.236(0.175)0.187(0.083)0.870(1.200)-----−0.313(0.021)
0.402(0.055)0.095(0.041)−0.546(0.177)0.242(0.043)0.290(0.044)0.205
39.116d ln wt
d ln Pt m
MS t d ln Pt m

0.250
(0.043)0.300(0.044)0.185
36.7712.727(0.964)0.241(0.043)0.325(0.044)0.186
38.544−0.089(0.179)0.117(0.087)1.137(1.286)0.321(0.045)0.300(0.047)0.116
4.2089(NOTES)
1.

The dependent variable is the first-differenced employment in the logarithm form ( d ln Lt )in all cases. The figures in parentheses are the standard errors. The columns (1) to (5) are theresults from the regressions assigning instrumental variables to wage, import price and importshare, while the column (6) is from the regression treating these variables as exogenous.

2.

All the regressions employ the fixed-effect (FE) model for the longitudinal data. χ 2 is thetest statistics for the Hausman test of FE vs. RE models.

21

TABLE IV
ESTIMATION RESULTS (WITH PERIOD DUMMY)
RHS variables/
Statistic s(7) IV(8) IV(9) IV(10) IVd ln Lt −1−0.321(0.022)−0.419(0.171)-----d ln ct −1

-----

R2
χ2

0.175
38.026−0.321(0.022)−0.519(0.179)0.257(0.135)−0.264(0.134)4.389(1.646)−3.419(1.186)0.238(0.043)0.301(0.046)
0.196
38.546−0.314(0.022)−0.528(0.179)0.518(0.099)−0.499(0.109)-----d ln ct−0.330(0.0218)−0.509(0.181)0.453(0.133)−0.408(0.134)2.769(1.606)−2.690(1.196)-----d ln wt
d ln Pt m
Dt * d ln Pt m

MS t d ln Pt m
Dt * MS t d ln Pt m----0.240(0.043)0.278(0.044)0.193
37.288----6.322(1.196)−4.833(0.962)0.241(0.043)0.320(0.044)0.194
40.819(Note) The period dummy, D, takes one until 1992 and zero from 1993. The panel data is estimatedby FE model with instrumental variables in all cases. The notes to Table III apply to this table.

22