Product Switching and Firm Performance in Japan

September, 2009

Atsushi Kawakami(Gakushuin University)
Tsutomu Miyagawa(Gakushuin University, RIETI Faculty Fellow)

Abstract
Following Bernard, Redding and Schott (2009), we investigate product switching
behavior in Japanese manufacturing firms. Using the firm-commodity level database in The
Census of Manufactures, we find that product adding accounts for 21.4% and product dropping,
21.7% in all manufacturing shipments in 2000. Empirical studies that examine thedeterminants of product switching show that productivity and the relative size of the firm
encourage product switching, while high fixed costs discourage it. When we examine theeffects of product switching on a firm’s performance, only product dropping throughrestructuring contributes to improved performance such as growth in output, employment,labor productivity or TFP in the short run. However, product switching improves firm
performance in the long run.
Keywords: Firm dynamics, Product switching, Productivity, Barrier to entry
JEL Classification: D21, E23, L11, L60

1. Introduction
A number of papers in firm dynamics have focused on the effects of entry and exit
behavior on productivity growth at the firm and industry levels.1 Nishimura, Kiyota, andNakajima (2005), and Fukao and Kwon (2006) examined the effects of entry and exit behavior
on productivity growth at both the firm and industry levels in Japan. However, they found thatthe major factor in productivity growth at the industry level was not the entry or exit effect ,but
the within effect. In addition, the entry and exit rates in Japan were lower than those in otheradvanced countries.
From the above empirical results, we would expect that Japanese firms might have
improved productivity growth through product switching or industry switching. For example,
the main products for Toray Co. are now chemical products, while its main product was textile
products thirty years ago. The main product for Canon Co. is office machinery, while its main
product thirty years ago was the camera.
Bernard, Redding, and Schott (hereafter referred to BRS) (2009) developed a model
incorporating not only entry and exit behavior but also product switching behavior in incumbent
firms. Using the U.S. Manufacturing Censuses from 1972 to 1997, BRS examined how U.S.
firms changed their composition of products and how product switching affected firm
performance. In Swedish manufacturing firms, Greenaway, Gullstrand and Kneller (2008) foundthat the probability of firm exits caused by switching industries is higher in industries withknown comparative disadvantage. Chan and Chen (2005) and Newman, Rand and Trap (2007)
also examined industry switching behavior in manufacturing firms in Taiwan and Vietnam
respectively.
1

In line with this field of research, Jovanovic (1982) and Hopenhayn (1992) developed the theoretical foundations.

For empirical works, see Baily,, Hulten and Campbell (1992), Dunne, Roberts and Samuelson (1989a,b) and Foster
Haltiwanger and Krizan (2006).

Following BRS (2009), we examine the effect of product switching, industry switching andsector switching on firm performance, using the Manufacturing Survey in Japan. Our paper isconstructed as follows. In the next section, we outline BRS’s model that incorporates productswitching. In the third section, we explain our data in detail and define the terms ‘sector’,‘industry’, and ‘product’. In the fourth section, we describe product switching behavior inJapanese manufacturing firms from 1998 to 2005. In the fifth section, we examine why theyswitch products and how product switching affects firm performance. In the last section, wesummarize our study and discuss topics that remain to be explored.

2. Why do firms switch products?
Theoretical models incorporating entry and exit behavior were developed by
Jovanovic (1982) and Hopenhayn (1992). Melitz (2003) considered entry and exit behavior
under monopolistic competition and applied his model to international trade. However, theseprevious models assumed that changes in product variety were associated with firm entry andexit and did not consider product change in surviving firms.
BRS (2009) developed a model that incorporates not only entry and exit behavior but
also product switching behavior. They extended Melitz’s model into a two-sector model. Bothgoods are differentiated in each sector and consumed. Fixed costs are different between the two
sectors. In Melitz (2003), zero profit cutoff and free entry conditions determined entry and exit
behavior. In BRS (2009), in addition to these two conditions, the product indifference cutoff
condition determined product switching behavior.
Figure 1 describes entry, exit and product switching behavior in the BRS (2009)
model. π i (i=1,2) is the revenue function of sector i. It increases when the productivity level( ϕ i ) improves. As described in Figure 1, when fixed costs in sector 2 ( f 2 ) are higher than thatin sector 1 ( f1 ) and profit increases associated with productivity improvement in Sector 2 islarger than that in sector 1 (dπ 2 dπ 1>), product switching occurs. In Figure 1, firms produce
dϕ 2 dϕ1

product 1 in the range from ϕ * to ϕ * * . When the productivity level exceeds ϕ * * ,production in firms is switched from product 1 to product 2. In a general equilibrium framework,
BRS (2009) endogenized entry, exit and product switching behaviors and these behaviors are
determined by the fixed cost in each sector, variable production costs, and consumer preference.

(Place Figure 1 around here)

3. Data description
We use the Census of Manufactures conducted by Ministry of Economy, Trade,a dn
Industry (METI) to examine product switching behavior in the Japanese manufacturing industry.
This is because the survey contains both establishment-level data and firm-level data. The
Census of Manufactures is conducted annually, but it covers all Japanese manufacturing
establishments only for the years that end in 0, 3, 5, or 8. Although the survey was started in
1909, we can integrate establishment level data

into firm level data from the 1998 survey tostudy product switching as there is not sufficient data availability. Consequently, our study
focuses on product switching behavior based on 1998, 2000, 2003, and 2005 surveys. The data
in 2005 covers 498,923 establishments and valid questionnaires were received from 468,841
establishments (response rate is 94.2%).
The Census of Manufactures arranges the survey data by industry and commodity.2 We
match the two kinds of survey data by using establishment identity code, and integrate

2 Technically, the database consists of reports by “industry”, “commodity”, “city, town and village”, “industrial site
and water”, and “enterprise”. Enterprise-level data has been reported since 1997.

establishment data into firm level data by using the address, telephone number, and names offirms.
The Census of Manufactures consists of three types of surveys by size ofestablishment; Form A ( “Kou Hyou” in Japanese) is applied to establishments with 30 or more
employees, Form B (“Otsu Hyou” in Japanese) is applied to those with 4 to 29 employees, andForm C (“Hei Hyou” in Japanese) is applied to those with 4 or fewer employees. For our study,
we used the surveys in the first two forms.3 The number of establishments responding to thesurvey in year 2005 is 276,686 covering 55.45% of all Japanese manufacturing establishments.
The Census of Manufactures has information on the number of employees, raw material
costs, fuel and electricity costs, value of shipments of manufactured goods and tangible fixed
assets. Using this information, we measure multilateral TFP (total factor productivity) suggested
by Caves, Christensen and Diewert (1982), capital intensity, and PCM (price cost margins) at
the establishment level. 4 Because the product switching decision is made not at theestablishment but at the firm level, we integrate establishment-level TFP, capital intensity and
PCM into a firm-level measure weighted by the shipment value of each establishment thatbelongs to the firm, following BRS (2006, 2009).
BRS (2006, 2009) referred to two digit SIC categories as sectors, four-digit SIC
categories as industries, and six-digit SIC categories as products. Following them, we

define sectors, industries, and products using the Census of Manufactures.5 Table 1 shows anexample of sectors, industries, and products in The Cencuc of Manufacuturers in Japanaccording to BRS (2006).
3 Because we are not allowed to use Form C, it remains to be a problem that the firm that employs over 4 but

reduces employees to fewer than 4 in periods between t -1 and t are counted as an “exit firm”, and vice versa withentry.
4

The detailed calculation process is explained in Appendix A.
Industry classification in the Census of Manufactures follows Japan Standard Industry Classification (JSIC) in thecase of 2-digit and 4-digit levels. JSIC which started from 1949 is revised every five years. Every version of JSIC is
adjusted to adhere to the International Standard Industry Classification (ISIC). However, in the case of 6-digitclassification, the Census of Manufacturers adopts its own classification
5

(Place Table 1 around here)

Table 2 shows the share of products in an industry and product characteristics by sector.
We find the Japanese distribution of products is similar to the US. There are many kinds ofproducts in the food sector, the chemical products sector, the general machinery sector, and theelectric machinery sector. As seen in the US, we find the highest capital intensity in the coal andpetroleum products sector.

(Place Table 2 around here)

4. Product switching in Japanese manufacturing firms
Using the Census of Manufactures, we examine the firm and product dynamics ofJapanese manufacturing in the 1998-2005 period. Figure 2 shows the definition of entry and exit
behavior and product switching in our data. Firm entry and firm exit in traditional firm
dynamics are defined as follows in our data, “Firm exit” denotes a firm which exists atyear t and no longer exists in year t +j6, and a firm that does not exist at year t and enters themarket by year t +j is defined as a “firm entry“. Meanwhile, a product that a firm doesn’t
produce at year t and starts to produce by year t +j is defined as a “product add”, and a productthat a firm produces at year t but stops producing by year t +j is defined as “product drop”.

(Place Figure 2 around here)

6 In empirical analysis using the Census of Manufactures, the interval of t and t +j is inconsistent and thisinterval is two or three years because survey years are 1998, 2000, 2003 and 2005.

According to the above definitions, Table 3 describes the firm dynamics in Japanesemanufacturing industries. In Table 3, we find that the number of total firms decreased drasticallyin the 21st century due to the increase in exit firms and the decrease in entry firms. This decrease
was caused by the transfer of plants from Japan to overseas. However, the value of total
shipments in 2005 were maintained at the 2000 level, implying that firms stopped making
products that were less profitable and started to make new products that were more profitable.
Gross shipments of product adding accounted for 21.4% and product dropping accounted for
21.7% of total shipments of all Japanese manufacturing in the year 2000. These percentages arelarger than the percentages of entry and exit of firms. However, they were closing in by 2003.
When we compare shipment amounts per firm between a new product and a product drop, theformer is greater than the latter. When we compare shipment amounts per firm between an entry
firm and an exit firm, we also find the same phenomenon as before.

(Place Table 3 around here)

Following BRS (2006), we describe product switching behavior in Japanesemanufacturing firms from 1998 to 2005. Table 4 shows the prevalence of firms producing
multiple products, industries and sectors. We find that the share of single product firms in total
firms in Japan is 57%, which is similar to the corresponding share in the U.S. (59%). Likewise,
the share of firms producing multiple products in multiple sectors is 15% which is also similar
to the corresponding share in the U.S. (13%). Though the share of output in a single productfirms in the entire sample is 9% in the U.S. -- which is smaller than the corresponding share of
19% in Japan -- the distribution of the with-in firm output share in Japan is also similar to that in
the U.S. We also find that the distribution of the within firm output share in Japan shown inTable 5 is similar to that in the U.S.

(Place Table 4 and Table 5 around here)

In Table 6, we examine the output, employment, wages, probability of export, andlabor productivity between single-product and multi-product firms. We find that the output ofmulti-product firms is 59% higher than that of single product firms. Employment in
multi-product firms is also 29% higher than that in single-product firms. In contrast to the resultin the U.S., labor productivity in multi product-firms is 29% higher than that in single-productfirms in Japan.

(Place Table 6 around here)

We break down the total output growth in the manufacturing sector from 1998 to2005 into three factors; the firm’s entry and exit effects, its extensive margins, and its intensive
margins (Table 7). Among these three factors, the firm’s extensive margins by product switching
are the major factors in total output growth. The net effects of the firm’s entry and exit on total
output growth are negative. We decompose output growth into three periods; from 1998 to 2000,
from 2000 to 2003, and the period from 2003 to 2005. In the first period, the Japanese economy
recovered from the financial crisis, but the financial institutions in Japan still held huge
non-performing loans. In the second period, the Japanese economy suffered from a depression
due to the burst of IT bubble in the U.S. In the last period, the Japanese economy recoveredagain due to increased exports. In the first two periods, entry and exit behavior and productswitching in the Japanese manufacturing firms were more active than those in the last period.

This implies that Japanese firms searched for their optimal product compositions throughrestructuring. After 2003, they tried to maintain their product mix.

(Place Table 7 around here)

Examining product switching behavior in detail in Table 8, the share of firms that did notchange their composition of products in Japan was 39% form 1998 to 2003, and 55% from 2000
to 2005. The share is larger than that in the U.S. (32%).7 In the case of output share of firmsthat did not change their product mix in Japan is also larger than the share in the U.S. These
results imply that Japanese manufacturing firms are more conservative than U.S. firms. In thecase of industry switching and sector switching, we also find that Japanese manufacturing firms
are more conservative than the U.S. firms.

(Place Table 8 around here)

5. Determinants of product switching and its effects on firm performance
In this section, we examine why firms switch products and how product switching affects
firm performance. Based on the theoretical model in BRS (2009), we estimate the following
equation.

(1)

PS t + j ,i = const. + α1 PROt ,i + α 2 PCM t ,i + α 3 RSIZEt ,i + α 4 ln( K t ,i / Lt ,i ) + et ,i

7 The comparison was not accurate because the period of measuring product switching is different between Japanand the U.S.

In Equation (1), PS t + j ,i represents a product switching dummy in firm i from t (1998,
2001,or 2003) to t +j (2001, 2003, or 2006). We consider three kinds of dummies; a dummy thatshows that firm i adds products, a dummy that shows that firm i drops products, and a dummythat shows that firms add and drop products.

PROt ,i represents productivity in firm i at t. We create two types of productivity
measures; TFP and labor productivity. In BRS (2009), when the productivity in a firm increases,
it is easy for the firm to enter the market and to switch product. Then, α 1 is positive when afirm adds product, and vice versa. However, as the productivity is endogenously determined in
BRS (2009), we take a lag in PROt ,i in our estimation.

PCM t ,i represents the price cost margin in firm i that shows the competitive environmentof firm i. As Baldwin and Gorecki (1985) show that firm entry decreases and firm exit increases
when the market becomes more competitive, α 2 is positive when the product adding dummy
is a dependent variable, and α 2 is negative when the product dropping dummy is a dependent
variable.8
Capital intensity ( ln(K t ,i) ) shows fixed costs when a firm enters a market or switches
Lt .i

products. In BRS (2009), the increase in fixed entry costs makes firm entry difficult and productswitching in incumbent firms easy. On the other hand, the increase in fixed switching costs
makes product switching in incumbent firms difficult. We expect that the increase in capitalintensity in an incumbent firm protects firm entry and makes product switching difficult. We
include relative firm size ( RSIZE t ) measured by employment as a scale measure in ourestimation.
We estimate Equation (1) by probit estimation with sector and year dummies. Estimation
8

The construction of TFP and price cost margin is described in Appendix A1.

results are shown in Table 9-1, 9-2, and 9-3. In Table 9-1, both productivity measures are
positive and significant.

This implies that the increase in productivity encourages productadding. However, coefficients in price cost margin are negative in contrast to our hypothesis.
The result implies that a firm looks for new products to make when the firm marks low returns.
However, an alternative interpretation is possible. Price cost margins are equal to fixed costs
under the zero profit condition in the model in BRS (2009). Therefore, the low price cost marginmeans low fixed costs that encourage firms to enter the market or add new products. The signs
in capital intensity are negative. The result implies that high capital intensity in incumbent firms
prevents product adding as we expected..

(Place Table 9-1around here)

In Table 9-2, coefficients in both productivity measures are positive and significant, whichis inconsistent with our hypothesis -- firms with good performance are aggressive in exiting or
product dropping. However, the result is consistent with Nishimura, Kiyota, and Nakajima(2005) and Fukao and Kwon (2006) who argued that relatively high performance firms exitedfrom the market in Japan. On the other hand, the negative sign in the price cost margin isconsistent with our hypothesis. The low price cost margin means intense competition
encourages firm exit or product dropping. The negative sign in the inverse Herfindahl index also
supports our hypothesis. As we expected, high capital intensity discourages firm exits or productdropping, because high fixed costs protect incumbent firms.

(Place Table 9-2 around here)

Table 9-3 shows the estimation results when we use the dummy that shows productadding and product dropping of a firm. Positive signs in both productivity measures imply thatfirms with high performance switch products aggressively. Negative signs in price cost margin
imply that intensely competitive environments encourage product switching. Negative signs ininverse Herfindahl index also support this argument. The coefficients in capital intensity areambiguous.

(Place Table 9-3 around here)

We also estimate the following equation to examine product switching behavior at theindustry level(2)

PSratet + j ,m = const. + β1ΔREGt ,m + β 2 PCM t ,m + β 3 Δyt ,m+ β 4 ln( K t ,m / Lt ,m ) + ut +1,m

In Equation (2), PSratet + j ,m denotes the product adding rate, entry rate, productdropping rate or exit rate in industry m during the period from t to t+j. The denominators of the
product adding and entry rates are the number of firms at t+j and of product dropping and exit
rates are the number of firms at t. Therefore, estimations of product adding and entry rate
explain how an industry is entered or products are added by the firms. ΔREGt ,m denotes thechange in regulation measure by industry compiled by the Cabinet Office, Government of Japan
from t to t+j. 9 A high value in REGt ,m implies that industry m is highly regulated.

Δyt ,m represents the growth rate in gross output in industry m in the sample period.
9 The levels of the regulation measure does not reflect the difference in market regulation by industry, because theindicator is normalized at 1 in 1995. Hence, we take change in the regulation measure as an independent variable.

Table 10-1 and 10-2 show the OLS regression results in Equation (2). The negative andsignificant signs in the regulation measure in Table 10-1 imply that the product adding rate or
entry rate decreases in a highly regulated industry. Monopolistic industries are difficult to not
only enter for new firms but also to add products by incumbent firms. In industries where highreturns are guaranteed, firm entry or product adding is not encouraged. In Table 10-2,
coefficients in ΔREG t ,m are negative and significant when the drop rate is a dependent
variable. As in Table 10-1, in industries where high returns are guaranteed, product dropping is
not encouraged. On the other hand, coefficients in ΔREG t ,mare positive and insignificant

when the exit rate is a dependent variable.

(Place Table 10-1 and 10-2 around here)

The coefficients in high capital intensity are negative and significant in all estimations inTable 10-1 and 10-2. The results imply that firms restrain product switching due to fixed highentry costs and fixed switching costs. Growth in gross output at the industry level stimulates
firm entry, product adding, or product dropping.
Finally, we examine the effects of product switching on firm performance by estimating
the following equation.

3(3)

FPt ,t + j ,i = const . + ∑ γ k PS t ,t + j ,k ,i + ε t + j ,t + j ,ik =1

In Equation (3), FPt ,t + j ,i denotes the change in firm performance of firm i from t to t+j.
We choose real gross output, number of employees, labor productivity and TFP as variables that

represent firm performance. PS t ,t + j ,i is the product switching dummy described in Equation(1).
Estimation results are shown in Table 11-1 and 11-2. In all estimations, product adding
significantly improves growth in output, employment, labor productivity, and TFP. On the other
hand, product dropping significantly decreases firm performance. When a firm adds and drops
products simultaneously, firm performance, with the exception of labor productivity, improves
significantly.
(Place Table 11-1 around here)

However, the above estimation results may include simultaneous bias. Therefore, wecreated another type of firm performance as an dependent variable: change in firm performance( FPt ,t + k ,i ) from 1998 (or 2001) to 2003 (or 2005). In Table 11-2, we estimate Equation (3)where FPt ,t + k ,i is a dependent variable. In this table, product switching contributes to output,
employment and labor productivity, and product dropping contributes to TFP. The result implies
that the selection of products through restructuring improves firm performance.

(Place Table 11-2 around here)

Our empirical studies on product switching are summarized as follows. Productivity
encourages product switching or exit behavior. Although the results that product dropping andfirm exit are stimulated in high productivity firms contradict our hypothesis, they are consistent
with the results by Nishimura, Kiyota, and Nakajima (2005) and Fukao and Kwon (2006). The
negative and significant coefficients in competition measures such as price cost margin and theinverse of the Herfindahl index imply that intense competition discourages product switching.
The increase in fixed costs represented by capital intensity restrains product switching behavior.
At industry level, product switching behavior is not stimulated in a highly regulated market.
When we examine the effects of product switching on firm performance, only productdropping through restructuring contributes to improved firm performance such as growth in
output, employment, labor productivity or TFP in the short run. However, product switching
improves firm performance in the long run.

6. Concluding Remarks
Following BRS (2009), we examined product switching behavior in Japanesemanufacturing firms. Using firm-commodity level data in The Census of Manufacturers, wefound the following results with respect to product switching in Japanese manufacturing firms.
(1) The prevalence of firms producing multiple products, industries and sectors and the
distribution of within firm output shares by product in Japan are similar to those in the U.S.
described in BRS (2006).
(2) Mean difference in labor productivity in Japanese manufacturing firms is higher than that of
U.S. manufacturing firms. The average growth in output from 1998 to 2005 is dominated by
the extensive margin in Japan, which is similar to the U.S.
(3) When we examine the determinants of product adding, product dropping and productswitching (product adding and dropping), we find that productivity encourages productadding, dropping and switching while fixed costs measured as capital intensity discourages
product switching (both product add and drop, and product dropping only), inversely, andencourages product adding only.
(4) At industry level data aggregated from firm level data in The Census of Manufactures, theestimation results show that a regulation measure protects not only entry but also productadding and dropping, and capital intensity discourages all activity of firm dynamics.
Moreover, consumer’s demand measured as the growth rate of market size stimulates firms
to switch their product and firm entry(5) When we examine the effects of product switching on firm performance, only productdropping through restructuring contributes to improving firm performance measured as
growth in output, employment, labor productivity or TFP in the short run. However, productswitching improves firm performance in the long run.
From these results, we find that lower entry costs stimulate product switching as well as
the entry of new firms. Deregulation is also an effective way to decrease entry costs. The
product switching rate of regulated industries is low. Otherwise, an expansion of the secondhand
market also decreases entry costs and encourages product switching. 10 In addition, theexpansion of finance from the government owned financial institutions to firms that diversify
their products is also helpful.
Our remaining tasks are as follows. First, in our study, we focus on only the domestic
market. Table 7 shows that the effects of product switching on output growth in the Japanesemanufacturing sector have been decreasing for years. The result suggests that many firms aretransferring their production plants abroad. As the plants transferred abroad are recognized to bea plant that has exited from the market, we should distinguish the plants which move abroadfrom plants that are simply exiting the market. Second, due to the limited availability of data,
we focus on the manufacturing sector. However, as Morikawa (2007) pointed out, firm
dynamics in the service sector may be more important than in the manufacturing sector when

10 Farinas and Ruano (2005) use the intensity of the second hand market as one of indexes of sunk cost. And theindex affects firm dynamics of Spanish manufacturing firms.

we consider low productivity growth in the Japanese economy.11 Thus, we need to apply ourwork to the Japanese services sector. Third, Toray co. and Canon co. might have succeeded in
product switching through huge R&D investments. When we consider the causality from R&D
investment to product switching, we may find an additional policy implication for encouraging
product switching.

11 Morikawa (2007) found that “level” of productivity in the Japanese services sector is not less than the
manufacturing sector from firm-level data.

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Table1. Example of Sectors, Industries and Products in The Census of Manufactures
Sector2-digit SIC

Industry
4-digit SIC

Product
6-digit SIC
181111 Gasoline
181112 Naphtha
181113 Jet fuel oil
181114 Kerosene
181115 Light oil
181116 Heavy fuel oil A

1811

Petroleum refining

181117 Heavy fuel oil B
181118 Heavy fuel oil C
181121 Lubricating oil, including grease
181122 Paraffin
181123 Asphalt
181124 Liquefied gas
181125 Stock oil for refining and mixing
181126 Petroleum gas

18

Manufacture of
Petroleum and Coal
Products

1821

Lubricating oils

182111Lubricating oils made of mineral, animal andvegetable oil purchased

1822

Greases182211

Greases made of mineral, animal andvegetable oil purchased

183111 Coke
1831

Coke

183112

Fuel gasses, including blast furnace gas
and coke oven gas

183113 Crude coal tar
183114 Pitch coke
1841

Paving materials

1891

Briquettes and briquette balls

1899

Miscellaneous petroleum
and coal products

Asphalt paving admixture and tar paving
184111 admixture, including asphalt block and tar
block
189111 Briquettes and briquette balls
189911 Recovered sulfur
189919 Miscellaneous petroleum and coal products

Note: The classification of these goods conforms to the Census of 2005. The Japan Standard Industrial Classification (4-digit SICs) was revised in
2002 and the 6-digit SICs were revised in 2001. For consistency, we converted the 2002 revisions using the tool created by
METI(http://www.meti.go.jp/statistics/tyo/kougyo/gaiyo/sonota/bunrui/txt/h-cnv14.txt) and converted the 2001 revision numbers on our own.

Table2. Products per Industry and Product Characteristics by Sector

SectorIndustries

Products

Industries/Products

Goods
Shipments(million yen)

Number of
Employees

Shipments
per Employee(million yen)

09 FOOD

40

95

2.38

22,677,541

1,104,292

20.54

10 BEVERAGES, TOBACCO AND FEED

13

28

2.15

9,665,997

103,010

93.84

11

TEXTILE MILL PRODUCTS, EXCEPT APPAREL AND OTHER FINISHEDPRODUCTS MADE FROM FABRICS AND SIMILAR MATERIALS

39

114

2.92

2,231,736

136,425

16.36

12

APPAREL AND OTHER FINISHED PRODUCTS MADE FROM FABRICS AND
SIMILAR MATERIALS

32

72

2.25

2,108,709

243,927

8.64

20

37

1.85

2,497,913

126,404

19.76

13 LUMBER AND WOOD PRODUCTS, EXCEPT FURNITURE
14 FURNITURE AND FIXTURES

10

21

2.10

2,161,703

129,238

16.73

15 PULP, PAPER AND PAPER PRODUCTS

19

59

3.11

7,089,182

210,460

33.68

16 PRINTING AND ALLIED INDUSTRIES

5

9

1.80

6,945,444

340,890

20.37

17 CHEMICAL AND ALLIED PRODUCTS

40

214

5.35

25,027,125

342,48173.08

18 PETROLEUM AND COAL PRODUCTS

7

24

3.43

13,429,286

23,824563.6919 PLASTIC PRODUCTS, EXCEPT OTHERWISE CLASSIFIED

23

43

1.87

10,905,871

436,897

24.96

20 RUBBER PRODUCTS

13

41

3.15

3,098,894

124,613

24.87

21 LEATHER TANNING, LEATHER PRODUCTS AND FUR SKINS

10

34

3.40

477,770

31,972

14.94

22 CERAMIC, STONE AND CLAY PRODUCTS

49

112

2.29

7,480,109

293,013

25.53

23 IRON AND STEEL

23

65

2.83

16,896,431

213,056

79.31

24 NON-FERROUS METALS AND PRODUCTS

20

56

2.80

6,711,626

132,753

50.56

25 FABRICATED METAL PRODUCTS

31

104

3.35

14,015,901

657,94221.30

26 GENERAL MACHINERY

47

236

5.02

31,210,883

983,449

31.74

27 ELECTRICAL MACHINERY, EQUIPMENT AND SUPPLIES

24

114

4.75

18,812,387

559,413

33.63

28 INFORMATION AND COMMUNICATION ELECTRONICS EQUIPMENT

11

52

4.73

11,534,270

205,33156.17

29 ELECTRONIC PARTS AND DEVICES

9

41

4.56

18,720,153

492,51238.01

30 TRANSPORTATION EQUIPMENT

16

77

4.81

53,999,911

944,35257.18

31 PRECISION INSTRUMENTS AND MACHINERY

22

62

2.82

3,784,716

151,18825.03

32 MISCELLANEOUS MANUFACTURING INDUSTRIES

37

102

2.76

4,316,743

171,922

25.11

Note: These figures were calculated using the industry data in the 2005 Census

Table3. Composition of Total Shipment into Firm Dynamics

Year

Total ProductsContinuing
Products
from t-1

Continuing
Products
to t+1

Products
Added

Products
Dropped

Entry
Firms

Exit Firms(billions of yen)
1998

279.7

2000

291.2

191.2

191.5
173.2

62.4

63.2

59.4
37.6

54.8

2003

272.3

177.8

196.5

46.6

39.2

47.9

36.6

2005

294.3

229.9

1998

100.0

2000

100.0

65.7

59.5

21.4

21.7

12.9

18.8

2003

100.0

65.3

72.2

17.1

14.4

17.6

13.5

2005

100.0

78.1

38.3

28.8

26.2

(%)
68.5

21.2

13.0

10.3

8.9

Table4. Prevalence of Firms Producing Multiple Products, Industries and Sectors

Japan(2005)

U.S.
(1972-1997)

type of Firm

Percent of Firms

Percent of Output

Mean Products,
Industries or Sectors
per Firm

Single-Product

60

21

1.0

Multiple-Product

40

79

2.8

Multiple-Industry

26

71

2.6

Multiple-Sector

13

53

2.3

Single-Product

59

9

1.0

Multiple-Product

41

91

4.0

Multiple-Industry

29

87

3.1

Multiple-Sector

13

76

2.5

Note: Results for the US (1972-1997) are figures from BRS (2006). The third and fourth columns show the distribution of firms producing
single or multiple products, and firms in multiple industries and sectors, and their output (shipment value). The fifth column shows themean number of products produced, industries and sectors of firms in multiple industries and sectors.

Table5. Distribution of Within-Firm Output Shares, by Product

Number of Products

Average Share of
Products in Output of Firms

1
2
3
4
5
6
7
8
9
10

1

2

3

4

5

6

7

8

9

10

100.0

78.4

67.2

58.7

55.0

51.8

54.2

47.6

45.2

46.3

22.0

24.2

24.8

24.2

23.3

22.1

21.7

21.9

22.5

9.5

12.2

13.0

13.1

12.5

13.3

14.0

13.0

5.5

6.8

7.7

7.6

8.5

9.0

8.1

3.0

4.3

4.7

5.4

5.9

5.4

2.2

2.6

3.2

3.7

3.9

1.1

1.9

2.4

2.7

0.9

1.3

1.6

0.6

0.9
0.4

Table6. Mean differences in some measures in Multiple Product, Multiple Industry and Multiple Sector firms.

Multipleproduct

Multipleindustry

Multiple
sectorReal Output

0.515

0.573

0.632

Employment

0.380

0.492

0.592

Wage per Employment-0.374-0.470-0.564

Labor Productivity

0.223

0.222

0.238

TFP

0.010

0.011

0.012

Note: We calculate the mean percentage differences of these firm measures in 2005 between single andmultiple product firms, and multiple industry and sector firms with firm fixed effect. We use dependent
variables except the TFP logarithm or employment into independent variables for the estimation of TFP. All
differences are significant at the 1% level.

Table7. Breakdown of Total Shipment Growth

Extensive Margins

Firm Entry and Exit

Aggregate
GrowthNet

Added
Products

DroppedProducts

Net

Firm Entry

Firm Exit

Intensive
Margins

1998-2005

14.7

-14.5

147.3

161.8

-8.6

111.6

120.3

37.8

1998-2000

11.5

3.0

62.4

59.4

8.8

37.6

28.8

-0.2

2003-2000

-18.9

-16.6

46.6

63.2

-6.9

47.9

54.8

4.6

2003-2005

22.1

-0.9

38.3

39.2

-10.5

26.2

36.6

33.4

1998-2005

100.0

-98.9

1005.11104.0

-58.8

762.0

820.8

257.7

Year
(billions of yen)(%)

Table8. Product Switching between Single and Multiple Product Firms in Japan

Japan(98-03)
All Firms

Percent ofFirms (%)

Shipment
Weighted
Percent ofFirms (%)

U.S.

Japan(00-05)

SingleProduct Firms

MultipleProduct Firms

All Firms

SingleProduct Firms

MultipleProduct Firms

All Firms

SingleProduct Firms

MultipleProduct Firms

None

39

67

25

55

70

34

32

46

11

Add Product(s) Only

7

10

6

8

9

7

11

13

8

Drop Product(s) Only

14

n.a.

20

9

n.a.

20

12

n.a.

30

Both Add nad Drop Products

40

23

48

28

21

40

45

41

50

None

22

67

11

26

70

14

7

49

3

Add Product(s) Only

7

14

6

7

12

6

5

20

3

Drop Product(s) Only

10

n.a.

12

12

n.a.

15

7

n.a.

8

Both Add nad Drop Products

60

18

72

55

17

65

81

31

86

Note: The summary for Japan shows surviving firms' switching behavior between 1998 and 2003. The summary in US is from BRS (2006) and it is aggregated surviving firms' switching profiles between from 1972 to1997.

Table9-1. Product Switching and Productivity, 1998-2005

Dependent Variable: Product Add Dummy t, t+j
marginal effect
PRO t(Total Factor Productivity)

marginal effectmarginal effect

0.00530.0273 ***0.0410 ***

0.84

4.12

6.09

PRO t
(Logarithm of Labor Productivity)

PCM t(Price Cost Margins)

marginal effectmarginal effectmarginal effect

0.0074 ***0.0109 ***

10.01

14.17

1.89

0.0018 *-0.0039 ***-0.0038 ***-0.0043 ***-0.0037 ***

-5.29

-4.98

-6.74

-4.93

lnKt/L t(Logarithm of Capital Intensity)

0.0011 *0.0012 *

1.82

1.86

0.0135 ***0.0144 ***0.0140 ***0.0123 ***0.0118 ***0.0122 ***(Relative Firm Size)

22.23

22.95

22.10

22.88

22.26

22.10

sector dummy

Yes

Yes

Yes

Yes

Yes

Yes

year dummy

Yes

Yes

Yes

Yes

Yes

Yes

Observations

709514709514578013709514709514578013R-squared

0.05000.05090.04900.0501

0.0511

0.0489Chi-squared

44265.20

44383.9935173.05

44331.2244607.32

35208.57

p-value

0.00000.00000.00000.00000.00000.0000

RSIZE tNote: The table summarizes the probit estimation results of the firm level product switching indicator on the firm's productivity. PCM, capital intensity and firm
relative size. We use firm-level sector dummy variables as control variables. The value below each coefficient. ***, **and * are statistical ssignificant at the 1%,
5% and 10% levels.

Table9-2. Product Switching and Productivity, 1998-2005 (continued)

Dependent Variable Product Drop Dummy t, t+j

PRO t(Total Factor Productivity)

marginal effectmarginal effectmarginal effect0.0827 ***0.0840 ***0.0983 ***

12.46

12.64

14.78

PRO t
(Logarithm of Labor Productivity)

PCM t(Price Cost Margins)

marginal effectmarginal effectmarginal effect

0.0129 ***0.0131 ***0.0076 ***

19.11

19.45

9.29

-0.0001 ***-0.0001 ***-0.0001 ***-0.0001 ***

-3.84

-3.87

-4.00

-3.79

lnKt/L t(Logarithm of Capital Intensity)-0.0014 **-0.0016 ***

-2.45

-2.71

0.0156 ***0.0157 ***0.0153 ***0.0111 ***0.0111 ***0.0111 ***(Relative Firm Size)

16.88

16.88

16.58

18.00

17.98

17.56

sector dummy

Yes

Yes

Yes

Yes

Yes

Yes

year dummy

Yes

Yes

Yes

Yes

Yes

Yes

Observations

709514709514578013709514709514578013R-squared

0.03980.03980.03830.04000.04000.0380Chi-squared

30700.61

30711.16

24353.43

31265.28

31290.94

24530.66

p-value

0.00000.00000.00000.00000.00000.0000

RSIZE tNote: See the note in Table 9-1.

Table9-3. Product Switching and Productivity, 1998-2005 (continued)

Dependent Variable: Both Product Add and Drop Dummy t, t+j

PRO t(Total Factor Productivity)

marginal effectmarginal effectmarginal effect0.0933 ***0.0949 ***0.1068 ***

16.35

16.64

18.43

PRO t
(Logarithm of Labor Productivity)

PCM t(Price Cost Margins)

marginal effectmarginal effectmarginal effect

0.0054 ***0.0056 ***0.0009

8.63

9.01

1.11

-0.0001 ***-0.0001 ***-0.0001 ***-0.0001 ***

-4.00

-4.07

-4.00

-3.92

lnKt/L t(Logarithm of Capital Intensity)-0.0015 ***-0.0009 *

-2.80

-1.77

0.0114 ***0.0115 ***0.0114 ***0.0079 ***0.0079 ***0.0081 ***(Relative Firm Size)

17.30

17.31

16.99

17.11

17.08

16.83

sector dummy

Yes

Yes

Yes

Yes

Yes

Yes

year dummy

Yes

Yes

Yes

Yes

Yes

Yes

Observations

709514709514578013709514709514578013R-squared

0.04690.04690.0451

0.04650.04660.0445Chi-squared

32977.20

33000.19

26286.1033081.19

33107.56

26208.20

p-value

0.00000.00000.00000.00000.00000.0000

RSIZE tNote: See the note in Table 9-1.

Table10-1. Estimation of Product Add and Firm Entry Rates and Industry Characteristics using Industry-Level Data

Add Rate t-j, t⊿REG t-j, t(Regulation)ln(K/L) t-j
ogarithm of Capital Intensity)⊿lnY t-j, t(Growth of Market Size)coefficietnt

coefficietnt

coefficietnt-0.2442 ***-0.2552 ***-0.0129 ***-0.0078 **

-5.53

-5.09

-3.39

-2.01

-0.0211 ***-0.0217 ***-0.0037 *-0.0074 ***

-3.87

-3.42

-1.77

-3.30

0.1179 ***0.1428 ***0.0179 **0.0158 *

6.24

5.74

2.45

1.79

PCM t-j(Price Cost Margins)constant
Year Dummy

Entry Rate t-j, tcoefficietnt-0.0108 **-0.0028

-1.98

-1.46

0.4596 ***0.3955 ***0.1423 ***0.1462 ***

14.35

10.76

11.69

11.23

Yes

Yes

Observations

1614

1145

1618

1149

R-squared

0.15010.17260.07780.1009F-value

56.7989

39.5715

27.1987

21.3664p-value

0.00000.00000.00000.0000

Table10-2. Estimation of Product Drop and Firm Exit Rates and Industry Characteristics using Industry-Level Data

Drop Rate t-j, t⊿REG t-j, t(Regulation)ln(K/L) t-j
ogarithm of Capital Intensity)⊿lnY t-j, t(Growth of Market Size)coefficietnt

coefficietnt

coefficietnt

coefficietnt-0.2310 ***-0.2505 ***-0.0156

0.0059

-5.07

-4.88

-0.68

0.24

-0.0280 ***-0.0335 ***-0.0417 ***-0.0454 ***

-4.13

-4.25

-12.37-12.040.0981 ***0.1534 ***-0.0915 ***-0.0936 ***

3.96

5.04

-7.31

-6.32

-0.0191 ***PCM t-j(Price Cost Margins)constant

Exit Rate t-j, t-0.0044-2.77
0.3890 ***0.4028 ***-1.31
0.4135 ***0.4293 ***

9.80

8.79

20.97

19.61

Year Dummy

Yes

Yes

Yes

Yes

Observations

1076

754

1079

756

R-squared

0.21580.26170.23500.2858F-value

73.699353.0272

82.498660.0309

p-value

0.00000.00000.00000.0000Table11-1. Product Switching and Change in Firm Performance⊿lnYt, t+j⊿lnLt, t+j⊿lnLPt, t+j⊿TFPt, t+j

coefficient

coefficient

coefficient

coefficient

0.0187 ***0.0009 **

13.50

7.24

2.34

-0.0256 ***-0.0164 ***-0.0004-10.69

-9.34

-4.55

-0.76

0.0093 ***0.0047 ***0.00120.0008 **

3.42

2.61

0.46

2.26

Year dummy

Yes

Yes

Yes

Yes

Observations

706827703741703741706827R-squared

0.53090.42670.57970.5473F-value

11644.46

5459.65

18220.70

14773.12

p-value

0.00000.00000.00000.0000

Product Add Only t, t+j

Product Drop Only t, t+j

Product Add and Drop t, t+j

0.0494 ***0.0252 ***17.99-0.0428 ***Note: This table summarizes the results of fixed effect estimation with industry fixed effect. Each dependent variable isa logarithm of differences in a firm's performance between t-j and t, and a switching dummy indicates a product add (ordrop) between t-j and t. We use year dummy variables as control variables. The values below each coefficient are tvalues and ***, ** and * are statistically significant a the 1%, 5% and 10% levels.

Table11-2. Product Switching and Change in Firm Performance⊿lnYt, t+k⊿lnLt, t+k⊿lnLPt, t+k⊿TFPt, t+k

coefficient

coefficient

coefficient

coefficient

0.0102 **0.00410.0043-0.0019 ***

2.28

1.29

0.93

-2.96

0.0030-0.0008

0.00380.0012 *

0.63

-0.25

0.79

1.87

0.0150 ***0.0067 **0.0078 **-0.0014 **

3.96

2.54

2.01

-2.43

Year dummy

Yes

Yes

Yes

Yes

Observations

398965396290396290398965R-squared

0.63180.46830.62380.5633F-value

10847.97

4105.97

14306.47

8514.55

p-value

0.00000.00000.00000.0000

Product Add Only t, t+j

Product Drop Only t, t+j

Product Add and Drop t, t+j

Note: See the note of Table 11-1.

Figure1

π

π₂
π₁

0
-f₁

-f₂

ϕ*

ϕ**

Figure2. Definition of Product Switching Definition of Product Switching

Firm A
Firm Exit

Product a
Product b

Firm A
Firm Entry

Product a
Product b

Product
Add

Firm A

Firm A

Product a

Product a

Product b

Product b
Product c

Product
Drop

Firm A

Firm A

Product a

Product b

Product b