Silviase/jgov_v1.4_full_ann huggingface dataset:
However, higher concentration may induce restricted competition and market power, which lead to a firm’s less incentive to improve productivity and competitiveness due to the “quiet life.” This view has been emphasized by many industrial organization economists. Although the concentration-innovation relation is still an open, and controversial problem (see for example Peneder and Wörter [2013]), the negative effect of concentration on innovation was partially supported by the empirics-oriented inverted-U relationship hypothesis (for example Scherer and Ross [1990] and Aghion et al. [2005] as representative studies). It is because the argument suggests that in highly-concentrated industries, the intensity of R&D activities tends to decline.

Thus, it is important to look at the relationship between competition and international competitiveness. But, the existing studies have scarcely paid attention to the empirical examination of the problem in Japan, possibly due to limited availability of necessary statistical data. In reality, economic globalization and innovation are inducing dynamic competition in many industries. The analysis of the relationship is becoming more and more important.

Also, as suggested above, the empirical examination may involve the question of what more useful indicators measuring the intensity of competition are. Usually industrial organization literature has used industry concentration measures, such as n-firm concentration ratio (for the largest n firms) and Herfindahl-Hirschman Index. But it is well-known that those measures have qualifications. They are static, and ignore dynamics of market share and position, which may capture the competition intensity. Therefore, it is necessary to find an alternative or a complementary measurement. One of the alternative measures is market share mobility or change in leader in an industry.

One more competition factor is international pressures. As Gorodnichinko et al. [2010] suggest, it is likely to be an effective competition factor which forces firms to innovate more and improve themselves more. Then, the measurement of the intensity of international competitive pressures is a major issue as well.

Thus, various competition factors should be taken into examination. In this paper we have introduced not only concentration, but also other competition factors such as market share mobility and international pressure factors.

### I II. Empirical Analysis 1: Analysis of World Export Share

### 1. Indicators used

This study examines competitiveness through the presence of Japanese industries or firms in global markets, which is related to the second indicator earlier referred to. It is largely because it is possible to measure the presence from available data in Japan. The presence is equivalent to the degree of
“internationalization” of a firm or an industry.

Generally, as overseas operations of a firm consist of both exports and FDI, the measurement of competitiveness should include both the operations. Thus, as a measurement of competitiveness, it is desirable to employ world market share of a domestic firm or an industry in the world production or sales. But unfortunately, in Japan there is no available statistical data on foreign production at a firm or an industry level. $ ^{3} $ This paper alternately makes use of the share of Japanese exports in the world total exports at an industry level (hereafter world export share) because various business documents suggest that Japanese firms with larger exports tend to prefer FDI to more expanded exports. As a positive relation exists between foreign production and exports at an inter-industry level, world export share is likely to reflect approximately the whole overseas operations.

### 2. Prior studies

There is scarcely existing study examining the world export share, except Sakakibara and Porter [2001]. Their study analyzed the determinants of world export share in Japanese manufacturing industries over 1991 to 1993, taking into account some possible factors, including the intensity of competition. The share is the same with the definition used here.

The study introduced concentration ratio and market share mobility index referred to later to examine the influences of competition-related factors on world export share. The market share mobility may capture the intensity of competition because frequent or great changes in market share and position of leading firms usually mean fierce competition. The results suggest that concentration is not amongst the significant influences on world export share. But, market share mobility in a domestic market has a positive and significant effect, suggesting that fierce competition plays a significant role of enhancing firm competitiveness and then promoting exports, as competition is likely to promote X-efficiency and/or innovation.

However, though the results have interesting implications, the study has some qualifications. First of all, a measurement problem is picked up. The measures based on only direct exports from Japan may under-evaluate the presence or competitiveness. As mentioned above, nowadays firms tend to prefer FDI to exports as overseas operations (an export-substituting type of FDI). Also, firms frequently export products manufactured in a foreign country to another foreign countries (an export platform type of FDI), and also to Japan (an inverse import type of FDI). The measurement of industrial competitiveness should involve both overseas production and exports. Then, the better measure is, as indicated above, for example the ratio of foreign sales to total sales, which reflects
total net sales from both exports and overseas production. $ ^{4} $

Also, the period covered in the study is before the large-scale globalization took place. The relationship between competition and international competitiveness during the period of globalization is more interesting.

Second, it is not clear that the used mobility indicators are a sufficient measure. It is because market mobility may be measured by alternative indicators. Therefore, the finding should be confirmed by utilizing those alternative indicators.

Third, competition consists of foreign market pressures as well as domestic competition. Other competition factors like cartels also should be taken into account.

Finally, global competition may be an important determinant of the intensity of competition. For example, international oligopoly or world concentration is a candidate for possible relevant determinants. $ ^{5} $

### 3. Analytical design: estimated equation

The inter-industry and inter-temporal variations in world export share of a Japanese industry may be explained by the following linear-form model:

$$ \begin{aligned}W E S=\beta_{0}+\beta_{1}(H H I\mathrm{o r}C R)+\beta_{2}M M_{i}(i=1,2,3,4)+\beta_{3}F R+\beta_{4}E X+\beta_{5}I T R\\+\beta_{6}R D+\beta_{7}A D+\beta_{8}P R+\beta_{9}K L+\beta_{10}D G+\beta_{11}M A+\beta_{12}C T+\epsilon,\end{aligned} $$

where WES is world export share of an industry, $ MM_{i} $ is market mobility index of method $ i(i=1,2,3,4) $ , HHI is Herfindahl-Hirschman Index, CR is 3-firm concentration ratio, EX is export intensity, ITR is intra-industry trade ratio, DG is growth of domestic demand, FS is firm size ratio, RD is research and development (R&D) intensity, AD is advertising intensity, KL is capital labor ratio, and PR is processing intensity. Also, dummy variables are used to account for variation by mergers and cartels. MA is a merger dummy and takes 1 for industry with merger and 0 otherwise, and CT is a cartel dummy, and takes 1 for industry with cartel and 0 otherwise. $ \epsilon $ is the error term. $ \beta_{i}(i=0,1,\ldots,12) $ is regression coefficient. The variables all involve letter f (industry), which indexes observations by industry, but in the equation the industry index is omitted for simplicity.

A cross-sectional analysis has a qualification when changes over time are examined. Then, cross-sectional data are usually complemented with time dummy. We analyzed the determinants of each year’s share and also their 5-year average. The results were similar among those years, and
also to the results with the average share. In fact, world export share is very stable over the period in most of the used sample. Therefore, discussion here was based on the estimations with 5-year average.

The sample size was 85, based on the availability of data. The sample industries are mostly of 4-digit level of Japan Standard Industrial Classification (JSIC).

Most of the independent variables are assumed to be predetermined or exogenous. But, as some variables (mobility indices, R&D intensity, advertising intensity and merger dummy) cover the period 2004 to 2008 as well, the estimation may involve the reverse causality problem. R&D intensity and advertising intensity both do not vary much after 2000. And we assume, from statistical constraint, that both mobility indexes and merger dummy also do not change over the period. Therefore, the equation may be estimated as a single equation rather than as part of a simultaneous equation system. The equation was estimated by ordinary least squares (OLS).

### 4. Variable explanation

Next, we will explain the definitions of the variables in turn.

## (1) World export share (WES)

This is an average of the ratio of Japanese exports to world total exports over 2004 to 2008. It was computed based on the United Nations's International Trade Statistical Yearbook.

## (2) Concentration (HHI and CR)

Many existing studies suggest that, in industries with higher concentration, firms are likely to have a greater market power through implicit or explicit collusion. The finding suggests market power interpretation for two situations: the first “structural” relationship is that highly concentrated industries are characterized with skewness in firm size distribution biasing for larger firms; the second “behavioral” relationship implies that in those industries leading firms can take strategies of giving smaller firms disadvantages. In those situations, leading firms can exercise market power. In other words, in a highly-concentrated industry, leading firms can set prices at discretion and collusively without fearing counterattack or reaction from smaller firms. Restricted competition may induce less incentive of firms to improve competitiveness due to “quiet life.” Then, high concentration is expected to be negatively related to world export share $ (\beta_{1}<0) $ .

But, concentration also, as suggested earlier, may have an export-promoting effect because of oligopolistic strategic interaction. Then, concentration may be positively related to world export share $ (\beta_{1}>0) $ . In addition, the square of concentration was introduced to test for the inverted U-shaped relationship: as concentration increases, the share rises until the critical level of
concentration, and beyond the level declines.

Thus, concentration involves the three possibilities: competitive, cooperative and mixed patterns. It is difficult to predict the effect a-priori. We use two measures for concentration in 2003: Herfindahl-Hirschman Index and 3-firm concentration ratio (based on production). These are made from the Report by Enterprise, Census of Manufactures, compiled by the Ministry of Economy, Trade and Industry (METI).

## (3) Market mobility index $(MM_{i}, i = 1, 2, 3, 4)$

The intensity of competition may be captured not only by concentration, but also by firms' changes in market share. The changes in share and position consist of growth or decline of existing firms, new entry, exit and mergers. In particular, strategic interaction is worth noting because a firm's share and position are affected by the actions of competitors, and the firm is aware of their impacts. The situation may be captured by leading firms' changes in share and position, which are called market mobility.

So far several indicators for the market mobility have been suggested, but it is difficult to determine theoretically and empirically the best indicator among them a-priori. $ ^{6} $ We use the following four market mobility indices.

## 1 ) Relative mobility index( $ MM_{1} $ )

Doi [2001] proposed the relative mobility index defined as

$$ M M_{1}=\frac{\sum_{i}|S_{i1}-S_{i0}|+\sum_{j}E X_{j0}+\sum_{k}E N_{k1}}{\sum_{i}S_{i0}+\sum_{j}E X_{j0}}\times\frac{1}{2}(i+j=i+k=5) $$

where $ S_{it}(S_{i1}, S_{i0}) $ is market share in year t in which t = 1 if it is the final year and t = 0 if it is the initial year of sample periods of a firm i surviving through the sample periods (1994 to 2008), $ EX_{j0} $ is market share in the initial year of a firm j that existed in the initial year but was not within the top 5 in the final year, and $ EN_{k1} $ is market share in the final year of a firm k, which was not within the top 5 in the initial year, but was within the top 5 in the final year. And, the denominator is equivalent to cumulative concentration ratio of the 5 largest firms (5-firm concentration ratio) in the initial year. The magnitude of the index means the equivalent of percentage of the initial total market shares of top 5 firms that changed hands over the period.
## 2 ) Absolute instability index $ (MM_{2}) $

This measure is what Sakakibara and Porter [2001] used in their study. It is the sum of the absolute value of changes in share between year t and year t-1 (previous year) for the largest four firms divided by number of firms in computation multiplied by sample periods minus one:

$$ M M_{2}=\frac{\sum_{i}\sum_{t}\left|S_{i,t}-S_{i,t-1}\right|}{m\times n} $$

where $ S_{i,t} $ is market share in year t of a firm with rank i over period 1995 to 2008; m is 14, the total year of observations; and n is 4, the number of firms in the computation. This index shows an average absolute change in market share for a firm par year in the sample periods.

## 3 ) Absolute share change ( $ MM_{3} $ )

Izumida et al. [2004] used squared, not absolute, values of changes in shares. This measure is the sum of squared change in share of top 4 firms divided by m - 1, where m is the number of observation years.

$$ M M_{3}=\frac{\sum_{i}\sum_{t}\left(S_{i,t}-S_{i,t-1}\right)^{2}}{m-1} $$

## 4 ) Relative instability index ( $ MM_{4} $ )

This measure is the sum of the absolute value of changes in share between year t and year t-1 (previous year) divided by share in previous year t-1 for the largest four firms, and then further divided by $ m \times n $ . It also was used in Sakakibara and Porter [2001].

$$ M M_{4}=\frac{\sum_{i}\sum_{t}\left|S_{i,t}-S_{i,t-1}\right|/S_{i,t-1}}{m\times n} $$

where the variables are the same ones used for $ MM_{2} $ . This index is a relative measure of $ MM_{2} $ in the sense that while $ MM_{2} $ indicates an average absolute change in market share of one firm par year, $ MM_{4} $ indicates an absolute change in market share relative to previous year of one firm par year.

Thus, $ MM_{2} $ and $ MM_{3} $ are a measure of “absolute” change, while the remaining $ MM_{1} $ and $ MM_{4} $ are a “relative” measure in which absolute change is normalized by individual share at a previous year, or total share of relevant firms at an initial year. The above-mentioned examination suggests that these indices all are expected be positively related to world export share ( $ \beta_{2} > 0 $ ). Market
shares used to compute these indices are from Yano Research Institute’s Market Share in Japan over 1994 to 2008.

## (4) Firm size ratio (FR)

Major exporters in Japan are large firms, which account for a larger percent of aggregate exports (Doi [1991]). The finding suggests that firm size may have an influence on exports. To take into account this relation, size-related variable was introduced: the share of value of shipments by firms with over 300 employees in an industry value of shipments in 2003.

But, it should be noted that the ratio is share of firms with over the critical size of employees, not share of large firms. Firms with less than 300 employees are defined as “small and medium sized enterprise” (SME) by the government. Therefore, the ratio is equivalent to market share of non-SME firms. FR is expected to have a positive effect $ (\beta_{3} > 0) $ . The data source is the Report by Enterprise, Census of Manufacture.

## (5) Export intensity (EX) and intra-industry trade ratio (ITR)

Firms are subject to competitive pressure from exposure to global markets. Then, larger international competitive pressure may provide for firms larger competitiveness-improving incentives. The presence of international competitive pressure was measured as proxy by export intensity and intra-industry trade ratio.

These factors serve as degree of internationalization. Export intensity was measured by ratio of exports to domestic output in 2003. Intra-industry trade ratio was introduced as indicator measuring export competitiveness. The ratio is given by (exports - imports) / (exports + imports) in 2003, based on the Updated Input-Output Table. Usually in international economics the numerator of ITR is defined as the absolute value of differences between exports and imports. But, because our purpose for the use of ITR is to measure export competitiveness and international competitive pressure, we do not adopt the approach here, and the ratio takes values between one and minus one: one when there is no import, zero when exports are equal to imports, and minus one when there is no export. The closer it is to one, the higher the export competitiveness.

Also, these two ratios may be understood as reflecting international competitiveness because they pick up the weight of exports in production and foreign trade, respectively. Then, there may be a tautological relationship between world export share and these ratios.

## (6) R&D intensity (RD) and advertising intensity (AD)

Competitiveness may reflect the “specific advantage” of a firm. In particular, marketing and R&D supports are frequently required for overseas operation because they are useful to adapt existing products or processes, or to develop new products or production processes, and then to sell products
in foreign markets. RD is measured as a R&D expenditure as a proportion of output, and AD is measured as an advertising expenditure as a proportion of output, which were both computed from the Input-Output Table.

Thus, these variables are expected to have a positive relation to world export share $ (\beta_{6} > 0, \beta_{7} > 0) $ .

## (7) Processing intensity (PR) and capital intensity (KL)

In Japan the vertical relation-specific “integral” production system and skills (“suri-awase” in Japanese) - carriers of “codified knowledge” - have been emphasized as strength. This study introduced processing intensity, i.e., value added / value of shipment as a surrogate for the intensity of integral and skill system. Its data are from the Report by Industry, Census of Manufacture.

Also, capital-intensive production is likely to be highly efficient, which in turn leads to improved competitiveness. It is captured by capital-labor ratio, of which the measure was fixed assets per employee, similarly from the Report by Industry, Census of Manufacture.

These variables both are expected to have a positive relation to world export share $ \left(\beta_{8}>0,\beta_{9}>0\right) $ .

## (8) Domestic demand growth (DG)

Exports may be affected by domestic demand growth. For example, with stagnant demand, firms may have an incentive to export more to make up for falling domestic sales. But, the factor may have an inverse relationship to exports. With expanding domestic demand, firms have an incentive to improve efficiency or to innovate more to expand their shares in domestic markets, which leads to larger competitive advantage in international markets. Therefore, the factor has no definite effect on world export share $ \left(\beta_{10} \gtrless 0\right) $ .

Domestic demand growth was measured by the ratio of “apparent consumption” (output - exports + imports) in 2008 to in 2003, from the Input-Output Table.

## (9) Merger and cartel dummy variables(MD and CD)

Mergers and cartels may be related to the intensity of competition together with concentration and mobility: they may induce restricted competition, leading to reduced competitiveness. The dummy variables were used to account for “by market behavior” variations in cross-industry model. These variables were introduced only for the subsamples due to limited availability of necessary information.

MD is 1 for industry in which mergers took place during periods 1994-2008, and 0 otherwise, and CD is 1 for industry in which illegal cartels took place during periods 1994–2003, and 0
otherwise. $ ^{7} $ Those variables are based on Japan Fair Trade Commission’s Annual Reports of Hearing Decisions (various years) and Yano Research Institute’s Market Share in Japan.

The above explanations of those used variables are summarized in Table A1 in Appendix, their summary statistics are shown in Table 1, and Pearson correlations coefficients between the independent variables are given in Table A2 in Appendix. Although we earlier suggested the importance of world concentration, the factor is not included because unfortunately there is no available large-scale statistics on world concentration ratio. World concentration ratio is available only for some industries in Japan. In this paper, alternative approach was adopted later.

< Table 1 here>

### 5. Estimated Results

Now, we will show the regression results. The regression results for the full sample without mobility index and the subsample with mobility index are reported in Tables 2 (the full sample without mobility index) and 3 (the subsample with mobility index), respectively. $ ^{8} $ We will discuss them in turn.

This study includes many independent variables, which may cause multi-collinearity. We tested for the problem using variance inflation factors (VIF) to eliminate the risk of suppressor effects in multiple regression estimation. The VIF measures how much the variance of an estimated regression coefficient increases due to collinearity. The computed VIF indices here range from 1.58 to 3.39, which are sufficiently less than the usually used cutoff value of 10. Therefore, there is no serious bias in the results. The VIFs are reported at the bottom of the Tables.

## (1) Results from equations without mobility index

First, both Herfindahl-Hirschman Index (HHI) and 3-firm concentration (CR) have a positive sign and are not statistically significant, suggesting that concentration has no discernible effect on world market share. This result is inconsistent with the argument prevailing in the business world that higher concentration leads to greater international competitiveness captured by the share and with the hypothesis that higher concentration impedes competitiveness through restricted competition. In addition, to test for the non-linear relationship between competitiveness and concentration, the two measures' squared terms were introduced to the empirical model. The squared $ HHI\ (HHI^{2}) $ has