Silviase/jgov_v1.4_full_ann huggingface dataset:
advantage in international markets. Frequently user-oriented product innovations and improvements are said to be more important than process innovations and improvements in overseas markets and in particular in emerging markets. This result may be consistent with such argument.

Finally, capital intensity (KL) is of a negative sign and is insignificant. Therefore, capital-intensive industries are not necessarily competitive.

$$ $$

## (2) Results from equations with mobility index: mobility subsamples

Next, the findings from equations with mobility index will be discussed following Table 2-2. The available sample is limited to fifty-four industries due to the computability of mobility index.

First of all, all the four mobility indices $ (MM_{i}, i = 1, 2, 3, 4) $ have no statistical significance, with variation in sign. This result is inconsistent with Sakakibara and Porter's [2001] finding.

Second, among other competition-related factors, concentration (HHI) has no discernible effect. On the other hand, merger dummy (MD) has a negative and significant effect, suggesting that industries with mergers tend to have lower share. This finding is worth being noted.

Third, firm size ratio $ (FS) $ , domestic demand growth $ (DG) $ , export intensity $ (EX) $ and intra-industry trade ratio $ (ITR) $ are all positively related to world export share, similarly to the findings from equations without mobility index.

Fourth, R&D intensity $ (RD) $ and advertising intensity $ (AD) $ both have a negative sign and are not significant, though significant in some models. The result about the advertising may suggest that consumer goods industries have smaller world export share, because those industries tend to have a larger advertising intensity. The AD result may reflect that in Japan producer goods have a larger “comparative advantage” than consumer goods, because advertising intensity is likely to be larger in consumer-goods industries than in producer-goods industries. Thus, the result does not statistically support the hypotheses that in Japan R&D and advertising lead to larger specific advantage in international markets.

Finally, processing intensity (PR) and capital intensity (KL) have both no significant and robust result. The results are consistent with the previous estimations here.

### I V. Empirical Analysis 2: Analysis of Foreign Sales Ratio

The second analysis is on the determinants of foreign sales ratio at a firm level. The first analysis, as indicated earlier, does not include overseas production, which is likely to lead to underestimation of
overall overseas operations of an industry. But, unfortunately industry-level data of overseas production is not available in Japan. To fill the gap, this study analyzes foreign sales ratio at a firm level. Table 3 shows the summary statistics of the data in the analysis of foreign sales ratio.

### 1. Indicator used

The used indicator is foreign sales as percentage of total sales of a firm. Foreign sales include sales of foreign subsidiaries (net of internal transactions such as sales to parent companies) as well as exports from Japan. The 5-year average over 2004 to 2008 was computed from the Annual Securities Reports (consolidated base) of sample firms.

### 2. Prior studies

Foreign sales ratio at a firm level has not been examined except Grogaard et al. [2011]. The study utilized three indicators as intensity of overseas operations in Norwegian large firms: foreign sales as percentage of total sales, foreign employees as percentage of total employees, and the number of foreign subsidiaries. The first indicator is the same as the foreign sales ratio used in this study.

There is no variation on the results among the three measures of overseas operation. Concentration has no significant effect on overseas operations. On the other hand, R&D intensity has a positive and significant effect, leading to the conclusion that technological advantages are likely to contribute to international competitiveness. Also, firm size has a positive and significant effect.

Finally, the study interestingly suggests that diversification has a negative and significant effect. Diversified firms are less interested in overseas operations.

### 3. Analytical design: estimated equation and sample

The inter-firm variations in foreign sales ratio (FSR) may be explained by the following linear-form equation model:

$$ FSR=\alpha+\sum_{i}\beta_{i}\times(industry-level factors)+\sum_{j}\gamma_{j}\times(firm-level factors)+\eta $$

where the dependent variable FSR is foreign sales ratio; the industry-level factors include the variables used for the analysis of world export share; the firm-level factors are R&D intensity (fRD), selling and administrative intensity (fAD), firm growth rate (FG), and firm size (FS); $ \beta_{i} $ and $ \gamma_{j} $ are the parameters to be estimated, and $ \eta $ is the error term.
The equation was estimated for 143 firms without mobility index (the full sample), and for 85 firms with mobility indices (the mobility subsample). Smaller sample sizes for the latter analysis are entirely due to availability of mobility indexes. Those sample firms were selected following a given rule. The rule is that; 1) a firm is within the top 5 in an industry, and 2) its share of sales in a particular industry in the whole sales (i.e., specialization ratio) is larger than 60 percent. When a firm operates in multiple industries, combined specialization ratio was adopted which could capture total share of sales of particular relevant industries in its whole sales.

### 4. Variable explanation

Now, we will explain the definitions of the variables in turn (summarized in Table A1 in Appendix). Foreign sales ratio (FSR) is as defined above, and is computed as average ratio over 2004 to 2008 from the Annual Securities Reports of sample firms. Following the accounting standard in Japan, firms with foreign sales ratio of less than 10 percent are not forced to disclose foreign sales, indicating only that their ratio is less than the critical line. In order to take into examination this practice, based on the computed average ratio we define an ordered variable that takes a value of 1 to 5 in the following way: 1 for firms with $ FSR < 10\% $ , 2 for firms with $ 10 \leq FSR < 30\% $ , 3 for firms with $ 30 \leq FSR < 50\% $ , 4 for firms with $ 50 \leq FSR < 70\% $ , and 5 for firms with $ 70\% \leq FSR $ . Then, the ordered logit estimation was applied.

Next, industry-level factors are the same ones used in the world export share analysis. Therefore, the explanations are omitted here. But, we have a note: when a firm includes two and more fields, average values of the relevant fields were used.

Turning to the firm-level factors, firm R&D intensity (fRD) is computed as R&D expenditures / sales in 2003. Selling and administrative intensity (hereafter shortly called as managerial intensity. fAD) is measured by selling and administrative expenditures as percentage of sales in 2003. This factor was introduced for two reasons. First, as some firms do not publish advertising expenditures, we use this variable as a proxy for advertising intensity. Second, the variable may pick up its specific effects of “marketing and administrative capabilities” in a wider way than advertising effects. Firm growth rate (FG) is defined as sales in 2008 / sales in 2003. And, firm size is the logarithm of sales in 2003. These factors are made from the Annual Securities Reports of sample firms.

Table 3 gives the summary statistics of the variables in the analysis, and Table A3 in Appendix gives Pearson correlation coefficients between independent variables used here.

< Table 3 around here >
### 5. Estimated Results

Regressions are performed for both samples without mobility index (the full sample) and with mobility index (the mobility subsample). Estimated results are shown in Table 4-1 for the former, and in Table 4-2 for the latter.

## (1) Results from equations without mobility index: the full sample analysis

First, we look at the effects of industry factors. Industry concentration (HHI) has a positive and significant effect in all the equations without the quadratic term of HHI. This finding is consistent with the results of existing studies. For example, Pugel [1978] finds that there is a positive relationship between concentration and overseas production. The results with both HHI and its squared term show that HHI has a positive and significant effect and squared HHI has a negative and significant effect. The latter association is of an inverted-U shape. That is, as concentration increases, FSR tends to increase until a critical level of HHI, and then beyond the level starts to fall. The results suggest that in highly-concentrated industries, overseas operations are likely to decline at least relatively.

On the other hand, competition-related variables, such as firm size ratio (FR), merger dummy (MD) and cartel dummy (CD) all have no significant relation to FSR.

Industry R&D intensity $ (RD) $ roughly has a positive and significant effect, with some exceptions. Also, industry export ratio $ (EX) $ and intra-industry trade ratio $ (ITR) $ both have a positive sign and statistical significance. These results indicate that in industries with higher export weight in production and trade, firms tend to have larger foreign sales ratio, being consistent with the a-priori prediction. That is, those firms are likely to have larger overseas operations.

Next, concerning firm-level factors, firm growth rate (FG) and firm size (FS) have both a positive and significant effect, and also R&D intensity (fRD) roughly has a similar effect. But, managerial intensity (fAD) has no significant effect. This result is not in accordance with the findings shown in many existing studies on MNEs (for example Pugel [1978]).

< Table 4-1 around here >

## (2) Results from equations with mobility index: the mobility subsample

To examine the effects of market mobility on foreign sales, this study introduced four indicators measuring the mobility, which were utilized in the above-mentioned world export share analysis as well. Unfortunately due to availability of market shares of firms, the sample size is reduced to 85.

Four mobility indexes roughly have a similar effect on both sign and significance test. Significant positive relationships were found for all the indexes. Therefore, mobility has a restrictive effect on
overseas operations, suggesting that in industries with fierce domestic competition, firms may concentrate their activities on domestic markets rather than on foreign markets to strengthen their home base as much as possible.

HHI has a significant positive effect, depending on the mobility indexes used. The equations with mobility indices $ MM_{2} $ and $ MM_{3} $ (of an “absolute” type) have statistical significance, while the equations with $ MM_{1} $ and $ MM_{4} $ (of a “relative” type) do not. These results suggest that there may be correlation between HHI and indices $ MM_{1} $ and $ MM_{4} $ .

The industry export ratio has a positive significant relation to foreign sales ratio. This result is the same as the finding in the results with the full sample. Also, intra-industry trade ratio has a similar effect except the estimation for mobility index $ MM_{1} $ (equation 1).

But, almost all of the other industry-level variables have consistently the same sign but no significant relation in all the models. The results suggest that they are not amongst the more important influences on the internationalization of firms. Among them, the result of cartel dummy should be noted because the variable has a negative sign in all equations, and is significant in some equations, though being at a lower significance level. Also, the intra-industry trade ratio is significant in all the models except ones with $ MM_{1} $ .

Next, concerning firm-level factors, R&D intensity has a positive and significant effect in equations with mobility indices $ MM_{1} $ , $ MM_{2} $ and $ MM_{3} $ , but has only a lower significance level for mobility index $ MM_{4} $ . Therefore, R&D-intensive firms have a larger internationalization activity. Also, the effect of firm size similarly varies among mobility indices: the variable is positive and significant in the equations with mobility indices $ MM_{2} $ , $ MM_{3} $ and $ MM_{4} $ , while it is insignificant for $ MM_{1} $ . Although there is a little variation among equations, we can conclude that these results are roughly in accordance with the ones from the full sample. These results raise the question of “which one of mobility indexes serves as a better proxy for market mobility.” $ ^{9} $

Firm growth rate and managerial intensity have a similar result in all equations, respectively. The former has a positive and significant effect, and on the contrary the latter has no significance, although being of a positive sign. These results also show the similar relation to the previous estimation.

< Table 4-2 around here >

### V. Concluding Remarks

In this paper, we have estimated the effects of domestic and international competitive pressures on
industry’s world export share and also on individual firms’ foreign sales ratio in Japanese manufacturing industries. The two measures of overseas operations were captured as a proxy for international industrial competitiveness. This section summarizes the findings and discusses their policy implications. $ ^{10} $

### 1. Analysis of world export share

First of all, concentration has no influence on world export share. This finding does not provide empirical support for the argument, prevailing in business world, that a concentration-increasing type of industrial reorganization is required for improving international or export competitiveness. But, it is necessary to note that the intensity of competition is not sufficiently picked up by only concentration. Market mobility which was introduced to take into account the problem has also no discernible influence on world export share. Therefore, we could not find the relationship that domestic competition had an impact on world market share.

On the other hand, it is noted that industries in which mergers took place have smaller world export share, suggesting that mergers do not lead to improved competitiveness. This result is consistent with the stylized fact, called the “merger paradox,” where mergers frequently have not improved financial performance of the merged firms. The implication from this result also is that industrial reorganization by mergers is not likely to induce improved competitiveness.

Also, international competitive pressures measured by export intensity and intra-industry trade ratio have a significant positive relationship to world export share. Therefore, international competitive pressures have an important role in international competitiveness.

Finally, the other main findings here are summarized as follows. Non-SMEs share and domestic market growth have both an export-promoting effect. The former never mean that big mergers between leading firms are desirable for competitiveness. Also, the effect of domestic demand growth is worth to be noted because in Japan, as domestic demand growth became stagnant, firms have lost international competitiveness as well. However, other factors have no effect.

### 2. Analysis of foreign sales ratio

First, concerning industry factors, concentration (i.e., HHI) has a positive relationship in both the full sample and the mobility subsamples, with some exceptions in the mobility subsamples. These facts are partly in line with the findings in existing works that show a positive relationship between concentration and exports to sales ratio. Also, HHI has a positive effect in all equations without
into examination: business model, industrial policy and comparative advantage of an industry. These problems will be left to another study.

## Note

The paper is based on a research project at Competition Policy Research Center (CPRC), Japan Fair Trade Commission. But, CPRC does not always concur in the view we have expressed here. We are indebted to Commissioner Hiroyuki Odagiri, Prof. Yosuke Okada, and participants at the CPRC seminar. Also the financial support (Grants-in-Aids for Scientific Research) of the Japan Society for the Promotion of Science (for Doi and Kato) is also greatly acknowledged.
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Table 1: Summary Statistics in the Empirical Analysis 1

N(1)	Mean	Median	Standard Deviation	Min	Max	CV2)
Dependent variable
World export share	84	6.566	4.672	5.964	0.006	26.876	0.908
Independent variables
Domestic demand growth	84	1.256	1.169	0.433	0.384	3.383	0.344
Export intensity	84	24.317	19.475	22.518	0.010	82.150	0.926
Research and development (R&D) intensity	84	3.400	2.355	3.036	0.170	17.100	0.893
Advertising intensity	84	1.184	0.620	2.239	0.000	17.370	1.891
Processing intensity	84	0.365	0.363	0.113	0.048	0.645	0.308
Capital intensity	84	15.232	8.654	17.979	3.267	133.753	1.180
Intra-industry trade ratio	84	0.118	0.328	0.584	-0.989	0.997	4.964
3-firm concentration ratio(CR)	84	52.762	52.238	18.263	14.771	100.000	0.346
CR2	84	3081.276	2771.39	2068.648	218.182	10000.000	0.670
Herfindahl-Hirschman Index (HHI)	84	0.165	0.142	0.102	0.025	0.427	0.616
HHI2	84	0.036	0.020	0.043	0.001	0.182	1.188
Firm size ratio	84	59.292	64.131	25.359	3.565	100.000	0.428
Merger dummy	54	0.429	0.000	0.498	0.000	1.000	1.162
Cartel dummy	54	0.131	0.000	0.339	0.000	1.000	2.592
Market mobility index
Relative mobility index (MM1)	54	0.272	0.239	0.194	0.045	1.069	0.715
Absolute mobility index (MM2)	54	1.367	1.274	0.694	0.265	3.250	0.508
Absolute share change (MM3)	54	29.533	18.872	29.345	0.639	145.465	0.994
Relative instability index (MM4)	54	0.101	0.079	0.085	0.014	0.588	0.843

2) CV stands for the coefficient of variation.

1) N stands for the number of observations.