Silviase/jgov_v1.4_full_ann huggingface dataset:
merger cases that attracted JFTC's concern, there may have been more cases of increased R&D intensity, that is, R&D expenditures per sales. However, in all cases including these, we found that more firms decreased patent applications after the mergers. We are aware that the number of patents is a poor measure of R&D output and the firms may have changed their patenting strategy after the mergers. For instance, if a firm merges with its main rival, it may find it less necessary to apply patents for defensive purposes. Also, with fewer rivals, it may find it easier to exploit monopoly profits from the invention regardless of whether they obtain patent protection or not. Therefore, we have to be cautious in interpreting our results as the evidence of decreasing R&D output or R&D efficiency. Still, the result is not in conflict with this interpretation. Besides, if the merger decreased the firms' propensity to patent for the reasons just discussed, it can be a manifest of reduced competition, which, of course, should cause a great concern to JFTC or any other competition policy authority.

### 6. Effects on Product Prices

#### 6.1. Model

In this section, we investigate if the retail prices of the products increased after the merger $ ^{14} $ . The products to be considered are differentiated consumer goods. Therefore, the prices can vary across firms (i.e., manufacturers) and even across different items (different brands, different package sizes, different types of package, etc.) of a firm. When two firms in such a market merge while other firms remain as the rivals, the merger can affect not only the prices of the items of the merging firms but also the prices of the rival firms' items, as suggested by differentiated oligopoly models. We will therefore investigate both the effect of the merger on the general market price, calculated as the weighted average over all the items in the market with their sales shares as the weights, and the effect on the price of the merged firm, calculated again as a weighted average over the items offered by the firm.

The model follows that of Ashenfelter and Hosken (2008): for i-th item, j-th region, and t-th month,

$$ p_{i,j,t}=\alpha_{i,j}+\sum_{m=1}^{11}\delta_{m}M_{t}+\beta_{1}POST_{t}+\beta_{2}POST_{t}\times MPP_{i}+\varepsilon_{i,j,t} $$

where $ p_{i,j,t} $ is the price (in logarithm), $ POST_{t} $ is a dummy variable that equals 1 for and only for the post-merger months, $ MPP_{i} $ (short for merging party product) is a dummy variable that equals 1 for and only for the items of the merging firms, $ \alpha_{i,j} $ is a product- and region-specific factors, $ M_{t} $ is a month of the year indicator, $ \delta_{m} $ is the month effect, and $ \varepsilon_{i,j,t} $ is the error term.

Therefore, the estimate $ \hat{\beta}_{1} $ indicates how the market price in general increased after the merger whereas the estimate $ \hat{\beta}_{2} $ indicates how the prices of the merger firms' items increased after the merger in addition to the general market price increase.
companies after the merger despite the former acquiring the 33.4 percent share of the latter in March 2007. Therefore, we can inquire into the post-merger price movement of these two firms separately. For this purpose, we estimated the following equation:

$$ p_{i,j,t}=\alpha_{i,j}+\sum_{m=1}^{11}\delta_{m}M_{t}+\beta_{1}POST_{t}+\beta_{2}POST_{t}\times AJI_{i}+\beta_{3}POST_{t}\times YAMA_{i}+\varepsilon_{i,j,t} $$

where $ AJI_{i}=1 $ if and only if the item belongs to Ajinomoto and $ YAMA_{i}=1 $ if and only if the item belongs to Yamaki.

The result is shown in Table 8. Interestingly, the cross term with Ajinomoto $ \left(\hat{\beta}_{2}\right) $ has a positive coefficient while that with Yamaki $ \left(\hat{\beta}_{3}\right) $ has a negative coefficient. This contrasts in the estimates agrees with the actual movement of the prices (weighted averages of all the items of Ajinomoto's or Yamaki's) as shown by the lines in Figure 2. That is, relatively to the market price, Ajinomoto raised its prices after the merger whereas Yamaki lowered them.

A likely interpretation of this contrasting result is that the combined firm reorganized its product positioning strategy so as to sell its Ajinomoto-related brands as high-end ones and the Yamaki-related brands as low-end ones. In fact, even before the merger, the average price of Ajinomoto-related brands was higher than that of Yamaki, implying that the consumers evaluated Ajinomoto brands more highly than Yamaki brands. After the merger, the firm apparently decided to exploit this consumer evaluation to its advantage, by widening the price differential.

This finding suggests that, in a market with differentiated products, a merger affects not only the price in general. It also affects the positioning of the firm’s various products $ ^{15} $ . This repositioning may affect consumers in different manners. In the seasoning case, those consumers who continued to buy Ajinomoto brands suffered from the price increase whereas Yamaki’s buyers benefitted from the price decrease. In that the cheaper brands became even cheaper, the merger may have had a favorable effect from the income distribution viewpoint.

More generally speaking, this example suggests that a competition policy authority may have to evaluate not just the expected movement of the average price, but also possible change in the structure of prices across different brands. Of course, this is no easy task: nevertheless, it is a necessary step towards understanding probable social effects of a merger.

### 7. Summary and Conclusion

To summarize, our studies indicate the following:

A. No evidence was found that merged firms improved their profitability relatively to that of control firms selected on the basis of similarity in propensity to merge. Actually, even though statistically insignificant, there were more cases of declining profit rates than increasing profit rates.

B. The share prices rose in many cases on the day of announcement but tended to decline within a few days, making the cumulative abnormal returns not
significantly different from zero in the majority of cases.

C. Both R&D intensity and the number of patents decreased in the majority of cases. Among R&D-intensive firms, more firms experienced an increase in the intensity but decrease in the number of patents.

D. As regards the effect on product prices, our study on three markets showed that the average market prices increased (except noodles, for which the market price slightly decreased) and the average prices of the merged firms' items increased even more.

These results suggest that efficiency increase associated with merger was limited, if any at all. Oligopoly models teach us that efficiency increase must be sufficiently large for the merger firms' profit rate to increase and, for the price to decrease, the efficiency increase must be even larger. Both findings A and D imply that the efficiency increase was either nonexistent or not large enough. Consumers' surplus was likely damaged and so was social surplus, that is, the sum of consumers' surplus and producers' surplus. The long-run effect of mergers was similar, in two senses. First, as finding B implies, there was no statistically significant evidence suggesting that investors were expecting the merger to improve long-run profits of the firms. Second, as finding C implies, the merger unlikely resulted in greater innovation efforts or more efficient R&D activity.

The results should be taken with caution, however, because of data limitations and other reasons mentioned earlier. In particular, we emphasize that looking only at the average can be misleading because variance across merger cases is large. There were cases, albeit in a minority, in which profitability increased, share prices increased, or R&D intensity increased. There may have been also cases in which consumers' surplus and social surplus increased. All this suggests is that the impact of merger has to be investigated case by case. To be true it is very difficult for a competition office to estimate accurately the merger's impact on efficiency and on prices; still, it has to be done and the merging firms have to cooperate by providing necessary data and information. With such an estimate in want, one had better be skeptic about efficiency claims made by merging firms.
Arai, Koki (2011) “Ex-Post Examination of Business Combination: Impacts on Retail Prices,” Discussion Paper CPDP 50-E, Competition Policy Research Center, Japan Fair Trade Commission (http://www.jftc.go.jp/cprc/english/discussionpapers.html)

Ashenfelter, Orley and Hosken, Daniel (2008) “The Effect of Mergers on Consumer Prices: Evidence from Five Selected Case Studies,” NBER Working Paper, No. 13859.

Cassiman, Bruno and Colombo, Massimo G. (2006) Mergers & Acquisitions. Cheltenham: Edward Elgar.

Cassiman, Bruno; Colombo, Massimo G; Carrone, Paola; and Veugelers, Reinhilde (2005) "The Impact of M&A on the R&D Process: An Empirical Analysis of the Role of Technological and Market Relatedness," Research Policy, 34, 195-220.

Colombo, Massimo G. and Garrone, Paola (2006) "The Impact of M&A on Innovation: Empirical Results," in Cassiman and Colombo (2006), 104-133.

Competition Policy Research Center (CPRC) (2003) "Kigyo Ketsugo no Kouritsusei to Shijo he no Eikyo ni Kansuru Keizai Bunseki" [Economic Analysis on Efficiency of Merger and Its Effect n Markets], CPRC Reports CR02-03, Competition Policy Research Center, Japan Fair Trade Commission (http://www.jftc.go.jp/cprc/english/reports.html)

Danzon, Patricia M.; Epstein, Andrew; and Nicholson, Sean (2007) “Mergers and Acquisitions in the Pharmaceutical and Biotech Industries,” Managerial and Decision Economics, 28, 307-328.

Farrell, Joseph and Shapiro, Carl (1990) “Horizontal Mergers: An Equilibrium Analysis,” American Economic Review, 80, 107-126.

Fukamachi, Masanori and Makino, Mai (2004a) "Kigyo Ketsugo ni Yoru Kakaku Henk ni Kansuru Bunseki" [Empirical Analysis on the Price Effects of Mergers and Acquisitions], Discussion Paper CPDP 11-J, Competition Policy Research Center, Japan Fair Trade Commission

(http://www.jftc.go.jp/cprc/english/discussionpapers.html)

Fukamachi, Masanori and Makino, Mai (2004b) "Kigyo Ketsugo ni Kansuru Kabuka Event Bunseki" [Event Studies on the Competitive Effects of Mergers and Acquisitions], Discussion Paper CPDP 12-J, Competition Policy Research Center, Japan Fair Trade Commission

(http://www.jftc.go.jp/cprc/english/discussionpapers.html)

Gandhi, Amit; Froeb, Luke; Tschantz, Steven; and Werden, Gregory J. (2008) "Post-Merger Product Repositioning," Journal of Industrial Economics, 56, 49-67.

Odagiri, Hiroyuki (1992) Growth through Competition, Competition through Growth. Oxford: Oxford University Press.

Odagiri, Hiroyuki (2008) "Mergers and Efficiency: Theory, Empirical Evidence, and Competition Policy in Japan," in Klaus Gugler and B. Burcin Yurtoglu [eds.] The Economics of Corporate Governance and Mergers, Cheltenham: Edward Elgar, 203-225. An early version is available as "Mergers and Economic Performance: Do Efficiency Gains Justify Horizontal Mergers?" Discussion Paper CPDP 27-E, Competition Policy Research Center, Japan Fair Trade Commission (http://www.jftc.go.jp/cprc/english/discussionpapers.html)

Odagiri, Hiroyuki and Hase, Tatsuo (1989) "Are Mergers and Acquisitions Going to Be
Popular in Japan Too?: An Empirical Study," International Journal of Industrial Organization, 7, 317-331.

Rosenbaum, Paul R., and Rubin, Donald B. (1983) "The Central Role of the Propensity Score in Observational Studies for Causal Effects," Biometrika, 70, 41-55.

Salant, Stephen W.: Switzer, Sheldon; and Reynolds, Robert J. (1983) “Losses from Horizontal Merger: The Effects of an Exogenous Change in Industry Structure on Cournot-Nash Equilibrium,” Quarterly Journal of Economics, 98, 185-199.

Sweeting, Andrew (2010) "The Effects of Mergers on Product Positioning: Evidence from the Music Radio Industry," RAND Journal of Economics, 41(2), 372-397.

Williamson, Oliver E. (1968) “Economies as an Antitrust Defense: The Welfare Tradeoffs,” American Economic Review, 58, 407-426.
Table 1. Variables, Samples, and Methodology of the Four Studies

Section 3	Section 4	Section 5	Section 6
Effects on	Profits	Share prices	Innovation	Product prices
Variables	Rate of return on equity (ROE)	Cumulative abnormal stock rate of return (CAR)	(1) R&D intensity (R&D expenditure/sales) (2) the number of patents	Retail prices
Comparison between	Pre-merger and post-merger, in comparison to firms with a similar propensity to merger (selected with the propensity score matching methodology)	The actual value and the value predicted with pre-merger data (event-study methodology)	Pre-merger and post-merger	Pre-merger and post-merger, in comparison to market average
Mergers used as samples	6 mergers of local banks	15 mergers (11 financial and 4 manufacturing)	39 mergers of manufacturing firms	Mergers in 3 product markets (seasonings, sugar, and instant noodles)
Table 2. Logit Estimation Result of the Propensity to Merger

Explanatory Variable	Estimated Coefficient	Estimated Standard Error	Statistical Significance
Constant	-407.693	194.857	***
ROE	0.188	0.205
Square of ROE	-0.020	0.005	***
Operating Cost Ratio	4.769	2.622	*
Capital Asset Ratio	-1.899	0.605	***
Bad Loans Ratio	0.535	0.156	***
Log of Assets	52.613	27.370	**
Square of Log of Assets	-1.723	0.956	*
Growth Rate of Regional Production	0.541	0.236	***
Sample Size	773
Pseudo-R<sup>2</sup>	0.410
Log of Pseudo-Likelihood	-20.739

Notes:

1. All explanatory variables except the constant term are measured with one-year lag.

2. Standard errors are adjusted for heteroskedasticity over banks.

3. ***、**、and *、respectively, indicate statistical significance at 1%、5%、and 10%.
Table 3. The List of Merged Banks and the Control Banks

Month/Year of Merger	Merged Bank (Surviving Bank + Absorbed Bank)	PS	Control Bank	PS
April/2000	The Kinki Osaka Bank (Osaka Bank + Kinki Bank)	0.447	The Towa Bank	0.200
April/2003	The Shinwa Bank (The Shinwa Bank + The Kyushu Bank)	0.013	The Chukyo Bank	0.013
April/2003	Tsukuba Bank (Kanto Bank + Tsukuba Bank)	0.157	Suruga Bank	0.145
May/2003	Momiji Bank (Hiroshima Sogo Bank + Setouchi Bank)	0.040	The Yachiyo Bank	0.029
October/2004	The Nishi-Nippon City Bank (Nishi-Nippon Bank + Fukuoka City Bank)	0.060	The Yachiyo Bank	0.029
October/2006	The Kiyo Bank (Kiyo Bank + Wakayama Bank)	0.124	The Hokuto Bank	0.043

Note: PS stands for “Propensity Score.” The third column shows estimated propensity scores of merged banks and the fifth column, those of control banks.
Table 4. Year-Adjusted ROE and Its Changes: Merged Banks and Control Banks Compared

Merged Banks	ROE	Change in ROE from one year before merger to	Control Banks	ROE	Change in ROE from one year before merger to
One year before merger	One year after merger	Two years after merger	Three years after merger	One year before merger	One year after merger	Two years after merger	Three years after merger
$ ROE_{i,-1} $	$ \Delta ROE_{i,1} $	$ \Delta ROE_{i,2} $	$ \Delta ROE_{i,3} $	$ ROE_{i,-1} $	$ \Delta ROE_{i,1} $	$ \Delta ROE_{i,2} $	$ \Delta ROE_{i,3} $
The Kinki Osaka Bank	34.664	-59.175	-50.313	-111.371	The Towa Bank	25.079	-15.021	-59.492	-40.053
The Shinwa Bank	9.696	-44.989	-36.705	-3.916	The Chukyo Bank	11.928	-8.357	-7.495	-8.519
Tsukuba Bank	4.784	-2.714	-33.387	-22.345	Suruga Bank	16.084	-4.692	-8.490	-7.381
Momiji Bank	11.682	-11.253	-7.769	-54.274	The Yachiyo Bank	2.017	-2.127	4.948	4.723
The Nishi-Nippon City Bank	3.334	1.415	7.341	The Yachiyo Bank	2.017	4.948	4.723
The Kiyo Bank	-14.035	20.960	18.492	The Hokuto Bank	3.282	-3.656	-108.485
Mean	8.354	-29.533 (0.14)	-17.633 (0.50)	-27.679 (0.95)	Mean	10.068	-7.549	-11.540	-25.832
Median	7.240	-28.121 (0.25)	-20.578 (0.44)	-13.131 (0.84)	Median	7.605	-6.525	-5.575	-7.950

Note: In three cases, the merger took place on the first day of a new accounting year. In another, the merger took place just one month after the first day of a new accounting year. In these four cases, this new accounting year is defined as t=1, and the previous accounting year is defined as t=-1. In two cases, the merger took place in the midst of an accounting year, in which case this accounting year was defined as t=1 but eliminated from the comparison of $ \Delta ROE_{i,l} $ . In parentheses are the p-values of a t test and a Wilcoxon's signed rank test with null hypotheses that means and medians, respectively, of the effects of merger on company performance are equal to zero.
Figure 1. CARs of Sankyo, Daiichi, and the Two Rival Firms, Eisai and Chugai, following the Daiichi-Sankyo Merger Announcement (21 February 2005)
Table 5. Number of Cases with Positive and Negative Cumulative Abnormal Returns from the Day of Merger Announcement:

Positive	Negative
All	Significant	All	Significant
Day 0 (event day)	25	16	7	3
Day 1	25	7	7	1
Day 2	23	2	9	1
Day 3	22	2	10	2
Day 4	21	2	11	1
Day 5	21	3	11	3
Day 6	21	1	11	2
Day 7	20	0	12	2

Notes:

1. In the column “Significant” is the number of cases that are statistically significant at the 5% level.

2. For individual CAR estimates, see the Appendix Table.
Table 6. The Number of Cases in which R&D Intensity and Patent Applications Increased or Decreased after the Merger

R&D intensity	Number of Patent Applications Published
All sample	Increased	Decreased	Increased	Decreased
Pre-merger 3 years vs. Post-merger 3 years	17	22	11	28
Pre-merger 3 years vs. Post-merger 5 years	17	17	9	25
Pre-merger 3 years vs. Post-merger 3-5 years	16	19	11	23
R&D-intensive firms only (R&D intensity $ \geq $ 3%)
Pre-merger 3 years vs. Post-merger 3 years	9	6	5	9
R&D-intensive firms only (R&D intensity $ \geq $ 4%)
Pre-merger 3 years vs. Post-merger 3 years	7	3	4	6
Cases with JFTC examinations
Pre-merger 3 years vs. Post-merger 3 years	5	1	2	3
With 2-year lag
Pre-merger 3 years vs. Post-merger 3 years	12	22
With 3-year lag
Pre-merger 3 years vs. Post-merger 2 years	12	22

Notes: “Pre-merger 3 years” is the average over the years (T-3, T-2, T-1) where T is the year the merger took place. “Post-merger 3 years” is the average over (T, T+1, T+2); “Post-merger 5 years”, over (T, T+1, T+2, T+3, T+4); and “Post-merger 3-5 years”, over (T+2, T+3, T+4). With 2-year lag, “pre-merger 3 years” is the average over (T-1, T, T+1) and “post-merger 3 years”, over (T+2, T+3, T+4). With 3-year lag, “pre-merger 3 years” is the average over (T, T+1, T+2) and “post-merger 2 years”, over (T+3, T+4).
Table 7. Estimated Effects of Mergers on Prices

Seasonings	Sugar	Noodles
$ \beta_{1} $	0.0016	0.0528	-0.0023
t-value	2.76***	40.31***	-2.91***
$ \beta_{2} $	0.0039	0.0384	0.0023
t-value	3.33***	14.37***	1.82***
Sigma_u	0.0904	0.0818	0.3264
Sigma_e	0.0741	0.1094	0.0558
rho	0.5980	0.3586	0.9716

Estimated coefficients of $ \alpha_{i,j} $ and $ D_{m} $ are suppressed.

***, **, and * indicate statistical significance at 1%, 5%, and 10%, respectively.
Table 8. Estimated Separate Effects on Prices of the Merger Firms

Seasonings
$ \beta_{1} $	0.00795
t-value	6.71***
$ \beta_{2} $	0.00255
t-value	0.76
$ \beta_{3} $	-0.0285
t-value	-5.91***
Sigma_u	0.1133
Sigma_e	0.1725
rho	0.3013

Notes: See Notes to Table 7.
Figure 2. The Movement of Market Price and the Prices of Ajinomoto and Yamaki Products

Panel A: Market price (black line) and the price of Ajinomoto products (gray line)

Note: Bars show the monthly market share (the right-hand side axis).
Panel B: Market price (black line) and the price of Yamaki products (gray line)

Note: Bars show the monthly market share (the right-hand side axis).
Appendix Table. Estimated Cumulative Abnormal Returns

Merger firms	Day 0
(Event Day)	Day 1	Day 2	Day 3	Day 4	Day 5	Day 6	Day 7
1	SANKYO CO.,LTD.	0.04*	0.02	0.05*	0.04	0.04	-0.01*	-0.03	-0.05
2	DAIICHI PHARMACEUTICAL CO.,LTD.	0.04*	0.02*	0.01	-0.00	-0.00	0.07*	0.02*	0.02
3	NSK Ltd.	0.00	-0.00	-0.02	-0.02	-0.03	-0.04	-0.04	-0.05
4	Amatsuji Steel Ball Mfg.Co.,Ltd.	0.27*	0.26	0.25	0.25	0.25	0.25	0.25	0.25
5	THE TOKYO-MITSUBISHI BANK,LTD	0.10*	0.21*	0.12*	0.19*	0.16	0.17	0.14	0.12
6	UFJ Holdings Inc.	0.17*	0.11	0.09	0.05	0.05	0.09	0.09	0.09
7	THE NISHI-NIPPON CITY BANK,LTD.	0.06*	0.05	0.03	-0.03*	-0.04	-0.07	-0.06	-0.06
8	THE FUKUOKA-CITY BANK,LTD.	0.11*	0.09	0.09	0.02*	0.03	0.04	0.05	0.05
9	YAMANOUCHI PHARMACEUTICAL CO.,LTD.	0.06*	0.08	0.08	0.11	0.07	0.09	0.07	0.09
10	FUJISAWA PHARMACEUTICAL CO.,LTD.	0.06	0.11	0.10	0.10	0.07	0.07	0.06	0.07
11	THE HOKURIKU BANK,LTD.	-0.06*	-0.03	-0.03	-0.01	-0.00	-0.04*	-0.05	-0.04
12	THE HOKKAIDO BANK,LTD.	0.12*	0.04*	0.05	0.06	0.07	0.10	0.12	0.13
13	NKK,LTD.	0.16	0.12	0.11	0.10	0.17*	0.23	0.21	0.24
14	KAWASAKI STEEL,LTD.	0.04*	0.03	0.04	0.01	0.04	0.09*	0.08	0.09
15	TOKIO MARINE CO.,LTD.	0.02	0.00	0.03	0.06	0.03	0.05	0.02	0.02
16	NICHIDO FIRE INSURANCE CO.,LTD.	0.03	0.09*	0.08	0.07	0.03*	0.07*	0.06	0.05
17	YASUDA FIRE INSURANCE CO.,LTD.	0.02	0.05	0.03	0.02	0.01	0.01	0.04	0.04
18	NISSAN FIRE INSURANCE CO.,LTD.	0.09*	0.13*	0.13	0.12	0.11	0.10	0.12	0.12
19	THE SHINWA BANK,LTD.	-0.02	-0.00	-0.01	0.01	0.02	0.01	0.01	0.00
20	THE KYUSHU BANK,LTD.	-0.01	0.00	0.02	0.02	0.02	0.03	0.03	0.02
21	THE MITSUI MARINE & FIRE INSURANCE CO.,LTD.	-0.02	-0.04	-0.05	-0.05	-0.11*	-0.17*	-0.14*	-0.08*
22	THE SUMITOMO MARINE & FIRE INSURANCE CO.,LTD.	-0.09*	-0.17*	-0.15	-0.20*	-0.22	-0.24	-0.22	-0.18*
23	NIPPON PAPER INDUSTRIES CO.,LTD.	0.20*	0.17	0.14	0.12	0.15	0.17	0.15	0.18
24	DAISHOWA PAPER INDUSTRIES CO.,LTD.	0.09*	0.06	0.01	-0.04	-0.06	-0.03	-0.06	-0.04
25	THE SANWA BANK,LTD.	0.13*	0.07*	0.03	0.02	-0.01	-0.03	-0.01	-0.03
26	THE TOKAI BANK,LTD.	0.11	0.12	0.07	0.03	-0.04	-0.06	-0.10	-0.15
27	THE TOYO TRUST AND BANK,LTD.	-0.03	-0.08	-0.05	-0.02	0.04	0.04	0.01	-0.03
28	THE TOKYO-MITSUBISHI BANK,LTD.	-0.03*	-0.02	-0.05	-0.04	-0.02	-0.02	-0.06*	-0.06
29	THE MITSUBISHI TRUST AND BANK,LTD.	0.09	0.03	-0.01	0.03	0.08	0.07	0.05	0.08
30	THE NIPPON TRUST AND BANK,LTD.	0.24	0.20	0.16	0.13	0.15	0.18	0.17	0.14
31	THE SUMITOMO BANK,LTD.	0.11*	0.11	0.08	0.09	0.09	0.08	0.08	0.08
32	THE SAKURA BANK,LTD.	0.10*	0.01*	-0.10*	-0.10	-0.11	-0.12	-0.11	-0.10

Notes: $ * $ indicates significance at the 5 % level.
国税局電話相談センター

運営事業

(直接行政サービス事業:直接型)
# 個別事業のフルコスト情報の開示について

1. 目的

○ 政策別コスト情報は、省庁の政策ごとのコストを表示したセグメント情報であり、人件費や事務費を含むフルコストで特定の政策に係る費用を一覧できることにより、①コストの経年変化や他事業との比較分析が可能となり、②行政活動に関する国民の理解の促進が図れること等を目的として作成・公表しておりますが、その一方で、政策別コスト情報には一つの政策単位に複数の事業が含まれており、コストの集計単位が大きいためにフルコストの分析が難しいといった課題があります。

○ このようなことから、平成27年4月30日に公表されました「財務書類等の一層の活用に向けて（報告書）」において、『政策別コスト情報の改善』の手段として、個別事業のフルコスト情報の把握が求められました。

「財務書類等の一層の活用に向けて（報告書）」（抜粋）

## 第2 活用の方向性

（３）行政活動の効率化・適正化のための活用

インフラ資産台帳の整備やフルコスト情報の把握・活用により、行政活動の効率化・適正化が可能となるのではないか。

○ 今回その取組として、代表的な事業についてのフルコストを算定し、公表することとしました。

○ この取組により、以下のような効果があると考えられます。

① 個別事業ごとに要する人件費や事務費に加え、減価償却費や退職給付引当金繰入額といった現金収支を伴わないコストを含むフルコストが明らかになる。

② 国から交付された資金が最終的に国民に行き渡るまでにどのようなコストがどのくらい発生しているのかが把握できるようになる。

③ 利用者 1 人当たりなどの「単位当たりコスト」を算出することにより、事業のボリュームを把握できるとともに、事業の効率性の分析が可能となる。

○ 財務省の省庁別財務書類や政策別コスト情報の参考情報として、個別事業のフルコスト情報を国民の皆様に開示することにより、国民の皆様に財務省の政策に関する理解を深めていただくとともに、財務省職員のコスト意識を向上させ、より効率的・効果的な事業の執行に努めてまいります。
## 2 ．フルコスト情報の見方

## （１）事業・業務の概要

この事業・業務がどのような内容なのか、誰のためにどのように役立つのか簡潔に記載しています。

## （２）単位当たりコスト

フルコストをその行政サービスを利用した利用者数などで割って算出しています。事業の大まかなボリュームを把握するための指標となります。

## （3） 自己収入（フルコストのみ）

当該事業の実施に伴って発生するコストの財源として、税以外で直接受け入れた収入を示しています。

## （4） フルコスト・単位当たりコストの推移

フルコストの金額及び単位当たりコストの3年間の推移を表しています。

## （５）フルコストの性質別割合

フルコストの総額におけるコストの内容の割合について表したものです。当該事業においてどのようなコストの割合が多いのか明らかになります。

## （6） 財務分析

27 年度における当該事業に係る取組について財務情報を使って説明します。

## （7） 単位当たりコスト分析

単位当たりコストが増減した要因を分析して説明します。