Silviase/jgov_v1.4_full_ann huggingface dataset:
better outcomes than males in terms of the percentage wage change. Perhaps lesser paid females are closer to their value on the external labor market because of less firm specific training.

The influence of gender on pay grows with age in Japan. The earnings of full-time females aged 20-24 relative to males is .89, this drops to .60 for those aged 40-44 [Rebick]. Columns 15 and 16 indicate that, while females under 35 have less favorable wage changes than males, females over 35 have more favorable wage changes than males. This pattern makes sense if male workers are more likely to be on delayed compensation contracts than female workers. Young female workers, earning close to their marginal product, may be harmed more by job loss relative to young males if males had accepted underpayment initially as part of a delayed payment contract. Older females fare better because older males are losing the premium that is paid towards the end of the delayed payment contract. Alternatively, older males may fare worse relative to females than younger males because of a greater loss of accumulated firm specific capital.

Involuntary job change harms older workers more than younger workers. Columns 15 and 16 show that wage change from involuntary job change is substantially more negative for older workers than their younger counterparts. The greater cost imposed on older workers in terms of wage change is to some extent mitigated by a larger severance payment upon job separation.

While industry change was disadvantageous as indicated by the negative industry change dummy variable in both columns 14 and 17, the penalty associated with industry change was diminishing. Column 14 suggests that sometime near 2000 industry change became neutral if not favorable for job changers, while at the start of the sample period, it was significantly negative. We can only speculate about the reason for this. It is possible that industry-specific human capital diminished in importance. Not surprisingly, as illustrated by the industry change dummy variable in columns 15 and 16, older workers finding reemployment in a different industry are harmed, while industry change has little discernable effect on the wage change of younger workers. This is reasonable since older workers lose more industry specific human capital than younger workers.

Occupation change has a different pattern than industry change in that the penalty from occupation change is growing during the sample. Again, as one would expect, the size of the penalty from occupation change is larger for older workers.
While it remained highly beneficial to be employed in a large firm, firm size fell in importance during the sample period. The consequences of a change in firm size diminished both in the rewards to moving to a larger firm and in the penalties to moving to a smaller firm. These results are evident in columns 14 and 17. The weakening of size effects suggests a diminishing firm-size premium.

Changes in employment status are considered through three dummy variables in table 5. Those workers who were initially employed part-time and remained part-time in subsequent employment are coded as ones for the “continuously part-time” dummy variable. Workers losing full-time employment status are coded as ones for the “from full-time to part-time” dummy variable. Workers gaining full-time employment status are coded as ones for the “from part-time to full-time” dummy variable. The status omitted from this coding scheme represents those who remain in full-time employment status through their job change. Naturally, the penalty from leaving full-time employment status is large as indicated by the dummy variable. However, there is a weak positive trend diminishing this penalty. The substantial gain in moving from part-time to full-time employment grows slightly larger over the sample.

The year dummy variables in the last panel of table 5 illustrate the rising overall job change costs during the sample. This rise is largely attributable to the increasing negative effects on those 35 years of age and older.

### 4. Conclusion

Few studies of job displacement in the Japanese labor market appear in the literature. This is largely due to the difficulty of obtaining worker level data and not on a lack of interest in the world’s second largest economy. We study a large national sample of firms with more than five employees to document basic trends in regards to job change. In doing so, we uncover both expected and novel results.

Because of a worsening in the labor market conditions during the period studied, it is not surprising that workers changing jobs had increasingly less favorable outcomes between 1991 and 2002. Given the strong returns to seniority in Japan, it was also not surprising that older workers had larger job displacement penalties. As well, the costs of changing industry, occupation and involuntary job separation were larger for older workers.
Other findings point to more nuanced changes taking place within the Japanese labor market in regards to the value assigned to workers changing jobs. The increasing strength in the age/job displacement penalty relationship suggests that the return to age in the Japanese labor market for those finding new employment is diminishing. The generally increasing job change costs were primarily born by older workers. The diminishing firm size wage premium suggests that the wage structures of larger and smaller firms may be gradually converging at least for the newly hired. Falling industry change penalties could be the result of less industry-specific human capital, perhaps reflecting a gradual decline in industry-specific training.

It is interesting to note that, hidden in the small gender differences in job change penalties, were larger penalties for young females in comparison with males and smaller penalties for older females. While younger females are treated more equitably in the labor market than older females relative to males in regards to pay, they suffer comparatively more from job change.
### 5. References

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Addison, John T.; Portugal, Pedro, 1989. "On the Costs of Worker Displacement: The Case of Dissipated Firm-Specific Training Investments." Southern Economic Journal, 56, (1), 166 - 182.

Blau, Francine and Kahn, Lawrence, 2000. "Gender Differences in Pay," The Journal of Economic Perspectives, Vol. 14, No. 4. (Autumn, 2000), pp. 75-99.

Bognanno, Michael and Delgado, Lisa, 2005. “Job Displacement Penalties in Japan.” Institute for the Study of Labor (IZA) Working Paper No. 1650.

Clark, R. L. and Ogawa, N., 1992. "The Effect of Mandatory Retirement on Earnings Profiles in Japan," Industrial and Labor Relations Review 45:2, 258-266.

Fallick, B. C., 1996. "A Review of the Recent Empirical Literature on Displaced Workers," Industrial and Labor Relations Review 50:1, 5-16.

Farber, H. S., 1997. "The Changing Face of Job Loss in the United States, 1981-1995,"

Brookings Papers on Economic Activity. Microeconomics, 55-142.

Hamermesh, D. S., 1989. "What Do We Know About Worker Displacement in the United States?" Industrial Relations 28(1): 51-59.

Hashimoto, M. and Raisian, J., 1985. "Employment Tenure and Earnings Profiles in Japan and the United States," American Economic Review 75:4, 721-735.

Japan Institute of Labor, Policy and Training, (2005), “Labor Situation in Japan and Analysis, 2004/2005,” http://www.jil.go.jp/english/laborinfo/library/situation2004.htm
Kambourov, Gueorgui and Manovskii, Iourii, 2005. “Occupational Specificity of Human Capital,” Manuscript, University of Toronto.

Kato, T., 2001. “The End of Lifetime Employment in Japan?: Evidence from National Surveys and Field Research,” Journal of the Japanese and International Economies. 15:4, 489-514.

Kletzer, Lori G., 1991. “Earnings after Job Displacement: Job Tenure, Industry, and Occupation.” In John T. Addison, ed. Job Displacement: Consequences and Implications for Policy. Ch. 4. Detroit, Mich.: Wayne State University Press.

Kletzer, Lori G., 1998. “Job Displacement,” The Journal of Economics Perspectives, Vol. 12, No. 1 (Winter), 115-136.

Koike, K., 1988. Understanding Industrial Relations in Modern Japan. London: Macmillan.

Munch, Jakob Roland, 2006. “Career Changes and the Loss of Human Capital,” Manuscript, University of Copenhagen.

Neal, Derek, 1995. “Industry-Specific Human Capital: Evidence from Displaced Workers,” Journal of Labor Economics, Vol. 13, No. 4, 653-677.

Parent, Daniel, 2000. “Industry-Specific Capital and the Wage Profile: Evidence from the National Longitudinal Survey of Youth and the Panel Study of Income Dynamics,” Journal of Labor Economics, Vol. 18, No. 2, 306-323.

Podgursky, Michael and Swaim, Paul, 1987. “Job Displacement and Earnings Loss: Evidence from the Displaced Worker Survey,” Industrial and Labor Relations Review, Vol. 41, No. 1, 17-29.

Rebick, Marcus, 2005. The Japanese Employment System: Adapting to a New Economic

Environment, Oxford : Oxford University Press.

Tachibanaki, T., 1998. ‘Introduction to Wage Differentials: An International Comparison,’ in T. Tachibanaki (ed.), Wage Differentials: An International Comparison. London: Macmillan Press.
Topel, R., 1993. "What Have We Learned from Empirical Studies of Unemployment and Turnover?" Amer. Econ. Rev. 83:2, Papers and Proceedings of the Hundred and Fifth Annual Meeting of the American Economic Association, 110-11.
Table 2Reasons for Job Separations (%)

Notes: This table replicates one in Abe et al. (2002) computed with 1995 data. Shukko refers to temporary transfer to another company.

Source: http://wwwdbtk.mhlw.go.jp/toukei/kouhyo/data-rou14/jikei/kd-jikeiretu-13.xls
Table 3
Wage change (Δ)	Unemployment rate(%)
Full Sample by Year	Female
Year	Δ<-30%	-30%<Δ<-10%	-10%<Δ<+10%	10%<Δ<30%	Δ>30%	Mean*	N	Total	Male	Female	Workforce
All	7.79	12.67	55.89	19.05	4.61	0.00	446,744
1991	5.15	12.25	45.99	30.66	5.96	3.01	45,836	2.1	2.0	2.2	38.88
1992	5.75	12.96	49.90	26.59	4.80	1.76	38,815	2.2	2.1	2.2	38.68
1993	6.89	13.97	50.60	23.89	4.66	0.82	31,710	2.5	2.4	2.6	38.47
1994	7.25	14.50	52.16	21.52	4.58	0.25	29,811	2.9	2.8	3.0	39.60
1995	7.17	13.79	53.92	20.64	4.47	0.22	33,514	3.2	3.1	3.2	39.18
1996	7.66	14.25	52.02	21.32	4.75	0.19	38,270	3.4	3.4	3.3	39.72
1997	7.39	14.31	51.41	22.26	4.63	0.37	42,209	3.4	3.4	3.4	39.72
1998	7.99	10.83	65.67	11.55	3.96	-1.10	36,287	4.1	4.2	4.0	40.07
1999	9.68	12.04	62.82	11.48	3.98	-1.79	33,103	4.7	4.8	4.5	41.04
2000	8.85	10.98	62.46	13.10	4.61	-0.95	38,478	4.7	4.9	4.5	40.53
2001	9.01	10.58	64.02	12.22	4.16	-1.21	38,606	5.0	5.2	4.7	39.78
2002	11.01	12.09	61.33	11.25	4.31	-2.13	40,105	5.4	5.5	5.1	43.05
Full Sample by Age
0-19	3.60	10.37	46.63	29.40	10.00	4.77	12,444
20-24	4.79	12.86	50.38	25.10	6.87	2.46	81,039
25-29	6.47	12.96	53.83	21.51	5.23	0.91	77,716
30-34	5.42	11.98	56.92	20.89	4.79	1.15	53,788
35-44	5.20	11.50	58.41	20.04	4.86	1.18	88,903
45-54	7.37	11.65	64.36	13.94	2.69	-1.06	77,393
55-59	14.79	15.31	58.68	9.71	1.52	-4.82	29,375
60-64	33.75	18.55	40.50	6.18	1.01	-11.68	20,929
65+	15.32	14.33	61.39	7.78	1.18	-5.22	5,157
Full Sample of Males
All	8.02	11.96	57.24	18.68	4.10	-0.17	268,462
0-19	3.60	9.45	45.26	30.05	11.64	5.50	7,061
20-24	3.65	10.58	49.51	28.08	8.18	3.98	40,862
25-29	3.78	10.86	55.79	23.98	5.59	2.51	46,188
30-34	3.70	10.95	59.72	21.54	4.09	1.71	35,418
35-44	4.47	11.01	63.03	18.40	3.08	0.69	49,928
45-54	7.72	11.18	67.34	12.03	1.73	-1.67	46,996
55-59	17.41	16.72	56.14	8.51	1.22	-6.09	21,605
60-64	39.26	19.70	34.82	5.33	0.89	-13.67	16,402
65+	16.94	15.42	59.02	7.37	1.25	-5.91	4,002
Full Sample of Females
All	7.43	13.73	53.86	19.60	5.37	0.26	178,282
0-19	3.60	11.59	48.43	28.53	7.84	3.81	5,383
20-24	5.94	15.18	51.27	22.07	5.54	0.91	40,177
25-29	10.42	16.04	50.95	17.88	4.71	-1.44	31,528
30-34	8.74	13.98	51.50	19.64	6.14	0.07	18,370
35-44	6.12	12.13	52.47	22.14	7.14	1.81	38,975
45-54	6.81	12.37	59.74	16.91	4.17	-0.11	30,397
55-59	7.49	11.36	65.75	13.02	2.37	-1.29	7,770
60-64	13.81	14.38	61.08	9.28	1.46	-4.47	4,527
65+	9.70	10.56	69.61	9.18	0.95	-2.83	1,155
Table 3 (continued)
Wage change (Δ)
Involuntary Male Job Change (excluding shukko)
Age	Δ<-30%	-30%<Δ<-10%	-10%<Δ<+10%	10%<Δ<30%	Δ>30%	Mean*	N
All	24.84	18.57	47.21	7.80	1.58	-8.59	38,947
0-19	10.34	17.77	46.95	16.71	8.22	-0.79	377
20-24	6.83	14.36	53.80	18.59	6.42	0.51	2,695
25-29	5.67	14.84	58.85	16.34	4.30	-0.19	3,067
30-34	6.20	15.41	60.01	15.25	3.14	-0.94	2,518
35-44	6.89	14.51	65.05	12.14	1.41	-2.00	4,672
45-54	17.17	17.77	57.30	6.99	0.77	-6.54	7,057
55-59	31.58	23.40	40.53	3.91	0.57	-12.23	6,264
60-64	50.54	21.38	25.77	2.04	0.27	-17.98	10,162
65+	22.11	17.00	56.39	3.61	0.89	-8.37	2,135
Males Temporarily Transferred to Another Company (shukko)
0-19	1.10	3.56	89.59	4.93	0.82	0.12	365
20-24	1.18	3.68	88.91	5.57	0.66	0.13	2,282
25-29	0.94	2.64	91.72	3.52	1.17	0.20	4,880
30-34	1.02	2.92	92.10	3.37	0.59	-0.06	5,960
35-44	0.93	2.31	93.08	3.43	0.25	-0.04	11,988
45-54	1.58	3.40	92.44	2.37	0.20	-0.57	15,671
55-59	6.56	8.97	82.34	1.83	0.29	-2.95	5,454
60-64	31.98	15.99	48.20	3.38	0.45	-11.35	444
65+	20.51	15.38	64.10	0.00	0.00	-8.46	39
Involuntary Female Job Change (excluding shukko)
All	8.75	14.77	62.37	11.47	2.64	-2.33	23,846
0-19	5.00	11.88	54.37	24.06	4.69	1.73	320
20-24	6.25	16.26	56.50	16.41	4.57	-0.48	3,345
25-29	8.47	15.99	58.72	13.72	3.10	-1.95	3,389
30-34	8.11	15.88	59.05	13.70	3.26	-1.78	2,022
35-44	6.48	13.91	61.96	13.99	3.67	-0.83	4,818
45-54	7.33	12.85	69.92	8.33	1.57	-2.41	5,345
55-59	9.26	13.03	70.36	6.28	1.07	-3.47	2,149
60-64	22.60	18.99	53.58	4.52	0.30	-8.86	1,969
65+	12.88	13.50	68.71	4.70	0.20	-5.12	489
Females Temporarily Transferred to Another Company (shukko)
All	1.08	3.48	89.70	4.58	1.18	0.20	3,999
0-19	0.00	1.41	94.37	2.82	1.41	0.63	71
20-24	0.89	4.02	89.14	4.61	1.34	0.22	672
25-29	0.64	2.44	90.97	3.29	2.66	0.73	941
30-34	0.93	2.79	91.78	3.41	1.09	0.14	645
35-44	0.89	3.82	88.68	6.49	0.13	0.17	786
45-54	1.46	4.39	88.16	5.85	0.15	-0.17	684
55-59	3.14	5.03	86.79	3.14	1.89	-0.66	159
60-64	6.06	6.06	87.88	0.00	0.00	-2.73	33
65+	12.50	0.00	75.00	12.50	0.00	-1.88	8

$ ^{*} $ Mean is calculated by assigning values -30%, -15%, 0%, 15% & 30% to the five categories.
Table 5 (continued)
Data	(1) Pooled	(2) Under 35	(3) 35 & over	(4) Pooled
Occupation change	Dummy	-0.105 (0.022)**	-0.010 (0.027)	-0.276 (0.036)**	-0.098 (0.015)**
× 1992	-0.032 (0.032)	-0.022 (0.041)	-0.017 (0.051)
× 1993	-0.025 (0.034)	0.032 (0.044)	-0.045 (0.053)
× 1994	-0.031 (0.035)	0.014 (0.047)	-0.007 (0.054)
× 1995	-0.046 (0.034)	0.012 (0.045)	-0.039 (0.052)
× 1996	-0.043 (0.032)	-0.004 (0.042)	-0.041 (0.050)
× 1997	-0.068 (0.031)*	-0.086 (0.040)*	0.009 (0.050)
× 1998	-0.085 (0.032)**	-0.056 (0.042)	-0.067 (0.050)
× 1999	-0.121 (0.033)**	-0.066 (0.044)	-0.103 (0.051)*
× 2000	-0.078 (0.032)*	-0.049 (0.041)	-0.030 (0.050)
× 2001	-0.094 (0.032)**	-0.061 (0.041)	-0.059 (0.050)
× 2002	-0.143 (0.031)**	-0.097 (0.042)*	-0.110 (0.049)*
× trend	-0.011 (0.002)**
Firm size change	Dummy: larger new firm	0.468 (0.022)**	0.544 (0.029)**	0.362 (0.033)**	0.399 (0.015)**
× 1992	-0.089 (0.032)**	-0.080 (0.043)	-0.073 (0.048)
× 1993	-0.110 (0.034)**	-0.082 (0.046)	-0.092 (0.050)
× 1994	-0.230 (0.034)**	-0.223 (0.048)**	-0.223 (0.050)**
× 1995	-0.226 (0.033)**	-0.197 (0.046)**	-0.216 (0.048)**
× 1996	-0.190 (0.032)**	-0.197 (0.044)**	-0.160 (0.047)**
× 1997	-0.121 (0.031)**	-0.136 (0.042)**	-0.107 (0.047)*
× 1998	-0.292 (0.032)**	-0.319 (0.043)**	-0.236 (0.048)**
× 1999	-0.294 (0.033)**	-0.299 (0.045)**	-0.267 (0.049)**
× 2000	-0.200 (0.032)**	-0.256 (0.043)**	-0.143 (0.047)**
× 2001	-0.225 (0.031)**	-0.250 (0.043)**	-0.190 (0.047)**
× 2002	-0.167 (0.031)**	-0.267 (0.043)**	-0.047 (0.046)
× trend	-0.016 (0.002)**
Dummy: smaller new firm	-0.591 (0.030)**	-0.567 (0.040)**	-0.599 (0.044)**	-0.564 (0.019)**
× 1992	0.057 (0.043)	0.076 (0.059)	0.052 (0.063)
× 1993	0.053 (0.044)	0.095 (0.062)	0.030 (0.064)
× 1994	0.158 (0.044)**	0.076 (0.064)	0.214 (0.063)**
× 1995	0.184 (0.044)**	0.220 (0.064)**	0.170 (0.062)**
× 1996	0.150 (0.043)**	0.169 (0.061)**	0.148 (0.062)*
× 1997	0.194 (0.042)**	0.186 (0.059)**	0.218 (0.062)**
× 1998	0.219 (0.043)**	0.164 (0.061)**	0.274 (0.062)**
× 1999	0.165 (0.043)**	0.213 (0.061)**	0.144 (0.062)*
× 2000	0.278 (0.042)**	0.333 (0.060)**	0.234 (0.061)**
× 2001	0.257 (0.042)**	0.272 (0.059)**	0.248 (0.060)**
× 2002	0.205 (0.042)**	0.255 (0.059)**	0.172 (0.060)**
× trend	0.020 (0.003)**
Table 5 (continued)
Data	(1) Pooled	(2) Under 35	(3) 35 & over	(4) Pooled
Changes in employment status	Continuously part-time	0.098 (0.037)**	-0.063 (0.066)	0.063 (0.046)	-0.044 -0.023
× 1992	-0.121 (0.053)*	0.065 (0.097)	-0.228 (0.066)**
× 1993	-0.007 (0.055)	0.074 (0.098)	-0.038 (0.068)
× 1994	-0.033 (0.055)	0.025 (0.097)	-0.067 (0.068)
× 1995	0.078 (0.051)	0.230 (0.091)*	0.021 (0.065)
× 1996	0.099 (0.050)*	0.217 (0.085)*	0.053 (0.063)
× 1997	0.128 (0.049)**	0.277 (0.083)**	0.062 (0.062)
× 1998	0.120 (0.049)*	0.163 (0.085)	0.120 (0.063)
× 1999	0.249 (0.048)**	0.217 (0.082)**	0.298 (0.062)**
× 2000	0.263 (0.046)**	0.219 (0.079)**	0.352 (0.060)**
× 2001	0.238 (0.046)**	0.285 (0.079)**	0.258 (0.060)**
× 2002	0.297 (0.045)**	0.278 (0.078)**	0.346 (0.058)**
× trend	0.039 (0.003)**
From full-time to part-time	-1.699 (0.049)**	-1.672 (0.064)**	-1.613 (0.076)**	-1.917 (0.029)**
× 1992	-0.083 (0.069)	-0.113 (0.092)	-0.097 (0.107)
× 1993	-0.250 (0.070)**	-0.312 (0.092)**	-0.207 (0.110)
× 1994	-0.178 (0.068)**	-0.299 (0.092)**	-0.112 (0.105)
× 1995	-0.161 (0.066)*	-0.310 (0.089)**	-0.096 (0.100)
× 1996	-0.049 (0.063)	-0.225 (0.083)**	0.119 (0.099)
× 1997	-0.029 (0.063)	-0.119 (0.082)	0.035 (0.097)
× 1998	0.105 (0.063)	-0.003 (0.084)	0.114 (0.096)
× 1999	0.103 (0.062)	0.030 (0.083)	0.105 (0.096)
× 2000	0.166 (0.061)**	0.166 (0.081)*	0.131 (0.094)
× 2001	0.098 (0.061)	0.123 (0.082)	0.034 (0.093)
× 2002	0.086 (0.059)	0.110 (0.079)	-0.023 (0.090)
× trend	0.031 (0.003)**
From part-time to full-time	1.205 (0.038)**	1.078 (0.051)**	1.293 (0.058)**	1.284 (0.026)**
× 1992	0.192 (0.056)**	0.166 (0.079)*	0.151 (0.082)
× 1993	0.200 (0.061)**	0.157 (0.083)	0.230 (0.090)*
× 1994	0.308 (0.060)**	0.266 (0.084)**	0.302 (0.088)**
× 1995	0.365 (0.059)**	0.407 (0.081)**	0.274 (0.088)**
× 1996	0.404 (0.056)**	0.448 (0.075)**	0.312 (0.086)**
× 1997	0.454 (0.053)**	0.513 (0.071)**	0.355 (0.081)**
× 1998	0.449 (0.057)**	0.567 (0.075)**	0.255 (0.087)**
× 1999	0.481 (0.058)**	0.462 (0.077)**	0.505 (0.090)**
× 2000	0.428 (0.055)**	0.441 (0.072)**	0.409 (0.087)**
× 2001	0.371 (0.055)**	0.365 (0.072)**	0.372 (0.086)**
× 2002	0.622 (0.055)**	0.618 (0.071)**	0.586 (0.087)**
× trend	0.042 (0.003)**
Year dummy variables	1992	-0.308 (0.044)**	0.007 (0.069)	-1.016 (0.128)**
1993	-0.394 (0.047)**	-0.085 (0.075)	-1.424 (0.134)**
1994	-0.398 (0.048)**	0.042 (0.077)	-1.151 (0.135)**
1995	-0.404 (0.046)**	-0.069 (0.075)	-1.262 (0.130)**
1996	-0.263 (0.045)**	0.048 (0.073)	-1.031 (0.129)**
1997	-0.286 (0.044)**	-0.009 (0.070)	-0.782 (0.128)**
1998	-0.601 (0.045)**	-0.073 (0.074)	-1.641 (0.129)**
1999	-0.474 (0.047)**	-0.120 (0.078)	-1.320 (0.132)**
2000	-0.417 (0.045)**	-0.112 (0.073)	-1.202 (0.129)**
2001	-0.508 (0.045)**	-0.255 (0.075)**	-1.251 (0.126)**
2002	-0.473 (0.045)**	0.004 (0.075)	-1.695 (0.125)**
trend	-0.032 (0.003)**
Observations	446100	224657	221443	446100

Notes: standard errors in parentheses, *significant at 5% level, **significant at 1% level
付録4 公害等調整委員会に係属した行政処分に対する不服の裁定事件一覧

事件番号	事件名	受付年月日	申请人	处分厅	終結年月日	終結区分	事件の概要	根拠法	備考
昭和27年土調委第231号	小倉市平尾台地内試掘権(石灰石)設定出願許可処分に対する取消裁定申請事件	27.7.17	小倉市長	福岡通商産業局長	27.12.26	棄却	福岡県小倉市平尾台地内における、石灰石の試掘権設定出願許可処分につき、景観及び観光の対象、天然記念物及び学術研究の対象として重要な価値を有し、また、採掘により、水源、かんがい用水等に悪影響を及ぼす等、鉱業法第35条に違反するとして、その取消しを求めた事件	鉱業法	28.2.18
東京高裁へ提訴
29.7.7
裁定取消しの判決
29.7.22
最高裁へ上告
37.4.12
上告棄却、差戻し
(昭和37年土調委第3号事件)
37.7.16
記録返戻
昭和27年土調委第303号	伊東市十足地内試掘権(明ばん石)設定出願許可処分に対する取消裁定申請事件	27.9.10	伊東市長	東京通商産業局長	28.2.25	取下げ	静岡県伊東市十足地内の明ばん石の試掘権設定出願許可処分につき、鉱業法第35条に違反するとして、その取消しを求めた事件	"
昭和30年土調委第284号	島田市地内試掘権(クローム鉄鉱等)設定出願不許可処分に対する取消裁定申請事件	30.8.6	東京都業者1人	"	30.10.24	"	静岡県島田市地内のクローム鉄鉱及び鉄鉱の試掘権設定出願に対し、クローム鉄鉱についてのみ許可し、鉄鉱については経済的価値がないとして不許可処分としたことにつき、鉱業法第35条に違反するとして、その取消しを求めた事件	"
昭和32年土調委第10号	山口県美祢市地内採掘権(金・銀等)設定出願不許可処分に対する取消裁定申請事件	32.1.8	山口県美祢市業者1人	広島通商産業局長	34.3.30	棄却	山口県美祢市地内の金、銀、銅及び硫化鉄鉱(後に石灰石を追加)の試掘権設定出願(後に採掘に転願)に対する不許可又は一部不許可、転願命令等の処分につき、故意又は重大な過失による違法処分であるとして、その取消しを求めた事件	"	(第10号～第13号合併審理)
34.5.20
東京高裁へ提訴
39.3.28
取下げ
昭和32年土調委第11号	"	"	"	"	"	"	"
昭和32年土調委第12号	"	"	"	"	"	"	"
昭和32年土調委第13号	"	"	"	"	"	"	"
昭和32年土調委第138号	鉱業権設定出願(山口県美祢市)に関し、処分庁が発表した文書及び事実に対する裁定申請事	32.5.28	山口県美祢市業者1人	広島通商産業局長	32.6.12	却下	山口県美祢市地内の金、銀、銅及び硫化鉄鉱の試掘権設定出願に、更に石灰石を加えた鉱種名変更出願につき、処分庁の返付等の事務処理をめぐり適切な指導を欠いた違法があると主張し	"
事件番号	事件名	受付年月日	申请人	处分	終結年月日	終結区分	事件の概要	根拠法	備考
件	た事件
昭和32年土調委第205号	秋田県阿仁町地内鉱業(坑口開設、磨石捨場)のための土地使用許可処分に対する取消裁定申請事件	32.7.8	東京都中央区林業会社	仙台通商産業局長	34.7.11	取下げ	秋田県阿仁町地内の山林における、新坑口の開設及び磨石捨場設置のための土地使用許可処分につき、手続上の瑕疵があり、法律の解釈を誤った違法があるとして、その取消し及び執行停止を求めた事件	鉱業法	33.5.7 執行停止申立て33.7.2 棄却
昭和33年土調委第128号	秋田県阿仁町地内鉱業のための緊急土地使用許可決定に対する取消裁定申請事件	33.5.20	"	秋田県収用委員会	33.6.18	却下	昭和32年土調委第205号の事件に関連し、秋田県収用委員会により行われた鉱山鉱業用の緊急土地使用許可決定につき、要件の認定が不十分かつ誤認しており、また、その担保額は余りにも小額である等の違法があるとして、その取消し及び執行停止を求めた事件	"	33.5.21 執行停止申立て33.6.18 却下
昭和33年土調委第286号	秋田県阿仁町地内鉱業のための土地使用裁決に対する取消裁定申請事件	33.11.15	"	"	34.7.6	取下げ	昭和32年土調委第205号の事件に関連し、秋田県収用委員会により行われた緊急土地使用許可及び土地使用を認める最終裁決等につき、土地所有者たる申請人の意見、陳述を極度に制限する等審理不尽等の違法があるとして、その取消し及び執行停止を求めた事件	"	33.11.15 執行停止申立て33.12.22 棄却
昭和34年土調委第245号	高知市地内鉱業(石灰石運搬索道)のための土地使用許可処分に対する取消裁定申請事件	34.7.10	高知県土地所有者2人	四国通商産業局長	35.10.28	棄却	高知県高知市地内において、セメント原料及び石灰石運搬のために索道を設けるための山林の使用許可処分につき、鉱業法第104条の要件に該当せず、また、この土地使用は農地に対する直接被害等を与え不当であるとして、その取消しを求めた事件	"	35.12.19 東京高裁へ提訴37.8.30 取下げ
昭和35年土調委第157号	東京都北区地内試掘権(金外7)設定出願不許可処分に対する取消裁定申請事件	35.5.13	東京都板橋区業者等3人	東京通商産業局長	35.7.15	却下	東京都北区地内の金等の試掘権設定出願に対し、当該鉱物の掘採が経済的に価値がないとする不許可処分につき、違法行為や事実誤認があり、行政措置として公明適正を欠き、申請人の法益を阻害されること甚大なものがあるとして、その取消しを求めた事件	"	35.9.16 東京高裁へ提訴36.2.4 取下げ
昭和36年土調委裁第1号	山口県美祢市地内試掘権(金・銀等)設定出願一部不許可処分等に対する取消裁	36.4.17	山口県美祢市業者1人	広島通商産業局長	36.5.1	"	山口県美祢市地内の金、銀、銅の試掘権設定出願(のち採掘権設定出願に転願)の一部不許可処分につき、さきに石灰石を加える更正願をなしたにももかわらず、	"
事件番号	事件名	受付年月日	申请人	处分	終結年月日	終結区分	事件の概要	根拠法	備考
定申請事件	金ほか2種についてのみ処置したものであるとして、その取消しを求めるとともに石灰石を加えた処分をすべきであると主張した事件
昭和36年土調委裁第2号	香川県小豆郡土庄町海岸保全区域内土砂採取不許可処分に対する取消裁定申請事件	36.12.7	香川県土庄町業者1人	土庄町長	37.8.18	取下げ	香川県土庄町小豊島池の浦海岸保全区域内における土砂採取許可申請に対し、国土保全に支障があるとする不許可処分につき、申請に係る程度の土砂採取ではなら影響を与えるものではなく、同地の土砂は良質なけい砂で製鉄、造船等に供給され、国家発展に寄与するものであるとして、その取消しを求めた事件	海岸法
昭和37年土調委裁第3号	小倉市平尾台地内試掘権（石灰石）設定出願許可処分に対する取消裁定申請事件（再審理）	37.4.12	北九州市長	福岡通商産業局長	45.2.16	11	昭和27年土調委第231号事件の再審理	鉱業法	38.2.10 北九州市発足44.12.23 平尾台関係鉱区禁止地域指定
昭和37年土調委裁第4号	東京都北区地内試掘権（金外7）設定出願不許可処分に対する取消裁定申請事件	37.12.26	東京都板橋区業者1人	東京通商産業局長	39.2.24	棄却	東京都北区地内の金等8鉱種の試掘権設定出願に対し、処分は経済的に価値なしとする不許可処分につき、事実認認で申請人の法益が阻害されること甚大であるとして、その取消しを求めた事件	11
昭和38年土調委裁第3号	青森県下北郡大畑町地内試掘権（砂鉱）設定出願一部不許可処分に対する取消裁定申請事件	38.5.1	青森県大畑町業者2人	仙台通商産業局長	38.8.22	取下げ	青森県大畑町の国有地内における砂鉱試掘権設定出願に対し、林業の利益を損じ、公共の福祉に反するとする一部不許可処分につき、不許可処分が稼行の中心となる部分で、かつ、鉱床が賦存しており、この部分の不許可は全部の不許可と等しく、また、関係官庁の回答を鶴呑みにした処分であるとして、その取消しを求めた事件	11
昭和39年土調委裁第3号	鳥取県米子市皆生海岸保全区域土石採取不許可処分に対する取消裁定申請事件	39.4.24	皆生砂利採取組合	建設大臣	41.5.20	棄却	鳥取県米子市皆生海岸の海岸保全区域内における土石採取許可申請に対し、海岸保全施設の保全上支障を来すとする不許可処分につき、この海岸は境港市の突堤ができてから侵食が起こったもので、当局は根本的対策を講じておらず、また、同所の砂利は満干潮、風向	海岸法