Silviase/jgov_v1.4_full_ann huggingface dataset:
Summary Table 2-2: The marginal effect of cost by care levels on exits: Health care facility

Care levels, co-residence	To home	To hospitals, clinics
Care Level 2	-0.0261 (0.0129)	0.0182 (0.0130)
Care Level 3	0.0077 (0.0137)	-0.0227 (0.0138)
Care Level 4	0.0595 (0.0153) $ ^{**} $	-0.0996 (0.0154) $ ^{**} $
Care Level 5	0.1076 (0.0182) $ ^{**} $	-0.1221 (0.0183) $ ^{**} $
No co-residence	-0.2019 (0.0359) $ ^{**} $	0.0639 (0.0362)

Summary Table 2-3: The marginal effect of cost by care levels on exits: Medical care facility

Care levels, co-residence	To home	To hospitals, clinics
Care Level 2	-0.0248 (0.0313)	0.0284 (0.0394)
Care Level 3	-0.0302 (0.0324)	-0.0485 (0.0408)
Care Level 4	-0.0675 (0.0329)	-0.0146 (0.0415)
Care Level 5	-0.0166 (0.0349)	-0.0060 (0.0439)
No co-residence	-0.0907 (0.0483)	0.147 (0.0607) $ ^{**} $

(note) ** refers to 5% level significance and * does to 10% level. Care level 1 is the reference so that it is excluded from the regression.

The Summary tables 2-1 and 2-3 report that the marginal effect of cost by care levels are small and not significant. On the other hand, Summary Table 2-2 shows that the coefficients on care level 4 and 5 in health care home are statistically significant to imply that probability to leave a nursing home is higher for clients with higher care levels. We also observe that the price effect on exit to hospitals and clinics is generally lower for clients with higher care levels. Especially, this is true for transfer from the health care facility to re-hospitalization in clients with care level 4 or 5 as evident in smaller coefficients for those categories.

Moreover, living with family members has statistically significant effects on exiting behavior. Without any co-resident family member, the probability of exit from facilities to return to home is reduced by 20 percentage for health care facility and 9
percentage points for medical care facility. In addition, no co-resident family members increase the probability to transfer clients from medical care institution to re-hospitalization by 15 percentage points. Although the effects of co-resident family members are not significant for other care facilities, “social-hospitalization” is increased in case of living without family members.

In sum, our findings demonstrate that the price elasticity with respect to exit to home is 0.04 percentage points (welfare care facility) and 3.7 percentage points (health care facility), which implies that a proper price policy might contribute to decrease in the institutional care. On the contrary, the price elasticity with respect to exit to re-hospitalization is minus 3.3 percentage points (health care facility) and minus 1.9 percentage points (medical care facility). These results suggest that at-home care is a substitute for institutional care but care services in medical institution are complement for services at nursing homes. Moreover, at-home care demand tends to increase if living with family members. Together with the higher limit to use at-home long-term care at smaller self-burden, it is possible that services provided by the welfare care facilities are substitutes for at-home care, especially for clients with higher care levels. Despite of insignificance in the results, the elderly with relatively lower care levels and thus higher self-burden to use long-term care tends to be re-hospitalized if they do not have any family members to live together. This implies that services provided by hospitals and clinics are complements with those offered by welfare care facilities for these types of the elderly. Therefore, policies to address deduction of the “socially hospitalized” elderly should focus on the elderly with lower care levels and without living with family members and these policies should keep in mind how to provide long-term care services for these types of the elderly.

### 5. The determinants of duration and price elasticity

Next, we apply a duration model to clients who stayed in and exit from their facilities in September 2000 to examine the timing of exit and the effect on price elasticity. We use the same sample used in the previous section in addition to these who stayed in their nursing facilities in the beginning of October, whose duration is truncated. The elderly who do have missing variables for explanatory variables we
used are excluded. As a result, the number of observations we used for this analysis declines to 1,556, 14,134, and 2,828, for long-term care welfare, health, and medical facilities, respectively (Table 3). The survival and hazard functions of timing to exit are defined as follows:

$$ \begin{aligned}&(6.1)\mathrm{S_{d}}(t_{d};\mathrm{P^{N}},P^{F},P^{I},H,Z)=\mathrm{P}(\mathrm{T_{d}}>\mathrm{t_{d}}\left|\mathrm{P^{N}},P^{F},\mathrm{P^{I}},H,Z\right.)=\mathrm{e}^{-\int_{0}^{\mathrm{t_{d}}}\lambda_{\mathrm{d}}(u_{\mathrm{d}};\mathrm{P^{N}},P^{F},\mathrm{P^{I}},H,Z)\mathrm{d}u}\\ &(6.2)\lambda_{\mathrm{d}}(t_{d};\mathrm{P^{N}},P^{F},P^{I},H,Z)=-[\mathrm{d}S_{\mathrm{d}}(t_{d},\mathrm{P^{N}},P^{F},\mathrm{P^{I}},H,Z)/\mathrm{d}t_{d}]/S_{\mathrm{d}}(t_{d},\mathrm{P^{N}},P^{F},\mathrm{P^{I}},H,Z)\\ \end{aligned} $$

where $ T_{d} $ refers to the timing to exit from a nursing home. Table 3 shows that the mean length of stay is about 1,440, 185, and 395 days, for long-term care welfare, health, and medical facilities, respectively. The results are seen to be consistent with the propensity of elderly persons' nursing home exit behavior, such that they are more likely to stay longer in long-term care welfare facilities until they die compared to health and medical facilities. $ P^{N} $ denotes price of facility care services, proxied by self burden of using facility care services subsidized by insurers and the price of at-home care services $ P^{I} $ measured by a client's care level and the number of co-resident family members. But, the price of community-based formal care $ P^{F} $ is not available in our data. H stands for a client's physical characteristics related to health stock and Z does for characteristics of facilities each client belongs to.

We assume three types of distribution to apply a duration model; Cox-proportional, Weibull, and Exponential. In these estimates, we include nursing home care price measured by self-burden to use as well as other factors to affect duration such as clients' ADLs.

Tables 4-1, 4-2 and 4-3 report the results on coefficients on the price factor. The price factor is statistically significant for long-term care welfare and health facilities to use different distributions, which indicates that an increase in self burden to use these types of facility care makes the probability of timing to exit from institution earlier, as indicated by the hazard ratios of larger than one. However, this is not the case for long-term care medical facilities. For Cox-proportional estimates for long-term care welfare facilities, the hazard ratio is 1.017 (95% confidential interval: 1.004-1.030), which is very similar to parametric estimates assuming Weibull or exponential
distributions. For long-term care health facilities, the hazard ratio based on the Cox-proportional function shows 1.018 (95% confidential interval: 0.997-1.038), which is slightly larger than the one for welfare facilities. This is seen to be somewhat inconsistent with the results from previous probit estimates, such that the price elasticity of demand for welfare facilities is much smaller than that for health care facilities. This is almost certainly because we do not control for where an elderly person is located after nursing home exit for our duration estimates. The impacts of care level on the length of stay in long-term care health facilities based on duration analyses are very consistent with previous results from probit regressions. Those whose care levels are higher or who live with other family members are more likely to discharge from health care facilities earlier than elderly persons whose care levels are lower with 5% level significance. Also, it would be interesting to see that the older are less likely to exit from facilities earlier than the younger in welfare and medical facilities, though that is not a case for health facilities. Therefore, we can confirm that both the own price elasticity of long-term facility care except for medical facility care and the relative price elasticity of facility to community-based informal care are elastic. Long-term facility care and community-based informal care are seen to substitute goods. That may give a reason to the government why we should focus on how to deliver long-term care to in particular the elderly who are less severe or who live alone in order to reduce social hospitalization in Japan's nursing care market.

### 6. Discussions and Conclusions

This paper uses a unique census data on Japanese nursing homes to evaluate the determinants of nursing home exit and the price elasticity of the institutional care. We take two approaches to address these by making use of micro-level data from Kaigo Service Shisetsu Zigyousho Chousa (Survey on Care Service Providers) conducted by the Ministry of Health, Labor and Welfare in September 2000. First, we use probit estimates to examine the choice decision to exit a nursing facility to home by making use of clients who left their facilities in September 2000. Our results show that one percentage point increase in self-burden to use institutional care will lead to an increase in probability to return to home by 0.04 percentage points for long-term care welfare.
facilities, 3.7 percentage points for long-term care health facilities, respectively. On the contrary, the price elasticity with respect to exit to re-hospitalization is minus 3.3 percentage points (health care facility) and minus 1.9 percentage points (medical care facility). These results suggest that at-home care is a substitute for institutional care but care services in medical institution are complement for services at nursing homes. Especially, the elderly with relatively lower care levels and thus higher self-burden to use long-term care tends to be re-hospitalized if they do not have any family members to live together. Therefore, policies to address deduction of the “socially hospitalized” elderly should focus on these types of the elderly. Then, we apply a duration model to the sample that consists of all clients who stayed in or left from a nursing home in September 2000 in order to evaluate the price effect on how long a client stays in a nursing home. Our results report that price elasticity with respect to duration staying in nursing homes is 1.7 percentage points (95% confidence interval: 0.4-3.0 percentage points) for long-term care welfare facilities; and 1.8 percentage points (95% confidence interval: 0.0-3.8 percentage points) for health facilities. Our findings demonstrate that price policy might be useful for allocating clients from institutional care to at-home care but the effect is relatively small for long-term care welfare facilities compared to health facilities.

If we could use information on patients in hospitals or clinics who do not need any medical care, it would be very fruitful to investigate how price mechanism works for exit from those medical institutions, which surely would shed light on a solution to diminish the “socially hospitalized” patients and thus reduce the tremendous medical cost in Japan.
## References

Chiswick, Berry (1976). “The Demand for Nursing Home Care: An Analysis of the Substitution Between Institutional and Non-Institutional Care.” Journal of Human Recourses. vol. 11 (3), pp.295-316

Garber, Alan M and McCurdy, Thomas (1990). “Predicting Nursing Home Utilization Among the High-Risk Elderly.” in David A. Wise ed. Ed. “Issues in the Economics of Aging.” pp.173-200. University of Chicago Press.

Green, Vernon L. and Ondrich, Jan I. (1990). “Risk Factors for Nursing Home Admissions and Exits: A Discrete-Time Hazard Function Approach.” Journal of Gerontology: SOCIAL SCIENCE 45(6), s250-258.

Header, Alvin E. (1993). “Economic Disability and Health Determinants of the Hazard of Nursing Home Entry.” Journal of Human Recourses 28 (1), pp.80-110

Ministry of Health, Labor and Welfare (2002). Long-term Care Insurance in Japan (http://www.mhlw.go.jp/english/topics/elderly/care/2.html)

Norton, E.C. (1992). “Incentive Regulation of Nursing Homes.” Journal of Health Economics 11(2), pp.105-128.

Scanlon, William J. (1980). “A Theory of the Nursing Home Market.” Inquiry 17(2), pp.25-41
Table 2-2: Determinants of long-term care facility exit based on Probit estimates (from long-term care health facility)

Variable	Definition	Home	Standard deviation	Long-term care welfare or health facility (n=1,893)	Standard deviation	Hospital or Clinic (n=5,323)	Standard deviation	Dead	Standard deviation

Note: $ \^{**} $ refers to 5% level significance and $ \^{*} $ does to 10% level.
Table 2-3: Determinants of long-term care facility exit based on Probit estimates (from long-term care medical facility)

Variable	Definition	Home	Standard deviation	Long-term care welfare or health facility (n=516)	Standard deviation	Hospital or Clinic (n=877)	Standard deviation	Dead	Standard deviation

Note: $ \^{**} $ refers to 5% level significance and $ \^{*} $ does to 10% level.
Table 3: Key variable definitions and summary statistics for exit behavior

Variable	Definition	From long-term care welfare facility Mean (Standard deviation) (n=1,556)	From long-term health care facility Mean (Standard deviation) (n=14,134)	From long-term medical care facility Mean (Standard deviation) (n=2,828)
dur	length of stay in facility (days)	1440.210	185.338	394.764
(1436.950)	(242.909)	(650.983)
lgX601	natural log of out-of-pocket payment	5.833	9.126	8.843
(4.202)	(1.906)	(2.805)
X311	=1 for care level 1	0.067	0.165	0.094
(0.250)	(0.371)	(0.291)
X312	=1 for care level 2	0.083	0.208	0.111
(0.276)	(0.406)	(0.314)
X313	=1 for care level 3	0.154	0.222	0.148
(0.361)	(0.416)	(0.355)
X314	=1 for care level 4	0.294	0.244	0.276
(0.456)	(0.429)	(0.447)
X315	=1 for care level 5	0.395	0.156	0.353
(0.489)	(0.363)	(0.478)
X11_2	=1 if male	0.733	0.708	0.650
(0.443)	(0.455)	(0.477)
age	age	85.153	83.432	81.915
(7.828)	(7.461)	(9.094)
sqage	squared age	7312.240	7016.600	6792.770
(1314.190)	(1218.320)	(1436.190)
X321	=1 for dementia stage I	0.056	0.135	0.102
(0.230)	(0.342)	(0.302)
X322	=1 for dementia stage II	0.134	0.249	0.151
(0.341)	(0.432)	(0.358)
X323	=1 for dementia stage III	0.243	0.330	0.218
(0.429)	(0.470)	(0.413)
X324	=1 for dementia stage IV	0.372	0.143	0.246
(0.484)	(0.350)	(0.431)
X325	=1 for dementia stage M	0.137	0.022	0.147
(0.344)	(0.147)	(0.354)
X332	=1 for disease stage A	0.130	0.400	0.178
(0.336)	(0.490)	(0.383)
X333	=1 for disease stage B	0.251	0.388	0.269
(0.434)	(0.487)	(0.444)
X334	=1 for disease stage C	0.602	0.184	0.500
(0.490)	(0.387)	(0.500)
Table 4-1: Determinants of long-term care facility exit based on cox-proportional and parametric hazard estimates

Variable	Definition	From long-term care welfare facility	From long-term health care facility	From long-term medical care facility
Haz. Ratio (Standard error)	95% confidential interval	Haz. Ratio (Standard error)	95% confidential interval	Haz. Ratio (Standard error)	95% confidential interval
(1) Cox proportional hazard estimates
Log likelihood	-8749.5716	-117313.05	-18576.449
lgX601	natural log of out-of-pocket payment	1.017 (0.007)	1.004	1.030	***	1.018 (0.010)	0.997	1.038	**	1.002 (0.010)	0.983	1.021
X311	=1 for care level 1	1.946 (0.854)	0.824	4.598	*	2.144 (0.255)	1.698	2.706	***	0.553 (0.100)	0.388	0.790	***
X312	=1 for care level 2	2.048 (0.895)	0.870	4.822	*	2.251 (0.268)	1.783	2.842	***	0.494 (0.088)	0.348	0.702	***
X313	=1 for care level 3	1.591 (0.700)	0.672	3.768	2.318 (0.277)	1.833	2.930	***	0.495 (0.088)	0.350	0.701	***
X314	=1 for care level 4	1.624 (0.720)	0.681	3.870	2.281 (0.275)	1.801	2.887	***	0.443 (0.076)	0.316	0.621	***
X315	=1 for care level 5	1.366 (0.606)	0.572	3.259	2.492 (0.304)	1.961	3.166	***	0.423 (0.073)	0.302	0.594	***
X11_2	=1 if male	0.797 (0.053)	0.700	0.909	***	0.892 (0.017)	0.859	0.926	***	0.813 (0.035)	0.747	0.884	***
age	age	1.057 (0.060)	0.946	1.182	0.952 (0.016)	0.921	0.983	***	1.068 (0.030)	1.012	1.128	***
sqage	squared age	1.000 (0.000)	0.999	1.000	1.000 (0.000)	1.000	1.000	***	1.000 (0.000)	0.999	1.000	***
X321	=1 for dementia stage I	1.391 (0.232)	1.003	1.928	***	1.012 (0.034)	0.947	1.082	1.014 (0.082)	0.865	1.189
X322	=1 for dementia stage II	1.368 (0.194)	1.036	1.806	***	0.920 (0.028)	0.867	0.977	***	0.967 (0.072)	0.836	1.118
X323	=1 for dementia stage III	1.307 (0.178)	1.001	1.706	***	0.829 (0.025)	0.781	0.879	***	0.955 (0.069)	0.829	1.102
X324	=1 for dementia stage IV	1.385 (0.188)	1.062	1.807	***	0.761 (0.027)	0.709	0.816	***	0.947 (0.069)	0.821	1.093
X325	=1 for dementia stage M	1.428 (0.210)	1.070	1.906	***	0.838 (0.054)	0.738	0.952	***	0.946 (0.078)	0.805	1.111
X332	=1 for disease stage A	0.672 (0.307)	0.275	1.644	1.001 (0.197)	0.680	1.471	0.633 (0.097)	0.469	0.853	***
X333	=1 for disease stage B	0.589 (0.269)	0.240	1.444	0.955 (0.188)	0.648	1.405	0.587 (0.088)	0.438	0.788	***
X334	=1 for disease stage C	0.566 (0.260)	0.230	1.393	0.935 (0.185)	0.633	1.379	0.557 (0.083)	0.416	0.744	***
X571	=if informal care available	1.116 (0.176)	0.819	1.521	1.078 (0.043)	0.997	1.166	**	1.143 (0.056)	1.038	1.258	***

Note: *** refers to 5% level significance; ** does to 10%; * does to 15%.
Table 4-2: Determinants of long-term care facility exit based on cox-proportional and parametric hazard estimates

Variable	Definition	From long-term care welfare facility	From long-term health care facility	From long-term medical care facility
Haz. Ratio (Standard error)	95% confidential interval	Haz. Ratio (Standard error)	95% confidential interval	Haz. Ratio (Standard error)	95% confidential interval
(2) Weibull
Log likelihood	-2224.4436	-23171.301	-4871.4212
lgX601	natural log of out-of-pocket payment	1.018	1.006	1.030	***	1.019	0.993	1.047	*	1.005	0.983	1.026
(0.006)	(0.014)	(0.011)
X311	=1 for care level 1	1.973	0.944	4.123	**	2.222	1.822	2.709	***	0.583	0.376	0.905	***
(0.742)	(0.225)	(0.131)
X312	=1 for care level 2	2.058	0.990	4.278	**	2.357	1.934	2.872	***	0.503	0.323	0.782	***
(0.768)	(0.238)	(0.113)
X313	=1 for care level 3	1.640	0.774	3.477	2.437	1.997	2.974	***	0.518	0.334	0.801	***
(0.629)	(0.247)	(0.115)
X314	=1 for care level 4	1.652	0.769	3.549	2.395	1.957	2.930	***	0.469	0.305	0.721	***
(0.645)	(0.247)	(0.103)
X315	=1 for care level 5	1.390	0.642	3.009	2.633	2.141	3.237	***	0.442	0.285	0.686	***
(0.548)	(0.278)	(0.099)
X11_2	=1 if male	0.804	0.704	0.918	***	0.887	0.851	0.925	***	0.810	0.737	0.891	***
(0.054)	(0.019)	(0.039)
age	age	1.054	0.954	1.165	0.953	0.920	0.987	***	1.077	1.018	1.139	***
(0.054)	(0.017)	(0.031)
sqage	squared age	1.000	0.999	1.000	1.000	1.000	1.000	***	0.999	0.999	1.000	***
(0.000)	(0.000)	(0.000)
X321	=1 for dementia stage I	1.373	0.997	1.890	**	1.019	0.950	1.092	1.016	0.839	1.230
(0.224)	(0.036)	(0.099)
X322	=1 for dementia stage II	1.347	1.049	1.730	***	0.915	0.858	0.976	***	0.962	0.808	1.144
(0.172)	(0.030)	(0.085)
X323	=1 for dementia stage III	1.283	1.020	1.613	***	0.819	0.769	0.873	***	0.940	0.794	1.112
(0.150)	(0.026)	(0.081)
X324	=1 for dementia stage IV	1.361	1.076	1.722	***	0.745	0.690	0.805	***	0.935	0.789	1.109
(0.163)	(0.029)	(0.081)
X325	=1 for dementia stage M	1.396	1.082	1.801	***	0.824	0.712	0.954	***	0.946	0.791	1.132
(0.182)	(0.062)	(0.087)
X332	=1 for disease stage A	0.666	0.330	1.345	0.985	0.698	1.391	0.651	0.462	0.916	***
(0.239)	(0.173)	(0.114)
X333	=1 for disease stage B	0.583	0.286	1.187	*	0.935	0.662	1.321	0.600	0.428	0.839	***
(0.212)	(0.165)	(0.103)
X334	=1 for disease stage C	0.564	0.275	1.160	*	0.911	0.643	1.291	0.550	0.390	0.775	***
(0.207)	(0.162)	(0.096)
X571	=if informal care available	1.100	0.811	1.491	1.083	0.993	1.181	**	1.158	1.039	1.290	***
(0.171)	(0.048)	(0.064)

Note: *** refers to 5% level significance; ** does to 10%; * does to 15%.
Table 4-3: Determinants of long-term care facility exit based on cox-proportional and parametric hazard estimates

Variable	Definition	From long-term care welfare facility	From long-term health care facility	From long-term medical care facility
Haz. Ratio (Standard error)	95% confidential interval	Haz. Ratio (Standard error)	95% confidential interval	Haz. Ratio (Standard error)	95% confidential interval
(3) Exponential
Log likelihood	-2224.4512	-23395.868	-5081.9539
lgX601	natural log of out-of-pocket payment	1.018 (0.006)	1.006	1.030	***	1.022 (0.016)	0.991	1.053	1.009 (0.015)	0.981	1.038
X311	=1 for care level 1	1.970 (0.740)	0.944	4.111	**	2.434 (0.270)	1.959	3.024	***	0.499 (0.149)	0.278	0.897	***
X312	=1 for care level 2	2.054 (0.766)	0.989	4.264	**	2.627 (0.289)	2.117	3.260	***	0.404 (0.120)	0.225	0.725	***
X313	=1 for care level 3	1.638 (0.627)	0.774	3.468	2.743 (0.304)	2.207	3.409	***	0.425 (0.125)	0.239	0.756	***
X314	=1 for care level 4	1.650 (0.643)	0.769	3.540	2.689 (0.303)	2.157	3.354	***	0.386 (0.111)	0.220	0.679	***
X315	=1 for care level 5	1.389 (0.546)	0.643	3.002	3.005 (0.347)	2.396	3.768	***	0.355 (0.104)	0.200	0.631	***
X11_2	=1 if male	0.804 (0.054)	0.706	0.917	***	0.874 (0.022)	0.832	0.917	***	0.778 (0.052)	0.682	0.888	***
age	age	1.054 (0.054)	0.954	1.165	0.949 (0.020)	0.910	0.989	***	1.102 (0.044)	1.020	1.191	***
sqage	squared age	1.000 (0.000)	0.999	1.000	1.000 (0.000)	1.000	1.001	**	0.999 (0.000)	0.999	1.000	***
X321	=1 for dementia stage I	1.372 (0.224)	0.997	1.889	**	1.025 (0.043)	0.945	1.112	1.036 (0.145)	0.788	1.361
X322	=1 for dementia stage II	1.346 (0.171)	1.049	1.727	***	0.901 (0.035)	0.835	0.972	***	0.971 (0.123)	0.759	1.244
X323	=1 for dementia stage III	1.282 (0.149)	1.020	1.611	***	0.793 (0.030)	0.737	0.854	***	0.932 (0.114)	0.734	1.183
X324	=1 for dementia stage IV	1.360 (0.162)	1.077	1.717	***	0.708 (0.032)	0.647	0.774	***	0.917 (0.111)	0.724	1.163
X325	=1 for dementia stage M	1.395 (0.181)	1.082	1.797	***	0.792 (0.069)	0.667	0.939	***	0.951 (0.120)	0.743	1.218
X332	=1 for disease stage A	0.667 (0.239)	0.331	1.345	0.970 (0.192)	0.658	1.431	0.553 (0.136)	0.342	0.895	***
X333	=1 for disease stage B	0.584 (0.212)	0.287	1.188	*	0.910 (0.181)	0.616	1.344	0.506 (0.119)	0.319	0.803	***
X334	=1 for disease stage C	0.565 (0.207)	0.276	1.160	*	0.880 (0.177)	0.594	1.304	0.447 (0.106)	0.280	0.712	***
X571	=if informal care available	1.099 (0.170)	0.812	1.488	1.094 (0.057)	0.988	1.210	**	1.199 (0.091)	1.034	1.391	***

Note: *** refers to 5% level significance; ** does to 10%; * does to 15%.
## ③－2 都道府県・市町村における施策の実施状況(高等学校)

平成22年度中に、日本語指導が必要な外国人生徒の高等学校への受入れに関し、各教育委員会が国(市町村については国及び都道府県)の補助金や委託費を受けずに、独自に予算措置を行うなどして、当該生徒に対して実施した施策。

1 都道府県における施策の実施状況(単独事業)

2 市区町村における施策の実施状況(単独事業)

1 担当教員（常勤）の配置

2 生徒の母語を話せる相談員の派遣

3 上記 1，2 以外の指導協力者の配置

4 担当教員の研修

5 受入れに際し、特別な配慮を行っている学校の有無(拠点校、センター校等)

6 研究協力校（地域）の指定

7 就学・教育相談窓口の設置

8 その他

入学選抜において特別枠の設定

多言語版の学校案内の作成

学校発文書文例集の作成・HPへの掲載等
## I mplications for policy exit

• No one-size-fit-all: exit is further advanced in some policy areas and in some countries according to circumstances

Fiscal policy is unsustainable in many OECD countries

• Unorthodox monetary policy will remain for a while

• Policy interest rates to remain low for a while to come in OECD countries

• Costs of current monetary policy

What if scenario is materialised?
## Government debt is rising rapidly

## Gross government debt, in per cent of GDP

Note: Data for 2009 are estimates for some countries.

1. Change between 2007 and 2009.

Source: System of National Accounts database; and OECD Economic Outlook 87 database.
## I mplications for policy exit

No one-size-fit-all: exit is further advanced in some policy areas and in some countries according to circumstances

• Fiscal policy is unsustainable in many OECD countries

- Unorthodox monetary policy will remain for a while

• Policy interest rates to remain low for a while to come in OECD countries

• Costs of current monetary policy

• What if scenario bis materialises?
## Central bank balance sheets have swollen

## Central bank liabilities

Source: Federal Reserve; Bank of Japan; European Central Bank; and Bank of England.