Silviase/jgov_v1.4_full_ann huggingface dataset:
panel.) Tables 7 and 8 display the regression results based on the constructed pseudo-panel data for homeowner households. The estimated MPCs are 0.0006–0.0015 (nondurable consumption) and 0.0052–0.0074 (total consumption). These estimates are statistically significant and similar to those obtained from the sample including renters. Furthermore, as in Tables 3 and 4, the MPCs tend to be larger for older than for younger households.

In sum, since the estimation results remain largely unchanged even when we exclude renters from the sample both in the cross-sectional and pseudo-panel analyses, we conclude that our main finding still holds that the most plausible explanation for the observed comovement between housing wealth and household consumption in Japan appears to be pure wealth effects.

### 4.4 Macroeconomic implications

As shown in Figure 1, Japan experienced a rapid increase in land prices per square meter during the period 1986–1991 and a significant drop during the years 1991–1994. In this subsection, we examine to what extent the volatile movement in land prices per square meter during the asset bubble and its aftermath affected household consumption by utilizing the estimates obtained above. Note that since the microdata used in other studies on Japan, such as data from the JPSC and KHPS, do not cover the period mentioned above, in particular the bubble period, $ ^{30} $ this, to the best of our knowledge, is the first attempt to investigate the extent to which changes in land prices per square meter contributed to the dynamics of household consumption during the bubble and its collapse based on microdata.

The results of this exercise are summarized in Table 9. From 1986 to 1991, the average nominal land price per square meter rose by 154%. Multiplying this by 0.0688, which is the estimated elasticity of total consumption with respect to land prices per square meter obtained in specification (7) in Table 3, suggests that the increase in land prices boosted consumption by 10.6%. Combining this with the fact that the actual growth rate of final consumption expenditure of households (excluding the imputed service of owner-occupied dwellings) during this period was 33.8%, this back-of-the-envelope calculation implies that about 31% of the growth rate of household consumption during the bubble period is explained by the surge in land prices, $ ^{31} $ which is consistent with the adjusted $ R^{2} $ derived from specification (7) in Table 3, 0.29.

The second row in Table 5 shows the result of the same exercise for the period 1991–1994. Our estimate indicates that the drop in land prices reduced household consumption by 2.8%. Given that actual household consumption continued to grow by 8.9% between 1991 and 1994, our estimate suggests that during this period the decline in land prices simply lowered the rate of increase in
household consumption; that is, household consumption would have increased by 2.8% more if land prices had remained unchanged.

## 5 Conclusion

This paper examined to what extent household consumption responds to changes in housing wealth using Japanese microdata covering approximately 500,000 households over the period 1983–2012. The cross-sectional analysis revealed that, keeping other factors fixed, households with greater housing wealth spend more, and the estimated MPCs are 0.0012 for nondurable and 0.0035 for total consumption. In addition, the comparison of consumption patterns between younger and older households showed that the estimates for older households were larger than those for younger households, which is consistent with the pure wealth effect hypothesis.

In addition, as a robustness check, we conducted regression analyses using pseudo-panel data constructed from the cross-sectional FIES data. The derived MPCs are 0.0008–0.0013 for nondurable consumption and 0.0059–0.0082 for total consumption and, again, the consumption of older households was found to be more responsive to changes in housing wealth than that of younger households.

Judging from these regression results, it appears that housing wealth effects can be observed in Japan, but they are weaker than in other developed countries. Moreover, the pure wealth effect channel provides the most plausible explanation for the positive relationship between consumption and housing wealth, which is consistent with the findings by Campbell and Cocco (2007).
## References

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Figure 1

Rate of change in land prices per square meter and final consumption expenditure of households (excluding imputed service of owner-occupied dwellings) Sources: Ministry of Land, Infrastructure, Transport and Tourism; Cabinet Office.
Figure 2

Elasticity of consumption with respect to the land price per square meter
Table 1

Descriptive statistics

Variable	Obs.	Mean	Std. Dev.	Obs.	Mean	Std. Dev.
Homeowners	Renters
Total consumption	358,870	301	172	138,791	249	136
Nondurable consumption	358,870	138	49	138,791	113	41
Annual income	358,870	695	451	138,791	547	287
Housing wealth (a)=(b)+(c)	358,870	3,258	4,007	138,791	0	0
House value (b)	358,870	467	703	138,791	0	0
Land value (c)=(d)*(e)	358,870	2,791	3,895	138,791	0	0
Land price per square meter (d)	358,870	15	19	138,791	18	22
Land area (square meters) (e)	358,870	235	184	138,791	0	0
Capital gain (land)	358,870	-2	785	138,791	0	0
1983-1991	102,105	248	1,237	46,033	0	0
1992-2012	256,765	-101	466	92,758	0	0
Financial wealth	151,654	1,822	2,327	52,095	736	1,137
Net financial wealth	151,654	1,247	2,734	52,095	635	1,214
Age of household head	358,870	55	13	138,791	43	13
# of working household members	358,870	1.5	1.0	138,791	1.4	0.7
Family size	358,870	3.3	1.3	138,791	3.3	1.1
# of household members aged 65 and over	358,870	0.6	0.8	138,791	0.2	0.5
# of household members aged 15 and younger	358,870	0.6	1.0	138,791	1.1	1.0
Male dummy (household head)	358,870	0.9	0.2	138,791	0.9	0.3

Notes: All monetary variables are in 10,000 yen. Housing-related expenditures are subtracted from total consumption. Annual income is the previous year's pretax annual income. Net financial wealth is calculated by subtracting outstanding debt from financial wealth. The observation period is 1983–2012. As for financial wealth and debt, only a limited number of households were surveyed before 2002. Capital gain is calculated by taking the first difference on the land value based on the assumption that, normally, the land area for each household is constant over time.
Table 2

Regression results (cross-sectional data)

Dependent variable:	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Nondurable consumption	Total consumption
Aged 65 or older	Aged 65 or older
Housing wealth	0.00100***	0.00120***	0.00123***	0.00143***	0.00328***	0.00351***	0.00361***	0.00329***
(0.0000339)	(0.0000785)	(0.0000888)	(0.0000906)	(0.000128)	(0.000266)	(0.000299)	(0.000320)
Housing wealth	-0.000370***	-0.00157***
* Young	(0.000131)	(0.000483)
Net financial wealth	No	Yes	Yes	Yes	No	Yes	Yes	Yes
MPC out of HW for Young	0.00086***	0.00205***
(0.00010)	(0.00040)
N	497,661	203,749	203,749	54,573	497,661	203,749	203,749	54,573
Adj. R-sq	0.357	0.351	0.352	0.283	0.280	0.299	0.300	0.270

Notes: The dependent variable is annualized nondurable or total consumption (excluding housing-related expenditure). All regressions include the age, sex, industry of occupation, and type of work of the household head, the previous year's (pre-tax) income, the prefecture of residence, family size, the number of household members aged 65 and over, the number of household members aged 15 and under, year dummies, cohort dummies, an urban dummy, and first month of the survey dummies. All monetary variables are converted into real terms using prefectural CPIs and are in 10,000 yen. The dummy “Young” takes one if the head of household is aged 40 or below and zero otherwise. Robust standard errors are in parentheses. $ ^{***} $ , $ ^{**} $ , and $ ^{*} $ indicate statistical significance at the 1, 5 and 10% levels respectively. The results of the test that examines whether the MPC out of housing wealth for young households is statistically different from zero are shown at the bottom of the table.
Table 3

Regression results (pseudo-panel data, log-log specification)

(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Dependent variable:	Δln(ND)	Δln(C)	Δln(ND)	Δln(C)
Δln(Housing wealth)	0.0236*** (0.00865)	0.0531*** (0.0131)	0.0411*** (0.0150)	0.105*** (0.0206)
Δln(Housing wealth)	-0.0540*** (0.0163)	-0.114*** (0.0259)
* Young
Δln(Price)	0.0217* (0.0112)	0.0352*** (0.0121)	0.0688*** (0.0184)	0.102*** (0.0197)
Δln(Price)	-0.0447*** (0.0168)	-0.114*** (0.0275)
* Young
MPC (β×C/HW)
Housing wealth	0.0013	0.0049	0.0012	0.0082
Old	0.0026	0.0111	0.0017	0.0108
Young	-0.0001	-0.0020	-0.0009	-0.0027
HW elasticity of consumption for young	-0.0009 (0.0108862)	-0.0090 (0.0172394)	-0.0095 (0.0155111)	-0.0125 (0.0249934)
N	962	962	962	962	962	962	962	962
Adj. R-sq	0.319	0.338	0.288	0.313	0.314	0.328	0.290	0.308

Notes: In all specifications, the real interest rate, the rate of change of the previous year's pretax income, family size, the number of working household members, the number of household members aged 15 or below, and the number of household members aged 65 or above are included. In addition, dummies for two-year intervals are also added to eliminate aggregate effects. The MPCs are calculated by multiplying the estimated elasticity by the consumption-housing wealth ratio. Robust standard errors are in parentheses. $ *\*\* $ , $ *\* $ and $ * $ indicate statistical significance at the 1, 5 and 10% levels respectively. The results of the test that examines whether the elasticity of consumption with respect to housing wealth for young households is statistically different from zero are shown at the bottom of the table.
Table 4

Regression results (pseudo-panel data, first-difference specification)

(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Dependent variable:	Δ(ND)	Δ(C)	Δ(ND)	Δ(C)
Δ(Price)*Qbar	0.000833**	0.000887**	0.00591***	0.00627***
(0.000368)	(0.000376)	(0.00127)	(0.00128)
Δ(Price)*Qbar	-0.00112	-0.00682**
* Young	(0.000731)	(0.00265)
Δ(Price)*Q(-1)	0.000993**	0.00101**	0.00681***	0.00688***
(0.000397)	(0.000400)	(0.00139)	(0.00138)
Δ(Price)*Q(-1)	-0.00105	-0.00640
* Young	(0.00111)	(0.00432)
MPC out of HW for Young	-0.0002354	-0.0005494	-0.0000385	0.0004801
(0.0007526)	(0.0026957)	(0.0011605)	(0.0044892)
N	968	968	968	968	968	968	968
Adj. R-sq	0.311	0.321	0.297	0.309	0.312	0.322	0.301	0.310

Notes: In all specifications, the real interest rate, the first difference of the previous year's pretax income, family size, the number of working household members, the number of household members aged 15 or below, and the number of household members aged 65 or above are included. In addition, dummies for two-year intervals are also added to eliminate aggregate effects. Robust standard errors are in parentheses. $ *\*\* $ , $ *\* $ and $ * $ indicate statistical significance at the 1, 5 and 10% levels respectively. The results of the test that examines whether the MPC out of housing wealth for young households is statistically different from zero are shown at the bottom of the table.
Table 5

Regression results (cross-sectional data, homeowners only)

Dependent variable:	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Nondurable consumption	Total consumption
Aged 65 or older	Aged 65 or older
Housing wealth	0.000824***
(0.0000349)	0.000953***
(0.0000782)	0.000990***
(0.0000854)	0.00114***
(0.0000916)	0.00276***
(0.000136)	0.00266***
(0.000269)	0.00277***
(0.000291)	0.00247***
(0.000328)
Housing wealth	-0.000455***
(0.000141)	-0.00151***
(0.000551)
* Young
Net financial wealth	No	Yes	Yes	Yes	No	Yes	Yes	Yes
MPC out of HW for Young	0.0005341***
(0.0001196)	0.0012589***
(0.0004902)
N	358,870	151,654	151,654	49,264	358,870	151,654	151,654	49,264
Adj. R-sq	0.314	0.303	0.303	0.270	0.263	0.282	0.282	0.255

Notes: See notes for Table 2.
Table 6

Regression results (cross-sectional data, renters only)

Dependent variable:	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Nondurable consumption	Total consumption
Aged 65 or older	Aged 65 or older
Housing wealth	0.000194***	0.000214**	0.000397***	0.0000918	0.00158***	0.00109***	0.00156***	0.000249
(0.0000491)	(0.0000851)	(0.000113)	(0.000266)	(0.000346)	(0.000303)	(0.000395)	(0.000820)
Housing wealth	-0.000396***	-0.00103**
* Young	(0.000134)	(0.000490)
Net financial wealth	No	Yes	Yes	Yes	No	Yes	Yes	Yes
MPC out of HW for Young	0.000000958	0.0005276
(0.0001017)	(0.0003813)
N	138,122	51,875	51,875	5,276	138,122	51,875	51,875	5,276
Adj. R-sq	0.372	0.373	0.374	0.262	0.305	0.324	0.325	0.310

Notes: See notes for Table 2.
Table 7

Regression results (pseudo-panel data, log-log specification, homeowners only)

(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Dependent variable:	Δln(ND)	Δln(C)	Δln(ND)	Δln(C)
Δln(Housing wealth)	0.0361**	0.0390**	0.0794***	0.104***
(0.0140)	(0.0151)	(0.0225)	(0.0237)
Δln(Housing wealth)	-0.0134	-0.119**
* Young	(0.0297)	(0.0479)
Δln(Price)	0.0261**	0.0338***	0.0800***	0.108***
(0.0112)	(0.0120)	(0.0186)	(0.0191)
Δln(Price)	-0.0298	-0.111***
* Young	(0.0219)	(0.0362)
MPC (β×C/HW)
Housing wealth	0.0015	0.0073	0.0011	0.0074
Old	0.0017	0.0095	0.0014	0.0099
Young	0.0011	-0.0014	0.0002	-0.0003
Elasticity out of HW for Young	0.0256	-0.0142	0.0040	-0.0030
(0.0273919)	(0.0447575)	(0.0206239)	(0.0345071)
N	885	885	885	885	885	885	885	885
Adj. R-sq	0.257	0.262	0.246	0.253	0.253	0.259	0.248	0.256

Notes: See notes for Table 3.
Table 8

Regression results (pseudo-panel data, first difference specification, homeowners only)

(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Dependent variable:	$ \Delta(\text{ND}) $	$ \Delta(\text{C}) $	$ \Delta(\text{ND}) $	$ \Delta(\text{C}) $
$ \Delta(\text{Price})*\text{Qbar} $	0.000573*	0.000712**	0.00518***	0.00649***
(0.000323)	(0.000339)	(0.00118)	(0.00121)
$ \Delta(\text{Price})*\text{Qbar} $	-0.000729	-0.00690***
* Young	(0.000704)	(0.00253)
$ \Delta(\text{Price})*\text{Q}(-1) $	0.000614*	0.000746**	0.00538***	0.00667***
(0.000335)	(0.000350)	(0.00123)	(0.00127)
$ \Delta(\text{Price})*\text{Q}(-1) $	-0.000732	-0.00715***
* Young	(0.000749)	(0.00265)
MPC out of HW for Young	-0.0000174	-0.0004127	0.0000138	-0.0004729
(0.0006796)	(0.0024399)	(0.0007249)	(0.0025473)
N	889	889	889	889	889	889	889	889
Adj. R-sq	0.271	0.272	0.253	0.260	0.272	0.272	0.254	0.260

Notes: See notes for Table 4.
Table 9

Contribution of changes in land prices to household consumption during 1986–1994

Period	Rate of change in land prices	Rate of change in consumption	Explained (share)
Explained	Actual
(a)	(b)=(a)*0.0688	(c)	(d)=100*(b)/(c))
1986-1991	154%	10.6%	33.8%	31%
1991-1994	-41%	-2.8%	8.9%	n.a.

Note: The elasticity of total consumption with respect to land prices per square meter is taken from specification (7) in Table 3.
# 9808 財政投融資特別会計（財政融資資金勘定）

平 成 3 0 年 度 歲 出 概 算 要 求 書

1. 平成 30 年度歳出概算要求額総表 ___ 1

2. 平成 30 年度歳出概算要求額明細表 2

(会計)08 財政投融資 2

3. 平成 30 年度概算要求定員表 …… 17
平 成 3 0 年 度 歲 出 概 算 要 求 額 目 次
9808財政投融資特別会計(財政融資資金勘定)
要求番号	区	分	ページ	要求番号	区	分	ページ
1	平成30年度歳出概算要求額総表	1
平成30年度歳出概算要求額明細表	2
(会計) 08 財政投融資	2
(勘定) 1 財政融資資金勘定	2
(項) 010 財政融資資金へ線入	2
01-95 財政融資資金へ線入れに必要な経費	2
(項) 020 事務取扱費	2
2	03-95 事務取扱いに必要な経費	2
3	07-95 財政融資資金の運用に必要な経費	12
(項) 030 諸支出金	15
4	01-95 預託金利子支払等に必要な経費	15
(項) 040 国債整理基金特別会計へ線入	15
5	01-20 国債整理基金特別会計へ線入れに必要な経費	15
(項) 070 公債等事務取扱費一般会計へ線入	15
6	01-20 公債等事務取扱費の財源の一般会計へ線入れに必要な経費	16
(項) 090 予備費	16
7	01-98 予備費	16
平成30年度概算要求定員表	17
平 成 3 0 年 度 歲 出 概 算 要 求 額 総 表
9808財政投融資特別会計(財政融資資金勘定)
要求
番号	区
分	前 年 度 予 算 額	3 0 年 度 概 算 要 求 額	对 前 年 度 較
增
(B-A)	明細書
頁数
一般行政經費	その他の經費	計
(A)	一般行政經費	その他の經費	計
(B)
1	08 財 政 投 融 資	0	26,961,172,358	26,961,172,358	0	26,164,790,723	26,164,790,723	4	796,381,635	2
1 財 政 融 資 資 金 勘 定	0	26,961,172,358	26,961,172,358	0	26,164,790,723	26,164,790,723	4	796,381,635	2
010 財 政 融 資 資 金 へ 繰 入	0	12,000,000,000	12,000,000,000	0	12,000,000,000	12,000,000,000	0	2
01-95 財政融資資金へ繰入に必要な経費	0	12,000,000,000	12,000,000,000	0	12,000,000,000	12,000,000,000	0	2
020 事 務 取 报 費	0	5,915,114	5,915,114	0	5,886,873	5,886,873	28,241	2
2	03-95 事 務 取 报 い に 要 な 経 費	0	4,148,109	4,148,109	0	4,187,228	4,187,228	39,119	2
3	07-95 財政融資資金の運用に必要な経費	0	1,767,005	1,767,005	0	1,699,645	1,699,645	67,360	12
030 諸 支 出 金	0	343,025,697	343,025,697	0	367,678,256	367,678,256	24,652,559	15
4	01-95 預託金利子支払等に必要な経費	0	343,025,697	343,025,697	0	367,678,256	367,678,256	24,652,559	15
040 国債整理基金特別会計へ繰入	0	14,612,106,487	14,612,106,487	0	13,791,061,477	13,791,061,477	821,045,010	15
5	01-20 国債整理基金特別会計へ繰入に必要な経費	0	14,612,106,487	14,612,106,487	0	13,791,061,477	13,791,061,477	821,045,010	15
070 公債等事務取撥費一般会計へ繰入	0	65,060	65,060	0	104,117	104,117	39,057	15
6	01-20 公債等事務取撥費の財源の一般会計へ繰入れ
に必要な経費	0	65,060	65,060	0	104,117	104,117	39,057	16
090 予 備 費	0	60,000	60,000	0	60,000	60,000	0	16
7	01-98 予 備 費	0	60,000	60,000	0	60,000	60,000	0	16
会 計 計	0	26,961,172,358	26,961,172,358	0	26,164,790,723	26,164,790,723	796,381,635
平 成 3 0 年度 蔵 出 概 算 要 求 額 明 细 表
9808財政投融資特別会計(財政融資資金勘定)
要求
番号	事 项	前
予 算 額	3 0 年 度
概 算 要 求 額	对 前 年 度
比較增△ 减	備	考
1	08 財 政 投 融 資
1 財政融資資金勘定	26,961,172,358	26,164,790,723	△ 796,381,635
010 財政融資資金入線入	2 4 年度	2 5 年度	2 6 年度	2 7 年度	2 8 年度
01-95 財政融資資金入線入	予 算 額	15,600,000,000	11,600,000,000	16,600,000,000	(14,000,000,000)	(19,600,000,000)
必要な経費	决 算 額	14,219,999,678	10,699,999,822	13,999,999,835	13,399,999,860	19,599,999,875
不 用 額	1,380,000,322	900,000,178	2,600,000,165	600,000,140	125
「特別会計に関する法律」第64条第1項の規定による財政融資資金入線入れ
95199-	6-22-1000 財政融資資金入線入	12,000,000,000	12,000,000,000	0
020 事 務 取 报 費	5,915,114	5,886,873	△ 28,241	2 4 年度	2 5 年度	2 6 年度	2 7 年度	2 8 年度
予 算 額	5,811,487	5,129,303	5,509,629	(5,648,824)	(5,877,823)
决 算 額	5,090,574	4,722,012	5,097,908	5,462,685	5,592,579
翌年度線越額	-	721	-	-	-
不 用 額	720,913	406,570	412,443	186,139	285,244
2	03-95 事務取扱いに必要な経費	4,148,109	4,187,228	39,119	2 4 年度	2 5 年度	2 6 年度	2 7 年度	2 8 年度
予 算 額	3,961,266	3,685,085	3,999,173	(3,820,131)	(3,965,332)
决 算 額	3,293,663	3,320,993	3,620,879	3,662,424	3,718,553
翌年度線越額	-	721	-	-	-
不 用 額	667,603	363,252	379,016	157,707	246,779
001 管 理 經 費	3,271,649	3,261,434	△ 10,215	2 4 年度	2 5 年度	2 6 年度	2 7 年度	2 8 年度
予 算 額	3,281,991	3,067,005	3,332,745	(3,178,333)	(3,253,881)
001 既定定員に伴う経費	2 4 年度	2 5 年度	2 6 年度	2 7 年度	2 8 年度
予 算 額	3,204,860	2,989,168	3,250,608	(3,099,582)	(3,176,076)
01 人 件 費	3,197,857	3,201,492	3,635
95016-	1-02-0000 職員基本給	1,507,051	1,502,677	△ 4,374
02-0100 職員俸給	1,309,436	1,305,550	△ 3,886	既定分	1,305,550	(1,309,436)
02-0200 扶養手当	40,694	40,640	△ 54	既定分	40,640	(40,694)
02-0300 地域手当	156,921	156,487	△ 434	既定分	156,487	(156,921)
95016-	1-03-0000 職員諸手当	778,045	774,856	△ 3,189