untitled
|
|
- すずり おおふさ
- 5 years ago
- Views:
Transcription
1
2
3 Horioka
4
5
6
7
8
9
10
11
12
13 Nakagawa and Oshima u ( c ) t+ 1 E β (1 + r ) 1 = t i+ 1 u ( c ) t 0 β c t y t uc ( t ) E () t r t c E β t ct γ ( + r ) 1 0 t+ 1 1 = t+ 1 ξ ct + β ct γ c t r ) E β t + 1 t ct (1 + r 1 ( t+ 1 t+ 1 γ )
14 c t + 1 log( β) γe log [ log( )] ( ξ ) ( ξ ) + E + r + E t t 1 t 1 t t 1 Et t+ 1 ct E ( ξ t t 1) = σ + t ε t+ 1 c 1 1 t 1 2 log + log( β ) + log(1 + r ) + σ ε t t t c γ γ γ t 1 σ t 2 log(c t / C t-1 ) = a 1 + a 2 r t-1 + a 3 RISK t-1 + a 4 log(y t / y t-1 ) + v t RISK y
15 C Y R RISK1 RISK2 RISK3 R t-1 RISK1 t-1 RISK2 t-1risk3 t-1 log(x t / X t-1 )log(g t / G t-1 )X G log(c t / C t-1 ) = log(y t / Y t-1 ) R t RISK1 t RISK RISK3 (2.94 *** ) (3.69 *** ) (1.88 * ) (3.45 *** ) (0.34) (2.37 ** ) Adjusted R 2 = S.E.= DW =1.95 ****** 10 SG1 SG2
16 WH YD SH CS SH = f(sg1, SG2, CS, WH, YD) SG2(-48)
17 z t = µ + k i= 1 A i z t-i ε t µ A i ε t k z t = µ + Π z t-1 1 i= 1 Γ i z t-i ε t Π z t-1 Π αβ α β β β β z t-1 βz t-1 = 0 Case 1 Case 2 SH, SG1, SG2, WH, YD SH, SG2, WH, YD
18 Trend stationary linear quadratic cointegration Π cointegration cointegration
19 β β SH = trend SG SG WH YD SH = trend SG SG WH YD
20
21
22 Carlson, J. A. and M. Parkin(1975), Inflation Expectation, Economica 42. Horioka, Charles Yuji (1990) Why is Japan's Household Saving Rates So High? A Literature Survey, Journal of the Japanese and International Economics, Vol.4, No.1 (March 1990) (1989), Why Is Japan's Private Saving Rate So High? in R. Sato and T. Negishi, eds., Developments in Japanese Economics (Tokyo: Academic Press), pp
23
24
25
26
27
28
29 Std. Coef. z P> z Err. SH SH SH SG SG WH YD constant SG1 SG SH SG SG WH YD constant SG2 SG SH SG SG WH YD constant WH WH SH SG SG WH YD constant YD SH SG SG WH YD constant beta Coef. Std. Err. z P> z SH 1 SG SG WH YD trend const
30 SH SH -1 SH SG1 SG2 WH YD const SG1 SG1-1 SH SG1 SG2 WH YD const SG2 SG2-1 SH SG1 SG2 WH YD const WH WH -1 SH SG1 SG2 WH YD const YD -1 SH SG1 SG2 WH YD const
Microsoft Word - Šv”|“Å‘I.DOC
90 ª ª * E-mailshinobu.nakagawa@boj.or.jp i ii iii iv SNA 1 70 80 2 80 90 80 80 90 1 80 90 98 6 1 1 SNA 2 1 SNA 80 1SNA 1 19931998 1 2-190 1,2 2 2-2 2-3,4 3 2-5 4 2030 2-3 3 2-15 97 20 90 2-15 9198 1.
More information遺産相続、学歴及び退職金の決定要因に関する実証分析 『家族関係、就労、退職金及び教育・資産の世代間移転に関する世帯アンケート調査』
2-1. (2-1 ) (2-2 ) (2-3 ) (Hayashi [1986]Dekle [1989]Barthold and Ito [1992] [1996]Campbell [1997] [1998]Shimono and Ishikawa [2002]Shimono and Otsuki [2006] [2008]Horioka [2009]) 1 2-1-1 2-1-1-1 8 (1.
More information研修コーナー
l l l l l l l l l l l α α β l µ l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l
More informationボーナス制度と家計貯蓄率-サーベイ・データによる再検証-
ESRI Discussion Paper Series No.139 by May 2005 Economic and Social Research Instute Cabinet Office Tokyo, Japan * 400 : JEL classification: D12, E21 * 186-8603 2-1 042-580-8369 FAX 042-580-8333 1 Abstract
More informationO1-1 O1-2 O1-3 O1-4 O1-5 O1-6
O1-1 O1-2 O1-3 O1-4 O1-5 O1-6 O1-7 O1-8 O1-9 O1-10 O1-11 O1-12 O1-13 O1-14 O1-15 O1-16 O1-17 O1-18 O1-19 O1-20 O1-21 O1-22 O1-23 O1-24 O1-25 O1-26 O1-27 O1-28 O1-29 O1-30 O1-31 O1-32 O1-33 O1-34 O1-35
More information第86回日本感染症学会総会学術集会後抄録(I)
κ κ κ κ κ κ μ μ β β β γ α α β β γ α β α α α γ α β β γ μ β β μ μ α ββ β β β β β β β β β β β β β β β β β β γ β μ μ μ μμ μ μ μ μ β β μ μ μ μ μ μ μ μ μ μ μ μ μ μ β
More informationVol. 42 No pp Headcount ratio p p A B pp.29
1990 2003 2005 2000 1998 2004 2001 2 2000 2001 2000 1 Vol. 42 No. 2 2005 pp.21-22 25 25-29 30-34 1999 1 Headcount ratio 2 1995 20-25 25-30 2005 p.25 2005 2000 2 15 34 2003 p.3 15 34 A B 3 4 3 3 2003 pp.29-332001
More information1 911 9001030 9:00 A B C D E F G H I J K L M 1A0900 1B0900 1C0900 1D0900 1E0900 1F0900 1G0900 1H0900 1I0900 1J0900 1K0900 1L0900 1M0900 9:15 1A0915 1B0915 1C0915 1D0915 1E0915 1F0915 1G0915 1H0915 1I0915
More informationy = x x R = 0. 9, R = σ $ = y x w = x y x x w = x y α ε = + β + x x x y α ε = + β + γ x + x x x x' = / x y' = y/ x y' =
y x = α + β + ε =,, ε V( ε) = E( ε ) = σ α $ $ β w ( 0) σ = w σ σ y α x ε = + β + w w w w ε / w ( w y x α β ) = α$ $ W = yw βwxw $β = W ( W) ( W)( W) w x x w x x y y = = x W y W x y x y xw = y W = w w
More informationSNAと家計調査における貯蓄率の乖離-日本の貯蓄率低下の要因-
RIETI Discussion Paper Series 10-J-003 RIETI Discussion Paper Series 10-J-003 2009 年 12 月 SNA と家計調査における貯蓄率の乖離 - 日本の貯蓄率低下の要因 - 宇南山卓 ( 神戸大学大学院経済学研究科 ) 要 旨 SNA と家計調査から計算される家計貯蓄率の乖離の原因を明らかにし 日本の貯蓄率の低下の原因を考察した
More information物価変動の決定要因について ― 需給ギャップと物価変動の関係の国際比較を中心に―
NAIRU NAIRU NAIRU GDPGDP NAIRUNon- Accelerating Inflation Rate of Unemployment GDP GDP NAIRU Lown and RichFisher, Mahadeva and Whitley raw materials G NAIRUTurnerFai WatanabeNAIRU Watanabe nested NAIRU
More information(Compton Scattering) Beaming 1 exp [i (k x ωt)] k λ k = 2π/λ ω = 2πν k = ω/c k x ωt ( ω ) k α c, k k x ωt η αβ k α x β diag( + ++) x β = (ct, x) O O x
Compton Scattering Beaming exp [i k x ωt] k λ k π/λ ω πν k ω/c k x ωt ω k α c, k k x ωt η αβ k α x β diag + ++ x β ct, x O O x O O v k α k α β, γ k γ k βk, k γ k + βk k γ k k, k γ k + βk 3 k k 4 k 3 k
More information第11回:線形回帰モデルのOLS推定
11 OLS 2018 7 13 1 / 45 1. 2. 3. 2 / 45 n 2 ((y 1, x 1 ), (y 2, x 2 ),, (y n, x n )) linear regression model y i = β 0 + β 1 x i + u i, E(u i x i ) = 0, E(u i u j x i ) = 0 (i j), V(u i x i ) = σ 2, i
More informationφ 4 Minimal subtraction scheme 2-loop ε 2008 (University of Tokyo) (Atsuo Kuniba) version 21/Apr/ Formulas Γ( n + ɛ) = ( 1)n (1 n! ɛ + ψ(n + 1)
φ 4 Minimal subtraction scheme 2-loop ε 28 University of Tokyo Atsuo Kuniba version 2/Apr/28 Formulas Γ n + ɛ = n n! ɛ + ψn + + Oɛ n =,, 2, ψn + = + 2 + + γ, 2 n ψ = γ =.5772... Euler const, log + ax x
More informationuntitled
IV 1 IV 2 (i) 2 0.13 0.23 1 (i) 3 ( 0.11 0.19 0.5% 2 (ii) 1% (ii) 1,000, 1,000 (1 Q) G A 0.02 {e i ) 1} Q (e 5 1) 0.02 β Ρ (iii) 1 1 QG {e ig ( i G ) 1} QG (e 5 1) Ρ e in e i G n Q e in 1 e i G n 1 1 1
More informationnsg04-28/ky208684356100043077
δ!!! μ μ μ γ UBE3A Ube3a Ube3a δ !!!! α α α α α α α α α α μ μ α β α β β !!!!!!!! μ! Suncus murinus μ Ω! π μ Ω in vivo! μ μ μ!!! ! in situ! in vivo δ δ !!!!!!!!!! ! in vivo Orexin-Arch Orexin-Arch !!
More informations = 1.15 (s = 1.07), R = 0.786, R = 0.679, DW =.03 5 Y = 0.3 (0.095) (.708) X, R = 0.786, R = 0.679, s = 1.07, DW =.03, t û Y = 0.3 (3.163) + 0
7 DW 7.1 DW u 1, u,, u (DW ) u u 1 = u 1, u,, u + + + - - - - + + - - - + + u 1, u,, u + - + - + - + - + u 1, u,, u u 1, u,, u u +1 = u 1, u,, u Y = α + βx + u, u = ρu 1 + ɛ, H 0 : ρ = 0, H 1 : ρ 0 ɛ 1,
More information日本の高齢者世帯の貯蓄行動に関する実証分析
196 2017 * ** ** 1 2 3 JEL Classification Codes D14, D15, E21 Keywords * 28 Hyun- Hoon Lee Robert Owen Kwanho Shin ** 29 196 An Empirical Analysis of the Saving Behavior of Elderly Households in Japan
More informationDP
KEIO UNIVERSITY MARKET QUALITY RESEARCH PROJECT (A 21 st Century Center of Excellence Project) DP2004-13 * ** * ** Graduate School of Economics and Graduate School of Business and Commerce, Keio University
More informationohpmain.dvi
fujisawa@ism.ac.jp 1 Contents 1. 2. 3. 4. γ- 2 1. 3 10 5.6, 5.7, 5.4, 5.5, 5.8, 5.5, 5.3, 5.6, 5.4, 5.2. 5.5 5.6 +5.7 +5.4 +5.5 +5.8 +5.5 +5.3 +5.6 +5.4 +5.2 =5.5. 10 outlier 5 5.6, 5.7, 5.4, 5.5, 5.8,
More information1 1.1 ( ). z = a + bi, a, b R 0 a, b 0 a 2 + b 2 0 z = a + bi = ( ) a 2 + b 2 a a 2 + b + b 2 a 2 + b i 2 r = a 2 + b 2 θ cos θ = a a 2 + b 2, sin θ =
1 1.1 ( ). z = + bi,, b R 0, b 0 2 + b 2 0 z = + bi = ( ) 2 + b 2 2 + b + b 2 2 + b i 2 r = 2 + b 2 θ cos θ = 2 + b 2, sin θ = b 2 + b 2 2π z = r(cos θ + i sin θ) 1.2 (, ). 1. < 2. > 3. ±,, 1.3 ( ). A
More information自由集会時系列part2web.key
spurious correlation spurious regression xt=xt-1+n(0,σ^2) yt=yt-1+n(0,σ^2) n=20 type1error(5%)=0.4703 no trend 0 1000 2000 3000 4000 p for r xt=xt-1+n(0,σ^2) random walk random walk variable -5 0 5 variable
More informationnm (T = K, p = kP a (1atm( )), 1bar = 10 5 P a = atm) 1 ( ) m / m
.1 1nm (T = 73.15K, p = 101.35kP a (1atm( )), 1bar = 10 5 P a = 0.9863atm) 1 ( ).413968 10 3 m 3 1 37. 1/3 3.34.414 10 3 m 3 6.0 10 3 = 3.7 (109 ) 3 (nm) 3 10 6 = 3.7 10 1 (nm) 3 = (3.34nm) 3 ( P = nrt,
More information医系の統計入門第 2 版 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 第 2 版 1 刷発行時のものです.
医系の統計入門第 2 版 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. http://www.morikita.co.jp/books/mid/009192 このサンプルページの内容は, 第 2 版 1 刷発行時のものです. i 2 t 1. 2. 3 2 3. 6 4. 7 5. n 2 ν 6. 2 7. 2003 ii 2 2013 10 iii 1987
More information総合薬学講座 生物統計の基礎
2013 10 22 ( ) 2013 10 22 1 / 40 p.682 1. 2. 3 2 t Mann Whitney U ). 4 χ 2. 5. 6 Dunnett Tukey. 7. 8 Kaplan Meier.. U. ( ) 2013 10 22 2 / 40 1 93 ( 20 ) 230. a t b c χ 2 d 1.0 +1.0 e, b ( ) e ( ) ( ) 2013
More information財政赤字の経済分析:中長期的視点からの考察
1998 1999 1998 1999 10 10 1999 30 (1982, 1996) (1997) (1977) (1990) (1996) (1997) (1996) Ihori, Doi, and Kondo (1999) (1982) (1984) (1987) (1993) (1997) (1998) CAPM 1980 (time inconsistency) Persson, Persson
More information,398 4% 017,
6 3 JEL Classification: D4; K39; L86,,., JSPS 34304, 47301.. 1 01301 79 1 7,398 4% 017,390 01 013 1 1 01 011 514 8 1 Novos and Waldman (1984) Johnson (1985) Chen and Png (003) Arai (011) 3 1 4 3 4 5 0
More informationCOE-RES Discussion Paper Series Center of Excellence Project The Normative Evaluation and Social Choice of Contemporary Economic Systems Graduate Scho
COE-RES Discussion Paper Series Center of Excellence Project The Normative Evaluation and Social Choice of Contemporary Economic Systems Graduate School of Economics and Institute of Economic Research
More information税制改正にともなう家計の所得弾性値 : 高齢者パネルデータによる実証分析
Kwansei Gakuin University Rep Title Author(s) 税制改正にともなう家計の所得弾性値 : 高齢者パネルデータによる実証分析 Uemura, Toshiyuki, 上村, 敏之 ; Kitamura Takayuki, 金田, 陸幸 Citation 経済学論究, 69(4): 1-16 Issue Date 2016-3-20 URL http://hdl.handle.net/10236/14671
More information_0212_68<5A66><4EBA><79D1>_<6821><4E86><FF08><30C8><30F3><30DC><306A><3057><FF09>.pdf
More information
1).1-5) - 9 -
- 8 - 1).1-5) - 9 - ε = ε xx 0 0 0 ε xx 0 0 0 ε xx (.1 ) z z 1 z ε = ε xx ε x y 0 - ε x y ε xx 0 0 0 ε zz (. ) 3 xy ) ε xx, ε zz» ε x y (.3 ) ε ij = ε ij ^ (.4 ) 6) xx, xy ε xx = ε xx + i ε xx ε xy = ε
More information01.Œk’ì/“²fi¡*
AIC AIC y n r n = logy n = logy n logy n ARCHEngle r n = σ n w n logσ n 2 = α + β w n 2 () r n = σ n w n logσ n 2 = α + β logσ n 2 + v n (2) w n r n logr n 2 = logσ n 2 + logw n 2 logσ n 2 = α +β logσ
More informationH 0 H = H 0 + V (t), V (t) = gµ B S α qb e e iωt i t Ψ(t) = [H 0 + V (t)]ψ(t) Φ(t) Ψ(t) = e ih0t Φ(t) H 0 e ih0t Φ(t) + ie ih0t t Φ(t) = [
3 3. 3.. H H = H + V (t), V (t) = gµ B α B e e iωt i t Ψ(t) = [H + V (t)]ψ(t) Φ(t) Ψ(t) = e iht Φ(t) H e iht Φ(t) + ie iht t Φ(t) = [H + V (t)]e iht Φ(t) Φ(t) i t Φ(t) = V H(t)Φ(t), V H (t) = e iht V (t)e
More informations s U s L e A = P A l l + dl dε = dl l l
P (ε) A o B s= P A s B o Y l o s Y l e = l l 0.% o 0. s e s B 1 s (e) s Y s s U s L e A = P A l l + dl dε = dl l l ε = dε = l dl o + l lo l = log l o + l =log(1+ e) l o Β F Α E YA C Ο D ε YF B YA A YA
More informationAuerbach and Kotlikoff(1987) (1987) (1988) 4 (2004) 5 Diamond(1965) Auerbach and Kotlikoff(1987) 1 ( ) ,
,, 2010 8 24 2010 9 14 A B C A (B Negishi(1960) (C) ( 22 3 27 ) E-mail:fujii@econ.kobe-u.ac.jp E-mail:082e527e@stu.kobe-u.ac.jp E-mail:iritani@econ.kobe-u.ac.jp 1 1 1 2 3 Auerbach and Kotlikoff(1987) (1987)
More information微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 初版 1 刷発行時のものです.
微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. ttp://www.morikita.co.jp/books/mid/00571 このサンプルページの内容は, 初版 1 刷発行時のものです. i ii 014 10 iii [note] 1 3 iv 4 5 3 6 4 x 0 sin x x 1 5 6 z = f(x, y) 1 y = f(x)
More information3/4/8:9 { } { } β β β α β α β β
α β : α β β α β α, [ ] [ ] V, [ ] α α β [ ] β 3/4/8:9 3/4/8:9 { } { } β β β α β α β β [] β [] β β β β α ( ( ( ( ( ( [ ] [ ] [ β ] [ α β β ] [ α ( β β ] [ α] [ ( β β ] [] α [ β β ] ( / α α [ β β ] [ ] 3
More informationTitle 最適年金の理論 Author(s) 藤井, 隆雄 ; 林, 史明 ; 入谷, 純 ; 小黒, 一正 Citation Issue Date Type Technical Report Text Version publisher URL
Title 最適年金の理論 Author(s) 藤井, 隆雄 ; 林, 史明 ; 入谷, 純 ; 小黒, 一正 Citation Issue 2012-06 Date Type Technical Report Text Version publisher URL http://hdl.handle.net/10086/23085 Right Hitotsubashi University Repository
More informationD = [a, b] [c, d] D ij P ij (ξ ij, η ij ) f S(f,, {P ij }) S(f,, {P ij }) = = k m i=1 j=1 m n f(ξ ij, η ij )(x i x i 1 )(y j y j 1 ) = i=1 j
6 6.. [, b] [, d] ij P ij ξ ij, η ij f Sf,, {P ij } Sf,, {P ij } k m i j m fξ ij, η ij i i j j i j i m i j k i i j j m i i j j k i i j j kb d {P ij } lim Sf,, {P ij} kb d f, k [, b] [, d] f, d kb d 6..
More informationN cos s s cos ψ e e e e 3 3 e e 3 e 3 e
3 3 5 5 5 3 3 7 5 33 5 33 9 5 8 > e > f U f U u u > u ue u e u ue u ue u e u e u u e u u e u N cos s s cos ψ e e e e 3 3 e e 3 e 3 e 3 > A A > A E A f A A f A [ ] f A A e > > A e[ ] > f A E A < < f ; >
More information基礎数学I
I & II ii ii........... 22................. 25 12............... 28.................. 28.................... 31............. 32.................. 34 3 1 9.................... 1....................... 1............
More information* n x 11,, x 1n N(µ 1, σ 2 ) x 21,, x 2n N(µ 2, σ 2 ) H 0 µ 1 = µ 2 (= µ ) H 1 µ 1 µ 2 H 0, H 1 *2 σ 2 σ 2 0, σ 2 1 *1 *2 H 0 H
1 1 1.1 *1 1. 1.3.1 n x 11,, x 1n Nµ 1, σ x 1,, x n Nµ, σ H 0 µ 1 = µ = µ H 1 µ 1 µ H 0, H 1 * σ σ 0, σ 1 *1 * H 0 H 0, H 1 H 1 1 H 0 µ, σ 0 H 1 µ 1, µ, σ 1 L 0 µ, σ x L 1 µ 1, µ, σ x x H 0 L 0 µ, σ 0
More information202
202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 DS =+α log (Spread )+ β DSRate +γlend +δ DEx DS t Spread t 1 DSRate t Lend t DEx DS DEx Spread DS
More informationAutumn II III Zon and Muysken 2005 Zon and Muysken 2005 IV II 障害者への所得移転の経済効果 分析に用いるデータ
212 Vol. 44 No. 2 I はじめに 2008 1 2 Autumn 08 213 II III Zon and Muysken 2005 Zon and Muysken 2005 IV II 障害者への所得移転の経済効果 17 18 1 分析に用いるデータ 1 2005 10 12 200 2 2006 9 12 1 1 2 129 35 113 3 1 2 6 1 2 3 4 4 1
More information高齢化とマクロ投資比率―国際パネルデータを用いた分析―
196 2017 * ** ** ** ** 160 2 2 JEL Classification Codes E21, E22, J11 Keywords * ESRI 28 ESRI 29 3 17 ESRI ** 115 196 Population Aging and Domestic Investment An Analysis Using International Panel Data
More informationタイトル
Flud Flow Smulton wth Cellulr Automt 00N2100008J 2002 225 1. cellulr utomton n t+ 1 t t = f( r, L, + r (1 t t+ 1 f t r t +1 Prllel Vrtul Mchne Messge-Pssng Interfce 1 2. 2. 1 t t 0 t = 1 = 1 = t = 2 2
More informationII III II 1 III ( ) [2] [3] [1] 1 1:
2015 4 16 1. II III II 1 III () [2] [3] 2013 11 18 [1] 1 1: [5] [6] () [7] [1] [1] 1998 4 2008 8 2014 8 6 [1] [1] 2 3 4 5 2. 2.1. t Dt L DF t A t (2.1) A t = Dt L + Dt F (2.1) 3 2 1 2008 9 2008 8 2008
More informationL Y L( ) Y0.15Y 0.03L 0.01L 6% L=(10.15)Y 108.5Y 6%1 Y y p L ( 19 ) [1990] [1988] 1
1. 1-1 00 001 9 J-REIT 1- MM CAPM 1-3 [001] [1997] [003] [001] [1999] [003] 1-4 0 . -1 18 1-1873 6 1896 L Y L( ) Y0.15Y 0.03L 0.01L 6% L=(10.15)Y 108.5Y 6%1 Y y p L 6 1986 ( 19 ) -3 17 3 18 44 1 [1990]
More information,,,17,,, ( ),, E Q [S T F t ] < S t, t [, T ],,,,,,,,
14 5 1 ,,,17,,,194 1 4 ( ),, E Q [S T F t ] < S t, t [, T ],,,,,,,, 1 4 1.1........................................ 4 5.1........................................ 5.........................................
More information1 Nelson-Siegel Nelson and Siegel(1987) 3 Nelson-Siegel 3 Nelson-Siegel 2 3 Nelson-Siegel 2 Nelson-Siegel Litterman and Scheinkman(199
Nelson-Siegel Nelson-Siegel 1992 2007 15 1 Nelson and Siegel(1987) 2 FF VAR 1996 FF B) 1 Nelson-Siegel 15 90 1 Nelson and Siegel(1987) 3 Nelson-Siegel 3 Nelson-Siegel 2 3 Nelson-Siegel 2 Nelson-Siegel
More informationchap9.dvi
9 AR (i) (ii) MA (iii) (iv) (v) 9.1 2 1 AR 1 9.1.1 S S y j = (α i + β i j) D ij + η j, η j = ρ S η j S + ε j (j =1,,T) (1) i=1 {ε j } i.i.d(,σ 2 ) η j (j ) D ij j i S 1 S =1 D ij =1 S>1 S =4 (1) y j =
More informationKEIRIN
KEIRIN KEIRIN PCOSS CIO PC PC OSS OSS 2003 CIO 2003 IT IT 2006 2006 IT IT IT IT 2008 2008 IT IT 2001 2001 5IT IT 5IT IT IT IT (NGN) Web2.0 (NGN) Web2.0 2005 IT CIO 2005 2005 IT CIO 2006 CIOIT IT SE 2006
More informationスケーリング理論とはなにか? - --尺度を変えて見えること--
? URL: http://maildbs.c.u-tokyo.ac.jp/ fukushima mailto:hukusima@phys.c.u-tokyo.ac.jp DEX-SMI @ 2006 12 17 ( ) What is scaling theory? DEX-SMI 1 / 40 Outline Outline 1 2 3 4 ( ) What is scaling theory?
More information( )
) ( ( ) 3 15m t / 1.9 3 m t / 0.64 3 m ( ) ( ) 3 15m 3 1.9m / t 0.64m 3 / t ) ( β1 β 2 β 3 y ( ) = αx1 X 2 X 3 ( ) ) ( ( ) 3 15m t / 1.9 3 m 3 90m t / 0.64 3 m ( ) : r : ) 30 ( 10 0.0164
More information朕醩佑宖醸æ−žã†®ã†�ã‡†ã†®æ··å’‹æŁ´æŁ°è¨‹çfl»ã…¢ã…⁄ã…«
1 / 34 Li-Yao,, Li-Yao The Life-Cycle Effects of House Price Changes (Li-Yao ),,,, ( ) 1 ω ( ) ω 1 γ Ct Ht t T βt U(C t, H t, N t) = N t N t t T βt N t 1 γ H t : t C t : t β : ω : γ : W. Li, R. Yao, The
More informationuntitled
2 book conference 1990 2003 14 Repeated Cross-Section Data 1 M1,M2 M1 Sekine(1998) Repeated Cross-Section Data 1 1. (1989), Yoshida and Rasche(1990), Rasche(1990), 19921997, Fujiki and Mulligan(1996),
More informationアジ研教科書「マクロ安定化」.PDF
1 2 3 4 5 6 7 8 9 Corbo, V., and S. Fischer, Structural Adjustment, Stabilization and Policy Reform: Domestic and International Finance, in J. Behrman and T. N. Srinivasan, eds., Handbook of Development
More information23 1 Section ( ) ( ) ( 46 ) , 238( 235,238 U) 232( 232 Th) 40( 40 K, % ) (Rn) (Ra). 7( 7 Be) 14( 14 C) 22( 22 Na) (1 ) (2 ) 1 µ 2 4
23 1 Section 1.1 1 ( ) ( ) ( 46 ) 2 3 235, 238( 235,238 U) 232( 232 Th) 40( 40 K, 0.0118% ) (Rn) (Ra). 7( 7 Be) 14( 14 C) 22( 22 Na) (1 ) (2 ) 1 µ 2 4 2 ( )2 4( 4 He) 12 3 16 12 56( 56 Fe) 4 56( 56 Ni)
More information1 Tokyo Daily Rainfall (mm) Days (mm)
( ) r-taka@maritime.kobe-u.ac.jp 1 Tokyo Daily Rainfall (mm) 0 100 200 300 0 10000 20000 30000 40000 50000 Days (mm) 1876 1 1 2013 12 31 Tokyo, 1876 Daily Rainfall (mm) 0 50 100 150 0 100 200 300 Tokyo,
More informationnewmain.dvi
数論 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. http://www.morikita.co.jp/books/mid/008142 このサンプルページの内容は, 第 2 版 1 刷発行当時のものです. Daniel DUVERNEY: THÉORIE DES NOMBRES c Dunod, Paris, 1998, This book is published
More information02.„o“φiflì„㙃fic†j
X-12-ARIMA Band-PassDECOMP HP X-12-ARIMADECOMP HPBeveridge and Nelson DECOMP X-12-ARIMA Band-PassHodrick and PrescottHP DECOMPBeveridge and Nelson M CD X ARIMA DECOMP HP Band-PassDECOMP Kiyotaki and Moore
More information1 (1) () (3) I 0 3 I I d θ = L () dt θ L L θ I d θ = L = κθ (3) dt κ T I T = π κ (4) T I κ κ κ L l a θ L r δr δl L θ ϕ ϕ = rθ (5) l
1 1 ϕ ϕ ϕ S F F = ϕ (1) S 1: F 1 1 (1) () (3) I 0 3 I I d θ = L () dt θ L L θ I d θ = L = κθ (3) dt κ T I T = π κ (4) T I κ κ κ L l a θ L r δr δl L θ ϕ ϕ = rθ (5) l : l r δr θ πrδr δf (1) (5) δf = ϕ πrδr
More informationglobal imbalances ) * 1
global imbalances 2 3 45 6 1) * 1 68 53 Denison 1958 2 Denison 1958 Feldstein and Fane 1973 1946 1968 Feldstein 19731978 David and Scadding 1974Furstenberg 1981Pitelis 1987 Poterba 1986 1948 1986 Bhatia
More information2.2 h h l L h L = l cot h (1) (1) L l L l l = L tan h (2) (2) L l 2 l 3 h 2.3 a h a h (a, h)
1 16 10 5 1 2 2.1 a a a 1 1 1 2.2 h h l L h L = l cot h (1) (1) L l L l l = L tan h (2) (2) L l 2 l 3 h 2.3 a h a h (a, h) 4 2 3 4 2 5 2.4 x y (x,y) l a x = l cot h cos a, (3) y = l cot h sin a (4) h a
More information日本の世帯属性別貯蓄率の動向について:アップデートと考察
RIETI Discussion Paper Series 18-J-024 RIETI Discussion Paper Series 18-J-024 2018 年 8 日本の世帯属性別貯蓄率の動向について : アップデートと考察 1 宇南 卓 ( 経済産業研究所 ) 野太郎 ( 信州 学 ) 要 旨 全国消費実態調査 家計調査 家計消費状況調査を補完的に利用することでマクロ統計と整合的な貯蓄率のデータを構築した宇南山
More informationTwist knot orbifold Chern-Simons
Twist knot orbifold Chern-Simons 1 3 M π F : F (M) M ω = {ω ij }, Ω = {Ω ij }, cs := 1 4π 2 (ω 12 ω 13 ω 23 + ω 12 Ω 12 + ω 13 Ω 13 + ω 23 Ω 23 ) M Chern-Simons., S. Chern J. Simons, F (M) Pontrjagin 2.,
More information杏香は2000年5月16日午前5時15分に横浜市立市民病院で生まれた
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 http://opac.ndl.go.jp/process NDL-OPAC2009 2 11 P12 19 2000 10 P19 2008 10 9 2008 3 PP14 17 20 2001 PP470 473 2007 PP81 176 1972 P86 2002 PP346 348 1982 P162
More information