Dynamics in Real Estate Market Reitaku-University 不動産価格変動のダイナミクス -マイクロ構造とマクロトレンド- 麗澤大学経済学部・准教授 清水千弘(Chihiro SHIMIZU) 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 1 2009/11/04 2008/05 2007/09 2007/01 2006/05 2005/09 2005/01 2004/05 2003/09 2003/01 2002/05 2001/09 2001/01 2000/05 1999/09 250.0 1999/01 1998/05 1997/09 1997/01 1996/05 1995/09 1995/01 1994/05 1993/09 1993/01 1992/05 1991/09 1991/01 1990/05 1989/09 1989/01 1988/05 1987/09 1987/01 1986/05 1985/09 1985/01 1984/05 1983/09 1983/01 Dynamics in Real Estate Market Reitaku-University 主要都市における住宅価格変動の因果性 300.0 Tokyo_Condo Tokyo_SingleHouse LosAngeles NewYork London HongKong Melbourne 200.0 150.0 100.0 50.0 0.0 page. 2 Dynamics in Real Estate Market Reitaku-University International property cycles - Speed of adjustment Capital index, December 2002 = 100 150 Australia 140 130 Japan US UK 120 110 100 90 80 12/02 6/03 12/03 6/04 12/04 6/05 12/05 6/06 12/06 6/07 12/07 6/08 12/08 6/09 12/09 2009/11/04 page. 3 Y1985Q1 Y1985Q3 Y1986Q1 Y1986Q3 Y1987Q1 Y1987Q3 Y1988Q1 Y1988Q3 Y1989Q1 Y1989Q3 Y1990Q1 Y1990Q3 Y1991Q1 Y1991Q3 Y1992Q1 Y1992Q3 Y1993Q1 Y1993Q3 Y1994Q1 Y1994Q3 Y1995Q1 Y1995Q3 Y1996Q1 Y1996Q3 Y1997Q1 Y1997Q3 Y1998Q1 Y1998Q3 Y1999Q1 Y1999Q3 Y2000Q1 Y2000Q3 Y2001Q1 Y2001Q3 Y2002Q1 Y2002Q3 Y2003Q1 Y2003Q3 Y2004Q1 Y2004Q3 Y2005Q1 Y2005Q3 Y2006Q1 Y2006Q3 Y2007Q1 Y2007Q3 Y2008Q1 Y2008Q3 Y2009Q1 Dynamics in Real Estate Market 1 2009/11/04 Reitaku-University 東京都区部のオフィス・住宅市場の動向 1.2 Office Residential 0.8 0.6 0.4 0.2 0 page. 4 Dynamics in Real Estate Market Reitaku-University 不動産市場分析:不動産市場を科学する • 1.ミクロ分析とマクロ分析 • ミクロ分析:各経済主体の行動を分析 • マクロ分析:市場の変動を分析し，予測する • 2.経済モデルと計量分析 • 理論経済モデルとは? • 検証的分析と探索的分析 • 3.探索的分析(地価動向指標)の問題と予測の失敗 • (Grammar of Science) • 予測ができるのか? • 市場の効率性の理解 2009/11/04 Chihiro SHIMIZU 2008 [email protected] page. 5 Dynamics in Real Estate Market Reitaku-University 本日のご報告: • 1.不動産市場のダイナミクス • 2.不動産市場の効率性 • 3.賃貸料市場の変化-マイクロストラクチャ• 4.キャップレートの決定構造 • 5.社会構造の変化と不動産価格 • 6.公示地価への教訓 2009/11/04 page. 6 Dynamics in Real Estate Market Reitaku-University 1. 不動産市場のダイナミクス 賃貸料(ドル) 資産市場: 価格評価 P= 賃貸市場: 賃貸料決定 R i D (R , Economy) = S ストック (平方フィート) 価格(ドル) P = f (C ) C δ (ΔS = C－δS ) S= 資産市場： 建築着工 建築着工 (平方フィート) 賃貸市場: ストック調整 Source:Denise Dipasquale,William Wheaton(1996).,Urban Economics and Real Estate Markets 2009/11/04 Chihiro SHIMIZU 2008 [email protected] page. 7 Dynamics in Real Estate Market Reitaku-University GDPとSNA土地資産額の推移 600,000 2006 500,000 1990 GDP:10億円 400,000 1985 300,000 1980 200,000 1975 100,000 1970 0 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 SNA土地資産額:10億円 2009/11/04 page. 8 Dynamics in Real Estate Market Reitaku-University Gordon Growth Model: 資産価格とは? 不動産価値の決まり方 yit pit R ft R pi G • • • • 経済活動/需給 キャップ・レート Yit : 費用控除後の賃料収益 Rf : 安全資産の投資利回り Rp : リスク・プレミアム G : 収益のマクロ的な上昇率 Rp f L( zi ),ξ • L : 流動性リスク • ξ:予期できぬリスク 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 9 Dynamics in Real Estate Market Reitaku-University 長期的な期待:人口は減少していく (千人) 140,000 130,000 120,000 110,000 100,000 90,000 80,000 70,000 60,000 2050 2040 2038 2036 2034 2032 2030 2028 2026 2024 2022 2020 2018 2016 2014 2012 2010 2008 2006 2004 2002 2000 50,000 出典：国立社会保障・人口問題研究所『日本の将来推計人口』（平成14年１月推計） による各年10月1日現在の推計人口より 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 10 Dynamics in Real Estate Market Reitaku-University 団塊世代のリタイアとオフィス市場 日本の人口ピラミッド（中位推計） 1 0 年後（2 0 1 5 年） 現在（2 0 0 5 年） （歳） 100 （歳） 100 90 90 80 80 70 70 60 60 団塊世代 50 50 男 男 女 女 団塊Jr ・ポスト団塊Jｒ 30 30 20 20 10 10 0 0 100 80 60 40 20 0 団塊Jr ・ポスト団塊Jｒ 40 40 120 団塊世代 0 20 40 60 80 100 120 （万人） 120 100 80 60 40 20 0 0 20 40 60 80 100 120 （万人） 出所）国立社会保障・人口問題研究所 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 11 1955.9 1956.9 1957.9 1958.9 1959.9 1960.9 1961.9 1962.9 1963.9 1964.9 1965.9 1966.9 1967.9 1968.9 1969.9 1970.9 1971.9 1972.9 1973.9 1974.9 1975.9 1976.9 1977.9 1978.9 1979.9 1980.9 1981.9 1982.9 1983.9 1984.9 1985.9 1986.9 1987.9 1988.9 1989.9 1990.9 1991.9 1992.9 1993.9 1994.9 1995.9 1996.9 1997.9 1998.9 1999.9 2000.9 2001.9 2002.9 2003.9 2004.9 2005.9 2006.9 2007.9 2008.9 対前年同期変動率(%) Dynamics in Real Estate Market 2009/11/04 Reitaku-University 高度経済成長・列島改造・国際都市化・ファンドバブル 100 六大都市 工業地 80 六大都市 商業地 六大都市 住宅地 六大都市 工業地 60 六大都市 全用途平均 六大都市 住宅地 六大都市 商業地 40 六大都市 全用途平均 20 0 -20 -40 （注１）六大都市とは，東京都区部，横浜，名古屋，京都，大阪および神戸をいう。 （注２）市街地価格指数の変動率は各年3 月時点の前年同期比を用いている。 （出典）財団法人 日本不動産研究所 「市街地価格指数」 Chihiro SHIMIZU 2009 [email protected] page. 12 Dynamics in Real Estate Market Reitaku-University 日本の地価の長期動向: ECM推定結果 0.20 (ECM残差) 予測地価(t+1期) 0.15 地代(GDP) 資金コスト 0.10 誤差修正項 d(ln_lp) 0.05 0.00 -0.05 -0.10 2008 2005 2002 1999 1996 1993 1990 1987 1984 1981 1978 1975 1972 1969 1966 1963 1960 1957 -0.15 入門計量経済学B 第13回講義ノートより 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 13 Dynamics in Real Estate Market Reitaku-University 2.日本の不動産市場は効率的か • 効率性の検証 – 疑問１： 短期的に効率的か？ ① uc一定のもとでの超過収益率の系列相関 Pi ,t 1 Pit Rit reit Pit ② 時変的なucのもとでの予測誤差の系列相関 eit Pi ,t 1 Rit Pit 1 ucit – 検定方法 xit i 0 i1xi ,t 1 i 2 xi ,t 2 i 3 xi ,t 3 it においてAR項の同時除外仮説を検定 2009/11/04 井上・清水・中神(2009) page. 14 Dynamics in Real Estate Market Reitaku-University • 効率性の検証結果1： 短期的効率性① 2.4 1.6 0.8 test1 2009/11/04 井上・清水・中神(2009) 0 20km page. 15 Dynamics in Real Estate Market Reitaku-University • 効率性の検証結果2： 短期的効率性② 2.4 1.6 0.8 test2 2009/11/04 井上・清水・中神(2009) 0 20km page. 16 Dynamics in Real Estate Market Reitaku-University – 疑問２： 長期的に効率的か？ • 長期的に効率的ならば，変数間に共和分関係 が存在するはずである eit Pi ,t 1 Rit Pit 1 ucit • 単位根検定を用いて検証 • 結果： 72市区中，68市区が1％水準で，残りの 4市区が5％水準で定常 2009/11/04 井上・清水・中神(2009) page. 17 Dynamics in Real Estate Market Reitaku-University – マンションの市場価格と理論値 1 2 60 60 50 50 40 40 30 30 20 20 4 12 80 13 50 60 40 30 40 90 95 00 05 17 60 40 20 90 95 00 05 10 90 95 22 60 80 60 40 60 40 20 40 00 05 90 95 00 05 90 95 26 00 90 95 00 05 100 95 95 00 05 80 60 60 20 95 00 05 90 95 00 05 20 90 95 00 05 14 3 05 100 80 80 60 60 40 40 95 00 05 0 90 95 00 05 95 00 05 160 120 120 95 00 95 00 00 05 40 90 95 00 05 15 4 95 00 05 80 40 60 60 40 60 20 40 40 40 0 90 16 1 95 00 05 20 90 1 62 95 00 05 160 95 00 05 95 00 95 00 17 0 20 95 00 05 90 80 60 60 95 00 05 40 40 90 95 00 05 95 00 05 20 80 20 90 19 3 95 00 05 20 90 1 94 00 05 90 95 95 00 05 95 00 80 60 60 40 40 160 160 120 120 80 05 05 00 05 00 05 00 05 00 05 00 05 00 05 40 0 90 95 00 05 90 15 0 00 05 95 00 05 95 1 51 160 120 120 80 60 30 50 20 40 10 30 0 20 95 00 00 05 90 95 0 95 00 05 90 05 40 0 90 95 00 05 90 15 9 95 1 60 80 80 60 40 60 80 40 60 20 40 95 00 95 00 05 95 00 05 95 00 05 90 100 100 80 80 60 60 60 40 40 20 20 90 95 00 05 40 20 90 95 00 05 90 19 1 100 100 80 80 80 60 60 60 40 40 40 20 90 20 3 95 00 05 20 90 2 04 95 00 05 90 20 6 80 80 80 80 60 60 60 60 60 40 40 40 40 40 20 20 20 20 95 00 05 90 95 00 05 90 95 00 05 95 2 07 80 90 95 1 92 100 05 95 1 69 80 1 82 00 95 16 8 20 90 20 90 100 05 20 90 20 90 17 8 20 0 00 05 1 67 20 90 05 00 100 16 6 40 19 6 40 90 95 95 20 90 60 RP 2009/11/04 00 95 1 42 40 90 80 05 0 90 19 5 20 95 95 90 200 1 58 40 90 05 40 90 50 90 17 7 100 40 20 00 80 60 40 95 14 1 200 20 90 17 3 60 40 00 20 90 40 20 17 2 80 60 05 250 40 0 1 71 80 05 60 60 20 90 60 00 80 15 7 80 40 40 80 95 1 49 100 60 40 05 90 05 40 00 20 50 90 05 120 60 80 80 95 40 20 100 16 5 80 100 90 60 150 40 16 4 120 120 20 00 100 20 90 16 3 100 80 95 94 40 200 15 6 80 100 90 60 80 15 5 80 05 05 40 200 120 90 100 00 00 87 1 40 160 20 90 80 95 95 60 05 40 40 95 100 90 20 90 80 14 8 60 80 60 20 05 80 300 05 80 80 60 00 80 13 9 120 100 80 90 14 7 120 120 95 150 90 05 05 0 14 6 160 1 53 00 90 84 100 90 120 95 00 0 90 160 90 05 100 15 2 0 95 50 14 5 20 90 90 150 100 80 20 00 100 1 44 100 95 20 200 200 20 00 90 13 8 300 40 95 20 80 13 7 80 90 10 60 40 20 100 20 90 40 20 80 60 10 5 40 30 100 60 60 40 40 20 40 1 00 80 30 60 83 80 80 20 90 80 05 40 0 50 81 60 20 60 40 40 0 24 80 19 50 100 20 20 21 18 120 20 90 95 00 05 90 95 P _S TA R_NORM 井上・清水・中神(2009) page. 18 Dynamics in Real Estate Market Reitaku-University 3.賃貸料市場の変化-マイクロストラクチャ3.5 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 19 QT2006/1 QT2004/1 QT2002/1 QT2000/1 3. The most important link between asset prices and goods & services prices is the one 1.0 through housing rents (Goodhart 2001) QT1998/1 1.5 QT1996/1 The probability of no change in housing rents is about 29 percent per year (Genesove 2003) QT1994/1 – 2.0 QT1992/1 2. Housing rents are very, very sticky 2.5 QT1990/1 26.3% 5.8% 18.6% 1.9% 3.0 QT1988/1 Expenditures for housing services: Housing rents: Imputed rents from owner occupied housing: Housing maintenance and others: “Consumer Price Index (CPI) in Tokyo, 2005” CPI rent Selling price index QT1986/1 1. Housing rents account for more than one fourth of personal spending 198601 198607 198701 198707 198801 198807 198901 198907 199001 199007 199101 199107 199201 199207 199301 199307 199401 199407 199501 199507 199601 199607 199701 199707 199801 199807 199901 199907 200001 200007 200101 200107 200201 200207 200301 200307 200401 200407 200501 200507 200601 200607 200701 200707 200801 200807 Dynamics in Real Estate Market 3.0 2009/11/04 Reitaku-University Comparison House Price and CPI-house in Tokyo 3.5 Tokyo_Condo Tokyo_SingleHouse Tokyo_SingleHouse_Rent 2.5 Tokyo_CPI 2.0 1.5 1.0 0.5 0.0 page. 20 198603 198609 198703 198709 198803 198809 198903 198909 199003 199009 199103 199109 199203 199209 199303 199309 199403 199409 199503 199509 199603 199609 199703 199709 199803 199809 199903 199909 200003 200009 200103 200109 200203 200209 200303 200309 200403 200409 200503 200509 200603 200609 200703 200709 200803 200809 Dynamics in Real Estate Market 4.000 3.500 2009/11/04 Reitaku-University Comparison House Price and CPI-house in Tokyo , LA, NY 5.000 4.500 Tokyo_SingleHouse LosAngeles_HP NewYork_HP Tokyo_CPI LosAngeles_CPI NewYork_CPI 3.000 2.500 2.000 1.500 1.000 0.500 0.000 page. 21 Dynamics in Real Estate Market Reitaku-University New Rent versus CPI Rent 2009/11/04 page. 22 Dynamics in Real Estate Market Reitaku-University Frequency of Rent Adjustments Rit Rit Rit1 P r(Rit 0) 1 P r( I 1) P r( I 1) N it R it P r(Rit 0 | I itN 1) P r( I itN 1) P r(Rit 0 | I 1) P r( I 1) R it 2009/11/04 R it page. 23 Dynamics in Real Estate Market Reitaku-University State-Dependent or Time-Dependent Pricing: Caballero-Engel’s definition of price flexibility log Rit* t it X it log Rit 1 log Rit* Caballero-Engel(1993) :Adjustment Hazard ( x) Pr(Rit 0 | X it x) log Rt t 0 t lim Caballero-Engel’s measure of price flexibility ( x)h( x)dx Intensive margin x ' ( x)h( x)dx Extensive margin Caballero-Engel(2007) ( x) Pr(Rit 0 | I itN 1, X it x) Pr( I itN 1 | X it x) Pr(Rit 0 | I itR 1, X it x) Pr( I itR 1 | X it x) 2009/11/04 page. 24 Dynamics in Real Estate Market Reitaku-University Adjustment Hazard Functions x (0.4,0.2] x (0.2,0.0] x (0.0,0.2] x (0.2,0.4] Pr( I itN 1 | X it x) 0.010 0.010 0.010 0.010 Pr( I itR 1 | X it x) 0.042 0.042 0.042 0.042 Pr(Rit 0 | I itN 1, X it x) 0.736 0.680 0.688 0.719 Pr(Rit 0 | I itR 1, X it x) 0.000 0.009 0.038 0.091 (x) 0.008 0.007 0.008 0.011 h(x) 0.082 0.312 0.348 0.161 Intensive margin: ( x)h( x)dx 0.0084 Extensive margin: x' ( x)h( x)dx 0.0013 2009/11/04 Caballero-Engel’s measure of price flexibility log Rt 0.0097 t 0 t lim page. 25 Dynamics in Real Estate Market Reitaku-University Micro-Macro Consistency : Calvo Parameter 1.45 1.40 R^{*} R CPI rent 1.35 1.30 0 0.032 ( s.e. 0.004) 2009/11/04 1.10 1.05 QT2006/1 QT2004/1 QT2000/1 QT1998/1 QT1996/1 QT1994/1 1.00 QT1992/1 Rt* Hedonic rent 1.15 QT1990/1 Rt CPI rent 1.20 QT1988/1 Rt log Rit di Rt* log Rit* di 1.25 QT1986/1 Rt (1 0 ) Rt 1 0 Rt* QT2002/1 ( x) 0 Micro estimate: 0.975 Macro estimate: 0.968 page. 26 Dynamics in Real Estate Market Reitaku-University 4.キャップレートの決定構造 • Jorgenson’s Theorem : Capital, Investment Behavior • Neoclassical theory is the response of the demand for capital to changes in relative factor prices or the ratio of factor prices to the price of output. • User cost / Yield • Capital Depreciation Problem • • 2009/11/04 Jorgenson, D. W. (1963), "Capital Theory and Investment Behavior," American Economic Review, 53, pp.247-259. Hayashi, F., and T. Inoue (1991), “The relation between firm growth and Q with multiple capital goods: Theory and evidence from panel data on Japanese firms,” Econometrica, pp.731–753. Chihiro SHIMIZU 2009 [email protected] page. 27 Dynamics in Real Estate Market Reitaku-University Stock Market vs. Asset Market 5.00% Stock CR Real CR 4.50% 4.00% 3.50% 3.00% 2.50% 2009/11/04 [email protected] 2008/11 2008/09 2008/07 2008/05 2008/03 2008/01 2007/11 2007/09 2007/07 2007/05 2007/03 2007/01 2006/11 2006/09 2006/07 2006/05 2006/03 2006/01 2005/11 2005/09 2005/07 2005/05 2005/03 2005/01 2.00% page. 28 2002:Q1 2002:Q2 2002:Q3 2002:Q4 2003:Q1 2003:Q2 2003:Q3 2003:Q4 2004:Q1 2004:Q2 2004:Q3 2004:Q4 2005:Q1 2005:Q2 2005:Q3 2005:Q4 2006:Q1 2006:Q2 2006:Q3 2006:Q4 2007:Q1 2007:Q2 2007:Q3 2007:Q4 2008:Q1 2008:Q2 2008:Q3 2008:Q4 Dynamics in Real Estate Market 1.3 1.2 2009/11/04 Reitaku-University Trends in Office Market: 1.4 NOI Capital Value/m2 NewRent 1.1 1 0.9 0.8 0.7 0.6 [email protected] page. 29 Dynamics in Real Estate Market Reitaku-University • Neoclassical theory is the response of the demand for capital to changes in relative factor prices or the ratio of factor prices to the price of output. • User cost / Yield • Capital Depreciation Problem • • 2009/11/04 Jorgenson, D. W. (1963), "Capital Theory and Investment Behavior," American Economic Review, 53, pp.247-259. Hayashi, F., and T. Inoue (1991), “The relation between firm growth and Q with multiple capital goods: Theory and evidence from panel data on Japanese firms,” Econometrica, pp.731–753. Chihiro SHIMIZU 2009 [email protected] page. 30 Dynamics in Real Estate Market Reitaku-University Stock Market vs. Asset Market 5.00% Stock CR Real CR 4.50% 4.00% 3.50% 3.00% 2.50% 2009/11/04 [email protected] 2008/11 2008/09 2008/07 2008/05 2008/03 2008/01 2007/11 2007/09 2007/07 2007/05 2007/03 2007/01 2006/11 2006/09 2006/07 2006/05 2006/03 2006/01 2005/11 2005/09 2005/07 2005/05 2005/03 2005/01 2.00% page. 31 2002:Q1 2002:Q2 2002:Q3 2002:Q4 2003:Q1 2003:Q2 2003:Q3 2003:Q4 2004:Q1 2004:Q2 2004:Q3 2004:Q4 2005:Q1 2005:Q2 2005:Q3 2005:Q4 2006:Q1 2006:Q2 2006:Q3 2006:Q4 2007:Q1 2007:Q2 2007:Q3 2007:Q4 2008:Q1 2008:Q2 2008:Q3 2008:Q4 Dynamics in Real Estate Market 1.3 1.2 2009/11/04 Reitaku-University Trends in Office Market: 1.4 NOI Capital Value/m2 NewRent 1.1 1 0.9 0.8 0.7 0.6 [email protected] page. 32 Dynamics in Real Estate Market Reitaku-University Gordon’s Growth Model : Present Value, Discount Rate yit yit pit R ft R pi G R ft R pi G pit • • • • Yit : Net Operating Income Rf :Risk Free Rate Rp : Risk Premium G : Growth in Real Rent • Gordon,M.J and E.Shapro,(1956), Capital Equioment Analysis: The Required Rate of Profit. Management Science, Vol.3,pp.102-110. Gordon,M.J,(1959), Dividends, Earnings and Stock Prices. Review of Statistics and Economics, Vol.41, pp.99-105. • Rp f L( zi ),ξ • L : Liquidity Risk • ξ : Unexpected Risk 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 33 Dynamics in Real Estate Market Reitaku-University Estimation Model yit 0 xij j exp 1it NOI Model j pit 0 xij exp 2it j Capital Value Model j ln(yit pit ) ln( 0 0 ) ( j j ) ln xij ( 1it 2it ) j Yield or Capitalization Rate : ln y it ln p it ( j j ) ln x ij ln x ij 2009/11/04 [email protected] page. 34 Dynamics in Real Estate Market Reitaku-University Estimation Results : See Table3 Unbalanced Panel Data : Pooling Data Analysis Transaction Model Age Age × residential1 Age × residential2 Area Area × residential1 Area × residential2 TS TS × residential1 TS × residential2 TT TT × residential1 TT × residential2 Adj. R-squared: Number of Obs.: 2009/11/04 Cap Rate Model α-β α:NOI Model 0.033 0.010 0.000 -0.046 0.037 0.026 -0.034 -0.002 0.025 0.100 -0.119 0.061 0.358 1,173 0.033 0.010 0.001 -0.047 0.037 0.026 -0.035 -0.002 0.026 0.099 -0.117 0.062 - -0.042 0.017 0.015 0.034 -0.044 0.007 -0.069 -0.024 0.082 -0.087 0.041 0.004 0.574 [email protected] β:Capital Value Model -0.075 0.007 0.014 0.081 -0.082 -0.018 -0.035 -0.021 0.056 -0.186 0.158 -0.058 0.683 page. 35 Dynamics in Real Estate Market Reitaku-University Depreciation Effect on Capitalization Rate Effects on Cap Rate (Transaction-based) 1.20 1.20 1.15 1.15 1.10 1.10 Office Residential (Family) Residential (Single) 1.05 1.05 1.00 1.00 0 2009/11/04 5 10 15 20 [email protected] 25 30 35 40 page. 36 0 Dynamics in Real Estate Market Reitaku-University Depreciation Effect on NOI and Capital Value Effects on NOI (Transaction-point) 1.00 1.00 0.95 0.95 0.90 0.90 0.85 0.85 Office Residential (Family) Residential (Single) 0.80 Office Residential (Family) Residential (Single) 0.80 0.75 0.75 0 5 10 15 20 25 30 35 40 0 5 10 Effects on Price (Transaction-based) 1.00 1.00 0.90 0.90 0.80 0.80 Office Residential (Family) Residential (Single) 0.70 0.60 0.60 0 2009/11/04 Office Residential (Family) Residential (Single) 0.70 5 10 15 20 25 [email protected] 30 35 40 0 5 page. 37 10 Dynamics in Real Estate Market Reitaku-University Quantity Effect on Capitalization Rate Effects on Cap Rate (Transaction-based) 1.40 1.40 1.30 1.30 1.20 1.20 1.10 1.10 1.00 1.00 Office Residential (Family) Residential (Single) 0.90 0.80 0.80 0.70 0.70 0.60 0.60 0 2009/11/04 0.90 5,000 10,000 15,000 20,000 [email protected] 25,000 30,000 35,000 40,000 page. 38 0 Dynamics in Real Estate Market Reitaku-University Quantity Effect on NOI and Capital Value Effects on NOI (Transaction-point) 1.20 1.20 1.15 1.15 1.10 1.10 1.05 Office Residential (Family) Residential (Single) 1.00 1.05 1.00 0.95 0.95 0.90 0.90 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 0 5,000 10,000 1 0 5,000 10,000 1 Effects on Price (Transaction-based) 1.60 1.60 1.50 1.50 1.40 1.40 1.30 1.30 1.20 1.20 1.10 Office Residential (Family) Residential (Single) 1.00 0.90 1.00 0.90 0.80 0.80 0 2009/11/04 1.10 5,000 10,000 15,000 20,000 25,000 [email protected] 30,000 35,000 40,000 page. 39 Dynamics in Real Estate Market Reitaku-University Accessibility Effect on Capitalization Rate: Distance to Central Areas Effects on Cap Rate (Transaction-based) 2.50 2.50 2.30 2.30 Office Residential (Family) Residential (Single) 2.10 1.90 1.90 1.70 1.70 1.50 1.50 1.30 1.30 1.10 1.10 0.90 0.90 0 2009/11/04 2.10 5,000 10,000 15,000 20,000 [email protected] 25,000 30,000 35,000 40,000 page. 40 0 Dynamics in Real Estate Market Reitaku-University Accessibility Effect on NOI and Capital Value: Distance to Central Areas Effects on NOI (Transaction-point) 1.00 1.00 Office Residential (Family) Residential (Single) 0.90 0.80 0.90 0.80 0.70 0.70 0.60 0.60 0.50 0.50 0.40 0.40 0.30 0.30 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 0 5,000 10,000 1 0 5,000 10,000 1 Effects on Price (Transaction-based) 1.00 1.00 Office Residential (Family) Residential (Single) 0.90 0.80 0.80 0.70 0.70 0.60 0.60 0.50 0.50 0.40 0.40 0.30 0.30 0.20 0.20 0.10 0.10 0 2009/11/04 0.90 5,000 10,000 15,000 20,000 25,000 [email protected] 30,000 35,000 40,000 page. 41 Dynamics in Real Estate Market Reitaku-University Comparison: Transaction-based vs. Appraisal-based Depreciation Effect on Capitalization Rate Effects on Cap Rate (Transaction-based) Effects on Cap Rate (Appraisal-based) 1.20 1.20 1.15 1.15 1.10 1.10 Office Residential (Family) Residential (Single) 1.05 Office Residential (Family) Residential (Single) 1.05 1.00 1.00 0 2009/11/04 5 10 15 20 25 30 35 40 0 [email protected] 5 10 15 20 25 30 35 40 page. 42 Dynamics in Real Estate Market Reitaku-University What is Capitalization Rate? • Conclusions; • Capitalization Rate is explained by ln y it ln p it ( j j ) ln x ij ln x ij • Link between asset prices and stock prices in Real Estate Investment Market. • 2009/11/04 Client Pressure Problems in Appraisal Process [email protected] page. 43 Dynamics in Real Estate Market Reitaku-University 5.社会構造の変化と不動産価格 • 米国での議論: • Baby Boom, Baby Burst and Housing Market! • 米国の住宅価格は，１９８７年～2007年まで47%下 落する!!! • →社会構造の変化と不動産市場 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 44 Dynamics in Real Estate Market Reitaku-University 出生者数の推移(JPN) (Ten thousands) 300 5.0 Number of Live Births [Left Scale] Total Fertality Rates [Right Scale] Baby boom (1947-49) 4.5 250 4.0 Echo baby boom (1971-73) 200 3.5 3.0 150 2.5 Baby bust (1955-60) 2.0 100 1.5 1.0 50 0.5 2010 2005 2000 1995 1990 1985 1980 1975 1970 1965 1960 1955 1950 1945 1940 1935 1930 1925 0.0 1920 0 Source: Ministry of Health, Labor and Welfare 2009/11/04 page. 45 Dynamics in Real Estate Market Reitaku-University 出生者数の推移(U.S.) (Ten thousands) 500 5.0 Baby boom （1946～1960） Number of Live Births [Left Scale] Total Fertality Rates [Right Scale] 450 Echo baby boom （1980～90's） 4.5 400 4.0 350 3.5 300 3.0 Baby bust （1965-79） 250 2.5 2010 2005 2000 1995 1990 1985 1980 1975 1970 1965 0.0 1960 0 1955 0.5 1950 50 1945 1.0 1940 100 1935 1.5 1930 150 1925 2.0 1920 200 Source: National Center for Health Statistics, "National Vital Statistics Reports." 2009/11/04 page. 46 Dynamics in Real Estate Market Reitaku-University 3-4(a).年齢別人口 30-44 (JPN) (Ten thousands) 3,500 Baby boomer （1947～1949） 3,000 Echo baby boomer （1971～1973） 2,500 Baby buster （1955-1960） 2,000 Age 40-44 1,500 Age 35-39 1,000 Age 30-34 500 2010 2005 2000 1995 1990 1985 1980 1975 1970 1965 1960 0 Source: Ministry of Internal Affairs and Communications Statistics Bureau 2009/11/04 page. 47 Dynamics in Real Estate Market Reitaku-University 3-4(b). 年齢別人口 30-44 (U.S.) (Ten thousands) 7,000 6,000 5,000 Age 40-44 Baby boomer （1946～1960） 4,000 Age 35-39 3,000 2,000 Age 30-34 Baby buster （1965-1979） 1,000 Echo baby boomer （1980～90's） 2010 2005 2000 1995 1990 1985 1980 1975 1970 1965 1960 0 Source: U.S. Bureau of Census, "Population Estimates." 2009/11/04 page. 48 Dynamics in Real Estate Market Reitaku-University Mankiw=Weil (1989)住宅需要指標 • The aggregate amount of housing demand for the specific age of each household member using the housing demand by household, and they created ; D N Dj (1) Dj is the amount of housing demand for the jth member in the household, and N is the number of household members. j 1 (2) D j 0 Dummy0 1Dummy1 i Dummyi • Dummy 0 is the dummy variable, and when age = 0, it becomes 1. Combining formulas (1) and (2) above results in formula (3). • D 0 Dummy0 j 1 Dummy1 j i Dummy (3) ij • the amount of housing demand i for each age (age i) was estimated 2009/11/04 page. 49 Dynamics in Real Estate Market Reitaku-University Estimation Method of House Demand by Home ownership rates • Home ownership demand: • we hypothesize that the increase in this rate is equivalent to the ownership demand occurring in that age group • Dj ,t Oj ,t O j ,t 1 N j ,t Dj,t Oj,t Nj,t : home ownership demand for j cohort over t period : ownership rate for j cohort over t period : population of j cohort over t period • Mankiw and Weil (1989) pointed out that there were no significant differences in the final housing prediction model estimates whether using adult population data or an estimated housing demand index based on individual data. 2009/11/04 page. 50 Dynamics in Real Estate Market Reitaku-University 住宅需要の推計(JPN & U.S.) 12,000 6,800 10,000 6,400 8,000 6,000 MW Index (JPN) 6,000 Population-based index (JPN.) 5,600 4,000 5,200 2,000 0 4,800 1970 1975 1980 1985 1990 1995 2000 2005 2,000 12,000 1,600 10,000 1,200 MW Index (U.S.) 8,000 Population-based index (U.S.) 800 6,000 400 0 4,000 1970 1975 1980 1985 1990 1995 2000 2005 Source: Mankiw and Weil (1989), Ootake and Shintani(1994) 2009/11/04 page. 51 Dynamics in Real Estate Market Reitaku-University Sample Selection Bias in Published Land Price • • 加重平均地価指数: • 同一地点の対前年比を加 重平均 • 調査地点の選定替えの実施: • 変動率で整合性が取れなくなっ た地点の入れ替え • 変動率のラグ→Shimizu and Nishimura(2004)(2006) 2009/11/04 Year 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Nt:Number of Samples in tperiod 9,346 9,338 9,183 9,442 10,322 10,867 11,146 11,339 10,782 10,782 10,774 10,557 10,591 10,821 10,868 10,901 10,906 11,223 13,519 17,966 19,947 19,948 19,919 20,143 20,249 20,445 20,447 20,544 20,630 20,618 20,274 20,273 19,426 18,834 Nt-1:Number of Samples in tperiod 8,800 8,772 8,640 8,498 7,751 8,596 9,098 8,112 4,904 10,219 10,267 10,123 10,119 10,227 10,421 10,441 10,442 10,394 10,435 12,984 17,480 19,722 19,562 19,683 19,933 20,023 20,144 20,192 20,295 20,383 20,027 20,035 19,300 18,719 Nt/Nt-1 0.942 0.939 0.941 0.900 0.751 0.791 0.816 0.715 0.455 0.948 0.953 0.959 0.955 0.945 0.959 0.958 0.957 0.926 0.772 0.723 0.876 0.989 0.982 0.977 0.984 0.979 0.985 0.983 0.984 0.989 0.988 0.988 0.994 0.994 page. 52 Dynamics in Real Estate Market Reitaku-University Estimation Results of Hedonic Function No Prefecture 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 2009/11/04 Hokkaido Aomori Iwate Miyagi Akita Yamagata Fukushima Ibaragi Tochigi Gunma Saitama Chiba Tokyo Kanagawa Niigata Toyama Ishikawa Fukui Yamanashi Nagano Gifu Shizuoka Aichi Mie Shiga Kyouto Oosaka Hyougo Nara Wakayama Tottori Shimane Okayama Hiroshima Yamaguchi Tokushima Kagawa Ehime Kouchi Fukuoka Saga Nagasaki Kumamoto Ooita Miyazaki Kagoshima Okinawa area rw ts tt gesui sui gas UX -1.180 -1.245 -1.149 -1.108 -1.157 -1.259 -1.135 -1.216 -1.257 -1.142 -1.039 -1.096 -0.871 -0.919 -1.309 -1.080 -1.170 -1.057 -1.143 -1.370 -1.062 -1.154 -1.013 -1.116 -1.310 -0.994 -0.965 -0.983 -1.060 -1.094 -1.199 -1.054 -1.232 -1.083 -1.143 -1.018 -1.142 -1.240 -1.232 -0.992 -1.294 -0.919 -1.222 -1.139 -1.168 -1.122 -1.225 0.179 0.418 0.016 0.237 0.150 0.234 0.135 0.181 0.221 0.279 0.145 0.120 0.144 0.096 0.369 0.242 0.175 0.168 0.215 0.113 0.204 0.116 0.267 0.329 0.395 0.270 0.221 0.201 0.255 0.168 0.561 0.133 0.156 0.197 0.146 0.117 0.247 0.306 0.284 0.157 0.153 0.685 0.311 0.418 0.125 0.108 0.318 -0.051 -0.038 0.035 -0.112 -0.074 -0.054 -0.028 -0.111 -0.050 -0.062 -0.148 -0.168 -0.125 -0.107 -0.131 -0.062 -0.057 -0.129 -0.039 -0.062 -0.047 -0.070 -0.066 -0.071 -0.074 -0.080 -0.129 -0.123 -0.133 0.014 -0.182 -0.094 -0.086 -0.103 -0.048 -0.037 -0.163 -0.077 -0.038 -0.072 -0.062 -0.006 -0.033 -0.097 -0.057 -0.092 0.015 -0.409 -0.236 -0.321 -0.365 -0.396 -0.342 -0.193 -0.140 -0.244 -0.063 -0.173 -0.283 -0.724 -0.038 -0.331 -0.179 -0.414 -0.318 -0.155 -0.281 -0.213 -0.125 -0.417 -0.040 -0.158 -0.318 -0.342 -0.062 -0.049 -0.158 -0.177 -0.290 -0.266 -0.329 -0.010 -0.303 -0.264 -0.208 -0.272 -0.434 -0.186 -0.211 -0.265 -0.232 -0.273 -0.384 -0.367 0.288 0.187 0.217 0.143 0.230 0.220 0.165 0.206 0.151 0.271 0.109 0.077 0.086 0.040 0.112 0.294 0.157 0.070 0.028 0.330 0.193 0.131 0.146 0.060 0.111 0.134 0.083 0.077 0.054 0.151 0.103 0.089 0.110 0.114 0.022 0.062 0.011 0.180 0.218 0.280 0.094 0.101 0.116 0.106 0.259 0.095 0.112 0.004 0.325 0.086 0.232 0.199 0.398 0.148 0.312 0.258 -0.100 0.307 0.089 0.024 -0.082 0.103 0.212 -0.106 0.335 0.812 0.010 -0.082 -0.051 0.155 0.092 0.830 -0.003 0.106 0.387 0.205 -0.670 0.079 0.237 0.366 0.065 0.254 -0.125 0.176 0.182 0.096 0.143 0.199 0.695 0.140 -0.067 0.415 0.441 0.256 0.180 0.196 0.303 0.257 0.330 0.235 0.179 0.110 0.261 0.186 0.122 0.316 0.231 0.146 0.124 0.158 0.142 0.154 0.258 0.131 0.318 0.268 0.241 0.186 0.380 0.247 0.156 0.158 0.228 0.236 0.279 0.402 0.237 0.256 0.251 0.195 0.232 0.200 0.374 0.315 0.254 0.244 0.330 0.006 -6.221 0.360 0.530 0.284 0.574 -0.177 0.050 -0.428 -0.204 -0.264 0.231 -1.646 -0.578 0.782 -0.418 -0.583 -0.604 -0.335 1.087 -0.122 -0.323 0.080 0.623 0.212 -1.340 1.174 0.009 0.911 -1.254 0.032 -0.298 -0.680 -0.444 0.265 0.330 -0.573 -0.626 0.307 0.304 0.611 0.243 -0.298 -0.147 -0.640 0.634 -0.264 -2.586 UY UXX UYY cp1 cp3 cp6 cp7 -24.091 0.022 0.276 -0.108 -0.275 0.878 -0.951 -0.919 -0.216 -0.034 0.339 -0.732 -63.865 0.805 -0.117 -0.010 -0.589 0.040 -0.079 -0.037 -0.592 -151.022 1.896 -0.054 0.506 -0.776 -42.895 0.560 -0.056 -0.691 -80.239 1.076 -0.001 0.139 -0.387 -0.839 -0.274 -0.091 0.325 -0.710 -0.651 -0.021 -0.369 -0.168 0.008 -0.455 -2.411 -0.026 0.244 0.301 -0.599 1.430 -0.055 -0.042 0.074 -0.560 -0.001 0.012 0.135 -0.349 -3.136 0.947 -0.008 -0.054 -0.195 -0.589 -11.409 0.150 -0.108 -0.797 1.121 -0.110 -0.325 -165.220 2.257 0.026 -0.044 -0.407 -0.935 -0.020 -1.107 0.627 -0.017 -0.078 -0.349 90.043 -1.247 -0.085 0.460 0.202 -0.424 0.771 -0.052 0.066 0.129 -0.559 0.118 -0.058 0.159 -0.455 -0.449 -0.033 -0.141 -0.314 -0.383 -59.555 0.853 -0.032 -0.016 -0.635 0.532 -0.085 -0.198 -0.490 -0.669 1.080 0.004 -0.165 -0.188 -1.101 0.691 -0.031 0.040 -0.847 -70.375 1.000 -0.110 -0.020 -0.930 2.115 -0.100 -0.572 -0.342 -0.225 -0.022 -0.171 -0.413 -0.233 -0.063 -0.102 -0.941 -50.651 0.724 -0.038 -0.656 -0.258 -0.110 -0.616 -0.905 0.002 0.097 -0.729 0.399 -0.058 -1.079 -0.327 0.090 -0.063 0.088 -0.097 -0.462 34.366 -0.518 -0.108 -0.263 -0.498 34.104 -0.527 0.051 -0.292 -55.140 0.821 -0.035 0.635 0.039 -0.954 1.040 -0.120 -0.181 -0.774 -9.789 0.148 -0.012 -0.384 -0.831 -0.607 -0.009 -0.349 -0.765 -0.085 -0.040 -52.347 0.816 -0.038 -0.520 1.593 -0.028 -0.064 -0.590 48.458 -0.873 -0.043 0.070 -1.261 tm Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Number of adjusted 2 Samples R 24,565 0.814 4,965 0.835 3,153 0.827 10,350 0.895 3,300 0.867 3,126 0.867 8,462 0.851 14,836 0.877 8,752 0.879 7,188 0.839 28,425 0.943 27,654 0.864 50,333 0.923 41,470 0.931 7,386 0.851 3,941 0.839 3,903 0.849 2,090 0.858 2,774 0.936 5,125 0.844 6,207 0.893 13,103 0.882 33,687 0.931 8,298 0.885 5,431 0.910 12,672 0.932 34,854 0.944 25,911 0.875 8,399 0.899 3,049 0.878 1,946 0.859 2,215 0.790 7,396 0.880 12,160 0.855 5,714 0.817 2,518 0.929 2,866 0.913 4,405 0.861 2,644 0.890 17,948 0.870 2,001 0.887 4,922 0.815 5,186 0.901 4,496 0.856 4,397 0.896 4,799 0.885 3,348 0.929 page. 53 Dynamics in Real Estate Market Reitaku-University 3-1(a). Real House prices by prefectures (JPN) 900,000 800,000 700,000 600,000 500,000 400,000 300,000 200,000 100,000 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 0 Hokkaido Aomori Iwate Miyagi Akita Yamagata Fukushima Ibaragi Tochigi Gunma Saitama Chiba Tokyo Kanagawa Niigata Toyama Ishikawa Fukui Yamanashi Nagano Gifu Shizuoka Aichi Mie Shiga Kyouto Oosaka Hyougo Nara Wakayama Tottori Shimane Okayama Hiroshima Yamaguchi Tokushima Kagawa Ehime Kouchi Fukuoka Saga Nagasaki Kumamoto Ooita Miyazaki Kagoshima Okinawa Source: Ministry of Land, Infrastructure, Transport and Tourism “Published Land Prices” 2009/11/04 page. 54 Dynamics in Real Estate Market Reitaku-University 3-1(b). Real House prices by states (U.S.) 800,000 700,000 600,000 500,000 400,000 300,000 200,000 100,000 2008 2007 2006 2004 2005 2003 2002 2000 2001 1999 1998 1997 1995 1996 1994 1993 1991 1992 1990 1989 1987 1988 1986 1985 1984 1982 1983 1981 1980 1978 1979 1977 1976 1975 0 AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY Source: Office of Federal Housing Enterprise Oversight, “House Price Index”, U.S. Census of Bureau, “Census of Housing: Median home value.” 2009/11/04 page. 55 Dynamics in Real Estate Market Reitaku-University 3.2.Gini's coefficient : Comparison between Japan and US 0.450 Japan 0.400 USA 0.350 0.300 0.250 0.200 0.150 0.100 0.050 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 0.000 2009/11/04 page. 56 Dynamics in Real Estate Market Reitaku-University Cluster Classification in Japan by Appreciation Rate of Land Price 80 70 Cluster1 Cluster2 60 Cluster3 50 Cluster4 Cluster5 40 30 20 10 -20 -30 2009/11/04 page. 57 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982 1981 1980 1979 1978 1977 -10 1976 0 Dynamics in Real Estate Market Reitaku-University Cluster Classification in US by Appreciation Rate of House Price 30 Cluster1 25 Cluster2 Cluster3 Cluster4 20 Cluster5 15 10 5 -5 -10 2009/11/04 page. 58 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982 1981 1980 1979 1978 1977 1976 0 Dynamics in Real Estate Market Reitaku-University House Demand by prefectures (JPN) 2,500,000 2,000,000 1,500,000 1,000,000 500,000 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 0 Hokkaido Aomori Iwate Miyagi Akita Yamagata Fukushima Ibaragi Tochigi Gunma Saitama Chiba Tokyo Kanagawa Niigata Toyama Ishikawa Fukui Yamanashi Nagano Gifu Shizuoka Aichi Mie Shiga Kyouto Oosaka Hyougo Nara Wakayama Tottori Shimane Okayama Hiroshima Yamaguchi Tokushima Kagawa Ehime Kouchi Fukuoka Saga Nagasaki Kumamoto Ooita Miyazaki Kagoshima Okinawa Source: Ministry of Internal Affairs and Communications Statistics Bureau, “Census" 2009/11/04 page. 59 Dynamics in Real Estate Market Reitaku-University House Demand by states (U.S.) 6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982 1981 1980 1979 1978 1977 1976 1975 0 AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY Source: U.S. Census of Bureau, “Population Estimates.” 2009/11/04 page. 60 Dynamics in Real Estate Market Reitaku-University 地域別 住宅需要 vs.住宅価格(JPN) Aomori Age 35-39 Age 40-44 Tokyo LP Index Age 35-39 Age 40-44 LP Index 300 120 2,500 300 250 100 2,000 250 200 80 200 150 60 100 40 50 20 1,500 150 1,000 0 1980 Osaka 1985 1990 Age 35-39 1995 2000 Age 40-44 500 1980 Yamaguchi LP Index 1,400 0 1975 2005 1,600 50 0 0 1975 100 1985 1990 Age 35-39 1995 2000 Age 40-44 2005 LP Index 300 300 140 250 250 120 1,200 100 200 200 1,000 80 800 150 150 60 600 100 100 40 400 200 0 1975 1980 1985 1990 1995 2000 2005 50 50 0 0 20 0 1975 1980 1985 1990 1995 2000 2005 Source: Ministry of Land, Infrastructure, Transport and Tourism , Ministry of Internal Affairs and Communications Statistics Bureau 2009/11/04 page. 61 Dynamics in Real Estate Market Reitaku-University 地域別 住宅需要 vs.住宅価格(U.S.) California Age 30-34 35-39 40-44 OFHEO HPI 9,000 8,000 3,500 450 4,000 300 0 1980 Michigan 1985 Age 30-34 1990 1995 35-39 2000 40-44 350 2,500 300 2,000 250 1,500 200 1,000 100 500 150 100 50 0 0 1975 2005 OFHEO HPI 3,000 350 2,500 300 250 2,000 400 3,000 200 0 1975 OFHEO HPI 600 400 1,000 40-44 500 5,000 2,000 35-39 4,000 500 3,000 Age 30-34 700 7,000 6,000 Florida 200 1980 New York 1985 Age 30-34 1990 1995 35-39 2000 40-44 2005 OFHEO HPI 5,000 700 4,500 600 4,000 3,500 500 3,000 400 2,500 1,500 1,000 500 150 2,000 300 100 1,500 200 50 0 0 1975 1980 1985 1990 1995 2000 2005 1,000 100 500 0 0 1975 1980 1985 1990 1995 2000 2005 Source: U.S. Census of Bureau, “Population Estimates,” and OFHEO “House Price Index”. 2009/11/04 page. 62 Dynamics in Real Estate Market Reitaku-University 住宅需要 vs.住宅価格 200 140 (DM7 5- 80 , LP75 -8 0) 120 (DM8 5- 90 , LP85 -9 0) Chiba Tokyo (DM7 5- 80 , LP75 -8 0) Washington (DM8 0- 85 , LP80 -8 5) (DM8 5- 90 , LP85 -9 0) (DM9 0- 95 , LP90 -9 5) Change rate of house price:% Japan: 35- to 44year-old population; U.S.: 30- to 44-yearold population Change rate of house price:% 150 California Delaware (DM8 0- 85 , LP80 -8 5) Oosaka (DM9 5- 00 , LP95 -0 0) (DM0 0- 05 , LP00 -0 5) Kanagawa Kyouto Kanagawa (DM0 5- 08 , LP05 -0 8) 100 Hyougo Okinawa Chiba 50 Ibaragi North Dakota California 100 Wyoming (DM9 0- 95 , LP90 -9 5) (DM9 5- 00 , LP95 -0 0) OregonNorth Dakota 80 (DM0 0- 05 , LP00 -0 5) (DM0 5- 08 , LP05 -0 8) 60 Alabama Nebraska 40 20 Arkansas 0 North Dakota 0 -50 -20 -30 -20 -10 0 10 20 30 40 50 -20 0 20 Change rate of house dem and:% 40 60 80 100 Change rate of house dem and:% 200 140 (DM7 5- 80 , LP75 -8 0) California Delaware (DM8 0- 85 , LP80 -8 5) Oosaka 120 (DM7 5- 80 , LP75 -8 0) Washington (DM8 0- 85 , LP80 -8 5) (DM8 5- 90 , LP85 -9 0) (DM8 5- 90 , LP85 -9 0) Chiba Tokyo (DM9 0- 95 , LP90 -9 5) (DM9 5- 00 , LP95 -0 0) 200 Kyouto 100 (DM0 0- 05 , LP00 -0 5) Kanagawa (DM7 5- 80 , LP75 -8 0) (DM0 5- 08 , LP05 -0 8) (DM8 0- 85 , LP80 -8 5) Kanagawa Hyougo Oosaka (DM8 5- 90 , LP85 -9 0) Chiba 150 Okinawa (DM9 0- 95 , LP90 -9 5) Tokyo 50 (DM9 5- 00 , LP95 -0 0) Chiba Kyouto Kanagawa (DM0 0- 05 , LP00 -0 5) Kanagawa Ibaragi (DM0 5- 08 , LP05 -0 8) 100 Hyougo Okinawa 0 Chiba 50 Ibaragi -50 -5 0 5 10 0 15 20 25 30 35 40 Change rate of house price:% Change rate of house price:% Change rate of house price:% Change rate of house price:% Mankiw House Demand Index 150 North Dakota Wyoming California 100 (DM9 0- 95 , LP90 -9 5) (DM9 5- 00 , LP95 -0 0) 140 80 Oregon California Delaware 120 (DM0 0- 05 , LP00 -0 5) North Dakota (DM7 5- 80 , LP75 -8 0) (DM0 5- 08 , LP05 -0 8) Washington (DM8 0- 85 , LP80 -8 5) (DM8 5- 90 , LP85 -9 0) 60 North Dakota California 100 Alabama Wyoming Nebraska (DM9 0- 95 , LP90 -9 5) (DM9 5- 00 , LP95 -0 0) 40 Oregon North Dakota 80 (DM0 0- 05 , LP00 -0 5) (DM0 5- 08 , LP05 -0 8) 20 Arkansas 60 Alabama North Dakota Nebraska 0 40 -20 20 -10 0 10 Change rate of house dem and:% 20 30 40 50 60 70 Arkansas Change rate of house dem and:% North Dakota 0 -50 -10 2009/11/04 -5 0 5 10 15 20 25 30 -20 -20 Change rate of house dem and:% -10 0 10 20 30 40 50 Change rate of house dem and:% 200 140 (DM7 5- 80 , LP75 -8 0) 60 70 80 page. 63 Dynamics in Real Estate Market Reitaku-University 住宅需要 vs.住宅価格 140 200 140 (DM7 5- 80 , LP75 -8 0) Chiba Change rate of house price:% Tokyo (DM8 5- 90 , LP85 -9 0) 120 (DM9 0- 95 , LP90 -9 5) 100 Change of house price:% Change rate rate of house price:% Oosaka Owner Occupied Demand index Delaware (DM8 0- 85 , LP80 -8 5) 150 (DM9 5- 00 , LP95 -0 0) Kyouto Kanagawa (DM0 0- 05 , LP00 -0 5) Kanagawa (DM0 5- 08 , LP05 -0 8) 100 Hyougo Okinawa Chiba 50 Ibaragi 0 California (DM7 5- 80 , LP75 -8 0) Washington California (DM8 0- 85 , LP80 -8 5) (DM7 5- 80 , LP75 -8 0) (DM8 5- 90 , LP85 -9 0) (DM8 0- 85 , LP80 -8 5) (DM9 0- 95 , LP90 -9 5) (DM8 5- 90 , LP85 -9 0) (DM9 5- 00 , LP95 -0 0) (DM9 0- 95 , LP90 -9 5) Delaware 120 100 California Washington North Dakota Wyoming California North Dakota Wyoming 80 80 Oregon North Dakota (DM0 0- 05 , LP00 -0 5) (DM9 5- 00 , LP95 -0 0) Oregon North Dakota (DM0 5- 08 , LP05 -0 8) (DM0 0- 05 , LP00 -0 5) (DM0 5- 08 , LP05 -0 8) 60 Alabama Nebraska 60 Alabama 40 Nebraska 40 20 Arkansas 20 Arkansas North Dakota 0 North Dakota 0 -20 -50 -10 -5 0 5 10 15 20 25 -20 30 -20 -10 0 -20 -10 0 10 Change rate of house dem and:% 50 60 70 10 20 40 and:% 50 Change rate of 30 house dem 20 30 40 60 70 80 80 Change rate of house dem and:% 200 (DM_ Co n tro l, LP85 -90 ) Oosaka Delaware 120 (DM8 0- 85 , LP85 -9 0) Tokyo California (DM_ Co n tro l, LP00 -05 ) Change rate of house price:% Change rate of house price:% Bubble era: Owner Occupied Demand index Rhode Island (DM8 5- 90 , LP85 -9 0) 150 Chiba Kanagawa Kanagawa 100 Hyougo 50 Okinawa Ibaragi 100 (DM0 0- 05 , LP00 -0 5) North Dakota (LP9 5-0 0 , LP00 -0 5) 80 Nebraska Arkansas 60 Wyoming 40 Oregon 0 20 0 -50 -10 -5 0 5 10 15 Change rate of house dem and:% 2009/11/04 20 25 30 -20 -10 0 10 20 30 40 50 Change rate of house dem and:% page. 64 Dynamics in Real Estate Market Reitaku-University 需要要因が住宅価格に与える影響 VAR Estimate : Japan VAR Estimate : USA grHousePriceIndex grHouseDemand grHousePriceIndex grHouseDemand Constant grHPI(Lag1) grHPI(Lag2) grHD(Lag1) grHD(Lag2) dRate grGDP F-statistic Log likelihood Akaike AIC 2009/11/04 0.000 (0.0020) 0.611 (0.0259) -0.130 (0.0247) -2.994 (0.6973) 4.274 (0.6712) 0.014 (0.0022) 0.418 (0.0615) 196.877 1882.096 -2.751 0.000 (0.0001) 0.000 (0.0012) -0.005 (0.0012) 0.850 (0.0344) 0.048 (0.0331) 0.000 (0.0001) -0.001 (0.0030) 1240.132 5983.415 -8.770 -0.001652 (0.0013) 0.03407 (0.0237) 0.066647 (0.0631) 0.066647 (0.0631) -0.237661 (0.0620) -0.011743 (0.0010) 0.353377 (0.0277) 240.292 2822.327 -3.680 Chihiro SHIMIZU 2009 [email protected] 0.001226 (0.0004) -0.009078 (0.0085) 0.391596 (0.0228) 0.391596 (0.0228) 0.269695 (0.0224) 0.004687 (0.0003) 0.092434 (0.0100) 241.092 4375.800 -5.711 page. 65 Dynamics in Real Estate Market Reitaku-University 需要要因が住宅価格に与える影響:日本 Response to Cholesky One S.D. Innovations ± 2 S.E. Response of House Price to House Price Response of House Price Housing Demand .08 .08 .06 .06 .04 .04 .02 .02 .00 .00 -.02 -.02 1 2 3 4 5 6 7 8 9 10 Response of Housing Demand to House Price 2 3 4 5 6 7 8 9 10 Response of Housing Demand to Housing Demand .004 .004 .003 .003 .002 .002 .001 .001 .000 .000 -.001 -.001 1 2009/11/04 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 Chihiro SHIMIZU 2009 [email protected] 6 7 8 9 10 page. 66 Dynamics in Real Estate Market Reitaku-University 需要要因が住宅価格に与える影響:米国 Response to Cholesky One S.D. Innovations ± 2 S.E. Response of House Price to House Price Response of House Price to Housing Demand .05 .05 .04 .04 .03 .03 .02 .02 .01 .01 .00 .00 -.01 -.01 1 2 3 4 5 6 7 8 9 10 Response of Housing Demand to House Price 2 3 4 5 6 7 8 9 10 Response of Housing Demand to Housing Demand .016 .016 .012 .012 .008 .008 .004 .004 .000 .000 -.004 -.004 1 2009/11/04 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 Chihiro SHIMIZU 2009 [email protected] 6 7 8 9 10 page. 67 Dynamics in Real Estate Market Reitaku-University 6.公示地価への教訓 • 不動産価格は予測できるか→市場の効率性 • キャッシュフローは市場を適切に反映しているか? • キャップレートは，どのように決定されているのか? • 需要ショックは価格変動に影響を及ぼすか? • →どうしたらいいのか??? 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 68 Dynamics in Real Estate Market Reitaku-University 時点修正課題への対応: • Valuation Error, Smoothingはなぜ起こるのか? • 起こってはいけないのか? 0.98 0.96 Index:2000.01=1 0.94 0.92 Test01 0.9 0.88 Test02 0.86 Test03 0.84 実績 2009/11/04 Chihiro SHIMIZU 2009 [email protected] 200202 200201 200112 200111 200110 200109 200108 200107 200106 200105 200104 200103 200102 200101 0.82 page. 69 199701 199702 199703 199704 199801 199802 199803 199804 199901 199902 199903 199904 200001 200002 200003 200004 200101 200102 200103 200104 200201 200202 200203 200204 200301 200302 200303 200304 200401 200402 200403 200404 200501 200502 200503 200504 200601 200602 200603 200604 200701 200702 200703 200704 200801 200802 200803 200804 Dynamics in Real Estate Market １ ９ ９ ７ 第 一 四 半 期 ＝ ０ ： 対 前 期 変 動 率 2009/11/04 Reitaku-University 住宅価格指数の比較 0.04 0.02 0 -0 .02 -0 .04 ヘドニ ック指数:RRPI -0 .06 -0 .08 -0 .1 ヘドニ ック指数:ハリファ ックス型 -0 .12 リピ ートセールス指数:香港大学型 -0 .14 リピ ートセールス指数:ケースシラ ー型 Chihiro SHIMIZU 2009 [email protected] page. 70 199701 199702 199703 199704 199801 199802 199803 199804 199901 199902 199903 199904 200001 200002 200003 200004 200101 200102 200103 200104 200201 200202 200203 200204 200301 200302 200303 200304 200401 200402 200403 200404 200501 200502 200503 200504 200601 200602 200603 200604 200701 200702 200703 200704 200801 200802 200803 200804 Dynamics in Real Estate Market -0.12 2009/11/04 Reitaku-University 複数回サンプルの比較:ヘドニック指数 0.02 0 -0.02 -0.04 -0.06 -0.08 -0.1 o ver1 o ver2 o ver3 o ver4 Tra d itio n a l Rep ea t S a les -0.14 Chihiro SHIMIZU 2009 [email protected] page. 71 Dynamics in Real Estate Market Reitaku-University 複数回サンプルの性質1 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 72 Dynamics in Real Estate Market Reitaku-University 複数回サンプルの性質2 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 73 Dynamics in Real Estate Market Reitaku-University 複数回サンプルの性質3 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 74 Dynamics in Real Estate Market Reitaku-University 地価回復が遅れた原因-最有効使用1:機会損失が発生しているビル:2004年 オフィスの分布 機会損失ビルの分布 Source) Shimizu and Karato(2010), Microstructure of Office Investment Market in Tokyo Metropolitan Area,(forthcoming) 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 75 Dynamics in Real Estate Market Reitaku-University 地価回復が遅れた原因-最有効使用2:機会損失が発生しているビルの特性 表 6. パネル・データの概要 年次 変数 単位 観測値の数 平均 1996 RR 円 40516 8399 RC 円 100 万円 40516 40516 - 2001 標準偏差 最小 最大 2836 2837 26542 4720 −10.91 765 55.11 3018 −2712.34 6451 −0.01 40516 2607 0.06 −2.25 0.25 7.07 0 −153.73 1 −0.01 37909 −11.51 56.90 −2712.34 −0.01 RR RC 円 円 40516 40516 6402 4808 2162 779 2163 3073 20232 6570 100 万円 - 40516 40516 −7.19 0.09 37.66 0.28 −1878.82 0 0.02 1 3576 36940 −1.44 −7.75 4.21 39.38 −101.27 −1878.82 0.00 0.02 注. RR は再開発された用途での賃貸料，RC は再開発されなかった場合の賃貸料を示している． Source) Shimizu and Karato(2010), Microstructure of Office Investment Market in Tokyo Metropolitan Area,(forthcoming) 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 76 Dynamics in Real Estate Market Reitaku-University 地価回復が遅れた原因-最有効使用3:再開発の確率 表 7. 再開発確率のプロビット推定 全サンプル 地域 1 地域 2 地域 3 0.3181 (0.0093) 0.0576 (0.0058) 0.4447 (0.0250) 0.3407 (0.0219) −13.5617 (0.4317) −5.7765 (0.1630) −9.3597 (0.5139) −9.7961 (0.6578) 10.5011 2.9883 7.6478 8.0016 (0.3327) 0.9910 (0.0903) 0.8993 (0.4046) 0.9832 (0.4998) 0.9846 (0.0006) (0.0055) (0.0017) (0.0019) 81032 40516 1160.1 [.000] −15071.5 30110 15055 98.8 [.000] −2567.9 19898 9949 315.3 [.000] −3792.0 30468 15234 242.8 [.000] −8043.3 Constant Number of obs. Individual Number of groups Wald (chi squared) Log likelihood Note. ( )内は標準誤差を示している．被説明変数はその区画が再開発された場合 1，現状のままであれば 0 となる 2 値変数である． はランダム効果を含む誤差構造の相関係数．Wald はすべてのパラメータが 0 であるという帰無仮説に対する検定統計量（自由度 1 の カイ 2 乗分布にしたがう）．[ ] は確率値を示す． Source) Shimizu and Karato(2010), Microstructure of Office Investment Market in Tokyo Metropolitan Area,(forthcoming) 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 77 Dynamics in Real Estate Market Reitaku-University Chihiro Shimizu: http://www.cs.reitaku-u.ac.jp/sm/shimizu/ • • • • • • • • • • • • • • • • • • 2009/11/04 論文: Shimizu,C, K.G.Nishimura and T.Watanabe(2009), “House Prices and Rents in Tokyo - A Comparison of Repeat-sales and Hedonic measures-,” 一橋大学物価研究センターWorking Paper,No.41. Journal of Statistics and Economics (forthcoming)./Paper Shimizu,C(2009), “Investment Characteristics of Housing Market -Focusing on the stickiness of housing rent-,”麗澤大学経済社会総合研究 センターWorking Paper,No.34.(Real Estate Investment, Nova Science Publishers, Inc.より出版予定)./Paper 清水千弘・渡辺努(2009),「日米における住宅価格の変動要因」(伊藤隆敏編『アメリカ特集』所収，フィナンシャル・レビュー95号/財務省財 務総合政策研究所./Paper 谷下雅義・長谷川貴陽史・清水千弘(2009)，「景観規制が住宅価格に及ぼす影響-東京都世田谷区を対象としたヘドニック法による検証-」 計画行政,Vol.32,No.2, pp.71-79. 清水千弘・渡辺努・西村清彦(2009)「住宅市場のマクロ変動と住宅賃料の粘着性」季刊住宅土地経済,No.72, pp.10-17. 清水千弘(2009)「都市基盤整備財源としての受益者負担金制度の課題」計画行政第32巻第1号,pp.74-82. 清水千弘(2009)「住宅賃料の粘着性の計測-住宅市場の変動とマクロ経済政策への応用-」麗澤経済研究，第１７巻第１号, pp.29-50. Shimizu,C(2009), “Estimation of Hedonic Single-Family House Price Function Considering Neighborhood Effect Variables,” 東京大学空間 情報科学研究センターDiscussion Paper, No.93./Paper 原野 啓・中川雅之・清水千弘・唐渡広志(2009)「情報の非対称性下における住宅価格とリフォー ム」東京大学空間情報科学研究センタ ーDiscussion Paper,No.94./Paper Shimizu,C, K.G.Nishimura and T.Watanabe(2008), “Residential Rents and Price Rigidity: Micro Structure and Macro Consequences,” 一橋大 学物価研究センターWorking Paper,No.29, revised 2009, RIETI Discussion Paper Series 09-E -044./Paper 清水千弘(2008),「企業不動産戦略の経済学的意義-外部性への配慮と企業の責任-」季刊不動産研究，第50巻，第2号,pp14-23. 清水千弘(2008),「ヘドニック住宅価格関数推定上の課題-過少定式化バイアスへの対応-」資産評価政策学,第10巻第2号(通巻17号 ),pp.56-61. 清水千弘(2008),「近隣外部性を考慮したヘドニック住宅関数の推定」麗澤経済研究,第16巻第1号, pp.29-44. Shimizu,C and K.G.Nishimura(2007), “Pricing structure in Tokyo metropolitan land markets and its structural changes: pre-bubble, bubble, and post-bubble periods,” Journal of Real Estate Finance and Economics, Vol.35,No.4,pp.495-496. 清水千弘・唐渡広志(2007),「土地利用の非効率性の費用」住宅土地経済, Vol.64(2007年春季号)，pp.22-29. 清水千弘・唐渡広志(2007),「住宅価格の非線形性」麗澤経済研究,第15巻第1号，pp.53-77. Shimizu,C,K.G.Nishimura and K.Karato(2007), “Nonlinearity of Housing Price Structure -Secondhand Condominium Market in Tokyo Metropolitan Area-,”東京大学空間情報科学研究センターDiscussion Paper,No.86, submitted to “Urban Studies"./Paper Chihiro SHIMIZU 2009 [email protected] page. 78 Dynamics in Real Estate Market • • • • • • • • • • • • • • • • • 2009/11/04 Reitaku-University Shimizu, C., H.Takatsuji, H.Ono and K.G.Nishimura, (2007), “Change in house price structure with time and housing price index”, RIPESS (Reitaku Institute of Political Economics and Social Studies) Working Paper, No.25./Paper 原野啓・清水千弘・唐渡広志・中川雅之(2007a)「リピートセールス法による品質調整済住宅価格指数の推計」住宅土地経済No.65(2007年 夏季号),pp.12-19. 原野啓・清水千弘・唐渡広志・中川雅之(2007b)「わが国におけるリピートセールス法による住宅価格指数の推計課題」麗澤経済研究,第 15巻第2号,pp.113-133. Shimizu,C and K.G.Nishimura (2006), “Biases in appraisal land price information: the case of Japan,” Journal of Property Investment & Finance, Vol.24, No.2，pp. 150- 175. Shimizu, and H.Ono, (2006), “Incorporting Land Characteristics into Land Valuation for Reconstruction Areas”, RIPESS (Reitaku Institute of Political Economics and Social Studies) Working Paper, No.20./Paper Shimizu,C, K.G.Nishimura and Y.Asami(2004), “Search and Vacancy Costs in the Tokyo housing market: Attempt to measure social costs of imperfect information,” Regional and Urban Development Studies,Vol.16,No.3，pp.210-230./Paper 学会報告: 清水千弘・川村康人,「既存住宅市場と住宅価格」,都市住宅学会(名城大学),2009.11. 清水千弘・川村康人,「不動産特性とキャップレート」,日本不動産学会,(豊橋技術科学大学), 2009.10. 清水千弘・川村康人,「介護保険財源の地域負担構造」,日本計画行政学会(香川大学),2009.9. Shimizu,C, K.G.Nishimura,T.Watanabe and K.Karato,House, Price Index in Tokyo Special District,ISA International Housing Conference 2009,(The University of Glasgow's Department of Urban Studies ),2009.9. Shimizu,C, K.G.Nishimura,T.Watanabe and K.Karato,House, Price Index in Tokyo Special District,SWET: Summer Workshop on Economic Theory2009,2009.8. Shimizu,C, K.G.Nishimura and T.Watanabe,House, House Prices and Rents in Tokyo - A Comparison of Repeat-sales and Hedonic measures,United Nations, 2009 Ottawa Group Meeting(Neuchatel, Switzerland, 27-29 May 2009),2009.5. Shimizu,C, and T.Watanabe,House,Housing Market Bubbles in Japan and the US,International Economy on U.S. Economy(Ministry of Finance),2009.3. Shimizu,C, K.G.Nishimura and T.Watanabe,Residential Rents and Price Rigidity-Micro Structure and Macro Consequences-,NBER-TCERCEPR Conference on Sticky Prices and Inflation Dynamics(Asian Development Bank Institute.),2008.12. 原野啓・中川雅之・清水千弘・唐渡広志「レモンモデルのテスト:リフォームと中古住宅価格」応用地域学会(釧路公立大学)，2008.11 Shimizu,C, H.Takatsuji, H.Ono and K.G.Nishimura,Change in house price structure with time and housing price index,第9回 マクロコンファレ ンス(慶応義塾大学),2007.12. Chihiro SHIMIZU 2009 [email protected] page. 79 Dynamics in Real Estate Market • • • • • • • Reitaku-University 谷下雅義・長谷川貴陽史・清水千弘,土地利用規制が住宅価格に及ぼす影響の分析,第36回土木計画学研究発表会(八戸工業大学),2007.11. 清水千弘,近隣外部性が宅地価格に与える影響-宅地価格構造の非線形性-,資産評価政策学会秋季全国大会(都市センターホテル),2007.11. 清水千弘「東京都区部事務所市場における土地利用の非効率性-収益格差が土地利用転換に与える影響」CSIS DAYS2007,全国共同利用研究発 表会(東京大学柏キャンパス)，2007.11. 原野啓・清水千弘・唐渡広志・中川雅之「リピートセールス法による品質調整済住宅価格指数の推計」，日本経済学会2007年度秋季大会(日本大学 経済学部)，2007.9 原野啓・清水千弘・唐渡広志・中川雅之(2007)「リピートセールス法による品質調整済住宅価格指数の推計」，日本不動産学会2007年度秋季全国大 会(北海道大学・学術交流会館)，2007.11. 清水千弘・唐渡広志,土地利用の転換コスト,日本不動産金融工学学会2006年定期大会報告(明海大学),2006.03. 清水千弘・唐渡広志,土地利用の非効率性の費用,応用地域学会第19回研究発表会(北九州市立大学),2005.12. 2009/11/04 Chihiro SHIMIZU 2009 [email protected] page. 80
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