Center for Spatial Information Science, The University of Tokyo 5-1-5, Kashiwanoha, Kashiwa 277-8568, JAPAN空間・マイクロ情報がもたらす不動産市場の変革-世界一透明な不動産市場を目指して-清水千弘(Chihiro SHIMIZU) June 25, 2019東京大学空間情報科学研究センター
本日の講演者と不動産情報科学研究部門
. 13:30-13:50趣旨説明•不動産情報科学研究部門の概要東京大学空間情報科学研究センター・特任教授清水千弘. 13:50–14:10 講演1不動産市場における官民情報の活用と今後の展望国土交通省不動産市場整備課長・武藤祥郎氏14:10–14:30 講演2不動産ポータルサイトがもたらす不動産市場の未来株式会社Lifull取締役執行役員・山田貴士氏. 14:30-15:50 講演3不動産投資市場における不動産情報の役割株式会社三井住友トラスト基礎研究所取締役社長•金子伸雄氏15:10–15:30 講演4地図基盤を用いた不動産関連の取り組みと今後の展開株式会社ゼンリンDB戦略室・高木和之氏. 15:30–15:50 講演5空間情報基盤と不動産情報NTT空間情報株式会社代表取締役社長•猪瀬崇氏15:50-16:10 講演6賃貸不動産市場におけるAI、BIM情報活用の現在とこれからスターツコーポレーション株式会社取締役副会長・関戸博高氏
図 六大都市市街地価格指数 Urban Land Price Index of Six Large City Areas Source: Japan Real Estate Institute
. US: . Mankiw, N. G., and D. N. Weil (1989), "The baby boom, the baby bust, and the housing market," Regional Science and Urban Economics, Vol. 19, 235-258.
.
Japan:
. Shimizu,C and T. Watanabe (2010) , ''Housing Bubble in Japan and the United States," Public Policy Review, 6 (2), pp.431-472. . Tamai, Y., C. Shimizu and K. G. Nishimura. (2017), "Aging and Property Prices: Theory of a Very Long Run and Prediction on Japanese Municipalities in the 2040s", Asian Economic Policy Review. 16(3), 48-74. . Saita, Y., C.Shimizu and T.Watanabe(2016), "Aging and Real Estate Prices: Evidence from Japanese and US Regional Data,” International Journal of Housing Markets and Analysis, 9, 69-87. . Deng, Y, Inoue., K.Nishimura and C. Shihizu (2017) , “Aging and Property Prices: Evidence from a Diverse Economies,” Presented at Economic Measurement Workshop 2017.
研究室設立と研究プロジェクト
•　地方都市のみならず，大都市部においても空地・空き家が増加し，その不動産の所有者すら特定ができないといった問題が指摘されている。 1980年代後半にハーバード大学のマンキューら(1989)が指摘したように，人口減少や高齢化といった社会構造の変化が，不動産価格を暴落させるという仮説（Asset meltdown）は，多くの地域で現実味を帯びるようになってきたと言ってもいいであろう。 •　しかし，不動産市場を取り巻く課題が露呈してきているものの，わが国においては，米国・英国をはじめとする欧州主要国のみならず，隣国である中国などと比較しても，マイクロデータに基づいた説得的な実証分析は極めて少ない状況にある。その最も大きな理由としては，取引の状況，取引価格，不動産(建物)利用に関するマイクロデータの整備が著しく遅れてきたためであると考えられる。 .本研究室では，不動産に関わる取引，取引価格，不動産利用に関わるマイクロデータを網羅的に整備し，不動産市場の実態をリアルタイムに把握できる統計指標の開発を進めることで，わが国の不動産市場を世界最高水準の透明度をもった市場へと進化させる。さらに，国際的な共同研究体制を整えることで，国際競争力を持った研究活動を推進する。
基礎研究:
●
テーマ1. Index Theory
- Diewert, W. E. and C. Shimizu. (2017), "Alternative Approaches to Commercial Property Price Indexes for Tokyo", Review of Income and Wealth, 63(3), 492-519. - Diewert, W. E. and C. Shimizu (2016), "Hedonic Regression Models for Tokyo Condominium Sales,"Regional Science and Urban Economics, 60, 300-315. - Shimizu,C, K.G.Nishimura and T.Watanabe(2016), "House Prices at Different Stages of Buying/Selling Process ,"Regional Science and Urban Economics, 59, 37-53. - Diewert, W. E., K. Fox and C. Shimizu (2016), "Commercial Property Price Indexes and the System of National Accounts," Journal of Economic Surveys, 30(5), 913-943. - Diewert, W. E. and C. Shimizu (2015), "Residential Property Price Indexes for Tokyo," Macroeconomic Dynamics, 19(8),1659-1714. .
→Constant Utility Index
- – Diewert, E, (1974), ''Intertemporal Consumer Theory and the Demand for Durables'', Econometrica 42:497-516. Diewert, E, (1978), “Superlative Index Numbers and Consistency in Aggregation”, Econometrica 46:4 (July 1978), pp. 883-900. .
→Financial Stability and Property Market
Reinhart, C and K. S. Rogoff (2009), This Time Is Different: Eight Centuries of Financial Folly. - G20 Data Initiative: Data Gap 2009, International Handbook on Residential Property Price Indexes, - EuroStat, UN, IMF, OECD and World Bank, CPI: ILO, PPI: OECD, Export and Import: IMF -品質調整済み価格指数:不動産価格指数• F 1 (p)を第1期の価格(P1)の累積分布関数(CDF) •不動産属性(z) •条件付きの価格の分布: F 1 (p I z)
u₁(z)は不動産価格を構成する属性zの分布不動産の相場の変化とは? ・F 2 (p)およびF 2 (p l z)を第2期の不動産価格の属性u 2 (z)に対応した不動産価格の累積分布関数•F1(p)からF2(p)の価格の変化は, • F 1 (p) — F 2 (p) = . [ F 1 (p | z) — F 2 (p | z)]u 1 (z)dz — 8 + ʃ_‰ F₂ (p l z)[u₁(z) − u₂(z)]dz
価格指数とは?
•効用不変と品質調整•   ƒ_ ∞ [ F 1 (p | z) — F 2 (p | z)]u 1 (z)dz •推計手順•  •  • → •  z)[u 1 (z) − u 2 (z)]dz

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Problems in estimating Hedonic and Repeat Sales Index
•  Hedonic Method:
. -not all the information that make up house prices is observable; as a result, it has been noted that “omitted variable bias” occurs.
•
Repeat Sales Method:
. - using only transaction price data from repeat sales . → sample selection bias . . - depreciation occurs over time, and in cases where renovations are done during that period, the houses may no longer have the same value as before. • →Depreciation Problem . →Renovation Problem . By Diewert, W. Erwin E.(2007), “The Paris OECD-IMF Workshop on Real Estate Price Indexes: Conclusions and Future Directions,” The University of British Columbia, Department of Economics, Discussion Paper 07-01.
I -2.
テーマ1. Index Theory: Housing Rent
- l Diewert, E and C.Shimizu(2019) , “Measuring the Services of Durables and Owner Occupied Housing,” CSIS Discussion paper 157, The University of Tokyo.清水千弘(2018)， 「住宅サービスはどのように測定すべきか?-持ち家のサービス価格測定を巡る議論を中心として-」土地総合研究，第26巻第4号, 14-24. - -清水千弘(2013),「持ち家の帰属家賃の測定」,季刊住宅土地経済.No.88, (2013年春季号), pp10-19. Shimizu, C., K. G. Nishimura and T. Watanabe (2010), "Residential Rents and Price Rigidity: Micro Structure and Macro Consequences," Journal of Japanese and International Economy, 24, 282-299.清水千弘・渡辺努(2010),「家賃の名目硬直性」,フィナンシャル・レビュー106号, 52-68. (財務省財務総合政策研究所) -
.
→Sticky Price and Price Stability
- Calvo, Guillermo A. (1983). "Staggered Prices in a Utility-Maximizing Framework". Journal of Monetary Economics. 12 (3): 383–398. doi:10.1016/0304-3932(83)90060-0. CSIS-Real Estate Information Science Lab Panel data for housing rents Frequency of Rent Adjustments △R t ≡ R it — R it-1 Pr(ΔR it = 0) = [1 + Pr(ΔR it = 0 | I,N = 1) Pr(I,N = 1) + Pr(ΔR it = 0 | I r = 1) Pr(I r = 1)
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n=18,582,863 CSIS-Real Estate Information Science Lab State-Dependent or Time-Dependent Pricing: Caballero-Engel’s definition of price flexibility Δ log R* = Δξ t + Vit X it  ≡ log R it –1 – log R it Λ(x) ≡ Pr(ΔR it ≠ 0 | X it = x) Caballero-Engel(1993) :Adjustment Hazard ll Caballero-Engel's measure of price flexibility Intensive margin Extensive margin Caballero-Engel(2007) Λ(x) =     Pr(ΔR, ≠ 0| I N = 1,X, = x)Pr(I N = 1| X, = x) + Pr(ΔR it ≠ 0 | I k = 1, X it = x) Pr(I k = 1 | X it = x) Estimates of intensive and extensive margins: Adjustment hazard functions     Figure5.Probability of Unit Turnover
CSIS-Real Estate Information Science Lab
Intensive margin: Λ(x)h(x)dx = 0.0084 Extensive margin: xΛ'(x)h(x)dx = 0.0013 Caballero-Engel's measure of price flexibility Δ log R t = 0.0097 lim - Δξ t
. The Paris OECD-IMF Workshop on Real Estate Price Indexes2006: . Erwin Diewert,   Discussion Paper 07-01, Department of Economics,The University of British Columbia • David Fenwick (2006; 6) suggested the following list of possible uses for house price indexes: • •As a general macroeconomic indicator (of inflation); • •As an input into the measurement of consumer price inflation; • •As an element in the calculation of household (real) wealth and • •As a direct input into an analysis of mortgage lender's exposure to risk of default. →統計としての整備の重要性
. Background paper &共同研究者– Badarinza, C., T. Ramadorai, and C.Shimizu. (2019), ''Nationality Bias at Home and Abroad: Theory and Evidence from Commercial Real Estate," SSRN-id3141255. — Miyakawa,D., C.Shimizu and I.Uesugi. (2019), “Geography and Realty Prices:Evidence from International Transaction-Level Data," RIETI Discussion Paper,19-E-11. — Deng, Y; X. Guo, D. McMillen and C. Shimizu(2018), “Change in the Distribution of Sale/Rental Prices: Comparison of Beijing and Tokyo," Presented at Society of Economic Measurement, D-4-3(Xiamen University, China). — Deng, Y; X. Guo, D. McMillen and C. Shimizu(2018), "Spatial Estimates of Bubbles: Tokyo House Prices and Rents,”Presented at AREUEA-Asia2018, (Jinan University, China) – Deng, Y; X. Guo, D. McMillen and C. Shimizu(2018), ''Distributional House Price Indices for Tokyo Metropolitan Area,’’Presented at ASA Philadelphia 2018. MIT Center for Real Estate: Price Dynamics Platformとの連携と共同研究PRICE DYNAMICS PLATFORM ABOUT Center for Real Estate
Analytics.
Below are the analytical products currently offered to the public by the Platform. We presently publish three products: (1) A Total Return Index (TRI) suite, (2) Forecasts of RCA Commercial Property Price Indices (CPPIs), and (3) An Investors Supply/Demand Index (ISDI). We aspire to update these products on a regular basis. If you wish to be notified about updates to the products, mail us here. Please click on the links below to download the files. White papers describing the product methodologies will be added to this site in due course.
Research Team
Dorinth van Dijk PhD Candidate Professor Real Estate Valuation
The RCA Commercial Property Price Indices (RCA CPPI™) are a suite of price indices developed and published quarterly. They are transaction-based and measure commercial real estate price movements using a repeat-sales regression methodology. 350+ Indices across 15 countries 41 Regional Indices 50 National Level Indices 190 Metro/Market Level Indices Top 25 Global Cities Composite
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. Background paper &共同研究者— Suzuki,M.,  S. E. Ong , Y.Asami , C. Shimizu. (2018), '' Long-Run Renewal of REIT Property Portfolio through Strategic Divestment’’ (mimeo) submitted to Journal of Real Estate Finance and Economics. – Shimizu, C. (2017), "Micro-Structure of Asset Prices, Property Income, and Discount Rates in Tokyo Residential Market,” International Journal of Housing Market and Analysis, 10 (4), 552-571. – Shimizu, C., W. E. Diewert, K. G. Nishimura and T. Watanabe (2015) , ''Estimating Quality Adjusted Commercial Property Price Indexes Using Japanese REIT ,” Journal of Property Research, 32(3), 217-239.デイビッド・ゲルトナー ・清水千弘(2015)「商業不動産価格はどのように測定すればいいのか?」経済研究,第66巻,第3号, 194-208. Two Discount Rate( rm ) from Appraisal & Stock market
Appraisal Price, Rent and Discount Rate
2005/3 2006/3 2007/3
……公示地価(東京都) -・・市街地価格指数(商業地,東京区部)不動産価格指数(オフィス,東京都) ----鑑定評価価格指数-市場評価価格指数2018/3
. Background paper &共同研究者–   Diewert, W. E. and C. Shimizu (2016), "Hedonic Regression Models for Tokyo Condominium Sales," Regional Science and Urban Economics, 60, 300-315. — Shimizu,C, K.G.Nishimura and T.Watanabe(2016), "House Prices at Different Stages of Buying/Selling Process ,” Regional Science and Urban Economics, 59, 37-53. Diewert, W. E. and C. Shimizu (2015), "Residential Property Price Indexes for Tokyo," Macroeconomic Dynamics , 19(8),1659-1714. Karato, K, O. Movshuk and C. Shimizu (2015), "Semiparametric Estimation of Time, Age and Cohort Effects in An Hedonic Model of House Prices ,” Asian Economic Journal, 29(4), 325–345. Shimizu, C., K. G. Nishimura and K. Karato (2014), ''Nonlinearity of Housing Price Structure    -Secondhand Condominium Market in Tokyo Metropolitan Area-," International Journal of Housing Markets and Analysis, 7(3), 459-488. Shimizu, C. (2014), “Estimation of Hedonic Single-Family House Price Function Considering Neighborhood Effect Variables," Sustainability,6, 2946-2960. Shimizu, C., K. G. Nishimura and T. Watanabe (2010), "House Prices in Tokyo - A Comparison of Repeat-sales and Hedonic Measures-," Journal of Economics and Statistics, 230 (6), 792-813. — — CSIS-Real Estate Information Science Lab
POINT
1986 – 1990 1991-1995 CSIS-Real Estate Information Science Lab Record num: 22,723 Year: 2017 Scale: 1:181,285 Column: price per unit of area 0.00 - 1000.00 =   1000.00 - 2000.00 ■ 2000.00 - 35000.00 ■ 35000.00 - 6000.00 ■ 6000.00 - 0.00 - 1000.00 =   1000.00 - 2000.00 ■ 2000.00 - 35000.00 ■ 35000.00 - 6000.00 Rent Record num: 605,996 Year: 2017 Scale: 1:181,285 Column: Monthly Price 0.00 - 5000.00 =    5000.00 - 10000.00 =    1000.00 - 5000.00 ■　5000.00 - 10000.00 10000.00 - Rent Record num: 605,996 Year: 2017 Scale: 1:45,386 Column: Monthly Price 0.00 - 5000.00 5000.00 - 10000.00 =    1000.00 - 5000.00 ■　5000.00 - 10000.00 10000.00 -
研究プロジェクト2:その他指標開発
•不動産取引・利用の状態と変化がリアルタイムで把握可能な指標開発。 .取引価格情報を用いた所有権移転に関する指標開発を行う。高齢化が進展する中では，所有権移転として相続件数が飛躍的に上昇してきている。その一方で，所有者すら把握できない不動産が増加している。本研究プロジェクトでは，地図基盤などを用いて，相続指標，所有権移転指標の開発を行う。 .建物利用に関わる時系列的な変化が測定できる指標開発を行う。不動産市場の動的な変化の中で，地上げなどの投機的な取引を招くことで土地の効率的な利用を阻害し，都市の生産性を低下させると指摘されてきた。しかしながら，この点に関する定量的な検証は限られている。そこで，大規模データを用いて不動産市場のダイナミクスと建物利用に基づく生産性との関係を解明する。
首都圏における土地取引面積流動率(%)土地取引件数密度変化率*所有権移転・相続移転・競売等の登記原因別、市町村のみならずメッシュ単位、建物単位での指標化を開発していく。居住環境指標の開発:シカゴ大学との共同研究● What are key factors about the growth of cities? • Storper and Scott (2009) argued that the growth of cities is profoundly related to characteristics of residents in cities and how the population characteristics change over time. • Cities are defined as places that attract many and diverse people, and they promote sharing, exchanging, and generating new information (Florida (2009), Jacobs (1969)). • Because of these characteristics of cities, Jacobs (1969) and Florida (2009) mentioned that cities can generate new ideas and technologies that make possible their strong and stable growth.
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•オ田友美・長田充弘・篠崎公昭・肥後雅博・清水千弘(2019), 「我が国における建設物価指数の作成方法の課題」総務省統計委員会担当室ワーキングペーパー  2019- WP02. •舘祐太・清水千弘・肥後雅博(2019),  「建築着工統計の個票データを用いた建築物価指数の作成」総務省統計委員会担当室ワーキングペーパー  2019-WP01.
東京大学空間情報科学研究センター 特任教授東京大学柏の葉キャンパス〒277-8568千葉県柏市柏の葉5-1-5総合研究棟4階 451号室電話:03-6453-1715(研究室直通) , Fax:04-7136-4292 Email: cshimizu@csis.u-tokyo.ac.jpマサチューセッツ工科大学不動産研究センター研究員Massachusetts Institute of Technology Center for Real Estate 105 Massachusetts Ave, Cambridge, MA 02139 Tel: (+1) 617-253-4373,(Office), Fax: (+1) 617-253-4373 e-mail: cshimizu@mit.edu日本大学スポーツ科学部教授〒154-8513東京都世田谷区下馬3-34-1電話:03-6453-1715(研究室直通) , Fax:03-6453-1630 Email: shimizu.chihiro@nihon-u.ac.jp