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06-25-2015ERES 2015 | Main Sessions A Hedonical Spatial Office Rent Index An Application for Madrid Market Ramiro J. Rodríguez A presentation for ERES.

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Presentation on theme: "06-25-2015ERES 2015 | Main Sessions A Hedonical Spatial Office Rent Index An Application for Madrid Market Ramiro J. Rodríguez A presentation for ERES."— Presentation transcript:

1 06-25-2015ERES 2015 | Main Sessions A Hedonical Spatial Office Rent Index An Application for Madrid Market Ramiro J. Rodríguez A presentation for ERES 2015 - Regular Sessions | Istanbul, Turkey The opinions and analyses are the responsibility of the authors and, therefore, do not necessarily coincide with those of BNP Paribas Real Estate

2 06-25-2015ERES 2015 | Main Sessions Motivation for the research 1.Explaining office letting rents dynamics with an econometric approach 1.An alternative to [weighted] average rents to describe rents evolution 2.Study the impacts of hedonic characteristics 2.Implementing spatial models for the office market 3.Performance comparison between ‘classical’ hedonic models and spatial hedonical models

3 ERES 2015 | Main Sessions Main findings Significant evidence on spatial feedback Spatial models have higher explanatory capacity than classical hedonical estimations Non-time variant unseen characteristics captured via Spatial endogenous-variable-lag model Business district, age, technical building quality are the main determinants of prices Spatial rent index indicates a lower rent in Madrid in the crisis period than shown by average rents –Sample composition issues corrected –Surface biases corrected 06-25-2015

4 Performance comparison (€/sqm/month) ERES 2015 | Main Sessions06-25-2015

5 ERES 2015 | Main Sessions On estimation methods Average rents present skewness towards –Large transactions –More transacted area Hedonical models: Not affected by deal sizes yielding more realistic estimated rents Spatial approach: –Fits the idea of non-observed interdependence of price levels among neighbours in real estate transactions –Uses the full power of the database, in opposition to pseudo-panels 06-25-2015

6 ERES 2015 | Main Sessions Market stylized facts Relatively small Madrid’s market, averaging 500,000 sqm of gross absorption each year with around 120 letting transactions Spanish crisis deeply affecting office market –Office space take-up more than halved –Prime rents plummeted 40% –Average rents decreasing around 30% –Strong implementation incentives for new contracts Demand seems to be recovering in 2015 06-25-2015

7 ERES 2015 | Main Sessions Market stylized facts – Prime rents Source: BNPPRE 06-25-2015

8 ERES 2015 | Main Sessions Reference literature Marginal effects Rent index Externalities Hedonic estimations Controlling underlying property characteristics Marginal effects Panel data Controlling unseen location feedback Lagged, error and Durbin models Panel data and pseudo panels Spatial econometrics Kain and Quigley (1970) Straszheim (1974) Clapp (1980) Torto and Wheaton (1994) Malle (2009) Quigley (1995) Gao and Wang (2007) Hansen (2009) Osland (2013) Cliff and Ord (1973, 1981) Anselin (1988, 1996) Kapoor, Kelejian and Prucha (2004) LeSage (2005) Rambaldi and Prasada (2011) 06-25-2015

9 ERES 2015 | Main Sessions Variables and data DDBB with most of the hedonic variables identified the literature review o Transaction list provided by BNP Paribas Real Estate (3,600 obs) o Matched with information from the Spanish Land Registry (Cadastre) o Structure: Half year data o Start date: 2003:1 o End date: 2014:1 o Rent deflated by the implicit GDP deflator (2010=100) 06-25-2015

10 ERES 2015 | Main Sessions Variable definition Endogenous: Real office rent per square meter (rrent)*  Headline rent from new contracts list Regressors: Business districts* (CBD, Centre, Decentralized, Outskirts  left out in regressions) Building characteristics** (Age, Stately, Exclusive, Stories, Quality index, distance to metro entrance) Lease contract*** (Corporate tenant  Dummy variable as commitment proxy ) Time dummies*** (H1 2003  left out in regressions) Spatial instrument Geographic coordinates** (X_coord Y_coord) Source: * BNPPRE ** Cadastre *** Calculated 06-25-2015

11 Office zones ERES 2015 | Main Sessions06-25-2015

12 Market intensity Office transactions Q1-Q4 2014 ERES 2015 | Main Sessions Transaction density under 100 mts. 2468010 06-25-2015

13 ERES 2015 | Main Sessions Spatial hedonical model (1) 06-25-2015

14 Spatial hedonical model (2) ERES 2015 | Main Sessions06-25-2015

15 ERES 2015 | Main Sessions Regression analysis (OLS) Number of observations: 3,912 R-Squared: 0.62 Root MSE: 0.22 Estimatorp-valueEstimatorp-valueEstimatorp-value cons2.75950.0000 cbd0.56580.0000H12004-0.10500.0000H12010-0.18700.0000 centre0.37530.0000H22004-0.11940.0000H22010-0.24640.0000 dec0.16900.0000H12005-0.12760.0000H12011-0.25100.0000 age-0.00120.0000H22005-0.09370.0000H22011-0.30630.0000 floors0.00210.0000H12006-0.06710.0000H12012-0.33840.0000 exclusive0.07520.0000H22006-0.05860.0010H22012-0.40910.0000 qual_adj-0.05000.0000H120080.06220.0010H12013-0.43640.0000 metro_distance-0.000010.0000H12009-0.08930.0000H22013-0.44270.0000 corporate0.09390.0000H22009-0.14820.0000H12014-0.47130.0000 06-25-2015

16 Regression analysis (Spatial) ERES 2015 | Main Sessions TestStatisticdfp-value ---------------------------------------------------------------------------------- Spatial error: Moran's I60.99610.000 Lagrange multiplier2683.7510.000 Robust Lagrange multiplier 1929.9810.000 Spatial lag: Lagrange multiplier 873.30810.000 Robust Lagrange multiplier 119.53610.000 ---------------------------------------------------------------------------------- 06-25-2015

17 ERES 2015 | Main Sessions Regression analysis (Spatial) Number of observations: 3,912 Variance ratio: 0.665 Estimatorp-valueEstimatorp-valueEstimatorp-value cons0.41340.0000H22003-0.03070.1070H12010-0.20770.0000 rho0.88630.0000H12004-0.13260.0000H22010-0.26250.0000 cbd0.27510.0000H22004-0.15510.0000H12011-0.26670.0000 centre0.12430.0000H12005-0.15640.0000H22011-0.32910.0000 dec0.02680.0330H22005-0.12170.0000H12012-0.36620.0000 age-0.00170.0000H12006-0.09160.0000H22012-0.42590.0000 stately0.02730.0400H22006-0.08030.0000H12013-0.46610.0000 floors0.00260.0000H12007-0.04740.0050H22013-0.46810.0000 exclusive0.08040.0000H120080.04480.0110H12014-0.48460.0000 qual_adj-0.04640.0000H12009-0.10900.0000 corporate0.08770.0000H22009-0.16880.0000 06-25-2015

18 Stability test 04-18-2015ERES 2015 | Main Sessions

19 Marginal effects comparison ERES 2015 | Main Sessions rhoNA0.8863 cons2.75950.4134 cbd0.56580.2751 centre0.37530.2751 dec0.16900.0268 age-0.0012-0.0017 floors0.00210.0026 exclusive0.07520.0804 qual_adj-0.0500-0.0464 metro_distance-0.00001NA corporate0.09390.0877 06-25-2015

20 Residuals normality (non parametric test) ERES 2015 | Main Sessions Parametric tests on residuals yield non-normal residuals distributions Issues on sample size 06-25-2015

21 The prototype office ERES 2015 | Main Sessions cbdcentredecx_coordy_coordage (years)statelyfloorsexclusivequal_adjmetro_distancecorporatelrrent 100441666.684476074.2441112.912.71831? 010442425.284477113.923417.312.61861? 001446734.164475984.321616.613.25621? 000450738.924477704.321912.412.91,5401? 1.Definition of the archetype office Average characteristics by zone Age, floors, metro distance, quality index, geographic coordinates 06-25-2015

22 Hedonical rent estimation ERES 2015 | Main Sessions06-25-2015

23 ERES 2015 | Main Sessions Rent estimation (€/sqm/month) 06-25-2015

24 Rent estimation (€/sqm/month) ERES 2015 | Main Sessions06-25-2015

25 Performance comparison (€/sqm/month) ERES 2015 | Main Sessions Flight to quality 06-25-2015 10 12 14 16 18 20 22 24 Hedonical rentAverage rentGeo-hedonical rentWeighted average rent

26 Rent index ERES 2015 | Main Sessions06-25-2015

27 Conclusions ERES 2015 | Main Sessions 1.Explanatory capacity improves with Spatial models 2.Estimation with spatial component yields normal residuals 3.Estimated rent index corrects: 1.Sample composition effects 2.Deal size issues 4.Classical hedonic techniques issues such as unobservable characteristics are corrected 5.Side products such as semi-elasiticities are valuable for market insights 06-25-2015

28 ERES 2015 | Main Sessions Q&A Suggestions are much appreciated! Thank you 06-25-2015


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