Seminar paper. Professor Kunst. The environmental property price effect in Padua. using panel data



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Seminar paper Professor Kunst The environmental property price effect in Padua using panel data by Petra Amrusch 2005

The environmental property price effect in Padua using panel data 1. Introduction The motivation posed by this seminar paper is the evaluation of the impact of air quality on the housing market in Padua using panel data from March 2003, May and July 2003. Possible effects of air pollutants caused by urban traffic on property prices will be exploited on the hedonic pricing model (HPM), introduced by Rosen (1974). Two data sources provide the essential information for this study. The ARPAV (The Regional Agency for Environmental Prevention and Protection of Veneto) provides data on C 6 H 6 (benzene) and traffic densities for which weighted averages were calculated.. Data on housing characteristics and property prices are obtained from advertisements published by various real estate agencies in the brochures Attico, Proposte Immobiliari, Casaffari, Vetrina immobiliare, Il Corriere Immobiliare. According to Freeman (1994) and brokers in Padua, the data published by real estate brokers assure that market prices are used. 2. Estimation of the property price effect On the basis of the specification plan of residential areas and variants (e.g. town development plan 1, the residential zoning plan, 2 samples of properties are drawn from residential settlements in the centre, outlying residential quarters and semi-central residential settlements that are mainly adjacent to the centre that should be homogenous with respect to greenery, public facilities, quiet, distance to the centre and accessibility. 1 http://www.padovanet.it/prg/download_fogli_zto.htm 10.11.2003 2 http://www.padovanet.it/prg/pdf/a1-a2-a3-a4/tav.a2/vi.pdf 2.5.2003 1

All 42 observations in the sample are defined by similar characteristics apartments are chosen in districts with similar socio-economic, criminality, etc. criteria, but differing in terms of environmental criteria (traffic density, benzenes) etc. The aim of the panel is to describe how 14 apartments the influence of different characteristics influence the property price/sqm over 3 points of time. Since it is impossible to find 14 apartments that are resold/bought 3 times within a period of half a year, different apartments with very similar housing characteristics (e.g. number of rooms, age of the apartment (new, restored etc.), floor) are chosen in one area/street in the way that 3 observations could be assumed to be representative for 1 apartment over 3 periods. The sample was also not random in the sense that in the second two periods only apartments were included at a similar or slightly higher price level/sqm representing one apartment (resold or offered 3 times) in the first period, since it is not realistic that the same house in the same location is offered/sold first at a high price and after 2 month at a lower price due to different reasons: 1. The general housing market is on an upward trend in Italy 3 (and Padua) 2. If a house is not sold within a short period, an experienced owner/broker would not decrease the price at once, otherwise his ability in price setting (e.g. from appraisals)/professionalism would not be questionable and his reputation would suffer.; L'agente immobiliare che alza artificialmente il prezzo per soddisfare il proprietario, ed ottenere cosi' l'incarico a vendere, dimostra una evidente mancanza di professionalità, e quindi anche una scarsa affidabilità Auch die Bewertung der Immobilie unter dem Marktpreis, die dann der Makler meist durch einen Aufpreis ausgleicht, weist ebenfalls auf mangelhafte Professionalität hin und kann illegal sein, wenn der Verkäufer dadurch geschädigt wird. Überdies ist diese Methode, bei der zwischen Verkäufer und Makler ein Minimalpreis festgelegt wird und der Makler den 3 http://www.waycasa.net/root/acquisto_art_1570.html 17. 11. 2003 2

Aufpreis mit dem Käufer aushandelt, nie zum Vorteil des Verkäufers und wird daher selten angewendet 4 ) 3. The hedonic model relies on real market prices : if a house would be offered at a lower price within this short time period due to other reasons (transactions among relatives 5 or if the seller is forced to sell due to financial problems), the real market price would be biased and the inclusion of such observations would not be reflect the assumptions of the hedonic model. 4. Pooled regression results The first variant of the hedonic specification employed here is: 1. Regression including D001 and D010: Dependent Variable: LOG(SQMP?) Method: GLS (Variance Components) Date: 09/13/05 Time: 12:47 Sample: 1901 1903 Included observations: 3 Total panel observations 42 Variable Coefficient Std. Error t-statistic Prob. C 4.875708 0.620298 7.860264 0.0000 D001 0.336334 0.049272 6.826038 0.0000 D010 0.143960 0.048469 2.970151 0.0052 C6H6? -0.004000 0.001276-3.133350 0.0034 LOG(SQ?^2) 0.290676 0.080704 3.601751 0.0009 Random Effects 1 C 0.193301 2 C 0.197500 3 C 0.189413 4 C -0.200264 5 C 0.180127 6 C -0.064103 7--C 0.349568 8--C 0.044131 9--C 0.192106 10--C 0.141701 11--C -0.323813 12--C 0.316166 13--C -0.140201 14--C -1.075632 GLS Transformed Regression R-squared 0.960417 Mean dependent var 7.248117 4 http://web.tiscali.it/no-redirect-tiscali/edilsud/infoagenzie.htm 13. 12. 2003 5 Vgl. Vainio, Matti: Traffic noise and air pollution 1995 p. 55 3

Adjusted R-squared 0.956138 S.D. dependent var 0.607691 S.E. of regression 0.127270 Sum squared resid 0.599317 Durbin-Watson stat 1.828523 Unweighted Statistics including Random Effects R-squared 0.975202 Mean dependent var 7.248117 Adjusted R-squared 0.972521 S.D. dependent var 0.607691 S.E. of regression 0.100735 Sum squared resid 0.375463 Durbin-Watson stat 2.918704 where D001 and D010 are positive due to the increasing price level in the sample and a 1 unit reduction in the C 6 H 6 pollution level decreases the property price/sqm by 0.004%. There is also a significant relation between LOG(square metres*square metres) and the LOG(property price/sqm). Other individual housing characteristics are explained by random effects. The fitting is satisfactory (97.5 the variation in P/sqm are explained). The DW-Statistic shows a negative autocorrelation of residuals after the inclusion of the Dummy Variables D001 and D010 in comparison to the following pooled regression: 2. Regression without TimeDummy variables D001, D010 Dependent Variable: LOG(SQMP?) Method: GLS (Variance Components) Date: 09/13/05 Time: 12:57 Sample: 1901 1903 Included observations: 3 Total panel observations 42 Variable Coefficient Std. Error t-statistic Prob. C 3.553304 0.673372 5.276877 0.0000 C6H6? -0.007055 0.001757-4.015058 0.0003 LOG(SQ?^2) 0.490904 0.091777 5.348885 0.0000 Random Effects 1 C 0.120968 2 C 0.115902 3 C 0.108139 4 C -0.226996 5 C 0.180160 6 C -0.098166 7--C 0.257470 8--C 0.024653 9--C 0.111132 10--C 0.104291 11--C -0.324678 12--C 0.261948 13--C -0.166307 14--C -0.468514 GLS Transformed Regression R-squared 0.872006 Mean dependent var 7.248117 4

Adjusted R-squared 0.865442 S.D. dependent var 0.607691 S.E. of regression 0.222914 Sum squared resid 1.937934 Durbin-Watson stat 1.548859 Unweighted Statistics including Random Effects R-squared 0.899749 Mean dependent var 7.248117 Adjusted R-squared 0.894608 S.D. dependent var 0.607691 S.E. of regression 0.197281 Sum squared resid 1.517877 Durbin-Watson stat 1.977490 In this case the DW-Test shows no autocorrelation of residuals, although the sample was chosen non-random. 3. Regression including D001 and an additional housing characteristic Dependent Variable: LOG(SQMP?) Method: GLS (Variance Components) Date: 09/13/05 Time: 13:02 Sample: 1901 1903 Included observations: 3 Total panel observations 18 Cross sections without valid observations dropped Variable Coefficient Std. Error t-statistic Prob. C 2.658709 0.846884 3.139400 0.0078 D001 0.377578 0.093683 4.030372 0.0014 C6H6? -0.008861 0.002959-2.995006 0.0103 LOG(SQ?^2) 0.584785 0.125489 4.660057 0.0004 GARD? 0.243696 0.130540 1.866825 0.0846 Random Effects 1--C 0.072776 2--C 0.141611 11--C -0.263356 12--C 0.348179 13--C -0.084133 14--C -0.215077 GLS Transformed Regression R-squared 0.967589 Mean dependent var 7.027372 Adjusted R-squared 0.957617 S.D. dependent var 0.861470 S.E. of regression 0.177352 Sum squared resid 0.408899 Durbin-Watson stat 2.779385 Unweighted Statistics including Random Effects R-squared 0.974339 Mean dependent var 7.027372 Adjusted R-squared 0.966443 S.D. dependent var 0.861470 S.E. of regression 0.157809 Sum squared resid 0.323747 Durbin-Watson stat 3.510420 Including another housing characteristic : garden that differs more than other housing variables and D001 also increases the DW-Statistic: 5

4. Regression results with inclusion of D010 without D001: Dependent Variable: LOG(SQMP?) Method: GLS (Variance Components) Date: 09/13/05 Time: 13:03 Sample: 1901 1903 Included observations: 3 Total panel observations 18 Cross sections without valid observations dropped Variable Coefficient Std. Error t-statistic Prob. C 2.833035 0.980257 2.890095 0.0126 D010-0.187334 0.135585-1.381677 0.1904 C6H6? -0.008916 0.004058-2.197358 0.0467 LOG(SQ?^2) 0.582304 0.155672 3.740589 0.0025 GARD? 0.442211 0.187266 2.361402 0.0345 Random Effects 1--C -0.005860 2--C 0.113161 11--C -0.201681 12--C 0.306691 13--C -0.036831 14--C -0.175479 GLS Transformed Regression R-squared 0.930358 Mean dependent var 7.027372 Adjusted R-squared 0.908929 S.D. dependent var 0.861470 S.E. of regression 0.259974 Sum squared resid 0.878625 Durbin-Watson stat 2.208719 Unweighted Statistics including Random Effects R-squared 0.939281 Mean dependent var 7.027372 Adjusted R-squared 0.920599 S.D. dependent var 0.861470 S.E. of regression 0.242747 Sum squared resid 0.766039 Durbin-Watson stat 2.533337 Including merely D010, it is notable that the Dummy variable is insignificant. Summarizing, C 6 H 6 - pollutants that define the negative effect of air pollution on the property price/sqm in the semicentral and outlying areas of Padua in the first half of 2003. 6

5. References 1. Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto ARPAV: 1. Rapporto annuale sullo stato dell ambiente a Padova 2002 -- MINISTERO DELL AMBIENTE E DELLA TUTELA DEL TERRITORIO; Bando 2000 per il cofinanziamento dei processi di Agenda 21 locale. http://www.padovanet.it/infoambiente/padova21/rsa/rsa.pdf 2. Freeman III, A. Myrick: The Measurement of Environmental and resource values, Theory and Methods Resource for the future, 2. Aufl., Washington 1994. 3. Vainio, Matti: Traffic noise and air pollution Helsinki: Helsingin Kauppakorkeakoulu, 1995. http://www.padovanet.it/prg/download_fogli_zto.htm 10.11.2003 http://www.padovanet.it/prg/pdf/a1-a2-a3-a4/tav.a2/vi.pdf 2.5.2003 http://www.waycasa.net/root/acquisto_art_1570.html 17. 11. 2003 http://web.tiscali.it/no-redirect-tiscali/edilsud/infoagenzie.htm 13. 12. 2003 7