What Price for “Free” On-Street Parking?
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Image source: jaymantri.com, CC0 licensed What price for “free” on-street parking? Tiziano Colombo Supervision: Prof. Dr.Kay W. Axhausen Georgios Sarlas, MSc Bachelor Thesis Civil Engineering June 2018 What price for “free” on-street parking? June 2018 Acknowledgements I would like to thank Prof. Kay W. Axhausen for giving me the possibility to do this bachelor thesis and for the meetings that were very useful in terms of getting the main points of the thesis. An enormous thanks goes to my supervisor Georgios Sarlas for the grand support and help provided each time I needed it, especially for helping me with the statistic software R and with the QGIS software, providing me all the datasets and giving me important and always useful advices on how to proceed. I would also like to thank Thomas Schatzmann for the help provided with QGIS. I would finally thank all the people that supported me in every way possible as my family and my friends. i What price for “free” on-street parking? June 2018 Bachelor Thesis What price for “free” on-street parking? Tiziano Colombo Bergacker 38, 8046 Zürich, Switzerland Phone: +41-79 194 68 75 E-Mail: [email protected] June 2018 Abstract The effect of the different parking categories on the rental price of rental units is quantified with hedonic pricing models. Two models are considered, which use different explained variables: The first describes the net rental price per month, while the second the net rental price per month per square meter. The main parking categories considered are blue zone, non-blue zone on-street parking and private parking. The spatial autocorrelation is taken into account with the SARerror model, with a weight matrix computed on a 100-meter radius and an over the distance inversed weighting, and the GWR model taking into account different neighbourhood depending on the model. All the building related variables increase the price, all the distances from services decrease it. A zone with a high percentage of blue zone parking spaces is likely to have higher rental prices up to the 8% and 0.8 CHF/m2 while if the percentage of private parking is high the rental price can lower down to 20% and 5.85 CHF/m2. Testing the parking categories not relating them to their total number appear to have a very small influence. Keywords Free parking; Spatial regression; House pricing; Real estate, Hedonic pricing Preferred citation style Colombo, T. (2018), What price for „free” on-street parking?, Bachelor Arbeit, IVT, ETH Zurich, Zurich. ii What price for “free” on-street parking? June 2018 Table of contents 1 Introduction .............................................................................................................................. 7 2 Background ............................................................................................................................... 8 2.1 Study area: City of Zurich ...................................................................................................... 8 2.2 Parking in Zurich ................................................................................................................... 9 2.3 Real estate market ................................................................................................................ 11 2.4 Influence of parking on the real estate market ..................................................................... 12 3 Hedonic Pricing Methodology ................................................................................................ 13 3.1 Background .......................................................................................................................... 13 3.2 OLS ...................................................................................................................................... 13 3.3 SAR ...................................................................................................................................... 14 3.4 GWR .................................................................................................................................... 16 4 Case study: Zurich .................................................................................................................. 17 4.1 Data description and analysis ............................................................................................... 17 4.2 Real Estate Data ................................................................................................................... 20 4.3 Parking Data ......................................................................................................................... 28 4.4 Hypothesis............................................................................................................................ 33 4.5 Potentially relevant variables tested ..................................................................................... 34 5 Model results .......................................................................................................................... 40 5.1 OLS models ......................................................................................................................... 40 5.2 SAR models ......................................................................................................................... 45 5.3 GWR model ......................................................................................................................... 52 6 Discussion ............................................................................................................................... 56 6.1 Comparison between the models ......................................................................................... 56 6.2 Estimates of the OLS Models .............................................................................................. 57 6.3 Estimates and lambda of the SAR Models .......................................................................... 61 6.4 Estimates of the GWR Models ............................................................................................ 62 6.5 Limitations of the model and its variables ........................................................................... 63 7 Conclusions ............................................................................................................................ 64 iii What price for “free” on-street parking? June 2018 8 Literature ................................................................................................................................ 65 Appendix ........................................................................................................................................ 68 List of tables Table 1: Potentially relevant variables ...................................................................................... 34 Table 2: Descriptive statistics of potentially relevant variables ............................................... 37 Table 3: OLS model 1 (log(rent)) ............................................................................................. 43 Table 4: OLS model 2 (rent per square meter) ......................................................................... 44 Table 5: Result of the Moran’I Test .......................................................................................... 45 Table 6: Result of the Lagrange-multiplier Test for model 1 ................................................... 46 Table 7: Result of the Lagrange-multiplier Test for model 2 ................................................... 46 Table 8: SARerror model 1 (log(rent)) ..................................................................................... 47 Table 9: SARerror model 2 (rent per square meter) ................................................................. 48 Table 10: Comparison between OLS and SARerror ................................................................. 49 Table 11: GWR model 1 (log(rent)) ......................................................................................... 53 Table 12: GWR model 2 (rent per square meter) ..................................................................... 54 Table 13: Comparison between the models ............................................................................. 56 List of figures Figure 1: Subdivision of Zurich in 12 quarters and in 216 statistical zones. .............................. 8 Figure 2: Distribution of on-street parking ............................................................................... 10 Figure 3: UBS Swiss real estate bubble index .......................................................................... 11 Figure 4: Number of web based housing ads by statistical zone .............................................. 18 Figure 5: Statistical zone division and names ........................................................................... 19 Figure 6: Average monthly gross rent by statistical zone (a) and average rent histogram (b) . 20 Figure 7:Average monthly gross rent per square meter by statistical zone (a) and average rent per square meter (b) .................................................................................................................. 21 Figure 8: Visible square meters of lake by statistical zone ....................................................... 22 Figure 9: Average square meters by statistical zone (a) and average square meter histogram (b) .............................................................................................................................................