The Annual Conference of the Regional Science Association International Ben-Gurion University of the Negev, 15 April 2008 Semi-Compensatory Model for Rental.

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The Annual Conference of the Regional Science Association International Ben-Gurion University of the Negev, 15 April 2008 Semi-Compensatory Model for Rental Apartment Choice Sigal Kaplan, Shlomo Bekhor, Yoram Shiftan The Faculty of Civil and Environmental Engineering, Technion Photo: Tour-Haifa

Contents Introduction Methodology and survey design Screening results Semi-compensatory model estimation 5 Conclusions

Introduction

Methodology Universal set Chosen alternative Reduced Choice set Elimination Utility maximization Null set Search criteria update Search criteria update

Methodology G - universal choice set Selection probability of choice set S Selection probability of screening criteria threshold combination Selection probability of alternative i from set S q – individual decision maker Manski (1977):

Survey design No results or over 100 results < =100 results Database User information Apartment inventory 600 apartments Apartment inventory 600 apartments User choice Apartment choice Check 7 categorical screening criteria 7 categorical screening criteria Personal information Zone rating Attitudinal survey Personal information Zone rating Attitudinal survey Stated preference survey: Rental apartment choice of students

Survey design

Screening results The survey yielded 1049 valid responses Only 14.4% screened by less than four criteria

Screening results Frequency of screening by each of the 7 criteria

Screening results Average max. price Roommates Price

Semi-compensatory model estimation Maximum price m=1,….M categories. M=10 : 250,300,350,…700 MNL Ordered Probit model for Maximal price Binary Probit model for apartment type (vacant / with roommates) Apartment type t=1,….T categories. T=2 : vacant / with roommates

Semi compensatory model estimation Dependent variable: 1 – vacant apartment 0 – with roommates Binary Probit model for apartment type

Semi compensatory model estimation LR = -2*( ( ))= >> χ 2 (0.05,5)=11.07 Ordered Probit for maximal price

Semi compensatory model estimation

Conclusions A synthetic screening and choice experiment is adequate for tracing real choice processes The survey proves the importance of the screening stage for rental apartment choice The screening criteria depend on individual characteristics 5 The semi-compensatory model has an advantage in comparison with the MNL The selection of the price criteria is related to quality minimal requirement – apartment type

Thank you Photo: Tour-Haifa