elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Estimating bid-auction models of residential location using census data with imputed household income

Heldt, Benjamin and Bahamonde Birke, Francisco Jose and Donoso, Pedro and Heinrichs, Dirk (2018) Estimating bid-auction models of residential location using census data with imputed household income. Journal of Transport and Land Use, 11 (1), pp. 1101-1123. University of Minnesota. DOI: http://dx.doi.org/10.5198/jtlu.2018.1040 ISSN 1938-7849

[img] PDF
1MB

Official URL: https://www.jtlu.org/index.php/jtlu/article/view/1040

Abstract

Modeling residential location as a key component of the land-use system is essential to understand the relationship between land use and transport. The increasing availability of censuses such as the German Zensus 2011 has enabled residential location to be modeled with a large number of observations, presenting both opportunities and challenges. Censuses are statistically highly representative; however, they often lack variables such as income or mobility-related attributes as in the case of Zensus 2011. This is particularly problematic if missing variables define utility or willingness-to-pay functions that characterize choice options in a location model. One example for this is household income, which is an indispensable variable in land use models because it influences household location preferences and defines affordable location options. For estimating bid-auction location models for different income groups, we impute household income in census data applying an ordered regression model. We find that location models considering this imputation perform sufficiently well as they reveal reasonable and expected aspects of the location patterns. In general, imputing choice variables should thus be considered in the estimation of residential location models but is also promising for other decision problems. Comparing results for two imputation methods, we also show that while applying the deterministic first preference imputation may yield misleading results the probabilistic Monte Carlo simulation is the correct imputation approach.

Item URL in elib:https://elib.dlr.de/123889/
Document Type:Article
Title:Estimating bid-auction models of residential location using census data with imputed household income
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Heldt, Benjaminbenjamin.heldt (at) dlr.dehttps://orcid.org/0000-0003-1053-835X
Bahamonde Birke, Francisco Josefrancisco.bahamondebirke (at) dlr.deUNSPECIFIED
Donoso, Pedropedrodonosos (at) gmail.comUNSPECIFIED
Heinrichs, Dirkdirk.heinrichs (at) dlr.dehttps://orcid.org/0000-0003-1242-2617
Date:2018
Journal or Publication Title:Journal of Transport and Land Use
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:11
DOI :http://dx.doi.org/10.5198/jtlu.2018.1040
Page Range:pp. 1101-1123
Editors:
EditorsEmail
UNSPECIFIEDUniversity of Minnesota Center for Transportation Studies
Publisher:University of Minnesota
ISSN:1938-7849
Status:Published
Keywords:land use; residential location; missing data; census; estimation; household income
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Transport System
DLR - Research area:Transport
DLR - Program:V VS - Verkehrssystem
DLR - Research theme (Project):V - Verkehrsentwicklung und Umwelt II (old), V - Urbane Mobilität (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transport Research > Mobility and Urban Development
Deposited By: Heldt, Benjamin
Deposited On:03 Dec 2018 09:47
Last Modified:03 Dec 2018 09:47

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.