Construction of register-based commuting measures
(2018) In CESifo Economic Studies 64(2). p.292-326- Abstract
Early empirical studies in labour and urban economics addressing the role of commuting (on, e.g., wages and locational choice) have typically been confined to the use of survey data. Researchers are, however, increasingly getting access to large register databases with detailed information on where individuals live and work. A variety of methods have thus emerged to exploit the geocoded characteristic of the data to calculate commuting measures that go beyond simple Euclidean metrics. These methods involve new techniques that make use of geographic information system (GIS) routing software or application programming interfaces provided by third-party developers. This article provides (i) a brief survey of the small but emerging... (More)
Early empirical studies in labour and urban economics addressing the role of commuting (on, e.g., wages and locational choice) have typically been confined to the use of survey data. Researchers are, however, increasingly getting access to large register databases with detailed information on where individuals live and work. A variety of methods have thus emerged to exploit the geocoded characteristic of the data to calculate commuting measures that go beyond simple Euclidean metrics. These methods involve new techniques that make use of geographic information system (GIS) routing software or application programming interfaces provided by third-party developers. This article provides (i) a brief survey of the small but emerging literature that uses geocoded register data to calculate different commuting measures, (ii) an example on how register-based commuting measures can be constructed along with descriptive evidence on how different commuting measures compare for different socio-economic groups using rich Swedish register data, (iii) a discussion of the pros and cons of different methods and measures, and (iv) a discussion of the potential of using mobile phone data to further improve registerbased commuting measures.
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- author
- Blind, Ina LU ; Dahlberg, Matz ; Engström, Gustav LU and Östh, John
- publishing date
- 2018-06-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Commuting measures, Geocoded register data, Mobile phone data
- in
- CESifo Economic Studies
- volume
- 64
- issue
- 2
- pages
- 35 pages
- publisher
- Oxford University Press
- external identifiers
-
- scopus:85048520129
- ISSN
- 1610-241X
- DOI
- 10.1093/cesifo/ify014
- language
- English
- LU publication?
- no
- id
- d9326a3b-8023-43a1-9ff7-f7b5257a1354
- date added to LUP
- 2019-05-21 13:21:32
- date last changed
- 2022-03-30 13:47:23
@article{d9326a3b-8023-43a1-9ff7-f7b5257a1354,
abstract = {{<p>Early empirical studies in labour and urban economics addressing the role of commuting (on, e.g., wages and locational choice) have typically been confined to the use of survey data. Researchers are, however, increasingly getting access to large register databases with detailed information on where individuals live and work. A variety of methods have thus emerged to exploit the geocoded characteristic of the data to calculate commuting measures that go beyond simple Euclidean metrics. These methods involve new techniques that make use of geographic information system (GIS) routing software or application programming interfaces provided by third-party developers. This article provides (i) a brief survey of the small but emerging literature that uses geocoded register data to calculate different commuting measures, (ii) an example on how register-based commuting measures can be constructed along with descriptive evidence on how different commuting measures compare for different socio-economic groups using rich Swedish register data, (iii) a discussion of the pros and cons of different methods and measures, and (iv) a discussion of the potential of using mobile phone data to further improve registerbased commuting measures.</p>}},
author = {{Blind, Ina and Dahlberg, Matz and Engström, Gustav and Östh, John}},
issn = {{1610-241X}},
keywords = {{Commuting measures; Geocoded register data; Mobile phone data}},
language = {{eng}},
month = {{06}},
number = {{2}},
pages = {{292--326}},
publisher = {{Oxford University Press}},
series = {{CESifo Economic Studies}},
title = {{Construction of register-based commuting measures}},
url = {{http://dx.doi.org/10.1093/cesifo/ify014}},
doi = {{10.1093/cesifo/ify014}},
volume = {{64}},
year = {{2018}},
}