Economics at your fingertips  

Measuring Remoteness Using a Data-Driven Approach

Stacey Chen (), Yu-Kuan Chen and Huey-Min Wu
Additional contact information
Yu-Kuan Chen: Teach-for-Taiwan Association
Huey-Min Wu: National Academy for Educational Research, Taiwan

No 17-03, GRIPS Discussion Papers from National Graduate Institute for Policy Studies

Abstract: Datasets of schools or hospitals often include an urban-rural divide drawn by government. Such partition is typically determined by subjective thresholds for a few variables, such as access to transportation and local population size, leaving aside relevant factors despite datavailability. We propose to measure eremoteness f by mapping a comprehensive set of covariates onto a scalar, and define an objective score of remoteness using a standard selection model. We apply the proposed method to data from Taiwanese public elementary schools. Our method replaces 35% and 47% respectively of the current official list of "remote" and "extra-remote" campuses, shifting the remoteness designation to those furthest from train stations, having the highest teacher vacancy percentages, and located in the least populous areas with the least well-educated populations. The campus- and district-level variables used are publicly available and periodically updated in most advanced economies, and the statistical model can be easily implemented.

Pages: 29 pages
Date: 2017-05
New Economics Papers: this item is included in nep-dcm
References: View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) ... bute_id=20&file_no=1 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in GRIPS Discussion Papers from National Graduate Institute for Policy Studies Contact information at EDIRC.
Bibliographic data for series maintained by ().

Page updated 2020-07-03
Handle: RePEc:ngi:dpaper:17-03