Adjusting for Cell Suppression in Commuting Trip Data

Christian Braathen (), Inge Thorsen () and Jan Ubøe
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Christian Braathen: Dept. of Business and Management Science, Norwegian School of Economics, Postal: NHH , Department of Business and Management Science, Helleveien 30, N-5045 Bergen, Norway
Inge Thorsen: Dept. of Business Administration, Western Norway University of Applied Sciences, Postal: Western Norway University of Applied Sciences , Department of Business Administration, Bjørnsonsgate 45, N-5528 Haugesund, Norway, https://www.hvl.no/en/employee/?user=Inge.Heldal.Thorsen

No 2022/13, Discussion Papers from Norwegian School of Economics, Department of Business and Management Science

Abstract: Maximum entropy methods are used to infer the true trip-distribution matrix in cases where parts of the data are suppressed due to privacy concerns. Large proportions of the suppressed data are found to be inferred correctly when the marginal totals in the trip distribution are known. Entropy-based approaches are further found to outperform a strategy of ignoring suppressed information in cases with suppressed marginal totals and/or a higher cut-off value of suppressing cell information. Our methods are demonstrated to reduce the systematic bias in estimates of the distance deterrence parameter to such small numbers that it is effectively zero, preventing potentially serious bias in estimates and predictions resulting from standard spatial interaction models. Another useful contribution is to identify what scenarios an entropy-maximization approach benefits from incorporating information on times series and/or information on distances in the transportation network.

Keywords: Maximum entropy methods; trip-distribution matrix; spatial interaction (search for similar items in EconPapers)
JEL-codes: C00 C10 R00 R12 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2022-12-13
New Economics Papers: this item is included in nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:nhhfms:2022_013

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