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The distance bias in natural disaster reporting – empirical evidence for the United States

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  • Michael Berlemann
  • Tobias Thomas

Abstract

Whenever governments or international organizations provide aid in the aftermath of natural disasters, they typically justify this support by humanitarian motives. Previous empirical research found that media reports on natural disasters have a systematic impact on the amount of provided disaster aid. While this is unproblematic as long as media reports are unbiased and thus deliver an undistorted picture of the occurrence and severity of worldwide occurring disasters, systematic reporting biases would lead to distorted aid flows and perhaps other distortions like an insufficient perception of a region in international organizations. Based on data on three US news shows we show that disaster reporting is subject to a distance bias, e.g., the likelihood that a disaster is covered by the media depends on the distance between the country where the media are located and the country where the disasters occur. We also find evidence that besides the distance bias the state of economic development of a country and importance as export markets have a positive effect on the probability that US news shows are reporting on a natural disaster. As a result, international aid flows might be systematically biased and not distributed in line with the needs of the victims.

Suggested Citation

  • Michael Berlemann & Tobias Thomas, 2019. "The distance bias in natural disaster reporting – empirical evidence for the United States," Applied Economics Letters, Taylor & Francis Journals, vol. 26(12), pages 1026-1032, July.
  • Handle: RePEc:taf:apeclt:v:26:y:2019:i:12:p:1026-1032
    DOI: 10.1080/13504851.2018.1528332
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    Citations

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    Cited by:

    1. Bernhardt, Lea & Dewenter, Ralf & Thomas, Tobias, 2020. "Measuring partisan media bias in US Newscasts from 2001-2012," Working Paper 183/2020, Helmut Schmidt University, Hamburg, revised 15 Nov 2022.
    2. Roger Few & Hazel Marsh & Garima Jain & Chandni Singh & Mark Glyn Llewellyn Tebboth, 2021. "Representing Recovery: How the Construction and Contestation of Needs and Priorities Can Shape Long-term Outcomes for Disaster-affected People," Progress in Development Studies, , vol. 21(1), pages 7-25, January.
    3. Bernhardt, Lea & Dewenter, Ralf & Thomas, Tobias, 2020. "Watchdog or loyal servant? Political media bias in US newscasts," DICE Discussion Papers 348, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    4. Hirsch, Patrick & Köhler, Ekkehard A. & Feld, Lars P. & Thomas, Tobias, 2020. ""Whatever it takes!": How tonality of TV-news affects government bond yield spreads during crises," Freiburg Discussion Papers on Constitutional Economics 20/9, Walter Eucken Institut e.V..
    5. Bernhardt, Lea & Dewenter, Ralf & Thomas, Tobias, 2023. "Measuring partisan media bias in US newscasts from 2001 to 2012," European Journal of Political Economy, Elsevier, vol. 78(C).
    6. Shi Shen & Ke Shi & Junwang Huang & Changxiu Cheng & Min Zhao, 2023. "Global online social response to a natural disaster and its influencing factors: a case study of Typhoon Haiyan," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.
    7. Jonghun Kam & Jihun Park & Wanyun Shao & Junho Song & Jinhee Kim & Fabrizio Terenzio Gizzi & Donatella Porrini & Young-Joo Suh, 2021. "Data-driven modeling reveals the Western dominance of global public interest in earthquakes," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-9, December.
    8. Raffaele Guetto & Maria Francesca Morabito & Daniele Vignoli & Matthias Vollbracht, 2021. "Media Coverage of the Economy and Fertility," Econometrics Working Papers Archive 2021_12, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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