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Good news and bad news: evidence of media bias in unemployment reports

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Abstract

This study employs information obtained from media content analyses, as well as economic and political data, to investigate negativity in unemployment news between 2001 and 2010 in Germany. The data indicate a substantial bias in terms of the amounts of negative and positive reports, compared with the actual development of unemployment. Moreover, the media tend to place negative unemployment reports more prominently than positive ones. The estimates suggest that the bias is not the consequence of journalists asymmetrically interpreting the official unemployment numbers. Instead, it is associated with the exploitation of often non-economic information and structural influences in the process of news production.

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Notes

  1. Note that government unemployment statistics are merely estimates of the “true” unemployment rate insofar as they are based on statistical sampling techniques and usually are corrected or adjusted at least once after they are first made public.

  2. News media also can “go easy” on the government, for example when policies comport with the political preferences of journalists..

  3. The sample contains information about every article and television segment that provides economic news (e.g., reports about economic conditions, economic policy, industries, companies, or unions), excluding articles from the financial or stock section, press reviews, letters by readers, and notes from the publisher.

  4. The seasonally unadjusted unemployment rate, as well as quarterly and annual changes, lead to very similar ratios. However, it is preferable to show the seasonally adjusted data in Figs. 1 and 2, because the seasonal pattern would make it more difficult to quickly recognize the overall trend.

  5. The model diagnostics support a statistical comparison of the estimates with and without seasonally adjusted data. In general, all specifications are satisfactory, as the link tests indicate. However, the Akaike and Bayesian information criteria and McFadden’s R2 suggest that the specifications with seasonally unadjusted unemployment and industrial production data provide a better model fit than the specifications with adjusted data (this result holds when conducting the test comparing only the unemployment rate or industrial production). The seasonally unadjusted data generally exhibit greater variation and thus provide more information to explain the dependent variables. However, this result also might be an indication that the seasonally unadjusted numbers are more important for journalists, maybe because they appear to be more impressive and thus more newsworthy. In line with this finding, the presentation of results refers to the estimates with seasonally unadjusted data only.

  6. The model specification is satisfactory when using seasonally unadjusted data. The different R2 measures and information criteria consistently indicate that specifying the model with seasonally adjusted data would reduce the model’s fit. Therefore, only the results based on the unadjusted data are presented.

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Authors and Affiliations

  1. Hamburg Media School, Finkenau 35, 22081, Hamburg, Germany

    Marcel Garz

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  1. Marcel Garz
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Correspondence to Marcel Garz.

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Garz, M. Good news and bad news: evidence of media bias in unemployment reports. Public Choice 161, 499–515 (2014). https://doi.org/10.1007/s11127-014-0182-2

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  • DOI: https://doi.org/10.1007/s11127-014-0182-2

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