nep-neu New Economics Papers
on Neuroeconomics
Issue of 2023‒12‒18
two papers chosen by

  1. Too hot to play it cool? Temperature and media bias By Stadelmann, David; Thomas, Tobias; Zakharov, Nikita
  2. "This time it's different" Generative Artificial Intelligence and Occupational Choice By Daniel Goller; Christian Gschwends; Stefan C. Wolter

  1. By: Stadelmann, David; Thomas, Tobias; Zakharov, Nikita
    Abstract: This paper examines the impact of outdoor temperature on media bias. We use 12 years of daily hand-coded data on the tonality of news broadcast by the three major US news networks, ABC News, CBS News, and NBC News, all headquartered in New York City, and merge it with granular, geospatial weather data. Our identification strategy exploits detailed variations in local daily high temperatures to estimate the effect of heat on media bias in news reporting about the Republican and Democratic parties, controlling for time and network-month fixed effects. We find a positive effect of a substantial magnitude: a 1êC increment in daily maximum temperature on a hot day (>25êC) leads to a 20% increase in the media bias measured as the difference in the share of negative news about the Republicans and the Democrats. This effect exists only for maximum temperatures, as opposed to minimum or average temperatures. The results are robust to placebo tests using past or future temperatures. Our findings extend the previously established link - from hot temperatures to negative affect and a decline in cognitive ability - to the determinants of media bias.
    Keywords: media bias, tonality, temperature, U.S. newscasts
    JEL: L8 D7
    Date: 2023
  2. By: Daniel Goller; Christian Gschwends; Stefan C. Wolter
    Abstract: In this paper, we show the causal influence of the launch of generative AI in the form of ChatGPT on the search behavior of young people for apprenticeship vacancies. There is a strong and long-lasting decline in the intensity of searches for vacancies, which suggests great uncertainty among the affected cohort. Analyses based on the classification of occupations according to tasks, type of cognitive requirements, and the expected risk of automation to date show significant differences in the extent to which specific occupations are affected. Occupations with a high proportion of cognitive tasks, with high demands on language skills, and those whose automation risk had previously been assessed by experts as lower are significantly more affected by the decline. However, no differences can be found with regard to the proportion of routine vs. non-routine tasks.
    Keywords: Artificial intelligence, occupational choice, labor supply, technological change
    JEL: J24 O33
    Date: 2023–11

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