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    <title>EconStor Community:</title>
    <link>https://hdl.handle.net/10419/244409</link>
    <description />
    <pubDate>Wed, 29 Apr 2026 17:43:39 GMT</pubDate>
    <dc:date>2026-04-29T17:43:39Z</dc:date>
    <item>
      <title>Real-time nowcasting of Kyiv's regional GRP using Google trends and mixed-frequency data</title>
      <link>https://hdl.handle.net/10419/339201</link>
      <description>Title: Real-time nowcasting of Kyiv's regional GRP using Google trends and mixed-frequency data
Authors: Drin, Svitlana; Zhuravlova, Anastasiia
Abstract: imely assessment of regional economic activity in Ukraine is severely constrained by institutional and data-related limitations. Official regional gross regional product (GRP) statistics are available only at low frequency, are published with substantial delays, and, in the post-2022 period, are further affected by disruptions to statistical production caused by martial law. At the same time, a growing set of potentially informative regional indicators derived from administrative records and official short-term statistics is available at higher frequencies but only over short and heterogeneous time spans. These features make the direct application of standard regional nowcasting models infeasible. This paper develops a mixed-frequency factor-augmented vector autoregressive framework tailored to the Ukrainian data environment and designed to incorporate short and incomplete regional indicators into the nowcasting of regional GDP. The model explicitly exploits the hierarchical structure of Ukrainian regional statistics by combining information from quarterly and annual measures of economic activity and by linking regional dynamics to national output developments. Short regional indicators are summarised through latent regional factors extracted using missing-data factor estimation techniques that are robust to ragged edges at both the beginning and the end of the sample. The proposed framework is implemented using Ukrainian macro-regional aggregates constructed from official data published by the State Statistics Service of Ukraine. Particular attention is paid to the treatment of labour market indicators, housing price dynamics, and other short-term variables that exhibit discontinuities or limited availability. A pseudo-real-time nowcasting exercise shows that conditioning regional GDP nowcasts on factor information derived from short regional data improves predictive performance when contemporaneous national GDP estimates are not yet available. Once national aggregates are released, the marginal informational contribution of regional short-term indicators diminishes. Overall, the results demonstrate that mixed-frequency factor-augmented VAR models provide a coherent and empirically viable framework for regional GDP nowcasting in Ukraine. The approach is particularly well suited to data environments 1 characterised by short samples, publication delays, and institutional disruptions, and thus offers a valuable tool for real-time regional economic monitoring in periods of heightened uncertainty.</description>
      <pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
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      <dc:date>2026-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Same storm, different boats: Generative AI and the age gradient in hiring</title>
      <link>https://hdl.handle.net/10419/339320</link>
      <description>Title: Same storm, different boats: Generative AI and the age gradient in hiring
Authors: Lodefalk, Magnus; Löthman, Lydia; Koch, Michael; Engberg, Erik
Abstract: We show that the age composition of employment within Swedish employers shifts after the arrival of generative AI, with no corresponding reduction in aggregate labour demand. Using 4.6 million job advertisements from Sweden's largest recruitment platform, we find that the broad decline in postings since 2022 aligns with monetary tightening rather than AI, exploiting Sweden's seven-month gap between the Riksbank's first rate hike and the launch of ChatGPT as a timing test. We then use full-population employer- employee register data and an employer-level difference-in-differences design to estimate how AI exposure affects employment composition across six age groups. An event study documents an accelerating decline in employment of 22-25-year-olds in high-AI-exposure occupations, reaching 5.5 per cent by early 2025 relative to less exposed occupations within the same employers, while employment of workers over 50 rose by 1.3 per cent. The widening age gradient suggests that generative AI reshapes hiring composition rather than aggregate demand, with the adjustment burden falling disproportionately on entry-level workers.</description>
      <pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://hdl.handle.net/10419/339320</guid>
      <dc:date>2026-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>"Behind blue eyes": The valuation of knowing someone who attempted or died by suicide in Sweden</title>
      <link>https://hdl.handle.net/10419/311622</link>
      <description>Title: "Behind blue eyes": The valuation of knowing someone who attempted or died by suicide in Sweden
Authors: Andrén, Daniela
Abstract: Advancing the economic understanding of suicide's externalities, this study uses the well-being valuation method (WVM) to quantify the exposure to suicide, specifically through knowing someone near, family, or friend (NFF) who attempted or died by suicide. First, using data from a survey of Swedish adults, we separately estimate several life satisfaction equations. For each equation, we use the same comparison group of individuals who reported never having been exposed to others' suicide, and compare them against different groups, each exposed to NFF-related suicide attempts or deaths. We find that income has a statistically significant positive impact on life satisfaction across all equations, and except for the experience of death alone, all other exposures to suicide have a statistically significant negative impact on life satisfaction. Next, we use these estimates to calculate the monetary compensation required to offset the decline in life satisfaction for individuals exposed to a NFF's suicide attempt or death. The required annual monetary compensation to offset this decline ranges from 6,400 to 9,910 euros, which suggests an economic value for mitigating the negative effects of suicide exposure equivalent to around a median monthly household income. However, our findings should be considered with caution when used to inform healthcare policies and prevention strategies aimed at reducing the spillover effects of exposure to suicide.</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://hdl.handle.net/10419/311622</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Neo-Schumpeterian growth theory: Missing entrepreneurs results in incomplete policy advice</title>
      <link>https://hdl.handle.net/10419/311621</link>
      <description>Title: Neo-Schumpeterian growth theory: Missing entrepreneurs results in incomplete policy advice
Authors: Henrekson, Magnus; Johansson, Dan
Abstract: The neo-Schumpeterian growth models, which appeared in the early 1990s, have ostensibly reintroduced the entrepreneur into mainstream growth theory. However, we show that by ignoring genuine uncertainty and by assuming that profits follow an objectively true and ex ante known probability distribution, the entrepreneur is made redundant. Thus, the theory fails to exhaustively explain innovation, the role of ownership competence, profits, the function of financial markets, wealth and income distribution, and, ultimately, economic growth. These shortcomings risk leading to erroneous or overly narrow policy conclusions by overestimating the importance of supporting R&amp;D investments. Rather, the presence of genuine uncertainty forms a fundamental theoretical basis for the importance of new venture creation as a source of innovation-driven growth; entrepreneurs must establish and expand firms to capture the subjectively perceived profit opportunities. Therefore, tax policy is decisive for the commercialization and dissemination of innovations by providing incentives to uncertainty-bearing, not only for entrepreneurs, but also for intrapreneurs and financiers taking an active part in the governance and development of firms based on innovations characterized by genuine uncertainty. Furthermore, taxation can distort the evolutionary selection of innovations and firms, for instance, by taxing owners and firms differently.</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://hdl.handle.net/10419/311621</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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