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  <title>EconStor Community:</title>
  <link rel="alternate" href="https://hdl.handle.net/10419/173295" />
  <subtitle />
  <id>https://hdl.handle.net/10419/173295</id>
  <updated>2026-04-28T11:21:01Z</updated>
  <dc:date>2026-04-28T11:21:01Z</dc:date>
  <entry>
    <title>The entanglement of attitudes toward inequality: The theoretical background and measurement for the EU countries in 2021</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/316205" />
    <author>
      <name>Kot, Stanisław Maciej</name>
    </author>
    <id>https://hdl.handle.net/10419/316205</id>
    <updated>2025-05-06T01:51:22Z</updated>
    <published>2025-01-01T00:00:00Z</published>
    <summary type="text">Title: The entanglement of attitudes toward inequality: The theoretical background and measurement for the EU countries in 2021
Authors: Kot, Stanisław Maciej
Abstract: This paper assumes two kinds of social planners who evaluate income distributions concerning social welfare, economic inequality and poverty. The first kind of social planner, SPε , comprises averters to income inequality as measured by the normative parameter ε. The second kind of social planner, SPv , comprises averters to rank inequality as measured by the normative parameter v. As every member of society may play the role of a social planner, there could be as many levels of ε and v as society members. It raises the question of which ranges of v and ε values are ethically sensible when conducting empirical welfare studies. This paper proposes an answer to this question, introducing the concept of inequality-entangled SPv and SPε. If a randomly selected SPv had vi , one could automatically find εi of the inequality-entangled SPε , and vice versa. The inequality-entangled SPv and SPε evaluate inequality, social welfare and poverty consistently. This paper offers a method of eliciting the pairs (vi , εi ), i=1, 2, …,n from empirical income distributions. Moreover, a single pair (v*, ε*) exists, representing all n pairs. This paper applies the inequalityentanglement methodological framework to assess social welfare, inequality and poverty for 27 European Union member countries in 2021.</summary>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Funding structure and university patenting: An analysis of European higher education institutions</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/322204" />
    <author>
      <name>Wolszczak-Derlacz, Joanna</name>
    </author>
    <author>
      <name>Parteka, Aleksandra</name>
    </author>
    <author>
      <name>Szymczak, Sabina</name>
    </author>
    <author>
      <name>Platkowski, Piotr</name>
    </author>
    <id>https://hdl.handle.net/10419/322204</id>
    <updated>2025-07-26T01:48:25Z</updated>
    <published>2025-01-01T00:00:00Z</published>
    <summary type="text">Title: Funding structure and university patenting: An analysis of European higher education institutions
Authors: Wolszczak-Derlacz, Joanna; Parteka, Aleksandra; Szymczak, Sabina; Platkowski, Piotr
Abstract: Relatively poor transfer of knowledge from higher education to the market remains a concern in Europe, universities being involved in at most 10% of all patented inventions. We examine the role of university funding in patenting, addressing three key research gaps: (i) the limited, countryspecific samples rather than pan-European data used in most patent-funding studies; (ii) scarce evidence on the impact of the funding structure on patent quality; and (iii) the lack of precise estimates of interactions between university patenting, funding structures, and regional systems. We fill these gaps thanks to a micro-level database of almost 2,900 higher education institutions (HEIs) in 31 European countries and 295 NUTS2 regions (2011-2019), containing detailed information on their activity as direct patent applicants and various institutional characteristics, including financial records. We show that universities with a greater share of third-party funds (research grants, contracts) apply for more patents and have better quality patents than those that rely mainly on core funding, i.e. national/regional allocations. The HEIs that do patent are richer and have more than twice the share of third-party revenues. This indicates that the very marked core-periphery pattern of university patenting in Europe is related both to the amount of university funding and to its sources. Additionally, we find that regional economic systems also influence the way in which the funding structure impacts university patenting. The positive effect of third-party funding is strongest in the wealthy European regions, less so in developed areas, and negligible in the poorest regions.</summary>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>A consistent assessment of social welfare by two methodologies: The theory and evidence from the Luxembourg Income Study database</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/300187" />
    <author>
      <name>Kot, Stanisław Maciej</name>
    </author>
    <author>
      <name>Paradowski, Piotr R.</name>
    </author>
    <id>https://hdl.handle.net/10419/300187</id>
    <updated>2024-07-12T01:14:28Z</updated>
    <published>2024-01-01T00:00:00Z</published>
    <summary type="text">Title: A consistent assessment of social welfare by two methodologies: The theory and evidence from the Luxembourg Income Study database
Authors: Kot, Stanisław Maciej; Paradowski, Piotr R.
Abstract: Research background: Applied welfare economics offers various social welfare functions (SWF) for appraising income distributions. Social planners commonly use two SWFs: SWF&amp;#x03b5; implied by income inequality aversion (&amp;#x03b5;) and SWFv implied by rank inequality aversion (v). However, a voluntary choice of &amp;#x03b5; or v may result in inconsistent assessments of social welfare embodied in a given income distribution. Purpose of the article: We search for the combinations of &amp;#x03b5; and v that guarantee consistent assessments of social welfare, inequality and poverty embodied in a given income distribution. Methods: We propose estimating the pairs (&amp;#x03b5;,v) by solving the system of two nonlinear equations. The first equation comprises the equally distributed equivalent incomes derived from SWF&amp;#x03b5; and SWFv . The second equation comprises the benchmark incomes. A small increase in income below the benchmark income reduces inequality, whereas a small increase above the benchmark income increases inequality. The system of these equations can be solved numerically. Findings and Value added: We have estimated &amp;#x03b5;, v, and related characteristics for selected Latin America and Caribbean countries using Luxembourg Income study database data.</summary>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>A dataset on knowledge creation and patenting by European Higher Education Institutions (KC-HEI)</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/300341" />
    <author>
      <name>Parteka, Aleksandra</name>
    </author>
    <author>
      <name>Płatkowski, Piotr</name>
    </author>
    <author>
      <name>Szymczak, Sabina</name>
    </author>
    <author>
      <name>Wolszczak-Derlacz, Joanna</name>
    </author>
    <id>https://hdl.handle.net/10419/300341</id>
    <updated>2024-07-19T01:43:14Z</updated>
    <published>2024-01-01T00:00:00Z</published>
    <summary type="text">Title: A dataset on knowledge creation and patenting by European Higher Education Institutions (KC-HEI)
Authors: Parteka, Aleksandra; Płatkowski, Piotr; Szymczak, Sabina; Wolszczak-Derlacz, Joanna
Abstract: This paper describes the construction of a microlevel database on knowledge creation by higher education institutions (KC-HEI), accompanying the Global Knowledge InputOutput database (KIO, Davies et al., 2023). The database was created as part of Project Rethink GCS. KC-HEI links PATSTAT information on the patenting activity of 866 universities (HEIs) in 31 European countries over four decades (1980-2019), using citation records and patent quality indicators from OECD/STI Micro-data. KC-HEI makes possible analysis of the Institutions' innovation performance across 128 internationally comparable technological sectors and, separately, with respect to Artificial Intelligence (AI). We also develop a unique crosswalk between PATSTAT and ETER that combines KCHEI with other institution-level datasets (such as ETER and RISIS) and allows us to build a parallel dataset covering 785 patenting and 2101 non-patenting universities in Europe between 2011 and 2019. We illustrate the potential of the KC-HEI database, providing key stylised facts on the role of universities in knowledge creation, while documenting extreme core-periphery patterns of university patenting in Europe and detecting several key university-level factors that reinforce this disparity.</summary>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </entry>
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