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    <link>https://hdl.handle.net/10419/238681</link>
    <description />
    <pubDate>Mon, 14 Sep 2026 01:22:31 GMT</pubDate>
    <dc:date>2026-09-14T01:22:31Z</dc:date>
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      <title>The effects of temporal data aggregation on price transmission analysis</title>
      <link>https://hdl.handle.net/10419/341687</link>
      <description>Title: The effects of temporal data aggregation on price transmission analysis
Authors: Hoffmann, Clemens; von Cramon-Taubadel, Stephan
Abstract: Applied price transmission analysis is often carried out with temporally aggregated data. However, the effects of temporal aggregation on estimation and interpretation are largely ignored in the price transmission literature. Following Marcelino (1999) we show how temporal aggregation affects the parameters of the vector error correction models (VECMs) that are commonly used in price transmission analysis. Temporal aggregation does not affect the parameters of the long-run equilibrium relationships between prices, but it does affect the adjustment and autoregressive parameters that describe the short-run dynamics of price adjustment. Temporal aggregation also introduces moving average components into the error terms of VECMs. We present a Monte Carlo experiment and an application to wheat prices in the EU and the US to illustrate how failure to account for these moving average effects further distorts estimates of the dynamics of price transmission. These results have important implications. First, estimation with different temporal aggregates of the same price data will lead to differing and sometimes contradictory conclusions regarding the speed of price transmission, impulse-response patterns and price discovery. Second, it is not possible to derive conclusions regarding the dynamics of price adjustment at a higher frequency from estimates generated with lower-frequency data. In general, reliable insights into the dynamics of price transmission can only be generated if the frequency of the data employed in estimation coincides with the time decision intervals of the agents whose transactions determine prices.</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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      <title>Combining geographical indication labels with nutri-scores: Preferences of German and Dutch consumers</title>
      <link>https://hdl.handle.net/10419/341692</link>
      <description>Title: Combining geographical indication labels with nutri-scores: Preferences of German and Dutch consumers
Authors: Höhn, Gero Laurenz; Huysmans, Martijn; Crombez, Christophe
Abstract: The introduction of a harmonised front-of-pack nutrition label remains a timely and contentious issue within EU policy debates. However, the effects of colour-coded candidates such as the Nutri-Score in combination with other prominent EU food labels such as Geographical Indications (GIs) remain underexplored - particularly, in northern European contexts and in a scenario of mandatory Nutri-Scores. To address this gap, we conduct a discrete choice experiment with over 800 German and Dutch respondents to quantify the willingness to pay for these labels. We find that consumers are willing to pay a premium of 72 cents for GI-labelled Parma ham and 48 cents for a Nutri-Score D rather than E. Consumers also prefer the combination of GI hams with a comparatively better Nutri-Score D but the interaction between the two labels is not significant, indicating no strong interplay between them in our experiment.</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>Measuring and benchmarking time-varying market efficiency</title>
      <link>https://hdl.handle.net/10419/341691</link>
      <description>Title: Measuring and benchmarking time-varying market efficiency
Authors: Mu, Yali; von Cramon-Taubadel, Stephan; Rosero, Gabriel; Brümmer, Bernhard
Abstract: This paper develops and implements an analytical framework combining spatial space techniques with panel stochastic frontier models to assess and benchmark time-varying market efficiency, with China's pork market serving as the empirical application. We analyze spatial and temporal dynamics in adjustment speeds and compare inefficiency under a range of translog frontier specifications and market characteristics. The estimated market efficiency frontiers decline with greater geographic distances but improve with greater inter-market trade volume. Our analysis indicates that the Chinese pork market experiences significant inefficiencies (approximately 50%) in the speed of adjustment. The higher inefficiency is associated with rising diesel fuel prices. Roughly 35% of this inefficiency stems from short-term or transient shocks, and about 25% results from persistent, structural market characteristics. Overall, the study demonstrates that overlooking persistent inefficiency leads to an overestimation of the market's ability to restore or maintain efficient spatial price transmission over time.</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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      <title>Strategic changes of the farming system in Italian rural areas</title>
      <link>https://hdl.handle.net/10419/341688</link>
      <description>Title: Strategic changes of the farming system in Italian rural areas
Authors: Henke, Roberto; Carillo, Felicetta; Cimino, Orlando
Abstract: This article examines the evolution of Italian farms over the past decade and assesses whether their structural and economic transformations align with the prevailing patterns of agricultural development across different rural areas, as identified by the Italian institutions responsible for implementing rural policies.  We conducted a comparative analysis based on repeated cross-sectional data covering the 2014-2020 programming period to evaluate changes in the structure of farms located in territories with different degrees of rurality. Using national microdata from the Farm Accountancy Data Network (FADN), we compared a set of farm characteristics observed in 2014 and 2023, which serve as two observational time points capturing strategic investment choices and behavioural adjustments across areas. The results indicate significant and articulated territorial differences in farm strategies and structural characteristics across the Italian rural continuum. Such complexity calls for a particular effort in enhancing a place-based approach to policy implementation, with targeted and selective measures tailored to the specific needs and potentials of rural areas.</description>
      <pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://hdl.handle.net/10419/341688</guid>
      <dc:date>2026-01-01T00:00:00Z</dc:date>
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