Institut für Volkswirtschaftslehre

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/24

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Browsing Institut für Volkswirtschaftslehre by Sustainable Development Goals "9"

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    Comparing cars with apples? Identifying the appropriate benchmark countries for relative ecological pollution rankings and international learning
    (2021) Hartmann, Dominik; Ferraz, Diogo; Bezerra, Mayra; Pyka, Andreas; Pinheiro, Flávio L.
    One of the most difficult tasks that economies face is how to generate economic growth without causing environmental damage. Research in economic complexity has provided new methods to reveal structural constraints and opportunities for green economic diversification and sophistication, as well as the effects of economic complexity on environmental pollution indicators. However, no research so far has compared the ecological efficiency of countries with similar productive structures and levels of economic complexity, and used this information to identify the best learning partners. This matters, because there are substantial differences in the environmental damage caused by the same product in different countries, and green diversification needs to be complemented by substantial efficiency improvements of existing products. In this article, we use data on 774 different types of exports, CO2 emissions, and the ecological footprint of 99 countries to create first a relative ecological pollution ranking (REPR). Then, we use methods from network science to reveal a benchmark network of the best learning partners based on country pairs with a large extent of export similarity, yet significant differences in pollution values. This is important because it helps to reveal adequate benchmark countries for efficiency improvements and sustainable production, considering that countries may specialize in substantially different types of economic activities. Finally, the article i) illustrates large efficiency improvements within current global output levels, ii) helps to identify countries that can best learn from each other, and iii) improves the information base in international negotiations for the sake of a cleaner global production system.
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    Predictor preselection for mixed‐frequency dynamic factor models: a simulation study with an empirical application to GDP nowcasting
    (2025) Franjic, Domenic; Schweikert, Karsten; Franjic, Domenic; Core Facility Hohenheim and Institute of Economics, University of Hohenheim, Stuttgart, Germany; Schweikert, Karsten; Core Facility Hohenheim and Institute of Economics, University of Hohenheim, Stuttgart, Germany
    We investigate the performance of dynamic factor model nowcasting with preselected predictors in a mixed‐frequency setting. The predictors are selected via the elastic net as it is common in the targeted predictor literature. A simulation study and an application to empirical data are used to evaluate different strategies for variable selection, the influence of tuning parameters, and to determine the optimal way to handle mixed‐frequency data. We propose a novel cross‐validation approach that connects the preselection and nowcasting step. In general, we find that preselecting provides more accurate nowcasts compared with the benchmark dynamic factor model using all variables. Our newly proposed cross‐validation method outperforms the other specifications in most cases.