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  1. Convergence rate of estimators of clustered panel models with misclassification
    Autor*in: Dzemski, Andreas; Okui, Ryo
    Erschienen: August 2020
    Verlag:  Department of Economics, University of Gothenburg, Göteborg

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    hdl: 2077/66141
    Schriftenreihe: Working paper in economics ; no. 790
    Schlagworte: Panel data; latent grouped structure; clustering; kmeans; convergence rate; misclassification
    Umfang: 1 Online-Ressource (circa 15 Seiten)
  2. Identifying key elements for adequate simplifications of investment choices - the case of wind energy expansion by
    Autor*in: Pöstges, Arne; Weber, Christoph
    Erschienen: January 2021
    Verlag:  House of Energy Markets and Finance, University of Duisburg-Essen, Essen

    The analysis of future energy systems with increasing shares of renewable energy production poses various challenges to models used in the field of energy system analysis. Aggregation is one solution to reduce the computation time of large... mehr

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    The analysis of future energy systems with increasing shares of renewable energy production poses various challenges to models used in the field of energy system analysis. Aggregation is one solution to reduce the computation time of large optimization problems, especially for optimization models with endogenous capacity expansion. Since the economic viability of renewable investments is not directly driven by physical and technical characteristics but rather by the corresponding revenue and cost streams, we propose a novel aggregation method. The aggregation covers both the spatial and the technological dimension of wind investment choices, i.e. the siting as well as the turbine choice. Four value components are defined, related e.g. to the total yield or the site-specific infeed profile of investment choices. A clustering approach is applied to these value components to identify groups of investment choices that can be aggregated without excessive loss of accuracy. The approach is applied in a case study for the German electricity system and the influence of the different value components on the combined technological and spatial aggregation is analyzed.

     
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    hdl: 10419/234072
    Schriftenreihe: HEMF working paper ; no. 2021, 01
    Schlagworte: aggregation; clustering; value components; wind energy expansion
    Umfang: 1 Online-Ressource (circa 40 Seiten), Illustrationen
  3. K-expectiles clustering
    Autor*in: Wang, Bingling; Li, Yingxing; Härdle, Wolfgang
    Erschienen: [2021]
    Verlag:  International Research Training Group 1792, Berlin

    K-means clustering is one of the most widely-used partitioning algorithm in cluster analysis due to its simplicity and computational efficiency, but it may not provide ideal clustering results when applying to data with non-spherically shaped... mehr

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    K-means clustering is one of the most widely-used partitioning algorithm in cluster analysis due to its simplicity and computational efficiency, but it may not provide ideal clustering results when applying to data with non-spherically shaped clusters. By considering the asymmetrically weighted distance, We propose the K-expectile clustering and search the clusters via a greedy algorithm that minimizes the within cluster τ -variance. We provide algorithms based on two schemes: the fixed τ clustering, and the adaptive τ clustering. Validated by simulation results, our method has enhanced performance on data with asymmetric shaped clusters or clusters with a complicated structure. Applications of our method show that the fixed τ clustering can bring some flexibility on segmentation with a decent accuracy, while the adaptive τ clustering may yield better performance.

     
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    hdl: 10419/233511
    Schriftenreihe: IRTG 1792 discussion paper ; 2021, 003
    Schlagworte: clustering; expectiles; asymmetric quadratic loss; image segmentation
    Umfang: 1 Online-Ressource (circa 27 Seiten), Illustrationen
  4. A technical toolkit to monitor a pandemic outbreak from a central bank perspective
    Autor*in: Alupoaiei, Alexie; Bálint, Csaba; Kubinschi, Matei
    Erschienen: January 2021
    Verlag:  National Bank of Romania, [Bucureşti]

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    Schriftenreihe: Occasional papers / National Bank of Romania ; no. 32
    Schlagworte: Coronavirus; epidemic forecasting; clustering; SEIR; lockdown policies,branching process; mobility; value of a statistical life; welfare analysis
    Umfang: 1 Online-Ressource (circa 92 Seiten), Illustrationen
  5. The distributional impacts of real-time pricing
    Autor*in: Cahana, Michael; Fabra, Natalia; Reguant, Mar; Wang, Jingyuan
    Erschienen: 09 April 2022
    Verlag:  Centre for Economic Policy Research, London

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    Schriftenreihe: Array ; DP17200
    Schlagworte: Dynamic pricing; electricity; Distributional Effects; Generalized method of moments; clustering
    Umfang: 1 Online-Ressource (circa 60 Seiten), Illustrationen
  6. Suporte agrícola a partir de dados da Organização Para a Cooperação e o Desenvolvimento Econômico (OCDE)
    duas décadas sob análise
    Autor*in: Freitas, Rogério Edivaldo
    Erschienen: abril de 2022
    Verlag:  Instituto de Pesquisa Econômica Aplicada, Rio de Janeiro

    Agricultural support is one of the main tools used by governments to achieve their domestic goals, especially since the food shortages during and immediately after World War II. However, specific agricultural support programs can affect agricultural... mehr

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    Agricultural support is one of the main tools used by governments to achieve their domestic goals, especially since the food shortages during and immediately after World War II. However, specific agricultural support programs can affect agricultural production in various ways, and support programs can alter the allocation of natural resources domestically and abroad. In this study, we measured agricultural support in OECD-reported countries during the period 2000-2019 using Spearman's correlation coefficient, time trend analysis and clustering procedures. Data from Organization for Economic Co-operation and Development (OECD) from 2000 to 2019 were employed, specifically the Producer Support Estimate (PSE) and Consumer Support Estimate (CSE). We compared the results of two agglomerative clustering methods and identified groups of similar countries on the basis of their consumer support and producer support estimates behavior during the period studied. Some countries, such as Switzerland, South Korea, Turkey and Canada, displayed specific support behavior, while other groups of countries shared similarities such as China, Indonesia and the Philippines; the European Union, Japan and Norway; and Brazil, South Africa and Chile. Policies implications are discussed and further research is recommended, including analyses of top-down geographical unities, crop-specific programs, and the effects of the covid-19 pandemic on agricultural support worldwide, as more data becomes available.

     
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    hdl: 10419/265280
    Schriftenreihe: Texto para discussão / Ipea ; 2758
    Schlagworte: agricultural support; OECD-reported countries; Spearman's correlation coefficient; clustering
    Umfang: 1 Online-Ressource (circa 32 Seiten), Illustrationen
  7. Expansão de área agrícola no Brasil segundo as lavouras temporárias
    Autor*in: Freitas, Rogério Edivaldo
    Erschienen: setembro de 2022
    Verlag:  Instituto de Pesquisa Econômica Aplicada, Brasília

    Food production remains one of the main challenges for humankind in this century, and Brazil is one of the main food-producing countries that have yet some land for economically or technically profitable farming expansion. Then, knowing which areas... mehr

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    Food production remains one of the main challenges for humankind in this century, and Brazil is one of the main food-producing countries that have yet some land for economically or technically profitable farming expansion. Then, knowing which areas constitute the Brazilian agricultural frontier is crucial for improving public policies and logistics infrastructure decisions. Data from the Brazilian Institute of Geography and Statistics from 1995 to 2019 were used in this study. The study aimed to map and measure the expansion of agricultural areas in Brazil from 1995 to 2019 for temporary crops according to their mesoregions. The study used a four-stage methodology, compared the results of two agglomerative clustering methods, and identified similar mesoregions based on their share trends in the Brazilian agricultural seeded area. Some mesoregions had higher positive trend values for their share of the Brazilian agricultural seeded area: mato-grossense north (MT), mato-grossense northeast (MT), Mato Grosso do Sul southwest (MS), goiano south (GO), Bahia extreme west (BA), maranhense south (MA), piauiense southwest (PI), and Tocantins eastern (TO). As a second leading group, the Paranaíba Upstream (MG), São José do Rio Preto (SP), mato-grossense southeast (MT), and goiano east (GO), must be emphasized. Further research is recommended, including extending the study to permanent crops and applying top-down analysis targeting microregions or municipalities in the identified mesoregions.

     
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    hdl: 10419/269165
    Schriftenreihe: Texto para discussão / Ipea ; 2796
    Schlagworte: agricultural frontier; Brazil; mesoregions; Spearman's correlation coefficient; clustering
    Umfang: 1 Online-Ressource (circa 35 Seiten), Illustrationen
  8. Approximating grouped fixed effects estimation via fuzzy clustering regression
    Autor*in: Lewis, Daniel J.; Melcangi, Davide; Pilossoph, Laura; Toner-Rodgers, Aidan
    Erschienen: [2022]
    Verlag:  Federal Reserve Bank of New York, New York, NY

    We propose a new, computationally-efficient way to approximate the "grouped fixed-effects" (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means... mehr

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    We propose a new, computationally-efficient way to approximate the "grouped fixed-effects" (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means objective to regression settings. As the regularization parameter m approaches 1, the fuzzy clustering objective converges to the GFE objective; moreover, we recast this objective as a standard Generalized Method of Moments problem. We replicate the empirical results of Bonhomme and Manresa (2015) and show that our estimator delivers almost identical estimates. In simulations, we show that our approach delivers improvements in terms of bias, classification accuracy, and computational speed.

     
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    hdl: 10419/272846
    Schriftenreihe: Staff reports / Federal Reserve Bank of New York ; no. 1033 (September 2022)
    Schlagworte: clustering; unobserved heterogeneity; panel data
    Umfang: 1 Online-Ressource (circa 27 Seiten), Illustrationen
  9. An electric vehicle migration framework
    Autor*in: Er Raqabi, El Mehdi; Li, Wenkai
    Erschienen: April 2022
    Verlag:  IUJ Research Institute, International University of Japan, [Niigata-ken]

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    Schriftenreihe: Economics & management series / International University of Japan ; EMS-2022, 03
    Schlagworte: Electric vehicle; range anxiety; public transport; optimization; MILP; data mining; remote sensing; clustering
    Umfang: 1 Online-Ressource (circa 43 Seiten), Illustrationen
  10. Expansão da área agrícola no Brasil segundo as lavouras permanentes
    Autor*in: Freitas, Rogério Edivaldo
    Erschienen: junho de 2023
    Verlag:  Instituto de Pesquisa Econômica Aplicada, Brasília

    Food production remains one of the biggest challenges for humankind in this century, and Brazil is one of the largest food-producing countries that have yet some land for economically or technically profitable farming expansion. Therefore, knowing... mehr

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    Food production remains one of the biggest challenges for humankind in this century, and Brazil is one of the largest food-producing countries that have yet some land for economically or technically profitable farming expansion. Therefore, knowing which areas constitute the Brazilian agricultural frontier is crucial for improving public policies and logistics infrastructure decisions. Data from the Brazilian Institute of Geography and Statistics from 1995 to 2020 were used in this study. We aimed to map and measure the expansion of agricultural areas in Brazil from 1995 to 2020 for permanent crops according to their mesoregions. We applied a four-stage methodology, compared the results of two agglomerative clustering methods, and identified similar mesoregions based on their share trends in the Brazilian agricultural harvesting destined area. Some mesoregions must be highlighted in terms of trend values for their share of the Brazilian agricultural harvesting destined area: Minas' South/Southwest (MG), Triângulo Mineiro/Paranaíba Upstream (MG), Paraense Southwest (PA), Bauru (SP), Woodland Zone (MG), Rio-grandense Northeast (RS), Pernambucano San Francisco (PE) and Minas' North (MG). Other areas such as the Espírito-santense North Coast (ES), Bahia's San Franciscano Valley (BA), Cearense North (CE), Cearense Northwest (CE), Alagoano East (AL), and Paranaense Southeast (PR) constituted a second leading group, and Minas' West (MG), Paraense Northeast (PA), and Doce River Valley (MG) should be emphasized as clusters by themselves. Policy implications are discussed and further research is suggested, especially running top-down analysis targeting microregions or municipalities in the identified mesoregions.

     
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    hdl: 10419/285015
    Schriftenreihe: Texto para discussão / Ipea ; 2893
    Schlagworte: agricultural frontier; Brazil; permanent crops; Spearman’s correlation coefficient; clustering
    Umfang: 1 Online-Ressource (circa 43 Seiten)
  11. A machine learning approach to deal with ambiguity in the humanitarian decision making
    Autor*in: Graß, Emilia; Ortmann, Janosch; Balcik, Burcu; Rei, Walter
    Erschienen: December 2021
    Verlag:  Bureau de Montreal, Université de Montreal, Montréal (Québec)

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    Schriftenreihe: CIRRELT ; CIRRELT-2021, 51
    Schlagworte: humanitarian decision making; ambiguity; data aggregation; clustering; Syrian conflict; needs assessment
    Umfang: 1 Online-Ressource (circa 33 Seiten), Illustrationen
  12. Spatial machine learning
    new opportunities for regional science
    Autor*in: Kopczewska, Katarzyna
    Erschienen: 2021
    Verlag:  University of Warsaw, Faculty of Economic Sciences, Warsaw

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    Schriftenreihe: Working papers / University of Warsaw, Faculty of Economic Sciences ; no. 2021, 16 = 364
    Schlagworte: spatial machine learning; clustering; spatial covariates; spatial cross-validation; spatial autocorrelation
    Umfang: 1 Online-Ressource (circa 55 Seiten), Illustrationen
  13. A probabilistic method for reconstructing the foreign direct investments network in search of ultimate host economies
    Autor*in: Accoto, Nadia; Astuti, Valerio; Catalano, Costanza
    Erschienen: [2023]
    Verlag:  Banca d'Italia, [Rom]

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    Schriftenreihe: Questioni di economia e finanza / Banca d'Italia ; number 760 (April 2023)
    Schlagworte: foreign direct investment; ultimate host economies; network reconstruction; clustering; absorbing Markov chain
    Umfang: 1 Online-Ressource (circa 26 Seiten), Illustrationen
  14. A hybrid modeling approach to joint matching and pricing in an intelligent freight transportation platform
    Autor*in: Padidar, Marjan; Keivanpour, Samira; Ben Ali, Maha
    Erschienen: August 2023
    Verlag:  Bureau de Montreal, Université de Montreal, Montréal (Québec)

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    Schriftenreihe: CIRRELT ; CIRRELT-2023, 24
    Schlagworte: smart freight platform; joint matching and pricing; clustering; multi-actor; vehicle routing; large-scale
    Umfang: 1 Online-Ressource (circa 40 Seiten), Illustrationen
  15. Parsimonious Wasserstein text-mining
    Autor*in: Gadat, Sébastien; Villeneuve, Stéphane
    Erschienen: September 2023
    Verlag:  [Toulouse School of Economics], [Toulouse]

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    Schriftenreihe: Working papers / Toulouse School of Economics ; no 1471
    Schlagworte: Natural Language Processing; Textual Analysis; Wasserstein distance; clustering
    Umfang: 1 Online-Ressource (circa 20 Seiten), Illustrationen
  16. La transición de la fecundidad en Colombia: nueva evidencia regional
    Autor*in: Jaramillo E., Juliana
    Erschienen: [2023]
    Verlag:  Banco de la República Colombia, Centro de Estudios Económicos Regionales (CEER), Cartagena

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    hdl: 20.500.12134/10696
    Schriftenreihe: Cuadernos de historia económica ; núm. 60 (septiembre, 2023)
    Schlagworte: fertility transition; geography; Colombia; census data; clustering
    Umfang: 1 Online-Ressource (circa 60 Seiten), Illustrationen
  17. Nowcasting economic activity with mobility data
    Autor*in: Matsumura, Kohei; Oh, Yusuke; Sugo, Tomohiro; Takahashi, Koji
    Erschienen: [2021]
    Verlag:  Bank of Japan, Tokyo, Japan

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    Schriftenreihe: Bank of Japan working paper series ; no. 21, E-2 (March 2021)
    Schlagworte: mobility data; nowcasting; clustering
    Umfang: 1 Online-Ressource (circa 24 Seiten), Illustrationen
  18. Democracy clusters and patterns of inequality
    a k-means approach
    Autor*in: Puzon, Klarizze Anne Martin
    Erschienen: June 2023
    Verlag:  United Nations University World Institute for Development Economics Research, Helsinki, Finland

    This paper employs k-means clustering, a multidimensional pattern recognition method, to categorize countries using information from five Varieties of Democracy indices. K-means country clusters are similar but not entirely identical to both... mehr

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    This paper employs k-means clustering, a multidimensional pattern recognition method, to categorize countries using information from five Varieties of Democracy indices. K-means country clusters are similar but not entirely identical to both k-medians clusters and arbitrary groups formed using only one measure, namely the liberal democracy index. Simple correlations with different inequality measures yield varying results. Despite having higher absolute inequality, country clusters with extremely high levels of democracy are characterized by lower relative inequality. They also have the lowest ratio of the income share of the richest 10 per cent to that of the poorest 40 per cent. K-means clusters with low- and medium-quality institutions generally do not differ much in terms of inequality outcomes.

     
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    ISBN: 9789292673802
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    hdl: 10419/283768
    Schriftenreihe: WIDER working paper ; 2023, 72
    Schlagworte: clustering; democracy; inequality; pattern recognition
    Umfang: 1 Online-Ressource (circa 22 Seiten)
  19. Endline study report and policy study for the ConVERGE project
    Autor*in: Briones, Roehlano M.; Galang, Ivory Myka R.; Espineli, Isabel B.; Orbeta, Aniceto C.; Magno-Ballesteros, Marife
    Erschienen: September 2023
    Verlag:  Philippine Institute for Development Studies, Quezon City, Philippines

    The Department of Agrarian Reform (DAR), in partnership with the International Fund for Agricultural Development (IFAD), implemented the project "Convergence on Value Chain Enhancement for Rural Growth and Empowerment" or Project ConVERGE with the... mehr

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    The Department of Agrarian Reform (DAR), in partnership with the International Fund for Agricultural Development (IFAD), implemented the project "Convergence on Value Chain Enhancement for Rural Growth and Empowerment" or Project ConVERGE with the goal of empowering Agrarian Reform Beneficiaries (ARBs) to drive rural economic growth across 10 provinces spanning three regions. DAR engaged the Philippine Institute for Development Studies (PIDS) to undertake baseline and endline studies, serving as a crucial assessment tool for the project's performance and providing insights to inform the comprehensive ARC Cluster Development (ARCCD) Strategy aimed at advancing smallholder agriculture in the Philippines. This Endline Report provides the analysis of the baseline and endline datasets. It discusses the following key points: i) results of the impact evaluation study; ii) result of final process evaluation; and iii) recommendations for the Agrarian Reform Communities Cluster Development (ARCCD) Strategy. The quantitative analysis part of the study indicates a significant 41% average treatment effect from the Project, validating its Theory of Change in boosting income for ARC cluster households through value chain interventions. The process evaluation generally confirms the assumptions and impact pathways, with some deviations and shortfalls. Beneficiaries express satisfaction with the Project but have limited understanding of its rationale. The clustering method, which links small farmers to value chains by forming agrarian reform beneficiaries (ARBs) into lead and participating ARB organizations (ARBOs), appears to enhance government support efficiency for organized groups. The paper underscores the importance of additional capacity building for both LARBOs and PARBOs, and it recommends a more active engagement of other government agencies to address value-adding technologies, food processing standards, credit accessibility, and market facilitation.

     
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    Sprache: Englisch
    Medientyp: Buch (Monographie)
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    hdl: 10419/284612
    Schriftenreihe: Discussion paper series / Philippine Institute for Development Studies ; no. 2023, 13 (September 2023)
    Schlagworte: agrarian reform beneficiary organizations; ARBOs; ARBs; DAR; IFAD; ConVERGE; value chains; treament effects; endline; baseline; Agrarian Reform Communities Cluster Development; ARC; ARCCD; Mindanao; clustering; cluster; impact evaluation; difference-in-difference; regression; process evaluation
    Umfang: 1 Online-Ressource (circa 49 Seiten), Illustrationen
  20. Clustering of R&D collaboration in Cournot oligopoly
    Autor*in: Caminati, Mauro
    Erschienen: [2016]
    Verlag:  [Università di Siena], [Siena]

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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Quaderni del Dipartimento di economia politica e statistica ; n. 737 (ottobre 2016)
    Schlagworte: Cournot collaboration game; directed knowledge distance; R&D networks; degree assortativity; clustering
    Umfang: 1 Online-Ressource (circa 22 Seiten)
  21. Improving out-of-sample forecasts of stock price indexes with forecast reconciliation and clustering
    Autor*in: Mattera, Raffaele; Athanasopoulos, George; Hyndman, Rob J.
    Erschienen: [2023]
    Verlag:  [Monash University, Department of Econometrics and Business Statistics], [Victoria, Australia]

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Schriftenreihe: Working paper / Monash University, Department of Econometrics and Business Statistics ; no. 23, 17 (July 2023)
    Schlagworte: financial time series; hierarchical forecasting; clustering; unsupervised learning; prediction; machine learning; finance
    Umfang: 1 Online-Ressource (circa 31 Seiten), Illustrationen