Search results for "jel:C38"

showing 5 items of 5 documents

Euro Area Structural Convergence? A Multi-Criterion Cluster Analysis

2015

Abstract This paper proposes a classification of the old member countries of the euro area in a structural data rich environment and run a convergence analysis using the same framework. First, we use a clustering approach and identify two structurally distinct clusters of countries that are not modified between 1999 and 2012: the South Countries Group (SCG) – composed of Greece, Italy, Portugal and Spain – and the Other Countries Group (OCG). Second, we propose a convergence metrics and reach three key findings: (i) increase over time of the between-clusters׳ dispersion; (ii) diverging demographics and innovation performance into the OCG, and (iii) an unfortunate convergence towards high la…

DemographicsDuality (mathematics)Convergence (economics)jel:C38Disease cluster[SHS.ECO]Humanities and Social Sciences/Economics and FinanceGeneral Business Management and Accountingjel:F33jel:E02Cluster Analysis European Monetary Union Structural Policies.Cluster analysisEconomyCluster (physics)EconometricsEconomics[ SHS.ECO ] Humanities and Social Sciences/Economies and financesEuro areaStatistical dispersionEuropean monetary union[SHS.ECO] Humanities and Social Sciences/Economics and FinanceCluster analysisGeneral Economics Econometrics and FinanceComputingMilieux_MISCELLANEOUS
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Evolution of the Global Distribution of Carbon Dioxide: A Finite Mixture Analysis

2015

Economists and environmental policymakers have recently begun advocating a bottom-up approach to climate change mitigation, focusing on reduction targets for groups of nations, rather than large scale global policies. We advance this discussion by taking a quantitative perspective, focusing on econometric identification of groups of countries that have statistically similar distributions of carbon emissions using a broad range of finite mixture models. Nearly all of our results yield a consistent pattern: after 1980, there are two distinct emissions distributions, and that these distributions continue to evolve over time. We provide a rigorous analysis of these distributional differences al…

MacroeconomicsEconomics and EconometricsFinite mixturePublic economicsjel:C30Carbon emissions; Emissions groups; Heterogeneity; Abatement policy; Finite mixture modelsCarbon emissionjel:C38Climate change mitigationGlobal distributionGreenhouse gasAbatement policyEconomicsHeterogeneityVolatility (finance)Settore SECS-P/01 - Economia PoliticaEmpirical evidenceEmissions groupFinite mixture model
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Models Used for Measuring Customer Engagement

2013

The purpose of the paper is to define and measure the customer engagement as a forming element of the relationship marketing theory. In the first part of the paper, the authors review the marketing literature regarding the concept of customer engagement and summarize the main models for measuring it. One probability model (Pareto/NBD model) and one parametric model (RFM model) specific for the customer acquisition phase are theoretically detailed. The second part of the paper is an application of the RFM model; the authors demonstrate that there is no statistical significant variation within the clusters formed on two different data sets (training and test set) if the cluster centroids of t…

jel:M31Pareto/NBD modellcsh:Marketing. Distribution of productsparametric modeljel:C12RFM modellcsh:HF5410-5417.5probability model parametric model relationship marketing Pareto/NBD model RFM modelRFM model Journal: Expert Journal of Marketingjel:C38relationship marketingjel:C14probability modelExpert Journal of Marketing
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An Examination of Tourist Arrivals Dynamics Using Short-Term Time Series Data: A Space—Time Cluster Approach

2013

The purpose of this study is to examine the development of Italian tourist areas ( circoscrizioni turistiche) through a cluster analysis of short time series. The technique is an adaptation of the functional data analysis approach developed by Abraham et al (2003), which combines spline interpolation with k-means clustering. The findings indicate the presence of two patterns (increasing and stable) averagely characterizing groups of territories. Moreover, tests of spatial contiguity suggest the presence of ‘space–time clusters’; that is, areas in the same ‘time cluster’ are also spatially contiguous. These findings appear to be more robust in particular for those series characterized by an…

spline interpolationjoin count testSeries (mathematics)Computer scienceSpace timeGeography Planning and Developmentk-means clusteringcluster analysis; short time series; spline interpolation; K-means; join count test; Italian tourist areasFunctional data analysisjel:C21jel:C22jel:C38jel:C14jel:L83K-meanshort time serieContiguity (probability theory)Tourism Leisure and Hospitality Managementcluster analysiItalian tourist areasEconometricsCluster (physics)Settore SECS-S/05 - Statistica SocialeSpline interpolationCluster analysisTourism Economics
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Volatility risk premia and financial connectedness

2014

In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to construct an index of connectedness among five European stock markets: France, Germany, UK, Switzerland and the Netherlands, by using volatility risk premia. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. The…

volatility risk premium long memory FIVAR financial connectednessjel:C32jel:C38jel:G13jel:C58
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