2010
DOI: 10.1080/00036840802112349
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A copula-VAR-X approach for industrial production modelling and forecasting

Abstract: Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in… Show more

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Cited by 11 publications
(4 citation statements)
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“…According to the 1 Although theoretical and empirical links between growth rates have been extensively studied in the context of the traditional economic cycle: i.e., GDP growth, inflation, interest rates, policy stance (Bianchi, De Giuli, Fantazzini, & Maggi, 2010), and the modern endogenous growth theory (e.g., economic growth and healthcare growth), the empirical literature on this topic has paid scarce attention to the dependence between tourism and economic growth. 2 A commonly used dependence measure is correlation which indicates the strength and direction of a linear relationship between two random variables, such as the Pearson correlation coefficient.…”
Section: Introductionmentioning
confidence: 99%
“…According to the 1 Although theoretical and empirical links between growth rates have been extensively studied in the context of the traditional economic cycle: i.e., GDP growth, inflation, interest rates, policy stance (Bianchi, De Giuli, Fantazzini, & Maggi, 2010), and the modern endogenous growth theory (e.g., economic growth and healthcare growth), the empirical literature on this topic has paid scarce attention to the dependence between tourism and economic growth. 2 A commonly used dependence measure is correlation which indicates the strength and direction of a linear relationship between two random variables, such as the Pearson correlation coefficient.…”
Section: Introductionmentioning
confidence: 99%
“…In this case, the method could consist in a non-linear VAR (Vector AutoRegressive) model (see, e.g. Bianchi et al, 2010) with three variables, applying a copula function on VAR skew-elliptical distributed residuals. Tail dependence coefficients for the multivariate t-copula are obtained according to Joe (2014).…”
Section: Data and Modeling Proceduresmentioning
confidence: 99%
“…Chen et al., 2013; He et al., 2017; Khedun et al., 2014). Researchers in economics also considered the use of copulas to predict macroeconomic variables such as GDP growth, inflation, unemployment, interest rate, industrial production, and price indices (Bianchi et al., 2010; Liu et al., 2014; Loaiza-Maya & Smith, 2019; Smith & Vahey, 2016). In the finance literature, the copula method is an attractive statistical tool for risk prediction estimation (Sahamkhadam et al., 2018; Segnon & Trede, 2018; Weiß, 2013).…”
Section: Introductionmentioning
confidence: 99%