Copula Modeling: An Introduction for PractitionersCopula Modeling explores the copula approach for econometrics modeling of joint parametric distributions. Copula Modeling demonstrates that practical implementation and estimation is relatively straightforward despite the complexity of its theoretical foundations. An attractive feature of parametrically specific copulas is that estimation and inference are based on standard maximum likelihood procedures. Thus, copulas can be estimated using desktop econometric software. This offers a substantial advantage of copulas over recently proposed simulation-based approaches to joint modeling. Copulas are useful in a variety of modeling situations including financial markets, actuarial science, and microeconometrics modeling. Copula Modeling provides practitioners and scholars with a useful guide to copula modeling with a focus on estimation and misspecification. The authors cover important theoretical foundations. Throughout, the authors use Monte Carlo experiments and simulations to demonstrate copula properties |
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Common terms and phrases
algorithm analysis appropriate copula bivariate distribution Clayton copula conditional consider continuous copula approach copula function copula modeling copula-based correlation covariates dence denote density dependence parameter dependence structure derive different copulas distribution function Econometrics empirical applications example FGM copula Frank copula Fréchet Frechet-Hoeffding bounds Gaussian copula Genest given Gumbel copula Hougaard independence joint distribution joint survival Journal Kendall's tau Laplace transform left tail likelihood function log likelihood function m-variate maize marginal distributions marginal probabilities Marshall and Olkin maximum likelihood method misspecification mixtures of powers model selection Monte Carlo experiments multivariate distributions negative dependence Nelsen nonparametric normal distribution outcomes overdispersion pairs Pr[U product copula properties random variables regression restrictive scatter diagrams scatter plots Schweizer Section selection model simulated Spearman's rho specification Statistical survival analysis survival copulas theorem tion Tobit model trivariate true values TSML u₁ univariate marginal upper bound upper tail dependence y₁ and y2