Applications of Copula Econometrics to Analyses of Some Economic Issues PDF Download

Author:
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 149

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Author: Van-Nam Huynh
Publisher: Springer Science & Business Media
ISBN: 3642354432
Category : Technology & Engineering
Languages : en
Pages : 323

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Book Description
Unlike uncertain dynamical systems in physical sciences where models for prediction are somewhat given to us by physical laws, uncertain dynamical systems in economics need statistical models. In this context, modeling and optimization surface as basic ingredients for fruitful applications. This volume concentrates on the current methodology of copulas and maximum entropy optimization. This volume contains main research presentations at the Sixth International Conference of the Thailand Econometrics Society held at the Faculty of Economics, Chiang Mai University, Thailand, during January 10-11, 2013. It consists of keynote addresses, theoretical and applied contributions. These contributions to Econometrics are somewhat centered around the theme of Copulas and Maximum Entropy Econometrics. The method of copulas is applied to a variety of economic problems where multivariate model building and correlation analysis are needed. As for the art of choosing copulas in practical problems, the principle of maximum entropy surfaces as a potential way to do so. The state-of-the-art of Maximum Entropy Econometrics is presented in the first keynote address, while the second keynote address focusses on testing stationarity in economic time series data.

Author: Ivan Medovikov
Publisher:
ISBN:
Category :
Languages : en
Pages : 204

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The essence of almost any multivariate econometric analysis is the analysis of dependence between sets of random quantities of interest. A series of new, powerful and omnibus non- parametric tools for the analysis of dependence emerged recently in the econometric literature, which are based on the statistical theory of copulas. A copula function completely, and in the case of random variables with continuous marginal distribution functions, uniquely character- izes their interdependence. The term?copula? emphasizes the manner in which it?couples? the marginal distributions into joint by specifying the dependence structure. This dissertation con- sists of four chapters and aims to contribute to both the theory and the applications of copulas to problems in economics, econometrics and finance. The second chapter is empirical in nature. It adopts the copula approach to the analysis of the relationship between macroeconomic news and financial markets. A large body of literature which studies the impact of news on equity markets exists. A common finding reported in such studies is that news relating to dividends, profits, and the overall state of the economy explains only a small part of the variability in the aggregate stock market returns. A common limitation of such studies is the use of the narrow measures of news, such as, for example, scheduled releases of economic data. The second chapter proposes a broad measure of macroeconomic news which is termed the?Macroeconomic News Index?. The index is based on a manual review and classification of thousands of news releases. Using the copula approach, new find- ings relating to the relationship between macroeconomic news measured using the Index and the stock markets are revealed. In particular, it is found that macroeconomic news has a much larger impact on the equity markets than reported in earlier studies, and that the relationship is highly asymmetric. The third chapter is theoretical, and aims to improve the existing non-parametric copula- based tools which help formally and rigorously establish the presence of dependence in the data. It provides an extension to the independence test statistic proposed in Genest and Remil- lard (2004) and recently Kojadinovic and Holmes (2009), which is obtained through the intro- duction of a weighted functional norm. The addition of the weights creates a channel through which the power properties of the test can be manipulated. The choice of the weights which favors observations closer to the median of the distribution is shown have the ability to give the statistic a significant power advantage. Quessy (2010) recently showed how a test for in- dependence can be used to test for the goodness of fit of parametric copulas. The addition of the weights may be particularly beneficial in this context, since it permits the imposition of asymmetric losses which arise as a consequence of modeling error. The third chapter provides additional results which enable the application of the test statistic to the problems which in- volve estimated quantities such as regression model residuals. In an illustrative application of these results, the test is used to probe the presence of conditional heteroscedasticity in a linear regression model, and is shown to have a power advantage over the test of White (1980) in several settings. This appears to be one of the first applications of the copula theory to the problem of residual-based testing which deserves closer attention and future work. The test statistic proposed in the third chapter cannot be directly applied to the analysis of time series. The fourth chapter provides a serial extension to the statistic, which is closely related to the serial test of Kojadinovic and Yan (2009). The ability to adjust the power of the test through the di erent choices of the weights is retained in the serial case. The fourth chapter further extends the results of Quessy (2010) to the serial setting, which permits the application of the statistic to the testing for the goodness of fit of serial copulas. One limitation of the statistics of Kojadinovic and Holmes (2009), Kojadinovic and Yan (2009), and the weighted statistic proposed in the third chapter is the lack of standardization, meaning that they cannot be used as measures of dependence. An upper bound for the statistic is derived in Chapter 4, which is subject to the empirical marginal copulas. A standardized version of the statistic is proposed, which can serve as an omnibus measure of vectorial dependence. A computational formula for the new copula-based dependence measure is provided.

Author: Kaddour Hadri
Publisher: World Scientific
ISBN: 9814513474
Category : Business & Economics
Languages : en
Pages : 616

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The volume aims at providing an outlet for some of the best papers presented at the 15th Annual Conference of the African Econometric Society, which is one of the OC chaptersOCO of the International Econometric Society. Many of these papers represent the state of the art in financial econometrics and applied econometric modeling, and some also provide useful simulations that shed light on the models'' ability to generate meaningful scenarios for forecasting and policy analysis. Contents: Financial Econometrics and International Finance: Modeling Interest Rates Using Reducible Stochastic Differential Equations: A Copula-Based Multivariate Approach (Ruijun Bu, Ludovic Giet, Kaddour Hadri and Michel Lubrano); Financial Risk Management Using Asymmetric Heavy-Tailed Distribution and Nonlinear Dependence Structures of Asset Returns Under Discontinuous Dynamics (Alaa El-Shazly); Modeling Time-Varying Dependence in the Term Structure of Interest Rates (Diaa Noureldin); Nonlinear Filtering and Market Implied Rating for a Jump-Diffusion Structural Model of Credit Risk (Alaa El-Shazly); Time-Varying Optimal Weights for International Asset Allocation in African and South Asian Markets (Dalia El-Edel); Econometric Theory and Methods: Econometric Methods for Ordered Responses: Some Recent Developments (Franco Peracchi); Which Quantile Is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression (Anil K Bera, Antonio F Galvao Jr., Gabriel V Montes-Rojas, Sung Y Park); The Experimetrics of Fairness (Anna Conte and Peter Moffatt); Uniform in Bandwidth Tests of Specification for Conditional Moment Restrictions Models (Pascal Lavergne and Pierre Nguimkeu); Joint LM Test for Homoscedasticity in a Two Way Error Components Model (Eugene Kouassi, Joel Sango, J M BossonBrou and Kern O Kymn); An Approximation to the Distribution of the Pooled Estimator When the Time Series Equation Is One of a Complete System (Ghazal Amer and William Mikhail); Monetary, Labor, Environmental and Other Econometric Applications: Monetary Policy and the Role of the Exchange Rate in Egypt (Tarek Morsi and Mai El-Mossallamy); International Migration, Remittances and Household Poverty Status in Egypt (Rania Roushdy, Ragui Assaad and Ali Rashed); Determinants of Job Quality and Wages of the Working Poor: Evidence From 1998OCo2006 Egypt Labor Market Panel Survey (Mona Said); A Contract-Theoretic Model of Conservation Agreements (Heidi Gjertsen, Theodore Groves, David A Miller, Eduard Niesten, Dale Squires and Joel Watson); Household Environment and Child Health in Egypt (Mahmoud Hailat and Franco Peracchi); Modeling the Relationship between Natural Resource Abundance, Economic Growth, and the Environment: A Cross-Country Study (Hala Abou-Ali and Yasmine M Abdelfattah); Global Cement Industry: Competitive and Institutional Frameworks (Tarek H Selim and Ahmed S Salem); On the Occurrence of Ponzi Schemes in Presence of Credit Restrictions Penalizing Default (Abdelkrim Seghir); Is Targeted Advertising Always Beneficial? (Nada Ben Elhadj-Ben Brahim, Rim Lahmandi-Ayed and Didier Laussel). Readership: Graduate students and researchers in the fields of econometrics, economic theory, applied econometrics.

Author: Pravin K. Trivedi
Publisher: Now Publishers Inc
ISBN: 1601980205
Category : Business & Economics
Languages : en
Pages : 126

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Copula 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

Author: Umberto Cherubini
Publisher: Springer
ISBN: 3319480154
Category : Business & Economics
Languages : en
Pages : 99

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This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest research developments in the field.

Author: Ly H. Anh
Publisher: Springer
ISBN: 3319731505
Category : Technology & Engineering
Languages : en
Pages : 1089

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This book addresses both theoretical developments in and practical applications of econometric techniques to finance-related problems. It includes selected edited outcomes of the International Econometric Conference of Vietnam (ECONVN2018), held at Banking University, Ho Chi Minh City, Vietnam on January 15-16, 2018. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. An extremely important part of economics is finances: a financial crisis can bring the whole economy to a standstill and, vice versa, a smart financial policy can dramatically boost economic development. It is therefore crucial to be able to apply mathematical techniques of econometrics to financial problems. Such applications are a growing field, with many interesting results – and an even larger number of challenges and open problems.

Author: Vladik Kreinovich
Publisher: Springer
ISBN: 3319507427
Category : Technology & Engineering
Languages : en
Pages : 693

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This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

Author: Riccardo Scarpa
Publisher: Springer Science & Business Media
ISBN: 9781402036835
Category : Business & Economics
Languages : en
Pages : 456

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Book Description
Simulation methods are revolutionizing the practice of applied economic analysis. In this book, leading researchers from around the world discuss interpretation issues, similarities and differences across alternative models, and propose practical solutions for the choice of the model and programming. Case studies show the practical use and the results brought forth by the different methods.

Author: Rainer Winkelmann
Publisher: Springer
ISBN: 9783642096402
Category : Business & Economics
Languages : en
Pages : 320

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Book Description
The book provides an up-to-date survey of statistical and econometric techniques for the analysis of count data, with a focus on conditional distribution models. The book starts with a presentation of the benchmark Poisson regression model. Alternative models address unobserved heterogeneity, state dependence, selectivity, endogeneity, underreporting, and clustered sampling. Testing and estimation is discussed. Finally, applications are reviewed in various fields.