.

0 (hodnocen0 x )

EB

EB

ONLINE

Cham : Springer International Publishing, 2017

1 online zdroj

ISBN 978-3-319-50742-2 (e-kniha)

ISBN 9783319507415 (print)

Studies in Computational Intelligence, ISSN 1860-949X ; 692

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..

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Part I Keynote Addresses: Robust Estimation of Heckman Model -- Part II Fundamental Theory: Sequential Monte Carlo Sampling for State Space Models -- Robustness as a Criterion for Selecting a Probability Distribution Under Uncertainty -- Why Cannot We Have a Strongly Consistent Family of Skew Normal (and Higher Order) Distributions -- Econometric Models of Probabilistic Choice: Beyond McFadden’s Formulas -- How to Explain Ubiquity of Constant Elasticity of Substitution (CES) Production and Utility Functions Without Explicitly Postulating CES -- How to Make Plausibility-Based Forecasting More Accurate -- Structural Breaks of CAPM-type Market Model with Heteroskedasticity and Quantile Regression -- Weighted Least Squares and Adaptive Least Squares: Further Empirical Evidence -- Prior-free probabilistic inference for econometricians -- Robustness in Forecasting Future Liabilities in Insurance -- On Conditioning in Multidimensional Probabilistic Models -- New Estimation Method for Mixture of Normal Distributions -- EM Estimation for Multivariate Skew Slash Distribution -- Constructions of multivariate copulas -- Plausibility regions on the skewness parameter of skew normal distributions based on inferential models -- International Yield Curve Prediction with Common Functional Principal Component Analysis -- An alternative to p-values in hypothesis testing with applications in model selection of stock price data -- Confidence Intervals for the Common Mean of Several Normal Populations -- A generalized information theoretical approach to Non-linear time series model -- Predictive recursion maximum likelihood of Threshold Autoregressive model -- A multivariate generalized FGM copulas and its application to multiple regression -- Part III Applications: Key Economic Sectors and Their Transitions: Analysis of World Input-Output Network --

Stochastic Frontier Model in Financial Econometrics: A Copula-based Approach -- Quantile Forecasting of PM10 Data in Korea based on Time Series Models -- Do We Have Robust GARCH Models under Different Mean Equations: Evidence from Exchange Rates of Thailand? -- Joint Determinants of Foreign Direct Investment (FDI) Inflow in Cambodia: A Panel Co-integration Approach -- The Visitors’ Attitudes and Perceived Value toward Rural Regeneration Community Development of Taiwan -- Analyzing the contribution of ASEAN stock markets to systemic risk -- Estimating Efficiency of Stock Return with Interval Data -- The impact of extreme events on portfolio in financial risk management -- Foreign Direct Investment, Exports and Economic Growth in ASEAN Region: Empirical Analysis from Panel Data -- Author Index.