Robustness in econometrics

• 其他作者：
  • Kreinovich, Vladik, editor.
  • Sriboonchitta, Songsak, editor.
  • Huynh, Van-Nam, editor.
  • SpringerLink (Online service)
• 其他題名：
  • Studies in computational intelligence ;
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Studies in computational intelligence,volume 692
• 主題： Econometrics. , Engineering. , Computational Intelligence. , Artificial Intelligence (incl. Robotics) , Econometrics.
• ISBN： 9783319507422 (electronic bk.) 、 9783319507415 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: 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 -- Natural Resources, Financial Development and Sectoral Value Added in a Resource Based Economy -- Can bagging improve the forecasting per
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• 摘要註: 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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