Robustness in Econometrics

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 ap...

Full description

Saved in:
Bibliographic Details
Other Authors: Kreinovich, Vladik (Editor)
Sriboonchitta, Songsak (Editor)
Huynh, Van-Nam (Editor)
Corporate Author: SpringerLink (online služba)  
Format: eBook
Language:English
Published: Cham : Springer International Publishing, 2017
Series:Studies in Computational Intelligence
Genre/form:elektronické knihy
ISBN:978-3-319-50742-2
9783319507415
Subjects:
Online Access:Plný text
Tags: Add Tag
No Tags, Be the first to tag this record!
Cover Image
LEADER 06553nam a22005535i 4500
001 001825389
003 CZ PrSTK
005 20170212182303.0
006 m f d
007 cr nn 008mamaa
008 170212s2017 gw | s |||| 0|eng d
020 |a 978-3-319-50742-2  |9 9783319507422  |9  
024 7 |a 10.1007/978-3-319-50742-2  |2 doi 
040 |a DE-He213  |b cze  |d ABA013 
072 7 |a 621  |x Strojírenství  |2 Konspekt  |9 19 
080 |a 621:338.45  |2 MRF 
245 1 0 |a Robustness in Econometrics /  |c edited by Vladik Kreinovich, Songsak Sriboonchitta, Van-Nam Huynh 
264 1 |a Cham :  |b Springer International Publishing,  |c 2017 
300 |a 1 online zdroj (X, 705 stran) :  |b 129 ilustrací, 120 barevných ilustrací 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 692 
505 0 |a 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 --- 
505 0 |9 ^^  |a 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 --- 
505 0 |9 ^^  |a Can bagging improve the forecasting performance of tourism demand models? -- The Role of Asian Credit Default Swap Index in Portfolio Risk Management -- Chinese outbound tourism demand to Singapore, Malaysia and Thailand destinations: A study of political events and holiday impacts -- Forecasting Asian Credit Default Swap spreads: A comparison of multi-regime models -- Forecasting Asian Credit Default Swap spreads: A comparison of multi-regime models -- Effect of Helmet Use on Severity of Head Injuries Using Doubly Robust Estimators -- Forecasting cash holding with cash deposit using time series approaches -- Forecasting GDP Growth in Thailand with Different Leading Indicators using MIDAS regression models -- Testing the Validity of Economic Growth Theories Using Copula-based Seemingly Unrelated Quantile Kink Regression -- Analysis of Global Competitiveness Using Copula-based Stochastic Frontier Kink Model -- Gravity model of trade with Linear Quantile Mixed Models approach --- 
505 0 |9 ^^  |a 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 
520 |a 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 
659 0 |a Engineering 
659 0 |a Artificial intelligence 
659 0 |a Computational intelligence 
659 0 |a Econometrics 
659 1 4 |a Engineering 
659 2 4 |a Computational Intelligence 
659 2 4 |a Artificial Intelligence (incl. Robotics) 
659 2 4 |a Econometrics 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
650 0 7 |a technika  |x ve  |7 psh12005  |2 psh 
650 0 7 |a umělá inteligence  |x vt  |7 psh12516  |2 psh 
650 0 7 |a ekonometrie  |x ev  |7 psh1548  |2 psh 
710 2 |a SpringerLink (online služba)  |7 ntk2018999494 
700 1 |a Kreinovich, Vladik  |4 edt 
700 1 |a Sriboonchitta, Songsak  |4 edt 
700 1 |a Huynh, Van-Nam  |4 edt 
776 0 8 |i Tištěné vydání:  |t Robustness in Econometrics  |z 9783319507415 
830 0 |a Studies in Computational Intelligence 
856 4 0 |u https://doi.org/10.1007/978-3-319-50742-2  |y Plný text 
910 |a ABA013 
950 |a Springer  |b Engineering 2017