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William Andrew Publishing

Financial, Macro and Micro Econometrics Using R

Medium: Buch
ISBN: 978-0-12-820250-0
Verlag: William Andrew Publishing
Erscheinungstermin: 20.01.2020
Lieferfrist: bis zu 10 Tage
Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.

Produkteigenschaften


  • Artikelnummer: 9780128202500
  • Medium: Buch
  • ISBN: 978-0-12-820250-0
  • Verlag: William Andrew Publishing
  • Erscheinungstermin: 20.01.2020
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2020
  • Produktform: Gebunden
  • Gewicht: 310 g
  • Seiten: 349
  • Format (B x H): 152 x 229 mm
  • Ausgabetyp: Kein, Unbekannt

Autoren/Hrsg.

Weitere Mitwirkende

Vinod, Hrishikesh D.

Hrishikesh D. Vinod is a Ph. D. in economics from Harvard University, who has published over 200 research papers in refereed journals in Economics and Statistics. His R books include: (i) Hands-On Intermediate Econometrics Using R, (ii) Hands-on Matrix Algebra Using R, (World Scientific Publishers: Hackensack), and (iii) Advances in Social Science Research Using R. (Springer). His Wiley Interscience book (joint with D. P. Reagle) is entitled Preparing for the Worst: Incorporating Downside Risk in Stock Market Investments. His Marcel Dekker book (joint with A. Ullah) is Recent Advances in Regression Methods. Vinod was a researcher at the prestigious Bell Laboratories before becoming a tenured full professor of Economics at the 177-year old Fordham University in New York, where he is the Director of the Institute of Ethics and Economic Policy within Economics Department. The exceptionally diverse range and depth of Vinod's research is seen from his CV at: http://www.fordham.edu/economics/vinod/hdv-cv.htm `ResearchGate' reports that Vinod's work is cited by other researchers some 2700 times, attesting its originality and pioneering quality. The cited research may be classified into six categories. 1) Economic theory and applications: Joint production function, Demand function, Disequilibrium models, Elasticity of substitution, Kernel estimation of shape of demand curve, Poisson Model for Measuring the Returns to R&D, Fuzzy Latin Squares. 2) Econometric theory and applications: Bounds on variance of regression coefficients, Unit root, Double bootstrap, Maximum entropy methods, Causality from non-experimental data, economic distance between blacks and whites, Godambe-Durbin Estimating Functions in Econometrics, Maximum Entropy for singular covariance matrices, Projection Pursuit models. 3) Economic policy issues: Controlling corruption, Corporate governance, India's over-population, Hindu economics, Human rights, Entrepreneurship, Unemployment reduction prowess under Bush versus Obama, Preventing Madoff-Style Ponzi Schemes, Enhancing US power and influence in the UN, Stress testing, Tax cuts, Bank divestitures. 4) Mathematical Statistics and applications: Generalized Durbin-Watson test, Ridge regression extensions, Nonparametric regression using clusters, Generalized t ratio, Canonical ridge estimator, Closed forms for asymptotic bias and variance in autoregressive models, Consequences of perturbations of collinear data. 5) Combinatorics, Matrix algebra and applications: Inventory theoretic models of demand and Clustering by integer programming. 6) Software: Vinod's Journal of Economic Literature and American Economic Review articles discuss software numerical accuracy issues. Vinod's R packages are: `meboot' for maximum entropy bootstrap and `generalCorr' for generalized correlation coefficients and causality. Winner of several honors and awards including Fellow of the Journal of Econometrics and keynote speaker at international meetings.

Part I: Finance 1. Financial econometrics and big data: A survey of volatility estimators and tests for the presence of jumps and co-jumps Arpita Mukherjee, Weijia Peng, Norman R. Swanson and Xiye Yang 2. Real time monitoring of asset markets: Bubbles and crises Peter C.B. Phillips and Shuping Shi 3. Component-wise AdaBoost algorithms for high-dimensional binary classification and class probability prediction Jianghao Chu, Tae-Hwy Lee and Aman Ullah

Part II: Macro Econometrics 4. Mixed data sampling (MIDAS) regression models Eric Ghysels, Virmantas Kvedaras and Vaidotas Zemlys-Balevicius 5. Encouraging private corporate investment in India Hrishikesh Vinod, Honey Karun and Lekha S. Chakraborty 6. High-mixed frequency forecasting methods in R-With applications to Philippine GDP and inflation Roberto S. Mariano and Suleyman Ozmucur 7. Nonlinear time series in R: Threshold cointegration with tsDyn Matthieu Stigler

Part III: Micro Econometrics 8. Econometric analysis of productivity: Theory and implementation in R Robin C. Sickles, Wonho Song and Valentin Zelenyuk 9. Stochastic frontier models using R Giancarlo Ferrara