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Conceptual Econometrics Using R Rao Vinod Hardback North Holland Volume 41

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Conceptual Econometrics Using R

The scope of the handbook covers many topics of practical interest to quantitative scientists, especially in economics and finance

C.R. Rao (Series edited by), Hrishikesh D. Vinod (Volume editor)

9780444643117

Hardback, published 22 August 2019

330 pages

22.9 x 15.2 x 2.4 cm, 0.65 kg

Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, 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, productivity and financial market jumps and co-jumps, among others.

Part I: Statistical Inference 1. Finite-sample inference and nonstandard asymptotics with Monte Carlo tests and R Jean-Marie Dufour and Julien Neves 2]

Conceptual Econometrics Using R Rao Vinod Hardback North Holland Volume 41

Conceptual Econometrics Using R

The scope of the handbook covers many topics of practical interest to quantitative scientists, especially in economics and finance

C.R. Rao (Series edited by), Hrishikesh D. Vinod (Volume editor)

9780444643117

Hardback, published 22 August 2019

330 pages

22.9 x 15.2 x 2.4 cm, 0.65 kg

Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, 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, productivity and financial market jumps and co-jumps, among others.

Part I: Statistical Inference 1. Finite-sample inference and nonstandard asymptotics with Monte Carlo tests and R Jean-Marie Dufour and Julien Neves 2]

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