1.

Record Nr.

UNINA9910462431303321

Autore

Chipman John Somerset <1926-, >

Titolo

Advanced econometric theory / / John S. Chipman

Pubbl/distr/stampa

Abingdon, Oxon : , : Routledge, , 2011

ISBN

1-283-60655-0

9786613919007

1-134-34045-1

0-203-18075-5

Descrizione fisica

1 online resource (409 p.)

Collana

Routledge advanced texts in economics and finance ; ; 14

Disciplina

330.015195

Soggetti

Econometrics

Economics, Mathematical

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Advanced Econometric Theory; Copyright; Contents; List of figures and tables; Preface; 1 Multivariate analysis and the linear regression model; 1.1 Introduction; 1.2 Existence of a solution to the normal equation; 1.3 The concept of wide-sense conditional expectation; 1.4 Conditional expectation with normal variables; 1.5 The relation between wide-sense and strict-sense conditional expectation; 1.6 Conditional means and minimum mean-square error; 1.7 Bayes estimation; 1.8 The relation between Bayes and Gauss-Markov estimation in the case of a single independent variable; 1.9 Exercises

2 Least-squares and Gauss-Markov theory2.1 Least-squares theory; 2.2 Principles of estimation; 2.3 The concept of a generalized inverse of a matrix; 2.4 The matrix Cauchy-Schwarz inequality and an extension; 2.5 Gauss-Markov theory; 2.6 The relation between Gauss-Markov and least-squares estimators; 2.7 Minimum-bias estimation; 2.8 Multicollinearity and the imposition of dummy linear restrictions; 2.9 Specification error; 2.10 Exercises; 3 Multicollinearity and reduced-rank estimation; 3.1 Introduction; 3.2 Singular-value decomposition of a matrix; 3.3 The condition number of a matrix

3.4 The Eckart-Young theorem3.5 Reduced-rank estimation; 3.6



Exercises; 4 The treatment of linear restrictions; 4.1 Estimation subject to linear restrictions; 4.2 Linear aggregation and duality; 4.3 Testing linear restrictions; 4.4 Reduction of mean-square error by imposition of linear restrictions; 4.5 Uncertain linear restrictions; 4.6 Properties of the generalized ridge estimator; 4.7 Comparison of restricted and generalized ridge estimators; 4A Appendix (to Section 4.4): Guide to the computation of percentage points of the noncentral F distribution; 4.8 Exercises; 5 Stein estimation

5.1 Stein's theorem and the regression model5.2 Lemmas underlying the James-Stein theorem; 5.3 Some further developments of Stein estimation; 5.4 Exercises; 6 Autocorrelation of residuals - 1; 6.1 The first-order autoregressive model; 6.2 Efficiency of trend estimation: the ordinary least-squares estimator; 6.3 Efficiency of trend estimation: the Cochrane-Orcutt estimator; 6.4 Efficiency of trend estimation: the Prais-Winsten weighted-difference estimator; 6.5 Efficiency of trend estimation: the Prais-Winsten first-difference estimator; 6.6 Discussion of the literature; 6.7 Exercises

7 Autocorrelation of residuals - 27.1 Anderson models; 7.2 Testing for autocorrelation: Anderson's theorem and the Durbin-Watson test; 7.3 Distribution and beta approximation of the Durbin-Watson statistic; 7.4 Bias in estimation of sampling variances; 7.5 Exercises; 8 Simultaneous-equations estimation; 8.1 The identification problem; 8.2 Anderson and Rubin's "limited-information maximum-likelihood" (LIML) method, 1: the handling of linear restrictions; 8.3 Anderson and Rubin's "limited-information maximum-likelihood" method, 2: constrained maximization of the likelihood function

8.4 The contributions of Basmann and Theil

Sommario/riassunto

When learning econometrics, what better way than to be taught by one of its masters.  In this significant new volume, John Chipman, the eminence grise of econometrics, presents his classic lectures in econometric theory.Starting with the linear regression model, least squares, Gauss-Markov theory and the first principals of econometrics, this book guides the introductory student to an advanced stage of ability. The text covers multicollinearity and reduced-rank estimation, the treatment of linear restrictions and minimax estimation. Also included are chapters on the autocorr



2.

Record Nr.

UNINA9910551831803321

Titolo

Higher Education Learning Methodologies and Technologies Online : Third International Workshop, HELMeTO 2021, Pisa, Italy, September 9–10, 2021, Revised Selected Papers / / edited by Gabriella Casalino, Marta Cimitile, Pietro Ducange, Natalia Padilla Zea, Riccardo Pecori, Pietro Picerno, Paolo Raviolo

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022

ISBN

3-030-96060-9

Edizione

[1st ed. 2022.]

Descrizione fisica

1 online resource (385 pages)

Collana

Communications in Computer and Information Science, , 1865-0937 ; ; 1542

Disciplina

378

378.17

Soggetti

Education - Data processing

Social sciences - Data processing

User interfaces (Computer systems)

Human-computer interaction

Application software

Artificial intelligence

Computers and Education

Computer Application in Social and Behavioral Sciences

User Interfaces and Human Computer Interaction

Computer and Information Systems Applications

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Methodologies for distance learning in higher education -- Technologies for Distance Learning in Higher Education -- Facing COVID19 Emergency in Higher Education Teaching -- Digital skills in e-learning and continuous online training -- Student’s perception of online learning, teaching, and assessment in higher education -- Faculty Development, Distance Education and online learning systems in higher education -- E-learning and disciplinary teaching: issues and



innovations in contemporary higher education -- From an emergency DaD to new forms of blended learning via effectie methodologies to design, deliver and evaluate learning.

Sommario/riassunto

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Higher Education Learning Methodologies and Technologies Online, HELMeTO 2021, held in Pisa, Italy, in September 2021. Due to the COVID-19 pandemic the conference was held online. The 26 revised full papers and 3 short papers presented were carefully reviewed and selected from a total of 65 submissions. The papers present recent research on challenges of implementing emerging technology solution for online, online learning pedagogical frameworks, facing COVID19 emergency in higher education teaching and learning, online learning technologies in practice, online learning strategies and resources, etc. .