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Books on the topic 'Econometrics'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 June 2025

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1

Congress, Econometric Society World. Advances in econometrics. Cambridge University Press, 1987.

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2

Babeshko, Lyudmila, Mihail Bich, and Irina Orlova. Econometrics and econometric modeling. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141216.

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The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag structure of variables. Methods of linearization and estimation of nonlinear models are considered. An apparatus for evaluating systems of simultaneous and apparently unrelated equations is presented. Attention is paid to time series models. Detailed solutions of the examples in Excel and the R software environment are included. Meets the requirements of the federal state educational standards of higher education of the latest generation. For undergraduate and graduate students studying in the field of "Economics", the curriculum of which includes the disciplines "Econometrics"," Econometric Modeling","Econometric research".

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3

Congress, Econometric Society World. Advances in econometrics: Fifth World Congress. Cambridge University Press, 1994.

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4

Congress, Econometric Society World. Advances in econometrics: Fifth World Congress. Cambridge University Press, 1987.

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5

Hill, R. Carter. Undergraduate econometrics. 2nd ed. Wiley, 2001.

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6

E, Griffiths William, and Judge George G, eds. Undergraduate econometrics. 2nd ed. Wiley, 2001.

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7

E, Griffiths William, and Judge George G, eds. Undergraduate econometrics. Wiley, 1997.

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8

Goldberger, Arthur Stanley. Introductory econometrics. Harvard University Press, 1998.

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9

Kennedy, Peter. A guide to econometrics. 4th ed. Blackwell, 1998.

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10

Baltagi, Badi H. Econometrics. Springer, 1998.

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11

Baltagi, Badi H. Econometrics. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80149-6.

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12

Eatwell, John, Murray Milgate, and Peter Newman, eds. Econometrics. Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-20570-7.

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13

Gujarati, Damodar. Econometrics. Macmillan Education UK, 2015. http://dx.doi.org/10.1007/978-1-137-37502-5.

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14

Baltagi, Badi H. Econometrics. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-00516-3.

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15

Baltagi, Badi H. Econometrics. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-58714-6.

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16

Baltagi, Badi H. Econometrics. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20059-5.

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17

Baltagi, Badi H. Econometrics. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04693-7.

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18

S, Maddala G., Rao C. Radhakrishna 1920-, and Vinod Hrishikesh D. 1939-, eds. Econometrics. North-Holland, 1993.

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19

Baltagi, Badi H. Econometrics. 5th ed. Springer, 2011.

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20

Jorgenson, Dale Weldeau. Econometrics. MIT Press, 2000.

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21

Jon, Stewart. Econometrics. P. Allan, 1991.

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22

Jorgenson, Dale Weldeau. Econometrics. MIT Press, 2000.

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23

Baltagi, Badi H. Econometrics. 2nd ed. Springer, 1999.

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24

Baltagi, Badi H. Econometrics. Springer-Verlag Berlin Heidelberg, 2008.

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25

Mendez, Santiago A. Econometrics: New research. Nova Science Publishers, 2011.

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26

Babeshko, Lyudmila, and Irina Orlova. Econometrics and econometric modeling in Excel and R. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.

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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluation, analysis, and practical implementation of Box — Jenkins stationary time series models, as well as multidimensional time series models: vector autoregressive models and vector error correction models. It includes basic econometric models for panel data that have been widely used in recent decades, as well as formal tests for selecting models based on their hierarchical structure. Each section provides examples of evaluating, analyzing, and testing models in the R software environment. Meets the requirements of the Federal state educational standards of higher education of the latest generation.  It is addressed to master's students studying in the Field of Economics, the curriculum of which includes the disciplines Econometrics (advanced course)", "Econometric modeling", "Econometric research", and graduate students."

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27

Schmidt, Stephen J. Econometria / Econometrics. McGraw-Hill Interamericana, 2006.

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28

E, Griffiths William. Undergraduate Econometrics. Wiley, 2000.

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29

Errouaki, Karim, and Edward J. Nell. Rational Econometric Man: Transforming Structural Econometrics. Elgar Publishing Limited, Edward, 2018.

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30

Hildenbrand, Werner. Advances in Econometrics (Econometric Society Monographs). Cambridge University Press, 1985.

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31

Errouaki, Karim, and Edward J. Nell. Rational Econometric Man: Transforming Structural Econometrics. Elgar Publishing Limited, Edward, 2013.

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32

Jorgenson, Dale W. Econometrics: Econometric Modeling of Producer Behavior. MIT Press, 2000.

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33

E, Griffiths William. Undergraduate Econometrics, Using Excel For. Wiley, 2000.

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34

Dynamic Econometrics (Advanced Texts in Econometrics). Oxford University Press, USA, 1995.

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35

Kanygina, Nadezhda, and Vladimir Chernyak. Applied Econometrics. LCC MAKS Press, 2022. http://dx.doi.org/10.29003/m3039.978-5-317-06842-4.

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This book is a collection of materials for conducting classes on the course "Econometrics-3" for master's students of the Faculty of Economics of Moscow State University, studying under the programs "World Economy" and "Economic Policy". The presented materials can be used both at seminars and in independent work of students when performing the necessary tasks. The presentation of the theoretical part of the course is extremely brief and concise, it is assumed that students have mastered the introductory econometrics course, and use this material mainly for reference without the need to refer to more comprehensive manuals. On the contrary, the analysis of applied and practical problems is presented in detail, in accordance with the main goal of the course – to teach students the methods and techniques of applied econometric analysis.

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36

(Editor), Terence C. Mills, and Kerry Patterson (Editor), eds. Palgrave Handbook of Econometrics: Volume 1: Econometric Theory. Palgrave Macmillan, 2007.

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37

Geweke, John, Gary Koop, and Herman Van Dijk, eds. The Oxford Handbook of Bayesian Econometrics. Oxford University Press, 2011. http://dx.doi.org/10.1093/oxfordhb/9780199559084.001.0001.

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Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. The Oxford Handbook of Bayesian Econometrics is a single source about Bayesian methods in specialized fields. It contains articles by leading Bayesians on the latest developments in their specific fields of expertise. The volume provides broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing. It reviews the state of the art in Bayesian econometric methodology, with articles on posterior simulation and Markov chain Monte Carlo methods, Bayesian nonparametric techniques, and the specialized tools used by Bayesian time series econometricians such as state space models and particle filtering. It also includes articles on Bayesian principles and methodology.

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38

Tinbergen, Jan. Econometrics. Taylor & Francis Group, 2004.

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39

Schmidt, Peter. Econometrics. Taylor & Francis Group, 2020.

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40

Schmidt, Peter. Econometrics. Taylor & Francis Group, 2020.

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41

Jorgenson, Dale W. Econometrics. The MIT Press, 2000. http://dx.doi.org/10.7551/mitpress/2577.001.0001.

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42

Jorgenson, Dale W. Econometrics. The MIT Press, 2002. http://dx.doi.org/10.7551/mitpress/2579.001.0001.

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43

Kumar, K. Nirmal Ravi. Econometrics. Taylor & Francis Group, 2020.

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44

Cameron, Samuel. Econometrics. McGraw Hill Higher Education, 2005.

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45

Greene, William H., and William Becker. Econometrics. Pearson Education, Limited, 2024.

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46

Econometrics. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-76516-5.

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47

Schmidt, Peter. Econometrics. CRC Press, 2020. http://dx.doi.org/10.1201/9781003066958.

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48

Novikov. Econometrics. Infra-M Academic Publishing House, 2013. http://dx.doi.org/10.12737/1596.

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49

Tinbergen, Jan. Econometrics. Routledge, 2004. http://dx.doi.org/10.4324/9780203486610.

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50

Tinbergen, Jan. Econometrics. Routledge, 2004.

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