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Books on the topic 'Autoregressive vectors'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Ooms, Marius. Empirical Vector Autoregressive Modeling. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-48792-7.

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2

Holden, K. Vector autoregression modelling and forecasting. Liverpool Business School, 1994.

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3

1943-, Holden K., ed. Vector autoregression modelling and forecasting. John Wiley, 1995.

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4

Brüggemann, Ralf. Model Reduction Methods for Vector Autoregressive Processes. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17029-4.

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5

Aggarwal, Shalini, Sunita Arora, and Arvinder Kaur. How to Use Vector Autoregressive (VAR) Models. SAGE Publications Ltd, 2025. https://doi.org/10.4135/9781036213596.

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6

Johansen, Søren. Likelihood-based inference in cointegrated vector autoregressive models. Oxford University Press, 1995.

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7

Brännström, Tomas. Bias approximation and reduction in vector autoregressive models. typescript, 1995.

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8

Ramaswamy, Ramana. Japan's stagnant nineties: A vector autoregression retrospective. International Monetary Fund, Asia and Pacific Department, 1999.

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9

universitet, Uppsala, ed. Essays on vector autoregressions with cointegrating restrictions. Uppsala University, 1992.

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10

Kadiyala, K. R. Forecasting with Bayesian vector autoregressions. Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1989.

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11

Johansen, Søren. A small sample correction for tests of hypotheses on the cointegrating vectors. European University Institute, 1999.

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12

Crone, Theodore M. Vector-autoregression forecast models for the third district states. Federal Reserve Bank of Philadelphia, Economic Research Division, 1992.

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13

Ghatak, Anita. Vector autoregression modelling and forecasting growth of South Korea. De Montfort University, School of Social Sciences, 1997.

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14

Wright, Jonathan H. Exact confidence intervals for impulse responses in a gaussian vector autoregression. Federal Reserve Board, 2000.

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15

Mocan, H. Naci. Business cycles and fertility dynamics in the U.S.: A vector-autoregressive model. National Bureau of Economic Research, 1989.

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16

Bayoumi, Tamim A. Foreign entanglements: Estimating the source and size of spillovers across industrial countries. International Monetary Fund, Western Hemisphere Dept., 2007.

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17

Elitzak, Howard. Quarterly forecasting of meat retail prices: A vector autoregression approach. U.S. Dept of Agriculture, Economic Research Service, Commodity Economics Division, 1989.

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18

Johansen, Søren. A small sample correction of the test for cointegrating rank in the vector autoregressive model. European University Institute, 2000.

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19

Bernanke, Ben S. Measuring the effects of monetary policy: A factor-augmented vector autoregressive (FAVAR) approach. National Bureau of Economic Research, 2004.

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20

Hasan, Mohammad S. Monetary policy, fiscal policy, and aggregate economic activity in a vector autoregressive model. University of Northumbria at Newcastle, 1995.

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21

Johansen, Søren. The asymptotic variance of the estimated roots in a cointegrated vector autoregressive model. European University Institute, Department of Economics, 2001.

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22

Love, Inessa. Financial development and dynamic investment behavior: Evidence from panel vector autoregression. World Bank, Finance, Development Research Group, 2002.

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23

Johansen, Søren. Controlling inflation in a cointegrated vector autoregressive model with an application to US data. European University Institute, Department of Economics, 2001.

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24

Kobler, Alexander E. Sources and dynamics of macroeconomic fluctuations in Switzerland: Evidence from a structural vector autoregressive approach. Peter Lang, 2000.

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25

Johansen, Søren. A small sample correction of the test for cointegrating rank in the vector autoregressive model. European University Institute, 2000.

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26

Derek, Deadman, ed. New directions in econometric practice: General to specific modelling, cointegration, and vector autoregression. 2nd ed. Edward Elgar Pub., 1997.

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27

Charemza, Wojciech. New directions in econometric practice: General to specific modelling, cointegration, and vector autoregression. E. Elgar, 1992.

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28

Ang, Andrew. A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables. National Bureau of Economic Research, 2001.

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29

Fund, International Monetary, ed. Recession and recovery in the United Kingdom in the 1990s: A vector autoregression approach. International Monetary Fund, 1995.

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30

Fernández-Villaverde, Jesús. A, B, C's, (and D's) for understanding VARS. Federal Reserve Bank of Atlanta, 2005.

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31

Fernández-Villaverde, Jesús. A, B, C's (and D)'s for understanding VARS. National Bureau of Economic Research, 2005.

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32

Reimers, Hans-Eggert. Analyse kointegrierter Variablen mittels vektorautoregressiver Modelle. Physica-Verlag, 1991.

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33

Cha, Baekin. The influence of the exchange rate on the U.S. wage process: A vector autoregression approach. City Polytechnic of Hong Kong, Department of Economics and Finance, 1993.

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34

Fund, International Monetary, ed. Italian unemployment 1975-95: An analysis of macroeconomic shocks and policies using evidence from a structural vector autoregression. International Monetary Fund, 1996.

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35

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 evaluati

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36

Skinner, David. Can vector autoregressive modelling with leading indicators serve as a useful supplement to mainstream modellers?: Astudy in the light of forecasting failures since the mid 1980s. typescript, 1992.

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37

Campbell, John Y. A variance decomposition for stock returns. LSE Financial Markets Group, 1990.

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38

Campbell, John Y. A variance decomposition for stock returns. National Bureau of Economic Research, 1990.

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39

Structural Vector Autoregressive Analysis. Cambridge University Press, 2017.

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40

Ooms, Marius. Empirical Vector Autoregressive Modeling. Springer London, Limited, 2012.

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41

Lütkepohl, Helmut, and Lutz Kilian. Structural Vector Autoregressive Analysis. Cambridge University Press, 2017.

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42

Empirical vector autoregressive modeling. Springer-Verlag, 1994.

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43

Lütkepohl, Helmut, and Lutz Kilian. Structural Vector Autoregressive Analysis. Cambridge University Press, 2017.

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44

Lütkepohl, Helmut, and Lutz Kilian. Structural Vector Autoregressive Analysis. Cambridge University Press, 2017.

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45

Empirical Vector Autoregressive Modeling. Springer, 2012.

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46

Model Reduction Methods for Vector Autoregressive Processes. Springer, 2004.

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47

Brüggemann, Ralf. Model Reduction Methods for Vector Autoregressive Processes. Springer London, Limited, 2012.

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48

Johansen, Søren. Likelihood-Based Inference in Cointegrated Vector Autoregressive Models. Oxford University Press, Incorporated, 1995.

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49

Likelihood-based inference in cointegrated vector autoregressive models. Oxford University Press, 1995.

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50

Rendu, Christel, and Ramana Ramaswamy. Japan's Stagnant Nineties - a Vector Autoregression Retrospective. International Monetary Fund, 1999.

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