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Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression

Publikation: Working paperForskning

Standard

Allowing the Data to Speak Freely : The Macroeconometrics of the Cointegrated Vector Autoregression. / Hoover, Kevin D.; Juselius, Katarina; Johansen, Søren.

Department of Economics, University of Copenhagen, 2007.

Publikation: Working paperForskning

Harvard

Hoover, KD, Juselius, K & Johansen, S 2007 'Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression' Department of Economics, University of Copenhagen.

APA

Hoover, K. D., Juselius, K., & Johansen, S. (2007). Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression. Department of Economics, University of Copenhagen.

Vancouver

Hoover KD, Juselius K, Johansen S. Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression. Department of Economics, University of Copenhagen. 2007.

Author

Hoover, Kevin D. ; Juselius, Katarina ; Johansen, Søren. / Allowing the Data to Speak Freely : The Macroeconometrics of the Cointegrated Vector Autoregression. Department of Economics, University of Copenhagen, 2007.

Bibtex

@techreport{670d3f90aed911dcbee902004c4f4f50,
title = "Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression",
abstract = "An explication of the key ideas behind the Cointegrated Vector Autoregression Approach. The CVAR approach is related to Haavelmo's famous {"}Probability Approach in Econometrics{"} (1944). It insists on careful stochastic specification as a necessary groundwork for econometric inference and the testing of economic theories. In time-series data, the probability approach requires careful specification of the integration and cointegration properties of variables in systems of equations. The relationship between the CVAR approach and wider methodological issues and between it and related approaches (e.g., the LSE approach) are explored. The specific-to-general strategy of widening the scope of econometric models to identify stochastic trends and cointegrating relations and to nest theoretical economic models is illustrated with the example of purchasing-power parity",
keywords = "Faculty of Social Sciences, cointegrated VAR, stochastic trends, PPP",
author = "Hoover, {Kevin D.} and Katarina Juselius and S{\o}ren Johansen",
note = "JEL Classification: B41, C32, C51",
year = "2007",
language = "English",
publisher = "Department of Economics, University of Copenhagen",
address = "Denmark",
type = "WorkingPaper",
institution = "Department of Economics, University of Copenhagen",

}

RIS

TY - UNPB

T1 - Allowing the Data to Speak Freely

T2 - The Macroeconometrics of the Cointegrated Vector Autoregression

AU - Hoover, Kevin D.

AU - Juselius, Katarina

AU - Johansen, Søren

N1 - JEL Classification: B41, C32, C51

PY - 2007

Y1 - 2007

N2 - An explication of the key ideas behind the Cointegrated Vector Autoregression Approach. The CVAR approach is related to Haavelmo's famous "Probability Approach in Econometrics" (1944). It insists on careful stochastic specification as a necessary groundwork for econometric inference and the testing of economic theories. In time-series data, the probability approach requires careful specification of the integration and cointegration properties of variables in systems of equations. The relationship between the CVAR approach and wider methodological issues and between it and related approaches (e.g., the LSE approach) are explored. The specific-to-general strategy of widening the scope of econometric models to identify stochastic trends and cointegrating relations and to nest theoretical economic models is illustrated with the example of purchasing-power parity

AB - An explication of the key ideas behind the Cointegrated Vector Autoregression Approach. The CVAR approach is related to Haavelmo's famous "Probability Approach in Econometrics" (1944). It insists on careful stochastic specification as a necessary groundwork for econometric inference and the testing of economic theories. In time-series data, the probability approach requires careful specification of the integration and cointegration properties of variables in systems of equations. The relationship between the CVAR approach and wider methodological issues and between it and related approaches (e.g., the LSE approach) are explored. The specific-to-general strategy of widening the scope of econometric models to identify stochastic trends and cointegrating relations and to nest theoretical economic models is illustrated with the example of purchasing-power parity

KW - Faculty of Social Sciences

KW - cointegrated VAR

KW - stochastic trends

KW - PPP

M3 - Working paper

BT - Allowing the Data to Speak Freely

PB - Department of Economics, University of Copenhagen

ER -

ID: 1947778