A Method for Experimental Events that Break Cointegration: Counterfactual Simulation
In this paper I develop a method to estimate the effect of an event on a time series variable. The event is framed in a quasi-experimental setting with time series observations on a treatment variable, which is affected by the event, and a control variable, which is not. Prior to the event, the two variables are cointegrated. After the event, they are not. Since the event only affects the treatment variable, the method uses observations on the control variable after the event and the distribution of difference in differences before the event to simulate values for the treatment variable as-if the event did not occur; hence the name counterfactual simulation. I describe theoretical properties of the method and show the method in action with purpose-built data.
|Date of creation:||07 Feb 2014|
|Date of revision:|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Deirdre N. McCloskey & Stephen T. Ziliak, 1996. "The Standard Error of Regressions," Journal of Economic Literature, American Economic Association, vol. 34(1), pages 97-114, March.
- Engle, Robert F & Granger, Clive W J, 1987.
"Co-integration and Error Correction: Representation, Estimation, and Testing,"
Econometric Society, vol. 55(2), pages 251-76, March.
- Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
- Bell, Peter N, 2014. "Farmland Ownership Restrictions: Between a Rock and a Hard Place," MPRA Paper 53033, University Library of Munich, Germany.
- Gregory, Allan W. & Hansen, Bruce E., 1996.
"Residual-based tests for cointegration in models with regime shifts,"
Journal of Econometrics,
Elsevier, vol. 70(1), pages 99-126, January.
- Allan w. Gregory & Bruce E. Hansen, 1992. "residual-Based Tests for Cointegration in Models with Regime Shifts," Working Papers 862, Queen's University, Department of Economics.
- Tom Doan, . "GREGORYHANSEN: RATS procedure to implement Gregory-Hansen test for Cointegration with breaks," Statistical Software Components RTS00082, Boston College Department of Economics.
- Gregory, A.W. & Hansen, B.E., 1992. "Residual-Based Tests for Cointegration in Models with Regime Shifts," RCER Working Papers 335, University of Rochester - Center for Economic Research (RCER).
- Tom Doan, . "RATS programs to replicate results from Gregory and Hansen(1996) JOE article," Statistical Software Components RTZ00081, Boston College Department of Economics.
- Christian Upper, 2007. "Using counterfactual simulations to assess the danger of contagion in interbank markets," BIS Working Papers 234, Bank for International Settlements.
- Ole Peters, 2010. "The time resolution of the St. Petersburg paradox," Papers 1011.4404, arXiv.org, revised Mar 2011.
- Ole Peters, 2011. "Menger 1934 revisited," Papers 1110.1578, arXiv.org.
When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:53523. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter)
If references are entirely missing, you can add them using this form.