The General Equivalence of Granger and Sims Causality
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- Chamberlain, Gary, 1981. "The General Equivalence Of Granger And Sims Causality," SSRI Workshop Series 292583, University of Wisconsin-Madison, Social Systems Research Institute.
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Cited by:
- Angrist, Joshua D., 1997.
"Conditional independence in sample selection models,"
Economics Letters, Elsevier, vol. 54(2), pages 103-112, February.
- Angrist, J.D., 1996. "Conditional Independance in Sample Selection Models," Working papers 96-27, Massachusetts Institute of Technology (MIT), Department of Economics.
- Markus Frölich, 2008. "Parametric and Nonparametric Regression in the Presence of Endogenous Control Variables," International Statistical Review, International Statistical Institute, vol. 76(2), pages 214-227, August.
- Pigini, Claudia, 2021.
"Penalized maximum likelihood estimation of logit-based early warning systems,"
International Journal of Forecasting, Elsevier, vol. 37(3), pages 1156-1172.
- Claudia Pigini, 2019. "Penalized Maximum Likelihood Estimation Of Logit-Based Early Warning Systems," Working Papers 441, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
- Manuel Arellano & Stéphane Bonhomme, 2017.
"Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models,"
Annual Review of Economics, Annual Reviews, vol. 9(1), pages 471-496, September.
- Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers CWP51/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers 51/16, Institute for Fiscal Studies.
- Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2016_1607, CEMFI.
- Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2017_1703, CEMFI.
- Colombi, R. & Giordano, S., 2012. "Graphical models for multivariate Markov chains," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 90-103.
- Truquet, Lionel, 2023. "Strong mixing properties of discrete-valued time series with exogenous covariates," Stochastic Processes and their Applications, Elsevier, vol. 160(C), pages 294-317.
- Roberto Colombi & Sabrina Giordano, 2013. "Monotone dependence in graphical models for multivariate Markov chains," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(7), pages 873-885, October.
- Pigini, Claudia & Bartolucci, Francesco, 2022. "Conditional inference for binary panel data models with predetermined covariates," Econometrics and Statistics, Elsevier, vol. 23(C), pages 83-104.
- José Julián Escario & José Alberto Molina, "undated". "Do tobacco taxes reduce lung cancer mortality?," Working Papers 2000-17, FEDEA.
- Didier Sornette & Wei-Xing Zhou, 2005.
"Non-parametric determination of real-time lag structure between two time series: the 'optimal thermal causal path' method,"
Quantitative Finance, Taylor & Francis Journals, vol. 5(6), pages 577-591.
- D. Sornette & W. -X. Zhou, 2004. "Non-parametric Determination of Real-Time Lag Structure between Two Time Series: the "Optimal Thermal Causal Path" Method," Papers cond-mat/0408166, arXiv.org.
- Ernst A. Boehm & Vance L. Martin, 1989. "An Investigation into the Major Causes 01 Australia's Recent Inflation and Some Policy Implications," The Economic Record, The Economic Society of Australia, vol. 65(1), pages 1-15, March.
- Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.
- Michael Lechner & Ruth Miquel, 2010.
"Identification of the effects of dynamic treatments by sequential conditional independence assumptions,"
Empirical Economics, Springer, vol. 39(1), pages 111-137, August.
- Michael Lechner & Ruth Miquel, 2005. "Identification of the Effects of Dynamic Treatments by Sequential Conditional Independence Assumptions," University of St. Gallen Department of Economics working paper series 2005 2005-17, Department of Economics, University of St. Gallen.
- Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2018_1703, CEMFI.
- Francesco Bartolucci & Claudia Pigini, 2017.
"Granger causality in dynamic binary short panel data models,"
Working Papers
421, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
- Bartolucci, Francesco & Pigini, Claudia, 2017. "Granger causality in dynamic binary short panel data models," MPRA Paper 77486, University Library of Munich, Germany.
- Admasu A. Maruta & Habtamu T. Edjigu & Woubet Kassa, 2023. "Does financial inclusion empower women in Africa?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 52(3), November.
- Rashid, Abdul, 2004. "Sectoral Linkages; Identifying the Key Growth Stimulating Sector of the Pakistan Economy," MPRA Paper 27210, University Library of Munich, Germany.
- Trond Petersen, 1991. "The Statistical Analysis of Event Histories," Sociological Methods & Research, , vol. 19(3), pages 270-323, February.
- Michael Lechner, 2006. "The Relation of Different Concepts of Causality in Econometrics," University of St. Gallen Department of Economics working paper series 2006 2006-15, Department of Economics, University of St. Gallen.
- Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1993. "Nonlinear Dynamic Structures," Econometrica, Econometric Society, vol. 61(4), pages 871-907, July.
- Zhou, Wei-Xing & Sornette, Didier, 2006. "Non-parametric determination of real-time lag structure between two time series: The "optimal thermal causal path" method with applications to economic data," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 195-224, March.
- Mosconi, Rocco & Seri, Raffaello, 2006. "Non-causality in bivariate binary time series," Journal of Econometrics, Elsevier, vol. 132(2), pages 379-407, June.
- Tsai, Grace Yueh-Hsiang, 1989. "A dynamic model of the U.S. cotton market with rational expectations," ISU General Staff Papers 1989010108000012168, Iowa State University, Department of Economics.
- Ashesh Rambachan & Neil Shephard, 2019. "Econometric analysis of potential outcomes time series: instruments, shocks, linearity and the causal response function," Papers 1903.01637, arXiv.org, revised Feb 2020.
- John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, April.
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