Causal Inference by Independent Component Analysis with Applications to Micro- and Macroeconomic Data
AbstractStructural vector-autoregressive models are potentially very useful tools for guiding both macro- and microeconomic policy. In this paper, we present a recently developed method for exploiting non-Gaussianity in the data for estimating such models, with the aim of capturing the causal structure underlying the data, and show how the method can be applied to both microeconomic data (processes of firm growth and firm performance) as well as macroeconomic data (effects of monetary policy).
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Bibliographic InfoPaper provided by Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics in its series Jena Economic Research Papers with number 2010-031.
Date of creation: 11 May 2010
Date of revision:
Causality; Structural VAR; Independent Components Analysis; Non-Gaussianity; Firm Growth; Monetary Policy;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
- L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
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- Tommaso Ciarli, 2012.
"Structural interactions and long run growth: An application of Experimental Design to Agent Based Models,"
Papers on Economics and Evolution
2012-06, Max Planck Institute of Economics, Evolutionary Economics Group.
- Tommaso Ciarli, 2012. "Structural Interactions and Long Run Growth. An Application of Experimental Design to Agent Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 295-345.
- Tommaso Ferraresi & Andrea Roventini & Giorgio Fagiolo, 2013.
"Fiscal Policies and Credit Regimes: A TVAR Approach,"
03/2013, University of Verona, Department of Economics.
- Tommaso Ferraresi & Andrea Roventini & Giorgio Fagiolo, 2013. "Fiscal Policies and Credit Regimes: A TVAR Approach," LEM Papers Series 2013/03, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
- Tommaso Ferraresi & Andrea Roventini & Giorgio Fagiolo, 2013. "Fiscal policies and credit regimes: a tvar approach," Documents de Travail de l'OFCE 2013-02, Observatoire Francais des Conjonctures Economiques (OFCE).
- Alex Coad, 2007.
"Neoclassical vs evolutionary theories of financial constraints : critique and prospectus,"
Documents de travail du Centre d'Economie de la Sorbonne
r07008, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- Coad, Alex, 2010. "Neoclassical vs evolutionary theories of financial constraints: Critique and prospectus," Structural Change and Economic Dynamics, Elsevier, vol. 21(3), pages 206-218, August.
- Alex Coad, 2007. "Neoclassical vs Evolutionary Theories of Financial Constraints : Critique and Prospectus," UniversitÃ© Paris1 PanthÃ©on-Sorbonne (Post-Print and Working Papers) halshs-00144415, HAL.
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