A bootstrap method for identifying and evaluating a structural vector autoregression

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Graph-theoretic methods of causal search based on the ideas of Pearl (2000), Spirtes et al. (2000), and others have been applied by a number of researchers to economic data, particularly by Swanson and Granger (1997) to the problem of finding a data-based contemporaneous causal order for the structural vector autoregression, rather than, as is typically done, assuming a weakly justified Choleski order. Demiralp and Hoover (2003) provided Monte Carlo evidence that such methods were effective, provided that signal strengths were sufficiently high. Unfortunately, in applications to actual data, such Monte Carlo simulations are of limited value, as the causal structure of the true data-generating process is necessarily unknown. In this paper, we present a bootstrap procedure that can be applied to actual data (i.e. without knowledge of the true causal structure). We show with an applied example and a simulation study that the procedure is an effective tool for assessing our confidence in causal orders identified by graph-theoretic search algorithms. © 2008. Blackwell Publishing Ltd and the Department of Economics, University of Oxford.






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Demiralp, S, KD Hoover and SJ Perez (2008). A bootstrap method for identifying and evaluating a structural vector autoregression. Oxford Bulletin of Economics and Statistics, 70(4). pp. 509–533. 10.1111/j.1468-0084.2007.00496.x Retrieved from https://hdl.handle.net/10161/2047.

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Kevin Douglas Hoover

Professor of Economics

Professor Hoover's research interests include macroeconomics, monetary economics, the history of economics, and the philosophy and methodology of empirical economics. His recent work in economics has focused on the application of causal search methodologies for structural vector autoregression, the history of microfoundational programs in macroeconomics, and Roy Harrod's early work on dynamic macroeconomics. In philosophy, he has concentrated on issues related to causality, especially in economics, and on reductionism -- the philosophical counterpart to microfoundations. Recent publications include:

  • "Trygve Haavelmo's Experimental Methodology and Scenario Analysis in a Cointegrated Vector Autoregression" (Econometric Theory, 2015), 
  • "Reductionism in Economics:  Intentionality and Eschatological Justification in the Microfoundations of Macroeconomics" (Philosophy of Science 2015), 
  • "Mathematical Economics Comes to America:  Charles S. Peirce’s Engagement with Cournot’s Recherches sur les Principes Mathematiques de la Théorie des Richesses" (Journal of the History of Economic Thought, 2015), 
  • "The Genesis of Samuelson and Solow’s Price-Inflation Phillips Curve" (History of Economics Review, 2015), 
  • "Solow's Harrod: Transforming Cyclical Dynamics into a Model of Long-run Growth" (European Journal of the History of Economic Thought 2015), 
  • "In the Kingdom of Solovia:  The Rise of Growth Economics at MIT, 1956-1970" (History of Political Economy 2014), 
  • “Still Puzzling: Evaluating the Price Puzzle in an Empirically Identified Structural Vector Autoregression” (Empirical Economics, 2014),
  • "On the Reception of Haavelmo's Econometric Thought" (Journal of the History of Economic Thought, 2014) – winner of the History of Economics Society Best Paper Award in 2015.  

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