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With the global rise in populism over the last decade, there has been an increase in political commentaries (PC) by leaders that criticize their central banks and argue for lower interest rates. We analyse the effects of PCs on exchange rates, bond yields, and the risk premium for six countries that are subject to political pressures. Utilizing a specification with time‐varying parameters, we show that PCs affect the level and the volatility of exchange rates, bond yields and the risk premium in Turkey. The response increases over time. In other countries, there is a significant impact on exchange rate volatility. [ABSTRACT FROM AUTHOR]

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1468-0084.2007.00496.x Byline: Selva Demiralp ([dagger]), Kevin D. Hoover ([double dagger]), Stephen J. Perez (s.) Keywords: C30; C32; C51 Abstract: Abstract 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. Author Affiliation: ([dagger])Department of Economics, Koc University, Sariyer, Istanbul 34450, Turkey (e-mail:sdemiralp@ku.edu.tr) ([double dagger])Department of Economics, Duke University, 213 Social Science Building, Box 90097, Durham, NC 27708-0097, USA (e-mail:kd.hoover@duke.edu) (s.)Department of Economics, California State University, Sacramento, 6000 J Street, Sacramento, CA 95819-6082, USA (e-mail:sjperez@csus.edu) Article History: Final Manuscript Received: October 2007

The authors demonstrate the application of graph-theoretic techniques to choosing the structural vector autoregression causal order. These techniques are used in a Monte Carlo situation; findings show they are useful tools in structural vector autoregression analysis.