This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a superior in-sample fit relative to linear models, the gain in prediction remains small. We confirm this result using simulated data for a wide range of specifications. In order to explain this poor performance, we use a forecasting error decomposition. We identify four components and derive their analytical expressions in different MS specifications. The relative contribution of each source is assessed through Monte Carlo simulations. We find that the main source of error is due to the misclassification of future regimes.
This paper explores the various shapes the recoveries may exhibit within a Markov-Switching model. It relies on the bounce-back effects first analyzed by Kim, Morley and Piger (2005) and extends the methodology by proposing i) a more flexible bounce-back model, ii) explicit tests to select the appropriate bounce-back function, if any, and iii) a suitable measure of the permanent impact of recessions. This approach is then applied to post-WWII quarterly growth rates of US, UK and French real GDPs.
The last review of the ECB's monetary policy strategy in 2003 followed a period of predominantly upside risks to price stability. Experience following the 2008 financial crisis has focused renewed attention on the question of how monetary and fiscal policy should best interact, in particular in an environment of structurally low interest rates and persistent downside risks to price stability. This debate has been further intensified by the economic impact of the coronavirus (COVID-19) pandemic. In the euro area, the unique architecture of a monetary union consisting of sovereign Member States, with cross-country heterogeneities and weaknesses in its overall construction, poses important challenges.12 Tax policy may also substitute interest rate policy to change real interest rates (the cost of current consumption in terms of future consumption), even in the case of balanced budgets. See Feldstein (2002) and Correia et al. (2013).
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