Volume 10, Issue 2

This paper considers the problem of estimating Markov regime switching models with endogenous explanatory variables. When the data-generating process for consumption is subject to Markov regime switching, the standard model for the term structure of interest rates based on the Euler equations for a utility-maximizing agent implies the presence of a time-varying risk premium which is also subject to Markov regime shifts. Under such conditions, the regression equations that are typically used to test the expectations hypothesis of the term structure do not only have regime-dependent parameters but also endogenous regressors (that is right-hand-side variables which are correlated with the disturbances within each regime). Using three-month and six-month interest rates for the G7 countries, we show that the (generalized) expectations hypothesis cannot be rejected when we allow for a risk premium with Markov regimes, provided that instrumental variables are used to account for endogeneity.

In this paper we study 2-state Markov switching VAR models of monthly unemployment and inflation for three countries: Sweden, United Kingdom, and the United States. The primary purpose is to examine if periods of low inflation are associated with high or low unemployment volatility. To interpret the regimes the empirical results are compared with the predictions from a version of Rogoff's (1985) model of monetary policy. Our version is consistent with equilibrium unemployment and has the realistic feature of allowing both variables to be persistent. We find that both the theoretical and the empirical results suggest that an increase in central bank "conservativeness" can be associated with either a higher or a lower variance in unemployment. In the U.S. case we find that the variance of unemployment is lower in the low inflation regime than in the high inflation regime, while the Swedish and the U.K. cases suggest that unemployment variability is higher in the low inflation regime.

This paper investigates whether output and inflation respond asymmetrically to credit shocks in the euro area. The methodology, based on a non-linear VAR system, follows work by Balke (2000) for the U.S. The results reveal evidence of threshold effects related to credit conditions in the economy. Consistent with this finding, the impulse responses show some signs of asymmetric responses over the lending cycle. However, the results of the paper suggest that in the euro area non-linearities arising from credit market imperfections may be less pronounced than in the U.S., probably reflecting specific institutional features of its banking sector.

We propose an estimation procedure for value-at-risk (VaR) and expected shortfall (TailVaR) for conditional distributions of a time series of returns on a financial asset. Our approach combines a local polynomial estimator of conditional mean and volatility functions in a conditional heterocedastic autoregressive nonlinear (CHARN) model with Extreme Value Theory for estimating quantiles of the conditional distribution. We investigate the finite sample properties of our method and contrast them with alternatives, including the method recently proposed by McNeil and Frey (2000), in an extensive Monte Carlo study. The method we propose outperforms the estimators currently available in the literature. An evaluation based on backtesting was also performed.

This paper analyzes whether or not the econometric methods usually applied to test for absolute convergence have provided this hypothesis a "fair" chance. I show that traditional (absolute and conditional) convergence tests are not consistent with even the simplest model that displays convergence. Furthermore, claims of divergence on the grounds of bimodalities in the distribution of GDP per capita can be made consistent with models in which neither divergence nor twin peaks are present in the long run.

This is a corrigendum. We correct the mistakes in Basci and Caner, "Are Real Exchange Rates Nonlinear or Non-stationary? Evidence from a New Threshold Unit Root Test" 2005, vol.9.4, Article 2.