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This paper discusses how the forecast accuracy of a Bayesian vector autoregression (BVAR) is affected by introducing the zero lower bound on the federal funds rate. As a benchmark I adopt a common BVAR specification, including 18 variables, estimated shrinkage, and no nonlinearity. Then I entertain alternative specifications of the zero lower bound. I account for the possibility that the effect of monetary policy on the economy is different in this regime, replace the federal funds rate by its shadow rate, consider a logarithmic transformation, feed in monetary policy shocks, or utilize conditional forecasts allowing for all shocks implemented through a rejection sampler. The latter two are also coupled with interest rate expectations from future contracts. It is shown that the predictive densities of all these specifications are greatly different, suggesting that this modeling choice is not innocuous. The comparison is based on the accuracy of point and density forecasts of major US macroeconomic series during the period 2009:1 to 2014:4. The introduction of the zero lower bound is not beneficial per se, but it depends on how it is done and which series is forecasted. With caution, I recommend the shadow rate specification and the rejection sampler combined with interest rate expectations to deal with the nonlinearity in the policy rate. Since the policy rate will remain low for some time, these findings could prove useful for practical forecasters.

In this paper we propose a very general multivariate Markov-switching regression (MSR) model considering the normal inverse Gaussian (NIG) distribution as conditional form of financial returns and model innovations. It is indeed well-known that the Gaussian distribution is not able to capture many stylized facts of the return series such as skewness, excess kurtosis and heavy tails. Through a large simulation study and an empirical analysis of the US stock market, we show that a NIG-based MSR model allows to adequately account for both skewness and fat tails in the data and, according to model selection criteria, is the best overall model in the majority of the cases considered, even preferred over other popular distributional assumptions such as Student- t and GED. We develop an EM algorithm which allows the estimation of the model parameters in closed form. As a natural byproduct of the algorithm we also derive the scores of the model estimators that allow us to perform dynamic specification tests to check for autocorrelation and for the violation of the first-order Markov assumption.

This study proposes an approach based on a perturbation technique to construct global solutions to dynamic stochastic general equilibrium models (DSGE). The main idea is to expand a solution in a series of powers of a small parameter scaling the uncertainty in the economy around a solution to the deterministic model, i.e. the model where the volatility of the shocks vanishes. If a deterministic path is global in state variables, then so are the constructed solutions to the stochastic model, whereas these solutions are local in the scaling parameter. Under the assumption that a deterministic path is already known the higher order terms in the expansion are obtained recursively by solving linear rational expectations models with time-varying parameters. The present work also proposes a method rested on backward recursion for solving general systems of linear rational expectations models with time-varying parameters and determines the conditions under which the solutions of the method exist.

In this paper, we discuss the relationship between three time lags (the consumption lag, the investment decision lag and the gestation lag) and oscillatory economic fluctuations in the Keynesian IS-LM system. We first confirm that in the absence of time lags, the monotone convergence to the unique equilibrium is observed. Next, we demonstrate that, in the Keynesian IS-LM system, in the existence of the investment decision lag and the gestation lag, oscillatory fluctuations are generated around the equilibrium if the gestation lag is relatively long, while in the existence of the consumption lag and the gestation lag, oscillatory behaviors may not occur. We then conclude that the existence of time lags may be one of the major causes of oscillatory fluctuations.

We consider the congestion effect of productive government spending in a monopolistic competition model with endogenous entry, and analyze the possibility of local indeterminacy. Some main findings emerge from the analysis. First, the indeterminacy condition is independent of the monopoly power. Second, productive government expenditure can be a source of local indeterminacy, while a higher degree of public goods congestion lessens the beneficial effect of productive government expenditure, and therefore reduces the possibility of indeterminacy. Third, a higher degree of internal returns to scale is associated with a lower possibility for the emergence of indeterminacy when production externalities are present.