In this paper, we use identification-robust methods to assess the empirical adequacy of a New Keynesian Phillips Curve (NKPC) equation. We focus on the Gali and Gertler's (1999) specification, on both U.S. and Canadian data. Two variants of the model are studied: one based on a...

We propose methods for testing hypothesis of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses...

This paper proposes a new nonparametric test for conditional independence, which is based on the comparison of Bernstein copula densities using the Hellinger distance. The test is easy to implement because it does not involve a weighting function in the test statistic, and it can be applied in...

The Swiss Federal government finances are in an excellent shape: debt is small (and decreasing), and carries a low interest rate. This paper reviews the prospects for the Swiss finances drawing on the recent literature. We argue that the current policy of running surpluses and paying down the...

The Swiss Federal government finances are in an excellent shape: debt is small (and decreasing), and carries a low interest rate. This paper reviews the prospects for the Swiss finances drawing on the recent literature. We argue that the current policy of running surpluses and paying down the...

In a fixed exchange-rate regime, monetary policy is not devoted to internal equilibrium, such that the Taylor principle is no more the condition to insure the determinacy of the dynamic. Monetary policy is in charge of stabilizing the fixed-exchange rate regime in the long run, i.e. to avoid an...

Statistical tests in vector autoregressive (VAR) models are typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with fairly large samples, especially when the number...