One of the key inputs for inflation targeting regime is the right identification of inflationary or disinflationary pressures. These pressures are usually approximated by the output gap. In this paper we provide an estimation of the Peruvian output gap using a multivariate unobserved component...

The dynamic properties of the The New Keynesian Phillips curve (NPC) is analysed within the framework of a small system of linear difference equations. We evaluate the empirical results of existing studies which uses `Euroland' and US data. The debate has been centered around the...

We develop a model of a small open economy with three types of nominal rigidities (domestic goods prices, imported goods prices and wages) and eight different structural shocks. We estimate the model's structural parameters using a maximum likelihood procedure and use it to compute...

This paper considers an important practical problem in testing time-series data for nonlinearity in mean. Most popular tests reject the null hypothesis of linearity too frequently if the the data are heteroskedastic. Two approaches to redressing this size distortion are considered, both of which...

This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when selection to treatment is based on observable characteristics. The paper also presents three estimation procedures for these parameters, all of which have two steps: a...

We compare the performance of a currency board, inflation targeting, and dollarization in a small, open developing economy with a liberalized capital account. We focus on the transmission of shocks to currency and country risk premia and on the role of fluctuations in premia in the propagation...

Recently there have been much discussion of the theory and applications of long memory processes. In this paper we consider the standard linear model y=X*b+u and assume that the variance covariance matrix of the errors being generated from an ARFIMA(0,d,0) model. Following Banerjee and Magnus...

A common problem in out-of-sample prediction is that there are potentially many relevant predictors that individually have only weak explanatory power. We propose bootstrap aggregation of pre-test predictors (or bagging for short) as a means of constructing forecasts from multiple regression...