We investigate empirically the inflation dynamics in New Zealand, a small open economy and a pioneer in inflation targeting, under various open-economy Phillips curve specifications. Our forecasting exercise suggests that open-economy Phillips curves under standard measures of global slack do...

We evaluate the performance of inflation forecasts based on the open-economy Phillips curve by exploiting the spatial pattern of international propagation of inflation. We model these spatial linkages using global inflation and either domestic slack or oil price fluctuations, motivated by a...

We evaluate two main views on pursuing financial stability within a flexible inflation-targeting regime. It appears that potential gains from an activist or precautionary approach to promoting financial stability are highly shock dependent. We find support for the conventional view that concern...

This paper addresses the notion that many fractional I(d) processes may fall into the ?empty box? category, as discussed in Granger (1999). We present ex ante forecasting evidence based on an updated version of the absolute returns series examined by Ding, Granger and Engle (1993) that suggests...

A long tradition in macro finance studies the joint dynamics of aggregate stock returns and dividends using vector autoregressions (VARs), imposing the cross-equation restrictions implied by the Campbell-Shiller (CS) identity to sharpen inference. We take a Bayesian perspective and develop...

Although macroeconomic forecasting forms an integral part of the policymaking process, there has been a serious lack of rigorous and systematic research in the evaluation of out-of-sample modelbased forecasts of China's real gross domestic product (GDP) growth and consumer price index inflation....

We bring together some recent advances in the literature on vector autoregressive moving-average models creating a relatively simple specification and estimation strategy for the cointegrated case. We show that in the cointegrated case with fixed initial values there exists a so-called final...

Many statistical applications require the forecast of a random variable of interest over several periods into the future. The sequence of individual forecasts, one period at a time, is called a path forecast, where the term path refers to the sequence of individual future realizations of the...