Evidence of stock return predictability by financial ratios is still controversial as documented by inconsistent results for in-sample and out-of-sample regressions as well as substantial parameter instability. This paper shows that these seemingly incompatible results can be reconciled if the...

It is widely known that significant in-sample evidence of predictability does not guarantee significant out-of-sample predictability. This is often interpreted as an indication that in-sample evidence is likely to be spurious and should be discounted. In this Paper we question this conventional...

The non-stationarity of many macroeconomic time series has lead to an increased demand for economic models that are able to generate fragile equilibria. For instance, in this literature the natural unemployment rate is allowed to shift over time depending on past unemployment. Actually, many...

Nowadays researchers can choose the sampling frequency of exchange rates and interest rates. If the number of observations per contract period is large relative to the sample size, standard GMM asymptotic theory provides unreliable inferences in UIP regression tests. We specify a bivariate...

We examine a two country model of the EU and the US. Each has a small sector of the labour and product markets in which there is wage/price rigidity, but otherwise enjoys flexible wages and prices with a one quarter information lag. Using a VAR to represent the data, we find the model as a whole...

Using Monte Carlo experiments, we examine the performance of indirect inference tests of DSGE models in small samples, using various models in widespread use. We compare these with tests based on direct inference (using the Likelihood Ratio). We find that both tests have power so that a...

We extend the method of indirect inference testing to data that is not filtered and so may be non-stationary. We apply the method to an open economy real businss cycle model on UK data. We review the method using a Monte Carlo experiment and find that it performs accurately and has good power.

It is well known that temporal aggregation has adverse effects on Granger causality tests. Time series are often sampled at different frequencies. This is typically ignored, and data are merely aggregated to the common lowest frequency. We develop a set of Granger causality tests that explicitly...

Using Monte Carlo experiments, we examine the performance of Indirect Inference tests of DSGE models, usually versions of the Smets-Wouters New Keynesian model of the US postwar period. We compare these with tests based on direct inference (using the Likelihood Ratio), and on the Del...

We examine whether by adding a credit channel to the standard New Keynesian model we can account better for the behaviour of US macroeconomic data up to and including the banking crisis. We use the method of indirect inference which evaluates statistically how far a model’s simulated behaviour...