This paper studies the robust estimation and inference of threshold models with integrated regres- sors. We derive the asymptotic distribution of the profiled least squares (LS) estimator under the diminishing threshold effect assumption that the size of the threshold effect converges to zero....

Nowcasting methods have become a crucial tool for central banks and investors due to their timeliness and ability to make 'on the spot' predictions. However, despite their popularity, there has been little research into statistical methods for the comparison of different nowcasts across multiple...

We develop theory of a novel fast bootstrap for dependent data. Our scheme deploys i.i.d. resampling of smoothed moment indicators. We characterize the class of parametric and semiparametric estimation problems for which the method is valid. We show the asymptotic re refinements of the new...

The contingency table literature on tests for dependence among discrete multi-category variables is extensive. Existing tests assume, however, that draws are independent, and there are no tests that account for serial dependencies -- a problem that is particularly important in economics and...

The modified Sharpe ratio is commonly used to evaluate the risk-adjusted performance of an investment with non-normal returns, such as hedge funds. In this note, a test for equality of modified Sharpe ratios of two investments is developed. A simulation study demonstrates the good size and power...

Numerous tests designed to detect realized jumps over a fixed time span have been proposed and extensively studied in the financial econometrics literature. These tests differ from “long time span tests” that detect jumps by examining the magnitude of the jump intensity parameter in the data...

We propose a new adequacy test and a graphical evaluation tool for nonlinear dynamic models. The proposed techniques can be applied in any setup where parametric conditional distribution of the data is specified, in particular to models involving conditional volatility, conditional higher...

This study addresses some modeling questions related to the possibility of structural change in models with non-stationary variables. Focusing on cointegration issues, some methodological aspects ere discussed, attempting to integrate coherently the several steps of the modelling strategy. These...

In this paper, we propose a new approach to model structural change in cointegrating regressions using penalized regression techniques. First, we consider a setting with known breakpoint candidates and show that a modified adaptive lasso estimator can consistently estimate structural breaks in...

This paper analyzes the relationship between the properties of the prediction errors of a predictor that assumes an autoregressive unit root and its optimal detection. According with this relationship, new autoregressive unit root tests are proposed based on multi-step prediction errors. It is...