The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one's data or a model estimated from the data. Under conditions that hold in a wide variety of econometric applications, the bootstrap provides approximations to distributions of statistics,...

This article introduces and investigates the properties of a new bootstrap method for time-series data, the kernel block bootstrap. The bootstrap method, although akin to, offers an improvement over the tapered block bootstrap of Paparoditis and Politis (2001), admitting kernels with unbounded...

A new bandwidth selection method that uses different bandwidths for the local linear regression estimators on the left and the right of the cut-off point is proposed for the sharp regression discontinuity design estimator of the average treatment effect at the cut-off point. The asymptotic mean...

This article introduces and investigates the properties of a new bootstrap method for time-series data, the kernel block bootstrap. The bootstrap method, although akin to, offers an improvement over the tapered block bootstrap of Paparoditis and Politis (2001), admitting kernels with unbounded...

The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one's data or a model estimated from the data. Under conditions that hold in a wide variety of econometric applications, the bootstrap provides approximations to distributions of statistics,...

Reporting effect sizes and corresponding confidence intervals is increasingly demanded, which generates interest to analyze the performance of confidence intervals around effect sizes. As effect sizes take on the value zero in case of no effect per definition, not only the inclusion of the...

Reporting effect sizes and corresponding confidence intervals is increasingly demanded, which generates interest to analyze the performance of confidence intervals around effect sizes. As effect sizes take on the value zero in case of no effect per definition, not only the inclusion of the...

In stratified sampling there are designs with one unit selected per stratum or when one is willing to make estimations on unplanned domains with one unit in some strata. In these cases the variance is generally estimated by the collapsed strata method, which requires identification of the strata...

In stratified sampling there are designs with one unit selected per stratum or when one is willing to make estimations on unplanned domains with one unit in some strata. In these cases the variance is generally estimated by the collapsed strata method, which requires identification of the strata...

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...

This paper analyzes the persistence property of energy use in 107 countries around the world during 1971-2011 using different subsampling confidence intervals introduced by Romano and Wolf (2001). These confidence intervals are much more informative than the unit root tests and are more robust...

This paper presents two computational techniques and shows that these techniques can improve tests for market efficiency based on profit of trading rules. The two techniques focus on interval estimates for expected profit per trade, in contrast to the standard approach that emphasizes point...

Standard approaches to constructing nonparametric confidence bands for functions are frustrated by the impact of bias, which generally is not estimated consistently when using the bootstrap and conventionally smoothed function estimators. To overcome this problem, it is common practice to either...

Standard approaches to constructing nonparametric confidence bands for functions are frustrated by the impact of bias, which generally is not estimated consistently when using the bootstrap and conventionally smoothed function estimators. To overcome this problem it is common practice to either...

The estimation of the sample size is a crucial part of the planning process of a survey and it can be accomplished in different ways, some of them require information not available or that may be obtained with a substantial cost. The estimation of the sample size can be done by using the design...

Standard approaches to constructing nonparametric confidence bands for functions are frustrated by the impact of bias, which generally is not estimated consistently when using the bootstrap and conventionally smoothed function estimators. To overcome this problem it is common practice to either...

This study examines the effect of feedback on calibration of auditors¡¯ probability judgment. Results from our experiment indicate that auditors¡¯ probability judgments are indeed poorly calibrated and auditors are in general overconfident. In addition, we investigate whether we can use...

A prominent use of local to unity limit theory in applied work is the construction of confidence intervals for autogressive roots through inversion of the ADF t statistic associated with a unit root test, as suggested in Stock (1991). Such confidence intervals are valid when the true model has...

To date, an operational measure of systemic risk capturing non-linear tail comovement between system-wide and individual bank returns has not yet been developed. This paper proposes an extension of the so-called CoVaR measure that captures the asymmetric response of the banking system to...

This paper investigates the use of bootstrap-based bias correction of semi-parametric estimators of the long memory parameter in fractionally integrated processes. The re-sampling method involves the application of the sieve bootstrap to data pre-filtered by a preliminary semi-parametric...

The paper asks how state of the art DSGE models that account for the conditional response of hours following a positive neutral technology shock compare in a marginal likelihood race. To that end we construct and estimate several competing small-scale DSGE models that extend the standard real...

This paper examines whether there is a threshold above which financial development no longer has a positive effect on economic growth. We use different empirical approaches to show that there can indeed be "too much" finance. In particular, our results suggest that finance starts having a...

The estimation of the sample size is a crucial part of the planning process of a survey and it can be accomplished in different ways, some of them require information not available or that may be obtained with a substantial cost. The estimation of the sample size can be done by using the design...

Motivated by the recent advances in the kappa statistic for the clustered physician–patients dichotomous data, we extend the development for the polytomous data. For the clustered physician–patients polytomous data, based on its special correlation and covariance structure, we propose a...

As an important extension of the regular kappa statistic, the weighted kappa statistic has been widely used to assess the agreement between two procedures for independent matched-pair ordinal data. For clustered matched-pair ordinal data, based on the delta method and sampling techniques, a...