Partial-least-squares path modeling (PLS-PM), a composite-based form of structural equation modeling (SEM), offers great practical advantages to researchers and practitioners. It has been gaining increasing attention in various disciplines, including management information systems, marketing,...

We review recent asymptotic results on some robust methods for multiple regression. The regressors include stationary and non-stationary time series as well as polynomial terms. The methods include the Huber-skip M-estimator, 1-step Huber-skip M-estimators, in particular the Impulse Indicator...

This paper connects two strands of the literature on social trust by estimating the effects of trust on growth through a set of potential transmission mechanisms directly. It does so by modelling the process using a three-stage least squares estimator on a sample of countries for which a full...

Academics and policymakers have shown great interest in cross-national comparisons of intergenerational earnings mobility. However, producing consistent and comparable estimates of earnings mobility is not a trivial task. In most countries researchers are unable to observe earnings information...

This paper investigates the hedging effectiveness of a dynamic moving window OLS hedging model, formed using wavelet decomposed time-series. The wavelet transform is applied to calculate the appropriate dynamic minimum-variance hedge ratio for various hedging horizons for a number of assets. The...

Relying on a large sample of countries, this paper quantifies the effect of political constraints, as measured by legislative control by the incumbent government, on the size of fiscal stimulus packages that have been put in place as reaction to the Great Recession. The results suggest that on...

We replicate eight influential papers to provide empirical evidence that, in the presence of heterogeneous treatment effects, OLS with fixed effects (FE) is generally not a consistent estimator of the average treatment effect (ATE). We propose two alternative estimators that recover the ATE in...

This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and...