Unconditional quantile regressions, as introduced by Firpo, Fortin, and Lemieux (2009), are a special case of Recentered Influence Functions (RIF) Regressions that can be used to relate how small changes in the distributions of explanatory variables affect an unconditional statistic of interest....

The Greek Shipping Estimation Model aims to provide a coherent statistical framework for the estimation of Balance of Payments (BoP) items related to shipping activity, based on administrative sources and commercial databases. Given the multi-territorial nature of the shipping sector and its...

We conduct an interdisciplinary meta-analysis to aggregate the knowledge from empirical estimates of inequality aversion reported from 1999 to 2022. In particular, we examine 85 estimates of disadvantageous inequality aversion (or envy) and advantageous inequality aversion (or guilt) from 26...

The fixed effects (FE) panel model is one of the main econometric tools in empirical economic research. A major practical limitation is that the parameters on time-constant covariates are not identifiable. This paper presents a new approach to grouping FE in the linear panel model to reduce...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

In this paper, we study the spatial dynamic panel data models with high-order time-varying endogenous weights matrices. The quasi-maximum likelihood (QML) estimator is inconsistent under heteroskedastic errors and would be computationally complicated due to the evaluation of the Jacobian...

This paper proposes a minimum distance (MD) estimator to estimate panel regression models with measurement error. The model considered is more general than examined in the literature in that (i) measurement error can be non-classical in the sense that they are allowed to be correlated with the...

This paper is concerned with variable selection in linear high-dimensional frameworks when the covariates under consideration are highly correlated. Existing methods in the literature generally require that the degree of correlation among covariates be weak, yet, often in applied research,...

Broadband availability data collected by the Federal Communications Commission (“FCC”) using its Form 477 are heavily criticized as inaccurate. These data certainly overstate availability since a census block is indicated as having broadband throughout the block even if only a single home in...

This paper initiates a non-linear fractional unit root test also known as autoregressive neural network–fractional integration (ARNN–FI) test. The test is based on a new multilayer perceptron of a neural network process which is applied in Yaya et al. (2021). Further, to investigate the...