The importance of units with pervasive impacts on a large number of other units in a network has become increasingly recognized in the literature. In this paper we propose a new method to detect such influential or dominant units by basing our analysis on unit-specific residual error variances...

This paper extends the cross sectionally augmented panel unit root test proposed by Pesaran (2007) to the case of a multifactor error structure. The basic idea is to exploit information regarding the unobserved factors that are shared by other time series in addition to the variable under...

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation...

This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models. Theoretical results and Monte Carlo simulations suggest that iterated forecasts dominate direct forecasts when estimation error is a...

This paper focuses on the analysis of the long-run response of the Real Exchange Rate (RER) to political risks and tests whether non-economic variables have an impact on RER in 31 emerging and developing countries. We use annual data from the International Country Risk Guide database over the...

Employing an endogenous growth model with human capital, this paper explores how productivity shocks in the goods and human capital producing sectors contribute to explaining aggregate fluctuations in output, consumption, investment and hours. Given the importance of accounting for both the...

We examine 22 determinants of stock market correlations in a panel setting with 651 country pairs of developed economies over the 2001-2018 period, while accounting for model uncertainty and reverse causality. On the one hand, we find, that a number of determinants, well established in the...

Epidemiological models assume gravity-like interactions of individuals across space without microfoundations. We combine a simple epidemiological frame-work with a dynamic model of individual location choice. The model predicts that flows of people across space obey a structural gravity...

The primary motivation behind quantitative modeling in international trade and many other fields is to shed light on the economic consequences of policy changes. To help assess and potentially strengthen the credibility of such quantitative predictions we introduce an IV-based goodness-of-fit...