Estimations and applications of factor models often rely on the crucial condition that the number of latent factors is consistently estimated, which in turn also requires that factors be relatively strong, data are stationary and weak serial dependence, and the sample size be fairly large,...

We investigate state-dependent effects of fiscal multipliers and allow for endogenous sample splitting to determine whether the US economy is in a slack state. When the endogenized slack state is estimated as the period of the unemployment rate higher than about 12 percent, the estimated...

While most of the convergence results in the literature on high dimensional covariance matrix are concerned about the accuracy of estimating the covariance matrix (and precision matrix), relatively less is known about the effect of estimating large covariances on statistical inferences. We study...

While applications of big data analytics have brought many new opportunities to economic research, with datasets containing tens of millions of observations, making usual econometric inferences based on extreme estimators would require huge computing powers and memories that are often not...

"Promoting a greater understanding of intercultural interactions, this timely and engaging Research Handbook provides an overview of the current state of research on cultural intelligence and analyzes its prospects for the future. Including contributions from key researchers in the field as well...

We develop a test for deciding whether the linear spaces spanned by the factor exposures of a large cross-section of assets towards latent systematic risk factors at two distinct points in time are the same. The test uses a panel of asset returns, with both the number of assets and the number of...

We study factor models augmented by observed covariates that have explanatory powers on the unknown factors. In financial factor models, the unknown factors can be reasonably well explained by a few observable proxies, such as the Fama-French factors. In diffusion index forecasts, identified...

In this paper, we estimate the time-varying COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model. Our measurement of the contact rate is constructed using data on actively infected, recovered and deceased cases. We propose a new trend filtering method that is a variant of the...