To limit the dramatic growth of U.S. health care expenditures, some states have mandated that medical providers publicly report their charge prices. Our study evaluates the heterogeneous effects of this price transparency policy. We use a comprehensive database that covers more than 2,000...

Since testing for COVID-19 infections is not at all randomized over the general population, most epidemiological model forecasts of deaths are subject to `selection bias.' This paper updates and supplements Vinod and Theiss (2020), where the bias correction using generalized linear models (GLM)...

In this paper we investigate the dynamic features of house prices in London. Using a generalized smooth transition model (GSTAR) we show that dynamic symmetry in price cycles in the London housing market is strongly rejected. We also show that the GSTAR model is able to replicate the features of...

This paper introduces a novel approach for dealing with the 'curse of dimensionality' in the case of large linear dynamic systems. Restrictions on the coefficients of an unrestricted VAR are proposed that are binding only in a limit as the number of endogenous variables tends to infinity. It is...

To limit the dramatic growth of U.S. health care expenditures, some states have mandated that medical providers publicly report their charge prices. Our study evaluates the heterogeneous effects of this price transparency policy. We use a comprehensive database that covers more than 2,000...

The authors model COVID infections and COVID deaths, both reported and implied, for the 50 U.S. states as well as the District of Columbia, and separately for a sample of 33 countries, as a function of pre-existing circumstances that citizens have no ability to control over the short term. These...

We propose a new generic method ROPES (Regularized Optimization for Prediction and Estimation with Sparse data) for decomposing, smoothing and forecasting two-dimensional sparse data. In some ways, ROPES is similar to Ridge Regression, the LASSO, Principal Component Analysis (PCA) and...

This paper introduces the concepts of time-specific weak and strong cross section dependence. A double-indexed process is said to be cross sectionally weakly dependent at a given point in time, t, if its weighted average along the cross section dimension (N) converges to its expectation in...

We capitalise on an opportunity in the UK Household Longitudinal Study, which asks respondents the same SAH question with identical wording two times. This is done once with a self-completion and once with an open interview mode within the same household interview over four waves. We estimate...

This paper introduces a novel approach for dealing with the 'curse of dimensionality' in the case of large linear dynamic systems. Restrictions on the coefficients of an unrestricted VAR are proposed that are binding only in a limit as the number of endogenous variables tends to infinity. It is...