The ability of Google Trends data to forecast the number of new daily cases and deaths of COVID-19 is examined using a dataset of 158 countries. The analysis includes the computations of lag correlations between confirmed cases and Google data, Granger causality tests, and an out-of-sample...

We show that the empirical distribution of the roots of the vector auto-regression of order n fitted to T observations of a general stationary or non-stationary process, converges to the uniform distribution over the unit circle on the complex plane, when both T and n tend to infinity so that...

We show that the empirical distribution of the roots of the vector auto-regression of order n fitted to T observations of a general stationary or non-stationary process, converges to the uniform distribution over the unit circle on the complex plane, when both T and n tend to infinity so that...

Using multivariate cointegration tests for non-stationary data and vector error correction models, this paper examines the determinants of trade balance for Argentina over the last forty to fifty years. Our investigation confirms the existence of long-run relationships among trade balance, Real...

A univariate first order stochastic cycle can be represented as an element of a bivariate first order vector autoregressive process, or VAR(1), where the transition matrix is associated with a Givens rotation. From the geometrical viewpoint, the kernel of the cyclical dynamics is described by a...

In this paper, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Exponential Smoothing, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. We investigate whether combining forecasts from different methods and from...

Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag (ADL) model is chosen. The results show that a...

The present project is related in the measurement of the risk and the improvement of the processes of monetary species. The main objective is to offer a methodology in the tickets administration because understanding of history is a situation that becomes in an advantage on the opportunities at...

This paper takes a time series analysis approach to evaluate the directions of causality between tourism flows, on the one side, and museum and monument attendance, on the other. We consider Italy as a case study, and analyze monthly data over the period January 1996 to December 2007. All...