explanatory variables (ARIMAX). The study also evaluates the forecasting performance of the alternative models. The results …, are able to pick up shocks, which are present in the data, and thus provide the best forecasting tool of office returns in … office market, such as the boom-bust cycle of the 1980s-90s, and thus are suitable for modelling and forecasting only part of …

In the wake of the recent international economic recession in 2008-2009, forecasting methods designed to anticipate …

This paper compares the out-of-sample forecasting accuracy of five classes of time series models for market shares of … employ a random-walk with drift (Naive), a univariate ARIMA, a near-VAR and a general BVAR. The out-of- sample forecasts are … also compared against forecasts generated from structural econometric market share models (SEM). Using four accuracy …

This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed … pseudo out-of-sample forecasting exercise with US real-time data yields that the mixed frequency VAR substantially improves … frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon …

-used probit approach, but the dynamics of regressors are endogenized using a VAR. The combined model is called a ‘ProbVAR’. At any … short-term interest rate, stock returns or corporate bond spreads. The forecasting performance is very good for the United …

Nigeria. Forecasts were produced using ARIMA, ARIMA with structural variables, VAR and VEC models. The performance of the …

notably with the pandemic. In a VAR, allowing the errors to have a distribution with fatter tails than the Gaussian one equips … the model to better deal with the COVID-19 shock. A standard Gaussian VAR can still be used for producing conditional …

estimate a non causal VAR with Brazilian typical data and compare its forecasts to a regular causal VAR, using the same data … determination of the effects fiscal policy, as the non causal VAR has shown substantially better predictive ability than the regular … causal VAR for that dataset. …

VAR operates with artificial series obtained from a DSGE model. The results indicate that the out-of-sample forecasting … quantitative macroeconomics. However, DSGE models were not considered as a forecasting tool until very recently. The objective of … this paper is twofold. First, we compare the forecasting ability of a canonical DSGE model for the Spanish economy with …