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...

Inflation is one of the most important macroeconomic indicators which affects the economic condition of a nation. Therefore, it is necessary to maintain its stability in order that it will not lead to a negative impact and an economic vulnerability. The drastic change in the rate of inflation is...

We examine the accuracy of survey-based expectations of the Chilean exchange rate relative to the US dollar. Our out-of-sample analysis reveals that survey-based forecasts outperform the Driftless Random Walk (DRW) in terms of Mean Squared Prediction Error at several forecasting horizons. This...

We use Bayesian factor regression models to construct a financial conditions index (FCI) for the U.S. Within this context we develop Bayesian model averaging methods that allow the data to select which variables should be included in the FCI or not. We also examine the importance of different...

This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...

In this paper we introduce a “power booster factor” for out-of-sample tests of predictability. The relevant econometric environment is one in which the econometrician wants to compare the population Mean Squared Prediction Errors (MSPE) of two models: one big nesting model, and another...

In this study, we evaluate the effectiveness of three popular econometric models ARIMA, MIDAS, and VAR for forecasting quarterly GDP in Madagascar. Our analysis reveals that ARIMA provides the most accurate forecasts among the three models, indicating its superiority in predicting the...

There has been a deep-rooted view that economic rents are the main cause of high levels of economic inequality, but if economic rents are temporary, they may not be the cause. By employing numerical simulations, I show that even if economic rents are temporary, they can generate a high level of...

A general correcting formula of forecasting (as a framework for long-use and standardized forecasts) is proposed. The formula provides new forecasting resources and areas of application including economic forecasting.

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