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...

The Department of Finance employs extensively a large macroeconomic model of the Canadian economy -- the QFS model(Quarterly Forecasting and Simulation Model) -- for economic and fiscal forecasting and simulation exercises. As with any large macroeconomic model, and particularly one that plays a...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

The aim of the paper is to contribute to the body of knowledge in the area of forecasting using Autoregressive Integrated Moving Average (ARIMA) modelling for liquefied petroleum gas (LPG) for Ghana using monthly data for the period 2000-2011. The ARIMA (1, 1, 1) model was identified as suitable...

In our study, we model both steady state and short-run dynamics of the important aspects of the national economy using quarterly data for the period 1999Q1-2016Q2. We explicitly model government, money market and external sector, but omit household sector, labor market, wage dynamics and volume...

Parallel calculations on modern multiprocessing technics open new opportunities in application of mathematical models for research ekonomy of region. Use of normative models was limited to complexity of their identification due to a lot of unknown parameters. In work the technique of...

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...

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...

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...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...