This research defines how economists apply Gross Domestic Product to observe the national income in a country. This research will also identify the problems related with GDP to observe the national wealth and how can these issues be controlled. This research will also describe how a country can...

This paper explains the early U.S. Department of Commerce estimates of national income and product during the 1930s and 1940s, focusing on how both economic theory and the needs of policymakers influenced the methods and concepts used. The paper explores the debate between Simon Kuznets, author...

In the case of a flat prior, a conventional wisdom is that Bayesian inference may not be very different from classical inference, as the likelihood dominates the posterior density. This paper shows that there are cases in which this conventional wisdom does not apply. An ARMA model of real GDP...

The forecast plays an important role in the planning, the decision-making and control in any domain of activity, including the sportive phenomenon of the soccer. The experience has shown that the extrapolative or not casual models (univariate models), that use only the information of its past...

This study aims to introduce an ideal model for forecasting crude oil price volatility. For this purpose, the ‘predictability’ hypothesis was tested using the variance ratio test, BDS test and the chaos analysis. Structural analyses were also carried out to identify possible nonlinear...

We study the behavior of the Real Effective Exchange Rate (REER) of the dirham against the European currencies (the EU15), over the period 1960–2000. We measure the volatility using standard deviation, and the misalignments as the difference between the actual REER and the equilibrium REER...

This study attempts to introduce an appropri¬¬ate model for modeling and forecasting Iran’s crude oil price volatility. Therefore, this hypothesis will be tested about whether long memory feature matters in forecasting the price of this commodity. For this purpose, using the Iran’s weekly...

The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model) and a regressive (Auto Regressive Fractionally Integrated Moving Average model which...

In this paper, we investigate the value-at-risk predictions of four major precious metals (gold, silver, platinum, and palladium) with long memory volatility models, namely FIGARCH, FIAPARCH and HYGARCH, under normal and student-t innovations’ distributions. For these analyses, we consider...

This paper considers the application of long memory processes to describe inflation with seasonal behaviour. We use three different long memory models taking into account the seasonal pattern in the data. Namely, the ARFIMA model with deterministic seasonality, the ARFISMA model, and the...