Economic Performance And Its Impact On Financial - amazonia.fiocruz.br

Badrihechmi gmail. For reliable results, the sample was divided into two subsamples, the Economic Performance And Its Impact On Financial : countries of the Gulf Cooperation Council GCCwhich have a high to cite : Badry hechmy, Financial income, and other countries. Deepening-Economic Performance On high frequencies, estimates show that the real and financial Economic Performance And Its Impact On Financial Nexus,An attempt to Study Granger- maintain causal relationships, showing a limit of the conventional Causality through Spectral Time Series method of causality assessment that sets in many cases a complete lack Analysis in MENA Countries, International Journal of Academic of connection between the proxies.

In the long term, finance dominates Research in Management and in some Gulf Cooperation Council GCC countries Plank For Leadership Center The we have the Business,vol:1,No:1,pp opposite effect in other countries. The main conclusion that one can reach is that the causal relationship between finance and growth is not linear, but it varies depending on the chosen time horizon. Introduction The studies on the relationship between finance and economic growth often use multivariate linear models such as vector autoregressive models VAR https://amazonia.fiocruz.br/scdp/essay/calculus-on-manifolds-amazon/analysis-of-the-book-the-birthmark.php and vector error correction models VECM models and operate the entire period.

However, it is known that the economic environment in a given country is not the same throughout the study period and the results that can be found may be wrong. Indeed; there are exogenous factors beside the endogenous factors that https://amazonia.fiocruz.br/scdp/essay/perception-checking-examples/correlation-between-money-and-real-interest-rate.php influence the finance and economic growth nexus, especially in developing countries.

Include, among others, political instability in these countries, their relationship with international bodies IMF and World Bankand climatic conditions and so on And to study this relationship, it makes more sense to decompose the study period into sub-periods according to the given economic context. In this regard, Granger and Lin, and Breitung Candelon reported that links between different phenomena are not linear, but vary depending on the selected frequency bands.

The decomposition of the study period into sub-periods has the inconvenience of reducing the number of observations that would question the robustness of the statistical tests based more often on asymptotic properties. Spectral analysis overcomes this disadvantage by measuring causality following different frequencies while keeping all observations of the study period in each of these frequencies. However, what about the choice of sub-periods?

For a long time classical decomposition of these movements into four components trend, seasonality, cyclical motion and random movement has used classical techniques of descriptive statistics. If determining the trend and seasonal movement is relatively simple, that of the cyclic movement is more complicated because it requires the subtraction of Impavt two previous movements.

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This led to seek more sophisticated methods to highlight the cyclical component representing in some cases the fundamental element that generates the data generating process. Early research in this area has used the harmonic analysis method.

This method consists in adjusting a periodic function to the observed series. But the nature of time series is generally characterized by imperfect periodicity which is always true for macroeconomic datawhich leads to a limit of application of applying this method. To solve this problem researchers are oriented towards spectral analysis, which is an extension of harmonic analysis that studies the time series in the frequency domain by replacing the time domain.

It consists to research solution from trigonometric functions that are composed of several sinusoids and each has its own frequency and therefore its own periodicity. This method has a better fit of the data as it is based on the sum of partial periodic functions. These are two ways of representation and study of stationary data that are not opposite, but complementary.

The transition from one representation to another is performed by Fourier transforms through the spectral representation theorem, which states that "any stationary in covariance process can be decomposed into a sum of sinusoidal oscillations whose amplitudes and offsets are independent random variables of a sine wave to the other".

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The rest of Psrformance article is organized as follows, Section 2 presents the literature review, section 3 focuses on the model and the estimation method, empirical validation shall be presented in Section 4 and Section 5 concludes. Literature revue The theory of the business cycle has developed in the last century by the famous work of Juglar, Schumpeter Schumpeter, one of the greatest economists of all time. Juglar stresses the need to find the causes of the recession in the phases of prosperity.

The economic cycle is a concept relatively complex and raises multiple and difficult issues. Detection of economic cycles is usually based on a decomposition of the time series into a trend, and cyclical components.]