A Multiple and Partial Wavelet Analysis of the Oil Price,Inflation, Exchange Rate,and Economic Growth Nexus in Saudi Arabia

This article provides a fresh insight into the dynamic nexus between oil prices, the Saudi/US dollar exchange rate, inflation, and output growth rate in Saudi Arabia’ economy, using novel Morlet’ wavelet methods. Specifically, it implements various tools of methodology: the continuous wavelet power spectrum, the cross-wavelet power spectrum, the wavelet coherency, the multiple and the partial wavelet coherence to the annual sample period 1969–2014. Our results unveil that the relationships among the variables evolve through time and frequency. From the time-domain view, we show strong but non-homogenous linkages between the four variables. From the frequency-domain view, we uncover significant wavelet coherences and strong lead-lag relationships. From an economic view, the wavelet analysis shows that Saudi economy is still exposed to several global risk factors, which are mainly related to the oil market volatility, and the pegging of the local currency to the US dollar. Such risk factors strongly and negatively affect the real economic growth, exert more pressure on inflation, and substantially limit the freedom to pursue an independent monetary policy.     

New membership function for poverty measure

Fuzziness in a fuzzy set is determined by its membership function (m.f) which translates the reality of a problem. Accordingly, the shapes of membership functions (m.fs) are important for a particular problem such as poverty since they effect on a fuzzy inference system. Some authors have used to visualize the behaviour of poverty, different shapes like triangular, trapezoidal. In this paper, a specific (m.f), named modified logistic membership function better illustrating the complicated reality, is proposed to measure poverty. The modified logistic membership function is first formulated for several states of poverty and its flexibility in taking up vagueness in poverty is established by an analytical approach using aggregate operators in order to infer a logical conclusion measuring poverty. An application based on individual well-being data from Tunisian households in 2010 is presented to illustrate use of proposed concepts.     

Strength of co-movement between sector CDS indexes and relationship with major economic and financial variables over time and during investment horizons

The main purpose of this article is to analyse the co-movement in both time and frequency between financial sector CDS indexes and between these indexes and their main economic and financial control variables for the period 2004–2014. Empirically, we implement the wavelet-squared coherence methodology to analyse the co-movement through time, frequency and power. Our results unveil that the co-movement between the three financial sectors’ CDSs changes through time and investment horizons, stressing the importance of hedging portfolios in real time. Also, we uncover that the changes in co-movement to relatively higher frequencies coincide with the inception of the recent global financial crisis. This result is collaborated with the co-movement between each CDS index and other global risk factors, including crude oil prices, interest rates and equity market volatility. Finally, we compare the wavelet coherence results with those of the DCC-FIAPARCH model and find that the two different approaches provide quite similar conditional correlations over time. Our results are important for investors, debtors, creditors and other decision-makers which are interested in CDS spread co-movements at different frequencies or investment horizons. It would be useful for all market participants to resort to an appropriate frequency domain to have better understanding of the sector CDS interrelationship behaviour in this domain.     

A new fuzzy unidimensional poverty index from an information theory perspective

This article proposes to use an information theory approach to design a fuzzy unidimensional poverty index. In order to avoid the usual binary definition of poverty, a fuzzy set approach has been used. The total population is partitioned into three mutually exclusive groups around the poverty line. This builds on fuzzy set theory whereby the definition of the threshold of who is poor or non-poor is fuzzy. This article proposes a method using a membership function and a confidence interval of poverty line to identify to what extent households can be considered as poor or non-poor. According to this membership function, a relative entropy measure is adopted to assess an aggregation method of fuzzy individual poverty. An application using individual well-being data from Tunisian households is presented.     

Unidimensional and multidimensional fuzzy poverty measures: New approach

the analysis of deprivation is usually seen as a unidimensional condition. However, recently it is considered to be a multidimensional one. A useful tool for such analysis is to view deprivation as a degree providing a quantitative expression to its intensity for individuals. Such fuzzy conceptualisation has been widely adopted in poverty and deprivation research. This paper aims to further develop and refine this strand of research. First, we re-examine two aspects introduced by the use of fuzzy measures, as opposed to conventional poor/non-poor dichotomous measures, namely the choice of membership functions and the rules to manipulate, resulting fuzzy sets. Secondly, we propose fuzzy monetary and non-monetary measures with the membership functions of poor and non-poor. An application based on individual well-being data from Tunisian households in 1990 is presented to illustrate use of one of the proposed concept.     

Zakat and Poverty Alleviation in Tunisia Using the Fuzzy Approach

Zakat is one of the five pillars of Islam, which is compulsory to all the well-off Muslims, and it is given to the needy. It is used to fight poverty. This study examines Zakat’s impact on poverty in Tunisia. Using simulated data of individual well-being from Tunisian household survey in 2010, the potential importance of the Zakat to struggle with poverty is highlighted. Fuzzy Poverty Measurement is computed which shows that Zakat does reduce this measurement. The simulation results display a significant decrease of the poverty index of Tunisia’s seven regions, and poverty can be eradicated under cases West regions.

     

Does Zakat reduce poverty? Evidence from Tunisia using the Fuzzy Approach

Zakat is one of the five pillars of Islam; it is compulsory for all the well-off Muslims and is given to the needy. This study examines Zakat's impact on poverty in Tunisia. Using simulated data of individuals from Tunisian household surveys in 2010 and 2015, we measure the effect of Zakat to reduce poverty. This study uses the Fuzzy Approach to conclude that Zakat does reduce poverty. The simulation results display a significant decrease in the poverty index of Tunisia's seven regions.     

A New Approach to Unidimensional Poverty Analysis: Application to the Tunisian Case

Fuzzy conceptualization of privation has been a step closer to more realistic handling of poverty. However, fuzzy approaches to poverty are still grounded on parametric axioms. Moreover, construction of poverty lines within these approaches still relies on ad‐hoc methods. In this paper, we advance instead a fuzzy procedure based on the non‐parametric bootstrap method, allowing us to depict fuzzy unidimensional privation states with boundaries drawn spontaneously from data. Fuzzy non‐parametric measures of privation within each state as well as a collective fuzzy non‐parametric index of poverty are derived, along with their corresponding confidence intervals. The new approach is applied to the analysis of poverty in Tunisia in 2005.