Oil price collapse and challenges to economic transformation of Saudi Arabia: A time-series analysis

2019 ◽  
Vol 80 ◽  
pp. 12-19 ◽  
Author(s):  
Fredj Jawadi ◽  
Zied Ftiti
Author(s):  
Hülya Saygı ◽  
Aysun Kop ◽  
Hatice Tekoğul ◽  
Özgür Altan

The main aim of this study is to estimate the future of the aquaculture of Middle Eastern Countries for the year 2030 by time series analysis method. In addition, it is a classification and clustering based on fisheries production, import, export and consumption data with basic component analysis (PCA) and hierarchical cluster analysis (HCA) methods for Middle Eastern countries. FAO (United Nations Food and Agriculture Organization) used the statistics of fisheries products of the Middle East countries between 1950 and 2016. Time series, clustering and factor analysis were applied to these data. As a result of the time series analysis, the aquaculture production will end up in Kuwait, Libya and Syria if the current situation continues. Also, in other countries, production for 2030 is projected to be lowest for Jordan and the highest for Egypt. Accordingly, the total amount of aquaculture production in the Middle East countries is estimated to be 4.8 million tons in 2030. In the PCA, according to PC1; Cyprus, Iraq, Israel, Jordan, Kuwait, Lebanon, Saudi Arabia, Turkey and the United Arab Emirates and according to PC2; Algeria, Egypt, Iran, Oman, Tunisia and Yemen have been associated with high rates, respectively. According to the HCA; first cluster, Jordan, Lebanon, Kuwait, Cyprus, Iraq; 2nd cluster Israel, United Arab Emirates, Algeria, Tunisia, Oman and Yemen; 3rd cluster Saudi Arabia; 4. Cluster consists of Iran, Turkey and Egypt. According to the results of this study, the aquaculture of these countries should be examined in more detail. It is also recommended that countries implement the necessary regulations in fisheries policies.


Energy ◽  
2016 ◽  
Vol 109 ◽  
pp. 29-37 ◽  
Author(s):  
Luis A. Gil-Alana ◽  
Rangan Gupta ◽  
Olusanya E. Olubusoye ◽  
OlaOluwa S. Yaya

2009 ◽  
Vol 4 (5) ◽  
Author(s):  
Dimitrios I Gerogiorgis

This paper presents historical price data for two different crude oil types and examines the stationarity and inherent structure in oil price variation, applying many degrees of time resolution. Time Series Analysis results are then used to identify patterns and analyze the variation timescales. A specific goal of this study is to investigate and demonstrate the presence of fractal scaling. In particular, we postulate and prove that the mean size of the absolute values of price changes obeys a fractal scaling law (a power law) and can be expressed as a function of the analysis time interval (here, the latter is an independently varying parameter, ranging from a day up to a calendar year). The fractal structure of crude oil price variation is confirmed, the drift exponent is computed and the power scaling window of validity is depicted for both types, illustrating the interplay of both short- and long-term effects on the intrinsic structure of crude oil prices before and after 2008.


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