This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates across districts in Iraq. Considering poverty rate as the dependent variable with eight explanatory variables. The analysis confirmed spatial dependence among regions, as indicated by the estimated values of the spatial correlation parameter (ρ) across different scenarios. It made clear that poverty rates are heavily influenced by spatial dependence and that failing to consider this could result in the loss of important information regarding the phenomenon and eventually impair the accuracy of statistical index estimation. This enhancement offers suggestions for methods of reducing poverty.
There are many applied Economic studies that have found positive nexus between financial development and poverty reduction in developing countries. Iraq has witnessed an increasing rate of poverty during the period 1980-2010 due to many internal and external factors such as wars, economic sanctions, inflation, a high rate of unemployment, and political and security instability. Therefore, the investigation about the solutions to reduce poverty becomes very necessary, and enhancing the financial development in Iraq is one of these options. This is due to that the financial development could reduce the poverty rates through two channels: the first is direct via the offering of the loans and other financial facilities to the poor, a
... Show MoreThe prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff
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The problem of poverty is one of the most important development challenges facing developing countries including Sudan for several decades. Although many efforts have been made to reduce poverty, however, its rates are increasing, and public policies adopted by the government in this regard remain elusive in achievinging its main objectives or making any significant progress. The purpose of the present study is to analyse poverty in Sudan by identifying its measurement, causes and the factors that have contributed to the increasing poverty rates over the past two decades. Also this study aims at investigating the interim poverty reduction strategy in Sudan as well as evaluates that strategy throug
... Show MoreThe proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
... Show MoreThis research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),
... Show MoreThe current study aims to identify soil pollutants from heavy metals The study utilized 40 topsoil (5 cm) samples, which adapted and divided into seven regions lies in Baghdad governorate, included (Al-Husainya,(Hs) Al-Doura (Do), Sharie Al-Matar (SM), Al-Waziria (Wz), Nharawan (Nh), Abu Ghraib (Abu) and Al-Mahmoodyia (Mh)). Spatial distribution maps of Nickel (Ni), Manganese (Mn), Lead (Pb) and Zinc (Zn) were created for Baghdad city using Geographic Information Systems (GIS). The concentrations of four heavy metals in the soil of different area of Baghdad were measured and observed using XRF instrument. The result found highest values of Pb and Zn at the middle of the Baghdad in (Wz
بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته
... Show MoreIn this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce
Paper Type: Review article.
another suggestion based on artificial neural networks.
The Fauqi field is located about 50Km North-East Amara town in Missan providence in Iraq. Fauqi field has 1,640 MMbbl STOIIP, which lies partly in Iran. Oil is produced from both Mishrif and Asmari zones. Geologically, the Fauqi anticline straddles the Iraqi/Iranian border and is most probably segmented by several faults. There are several reasons leading to drilling horizontal wells rather than vertical wells. The most important parameter is increasing oil recovery, particularly from thin or tight reservoir permeability. The Fauqi oil field is regarded as a giant field with approximately more than 1 billion barrels of proven reserves, but it has recently experienced low production rate problems in many of its existing wells. This study
... Show MoreIraq within the ranks of the fledgling communities characterized by a broad base of the population pyramid, because they pose the age group (under 15 years) of a large proportion of the community, as it exceeded the proportion (40%) during the years of research extended (1986-2010) Despite the relative decline in the rates fertility during that period, but the proportion of young people remained high, especially for groups of at least five years, amounting to about 14% in 2012, a little more than the proportion of what constitutes age group (5-9 above) years, where it was (13%) and this naturally predicts continuing population increases in coming decades, due to the entry of those numbers of individuals in the reproductive stage,
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