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.
This paper deals to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th
... Show MoreThe phenomenon of poverty is one of the most important phenomena facing the world at large. Despite the tremendous technological progress witnessed by mankind and despite the unprecedented high levels of world economic production, poverty remains the greatest challenge facing the world. Statistics and studies have shown that poverty is caused by several problems: (health, social, economic, educational, etc.) These problems are obstacles to the ability to obtain employment opportunities, which leads in the beginning to the growth phenomenon of unemployment, and ultimately to the growth of poverty.
The results of a range of research in the field of psychology have confirmed that children from poor homes suffer from a high level of
... Show MoreThe use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode
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The issues related to foreign trade is a broad field for discussions and captures the interest of economists for their contribution to the process of economic development in the economies of the countries, especially developing ones. The imports of goods and services in foreign trade constitute an important part of the local by which the economy gets goods and services that the economy cannot produce because of the incompetent base of production. Further, the demand function of imports occupied a good deal of the attention of researchers in the field of international economics for which agricultural imports constitute an important part. The reason for the interest in the subject is due to its im
... Show MoreA large number of researchers had attempted to identify the pattern of the functional relationship between fertility from a side and economic and social characteristics of the population from another, with the strength of effect of each. So, this research aims to monitor and analyze changes in the level of fertility temporally and spatially in recent decades, in addition to estimating fertility levels in Iraq for the period (1977-2011) and then make forecasting to the level of fertility in Iraq at the national level (except for the Kurdistan region), and for the period of (2012-2031). To achieve this goal has been the use of the Lee-Carter model to estimate fertility rates and predictable as well. As this is the form often has been familiar
... Show MoreThe current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances. From the diversity of Big Data variables comes many challenges that can be interesting to the researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter
... Show MoreThe problem of poverty and deprivation constitute a humanitarian tragedy and its continuation may threaten the political achievements reached by the State. Iraq, in particular, and although he is one of the very rich countries due to availability of huge economic wealth, poverty indicators are still high. In addition, the main factor in the decline in the standard of living due to the weakness of the government's performance in the delivery of public services of water, electricity and sanitation. Thus, the guide for human development has been addressed which express the achievements that the state can be achieved both on a physical level or on the human level, so in order to put appropriate strategies and policies aimed at elimin
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In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach
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