جدید مالیاتی ادارے اور تقسیم زکوۃ

One of the main features of the property that Islam does not allow the wealth is concentrated around few peoples; any group or class of society, but according to Islamic point of view money should be in circulation so that poor class of the society could enjoy this blessing from Almighty Allah. Zakat Distribution System is a system of fair procedure for this world by Islam; if it is implemented with true spirit of Islam it can end poverty from the society. Islam obligate rich people of the society to distribute Zakat from their wealth amongst poor people however Islam has ordered not to receiver Zakat more than their needs so that it could be distribute to other poor people of the society. Zakat is an important and has significance in Islam. Islamic law imposed the duty on the Islamic government to collect Zakat from the rich and distribute it to the poor of the society, which caused not only undermined the dignity of the poor. Islamic law imposed the duty on Islamic government to take steps of receiving Zakat. If the government imposed the proper procedures in current banks and other financial institutions to receive Zakat from the rich people of the society and distribute it amongst the poor of the society than it could help to get rid of poverty from the society and it also help for the stability of the economy of any Country?

Some Contributions to Scrambled Randomized Response Technique Using Auxiliary Variable for Parameters in Finite Population

In this dissertation, some generalized scrambled randomized response models for sensitive characteristics have been proposed using two scrambling variables. Similarly, some regression, ratio, exponential, regression-cum-exponential, regression-cum-ratio and ratio in exponential estimators have been proposed to estimate population characteristics for sensitive surveys using auxiliary information. The estimators are proposed for simple random sampling design for both single-phase sampling and two-phase sampling. In Chapter 1, the discussion on sensitive surveys has been made. The techniques to collect information on sensitive characteristics such as randomized response and scrambled randomized response techniques have been introduced into more detail. Further, the use of auxiliary information and two-phase sampling have been illustrated. In Chapter 2, the review of literature regarding the use of auxiliary information in single-phase sampling and two-phase sampling have been discussed with the estimators developed by different statisticians for both sensitive and non-sensitive surveys. Various development on randomized response models in literature have also been presented. The major work of this dissertation start from Chapter 3. In this chapter, four generalized scrambled randomized response models have been proposed combining additive and multiplicative models. These four generalized models have been proposed using two scrambling variables with known distribution. The expressions of the mean, variance, covariance and correlation have been derived for each of the proposed models. Additionally, the privacy measure have been derived for some existing models presented in literature review and the proposed models. The privacy protection comparisons between existing models and proposed models have also been discussed. In Chapter 4, the generalized exponential-type estimators have been constructed using two auxiliary variables to estimate population mean of the sensitive variable. The bias and mean square error have been derived for each proposed estimator. To examine the performance of the proposed generalized estimators, the simulation study have been performed under the observed response using additive and proposed scrambled randomized response models. In Chapter 5, the regression, ratio, regression-cum-ratio, regression-cum exponential and ratio in exponential-type estimators have been proposed under two-phase sampling to estimator population mean of sensitive study variable. The estimators have been proposed for three cases of two-phase sampling such as full-information-case, partial-information-case and no-information-case. The x expressions of the bias and mean square error have been derived for each proposed estimator. Additionally, the simulation study has been conducted to examine the performance of estimator using additive and proposed models. To estimate the population variance of sensitive study variable, some exponential estimators have been proposed in Chapter 6. These estimators have been presented for both single-phase and two-phase sampling. In this chapter, the additive model is considered to estimate population variance. The expressions of the bias and mean square error have been derived. The simulation study have also been presented for both single-phase and two phase sampling.