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With the great development of economy in China, market economyis getting increasingly well formed, the demand for the statistic data issoaring,and the quality of statistics data becomes an extremely importantissue, at the same time the complex and uncertain statistic environmentput forward numerous challenges to us and places a higher requirementfor statistic authority. Meanwhile, these challenges also provide animportant opportunity for further data quality improvement. On April21of2002, China became a member of General Data DisseminationSystem(GDDS). Comparing to the world advanced level, the theoreticalresearch which guarantees the quality of data in China is urgentlydemanded.With the rapid development of economic, both private andpublic sectors pay more attention to macroeconomic data globally.Additionally, these data is the factor which can significantly affect theeconomic. In order to provide a reference to government sector, it isnecessary to establish an assessment system to evaluate the quality ofdata.In the article, we will introduce the principle of the Benford’s Law,then analysis the necessity and feasibility of Benford’s Law, providethe assessment procedures and matlab and R program manipulation.Next, evaluating the five major indexes from2001to2012of China’smacroeconomy (i.e. Gross Domestic Product, Total Investment in Fixed Assets, Consumer Price Index, the per capita disposable income of urbanresidents and total volume of foreign trade) by Benford Law;and then,drawing the conclusion from the analysis. According to the results drawnfrom the above calculation and the real condition, estimating the fiveindexes further and finding the potential reasons of the problems thatmay exist, as well as providing some correspondingsolutions. In the endof this paper, concluding the data quality of the five macroeconomicindexes, at the same time, pointing out the limitation of this method, asfor its practical application. Also, analyzing and summarizing thepracticability of this method in terms of the evaluation of quality ofstatistical data, in order to apply this method to the evaluation of thequality of data to the largest extent.
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