Game Model Analysis on Statistics Enforcement
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At present,the distortion of statistical data in China is so serious that it has caused the widespread concern of social public.This paper is mainly about the relationship between data offerers and data inspectors during the period of statistics enforcement by use of Game Theory and Repeated Games.It reveals the cause about the distortion of statistical data from the point of view about the statistics enforcement and gives some corresponding suggestions and policies also.Keywords:
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The paper analyzes the reasons of the distortion of statistical information and statistical department's inefficient cooperation with the sueveyed ones and puts forward the corresponding countermeasures.
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The gradual establishment and improvement of socialistic market economy advance higher requirements for statistical work.Whether the statistical data are exact or not impacts right the country's macroscopical management and scientific decision.At present,there are many problems existing in our country's statistical work.On the basis of analyzing the reasons,in order to ensure the reality and reliability of statistical information,must improve the statistical work.
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The article states the significance and countermeasures of the spersonnel statistic information work and proposes that the main problems of the personal statistic work are the bad information circulation,lack of the system's ability in dynamic analysis and predition.At last the article analyses the reason of it.On this basis,the article proposes the countermeasures such as strengthing the information construction of the spersonnel statistics,putting greater efforts in data analysis,and increasing the utilization value of spersonnel statistics.
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In this paper, we measure the treatment difference between administrative and criminal enforcement of environmental violations. Our aim is to make a comparison between similar offenses and evaluate how they would have been treated in both enforcement tracks. This paper can help to evaluate the compliance and welfare outcomes in a complementary criminal/administrative enforcement system with an enforcement system relying on criminal prosecution only. Given the discussions at European level on the most appropriate enforcement system and the different practices at national level, answering our research question is quite relevant. We apply statistical matching techniques on a unique dataset of environmental enforcement cases to control for sample selection bias and approximate the setup of a randomized experiment. We do the matching on case characteristics and estimate the average treatment effect for similar cases. Overall, we find that the marginal penalty is slightly lower in administrative enforcement compared to criminal enforcement, but that this difference would be widely overestimated without the matching procedure. Our methodology can be more generally applicable than the environmental law context that we use: it can help to control for caseload difference, which is a typical problem in law enforcement evaluation, and allow for correct causal inferences in a wide variety of law enforcement evaluation settings.
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Economic statistics are often taken as given facts, assumed to describe exactly, actual phenomena in society. Many economic series are published in various forms from preliminary, via revisions to definitive estimates. Preliminary series are issued for a number of central economic processes in order to allow for rapid, up-to-date signals. This dissertation focuses on qualitative aspects of available data, and effects of possible inaccuracy when data are used for economic modelling, analysis and planning. Four main questions are addressed: How to characterize quality of data for central economic time series? What effects may possible inaccuracies in data have when used in econometric modelling? What effects do inaccuracies and errors in data have when models are used for economic analysis and planning? Is it possible to specify a criterion for deciding the cost-effective quality of data to be produced as input for economic policy analysis? The various realizations of economic variables often show considerable systematic as well as stochastic discrepancies for the same quantity. Preliminary series are generally found to be of questionable quality, but still considerably better than simple trend forecasts. Compared with the situation in a few other industrialized countries, the variability of Swedish economic statistics is, though, not extraordinary. Illustrations of effects of using inaccurate data, especially of combining preliminary, revised and definitive observations in the same model, are presented. Such inconsistent combinations of various realizations are in actual fact found in many open sources. Inclusion of preliminary series tends to indicate stronger changes in the economy than when definite observations are used throughout. The study is concluded with a section on cost-benefit aspects of economic statistics, and a sketch model for appraising data of variable quality is proposed.
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The article gives a critique of parametric and nonparametric tests and processes of inferential statistics in forecasting customer flows in 7 selected small business enterprises in Uganda. Forecasting is one of the decision making tools in a business enterprise. This may include forecasting customer flows, volumes of sales and many others. This is a vital component of small businesses success. In the long run, what drives business success is the quality of decisions and their implementation. Decisions based on a foundation of knowledge and sound reasoning can lead the company into long-term prosperity; conversely, decisions made on the basis of flawed logic, emotionalism, or incomplete information can quickly put a business out of commission. In many instances, business decisions have been guided by parametric tests and processes and /or non-parametric tests and processes of inferential statistics, which have subsequently affected the futures of business differently. As we refer to population mean knowledge for hypothesis testing using parametric tests, we only refer to mediums for samples, for nonparametric tests. A parameter is a characteristic that describes a population. These may include μ (the Mean), δ2 (the variance) of a distribution. We commonly refer to the normal distribution, when it is symmetric, with the measures of central tendency (Mean = medium = mode). Usually these parameters are very useful, when testing hypotheses to enable researchers and decision makers infer about the population using samples. It would always be better to have knowledge of or/and about the population parameters, but more often than not, we find ourselves with very minimal, or no knowledge about the population parameters. To make the generalization about the population from the sample, statistical tests are used. In other words, we want to know if we have relationships, associations, or differences within our data and whether statistical significance exists. Inferential statistics help us make these determinations and allow us to generalize the results to a larger population. We employ parametric and nonparametric statistics to show basic inferential statistics by examining the associations among variables and tests of differences between groups. It is recommended by many scholars that business analysis uses parametric and nonparametric inferential statistics in making decisions about effects of independent variables on dependent variables. On the contrary, it is argued that the use of inferential statistics adds nothing to the complex and admittedly subjective, no statistical methods that are often employed in applied business decision making analysis. There are several attacks made on inferential statistics, perhaps with increasing frequency, by those who are not business analysts. These attackers are not in for the use of inferential statistics in research and business decision making, and commonly recommend the use of interval estimation or the method of confidence intervals. However, interval estimation is shown to be contrary to the fundamental assumption of business decision making analysis.
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At present,the community is still generally reflecting the poor quality of government statistics.One of the most important reasons for this is external intervention.In the paper,three game models of statistical data nongeneration process are established to confirme and simulate the power and approach of external intervention,and explain the tendency of statistics in Intervention.It analyzes the balance and parameters of game models,draws the corresponding conclusions and balanced view of the game.
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At present,the phenomenon about the distortion of statistical data in China is so serious that caused the widespread concern of social public.This paper is mainly about researching the conflict of interest between data offerers and data inspectors during the period of statistical enforcement by use of Game Theory and Repeated Games.It reveals the cause about the distortion of statistical data from the point of view about the statistical enforcement and gives some corresponding countermeasures also.
Statistical Analysis
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Phenomenon
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This paper analyzes the reasons of the distortion of statistical information and the harmfulness caused by it,emphasizes the importance of the quality of statistical information,and puts forward some countermeasures for improving the quality of statistical information.
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Statistical Analysis
Information Quality
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