Abstract
To ensure sustainable tax revenue growth, decision variables of tax revenue were researched in this paper by using mixed nonparametric kernel method based on a dataset of tax revenue containing both continuous and discrete data in Hangzhou; compared to parameters regression method, it can automatically reduce the dimension of model and possess high model fitting precision. The mean square error of mixed nonparametric kernel method reduces by 49.3 % after deleting 12 irrelevant variables, while it increases by line regression method and stepwise regression. In addition, it is found that the variables of real-estate investment are not a decision variable of tax revenue in nonparametric methods, which is different from stepwise regression. This conclusion provides the negative evidence of experience in tax revenues about whether it will produce decisive influence to tax revenues to control and regulate the real-estate investment.
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