Effects of Real Estate Regulation Policy of Beijing Based on Discrete Dependent Variables Model

Abstract

This paper comprehensively analyzes the previous real estate regulation policies of Beijing from 2008 to 2017 and classifies them, then it expounds the regulation policies theoretically and uses a discrete dependent variable model to empirically test the probabilities of various policies to obtain the expected results. The research conclusions show that the probability of various types of real estate regulation policies achieving expected results is not the same. The probability of a tightened policy achieving expected results is higher than that of a loose policy; from the three dimensions of time, house prices, and volume, the probability of a purchasetype policy achieving the desired effect is the highest, and that of the payment-type policy is the second highest, but the stability is the highest, interest-rate policy is the lowest; moreover, whether real estate regulation policies can achieve the desired results is not related to the price of housing and volume. The above conclusions have provided the effects of various types of real estate regulation policies, analyze their causes, and provide suggestions for the further reform of real estate regulation policies.