Tax Policy and Toxic Housing Bubbles in China
King Yoong Lim () and
Pengfei Jia ()
NBS Discussion Papers in Economics from Economics, Nottingham Business School, Nottingham Trent University
This paper explores the effects of a government tax policy in a growth model with economic transition and toxic housing bubbles applied to China. Such a policy combines taxing entrepreneurs with a one-time redistribution to workers in the same period. Under the tax policy, we find that the welfare improvement for workers is non-monotonic. In particular, there exists an optimal tax at which social welfare is maximized. Moreover, we consider the welfare effects of setting the tax at its optimum. We show that the tax policy can be welfare-enhancing, compare to the case without active policies. The optimal tax may also yield a higher level of welfare than the case even without housing bubbles. Finally, we calibrate the model to China. Our quantitative results show that the optimal tax rate is about 23 percent, and social welfare is signicantly improved with such a tax policy.
Keywords: China; Economic Transition; Housing Bubbles; Welfare. (search for similar items in EconPapers)
JEL-codes: O18 P31 R21 R28 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cna, nep-env, nep-tra and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://www.ntu.ac.uk/__data/assets/pdf_file/0035/6 ... bubbles-in-china.pdf First version, 2018 (application/pdf)
Working Paper: Tax Policy and Toxic Housing Bubbles in China (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:nbs:wpaper:2018/03
Access Statistics for this paper
More papers in NBS Discussion Papers in Economics from Economics, Nottingham Business School, Nottingham Trent University
Bibliographic data for series maintained by King Lim ().