Dare You Sue the Tax Collector? An Empirical Study of Administrative Lawsuits Against Tax Agencies in China
Rutgers, The State University of New Jersey - Law School
April 24, 2013
Pacific Rim Law & Policy Journal, volume 23 no.1, January 2014
Though taxes are as certain as death, each year tens of thousands in the United States go to court to challenge their assessed tax liabilities, and many will succeed. By contrast, very few Chinese taxpayers litigate against tax agencies, and most of those who sue eventually settle, despite low formal litigation costs. Non-litigious culture does not fully explain the reluctance to sue, as courts in Taiwan (about 2% of the Chinese population) adjudicated five times more lawsuits against tax agencies. I contend that judicial bias favoring government officials, weak enforcement of judgments against the state, and agency retaliation explain the aversion to litigate disputes with tax agencies in China. But once the reluctance to sue is explained, the cases that go to trial, though small in number, constitute a more intriguing empirical puzzle. Why would anyone in China insist on judicial resolution of disputes with powerful tax agencies, given all the adverse conditions that have deterred hundreds of thousands from doing so? I provide a number of theoretical explanations, which are evaluated and substantiated with an empirical analysis of all tax-related administrative lawsuits that went to trial from 2009 to 2011 in Henan Province, one of the most populous provinces in China. In contrast to existing literatures on Chinese administrative litigation, this study is the first to include substantive analysis of an unbiased sample of cases. The findings contribute to the literatures on Chinese tax administration, administrative litigation in China, and extant trial selection theories.
Number of Pages in PDF File: 56
Keywords: tax administration, tax litigation, Chinese tax, administrative law, administrative litigation, Chinese law, trial selection theory, dispute resolutionAccepted Paper Series
Date posted: November 21, 2013 ; Last revised: January 20, 2015
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