Policy uncertainty and land transaction prices in China

Abstract

Economic policy uncertainty has prominent effects on investment and output. Using unique transaction-level data in China, this paper explores the impact of economic policy uncertainty on land transaction premiums in China. On average, a 1% increase in the policy uncertainty level reduces land transaction premiums by 3.907 percentage points. The impact of policy uncertainty is more profound for firms with tighter financial constraints and land located in cities with lower rent-to-price ratios. The influence of policy uncertainty becomes weaker after the anti-corruption campaign in China, especially in provinces scrutinised by the central inspection teams, implying that improvements in the political environment alleviates the impact of policy uncertainty.

Keywords:

• Policy uncertainty
• land transaction
• price premium
• anti-corruption campaign

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Pástor and Veronesi (2013) and Liu, Shu, and Wei (2017) provide evidence that asset prices are affected by policy uncertainty. Liu, Shu, and Wei (2017) use the event of the Bo Xilai scandal in 2012 in China as an exogenous shock to identify the impact of political uncertainty on asset prices. They find that the Bo scandal causes a significant drop in stock prices, especially for firms that are more politically sensitive.

2 As we will introduce in the next section, one unique feature of China’s land market is that land is owned by governments (or collectives), and individuals can only obtain the land use right for a limited period of time (i.e. 40 or 70 years). Therefore, instead of transferring the ownership of land, ‘transaction’ or ‘purchase’ in this paper refers to obtaining the use right for certain years.

3 This kind of conflict mainly undermine the relationship between the central government and the provincial-level local governments. However, as the provincial-level local governments are responsible for reallocating fiscal resources to lower-level cities, the fiscal pressure on provincial-level governments could be easily transferred to the city-level governments.

4 For example, we see evidence of the impact of EPU on risk premia (Pástor and Veronesi 2013), asset pricing (Brogaard and Detzel 2015), firm investment (Gulen and Ion 2016; Kim and Kung 2017), M&A (Nguyen and Phan 2017; Bonaime, Gulen, and Ion 2018), and bank credit growth (Bordo, Duca, and Koch 2016).

5 Available at: www.policyuncertainty.com.

6 We only introduce the idea and key steps in the construction of China’s EPU index, without digging into the technical detail of choosing text filters. The full set of text filters and the logic relationship between filters are available at: http://www.policyuncertainty.com/china_monthly.html.

7 In response to the global financial crisis in 2008, China implemented a massive four-trillion yuan (US$564 billion) stimulus package, planning to invest in infrastructure and social welfare by the end of 2010.

8 Lack of competition and corruption are believed to be the reasons for the 0% premiums (Cai, Henderson, and Zhang 2013).

9 The rent-to-price ratio data are collected from China Real Estate Association.

Additional information

Funding

Xiaoyang Li thanks the National Natural Science Foundation of China [Grant No. 72303197] for financial support. Mo Liang thanks the National Natural Science Foundation of China [Grant No. 71803188] for financial support. Jidong Yang thanks the Humanities and Social Sciences Research Project of the Ministry of Education [Grant No. 22YJA790076], and the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China [Grant No. 23XNA011] for financial support.