Land Finance, Real Estate Market, and Local Government Debt Risk: Evidence from China
Round 1
Reviewer 1 Report
Please refer to the attached document. I urge the authors to consider every comment and incorporate the proposed discussions and analyses in detail to enhance the scholarly quality of their work.
Comments for author File: 
Comments.pdf
Only minor edits are required.
Author Response
Point 1: Fixed-effects model. I am raising this issue first because the entire analysis hinges upon the correct understanding of the reduced-form model estimated by the authors. In subsection 3.2, page 6, the authors say that“ is the year and city fixed effect.” It is important to understand the differences between (1) a model that includes both year-fixed effects and city-fixed effects and (2) a model that includes year and city fixed effects. In (1), city fixed effects () and year fixed effects () are included. In (2), fixed effects indicating all possible combinations of city and year (i.e., pairs of ()) are included. Based on the text and notation (with indexed by combinations of ()), the authors seem to be referring to (2). However, a model with fixed effects indicating combinations of () cannot be estimated in this case because the dataset is a panel of 224 cities and 10 years (yielding 2240 observations) where each combination of city-year appears just once. The inclusion of city-year fixed effects would make the OLS matrix of covariates full-ranked (not invertible). Please clarify what fixed-effect estimation is considered and use a consistent notation. If the model includes both city-fixed effects and year-fixed effects, please consider the notation .
Response 1: Thank you for pointing out our unclear expressions of fixed effects. In this study, we controlled for both year-fixed effects and city-fixed effects to avoid some confounding variables. In the revised version, we have modified to in the models. The revisions are marked in red in the revised manuscript. Please see lines 252-263.
Point 2: Confounding variables. China’s real estate boom is particularly unique in that it relates to specific economic features of China’s development model (see Liu and Xiong,2018; Brunnermeier et al.,2022). Moreover, it is important to note that China’s real estate bubble possibly coincided with important global economic developments, including monetary policy expansions by the US Fed (see Cortes et al.,2022), increases in government deficits that undermined the strength of government guarantees (refer to Silva,2021; Dantas et al.,2023), and the rise in policy uncertainty and populism in developed economies (see Born et al.,2019; Campello et al.,2022). To account for these confounding macroeconomic trends, the authors should (1) discuss how different channels should affect the variables of interest and (2) perform a robustness test to estimate the effect of omitted correlated variables. From a practical standpoint, I encourage the authors to add a section just before the conclusion (which then would become section 7), where the authors discuss the following economic channels and perform a simple robustness test.
Monetary expansions. In response to the subprime and Eurozone crises, several central banks of developed nations engaged in massive rounds of quantitative easing (refer to Figure 1 of Cortes et al.,2022). These policies distort international capital flows and reduce the cost of capital in emerging market economies such as China, leading to credit booms (Baron and Xiong,2017) and asset price bubbles that cannot be detected by traditional risk management techniques (Jarrow and Silva,2015). In turn, quantitative easing policies not only may feed real estate bubbles but also affect the price of Chinese government bonds.
Deficits and fiscal multipliers. During financial crises, implicit government guarantees are critically relevant to ensure the stability of the banking sector and capital availability for real estate financing. Because the sample period comprises the subprime and Eurozone crises, increasing deficits and debt-to-GDP ratios due to fiscal stimuli may have weakened implicit guarantees and fiscal multipliers (refer to Silva,2021; Dantas et al.,2023). Although these crises have not affected the Chinese market directly, there are several indirect effects given the interconnectedness of the global banking sector (Schnabl,2012).
Geopolitical uncertainty. The sample period in question is characterized by rising policy uncertainty due to events such as the Brexit referendum and the 2016 US election (Wagner et al.,2018; Born et al.,2019; Campello et al.,2022). Such events may have helped generate abnormal capital flows to China given its relative political stability
Response 2: Thank you for you valuable comments. In this study, we focused on the relationship between China's real estate market risk and local government debt risk, and highlighted the role of land finance therein. The macroeconomic trends you raised provide us very valuable insights to improve our manuscript. According to your suggestions, we added section 6 (Further discussion: considering macroeconomic trends, lines 490-554, pages 14-16) to discuss the potential impacts of macroeconomic trends on the relationship between China's real estate market risk and local government debt risk.
First, we chose 1) broad money supply (M2) to reflect China's monetary expansion under the fluctuating external economic environment, 2) fiscal pressure as the proxy variable of fiscal deficit, 3) the 2016 US election as a proxy variable to examine the impact of geopolitical uncertainty.
Second, we conducted the interactive regression and find that 1) monetary expansions would exacerbate the positive impact of real estate market on local government debt, 2) fiscal pressure negatively moderate the impact of the real estate market on local government debt, 3) geopolitical uncertainty would restrain debt issuance and weaken the dependence of local government debt on real estate.
Third, we used grouping regression to verify the robustness of the above findings.
Point 3: Robustness test. The DID estimation of section 5 (results presented in Table 6) is important to overcome endogeneity concerns. I encourage the authors to estimate parametric bounds to omitted correlated variables following the methodology proposed by Oster (2019) and exemplified in Dantas et al. (2023) (see Tables 11 and 12 of Dantas et al.,2023).
Estimate their DID model without fixed effects and collect the coefficient estimates of the DID term. Call these coefficients and the R-squared of the regression .
Estimate their DID model including both city-fixed effects and year-fixed effects. Call these coefficients and the R-squared of the regression .
Estimate the Oster (2019) parametric bounds for the coefficients of the DID term following the expression of Tables 11 and 12 of Dantas et al.(2023).
Response 3: Thank you for your valuable comments. According to your suggestions, we further estimated parametric bounds to omitted correlated variables following the methodology proposed by Oster (2019) and Dantas et al.(2023). We also added a Table (Table 7 Bounds for robustness to proportional selection on unobservables, pages 12-13) to report the regression results (lines 473-490) which suggest that the DID model in this study is robust by considering the omitted correlated variables.
Point 4: Sample period justification. The authors explain that they restrict the sample period to 2010–2019 because of data availability. The authors can justify stopping the sample in 2019 to avoid overlapping with the COVID–19 pandemic, which had major effects on global capital markets and global policy responses (Cortes et al.,2022).
Response 4: Thank you for your valuable comments. According to your suggestions, we have added some explanations for the sample period. First, there is a significant amount of missing data on Chengtou bonds after 2020 which might bias the empirical results. Second, we stop the sample in 2019 to avoid overlapping with the COVID–19 pandemic, which had major effects on global capital markets and global policy responses. The revisions are marked in red. Please see the lines 233-236 on page 5.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The relationship between land finance and local debt crisis has always been a hot topic in politics and academia. Based on the open data system, the author explores the relationship between land transfer, real estate market development and local debt. The topic selection is of certain significance, but the research design still has some shortcomings. Some suggestions are for reference:
(1) The definition of core concepts. Is real estate development and local debt crisis related to land transfer or land expropriation? I think the author may have confused the concepts of land transfer and land expropriation. Land transfer generally does not involve changing the nature of land (from cultivated land to construction land), but land expropriation does. If you follow this logic, then the author's writing logic of the whole paper is problematic.
(2) Compared with the existing research, the key scientific problems and marginal contributions to be solved in this study are not clear. Why is land circulation once used as a regulating variable and then as an intermediary variable? What is the mechanism of action between the core variables? At the same time, the author also lacks rigorous theoretical analysis and puts forward theoretical analysis framework and research hypothesis.
(3) The analysis can go further. As I said before, the author has chosen a very meaningful topic to study, but readers may want to know what kind of cities will rely more on this model and how to specifically prevent the corresponding risks. In other words, the author may need to conduct some in-depth heterogeneity analysis based on the size or development level of the city.
Minor editing of English language required.
Author Response
Point 1: The definition of core concepts. Is real estate development and local debt crisis related to land transfer or land expropriation? I think the author may have confused the concepts of land transfer and land expropriation. Land transfer generally does not involve changing the nature of land (from cultivated land to construction land), but land expropriation does. If you follow this logic, then the author's writing logic of the whole paper is problematic.
Response 1: we are sorry for this confusion. In the revised version, we have changed land transfer to land finance, which might better reflect the purpose of our study.
In this study, land finance refers to local government obtain fiscal revenue by selling land use rights. China's unique land finance began after the tax sharing reform in 1994. Since local governments hold a monopoly supply right in the primary land market, selling land use rights has emerged as a significant avenue for local governments to directly generate fiscal revenue. In the past decades, more than 40% of local government fiscal revenue is derived from the sale of land use rights.
In the revised version, we have made several modifications. First, in Section 1 (Introduction, lines 68-79, page 2) and Section 2 (Institutional background and literature review, lines 177-226, page 5), we briefly introduced the background of land finance. Second, in Section 3 (Methodology, lines 234-235, page 5), we pointed out that Land finance is measured by the city's land income through selling land use right for the given year.
Point 2: Compared with the existing research, the key scientific problems and marginal contributions to be solved in this study are not clear. Why is land circulation once used as a regulating variable and then as an intermediary variable? What is the mechanism of action between the core variables? At the same time, the author also lacks rigorous theoretical analysis and puts forward theoretical analysis framework and research hypothesis.
Response 2: Thank you for your valuable comments. In the revised version, we clarified the key scientific problems and marginal contributions.
First, although existing studies have proven the importance of land in China and high-lighted the effect of land finance on local economic development, real estate bubble and official promotion, the investigations of the role of land finance in the real estate market affecting local government debt are still rare. Especially in the past two years, the simultaneous increase in China's real estate market risk and local government debt risk triggers our rethinking of land finance. In section 1 (Introduction, lines80-89, page 2; 108-113, page 3), Section 7 (Conclusions, lines 585-590, page 17), we rewrite the marginal contributions of this study.
Second, local government could obtain fiscal revenue by selling land use rights, which means that land serves as a source of local government’ direct fiscal revenue. In addition, land is also a high-quality collateral which has leverage effect when local government issuing debts. Therefore, we suggest that land finance may further amplify the debt issuance of local governments during a booming real estate market. This means that land finance not only serves as the channel through which local government debt expansion during the real estate boom, but also act as an amplifier of real estate market boom promotes local government debt issuance. Therefore, we construct the moderated mediation model to conduct the empirical study. In Section 1 (Introduction, lines 68-79, page 2) and Section 2 (Institutional background and literature review, lines 178-226, page 5), we modified the potential mechanism of land finance, real estate market and local government debt risk.
Fourth, we rewrite Section 2.2 (Land finance, real estate market and local government debt risk, lines 178-220, pages 5-6). We proposed several hypotheses based on theoretical analysis, including: 1) The boom of real estate market has positive effect on local government debt, 2) Land finance serves as the channel through which local government debt expansion during the real estate boom, 3) Land finance also acts as an amplifier of real estate market boom promotes local government debt issuance. Since the cooling down real estate market result in the decrease of land value, local governments may face the challenges in repaying their debts. We also proposed an additional hypothesis H4: the government's debt repayment risk would increase given a downturn real estate market. If this assumption holds true, it can not only serve as a robustness test for the above hypotheses, but also explain the simultaneous increase in the current downturn of China's real estate market and the rising risks associated with local government debt repayment.
Point 3: The analysis can go further. As I said before, the author has chosen a very meaningful topic to study, but readers may want to know what kind of cities will rely more on this model and how to specifically prevent the corresponding risks. In other words, the author may need to conduct some in-depth heterogeneity analysis based on the size or development level of the city.
Response 3: Thank you for your valuable comments. According to your suggestions, we modified Section 4.3 (Heterogeneity test, lines 346-358, lines 362-372). We conducted heterogeneity test from two aspects. First, we divided the sample into five categories according to city economic development level, namely, first-tier, second-tier, third-tier, fourth-tier and fifth-tier cities. The grouping criteria is from First Financial Weekly in China and first-tier cities are highly developed. Second, since the issuance of Chengtou bonds is related to the government’s income level, we divided the sample into two groups according to the urban general public budgeting income. We defined cities with higher than median urban general public budgeting revenue as high-income group, and vice versa. In general, cities with higher general public budgeting revenue are economic developed, the regressions of the above two aspects can therefore mutually verify the robustness of heterogeneity.
Based on the heterogeneity test, we emphasized the importance of differentiated regulations based on the type of cities. For example, cities with higher economic development and lower fiscal pressure generally have flourishing housing market and high land values. The central government should strengthen the supervision of these cities and maintain the stability of regulatory policies to the interaction between real estate market risks and government debt risks. The revisions are marked in red in Section 7 (Conclusions, lines 585-590, page 17)
Moreover, according to other reviewer’s suggestions, we added section 6 (Further discussion: considering macroeconomic trends, lines 490-545, pages 14-16) before the conclusion to discuss the potential impacts of macroeconomic trends on the relationship between China's real estate market risk and local government debt risk.
Author Response File: Author Response.docx
Reviewer 3 Report
The topic of the paper is actual and exciting. It examines the role of land transfer in the relationship between the real estate market and local debt risk. The research examined 224 cities and used the so-called Chengtou bonds to measure local government debt. The novelty of the research is that it explores the impact of the real estate market on local government debt from the perspective of land transfer and highlights the interconnected influence between the significant risk factors.
For me, the most important strengths are: Chengtou bonds and the Chinese regulations are so unique that it’s interesting to analyse its operation, advantages, and possible disadvantages. As the authors have mentioned there are a lot of data available but there aren’t many comprehensive analyses about the situation. Several different methods were used like Robustness, Heterogeneity or Endogeneity test. The built model is appropriate. The paper has a new approach as well as it and highlights the interconnected influence of the significant risk factors as well.
The only weakness or so to say thing to correct in the paper is in Chapters 1. and 2. It’s a disturbing repetition that the authors introduce the Chinese regulation and Chengtou bond several times and highlights that the government's assessment of local officials mainly depends on GDP and how this fact influences local decisions.
The language of the paper is appropriate and easy to understand but I’m not in the position to evaluate it professionally as I’m only an English language user at an upper level and not a language teacher or reviewer.
There aren’t any unnecessary tables in the paper, all of them help the understanding.
Author Response
Point 1: The topic of the paper is actual and exciting. It examines the role of land transfer in the relationship between the real estate market and local debt risk. The research examined 224 cities and used the so-called Chengtou bonds to measure local government debt. The novelty of the research is that it explores the impact of the real estate market on local government debt from the perspective of land transfer and highlights the interconnected influence between the significant risk factors.
For me, the most important strengths are: Chengtou bonds and the Chinese regulations are so unique that it’s interesting to analyse its operation, advantages, and possible disadvantages. As the authors have mentioned there are a lot of data available but there aren’t many comprehensive analyses about the situation. Several different methods were used like Robustness, Heterogeneity or Endogeneity test. The built model is appropriate. The paper has a new approach as well as it and highlights the interconnected influence of the significant risk factors as well.
The only weakness or so to say thing to correct in the paper is in Chapters 1. and 2. It’s a disturbing repetition that the authors introduce the Chinese regulation and Chengtou bond several times and highlights that the government's assessment of local officials mainly depends on GDP and how this fact influences local decisions.
The language of the paper is appropriate and easy to understand but I’m not in the position to evaluate it professionally as I’m only an English language user at an upper level and not a language teacher or reviewer.
There aren’t any unnecessary tables in the paper, all of them help the understanding.
Response 1: Thank you for your valuable comments. According to your and other reviewers’ suggestions, we rewrite Section 1 (Introduction) and Section 2 (Institutional background and literature review). In section 1, we briefly introduced the simultaneous increase in China's real estate market risk and local government debt risk and discuss why we focus on the role of land finance in the relationship between the real estate market and local debt risk. In section 2, we discussed the potential mechanism of land finance, real estate market and local government debt risk and then propose several hypotheses based on theoretical analysis. The revisions are marked in red. Please see the lines 65-76 on page 5, lines 175-221 on pages 4-5.
Author Response File: Author Response.docx
Round 2
Reviewer 2 Report
The authors have addressed well with my comments and it is suggested to be accepted.
Author Response
Response to Editor:
Comments: the literary review is very poor. It should be enhanced. I suggest another round of major. my suggestion is related only to literary review. It's almost absent. The authors should contexualize their study demonstrating knowledge of the scientific context.
Response: Thank you for your valuable comments. According to your suggestions, we have revised Section 2 (Institutional background and literature review) to make the scientific context of this study clearer.
First, in Section 2.1 (Local government debt and Chengtou bonds), we added some literature to introduce the background of local government debt and Chengtou bonds in China.
Second, in Section 2.2 (Land finance, real estate market and local government debt risk), we reorganized the research related to the topic of this paper and outlined the main findings and concerns of the existing studies. We also added some literature on land finance and local government debt, and introduced that land serves not only as a source of local government’ direct fiscal revenue but also as high quality collateral. The revised version could better support the hypotheses raised in this study.
The revisions are marked in red. Please see the lines 128-222 on pages 3-5.
Response to reviewer:
I) Please check that all references are relevant to the contents of the manuscript.
Response: We have carefully revised our manuscript and have checked that all references are relevant to the contents of the manuscript. We also modified the format of all references to meet the requirement of your journal. We hope the revised version meet your approval. Please see the lines 621-673.
(II) Any revisions to the manuscript should be highlighted, such that any changes can be easily reviewed by editors and reviewers.
Response: thanks for this comment. I highlighted the revised contents by red, please find them.
(III) Please provide a cover letter to explain, point by point, the details of the revisions to the manuscript and your responses to the referees’ comments.
Response: I wrote a cover letter explaining the revisions point by point.
(IV) If you found it impossible to address certain comments in the review reports, please include an explanation in your appeal.
Response: Thanks, we have addressed all the comments from editor and reviewers.
