Strategic Interaction in the Supply of Affordable Housing Construction Land: Evidence from China’s Cities

Abstract

This study examines strategic interaction effects in the supply of affordable housing construction land among Chinese urban governments. Existing studies have predominantly examined China’s subsidized housing land supply from a vertical intergovernmental perspective, whereas this study investigates strategic interaction effects in municipal governments’ land allocation for subsidized housing from a horizontal and regional viewpoint. By conducting spatial econometric analysis on panel data from 278 prefectural-level cities in China (2010–2019) and constructing multiple patterns of intergovernmental strategic interactions based on diverse spatial weight matrices, this study provides robust evidence of strategic interactions and their underlying mechanisms among Chinese municipal governments in allocating construction land for affordable housing. The study reveals that Chinese urban governments exhibit positive strategic interactions in the supply of affordable housing construction land. This collaborative pattern demonstrates convergent (rather than divergent) supply strategies among horizontal intergovernmental relationships, further indicating a cross-regional equalization trend in China’s affordable housing provision. Two latent mechanisms drive these strategic interactions: spillover effects from intra-provincial political competition and the proactive agency effects of key local leadership figures. Therefore, China’s central government must fully account for the strategic interactions among municipal governments in allocating construction land for affordable housing. It is essential to establish adaptive regulatory mechanisms for regional cities’ supply of such land and ensure healthy, sustainable allocation of urban construction land for affordable housing through targeted interventions.

1. Introduction

Land is a critical factor in urban development and a key source of fiscal revenue for local governments in China. The supply of affordable housing construction land is directly reducing the supply of construction land for affordable housing by municipal governments. Following the 1994 tax-sharing reform, China’s central government decentralized fiscal revenue authority but made limited adjustments to fiscal expenditure responsibilities. Sub-provincial local governments are tasked with providing essential social support and nearly all public services, resulting in a system of “centralized fiscal revenue rights and decentralised expenditure responsibilities”. Beyond central fiscal transfers, local governments depend primarily on land-based financing—notably revenue from land sales—to finance their operations, resulting in significant reliance on land market proceeds. Consequently, to maximize land conveyance revenue, local governments often restrict residential land supply. This artificial scarcity exacerbates housing shortages, drives up property prices, and shifts residents’ housing demand from basic living needs to investment and speculation, further intensifying the imbalance between housing supply and housing demand. This cycle perpetuates systemic risks in real estate markets and undermines equitable access to affordable housing [1,2]. Consequently, China’s central government has emphasized in its real estate regulatory policies the principle of “Houses are for living, not for speculation”, which mandates that local governments fulfil their primary responsibilities, rationally expand land supply, increase the share of residential land, and accelerate the construction of affordable housing alongside its associated land allocation.

The strategic interaction among local governments has long been a significant topic in public economics. Early scholars empirically discovered that local governments engage in strategic interaction in tax policies, specifically manifested as tax competition behavior; that is to say, local governments adjust their own tax rates based on the tax rates of their neighboring competitors [3]. On this basis, strategic interaction has gradually been summarized as governments within a region adapting their policies in order to either mimic or counter the behavioral changes of neighboring governments. Specific strategic interaction behaviors include competition among local governments (such as investment attraction competition, fiscal competition, and political yardstick competition) [4,5], learning, “free-riding”, etc. [6].

Previous studies have often focused on the vertical intergovernmental perspective and policy implementation in the supply of China’s affordable housing [7,8]. This study, in contrast, employs an intercity interaction framework centering on development-oriented municipal governments to examine the existence of strategic interactions in their horizontal allocation of affordable housing construction land and decode the behavioral logic driving such interactions. Using city-level panel data, we construct multiple intercity strategic interaction models based on different spatial weight matrices, forming the foundation for a spatial econometric framework with which to conduct empirical tests. China’s affordable housing system was established in the 1980s, and its construction scale has continuously expanded alongside national development and urbanization [9]. In this study, “affordable housing” encompasses forms like low-rent housing, public rental housing, price-capped housing, economically affordable housing, subsidized rental housing, and shared-ownership housing, all of which involve independently allocated construction land. The concept of “affordable housing construction land” originates from the refined classification of residential land categories in the 2011 revised national standard “Urban Land Classification and Construction Land Standards (GB50137-2011)” by the Ministry of Housing and Urban–Rural Development (MO-HURD) [10]. For brevity, this term is simplified as “affordable housing land” in the text. “Strategic interaction” in this research refers to the phenomenon in which municipal governments adjust their affordable housing land supply strategies in response to changes in the supply scale of neighboring cities. This reflects a dynamic, interdependent decision making process shaped by regional competition, policy emulation, and resource coordination among local governments.

The current paper yields four main contributions. Firstly, this paper focuses on the construction and supply of public rental housing among cities at the same level and from a regional perspective. Secondly, by using the large and accurate land transaction data provided by the China Land Market Network (CLMN; see http://www.landchina.com (accessed on 16 September 2022)), which is managed by the Ministry of Natural Resources of China, this paper empirically examines this issue and the possible underlying mechanisms. Thirdly, this paper extends the impact of administrative boundaries on spatial intergovernmental interactions, which compensates for the omission of the administrative scope of political competition in existing studies. Finally, the research results of this paper are helpful in determining the regulatory mechanism for the supply of public rental housing construction land in regional cities, more precisely regulating the healthy and sustainable supply of public rental housing construction land in cities, and promoting local governance.

The remainder of this paper is organized as follows. Section 2 briefly introduces the affordable housing system and the land supply characteristics in China. Section 3 introduces the theoretical analysis and hypotheses. Section 4 reports the identification strategy, data, and variables. Section 5 presents the empirical results. Section 6 discusses the pros and cons of the study and introduces future work. Section 7 reports the concluding remarks.

2. Literature Review

2.1. China’s Affordable Housing System and Land Supply Characteristics

Since 1998, China’s urban housing provision framework has undergone a transformative evolution, progressively transitioning from a welfare-oriented model to a market-driven system in alignment with the nation’s rapid economic expansion and accelerated urbanization trajectory [11]. During this transition, the central government has established an affordable housing supply system to alleviate housing inequality for low-to-middle-income households while suppressing commodity housing prices [12,13]. The mainstay of China’s multi-tiered affordable housing system is cheap rental housing (CRH), public rental housing (PRH), and economic and comfortable housing (ECH) [14]. With a regionally decentralized authoritarian (RDA) regime that mandates local governments to deliver essential public services [15,16], the land supply for the affordable housing programs has been decided by local governments and listed separately in governments’ annual land use plan since 2009 [13].

A considerable amount of literature has been published on affordable housing. These studies either focus on policy and its structure [11,12,14,17], analyze the influence of affordable housing supply on other socioeconomic aspects, like housing price and community control [13,18], or investigate the incentive and characteristics of land supply for affordable housing [8,19,20,21]. The fragmented intergovernmental structure forms the bedrock of strategic interactions in land supply. A systemic misalignment between central mandates and local implementation is identified; while the central government prioritizes social equity, local governments face disincentives due to fiscal dependence on land commodification [17]. This “division of powers, incentives, and revenue sources” creates intrinsic contradictions, as affordable housing programs often require sacrificing lucrative land-leasing revenues [8,21]. It is further revealed how Beijing strategically locates affordable housing on low-value urban fringes to minimize fiscal losses, demonstrating how land-based interests override equity objectives [19]. These studies underscore the political economy of land allocation, where local governments balance top–down policy pressures against revenue maximization. Prevailing research uses traditional empirical models that treat cities as isolated entities and assume that the land supply of affordable housing construction is mainly determined by fiscal concern. The mechanisms underlying spatial interdependencies among cities in the dynamic process of affordable housing construction land allocation remain poorly understood. This study attempts to fill this knowledge gap using spatial econometric models.

2.2. Strategic Interaction Among Local Governments’ Public Goods Decisions

Strategic interactions—referring to how cities strategically respond to neighboring jurisdictions’ policy choices—may arise from intercity interdependencies driven by mimicry, externality spillovers, resource competition, or collaborative governance networks. A large and growing body of literature has investigated strategic interactions among governments at the same level of jurisdiction, with predominant emphasis on their tax policy [3,22,23] and the provision of public goods and services [4,24,25,26,27]. In the context of transitional economies like China, researchers have rarely studied strategic interaction in tax, as local governments lack legislative authority over taxation systems yet operate under uniform fiscal frameworks. The tournament competition hypothesis is testified through the spatial effect of city-level total investment across Chinese prefectural-level cities [24]. Mimetic behaviors in municipal green space provision is identified, driven by intercity competition for live ability rankings [25]. Industrial land supply is investigated using spatial panel models, and strategic price undercutting among neighboring cities to attract investments is demonstrated [4]. Strategic interactions among governments and foundations in funding basic medical research for infectious and parasitic diseases are examined, revealing that an increase in US funding for a disease is associated with a decrease in funding by other governments and organizations in the following year, suggesting potential free riding or optimal reallocation of resources [26]. A public services index was constructed, and it proved that direct and indirect mechanisms causing strategic interactions exist, while the interaction intensity is decreasing with the obstacle of economic catch-up and the hukou system [27]. While the literature on strategic interactions surrounding public goods and services has expanded exponentially in recent decades, housing policy interaction, particularly in land allocation for affordable housing, remains a critical yet underexplored dimension. In this paper, we try to answer whether and how local governments respond strategically to other cities’ supply of affordable housing construction land.

3. Theoretical Analysis and Hypothesis Development

The mechanism behind strategic interaction can be classified into two models: the spillover model and the resource flow model [28]. The spillover effect is a direct influence from neighbors, which has two forms: horizontal externalities [29,30] and yardstick competition [5]. The resource flow effect is caused by the flow of particular resources within its neighbors [4]. Because the affordable housing construction process takes 3–5 years after the supply decision and the eligibility requirements are complicated, the effect of either horizontal externality or resource flow in the affordable housing context is weak. Yardstick competition can explain the potential strategic interactions among local governments in the supply of affordable housing land construction. In China, the central government strategically employs comparative assessments of public service delivery outcomes across jurisdictions as a key performance indicator in evaluating the performance of local government officials [16]. This is formalized as a top–down yardstick competition with the spillover of governments’ behavioral information, which compels local officials to engage in strategic mimicry of administrative counterparts’ outcomes as a performance optimization tactic under competitive evaluation systems [6]. This tournament-like competition is quite different from the traditional yardstick competition, which is bottom–up in consideration of voters in developed economies [31]. We show in this paper that a spatial spillover mechanism exists and whether the main local officials are newly appointed matters in the supply of affordable housing construction land, which expands the scope of strategic interaction research.

The strategic interaction behavior in this study refers to the fact that the supply behavior of local governments in providing construction land for affordable housing will be adjusted strategically in response to changes in the supply behavior of similar local governments. Against the backdrop of commercial housing gradually becoming the mainstay of urban housing supply and soaring housing prices in China, the central government has gradually increased the intensity of affordable housing construction since 2007 to alleviate social conflicts caused by housing affordability issues. Under the top–down requirements of the central government, the supply of affordable housing has been incorporated into the performance assessment standards for local officials. Local city governments can use the performance of their competitors as a benchmark and imitate the supply policies of neighboring city governments for affordable housing. When determining the scale of affordable housing supply, local governments may seek to compete with their neighboring cities by providing more affordable housing, thereby gaining a significant competitive advantage in performance evaluations and political achievement assessments [32,33].

Meanwhile, relevant theoretical literature and empirical studies on local government public service supply also indicate that there may exist “free-rider” behavior in the spatial interaction of local government public service supply [25,27,30]. Because local governments providing public services can benefit not only local residents in a specific region but also those in neighboring areas, local governments can benefit from neighboring cities without increasing local public service supply [34], e.g., investments in infrastructure and educational facilities. There are also studies showing that in terms of environmental protection expenditure, as environmental protection investments in surrounding cities increase, local governments tend to reduce their own environmental protection expenditure [6].

Local governments make their own strategic choices and decisions in land transfer. Due to the interregional competition for political achievements and local endowment conditions, which have an impact on the land transfer behavior of local governments [2], land transfer, as one of the main means for local governments to promote growth, has a significant impact on the industrialization and urbanization development of local areas. Meanwhile, an increasing number of empirical studies have found that there is an interactive effect among local governments in land transfer in China. At the national level, there is a significant positive interactive effect among local governments in the transfer of newly added construction land, and there are significant differences in regions [35]. From the perspective of use differences, the interactive behavior of local governments in the transfer of newly added industrial use construction land and the interactive behavior of local governments in the supply of public green space have both been verified to exist significantly [4,25]. Therefore, this paper proposes Hypothesis 1, as follows.

H1: 

There exists strategic interaction among local governments in China in the supply of affordable housing construction land.

With the overall progress of the modernization of national governance and the transformation of the economy from high-speed growth to high-quality development, the functions and missions of local governments are undergoing a series of adjustments. Under the promotion and assessment mechanism, the behavior of local governments “competing for growth”, mainly based on GDP, is gradually evolving into competing for high-quality development. In the current Chinese political system, the promotion of local government officials is determined by their superior governments. The superior governments mainly evaluate the relative performance of local governments based on comprehensive assessment indicators of their subordinates. In particular, as a basic public service, the provision of affordable housing is embedded into the assessment of lower-level city governments by higher-level governments through target responsibility systems and assessment rewards [34]. Therefore, under the influence of this political assessment and promotion incentive mechanism, local governments and officials have a strong motivation to enhance their performance and reputation during their tenure by providing more affordable housing services. According to the benchmark competition theory, within a certain geographical range, local governments will have a stronger response to the public service supply and public investment feedback of neighboring city governments [6]. This is because provincial political decision makers will comprehensively compare and evaluate the performance of all lower-level cities within their jurisdiction to determine local assessment performance. Hypothesis 2 is proposed as follows.

H2: 

The strategic interaction of local governments in China regarding the supply of affordable housing construction land is positively influenced by the pressure of political competition.

From the perspective of the dynamic effects of local officials and their terms of office, in countries with universal suffrage, officials are mainly replaced through political elections, with fixed terms, so the cycle of elections and party rotation is basically the same as the cycle of official replacement. In China, the two are not the same. Besides the personnel changes that occur during the Party Congress, changes also take place in non-Party Congress years, and officials cannot accurately predict their own transfers in non-Party Congress years because there are often complex reasons behind them. Research has found that based on descriptive statistics regarding the personal characteristics of secretaries and mayors of prefectural-level cities and above, the average tenure of secretaries and mayors is about 2.7 years, indicating that local officials change frequently and that most have some job changes within one term. Compared with the Party Congress held every five years, job changes of officials are more difficult to predict and are often transferred by the higher-level Party Committee before the end of their term [2,36]. Therefore, on the one hand, from the perspective of the replacement and tenure of local officials in governance, officials tend to maximize their performance during their term of office. Because it is difficult to undertake short-term responses to their behavior before leaving office [37], new officials, in order to quickly prove their ability with political achievements, learn advanced practices from their neighbors, and the interaction is more in-depth and frequent. On the other hand, when the main officials take office, their enthusiasm and initiative are relatively high. Because the supply of construction land for affordable housing requires a large amount of public funds and energy, it requires more personal energy input from local officials and the exertion of their personal, dynamic effects. Therefore, Hypothesis 3 is proposed as follows.

H3: 

The strategic interaction of the supply of affordable housing construction land among local governments in China is positively influenced by new appointments of local key officials.

4. Identification Strategy, Variables, and Data

4.1. Identification Strategy

4.1.1. Moran’s I

This study first analyzes the spatial clustering and evolutionary characteristics of land supply for affordable housing by measuring the global Moran index and then determines whether to use a spatial econometric regression model. The index can be expressed as follows.

$$I={\displaystyle \frac{{\sum }_{i=1}^n{\sum }_{j=1}^n{w}_{ij}(X_i-\overline{X})(X_j-\overline{X})}{\frac{1}{n}{\sum }_{i=1}^n{(X_i-\overline{X})}^2{\sum }_{i=1}^n{\sum }_{j=1}^n{w}_{ij}}}$$

(1)

where $\overline{X}={\displaystyle \frac{1}{n}}{\sum }_{i=1}^n{X}_i$, $X_i$ is the value of a spatial element for the $i$th region. $w_{ij}$ is the weight of spatial unit $j$ on spatial unit $i$. To verify the robustness of spatial autocorrelation, three kinds of spatial weight matrices were constructed in this study. The first one is a spatial adjacency matrix based on whether city $i$ is adjacent to city $j$ or not. The second is the spatial inverse distance matrix based on the geographical distance between city $i$ and city $j$. The third is a nested matrix based on the square of the inverse distance between city $i$ and city $j$ and an economic indicator, and the spatial units that are closer and more economically powerful have greater spillover effects.

4.1.2. Baseline Model

This study uses spatial econometric models to identify strategic interactions between governments at the prefectural level. Classical spatial econometric models include the spatial autoregressive model (SAR), the spatial error model (SEM) and the spatial Durbin model (SDM) [38]. The spatial autoregressive model is primarily used to detect whether there are spatial spillover effects of the dependent variable across districts. The spatial error model, on the other hand, examines the spatial effects of omitted variables that are not included in the explanatory variables or unobservable random shocks. The spatial Durbin model based on panel data is specified as follows.

$$Y_{it}=\rho \sum _{j=1}^N{w}_{ij}{Y}_{jt}+X_{it}\beta +\theta {\sum _{j=1}^N{w}_{ij}X}_{jt}+{\omega }_i+{\gamma }_t+{\epsilon }_{it}$$

(2)

where $Y_{it}$ denotes the per capita area of land supply for affordable housing in city $i$ in year $t$. ${\sum }_{j=1}^N{w}_{ij}{Y}_{jt}$ is the spatial lag term of $Y_{it}$, which indicates that the explanatory variable in city $i$ is influenced by the explanatory variables in neighboring cities. $X_{it}$ represents the explanatory and control variables, and ${{\sum }_{j=1}^N{w}_{ij}X}_{jt}$ denotes the spatial lag term for these variables. ${\omega }_i$ and ${\gamma }_t$ are city and year fixed effects, respectively. ${\epsilon }_{it}$ is the random error term. $\beta$, $\theta$, and $\rho$ are the parameters to be estimated. If $\rho$ is significantly positive, there is a positive strategic interaction between city governments. On the contrary, if $\rho$ is significantly negative, there is a negative strategic interaction between city governments. In Equation (2), if $\theta =0$, it will degenerate into a spatial lag model; if $\theta +\rho \beta =0$, it will degenerate into a spatial error model, so the above spatial Durbin model, Equation (2), is more applicable.

4.1.3. Mechanism Test Model

The product of the official turnover variable (${change}_{it}$) and the spatial lag term (${\sum }_{j=1}^N{w}_{ij}{Y}_{jt}$) is introduced in the model to capture the effect of official turnover on strategic interactions. The test model is specified as follows.

$$Y_{it}=\rho \sum _{j=1}^N{w}_{ij}{Y}_{jt}+\lambda {change}_{it}\sum _{j=1}^N{w}_{ij}{Y}_{jt}+\delta {change}_{it}+X_{it}\beta +\theta \sum _{j=1}^N{w}_{ij}{X}_{jt}+{\omega }_i+{\gamma }_t+{\epsilon }_{it}$$

(3)

where ${change}_{it}{\sum }_{j=1}^N{w}_{ij}{Y}_{jt}$ is the product term. If the coefficient on the product term is significantly positive, it indicates that official replacement strengthens the strategic interaction of land supply for affordable housing. The definitions of the other variables are the same as in Equation (2).

4.2. Variables

In this study, the area of land supply for affordable housing is used as the explanatory variable. In addition, a set of city characteristic variables are controlled in the model to minimize the bias caused by omitted variables. On the basis of reference to the existing literature, we chose the indicators of land finance dependence (lp), financial freedom (fs), residential land supply structure (perzf), per capita gross domestic product (pcgdp), house price to income ratio (hir), secondary industry share (sip), tertiary industry share (tip), population density (pd), and urbanization rate (up) as the control variables, reflecting the situation of each city in the fields of local government finance, land grant, population, the economy, and industrial structure, respectively, which are used to control the influence of governmental capacity, social, and economic factors in different cities. The reasons for this are elaborated below.

The project of affordable housing provision in urban China cannot be successfully implemented unless local governments’ reliance on urban land-based interests is weakened [21]. Financial resources, as an important component of government organizational resources, reflect the scale and volume of funds that local governments can mobilize and use, and they are measured using two indicators: local fiscal freedom (fs) and land finance dependence (lp). Local fiscal freedom is measured by the ratio of local budget revenue to local budget expenditure. Land finance dependence is measured as the ratio of land premiums to local budget revenue, and higher fiscal freedom indicates that local governments’ budgeted expenditure comes increasingly from local revenue and relies less on fiscal transfers.

Local governments tend to reduce the supply of residential land in order to obtain higher land grant revenue. Therefore, the structure of residential land supply (perzf) influences affordable housing, which is measured using the ratio of the area of local government residential land supply to the total area of land disposed of. The commercial value of land is higher in areas with fast economic growth, which is measured by per capita gross domestic product (pcgdp). Local governments may prioritize the use of land plots for commercial housing, and land for affordable housing is often located in remote or less well-supported areas or even reduced in supply. The house price to income ratio (hir) can help achieve convergence in housing affordability across cities [39]. When the house price to income ratio exceeds a reasonable level, middle- and low-income groups have difficulties purchasing homes, which may trigger social discontent. To alleviate the conflict, local governments will divert market demand by increasing the supply of land for affordable housing.

Industrial restructuring, measured by secondary industry share (sip) and tertiary industry share (tip), will increase the demand for industrial land, which will crowd out the supply of land for affordable housing. The concentration of housing demand in cities with a high population density (pd) forces the government to increase the supply of land for affordable housing in order to alleviate social conflicts. Urban residential land supply is significantly driven by urbanization processes, the optimization of which is necessary in order to address housing issues [40].

In addition, this study controls for the important variable of official replacement (change) to capture the performance incentives of land supply for affordable housing. Specifically, change in the position of city mayor is used as a proxy variable for official change. The variable is 1 if the new mayor takes office in the current year and 0 for the others. At the same time, we also control for characteristic variables, such as the tenure and age of the officials.

4.3. Data

The data used in this paper include data from 278 cities from 2010 to 2019. Data on the area of land supplied for affordable housing construction, the area of residential land, the total area of supplied land, and the total amount of land premiums were obtained from the China Land Market Network (http://www.landchina.com/ (accessed on 16 September 2022)). Most of the data for the remaining variables come from the China City Statistical Yearbook and the macroeconomic and real estate database of the National Information Centre. Very few missing data are filled in using data published by local statistical bureaus. Data on the replacement of officials and personal characteristics come from local government websites. In order to mitigate the problem of heteroscedasticity, the natural logarithm is taken for some of the control variables in this paper. Descriptive statistics for the main variables are shown in

Table 1. Descriptive statistics for the main variables.

Variable	Definition	Mean	SD	Min	Max
pcbzf	Per capita area of land supply for affordable housing	0.166	0.252	0.000	2.822
lnlp	Land finance dependence (in logarithm)	−0.652	0.744	−8.310	1.321
lnfs	Financial freedom (in logarithm)	−0.890	0.530	−2.705	0.433
perzf	Residential land supply structure	20.685	10.589	0.381	81.547
lnpcgdp	Per capita gross domestic product (in logarithm)	10.647	0.590	8.576	13.056
lnhir	House price to income ratio (in logarithm)	−2.330	0.327	−3.342	−0.658
lnsip	Secondary industry share (in logarithm)	3.825	0.254	2.370	4.409
lntip	Tertiary industry share (in logarithm)	3.674	0.245	2.667	4.425
lnpd	Population density (in logarithm)	5.769	0.899	1.609	7.882
lnup	Urbanization rate (in logarithm)	3.964	0.281	2.725	4.605
change	Official replacement	0.297	0.457	0.000	1.000
lntenure	Official tenure (in logarithm)	0.770	0.590	0.000	2.485
lnage	Official age (in logarithm)	3.935	0.073	3.611	4.174

.

5. Empirical Results

5.1. Spatial Autocorrelation Analysis

Prior to the development of a spatial econometric model, the existence of spatial dependence in the data on land supply for affordable housing needs to be tested. In this paper, three spatial weighting matrices are used to measure Moran’s global I to examine the spatial agglomeration of land supply for affordable housing construction. The results of Moran’s I are shown in

Table 2. Moran’s I for affordable housing land supply.

Year	Adjacency Matrix			Geographic Distance Matrix			Nested Matrix
	Moran’s I	Z	P	Moran’s I	Z	P	Moran’s I	Z	P
2010	0.308	8.016	0.000	0.188	7.897	0.000	0.229	9.373	0.000
2011	0.211	5.351	0.000	0.152	6.192	0.000	0.169	6.726	0.000
2012	0.292	7.483	0.000	0.239	9.815	0.000	0.245	9.846	0.000
2013	0.244	6.180	0.000	0.183	7.441	0.000	0.185	7.340	0.000
2014	0.185	4.854	0.000	0.112	4.763	0.000	0.099	4.133	0.000
2015	0.237	6.051	0.000	0.241	9.862	0.000	0.228	9.119	0.000
2016	0.189	4.778	0.000	0.177	7.199	0.000	0.174	6.926	0.000
2017	0.063	1.703	0.088	0.053	2.313	0.021	0.053	2.248	0.025
2018	0.152	3.899	0.000	0.118	4.876	0.000	0.127	5.120	0.000
2019	0.168	4.774	0.000	0.104	4.789	0.000	0.086	3.890	0.000

.

As seen from Table 2, the value of Moran’s I of land supply for affordable housing of local governments in China’s cities from 2010 to 2019 is significantly positive. This indicates that there is a positive spatial correlation in the supply of land for affordable housing in China’s cities; in other words, there is a positive spatial interaction in the supply of land for affordable housing construction among cities. Therefore, it is reasonable to use the spatial econometric model for estimation in this study.

5.2. Baseline Regression for the Spatial Durbin Model

Whether the spatial Durbin model (SDM) can be degraded to the spatial autoregressive model (SAR) and the spatial error model (SEM) is subject to the Wald test and the LR test [41]. The results of the tests are shown in

Table 3. Estimation of the spatial Durbin model based on three different weight matrices.

	Adjacency Matrix		Geographic Distance Matrix		Nested Matrix
	(1)	(2)	(3)	(4)	(5)	(6)
Wpcbzf	0.1783 ***	0.1694 ***	0.2506 ***	0.2283 ***	0.2377 ***	0.2034 ***
	(0.0265)	(0.0267)	(0.0366)	(0.0372)	(0.0355)	(0.0362)
lnlp	0.0253 ***	0.0202 **	0.0278 ***	0.0229 ***	0.0286 ***	0.0222 ***
	(0.0081)	(0.0083)	(0.0082)	(0.0083)	(0.0082)	(0.0083)
lnfs	0.0783 ***	0.0664 **	0.0716 ***	0.0572 **	0.0658 **	0.0541 *
	(0.0266)	(0.0275)	(0.0271)	(0.0279)	(0.0270)	(0.0278)
perzf	0.0041 ***	0.0042 ***	0.0041 ***	0.0040 ***	0.0040 ***	0.0040 ***
	(0.0004)	(0.0004)	(0.0004)	(0.0004)	(0.0004)	(0.0004)
lnpcgdp		0.0021		0.0274		0.0099
		(0.0412)		(0.0400)		(0.0390)
lnhir		−0.0070		0.0141		0.0126
		(0.0298)		(0.0301)		(0.0300)
lnsip		−0.0791		−0.0715		−0.0795
		(0.0669)		(0.0664)		(0.0658)
lntip		−0.1445 **		−0.0996		−0.1104 *
		(0.0649)		(0.0633)		(0.0627)
lnpd		0.0951		0.1571 **		0.1688 ***
		(0.0642)		(0.0647)		(0.0647)
lnup		0.1592 **		0.1301 **		0.1427 **
		(0.0645)		(0.0647)		(0.0644)
Wlnlp	0.0999 ***	0.0838 ***	0.1171 ***	0.0915 ***	0.1116 ***	0.0771 ***
	(0.0136)	(0.0145)	(0.0203)	(0.0234)	(0.0205)	(0.0238)
Wlnfs	−0.0873 **	−0.0822 *	−0.0906	−0.1311 *	−0.0728	−0.1415 *
	(0.0402)	(0.0455)	(0.0570)	(0.0707)	(0.0634)	(0.0744)
Wperzf	−0.0018 **	−0.0019 **	−0.0027 **	−0.0025 **	−0.0030 **	−0.0025 **
	(0.0008)	(0.0008)	(0.0012)	(0.0012)	(0.0012)	(0.0013)
LR-lag	45.57 ***	64.95 ***	27.91 ***	36.15 ***	25.07 ***	41.71 ***
LR-error	50.44 ***	72.38 ***	28.15 ***	42.13 ***	23.73 ***	48.35 ***
Wald-lag	45.86 ***	65.54 ***	28.03 ***	36.33 ***	25.18 ***	41.96 ***
Wald-error	50.19 ***	71.95 ***	28.00 ***	41.97 ***	23.65 ***	48.48 ***
City fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
N	2780	2780	2780	2780	2780	2780
R2	0.0788	0.0758	0.0628	0.0358	0.0620	0.0316

*** means that the result is significant at the 1% level. ** means that the result is significant at the 5% level. * means that the result is significant at the 10% level. Clustering robust standard errors are reported in parentheses.

, where the original hypothesis is rejected at the 1% significance level, which indicates that the spatial Durbin model (SDM) is more suitable for the sample data.

Gradually increasing the number of control variables helps to test the robustness of the strategic interaction for affordable housing. Table 3 shows that the coefficients of the spatially lagged dependent variables of the Durbin model based on the three different weight matrices are all significantly positive. This robustly suggests that there is positive strategic interaction behavior of city governments in China in terms of land supply for affordable housing. That is to say, when a city’s neighbors increase the supply of land for affordable housing, the city will also strategically increase its own supply of land for affordable housing.

The fiscal system is one of the root causes of local governments’ lack of attention to the construction of affordable housing [12]. In Table 3, the estimated coefficients of land finance dependence (lp) are significantly positive across all of the three matrices. The estimation results suggest that cities with a higher dependence on land finance are better able to promote the supply of land for affordable housing. This is because the construction of affordable housing requires an injection of funds from local governments, and land finance revenue is an important source of local funds. Similarly, the table shows that the higher the fiscal freedom and the share of residential land, the higher the supply of land for affordable housing.

5.3. Mechanism Test

5.3.1. Political Competition

Because political competition is generally confined to a province, cities in the province can be considered direct competitors belonging to the same circuit. They are more competitive with one another and may be affected by the same provincial policies. Therefore, in Equation (2), we constructed the spatial weight matrix between cities in the same province and the spatial weight matrix between cities in different provinces, respectively, in order to examine how the strategic interaction effect between cities in the same province is greater than that between cities in different provinces. The relevant estimation results are shown in

Table 4. Comparing within-province and across-province strategic interactions.

	Adjacency Matrix		Geographic Distance Matrix		Nested Matrix
	Within-Province	Across-Province	Within-Province	Across-Province	Within-Province	Across-Province
	(1)	(2)	(3)	(4)	(5)	(6)
Wpcbzf	0.1433 ***	0.0972 ***	0.1515 ***	0.1469 **	0.1357 ***	0.1067
	(0.0229)	(0.0264)	(0.0237)	(0.0746)	(0.0228)	(0.0672)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes
City fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
N	2780	2780	2780	2780	2780	2780
R2	0.0775	0.0792	0.0604	0.0003	0.0647	0.0008

*** means that the result is significant at the 1% level. ** means that the result is significant at the 5% level. Clustering robust standard errors are reported in parentheses.

.

In column (5) of Table 4, the estimated coefficient on the spatially lagged dependent variable is significantly positive for the within-province nested matrix model, while in column (6) the coefficient on the spatially lagged dependent variable for the across-province model is not significant. This suggests that the interactive behavior of land supply for affordable housing is more likely to occur within the province, with a tendency to “catch up with each other”. In columns (1) and (2), the estimated coefficients on the spatially lagged dependent variable are significantly positive for the within-province and across-province adjacency matrix models. Furthermore, the coefficient in column (1) is larger than that in column (2). This suggests that the spatial strategic interaction of land supply for affordable housing is stronger between cities within the province than across provinces. The same conclusion was found in the case of the geographic distance matrix. This may be due to the fact that cities in the same province are assessed under the same system, and they are the most direct competitors, facing direct competition for performance appraisals and promotions. The cities will consciously continue to narrow the gap between them, showing a tendency to “catch up with each other” in the provision of public services in the area of affordable housing.

5.3.2. Enabling Effect of the Key Leader in Local Governance

Considering the influence of key leaders in local governance, we created a dummy variable for the time of mayoral replacement. Under the existing system of local powers and responsibilities, local mayors are mainly responsible for local economic development and livelihood work. Moreover, the construction of affordable housing is a major livelihood project. The Guiding Opinions of the General Office of the State Council on the Construction and Management of Affordable Housing Projects (https://www.gov.cn/zhengce/zhengceku/2011-09/29/content_7236.htm (accessed on 26 June 2022)) explicitly state that the people’s governments of cities and counties will specifically implement the construction of affordable housing in their localities and that an assessment and accountability mechanism will be established for the regional governments and relevant departments responsible for affordable housing projects. The mayor, as the highest executive officer, signs the target responsibility for the construction of affordable housing; as such, the mayor bears more responsibility and reputation for performance than any other leader of the city. We introduce a product of the dummy variable for mayoral replacement and the spatially lagged dependent variable in the spatial Durbin model. Finally, we re-estimate the model by restricting the sample to cities in the same province. The estimation results are shown in

Table 5. Effect of officer replacement on strategic interaction.

	Adjacency Matrix	Geographic Distance Matrix	Nested Matrix
	(1)	(2)	(3)
Wpcbzf	0.0840 ***	0.0623 **	0.0614 **
	(0.0239)	(0.0254)	(0.0242)
change	−0.1112 ***	−0.1187 ***	−0.1155 ***
	(0.0251)	(0.0282)	(0.0273)
change × (Wpcbzf)	0.7859 ***	0.8068 ***	0.7401 ***
	(0.0566)	(0.0500)	(0.0483)
Control variables	Yes	Yes	Yes
City fixed effect	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes
N	2780	2780	2780
R2	0.1667	0.1696	0.1677

*** means that the result is significant at the 1% level. ** means that the result is significant at the 5% level. Clustering robust standard errors are reported in parentheses.

.

We can see from Table 5 that the estimated coefficients of the product term, change $\times$ (Wpcbzf), are significantly positive across all matrices. This indicates that after a new mayor has taken office, on the one hand, in order to prove his or her ability as soon as possible with political achievements in public service provision and in safeguarding people’s livelihoods, the mayor will learn from his or her neighboring cities regarding their advanced experience with and practices of land supply for affordable housing, and the interactions will be more in-depth and frequent. On the other hand, officials are more enthusiastic and motivated to work when they are newly appointed, and they put relatively more energy into land supply for affordable housing. This finding strongly confirms that the enabling effect of key leaders in local governance is an important mechanism for the interaction of affordable housing land supply strategies in Chinese cities.

6. Discussions

This study examines the supply of affordable housing construction land by municipal governments as a critical observable variable for affordable housing provision, exploring the interactive linkages among peer local governments. The findings reveal a robust positive strategic interaction in affordable housing land supply among Chinese municipal governments. This conclusion remains consistent when replacing the spatial adjacency matrix with spatial inverse distance matrices and nested matrices, demonstrating methodological robustness. Specifically, local governments’ decisions on affordable housing land supply are significantly influenced by the land supply behaviors of neighboring jurisdictions. Such strategic interactions reflect convergence rather than differentiation in affordable housing land provision, indicating that cities tend to align their supply scales with those of their peers. Under the governance framework of China’s central and provincial governments, minimum standards for affordable housing construction are clearly defined. Through strategic interactions, the supply of affordable housing exhibits a trend towards cross-regional equalization, suggesting that this intergovernmental dynamic may serve as a latent mechanism with which to advance national strategic goals of affordable housing provision and public service homogenization. The interplay and adjustments in horizontal intergovernmental relations can enhance the effectiveness of coordination and competition within the government’s organizational system, fostering regionally complementary advantages and promoting equitable urban development.

The strategic interactions in municipal governments’ supply of affordable housing construction land are driven by two underlying mechanisms: the spillover effects of intra-provincial political competition and the agency effects of newly appointed local officials. Research reveals that horizontal intergovernmental competition among cities significantly enhances the supply of local public goods. Against the backdrop of China’s longstanding land-driven development model, the competitive dynamics among municipal governments are no longer solely governed by GDP-based performance evaluations. Political competition between cities must also prioritize land allocation for affordable housing to balance urban development and social welfare within finite land resources. The appointment of new officials serves as a critical juncture. Amidst complex constraints in affordable housing provision—including funding shortages, land quotas, and political factors [42,43,44]—newly appointed officials are often better positioned to break institutional inertia. By expanding public service delivery and safeguarding people’s livelihoods, they demonstrate administrative competence, earning both public support and recognition from higher authorities. This strategic behavior not only addresses immediate housing inequities but also fosters a ripple effect, incentivizing neighboring cities to adopt similar policies, thereby amplifying regional coordination in affordable housing governance.

On the other hand, newly appointed officials must closely monitor the development dynamics of neighboring competitive cities within the province during their early tenure, often adopting a follow-the-leader approach. This creates a “blame sharing effect” [45] in local performance evaluations, where relative underperformance or development risks are collectively diffused, reducing accountability for lagging behind. Consequently, new officials may exhibit cautiousness, delayed actions, or constrained ambitions in affordable housing provision due to local economic realities. However, China’s municipal governments typically set binding targets for affordable housing construction through multi-year urban development plans. Given these fixed baseline targets, newly appointed officials often engage in a catch-up competition to exceed goals (rather than risk underperformance). For instance, cities like Nanjing and Chengdu have institutionalized annual land supply quotas for affordable housing, compelling officials to prioritize such projects to avoid penalties for unmet targets. These dynamics transform initial inertia into a race to “outperform peers”, ultimately amplifying intercity competition in public goods provision while adhering to centralized planning frameworks.

China has significantly increased the scale of affordable housing construction land in the past decade, yet substantial gaps remain in comparison to Western countries. The Chinese government has explicitly pledged to further expand urban affordable housing supply in the future, a policy expected to stabilize the real estate market and enhance public welfare. Local public service provision is not spatially isolated [27], and our findings highlight the necessity of integrating affordable housing land supply into coordinated regional urban development policies to elevate housing security levels across interconnected regions. However, this study has limitations. While focusing on issues related to affordable housing land supply in China’s regional cities, it offers limited exploration of individual city characteristics, broader economic impacts of affordable housing construction, and cross-national economic policy implications. Future research will address and expand these dimensions to advance global comparative studies on housing governance.

7. Conclusions

The present study contributes to this line of research by studying strategic interaction in the supply of affordable housing construction land. Based on theories of strategic interactions among local governments, the study explores the underlying logic of horizontal intergovernmental relationships among cities in the allocation of affordable housing land. To examine the occurrence of strategic interactions and their underlying mechanisms, the empirical methodology constructs multiple spatial weight matrices to analyze spatial autocorrelation among the dependent variables. Building on this, the study employs the spatial Durbin model (SDM) within the spatial econometric framework for empirical testing.

Based on a spatial econometric analysis of over 1 million land transaction records across 278 Chinese cities from 2010 to 2019, we find that there exists a positive strategic interaction in affordable housing land supply among municipal governments in China. This indicates that the increase in affordable housing land supply in a given city is significantly promoted by expansion of the scale of affordable housing land in neighboring cities, demonstrating a convergence characteristic in land supply for affordable housing among adjacent cities. Furthermore, given that the supply of affordable housing land involves complex interactions among multiple factors, political competition manifests a stronger “catch-up” dynamic in spatial strategic interactions in affordable housing land supply between cities within the same province in comparison to inter-provincial contexts. In terms of the agency effect of key individuals in local governance, the appointment of a new mayor emerges as a significant positive factor driving strategic interactions between local governments and their neighboring cities, substantially enhancing the supply of local public goods.

These results pose important policy implications. Firstly, the strategic interactions in affordable housing construction land supply among municipal governments may drive the improvement of regional housing security levels, achieving complementary advantages in the provision of regional housing and public services. Secondly, it is imperative to further refine the performance evaluation system for municipal governments. By better incentivizing healthy intercity competition and collaboration, local social welfare can be elevated, driving high-quality urban development. Thirdly, there is a need to establish adaptive regulation and monitoring mechanisms for the supply of urban affordable housing land. This will enable precise control over the healthy and sustainable supply of land dedicated to affordable housing, ensuring long-term alignment with policy objectives.