Domestic Market Integration and Subsidies Provided by Local Government to Zombie Firms: Evidence from China’s City-Level Data

Abstract

With the advancement of economic globalization, market integration has become a critical contributing factor for sustainable economic development. However, the persistence of zombie firms continues to undermine fiscal sustainability, creating a critical policy challenge. The core purpose of this article is to propose novel policy directions for emerging economies to foster domestic market integration (DMI) and sustainable development. Based on panel data from 297 cities in China from 2008 to 2020, this paper employs a two-way fixed effects model to empirically test the impact of subsidies allocated to zombie firms on DMI. The results indicate that targeted subsidies provided by local governments to zombie firms exacerbate regional market segmentation and hinder the process of DMI. The analysis reveals several key mechanisms underlying this phenomenon: on the one hand, local governments may shift expenditure burdens to enterprises located outside their jurisdiction, leading to higher institutional trade costs and lower fiscal sustainability; on the other hand, the persistence of zombie firms crowds out the resources available to healthy enterprises and distorts the allocation of factor resources, thereby impeding the ability of local products to compete effectively in intercity markets. However, enhancing the business environment and upgrading the industrial structure can effectively mitigate the market fragmentation induced by such inefficient subsidies. This research offers a novel perspective for quantifying local protectionism and provides important implications to improve DMI as well as sustainable economic development.

1. Introduction

Amidst the profound transformations witnessed in the global arena in recent years, the imperative of domestic market integration (DMI) has gained heightened strategic importance for China’s pursuit of sustainable economic development [1,2,3]. DMI represents a state characterized by a high degree of interregional market integration and free flow of commodities across regions, which serves as a fundamental driver of long-term economic development. This stands in contrast to market segmentation—a state characterized by institutional and regulatory barriers that artificially fragment interregional economic activity. Such segmentation strategically prioritizes short-term jurisdictional gains at the expense of broader economic efficiency and long-term growth potential, ultimately impeding sustainable economic development.

Since China’s accession to the World Trade Organization (WTO) in 2001, its domestic market has shown a general trend toward integration [4]. However, significant market segmentation remains a persistent issue within China’s market system [5,6]. Many researchers have investigated the multifaceted determinants influencing DMI in China, encompassing both non-institutional and institutional dimensions. The non-institutional factors include dialect patches, official mobility, trust distance, transportation infrastructure, and regional economic environments [7,8,9,10]. More significantly, institutional factors, particularly those stemming from China’s fiscal decentralization system and the tournament-style promotion incentives for local government officials, have been identified as fundamental determinants of DMI [11,12,13]. Within this institutional framework, local governments pursue the development of comprehensive yet inefficient industrial chains, prioritizing local interest maximization over national economic efficiency. This protectionist paradigm has not only hindered cross-regional resource reallocation but also institutionalized the survival of zombie firms, thereby exacerbating challenges to sustainable economic development such as overcapacity and homogeneous production. Addressing these institutional barriers through comprehensive reform measures has become an urgent task for promoting DMI as well as economic sustainability under the current new development pattern. In particular, resolving the persistent issue of zombie firms, which are largely sustained by excessive local government intervention in market operations, could be a viable direction to crack this challenge.

As a typical manifestation of local protectionism and market distortions, zombie firms exert a profound impact on economic sustainability [14]. The economic ramifications of zombie firms encompass the disruption of market feedback mechanisms and the process of “creative destruction” [15], the erosion of production factor allocation efficiency [16,17,18,19], and spillover effects on non-zombie firms [20,21]. Its impact on the DMI as well as sustainable development cannot be ignored either. As shown in Figure 1 (collected through the 2008–2020 China Tax Survey Database), the proportion of zombie firms in China is lower in the eastern region, which benefits from well-developed infrastructure and higher levels of innovation. In contrast, the central and western regions show a higher proportion of zombie firms. This trend mirrors the regional distribution of market segmentation observed in China.

Zombie firms are defined as chronically unprofitable enterprises sustained exclusively through external financial and fiscal support [22,23]. These firms are typically inefficient and non-competitive but consuming substantial fiscal resources and production factors, thereby undermining the market order and economic sustainability. This phenomenon is particularly prevalent in regions with underdeveloped business environments and concentrated resource-dependent industries, where weaker fiscal capacity and the “common pool” effect jointly contribute to inefficient and excessive subsidization. Given their large scale and ability to provide substantial employment opportunities and GDP contributions, zombie firms always receive continuous government support [24,25]. These supports include fiscal subsidies [26], resource support [27], and preferential bank credit policies [28]. Among the various forms of assistance, fiscal subsidies are the most prevalent tool employed by local governments to sustain zombie firms [29]. From 2008 to 2022, the average subsidy rate for listed companies in China rose sharply from 1.71% to 6.21%, reflecting the growing significance of government subsidies in the economy. As locally led industrial policies gained momentum, governments increasingly employed regionally targeted subsidies to bolster the competitiveness of local enterprises [30]. Nevertheless, this trend has exacerbated the persistent issue of zombie firms. An examination of China’s tax survey database from 2010 to 2020 indicates that the average fiscal subsidy rate for non-zombie firms stood at 0.33%, whereas zombie firms received subsidies at a rate of 0.73%, which is 121.2% higher than for non-zombie counterparts. This disparity underscores the role of fiscal subsidies as a pivotal factor in sustaining the operations of zombie firms. Therefore, regional fiscal subsidies allocated to zombie firms warrant considerable scrutiny regarding DMI. Yet, the existing literature has paid limited attention to the implications of zombie firms on market integration, and the elucidation of relevant mechanisms remains scarce.

While regional fiscal subsidies allocated to zombie firms may provide short-term benefits by stabilizing employment and preventing immediate socio-economic shocks, these measures pose significant long-term challenges to economic sustainability. The subsidies divert scarce fiscal resources that could otherwise be allocated to public services and infrastructure development, thereby reducing the efficiency of public expenditure. Moreover, prolonged subsidization fosters path dependence and moral hazard, discouraging these firms from pursuing necessary restructuring and innovation. This creates a vicious cycle that intensifies fiscal burdens, leading to what may be termed a “fiscal black hole” effect. Compounding these issues, the substantial fiscal resources devoted to sustaining zombie firms not only undermine fiscal sustainability but may also transfer to other regions through the production network, ultimately jeopardizing the sustainability of the broader economic system [31]. Consequently, examining local governments’ subsidy policies toward zombie firms also yields critical insights into economic sustainability challenges.

The core purpose of this article is to investigate the impact of subsidies allocated to zombie firms on DMI. The main contributions of our study are as follows:

First, by analyzing fiscal subsidies as local protectionism tools and linking DMI with zombie firm issues, we offer new insights for emerging economies pursuing sustainable development. As a significant form of local protectionism, subsidies provided by local government to zombie firms directly affect the progress of DMI. But, to the best of our knowledge, this paper is among the first to bridge these two research areas. Second, we clarify the mechanisms underlying this phenomenon in the context of China and propose methods to mitigate the effects of inefficient subsidies. Although the subsidy–DMI relationship may entail more complex mechanisms, our study offers valuable preliminary evidence and a conceptual framework for future research. Finally, by examining subsidies allocated to zombie firms, we present a practical approach to quantifying local protectionism. Research on local protectionism has been primarily theoretical, with empirical evidence remaining scarce due to methodological constraints related to data availability. This study may extend the empirical research in that field. While Barwick et al. (2021) [3] also measure local protectionism via fiscal subsidies, our study advances the methodology by using city-level data and incorporating finer regional and enterprise variations in subsidies.

2. Literature Review and Theoretical Analysis

2.1. Literature Review

China’s recent proliferation of locally driven industrial policies has significantly reshaped regional economic landscapes. These policies, implemented through discriminatory fiscal incentives and financial privileges for local enterprises, have established robust protectionist mechanisms within jurisdictional boundaries. While effectively safeguarding local economic interests, such policy exhibits a pronounced tendency to prioritize short-term regional gains at the expense of long-term overall benefits. These approaches have engendered systemic challenges to sustainable economic development, including redundant construction, industrial homogenization, and fiscal unsustainability, thereby undermining the evolution of an efficient, nationally integrated production specialization system [29].

Prior scholarship has identified two primary categories of factors influencing DMI: non-institutional and institutional determinants [7,8,9,10,11,12,13]. Non-institutional research has identified several key factors: Guiso et al. found that cultural heterogeneity significantly impedes interregional economic transactions and market integration processes [7], while Niu et al. demonstrated that high-speed railway (HSR) expansion will reduce market segmentation and enhance trade value [9]. However, contemporary research has increasingly emphasized the critical role of institutional factors in explaining market fragmentation, especially within the evolving global supply chain context. A growing consensus suggests that China’s distinctive institutional environment—characterized by local governments’ protectionist “beggar-thy-neighbor” policies and the intense “promotion tournament” among regional officials—constitutes the fundamental barrier to DMI [11,12,13]. Local officials frequently employ irregular protective measures to interfere in the market and establish protectionist barriers [32]. Methodologically, studies examining institutional barriers to DMI have predominantly employed difference-in-differences (DID) approaches, utilizing quasi-natural experiments to characterize changes in institutional factors. This is primarily due to the inherent challenges in quantifying complex institutional obstacles. Our study innovatively addresses this research gap by measuring government subsidies allocated to zombie firms. This approach to quantify local protectionism is methodologically similar to that of Barwick et al. (2021) [3]. They integrated provincial-level automobile registration data in China and constructed a structural model to simulate the economic effects of local protectionism. However, Barwick et al.’s study has two main limitations: first, they applied a uniform implicit subsidy rate to firms with the same characteristic but within different regions, resulting in a relatively coarse measurement; second, their use of provincial-level data to simulate local protectionism in a single industry restricts the analysis’s granularity. Referring to Barwick et al. (2021) [3], this paper advances this methodology by utilizing municipal-level data to measure fiscal subsidies allocated to zombie firms, and then incorporating this quantitative indicator into empirical regression techniques to systematically examine the impact pathways of discriminatory fiscal subsidies on DMI.

The academic investigation of zombie firms has systematically progressed through four research phases: identification, causes, economic consequences, and effective governance. The identification of zombie firms typically centers on three core characteristics: loss of sustainable operational capacity, dependence on external financial support for survival, and inefficient resource allocation [15,24,33,34]. The genesis of zombie firms predominantly reflects institutional failures in government–market relations. Chinese local governments, constrained by dual objectives of political career incentives and social stability maintenance, actively sustain these economically nonviable enterprises through various market-distorting tools [22,23,24,25], with fiscal subsidy being the most prevalent instrument. However, these interventions have also led to numerous long-term problems, including crowding out of healthy firms, resource misallocation, and fiscal unsustainability [14,15,16,17,18,19,20,21]. Discriminatory subsidies allocated to zombie firms consume substantial financial resources and even create interregional fiscal externalities through transfer payment, which has posed latent threats to fiscal sustainability. As a typical product of local protectionism, zombie firms’ impact on DMI still remains strikingly understudied.

Fiscal subsidy is obviously a critical factor supporting the persistence of zombie firms [35]. There are three predominant theoretical frameworks explaining the relationship between government subsidies and corporate performance: (1) the Resource-Based View [36,37], which posits subsidy-induced efficiency gains; (2) the Efficiency Distortion Hypothesis [38], warning of potential resource misallocation and subsidy dependency traps; and (3) the Contingency Perspective [39], suggesting optimal subsidy thresholds for positive outcomes. Our study focuses on subsidies allocated to zombie firms and predominantly supports the Efficiency Distortion Hypothesis. It is highly correlated with a distinctive Chinese institutional phenomenon where local governments perpetuate economically unjustifiable subsidies to protect enterprises within their jurisdiction. The economic consequences of these targeted and discriminatory fiscal subsidies primarily manifest in three ways: (1) crowding out productive enterprises [40], (2) distorting resource allocation [17], thereby reducing regional production efficiency and exacerbating overcapacity, and (3) undermining fiscal sustainability—since subsidizing zombie firms may compel local governments to adopt new cost-shifting strategies to maintain fiscal balance.

2.2. Theoretical Analysis and Research Hypothesis

As shown in Figure 2, subsidies provided by local governments to zombie firms may hinder DMI through the combined effects of cost-shifting, innovation crowding-out, and resource misallocation. Section 5 will empirically test theses mechanisms.

Firstly, the crowding-out effect of zombie firms fundamentally distorts regional economic ecosystems. These financially distressed enterprises, sustained through external support despite chronic insolvency, disproportionately consume critical economic resources across four key dimensions: financial credit, innovation capacity, product upgrading resources, and labor employment [41]. Their large operational scale and systemic importance in local economies enable zombie firms to command substantial fiscal support and production inputs [42]. Nevertheless, their technological capabilities and product efficiency fall far short of the requirements for establishing a strong foothold in the domestic market [43]. That even creates a cascading effect that propagates through supply chains, undermining regional economic vitality. Paradoxically, viable firms, which maintain operational autonomy, demonstrate strong capacity and competitiveness in adapting in the innovation-driven market. So, the entrenched presence of zombie firms creates a resource allocation paradox: instead of exiting the market as economic logic would dictate, these inefficient entities appropriate financial resources and fiscal support that would otherwise fuel healthy enterprises’ innovation and market adaptation. This misallocation of resources constrains viable firms’ ability to compete in an increasingly integrated market.

Secondly, the implementation of non-neutral fiscal subsidies inevitably leads to resource misallocation. According to the OECD framework, competitive neutrality represents an economic environment where no business entity enjoys gains from undue competitive advantages or suffers from artificial disadvantages. However, this principle is particularly undermined by local protectionist policies, especially through subsidies toward zombie firms, which inherently discriminate against enterprises based on their ownership structures, developmental stages, and operational scales. Such selective and biased non-neutral government subsidies create substantial distortions in the resource allocation pattern and have profound implications for DMI. Given that resource allocation efficiency directly determines intercity market competitiveness [44], regions reliant on discriminatory subsidy policies become systematically marginalized within the national production value chain. This marginalization, in turn, reinforces their resistance to integration into the unified national market, creating a self-perpetuating cycle of economic fragmentation.

In the framework of interregional trade dynamics, product competitiveness is fundamentally determined by three core dimensions: the cost of production factors, the scale of production, and value-added technological sophistication. Empirical studies have established that resource misallocation induces productivity losses, thereby significantly increasing production costs [45], while constraints on innovation capacity systematically reduce the technological value-added component of products [46]. This dual mechanism of efficiency loss undermines the competitiveness of local products in intercity markets, preventing them from securing substantial market penetration.

Finally, subsidies to zombie firms have exacerbated the fiscal unsustainability of local governments, potentially prompting cost-shifting tactics. Fiscal cost shifting refers to the strategic practice through which local governments transfer part of their fiscal expenditure pressures to other entities. This phenomenon can be categorized into two distinct types based on the target of shifting: intergovernmental shifting and enterprise-level shifting. The intergovernmental fiscal cost shifting mechanism primarily operates through fiscal instruments, particularly transfer payments, enabling local governments to redistribute fiscal burdens to the central government or other regional governments via common pool channels [47]. At the enterprise level, fiscal cost shifting typically manifests through strategic government–business interactions. When confronted with substantial fiscal pressures, local governments may transfer certain social responsibilities or expenditure burdens to enterprises within their jurisdiction to alleviate fiscal stress [48]. In the context of an increasingly integrated national production division system, a significant transformation has occurred in local governments’ revenue sources. Through cross-regional commercial flows, local government’s revenue sources now extend beyond traditional tax contributions to encompass non-tax administrative revenues [49]. These alternative revenue streams are predominantly generated through market access barriers, including administrative licensing requirements and elevated market entry standards.

So, this article advances the proposition that local governments’ enterprise-level cost shifting strategies have expanded beyond domestic enterprises to incorporate extra-jurisdictional entities. This expansion is achieved through increasing compliance costs on external producers operating within their region. The operationalization of this strategy involves non-tax revenue instruments, including administrative fees, punitive fines, and compulsory apportionments. These measures have elevated entry barriers for intercity products and generated alternative revenue streams to counterbalance local fiscal subsidy expenditures. However, the evolving landscape of interregional trade conditions has empowered enterprises to implement nationwide sales strategies [50]. This development may prompt enterprises to strategically reduce or completely withdraw market allocation from regions with higher entry barriers. Combing local governments’ incentives to increase compliance cost with enterprises’ strategy of nationwide sales, regional isolation tendencies will inevitably be exacerbated.

Accordingly, the research hypothesis is proposed:

H1. 

The subsidies allocated to zombie firms by local governments have exacerbated regional market segmentation, thereby impeding the formation of DMI.

3. Research Design

3.1. Baseline Modeling

In order to study the impact of subsidies allocated to zombie firms on DMI, the following benchmark model is constructed:

$${DIV}_{it}={\alpha }_0+{\alpha }_1·{TaxBefit}_{it}+{\sum }_k{\alpha }_k·Z_{kit}+{\gamma }_t+{\vartheta }_i+{ϵ}_{it}$$

where the subscript i indicates city and the subscript t indicates year; ${DIV}_{it}$ represents market segmentation, an inverse proxy indicator for DMI, calculated using the relative price method. ${TaxBefit}_{it}$ represents the average subsidy rate provided by local governments within their jurisdiction, including the overall subsidy rate (${TaxBefit\_all}_{it}$) and the subsidy specifically for zombie firms (${TaxBefit\_zom}_{it}$). $Z_{kit}$ represents control variables. ${\gamma }_t, {\vartheta }_i,$ and ${ϵ}_{it}$ represent the year fixed effect, city fixed effect, and error term, respectively.

3.2. Variable Calculation

3.2.1. Explained Variable

Market segmentation (${DIV}_{it}$) is the core explained variable in this paper. As mentioned earlier, market segmentation acts as a counter-indicator of DMI. The larger this indicator, the larger the local protectionist barriers, and thus the increased impediment to the transaction of goods and factors. Previous research mainly uses three methods for measuring market segmentation, including the relative price method [51], the trade-flow method, and the production structure method [52]. Among these, the relative price method has gained prominence due to its strong economic intuition and widespread application in empirical research. It is rooted in Freedman’s “Law of One Price” and Samuelson’s “Iceberg Cost” model and operates on the principle that heightened sensitivity of interregional commercial activity to price fluctuations indicates greater market integration. So, referring to Parsley and Wei (2001) [32], we employ the relative price method to calculate the market segmentation. The following are the detailed steps:

First, we use the logarithmic first difference of price ratios to measure relative prices:

$$∆Q_{ijt}^k=\ln \left(p_{it}^k/p_{jt}^k\right)-\ln \left(p_{it-1}^k/p_{jt-1}^k\right)=\ln \left(p_{it}^k/p_{it-1}^k\right)-\ln \left(p_{jt}^k/p_{jt-1}^k\right)$$

where subscript i and j represent pairs of prefecture-level cities; k represents the category of goods; Q is the relative price; and p is the retail price index.

Then, the absolute value of the relative price is taken to ensure that the ordering of city pairs (i,j) does not influence the sign of $∆Q_{ijt}^k$:

$$\left|∆Q_{ijt}^k\right|=\left|\ln \left(p_{it}^k/p_{it-1}^k\right)-\ln \left(p_{jt}^k/p_{jt-1}^k\right)\right|$$

Second, we subtract the mean of all absolute relative prices ($\overline{\left|∆Q_t\right|}$) to eliminate the non-additive effects caused by product heterogeneity:

$$q_{ijt}^k=\left|∆Q_{ijt}^k\right|-\overline{\left|∆Q_t\right|}$$

Third, we calculate the variance of the adjusted relative price fluctuations (sd$\left(q_{ijt}^k\right)$). This variance serves as the degree of market segmentation between cities i and j in period t. To facilitate the interpretation of regression coefficients, these variances are multiplied by 100.

Finally, to construct panel data reflecting market segmentation for each prefecture-level city, we calculate the weighted average of the market segmentation levels across all city pairs involving that city. The weights are the inverse of the geographic distance between the cities in each pair, normalized by the sum of the inverse distances for that specific city.

3.2.2. Core Explanatory Variable

Subsidy rate ((${TaxBefit\_all}_{it}$, ${TaxBefit\_zom}_{it}$) is the core explanatory variable of this paper. The subsidy rate is measured by the ratio of government subsidies received by each firm (or zombie firm) in a given year to its total assets at the end of the year, and then this ratio is weighted against the regional level based on the proportion of total assets.

The zombie firm identification criteria that are widely adopted by the academic community are derived from the FN-CHK model, originally developed by Caballero et al. (2008) [15] and subsequently refined by Hoshi (2006) [24] and Fukuda and Nakamura (2011) [33]. This established model primarily employs the existence of continuous credit support in the case of sluggish returns to identify zombie firms.

Combined with China’s unique national conditions and institutional context, this study adapts the adjusted FN-CHK method [34] to identify zombie firms. Specifically, we identify a firm as a zombie firm if it satisfies two conditions: (1) its total net profits remain negative for three consecutive years after deducting both fiscal and credit subsidies, and (2) it demonstrates no sustained growth in net assets throughout the same three-year period.

The profit deduction is conducted as followed:

$${realprofit}_{i,t}={profit}_{i,t}-\left({govsub}_{i,t}-{banksub}_{i,t}\right)$$

where ${realprofit}_{i,t}$ is the real profit of firm i in period t, which is also the profit after deduction; ${profit}_{i,t}$ is its net profit; ${govsub}_{i,t}$ is the government subsidies received by firm i, which is derived from the “non-operating income—subsidy income” indicator in the tax survey database; ${banksub}_{i,t}$ is the credit subsidies obtained by firm i, which is estimated as the difference between the minimum net interest and the actual interest rate.

$${banksub}_{i,t}={RA}_{i,t}-{BA}_{i,t}$$

${RA}_{i,t}$ represents the actual net interest expenditure, with the data sourced from the “total interest expenditure” indicator in the tax survey database; ${BA}_{i,t}$ is the minimum net interest expenditure to maintain normal operation.

$${RA}_{i,t}={rs}_t\times {BS}_{i,t-1}+\left({\displaystyle \frac{1}{5}}{\sum }_{j=0}^4{rl}_{t-j}\right)\times {BL}_{i,t-1}$$

where ${rs}_t$ is the short-term optimal lending rate, which is annualized based on the benchmark interest rates for loans with maturities of up to six months (inclusive) and six months to one year (inclusive). $rl$ is the long-term optimal lending rate, calculated as the arithmetic mean of the benchmark interest rates for loans with maturities of 1–3 years (inclusive), 3–5 years (inclusive), and over 5 years. $BS$ and $BL,$ respectively, represent enterprises’ short-term and long-term bank loans, which are proxied by current debt and long-term debt. The short-term and long-term optimal lending rates are presented in

Table 1. Optimal lending rates table from the year 2008 to 2020.

Year	$\mathit{r}\mathit{s}$	$\mathit{r}\mathit{l}$
2008	3.32%	6.47%
2009	2.54%	6.47%
2010	2.58%	6.44%
2011	3.06%	6.52%
2012	3.02%	6.41%
2013	2.90%	6.22%
2014	2.88%	6.34%
2015	2.46%	6.26%
2016	2.17%	5.89%
2017	2.17%	5.53%
2018	2.17%	5.22%
2019	2.17%	4.91%
2020	2.17%	4.80%

. Additionally, in the subsequent robustness tests, we refer to Imai (2016) [53] and require consecutive annual losses rather than cumulative losses to implement stricter standards.

Figure 3 shows the average subsidy rate in different regions of China. After 2011, the intensity of government fiscal subsidies experienced a notable decline, consistent with the timeline of the 4 trillion investment plan in China to the end of 2010. This suggests that the stimulus policies significantly alleviated the survival pressures on enterprises. However, the policy effect was not durable. Between 2013 and 2020, the average subsidy rate gradually stabilized at a relatively consistent level. Moreover, compared to the full sample data, the subsidy rate for zombie firms was markedly higher, suggesting that local governments implemented targeted subsidy policies to zombie firms.

3.2.3. Control Variables

Referring to the existing literature, fiscal decentralization mismatch ratio (FD), openness level (FDI), technological disparity (Tec), regional economy (GDP), government scale (GovScal), employment level (Pop), and minimum wage level (Minwage) are used as control variables.

Among them, the fiscal decentralization mismatch ratio is the ratio of administrative decentralization to fiscal decentralization. Administrative decentralization is represented by the proportion of locally self-financed expenditures relative to total local fiscal expenditures, while fiscal decentralization is measured by the proportion of local government fiscal revenue to total fiscal revenue. The fiscal imbalance resulting from decentralized mismatches exacerbates the financial pressures on local governments, thereby intensifying their inclination toward regional protectionism. Openness level is the ratio of actual foreign direct investment utilized by each city in relation to its GDP. Within regions with greater openness to international trade, firms exhibit a stronger tendency to reorient their sales strategies from domestic to foreign markets. This trend can effectively counteract the adverse effects of local protectionism. Technological disparity is the ratio of each city’s per capita GDP to the national per capita GDP. Less developed local governments, facing competitive disadvantages in regional specialization, often resort to protectionist policies to boost strategic industries and achieve economic catch-up. Regional economy is the gross regional product. Government scale is the ratio of budgetary fiscal expenditures to its GDP. Employment level is the logarithm of year-end employment (in millions). Minimum wage level is the minimum wage (in millions). Considering the backdrop of significant labor market disequilibrium and pronounced structural employment challenges in China, the migration of working-age populations poses a substantial risk to regional industrial equilibrium. So, we introduce Pop and Minwage to control the effects of labor force mobility on DMI. Through preliminary analysis, we tested alternative specifications and retained variables that avoid multicollinearity issues. These choices of control variables were made to maximize both modeling fit and interpretability while maintaining a parsimonious specification.

The determinants of market segmentation are inherently complex, involving both objective conditions (geographical characteristics, regional economic development, and transportation infrastructure) and subjective factors (formal institutional arrangements and informal institutional constraints). While our model incorporates a comprehensive set of control variables, these may not fully account for all potential confounding factors. To mitigate concerns about omitted variable bias, we also implemented the 2SLS approach in the following robustness test.

3.3. Data Source

The data used in this study are sourced from the 2008–2020 China Tax Survey Database, China Municipal Statistical Yearbooks, CEIC Database, multi-regional input–output tables from the China Emission Accounts and Datasets (CEADS), and CNRD Database.

Following the methodology established by Cai and Liu (2009) [54], we conducted a data cleansing protocol on the tax survey database. This involved two primary exclusion criteria: first, the removal of observations containing non-positive values in critical financial indicators, specifically year-end total assets, annual operating revenue, year-end liabilities, year-end paid-in capital, and average annual employment figures; second, the elimination of observations demonstrating accounting inconsistencies, particularly those instances where reported year-end total assets were less than year-end current assets.

Additionally, to mitigate potential distortions caused by outliers, all variables in the study were subjected to a 1% winsorization at both tails of the distribution. This yielded a refined dataset that ensured the reliability and validity of subsequent zombie firm identification analyses. Finally, we collected an unbalanced panel dataset spanning 297 Chinese cities from 2010 to 2020.

3.4. Descriptive Statistics

Descriptive statistics for all variables are presented in

Table 2. Results of descriptive statistical analysis.

Variables	Sample Size	Mean	Standard Deviation	Min Value	Max Value
DIV	3070	0.038	0.023	0.016	0.167
TaxBefit_zom	3278	0.006	0.011	0	0.072
TaxBefit_all	3278	0.003	0.004	0	0.025
FD	3278	3.714	1.211	1.850	8.453
FDI	3278	0.018	0.019	0	0.091
Tec	3278	0.828	0.508	0.182	2.825
GDP	3278	7.193	0.993	4.835	9.817
GovScal	3278	0.220	0.163	0.071	1.091
Pop	3278	0.538	0.515	0.062	2.519
Minwage	3278	0.821	0.152	0.489	1.105

.

4. Empirical Results

4.1. Baseline Results

In

Table 3. Regression analysis results.

	DIV
Variables	(1)	(2)	(3)	(4)
TaxBefit_all	0.206	0.165
	(1.483)	(1.178)
TaxBefit_zom			0.096 **	0.089 **
			(2.178)	(2.012)
FD		0.000		0.000
		(0.130)		(0.137)
FDI		−0.004		−0.007
		(−0.088)		(−0.152)
Tec		−0.001		−0.001
		(−0.356)		(−0.389)
GDP		−0.007 **		−0.007 **
		(−2.000)		(−2.001)
Govscal		0.002		0.001
		(0.198)		(0.143)
Pop		−0.012 *		−0.012 *
		(−1.873)		(−1.880)
Minwage		0.019 *		0.019 *
		(1.721)		(1.697)
Year FE	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes
N	3070	3070	3070	3070
R2	0.156	0.161	0.157	0.162

Note: t-statistics within (), **, and * indicate significance at the 5%, and 10% levels.

, columns (3)–(4) are the regression results of ${TaxBefit\_zom}_{it},$ where column (4) has control variables added. The regression coefficients here are significantly positive, and one standard deviation increase in the government subsidy rate for zombie firms leads to a 2.58% increase in market segmentation (DIV). The statistics verified that the targeted subsidies provided to zombie firms have significantly exacerbated regional market segmentation and hindered the construction of DMI. Hypothesis 1 in Section 2.2 is therefore verified.

Columns (1)–(2) are the regression results of ${TaxBefit\_all}_{it}$, where column (2) has control variables added (fiscal decentralization mismatch ratio, openness level, technological disparity, regional economy, government scale, employment level, and minimum wage level). The regression coefficients here are not statistically significant, suggesting that the overall fiscal subsidies may have limited systematic impact on DMI, at least within our current model specification and sample period. This is similar to the findings of Clausen (2009) [39], that the relationship between fiscal subsidies and corporates is complex. This could be due to the diversity of subsidy implementation entities and policy objectives, introducing confounding factors that obscure the true effect. Further decomposition (like isolating fiscal subsidies specifically targeted at zombie firms) is therefore necessary. Additionally, the signs of control variables are also consistent with theoretical expectations.

4.2. Robustness Test

To ensure the reliability of our baseline regression, we performed a battery of robustness tests. The estimated results in

Table 4. Results of robustness test.

	DIV	DIV	DIV	FRI	TaxBefit_zom	DIV	TaxBefit_zom	DIV
Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
TaxBefit_zom	0.074 *	0.376 ***	0.086 *	−0.178 *		1.522 **		1.067 **
	(1.806)	(3.065)	(1.942)	(−1.751)		(1.970)		(2.314)
IV_2008					0.111 ***
					(3.530)
IV_2010							0.165 ***
							(5.477)
Wald F					12.460	2.147	29.990	2.620
Control variables	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
N	3070	3070	3026	3014	3069	3069	3069	3069

Note: t-statistics within (), ***, **, and * indicate significance at the 1%, 5%, and 10% levels.

conform the robustness of our findings.

First, we substitute the key explanatory variables (TaxBefit_zom): (1) The representativeness of total assets for service-oriented and technology-intensive enterprises is limited. So, we re-weighted the government subsidy rate aggregated at the regional level using net asset share (column 1); (2) The methodology employed to identify zombie firms may potentially overlook certain cases due to inherent limitations in screening criteria and measurement scales. So, we redefined the zombie firms as those experiencing three consecutive years of negative actual profits (column 2); (3) In order to mitigate potential effects arising from regional administrative hierarchies, we excluded samples from cities directly under the central government—Beijing, Tianjin, Shanghai, and Chongqing (column 3). The coefficients of TaxBefit_zom in columns 1–3 are significantly positive, supporting the stability of our findings.

Second, different measurement methodologies may introduce systematic discrepancies in the degree of market segmentation obtained. Therefore, we adopted the production structure method (Young, 2000) [52] for measuring market segmentation (column 4). The theoretical logic of this method is that higher DMI leads regions to choose production based on local factor endowments and comparative advantages, resulting in greater spatial concentration of specific factors. A higher value of this indicator indicates a higher level of DMI.

The equation for calculation is as follows:

$${FR}_r={\displaystyle \frac{1}{2}}{\displaystyle \frac{\sum _j\left\{\left|S_{rj}-\overline{S_j}\right|\times {\sum }_j^n{E}_{rj}\right\}}{{\sum }_{j=1}^n{E}_{rj}}}={\displaystyle \frac{1}{2}}{\sum }_{j=1}^n\left|S_{rj}-\overline{S_j}\right|$$

where ${FR}_r$ is the degree of DMI in region r calculated using the production structure method; $S_{rj}$ represents the proportion of employment in industry j to the total employment across all industries in region r; $\overline{S_j}$ is the corresponding proportion at the national level; $E_{rj}$ represents the number of employees in industry j within region r. The coefficient of TaxBefit_zom in column 4 is significantly negative, which similarly confirms that our baseline regression findings are robust. Specifically, a 10% increase in the government subsidy rate for zombie firms leads to a 1.78% decrease in DMI (FR), indicating that the higher the fiscal subsidy rate of zombie firms, the lower the level of regional specialization in production, and, consequently, the greater the inefficiency in DMI.

Finally, we employ the 2SLS approach to alleviate endogeneity. We use the interaction term between the region’s resource dependency in the initial period (years 2008 to 2010) and the zombie firms’ subsidy rate at the province level where the city located in the previous year as instrumental variables (columns 5–8). Resource dependency is measured as the proportion of the number of employees in the mining industry. Regions with higher resource dependency are more likely to allocate targeted subsidies [27], thus satisfying the correlation requirement (F-statistics > 10 in column 5 and column 7). The indicators from the initial period meet the exclusivity constraints. To introduce time-varying variation, referring to Duranton and Turner (2012) [55], we multiplied it by the provincial-level indicator in the previous year. The coefficients on TaxBefit_zom (1.522 and 1.067, respectively) are both statistically and economically significant. Therefore, we obtain a conclusion that the consistency in magnitude and significance across different IVs reinforces the causal interpretation of our findings.

5. Mechanism Analysis

Through the previous analysis, it can be seen that the subsidies provided by local government to zombie firms may hinder DMI through the combined effects of cost-shifting, innovation crowding-out, and resource misallocation, as shown in Figure 2. These mechanisms are verified by institutional trade costs, regional patent grants, and resource misallocation, respectively.

Institutional trade costs for each city are measured by the regression-based separation method [56]. This method leverages intercity trade networks and the Head–Ries index (derived from a gravity model) to isolate objective trade costs (e.g., distance) from total trade costs. The residual component is identified as the institutional costs of intercity trade. Column (1) in

Table 5. Mechanism analysis.

	Instcost	Lnpatent	Disrel
Variables	(1)	(2)	(3)
TaxBefit_zom	0.957 *	−3.458 ***	0.759 **
	(1.861)	(−3.340)	(2.129)
Control variables	Yes	Yes	Yes
Year FE	Yes	Yes	Yes
City FE	Yes	Yes	Yes
N	3278	3278	3278

Note: t-statistics within (), ***, **, and * indicate significance at the 1%, 5%, and 10% levels.

shows that the coefficient of TaxBefit_zom is significantly positive. Specifically, a 10% increase in the fiscal subsidy rate for zombie firms leads to a 9.57% rise in institutional costs, achieving near-complete pass-through of fiscal burdens, indicating that discriminatory fiscal subsidies implemented by local governments have effectively raised the institutional transaction costs for extra-regional goods entering their jurisdictions. To alleviate financial strain, local governments may transfer expenditure burdens to enterprises, especially those located outside their jurisdiction, thereby hindering interregional circulation. This fiscal cost transfer initiates a self-reinforcing cycle that disrupts interregional trade, diminishes local tax revenues, and intensifies fiscal pressures on local governments. It undoubtably poses significant threats to long-term fiscal sustainability.

Regional patent grants are the logarithm of the number of regional patent grants (in thousands). Column (2) in Table 5 shows that the coefficient of TaxBefit_zom is significantly negative. Specifically, a 1% increase in the fiscal subsidy rate for zombie firms leads to a 3.458-unit decrease in regional patent grants, indicating that subsidies allocated to zombie firms have profoundly suppressed regional innovation incentives. This phenomenon aligns with Bernini and Pellegrini’s (2011) [38] findings that excessive subsidies allocated to inefficient corporates will stifle innovation. Given the limited resources in each region, the persistence of zombie firms severely crowds out the profits and financial resources available to healthy enterprises. This scarcity constrains technological innovation in healthy firms, ultimately leading to a decline in regional product quality.

Resource misallocation is quantified by the standard deviation of TFP distribution for firms within each industry in every city. A weighted average of these standard deviations is then computed, using each industry’s share of the city’s total annual revenue as weights. A larger dispersion index indicates greater productivity disparities among enterprises, suggesting that inefficient firms have not been eliminated in accordance with market principles, thereby reflecting more severe resource misallocation distortions. Column (3) in Table 5 shows that the coefficient of TaxBefit_zom is significantly positive. Specifically, a 10% increase in the fiscal subsidy rate for zombie firms leads to a 7.69% rise in resource misallocation, indicating that the targeted subsidies undermined the regions’ resource allocation efficiency. This finding is consistent with Kwon et al. (2015) [17]’s early evidence from Japan.

6. Heterogeneity Analysis

6.1. Region Heterogeneity

China’s expansive territory is characterized by notable disparities in economic development levels, natural resource endowments, and institutional environments across various regions. To delve deeper into whether the influence of local protectionism, as exemplified by discriminatory fiscal subsidies, on DMI demonstrates regional heterogeneity, we perform subsample regressions. Following the classification criteria established by China’s National Bureau of Statistics, we categorize prefecture-level cities into eastern, central, and western regions. As shown in

Table 6. Region heterogeneity.

	Nationwide	Eastern	Central	Western
Variable	(1)	(2)	(3)	(4)
TaxBefit_zom	0.089 **	−0.115	−0.048	0.416 ***
	(2.012)	(−1.559)	(−0.695)	(5.165)
Control variables	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes
N	3070	1047	944	1079
R2	0.162	0.279	0.157	0.178

Note: t-statistics within (), ***, and ** indicate significance at the 1%, and 5% levels.

, the results are notably diverse in the different regions: while the coefficients of TaxBefit_zom in the eastern and central regions are not statistically significant, they are significantly positive at the 1% level for the western region. This suggests that government subsidies allocated to zombie firms in the western region are more likely driven by political motives centered on local protectionism, or that the relationship between local protectionism and market segmentation is more pronounced in this area.

6.2. Location Heterogeneity

With the ongoing evolution of economic globalization, China has become profoundly integrated into the global value chain division system. Considering the relationship between international trade and DMI, we use the distance to the nearest port as a proxy of a city’s cost of participating in international trade. Specifically, we introduce an interaction term between the subsidy rate for zombie firms and the logarithmic distance to the nearest port (TaxBefit_zom × lndis) into the baseline model. As shown in

Table 7. Location heterogeneity.

Variable	DIV
TaxBefit_zom	0.104 **
	(2.324)
TaxBefit_zom × lndis	0.289 **
	(2.026)
Control variables	Yes
Year FE	Yes
City FE	Yes
N	3070
R2	0.164

Note: t-statistics within (), ** indicates significance at the 5% level.

, the coefficient of the interaction term is significantly positive, suggesting that cities closer to ports experience a weaker market segmentation effect from targeted government subsidies. This implies that international trade may mitigate the adverse effects of the subsidies allocated to zombie firms. Cities near ports benefit from more convenient access to international trade, enabling firms to counteract the crowding-out effects of domestic local protectionism by increasing their engagement in international trade activities. Consequently, international trade circulation can alleviate the domestic market distortions, and thereby foster DMI.

6.3. Upstreamness Heterogeneity

The input–output network serves as a pivotal medium in shaping a unified market. The region’s role and position within the domestic value chain also significantly influence the formation of DMI. So, we introduce an interaction term between the subsidy rate for zombie firms and the city’s upstreamness in the domestic value chain (TaxBefit_zom × Up) into the baseline model. Upstreamness is calculated using data from the 2017 China city-level multi-regional input–output table provided by CEADs [57]. The equation for the calculation is as follows:

$${Up}_{rj}={\displaystyle \frac{\widehat{V}BB\widehat{Y}u}{\widehat{V}B\widehat{Y}u}}={\displaystyle \frac{\widehat{V}BX}{\widehat{V}X}}={\widehat{X}}^{-1}BX=\mathrm{G}\mathrm{u}$$

where ${Up}_{rj}$ is the upstreamness of industry j in region r; $\widehat{V}$ is the diagonalized matrix of value-added coefficients; B is the Leontief inverse matrix; $\widehat{Y}$ is the diagonalized matrix of final demand; X is the column vector of total output; G is the Ghosh inverse matrix; and u is a unit column vector. The upstreamness at the regional industry level is weighted by the output share to obtain the upstreamness at the prefecture level and city level, expressed as:

$$\overline{{Up}_i}={Up}_{rj}·{\displaystyle \frac{X_{rj}}{\sum _{j^{\prime }}{X}_{r{j}^{\prime }}}}$$

$X_{rj}$ represents the output of industry j in region r; $\sum _{j^{\prime }}{X}_{r{j}^{\prime }}$ is the total output.

As shown in

Table 8. Upstreamness heterogeneity.

Variable	DIV
TaxBefit_zom	0.068
	(1.501)
TaxBefit_zom × Up	0.191 **
	(2.017)
Control variables	Yes
Year FE	Yes
City FE	Yes
N	3070
R2	0.163

Note: t-statistics within (), ** indicates significance at the 5% level.

, the coefficient of the interaction term is significantly positive, suggesting that subsidies to zombie firms have a stronger negative effect on DMI in regions closer to the upstream. Upstream industries, such as metal smelting and non-metallic mineral products, are predominantly manufacturing sectors heavily reliant on natural resource extraction activities. These industries often exhibit monopolistic characteristics, with state-owned enterprises accounting for a relatively higher proportion. Consequently, in regions where these industries are concentrated, local governments are more inclined to use targeted subsidies, aligning political motives with local protectionism. This creates a situation where a larger portion of subsidies is driven by protectionist objectives, directly exacerbating market segmentation effects.

6.4. Financial Development Heterogeneity

Fiscal subsidies and bank credit support are the two major external factors contributing to the emergence and persistence of zombie firms [28]. To investigate the potential substitutability between these two forms of external support, we use the ratio of the year-end deposit and loan balances from financial institutions to the region’s gross product as a measure of regional financial development (Fin). A higher ratio indicates a more developed and extensive financial sector. We then introduce an interaction term between the subsidy rate for zombie firms and the city’s financial development (TaxBefit_zom × Fin) into the baseline model. As shown in

Table 9. Financial development heterogeneity.

Variable	DIV
TaxBefit_zom	0.127 ***
	(2.665)
TaxBefit_zom × Fin	0.086 **
	(2.090)
Control variables	Yes
Year FE	Yes
City FE	Yes
N	3070
R2	0.164

Note: t-statistics within (), ***, and ** indicate significance at the 1%, and 5% levels.

, the coefficient of the interaction term is significantly positive, suggesting that subsidies to zombie firms exacerbate market segmentation in regions with a more developed financial system. In these regions, local governments have less flexibility to support low-quality enterprises through preferential loan rates and therefore rely more heavily on fiscal subsidies. This, in turn, strengthens the effect of fiscal subsidies to zombie firms on DMI.

7. Further Analysis

To explore more potential pathways that can mitigate the negative effects of subsidies allocated to zombie firms and foster sustainable economic development, we investigate the roles of business environment and industrial structure upgrading. We employ the Herfindahl–Hirschman index (HHI) as a proxy for market environment, where a higher value indicates a less competitive environment, and the industrial structure upgrading index (ISUI) to assess the quality of regional industrial structure [58], where a higher value indicates a more advanced industrial structure. Then, we conduct grouped regressions based on a mean split of city–year values for each indicator.

Table 10. Further analysis.

	Low HHI	High HHI	Low ISUI	High ISUI
Variables	(1)	(2)	(3)	(4)
TaxBefit_zom	−0.077	0.243 ***	0.194 ***	−0.052
	(−1.459)	(2.743)	(2.833)	(−0.893)
Control variables	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
City FE	Yes	Yes	Yes	Yes
N	2051	1019	1499	1571
R2	0.176	0.164	0.149	0.215

Note: t-statistics within (), *** indicates significance at the 1% level.

shows that in regions with lower market monopolization and higher industrial structure quality, the adverse effects of zombie firms’ subsidy rate on market integration are no longer significant. Therefore, the endeavor of local governments to enhance business environment and upgrade the industrial structure can effectively mitigate the market fragmentation induced by such inefficient subsidies.

8. Conclusions and Policy Recommendations

8.1. Conclusions

Based on city-level panel data from China between 2008 and 2020, this paper empirically examines the impact of subsidies allocated to zombie firms by local governments on DMI and draws the following conclusions: First, targeted subsidies provided by local governments to zombie firms exacerbate regional market segmentation and hinder the process of DMI, which poses great challenges to sustainable economic development. Second, the mechanism analysis reveals that local governments may shift expenditure burdens to enterprises located outside their jurisdiction, leading to higher institutional trade costs and fiscal unsustainability. In the meantime, the persistence of zombie firms crowds out resources available to healthy enterprises and distorts the allocation of factor resources, thereby impeding the ability of local products to compete effectively in intercity markets. This phenomenon exhibits heightened intensity across multiple dimensions of regional heterogeneity: geographically disadvantaged western cities, inland areas with limited access to coastal ports, regions closer to the upstream within production value chains, and regions with more developed financial systems. Additionally, we find that improving business environments and upgrading industrial structure quality can alleviate the market fragmentation caused by such inefficient subsidies. This research establishes a critical link between DMI and zombie firms by investigating fiscal subsidies as a transmission tool, while uncovering the mechanisms through which zombie firm subsidies affect market fragmentation.

Our findings hold critical implications for sustainable development in emerging economies. By empirically demonstrating how subsidies to zombie firms exacerbate market fragmentation, this study reveals a core policy paradox: the tension between short-term local protectionism and long-term macroeconomic stability. This contradiction directly undermines progress toward SDG 8 (Decent Work and Economic Growth) and SDG 10 (Reduced Inequalities), particularly in developing economies where subnational distortions compromise national sustainability objectives. The resource misallocation perpetuated by zombie firm subsidies will not only jeopardize fiscal sustainability but also constrain overall economic sustainable development. Additionally, our proposed solution—business environment improvement—offers a pathway to reconcile these tensions through administrative efficiency gains. This institutional approach aligns with OECD principles of sustainable governance by enhancing market-driven resource allocation and inclusive growth mechanisms.

8.2. Policy Recommendations

Based on the above conclusions, this paper puts forward the following policy recommendations:

First, establish the primacy of central government-led industrial policy. Local government-led industrial policies often exhibit particularism and selectivity, inherently carrying protectionist intentions that tend to ignite competitive races for political achievements. Therefore, it is imperative to strengthen the dominance of central government-led industrial policies and enhance coordination among local governments. For instance, in addressing cross-regional public goods and services provision, a viable approach would be to establish public institutions through the voluntary devolution of certain administrative powers from local governments. However, central government-led industrial policy may encounter implementation gaps at the local level, particularly in less developed regions. The excessive centralization risks may also dampen local innovation vitality. Thus, while strengthening centrally led industrial policies, it is essential to strike a balance by accommodating regional disparities and combining delegation with regulation.

Second, strengthen the performance evaluation system for local government fiscal subsidies. A two-pronged approach is recommended. On the one hand, it is crucial to improve the transparency and accountability mechanisms of local government fiscal subsidies by publicly disclosing detailed information regarding subsidy recipients, purposes, amounts, and justifications, while simultaneously establishing robust public oversight and whistleblowing systems. On the other hand, a comprehensive performance evaluation and monitoring mechanism should be established for subsidized enterprises. This mechanism should incorporate multiple sustainable development targets, including environmental protection, production innovation, and regional cooperation, with appropriate weighting for each indicator. The system should rigorously assess the efficiency of subsidy utilization by recipient enterprises. For enterprises failing to meet sustainable standards, timely corrective measures must be implemented to prevent their degeneration into subsidy-dependent zombie firms. Nevertheless, it should also be noted that transparent fiscal subsidy mechanisms may face resistance from vested interest groups, thereby necessitating corresponding anti-corruption measures—as exemplified by the nationwide implementation of “Sunshine Public Finance” reforms.

Third, enhance industrial chain infrastructure in less developed regions. Less developed areas face significant infrastructure gaps, which not only fail to meet the threshold for attracting industrial relocation from eastern regions (the “peacocks flying west” phenomenon) but also create “tax havens” that result in inefficient use of fiscal subsidy funds. To address these challenges, it is imperative to substantially improve the infrastructure supply system in underdeveloped regions. Improving business environments and upgrading industrial structure quality in western cities will stimulate their motivation to integrate into the national unified market, ultimately promoting DMI and sustainable economic development. Given the substantial fiscal resources required for infrastructure investment, integrating green finance instruments—including special-purpose bonds and public–private partnership (PPP) arrangements—can effectively address fiscal sustainability challenges in less developed regions.

Fourthly, establish a market mechanism for unimpeded factor mobility. The impact of fiscal subsidies to zombie firms on DMI primarily operates through the channel of resource misallocation. To address this issue, the government should accelerate the establishment of a market mechanism that facilitates the free flow of production factors across regions and industries. This involves improving the human resources market system, enhancing the market’s decisive role in resource allocation, and eliminating institutional barriers to improve allocation efficiency. Simultaneously, the government should refine the labor-based distribution policy system by increasing the proportion of labor compensation in primary distribution. This can boost residents’ disposable income, thereby fully unleashing consumer potential. Such measures will stimulate intercity trade from the demand side, fostering deeper economic integration and sustainable economic development in the long run. However, the implementing of these recommendations may encounter challenges. In the short term, the free flow of production factors could potentially amplify regional disparities through the “Matthew Effect”. Less developed regions may risk falling into a “low-skill trap” if the compensatory mechanisms are absent. Therefore, a carefully sequenced pilot program should be implemented, potentially incorporating institutional innovations such as a Horizontal Fiscal Equalization Fund to promote sustainable development.

8.3. Research Limitations and Further Research Directions

While our study is among the first to bridge the gap between zombie firms and DMI, several limitations should be acknowledged. First, our reliance on city-level data may mask firm-level heterogeneity in subsidy allocation and competitive dynamics. Second, while our empirical framework centers on fiscal subsidies, other forms of institutional support for zombie firms—including preferential credit policies, regulatory forbearance, and tax payment deferrals—could also influence DMI. So, future research could productively explore the dynamic effects of zombie firms’ characteristics on DMI. Such analysis would elucidate the underlying mechanisms through which the elimination of inefficient entities like zombie firms enhances sustainable economic development.