Enterprise Spatial Agglomeration and Economic Growth in Northeast China: Policy Implications for Uneven to Sustainable Development

Abstract

Many countries and regions around the world are experiencing this development dilemma, and Northeast China is a typical representative. To explore the reason for the backwardness of Northeast China, we analyze the formation mechanism and efficiency of enterprise agglomeration in this research. Based on the panel data of 34 prefectural level or above cities in Northeast China and 241 citescities in other regions from 1999 to 2015, a fixed effects panel model is used, considering enterprise agglomeration, foreign direct investment (FDI), investment in fixed assets, and the non-agricultural industry structure. It is found that enterprise agglomeration has a highly significant negative impact on urban productivity in Northeast China, and this phenomenon of agglomeration diseconomy in the northeast is most significant among the four regions of the country. Furthermore, according to the moderation mechanism analysis, the enterprise agglomeration in Northeast China reduces the pulling effects of fixed asset investment and FDI on economic efficiency but enhances the promotion effect of the non-agricultural industry structure on urban productivity. After the robustness test and extension analysis, this study determines that the enterprise agglomeration in Northeast China does not effectively stimulate the driving role of investments. Finally, we discuss measures that can help resolve the current agglomeration diseconomy problem in Northeast China and achieve sustainable development.

1. Introduction

Many countries and regions around the world are facing imbalanced development problems, such as the difference in the level of socio-economic development between the north, south, and center of Italy [1], the pattern of rich west and poor east in Poland [2], and the gap between rich and poor regions caused by the rapid but uneven growth of urbanization in Thailand [3]. Regional imbalance has proven to be a serious obstacle to sustainable development [4,5]. Sustainable development targets three key dimensions of human existence (i.e., the economic, social, and environmental spheres) [6]. Addressing regional imbalances will become a crucial tenet for economic sustainability, which is one of the three pillars of sustainable development [7]. In China, an important aspect of regional imbalance is the decline of the northeast region. Exploring the reasons for the backwardness of the northeastern region, which is what this paper aims to investigate, can help explain China’s regional imbalance and thus promote China’s sustainable development.

In general, imbalances derive mainly from regional gaps in investments, industries, and technology. Such imbalances have become a gradually expanding chain, from investment to industry to technology, thereby resulting in a dual circle with vicious and virtuous effects. Regional efficiency has gradually become an important reason for investors to make choices. The higher the efficiency, the more investments there are and the better the optimal efficiency, and vice versa. As a state of high-density spatial agglomeration, enterprise clusters often play an effective role in developing and releasing regional efficiency, which is also known as spatial collaborative development. Ding et al. [8] found from a spatial perspective that industrial collaborative agglomeration can effectively promote regional development. Strengthening the spatial agglomeration of regional enterprises has gradually become a significant path for regional economic growth [9]. In recent years, the “new northeast phenomenon” in Northeast China has attracted extensive attention from every sector of society [10,11]. In 2015, the nominal GDP growth of Heilongjiang, Jilin, and Liaoning was −0.29%, 3.41%, and 0.26%, respectively, which was far below China’s average nominal growth rate of 6.3%. In addition, the average level and growth rate of agglomerations showed an overall steady increasing trend despite divergence in the three provinces. Heilongjiang had the lowest agglomeration level, which rose from 800 enterprises per 10,000 km² in 2011 to nearly 1000 enterprises per 10,000 km² in 2015. Liaoning had the highest agglomeration level, rising from 1200 enterprises per 10,000 km² in 2011 to nearly 1500 enterprises per 10,000 km² in 2015. Meanwhile, Jilin Province experienced the fastest growth, increasing 56% from 900 enterprises per 10,000 km² to 1400 enterprises per 10,000 km². The relevant data are calculated from the China Urban Statistical Yearbook [12] and the China Statistical Yearbook [13]. Obviously, the improvement of enterprise agglomeration levels in Northeast China does not result in relatively satisfactory economic efficiency. Therefore, this paper adopts a fixed-effects model to assess the impact of enterprise agglomeration on regional productivity, in order to provide a new perspective for solving the puzzle of the “new northeast phenomenon”.

The main contributions of this study are as follows: Firstly, we find evidence of agglomeration diseconomies in Northeast China. In contrast to several previous studies [11,14,15,16], our research on the effect of enterprise agglomeration on economic growth is a new attempt to provide an explanation for the regional decline in Northeast China. Secondly, this study fully demonstrates the interaction between enterprise agglomeration and internal-external investments in Northeast China and verifies that enterprise agglomeration has a significant reducing effect on investment efficiency. Thirdly, in the discussion section, it is further argued that in order to resolve the current agglomeration diseconomy problem in Northeast China and achieve sustainable development, a triple synergy of a reasonable industrial structure, a healthy business environment, and an interest-sharing mechanism between regions is required. This finding points to a way to revive the economy. Most importantly, this conclusion provides an effective reference for areas around the world that have the same characteristics.

The rest of this paper is laid out as follows: Section 2 reviews the literature on agglomeration economies, and Section 3 presents the theoretical mechanism and research hypotheses. Section 4 describes the methodology. Section 5 and Section 6 provide the empirical results and discussions, respectively. Finally, Section 7 concludes the study.

2. Literature Review

As cities grow, scale economies, which Marshall [17] called agglomeration economies, develop. Marshall discussed the causes of this phenomenon, including labor market sharing, the specialized intermediate input product market, and knowledge spillover externalities. Subsequently, academia called this viewpoint “Marshall externalities,” which posits that agglomerations can play a positive role in improving economic production efficiency through the effect of positive externalities. Jacobs [18] further enriched the causes of agglomeration economies from the perspective of diversification externalities, claiming mainly that enterprises’ labor force will become increasingly diversified and the knowledge spillover effect among industries will increase. As a result, the findings on externality theories inside and outside enterprises gradually formed an important theoretical basis for agglomeration economies [19,20,21]. At the same time, agglomeration economies were gradually confirmed in extensive empirical research and accepted as a major driving force in regional economic development [22,23,24].

City agglomeration diseconomies also exist but have long been neglected [11,25,26,27]. Industries are the leading factors of agglomeration, and whether an industry can form agglomeration synergy determines agglomeration economies [28,29]. Ohlin [30] proposed a theory of trade comparative advantage, stating that general location theory should be considered. The agglomeration process can improve production efficiency and reflect its advantages. With the expansion of production scale, the formation of increasing returns will accelerate, and an industrial situation of monopolistic competition will emerge [31]. When regional development advantages are formed, overdependence on advantages and other systems and mechanisms derived from such advantages will occur, which in turn can interfere with the release of new agglomeration economies. The capital creation model proposed by Baldwin [32] is the first to explain this interference effect. An interactive promoting effect exists between economic growth and location, and capital expenditure tends to form an economic “subsidence area” under the gravity of structural advantages. Wang et al. [33] found that the colocation of large firms contributes significantly to productivity. Structural advantages depend mainly on the agglomeration of large firms, which should be in a satisfactory system and mechanism environment. System and mechanism flaws will increase the cost of factors flowing between regions, thereby making the improvement of the agglomeration effect difficult. This outcome is observed because the skilled workforce can be easily influenced by an ineffective system [34,35]. The more rigid the system, the more difficult it is to improve the quality of the market and business environment. According to several studies, the business environment tends to cause an “overall downturn” and a “wave phenomenon” in the regional investment environment [36]. Moreover, the business environment will generate unreasonable expectations for the entry of factors. Thus, attaining an optimal degree of agglomeration and stimulating the agglomeration’s economic effect are difficult. Hence, agglomeration will perform differently in different regions [37]. This finding provides a study reference for considering regional economic growth from the perspective of agglomeration.

Specific to the northeastern region of China, most related studies explained the reasons for the slow economic growth from the perspective of advantages and structures. Several studies have posited that the land supply policy is a barrier against agglomeration economies [38]. Development advantages will gradually form a “rivet effect”, which is crucial to the stable balance of the entire ecosystem. In the northeastern region, industries have played a leading role for a long time. Path dependence and structure-locking situations generally make this region less resistant to risks compared with other regions. For example, in 2016, negative growth was recorded in the production value of secondary industries in the northeastern old industrial base, which was far lower than the national average. The main reason for this finding is that the northeastern region cannot meet the expansion or transformation conditions of development advantages during times of advancement and development. The lagged development of high-end service sectors will considerably hinder the agglomeration efficiency improvement of the service industry. Financial and other producer services lack effective follow-ups, and the development of the manufacturing industry cannot form an effective auxiliary thrust; thus, existing cluster economies experience difficulties achieving high-quality development. Therefore, the advantages of regional development in this new era require the integration of the manufacturing industry and the service industry, and the lag of either industry will restrict the further improvement of these advantages.

In summary, previous studies demonstrated the following limitations: First, agglomeration diseconomies have long been ignored when explaining the slow regional economic growth, especially the puzzle regarding the northeastern region of China. Second, investigations on the agglomeration efficiency of enterprises in the northeastern region are inadequate, which is a prerequisite that cannot be solved in the process of attracting investments. Third, the interaction effect among enterprises as important economic subjects is not fully discussed, which has considerable significance for the value enhancement of the industrial chain. Based on the aforementioned limitations, this study first explores the problem of economic growth in Northeast China from the perspective of agglomeration diseconomies. Then we attempt to analyze the reasons for agglomeration diseconomies and demonstrate the interaction between enterprise agglomeration and internal and external investments. Finally, we conclude with recommendations for reversing agglomeration diseconomies and achieving sustainable economic growth in Northeast China.

3. Theoretical Mechanisms and Research Hypotheses

3.1. Conflicting Manifestations of Investment in the Enterprise Agglomeration Process

Fujita and Thisse [39] expounded on the theory of agglomeration systematically, positing that the important dependent mechanism of agglomeration economies is the twin engine of structural change and factor movement. Investments are the most critical driving factors for ensuring the continuous evolution of structures and elements. New investments can lead to new industry entries, new economic growth, and new factor inflows. However, if investment conflicts exist, then agglomeration can amplify such conflicts and directly result in a decrease in investment efficiency.

Structural conflict in investment indicates low matching between investments and factor endowments in a target region during the investment process. Thus, enterprise agglomeration will aggravate the degree of distortion in the factor market. Structural problems can be classified as rationalization and elevation. The former focuses on factor allocation efficiency, whereas the latter emphasizes the status of industrial upgrading. Overall industrial allocation efficiency in labor, capital, and technology will directly affect the operating efficiency of the economy. In a state of industrial agglomeration with low production factor allocation efficiency, knowledge spillover among enterprises will be reduced substantially, thereby leading to adverse learning effects. Such effects can make attaining agglomeration economies and expanding agglomeration diseconomy tendencies difficult.

Furthermore, the upgrading of the industrial structure will directly cause important engine thrust to be lost, and a high-level market pattern will not be formed, which will discount the policy effect to drive industrial upgrading and further embed structural problems.

Investments lead to conflicts. The leading conflict of investment refers to the situation in which an investment is either considerably deviated from the regional sunrise industry in the medium or long term or substantially dependent on the original sunset industry. Regional economic development often demonstrates path dependence, that is, excessive dependence on the original advantageous industries. The development advantage problem refers to the situation in which scarce traditional advantages are consumed blindly in the process of economic development instead of grasping the frontier of the times. New highlights in economic development and new impetus for economic growth are lacking. Advantages mainly derive from resources, geographical features, locations, and so on, which can support related industries to develop into characteristic economies. Meanwhile, the formation of characteristic economic cities or regions will accumulate brand effects in the long-term development process. Although the formation of brand effects can better attract talents, capital, and enterprises for regional development, it tends to form stereotypical thinking and fall into a single mode of development. In this case, enterprise agglomeration cannot develop an effective layout with complete structures and categories and generate the spillover effect. On the contrary, it will form small and inefficient enterprises, thereby generating huge resource waste. If so-called “advantageous industries” are allowed to gather and develop in a disorderly manner, then a region will likely experience a single-economic situation, thereby restricting the release of regional agglomeration vitality.

Thus, we propose Hypothesis 1 as follows:

Hypothesis 1 (H1).

The improvement of the agglomeration level in Northeast China will aggravate the decline of investment efficiency, and the improvement of the investment level will further restrict the formation of agglomeration economies owing to the existence of conflicts, which can lead to the emergence of agglomeration diseconomies in the northeastern region.

3.2. Efficiency Release at the Level of Agglomeration and Openness

The long-term unsatisfactory economic growth in Northeast China will send pessimistic signals to the outside world, thereby accumulating such signals in the process of enterprise agglomeration and accelerating the spillover effect. This converse consequence, together with the long-standing rigidity of the system and mechanism, will generate an ineffective business environment. Furthermore, an ineffective business environment will cause rigid and conservative problems in a series of areas, such as the employment direction and learning status of local personnel. Business environment problems tend to lead to rent-seeking behavior in the government, conservative enterprises, and lax personnel, which can cause guidance deviation in government policies and poor motivation in enterprise and public innovations [40]. In the process of leading effects and interactive feedback, an unhealthy business environment in the government, enterprises, and the public will develop into a “chronic disease” of economic development, affecting the spirit and social evaluation of a city or region. When foreign investments appear, emerging producers encounter difficulties developing innovations in environments fraught with speculation, thereby blocking their ability to drive self-innovation and resulting in a large decrease in the learning effect. The agglomeration effect will further reduce the learning effect, amplify speculation owing to business environment problems, and hamper the productivity improvement of the economy. Therefore, we propose the following hypothesis:

Hypothesis 2 (H2).

The agglomeration level of Northeast China has a decreasing effect on the efficiency of opening up, which in turn will have difficulties improving agglomeration efficiency.

When these two types of problems are interwoven, forming a geometric acceleration effect on agglomeration diseconomies is easy, and the initial starting point is the interaction between regional institutional mechanisms and the business environment. Failing to establish an incentive mechanism for innovation and entrepreneurship will result in a conservative atmosphere. Through mutual transmission among enterprises, the business environment will eventually lead to the continued spread of so-called “insurance” competitive industries in the region. However, the emergence of venture capital that can provide new driving forces for regional development will be difficult. Therefore, the formation of a single structure will accelerate and lead to a structural breakthrough obstacle, thereby making the effective attainment of structural optimization difficult. In the context of this structure as an important “region calling card,” shifting ethos and mechanisms is extremely challenging (see Figure 1 for details).

4. Methodology

4.1. Investigation Area

According to “the Opinions of the CPC Central Committee and State Council on the Promotion of the Rise of the Central Region” and “the Opinions of the State Council on the Implementation of Policies and Measures for the Great Development of the West”, mainland China is divided into four regions, namely, northeastern, eastern, central, and western. The specific divisions are presented in Figure 2. The northeastern region consists of Heilongjiang Province, Jilin Province, and Liaoning Province.

Our main reason for selecting the northeastern region as our investigation area is its high potential for agglomeration diseconomies. The northeastern region is gradually experiencing a growth dilemma, which is a puzzle that is difficult to explain. The current situation is in stark contrast to the situation before the 1990s, when the economy of the northeastern region was a very important part of the country. However, it worsened gradually each year after this period. Specifically, the region’s economic growth rate is at the bottom, which is difficult to understand. Finding a new power supply for the northeastern region has become a valuable research topic. Scholars have yet to consider this question from the angle of agglomeration. Agglomeration diseconomies likely lead to waste elements, which can be an obstacle to economic growth.

4.2. Model Setting

In this study, the agglomeration effect model of urban productivity in the northeastern region of China is set as follows:

$$u{y}_{it}={\beta }_0+{\beta }_{1}e{d}_{it-1}+{\beta }_{2}ui{a}_{it}+{\beta }_{3}ui{s}_{it}+{\gamma }_j{\displaystyle {\sum }_j{w}_{jit}}+{\epsilon }_{it}$$

(1)

where $u{y}_{it}$ is the productivity of the city $i$ in year $t$; $ed$ is the agglomeration level of enterprises; $uia$ is the level of industrial diversification in a city; $uis$ is a city’s industry specialization level; and $w_{jit}$ is the $j$-th control variable in a city $i$ at the first level in a year $t$. The control variables are as follows: $li$ represents investment in fixed assets per worker; $fdi$ is actual foreign investment; $hc$ is human capital (education expenses per student); $nar$ is the employment proportion of non-agricultural industries; $sea$, $pc$, and $rc$ are three dummy variables indicating whether a city is a coastal city, an administrative center city, or a resource-driven city, respectively; and ${\epsilon }_{it}$ is the random error term. In addition, $uy$, $ed$, $uis$, $li$, $fdi$, and $hc$ are processed logarithmically to match the data magnitude.

4.3. Variable Selection, Data Source, and Processing

The explained variable is urban non-agricultural productivity per worker. The average productivity of non-agricultural labor pays attention to the development efficiency of secondary and tertiary industries to better highlight the level of urban development and depict the level of economic modernization. The core explanatory variable is the number of industrial enterprises over the designated size per km² within the built area. Enterprises are the microsubjects of economic operations; thus, the number and agglomeration degree of enterprises indicate the economic agglomeration degree at the microlevel (

Table 1. List of Variables.

Symbol	Name	Calculation Method
$uy$	Urban productivity	Nonagricultural GDP/nonagricultural employment
$ed$	Enterprise density	Number of industrial enterprises over the designated size/built-up area
$uia$	Urban diversity level	See the body
$uis$	Level of urban specialization	See the body
$li$	Fixed asset investment level	Fixed asset investment/nonfarm employment
$fdi$	Foreign direct investment	Actual level of foreign investment
$hc$	Human capital	Expenditure on education/number of students
$nar$	Nonagricultural industry proportion	Proportion of nonagricultural output in municipal GDP
$sea$	Whether a city is coastal city	Dummy variable; 1 if a coastal city, and 0 otherwise
$pc$	Whether a city is an administrative center	Dummy variable; 1 if the provincial capital, and 0 otherwise
$rc$	Whether a city is a resource-based city	Dummy variable; 1 if a resource-based city, and 0 otherwise

).

Urban diversification represents the diversity and uniformity of the industrial structure, which can be calculated using $ui{a}_i=1-{\displaystyle {\sum }_{i=1}^n{\left(p_{ij}-p_j\right)}_X^2}$, where $p_{ij}$ is the ratio of employment in the $j$ industry to the total employment rate of the city $i$, and $p_j$ is the ratio of employment in the $j$ industry in the city $i$ to the total employment rate in the $j$ industry of the entire country. Moreover, $0\le ui{a}_i\le 1$, and the closer to 0, the higher the degree of urban industry specialization, and conversely, the higher the degree of urban industry diversification. This study uses primary, secondary, and tertiary industries to solve the proposed model, mainly by focusing on the collocation index of the three types of industries in a city. The industry specialization index represents the specialization degree of an industry in a city. Glaeser et al. [41] believed that the relative specialization level could improve urban productivity and be used as a proxy variable for the specialization level of the manufacturing industry. In China, manufacturing employment records began only after 2003; thus, we use the specialization degree of secondary industries.

The control variables include fixed asset investment per labor, the actual amount of foreign investments, education expenditure per student, the proportion of non-agricultural industries, and whether a city is a coastal city, an administrative center city, or a resource-based city. Whether a city is a coastal city, an administrative center city, or a resource-based city represents dummy variables to distinguish the three types of cities. An administrative center city is the capital city of a province or autonomous region; coastal cities are set according to the definition in the 2016 China Marine Statistical Yearbook [42]; and resource-based cities were first confirmed in the National Sustainable Development Plan for Resource-Based Cities (2013–2020) [43], which was issued by the State Council in 2013, representing cities with mineral processing and mining, forest, and other natural resources as their leading industries.

The data used in this study are from the China Urban Statistical Yearbook [12] and the China Statistical Yearbook [13]. The data processing steps are described as follows: (1) Time period of data: data from 1999 are collected. On the one hand, the statistical caliber of some indicators changed in 1998; thus, data integration before and after this year is impossible, and specific statistical details are not explained. Hence, we could not match the data. On the other hand, after the reform of state-owned enterprises in China in 1998, a large difference was seen in the number of enterprises. In other words, the important event of reform affected the agglomeration calculation; thus, the data before and after this event are not comparable. In addition, the promotion and practice of the green development concept after 2015 have profoundly affected the traditional industries in Northeast China. This shock will promote the optimization of industrial structure, which is closely related to industrial agglomeration. The test for agglomeration diseconomies in Northeast China may be disturbed, so it is more valid to use data before 2015. (2) The statistical caliber of the number of enterprises: the statistical caliber of enterprises above the designated size changed during three periods, that is, from 1999 to 2004, from 2005 to 2010, and from 2011 to 2015. Thus, conducting a regression at different stages is necessary in the econometric analysis. (3) Administrative area: administrative areas are divided into municipal districts, the entire city, and built-up areas. A built-up area refers to an area developed and constructed as a whole, where municipal and public facilities are located. The present study used the built-up area to solve the employment density problem. This method avoided the problem of underestimating the agglomeration effect of cities with large administrative areas and accorded with the connotation of an agglomeration economy. (4) Price adjustment: the GDP is adjusted to the level of constant prices in 1999 using the GDP index. If not explained below, then the same treatment is employed if the price needs to be adjusted. Actual foreign investments are converted using the RMB annual exchange rate published in the China Statistical Yearbook [13], and the GDP index is used for deflating. The average wage of employees is deflated using the consumer price index of various regions in accordance with unchanged prices in 1999. (5) Human capital: the human capital indicator is expressed as education expenditure per student. Owing to the gradual increase in the categories in the statistics, only the number of students in colleges and universities, the number of students in ordinary middle schools, and the number of students in primary schools are used for consistency. The level of education expenditure is deflated using the GDP index. (6) The influence of hysteresis: considering the lagged effect of foreign direct investment (FDI) and fixed asset investment on urban productivity, the data of one lagged phase are adopted in the subsequent econometric analysis.

5. Empirical Results

5.1. Test of Enterprise Agglomeration Diseconomies

Based on the Hausman test, among the regression data in the three periods, the test results were 137.35 and prob > chi-square value = 0.0000, which are highly significant and support the existence of fixed effects. Therefore, a fixed-effects model should be used for the regression analysis.

Table 2. Regression results of the effect of enterprise agglomeration on urban productivity in Northeast China.

Variable	1999–2004	2005–2010	2011–2015
$e{d}_{t-1}$	−0.1724 *** (−3.34)	−0.1272 *** (−3.15)	−0.2086 *** (−3.97)
$uia$	−0.2084 (−0.34)	0.6717 (1.31)	−0.2465 (−0.33)
$uis$	−0.2287 *** (−3.73)	−0.2021 *** (−3.70)	−0.2282 *** (−3.13)
$l{i}_{t-1}$	0.4617 *** (8.04)	0.4537 *** (11.19)	0.5225 *** (6.78)
$fd{i}_{t-1}$	−0.0052 (−0.39)	−0.0147 (−1.43)	−0.0321 * (−1.81)
$hc$	−0.1482 * (−1.91)	0.0183 (0.23)	−0.0803 (−1.06)
$nar$	−0.0045 (−0.75)	−0.0001 (−0.03)	0.0129 *** (3.06)
$sea$	0.2753 *** (3.02)	0.0878 (1.29)	−0.1661 * (−1.82)
$pc$	−0.2130 (−1.29)	−0.4497 *** (−3.40)	−0.7521 *** (−4.10)
$rc$	0.0776 (0.98)	0.0133 (0.24)	−0.0641 (−0.92)
$constant$	13.6402 *** (12.21)	11.2228 *** (13.50)	11.7023 *** (9.21)
$R_{}^2$	0.4331	0.5540	0.4886

Notes: *** and * denote significance at the 1% and 10% levels, respectively, with t-values in brackets. The $R_{}^2$ equation indicates the goodness of fit of the population. All the results are those under the robust standard error, which are the same as those below.

shows the effect of enterprise agglomeration on urban productivity in 34 prefecture-level cities in Northeast China. Obviously, enterprise agglomeration has a highly significant negative impact on urban productivity during all periods and tends to increase during recent periods. This finding shows that enterprise agglomeration in Northeast China hinders, rather than accelerates, the promotion of urban productivity. Enterprise agglomeration results in the congestion effect instead of the positive spillover effect, thereby providing evidence for the basic hypothesis of the agglomeration diseconomies of enterprises in Northeast China. This may be due to the fact that enterprise agglomeration in the Northeast has not been effective in promoting the expansion of the horizontal scale of firms, i.e., the deepening of the division of labor. It is a general principle of Division of Labor Theory (DT) that the deepening of the division of labor leads to an increase in the efficiency of production. Tirole [44] pointed out that the size of an enterprise has two meanings: first, the size of the quantity of the same product that an enterprise produces over and over again (the horizontal size of the enterprise); and second, the number of production chains contained within the enterprise (the vertical size of the enterprise). Horizontal scale expansion and vertical scale contraction of firms help to achieve economies of scale and thus gain a competitive advantage for cluster industries [45]. Enterprise agglomeration in the Northeast may not have had this positive impact.

The impact of industrial diversification is not significant, but the impact of industrial specialization on urban productivity is highly significant. This finding suggests that the industry specialization degree of a city in Northeast China contributes substantially to productivity growth. However, this finding also reflects the problem of the single-industry structure from another angle. The single-industry structure plays a large role in promoting economic development during a period of industrialization [46]. However, with the improvement of the urbanization level, the unitary structure will gradually become the bottleneck in urban development. The existence of a single structure in the northeastern region is due to long-term dependence on traditional advantageous industries and the lack of the introduction and attempt of new business forms. For example, in this region, the heavy industry is the supporting industry, which results correspondingly in the disregard of the development of the light industry, high-tech industry, productive service industry, and so on.

Fixed asset investment shows a significant positive impact. The driving effect of fixed asset investment on urban productivity further demonstrates that Northeast China “prefers hard power to soft power” and relies on investment for long-term driving rather than absorbing key technologies and concepts to improve quality and efficiency. Therefore, long-term investment accumulation forms a large proportion of facility stocks. However, the subsequent growth of investment returns is typically weak owing to low turnover.

FDI has a negative influence but is significant in one period. Similarly, the significance level of human capital is low and negative in two periods. Obviously, foreign capital investment and human capital have little or a contradictory effect on urban productivity in the northeast, which is inconsistent with the current starting point of overall economic growth. Through large amounts of foreign investment and human capital, developed coastal areas rapidly promoted economic growth, invigorated the regional economy, and attracted numerous factor-personnel enterprises to cluster. This situation in Northeast China highlights the lack of openness and scarcity of human capital.

In addition, city type has a certain influence on urban productivity. In the first two periods, the coastal city type had a positive promotion effect on urban productivity, which had a significant influence during the period of 1999–2004 but was negative from 2011 to 2015. This result indicates that the enhancement advantage in the productivity of coastal city development is gradually disappearing. The influence of the administrative center city type is consistently negative and highly significant in the latter two periods, with an increasing trend. The influence of the resource-based city type also changes gradually from positive to negative but is not significant. This finding also demonstrates that cities with advantages in terms of geographical location, political status, and resource endowments cannot sustain the model promoting urban development through their own advantages.

5.2. Regional Comparison

We perform the same regression for 241 cities at the prefectural level or above in the other three regions to compare regional variations in the agglomeration effect between Northeast China and the other regions and clearly define the differences and gaps. The regression results in

Table 3. Coefficient comparison of the agglomeration effect on productivity between Northeast China and other regions.

Region	1999–2004	2005–2010	2011–2015
Eastern	0.0059 (0.22)	−0.0461 * (−1.94)	−0.0040 (−0.16)
Central	0.0215 (1.05)	−0.0053 (−0.23)	−0.0098 (−0.28)
Western	−0.0367 (−1.25)	−0.0233 (−1.03)	−0.0219 (−1.10)
Northeastern	−0.1724 *** (−3.34)	−0.1272 *** (−3.15)	−0.2086 *** (−3.97)

Notes: *** and * denote significance at the 1% and 10% levels, respectively, with t-values in brackets. Owing to space limitations, only the coefficient of enterprise agglomeration is reported, and the other regression results are collated.

show that in the four regions, the negative effect of enterprise agglomeration on urban productivity is highest in Northeast China and far higher than that in the other three regions. This finding indicates that enterprise operations in Northeast China exhibit serious agglomeration diseconomies, which may be an important cause of the current serious lag in the economic development of the region. The following section analyzes the transmission mechanism of enterprise agglomeration on urban productivity through the interactive terms of enterprise agglomeration, fixed asset investment, FDI, and industrial structure to assess the practical causes of agglomeration diseconomies more concretely.

5.3. Mechanism Analysis

As shown in

Table 4. Regression results of interaction terms between enterprise agglomeration and major variables.

Variable	1999–2004	2005–2010	2011–2015
$lne{d}_{t-1}\times lnl{i}_{t-1}$	−0.2345 *** (−2.73)	−0.1817 *** (−3.21)	−0.1832 (−1.36)
$lne{d}_{t-1}\times lnfd{i}_{t-1}$	−0.0212 (−0.94)	−0.0471 *** (−2.77)	0.0126 (0.41)
$lne{d}_{t-1}\times na{r}_t$	−0.0002 (−0.03)	0.0210 *** (3.42)	0.0330 ** (2.21)

Notes: *** and ** denote significance at the 1% and 5% levels, respectively, with t-values in brackets.

, the coefficients of the interaction terms between agglomeration and fixed asset investment are negative and relatively high. This result indicates that enterprise agglomeration can reduce the pulling effect of fixed asset investment on urban productivity, thereby verifying Hypothesis 1. Generally, the greater the density of local enterprises, the better the supporting infrastructure needed to ensure their efficient operation, and accordingly, the greater the amount of fixed asset investment. The pulling effect of fixed asset investment on urban productivity is that it can stimulate employment, drive production, and improve efficiency. Especially in less developed countries, the attraction of investment is seen as a motor for regional development. Investors bring not only financial capital but also technology and knowledge. In Northeast China, the agglomeration effect of fixed asset investment on the growth promotion of urban productivity is decreasing, which directly indicates that agglomeration affects the intermediary mechanism of fixed asset investment on productivity growth. Fixed asset investment is an important source of regional development advantages and a major driving force of regional transformation and advancement. This finding indicates that the northeastern region has yet to achieve a satisfactory transformation of its developing advantages and demonstrates serious “path dependence” on its original development advantages. Only one of the three periods shows significant interaction coefficients between agglomeration and FDI, and two periods have negative coefficients, thereby indicating that the negative effect is substantial. In other words, enterprise agglomeration also reduces the effect of FDI on urban productivity; thus, Hypothesis 2 is verified. FDI differs from short-term investment behavior. The former is a long-term choice for decisions made typically based on the long-term analysis of the investment region. If the external investment condition is satisfied, then the internal operation mechanism will dictate long-term investment success. Improvement of the enterprise agglomeration level can create an active environment for FDI, but the premise involves a system and mechanism for fully releasing the vitality of enterprises. As Northeast China is influenced most by the planned economy system, its property rights system and industrial structure remain from the 1950s and 1960s. This finding leads to the slow development of private capital in the northeast. During the first half of 2019, private investments in Liaoning increased 5.1% year on year but remained lower than the national average. In 2018, the northeastern region accounted for only nine enterprises in the top 500 private enterprises in China. Without reform in the property rights system, numerous zombie state-owned enterprises could not be revitalized, large-scale enterprise agglomeration would devour the established “agglomeration effect,” and recovering long-term FDI returns would be impossible and eventually become the embarrassing situation of forced withdrawal. Obviously, a poor business environment could result in low foreign investments and rigid institutional frameworks, which can also hinder the expansion of foreign investments. In other words, the business environment and institutional mechanisms have become major obstacles.

The two coefficients of the interaction terms between enterprise agglomeration and the non-agricultural industrial structure are significantly positive, thereby indicating that enterprise agglomeration can enhance the promotion effect of the non-agricultural ratio in the industrial structure on urban productivity. Enterprise agglomeration in Northeast China cannot generate benign growth in the manufacturing industry but can do so in the service industry, especially the productive service industry. Therefore, enterprise agglomeration promotes the development of the service industry. The development of the productive service industry can increase efficiency in industrial production, whereas the development of the consumer service industry can further raise productivity by improving consumers’ moods, stimulating consumers’ work enthusiasm, and improving work efficiency through the promotion of the quality and convenience of consumption.

Obviously, agglomeration narrows the efficiency-enhancing effect of fixed asset investment and FDI but can be improved through the service industry. However, as fixed asset investment and FDI have a strong impact on urban productivity, the efficiency improvement from the service industry cannot offset the decline effect of fixed asset investment and FDI; thus, the net effect of agglomeration on urban productivity remains negative.

5.4. Robustness Test

To test the model’s robustness, population density $n{a}_{t-1}$ is used as the explanatory variable and performed with one lag phase. The robustness test is conducted on the productivity effect of agglomeration in Northeast China. The population density unit is the size of the population per unit area in an urbanized area. The results are shown in

Table 5. Robustness test results.

Variable	$\mathit{n}{\mathit{a}}_{\mathit{t}-1}$	$\mathit{u}\mathit{i}\mathit{a}$	$\mathit{u}\mathit{i}\mathit{s}$	$\mathit{l}{\mathit{i}}_{\mathit{t}-1}$	$\mathit{f}\mathit{d}{\mathit{i}}_{\mathit{t}-1}$	$\mathit{h}\mathit{c}$	$\mathit{n}\mathit{a}\mathit{r}$	$\mathit{o}\mathit{b}\mathit{s}$
coefficient	−0.1634 *** (−3.31)	0.8307 *** (3.05)	0.7257 *** (10.95)	0.0679 * (2.58)	0.0068 (1.28)	−0.0158 (−0.81)	0.0281 (9.42)	475

Notes: *** and * denote significance at the 1% and 10% levels, respectively, with t-values in brackets.

. The agglomeration regression coefficient is −0.1634, which is very close to the empirical results above and highly significant. This finding further indicates that the negative effect of agglomeration in Northeast China is significant, and the conclusions of this study are robust.

6. Discussion

Compared with previous studies, we obtained evidence on agglomeration diseconomies using samples from Northeast China. Our conclusions provide new growth insights into the northeastern region and push for improved collaborations between the three provinces. In contrast to previous studies, we regard entrepreneurial employment agglomeration as the core measurement variable, and the effectiveness of our conclusions meets the field of production. By contrast, agglomeration is examined mainly from the holistic perspective of a city, and the conclusions are based on the liquidity of populations [47,48]. Unfortunately, these data cannot reflect actual productive activity. Some scholars tried to use hukou and non-hukou residents to overcome this problem [11]. In addition, the conclusion of becoming either relaxed or strict is from the perspective of city agglomeration. Hence, the conclusions in this study are from the production angle. We provide several meaningful recommendations below.

Only in the normal state of agglomeration economies can investments pour in and enterprises set up camp with ease. Furthermore, the questions become: how to resolve the current agglomeration diseconomy problem in Northeast China, and what measures should be taken to achieve agglomeration economies? Based on previous findings, this study believes that a reasonable structure, a healthy business environment, and mutual benefits are the three necessary conditions.

6.1. Optimising the Industrial Structure

Typical problems of the economic structure in Northeast China involve the poor vitality of the private economy, the limited power of the state-owned economy, and the lack of sharing in the emerging economy. Hu et al. [49] found that upstream industries contribute substantially to agglomeration economies, which are satisfactory emerging economies. As a result of the above factors, industry development remains completely undynamic, similar to stagnant water without a healthy or large cycle. As the traditional industrial base, a large number of traditional and resource-based industries have formed agglomerations, which produce a historical burden rather than a source of the spillover effect. Single attributes and enterprise types require considerable effort in terms of structure transformation. “Time-honored brands” require deep and effective integration with the new economy to create a second spring of industrial development. The relocation and renovation of old industrial zones should be accelerated to rebuild industrial bases or development zones around cities and to optimize and combine the spatial distribution of old industries. The original advantageous technology of resource industries should be linked with new-generation technology, such as big data and AI, and matched with deep and wide market demands to further push innovation forward and continuously strengthen the connections between the innovation chain and the industrial chain, service chain, and capital chain [50]. In addition, the development of new products, new industries, new organizations, new forms of business, and new systems should be accelerated under the leadership of the market. The establishment of new industrial parks may influence the spillover effect of factors and technologies and further promote the agglomeration effect. In fact, the agglomeration of highly skilled workforces that new industries need can present human capital externalities [19,22,51,52]. In addition, supporting network facilities and traffic rates in and out of urban areas are important aids in the formation of the agglomeration effect after the optimization of the enterprise structure. Thus, offering preferential funds for such construction is necessary.

6.2. Cultivating a Healthy Business Environment

The trustworthiness of the local government plays a statistically significant role in individuals’ decisions regarding investments [53]. Only when the investment environment of the local government is fully inclusive and shared can the inflow of labor, capital, and other production actors be proactive and continuous [54,55]. If investment is compared to a phoenix, then the business environment is the plain tree that can attract the phoenix. Song et al. [56] found that Chinese special economic zones constantly attract significant foreign direct investment because they provide favorable institutional environments. The optimization of the business environment depends on the transformation of government functions to avoid offside and dislocation management, which is an indispensable condition. The promotion of reforms to streamline administration, delegate power, and improve regulatory services is an important step for the government to gradually change its role from management to service provision. On the one hand, improving efficiency in various administrative approval links during enterprise operations is necessary to reduce transaction costs as much as possible. Local governments may consider setting up special offices in industrial parks and other major enterprise clusters to deal with related enterprise affairs and demands in a unified and coordinated way to solve problems quickly and accurately. On the other hand, the progress of a project should be strictly reviewed rather than only granted approval. The implementation of approved projects should be supervised and managed in strict accordance with a schedule. For projects not started on time, whether they should be cancelled after timely assessment or transferred to a suitable enterprise should be determined. Therefore, the government should streamline administration and delegate power in a targeted way, thereby reducing “physical work” and increasing “mental work” to make decision making scientific, reasonable, and feasible. In the early introduction stage, private entrepreneur forums can be convened appropriately to demonstrate sincerity, show face, and have a genuine heart to showcase the government’s determination to improve the business environment and increase private entrepreneurs’ confidence in investing in Northeast China.

6.3. Promoting Coordinated Development and Mutual Benefit

The construction of a community of interests is an important path for industrial cooperation and inclusive development among regions. Human capital externality is generated through face-to-face communication [53,57,58,59,60,61]. Hence, breaking geographical boundaries is necessary. The establishment of a regional benefit-sharing mechanism in the three provinces is a highly effective technique. This method should be explored to achieve mutual benefits and win-win situations in the investment coordination between the three provinces [62]. In fact, some institutions can be reformed, such as the Hukou institution, which has been focused on and considered an obstacle to the free movement of populations [49]. In addition, when addressing large-scale foreign investments, a typical regional distribution pattern of tandem and subdivision should be formed, and responding organizations for coordination and communication should be established for overall planning, which can be divided into three main aspects. The first aspect involves the internal joint reorganization of state-owned assets. For large state-owned enterprises with major duplications, interprovincial joint reorganization can be considered to lead the industrial division between the three provinces, avoid redundant construction, optimize resource allocation, and realize coordinated development as soon as possible. The second aspect involves the unified layout in the construction of a traffic pipe network and infrastructure to better improve supporting efficiency and cover the industrial clusters in border areas. As for the resulting social cost savings, a common development fund can be established for the three provinces and used for the optimization and adjustment of facilities in border areas. The third aspect involves the promotion of the inclusive development of city circles through transportation. The Shenyang economic zone, with Shenyang as the core; the Liaoning coastal economic belt, with Dalian as the core; the Changchun-Jilin-Tureen development and opening-up pilot zone, with Changchun as the core; and the Harbin-Daqing-Qiqihar economic circle, with Harbin as the core, account for nearly 90% of the total economic output of the three northeastern provinces. The four economic circles can form a foreign advantageous brand through the channel connection dominated by the Harbin and Dalian high-speed railways. Particularly, substantial effort should be exerted on economic and trade services.

7. Conclusions

This study analyzes the causes of low enterprise agglomeration efficiency in Northeast China from a theoretical perspective. Moreover, we empirically examine the uneconomic condition of enterprise agglomeration in Northeast China. The empirical results show that the agglomeration diseconomy in Northeast China is obvious and the most serious among the four major regions of the country. In Northeast China, agglomeration reduces the effects of fixed asset investment and FDI on economic efficiency, and fixed asset investment and FDI impede the release of agglomeration efficiency. Based on the above findings, this paper makes the following policy recommendations to help other regions with the same characteristics achieve agglomeration economies and sustainable development:

First, giving full play to the potential of competitive sunrise enterprises to inject new vitality into economic development is of great practical significance to change the original high energy consumption, high pollution industrial agglomeration model and vigorously develop new energy and new materials instead of traditional energy and materials. Second, we suggest accelerating the process of political system reform and transforming an economy-led government into a service-led government. It helps to eliminate local protectionism and actively attract foreign and private investment in local construction, thus promoting sustainable and healthy economic development. Third, the government should firmly grasp existing policy advantages and fully stimulate the dividends of existing policies. Under the gradual improvement of the agglomeration diseconomy, the region should realize the integration of its industries with the surrounding economic circle. At this time, it is appropriate to develop an agglomeration economy and generate a spatial spillover effect. This helps to gradually eliminate economic imbalances with other regions and achieve sustainable development.

This study is an important attempt to explain the regional decline in Northeast China from the perspective of the enterprise agglomeration. Nevertheless, there are still some limitations to this paper that require further research in the future. For instance, this study evaluates agglomeration economies for a specific period (1999–2015) because of data limitations. Further studies should investigate the long-term impact of enterprise agglomeration by using better data.