The Impact of Urbanization on Industrial Transformation and Upgrading: Evidence from Early 20th Century China

Abstract

Urbanization is key to advancing national modernization and regional socioeconomic sustainable development. This paper empirically investigates the impact of urbanization on industrial transformation and upgrading in early 20th-century China, based on historical data from the initial stages of China’s economic development. We utilized industrial and commercial data from China spanning 1910 to 1927 to construct a fixed-effect model, incorporating instrumental variables to ascertain the causal relationship between urbanization and industrial transformation and upgrading. Additionally, this study tested the hypotheses concerning the effects of human capital and transportation scale, which are identified as the primary channels influencing this relationship. Our findings reveal that (1) the development of urbanization in modern China has significantly promoted industrial transformation and upgrading, and this conclusion remains valid under various robustness tests and the examination of instrumental variables. (2) The improvement in urbanization levels has a more obvious promoting effect on secondary industry, commercial enterprises, and small and medium-sized enterprises, and the positive effect of urbanization on industrial transformation and upgrading is most prominent in the eastern region. (3) Modern Chinese urbanization promoted industrial transformation and upgrading by improving the level of human capital and expanding the scale of transportation. This paper provides historical empirical evidence to study the current social urbanization and industrial policy formulation.

1. Introduction

Urbanization is one of the key drivers of sustainable economic development in modern economies. Can urbanization impact industrial transformation and upgrading in developing countries like China? And if so, how does it affect this transformation? In this study, we focus on the historical process of economic transformation in modern China (1840–1949), using data from industrial and commercial enterprises in China from 1910 to 1927 to explore the impact of urbanization on industrial transformation and upgrading in modern China. The aim is to provide a new perspective on the economic growth effects of urbanization and offer historical evidence that can inform the formulation of current urbanization and industrial policies.

We focus on China for several reasons. First, as China is currently one of the most prominent developing countries in the world, studying the patterns of industrial transformation during China’s industrialization process offers valuable historical insights that can guide other developing countries in achieving industrial upgrading and sustainable development. Second, China is a typical late-developing major country that now boasts a comprehensive industrial system and leading manufacturing capabilities, making it one of the world’s largest manufacturing nations. Yet, it evolved from being a closed country with underdeveloped industrial capabilities. The transformation of such a late-developer is highly representative, and understanding the mechanisms, pathways, and historical opportunities of this transformation warrants careful examination. Third, the early stages of China’s economic development and industrial transformation provide an ideal setting to study the economic effects of urbanization. Studying the transition from an agricultural to an industrial economy from a historical perspective helps us understand the complex dynamics of industrial transformation at different stages and the diverse paths nations might take toward modernization and economic development.

Urbanization plays a crucial role in the transformation process of economic modernization. During its development, the significant agglomeration effects of population, capital, and information greatly influence the advancement of industrial transformation and the evolution of social structures [1]. In fact, researchers have extensively discussed the economic growth effects of urbanization, but the majority of studies focus on contemporary urbanization’s impact on industrial upgrading and economic development [2,3,4], with few empirically analyzing the relationship between urbanization and industrial upgrading in modern history from a historical perspective. The modern economy is highly complex, and the relationship between urbanization and industrial transformation and upgrading is intricate [5,6,7], making it challenging to clearly discern the impact of urbanization on industrial transformation using contemporary data. By looking back to the early stages of economic development, when the economic system was relatively simpler, we can avoid the interference of complex factors and more clearly identify the impact of urbanization on industrial upgrading. Our study discusses the impact of urbanization on China’s industrial development from a broader perspective, attempting to unearth the long-term significance of urbanization’s economic growth effects based on the experiences of modern China’s urban development.

Unlike the “precocious endogenous” industrial development model of the pioneer countries, China’s industrial transformation exhibits a pattern of exogenous economic catch-up, typical of late-developing countries [8]. China has undergone a development trajectory completely different from that of the West. After the 18th century, the developmental paths of China and the Western world experienced what is known as the “Great Divergence” [9]. After the Industrial Revolution, China was far behind Western countries. The Opium War of 1840 marked a turning point in Chinese history, as China was forced to open its treaty ports and began to shift toward a modern industrial civilization [10]. Thus, in the historical progression from traditional to modern China, what role did urbanization play in industrial transformation and upgrading? And how did it affect the “industrialization” transformation of the agrarian civilization? Since the mid-19th century, the opening of modern treaty ports facilitated the rise of modernized cities, which became centers of goods circulation and trade. These cities attracted the aggregation of labor, capital, and other resources, profoundly impacting the development of modern industry and commerce [11]. The urbanization process in modern China not only altered the country’s industrial structure and layout but also carved out a development path with unique Chinese historical characteristics. Accordingly, this paper focuses on the economic transformation process of modern China, utilizing data from 246 prefectures in 18 provinces on the mainland from 1910 to 1927 on modern enterprises, combined with data on urbanization rates, to construct a prefectural-level panel dataset to explore the impact of urbanization on industrial upgrading and transformation in modern China.

Compared to existing research, this paper’s potential marginal contributions are highlighted in three main areas: First, by focusing on the industrial transformation of late-developing countries and utilizing the rich historical data of modern China, this study examines the impact of urbanization on industrial upgrading, clarifies specific mechanisms at work, and deepens the understanding of the relationship between urbanization and industrial upgrading in developing countries, enriching the historical evidence of the economic growth effects of urbanization. Second, unlike studies that use contemporary data to examine the impacts of urbanization, this paper adopts a long-term historical perspective to explore China’s economic system during its early development stages, which is relatively simple and more conducive to clearly identifying the impacts of urbanization on industrial upgrading, thereby largely avoiding the interference of complex factors. Third, by using historical instrumental variables to identify the causal relationship between urbanization and industrial upgrading in modern China, the study confirms the promotional effect of urbanization on industrial upgrading, enriches the literature on urbanization and industrial transformation, and provides new evidence for subsequent research on the relationship between urbanization and industrial upgrading.

The remainder of this paper is organized as follows: Section 2 provides a review of the literature; Section 3 reviews the historical background; Section 4 presents the research hypotheses of this paper; Section 5 describes the methods, including variables, data, and models; Section 6 presents the results and discussion, which includes baseline regression, robustness tests, endogeneity issues, and heterogeneity analysis, and also testing hypotheses related to human capital effects and transportation scale effects; the final section concludes the study.

2. Literature Review

The impact of urbanization on industrial transformation and upgrading has garnered widespread attention in the academic community. One perspective posits that urbanization has a positive effect on the upgrading of industrial structures. Urbanization facilitates the concentration of labor resources, providing industries with a wealth of human capital, especially promoting the sustainable development of knowledge- and technology-intensive industries, thus fostering the transformation and upgrading of industrial structures [12,13]. Cities are the primary venues for innovation activities; urbanization promotes information exchange and technology diffusion, accelerating the application of new technologies in industries and playing a significant role in industrial structural adjustment [14]. Furthermore, advancements in agricultural technology have transformed the employment structure, driven the improvement in urbanization levels, and thereby positively influenced industrial evolution [15]. From the perspective of industrial division and integration reorganization, the urbanization process has promoted the specialization of industrial division and further agglomeration, thereby driving technological advancements and the evolution of industrial structures [16].

However, there exists an alternative viewpoint that urbanization can have negative impacts on industrial transformation and upgrading. Urbanization often comes with rapid population growth and an expansion of economic activities, which may lead to excessive resource consumption and exacerbated environmental pollution. Additionally, to support urbanization and industrial development, developing countries frequently resort to production methods characterized by high energy consumption and emissions. There is an over-reliance on certain industries, particularly those that are pollution-intensive and resource-intensive, to the extent that some countries may even become “pollution havens” for developed nations. This increases the economy’s sensitivity and vulnerability to external shocks, which is detrimental to the sustainability of industrial transformation, upgrading, and development [17,18].

In contemporary society, the critical role of urbanization in the development of the tertiary sector is undeniable, and researchers have extensively discussed this topic. Urbanization, as the process of concentrating population, economic, and social activities in urban areas, has spurred the growth of service demand, increased the proportion of the service sector in GDP, and optimized industrial structure [19]. During the development of urbanization, the agglomeration of various factor resources generates scale effects and industrial clustering, effectively promoting the rapid development of the modern service industry and thereby facilitating industrial structure upgrading [20]. Moreover, urbanization, accompanied by increased household income levels, boosts the demand for education, finance, entertainment, and other services. This not only provides a vast market and ample employment opportunities for the development of the tertiary sector but also, by fostering the growth and innovation of the service industry, especially high-end services, drives economic transformation and upgrading, accelerating the process of modernization [21,22,23]. Currently, China’s new urbanization has become a new approach to industrial upgrading under the new normal of the economy. By enhancing the level of technological innovation, increasing human capital, and raising the per capita disposable income of urban households, new urbanization can significantly promote the sophistication of industrial structure and internal changes within the manufacturing sector [4]. Some scholars have focused on the spatial heterogeneity of the impact of new urbanization on industrial upgrading, concluding that the positive impact of new urbanization on industrial upgrading is prominent in the eastern region, while it has no significant effect in the central and western regions [24].

Numerous researchers have focused on the interplay between urbanization and the upgrading of industrial structures, indicating that there exists a mutually beneficial and adaptive relationship between the two. Urbanization provides the essential human resources, market demand, capital investment, and technological innovation environment required for industrial development. In turn, the development of industries, particularly the emergence of new industries and the transformation and upgrading of traditional ones, offers economic support, employment opportunities, and societal needs for urbanization, facilitating mutual advancement [5,25]. The coupling and coordination between urbanization and industrial development are key to achieving sustainable urban development and industrial upgrading. Through effective management and policy support, a positive interaction between the two can be promoted, driving comprehensive socioeconomic development [26,27]. Furthermore, studies have identified the urban–rural divide and the excessive distortion of resource allocation as the root causes of the discordance between China’s urbanization and industrialization, highlighting the market mechanism as a crucial foundation for the positive interaction and coordinated development of urbanization and industrial sectors [28].

The literature review reveals varied perspectives on the impact of urbanization on industrial transformation and upgrading. Researchers acknowledge both the positive stimulative effects and the negative consequences of rapid urbanization. However, most studies focus on contemporary societies, with scant literature exploring the historical roots of urbanization’s impact on industrial development from a historical perspective. Moreover, the existing literature predominantly examines the effects of urbanization on the tertiary sector, with insufficient discussion on its role across different stages of industrial evolution. Previous research has concentrated on the relationship between urbanization and industrial upgrading in developed countries, and studies on developing countries have mainly focused on the later stages of industrialization, with fewer addressing the early stages of economic development in these countries, where it might be easier to isolate the effects of urbanization on industrial transformation. Additionally, while some scholars have focused on the interplay between urbanization and industrial upgrading, there is a lack of empirical research concerning the long-term effects of urbanization on industrial development, and few studies retrospectively examine the relationship between urbanization and industrial upgrading during historical development phases. Therefore, this paper adopts a historical perspective, focusing on the initial stages of urbanization and industrial transformation and upgrading in China. By employing historical data from modern China, this study empirically evaluates the impact and mechanisms of urbanization on industrial upgrading, aiming to derive useful insights. This research intends to provide a new perspective and evidence on the relationship between urbanization and industrial upgrading, enriching the studies on the economic growth effects of urbanization and offering a substantial supplement to the existing literature.

3. Historical Background on Urbanization and Industrial Development in Modern China

3.1. The Process of Urbanization in Modern China

Following the Opium Wars, the impact of Western industrial civilization prompted significant transformations in Chinese economic and social structures. The establishment of treaty ports markedly altered the fate of Chinese towns, propelling the urbanization process into a new phase of development. China’s forced opening of major treaty ports such as Guangzhou, Xiamen, Fuzhou, Ningbo, and Shanghai marked a critical historical juncture in the economic transformation of modern China. Post-opening, cities underwent fundamental changes in their economic functions, leading to the formation of true modern cities and industrial agglomerations, thereby providing greater scope for urban development. Subsequently, ports such as Niuzhuang, Shantou, Taiwan, Dengzhou, and Danshui were also opened, modernizing the coastal urban agglomerations and altering the economic geography. Coastal cities, as windows to an open economy, leveraged their prime geographical locations and convenient transportation networks to promote trade liberalization and accelerate the aggregation and transformation of related industries, enhancing the competitiveness of industrial chains and becoming key drivers of regional economic growth. Centered around these cities, the gradual inland radiance promoted the overall development of coastal and surrounding urban agglomerations, also impacting the hinterland’s rural areas and market towns, creating a port-to-hinterland economic spatial connection model. This model defined the path of urban development in modern China, further advancing the process of urbanization.

As Western economic aggression and capital outflow expanded into China’s interior, the rights to inland waterway navigation were seized, and port openings extended from coastal areas deep into the middle and lower reaches of the Yangtze River, promoting the modernization of inland cities along the river. This development demonstrated a progressive pattern of urbanization from “coastal to riverine to inland” in modern China [29]. By the early 20th century, China had opened over 100 ports to foreign trade, with port cities becoming the epicenters of economic growth, establishing a developmental pattern from specific points to broader areas, and ultimately to a fan-shaped expansion. This trend is a significant aspect of modern urbanization. On the one hand, the economic connections between coastal and riverine port cities and the interior deepened, with the opening of trade ports serving as a bond among regions and a foundation for urban integration into the global economy. On the other hand, the spillover effects of urban economic growth spurred social transformation in rural areas, with rural labor moving toward nonagricultural industries and actively participating in urbanization, thereby fostering a transformation and positive interaction between urban and rural relations. Figure 1 illustrates the spatial distribution of modern urbanization rates, revealing that the urbanization rates in the eastern and central regions are higher than those in the western region.

3.2. Overview of Industrial Transformation and Upgradation in Modern China

After the Opium Wars, China took a historic step from a traditional society to a modern one. The impact of Western industrial nations led to the disintegration of the traditional smallholder economy, resulting in widespread bankruptcy among peasants and artisans, a decline in the rural economy, and lagging agricultural development. Furthermore, the decline in traditional handicrafts spurred attempts to transition to the machine industry. During the Self-Strengthening Movement, China established new enterprises using machines and mechanical power, marking the rise of modern industry and the beginning of industrialization, which became a distinct characteristic of industrial structural transformation and upgrading. It should be noted that the modern enterprises emerging in China from the late 19th to early 20th century represented a new type of business that adopted Western management practices, production technologies, and business philosophies. This signified a shift in China’s industrial development from traditional handicrafts to modern machine industry and reflected the transformation of the traditional agricultural economy into a modern industrial economy. These enterprises introduced mechanized production equipment and implemented scaled, standardized production, which resulted in higher production efficiency and stronger market competitiveness compared to earlier workshops and family businesses.

The development of modern national industry in China was fraught with challenges, from its beginnings during the Self-Strengthening Movement through to the start-up phase after the First Sino-Japanese War, the brief development during World War I, and the industrial revival during the Nationalist Government era, until its gradual decline. The modern national industry, born under the oppression of Western capitalism, faced inherent shortcomings in capital, technology, and talent, compounded by subsequent developmental imbalances, making its growth process complex and variable, and full of challenges. The structural characteristics of modern national industry were prominently reflected in the imbalance between light and heavy industrial development. The modern national industry lacked substantial economic strength and modern investment methods, with industries primarily concentrated in light industries such as textiles and food. Heavy industry had a weak foundation and slow development. Insufficient capital also meant that the scale of light industries remained small, with a low level of capital-intensive infrastructure. Small and medium-sized enterprises and workshop handicrafts grew rapidly [31]. Although the banking sector, representing the financial industry, underwent some development, its influence within the overall industry remained relatively minor.

From an industrial layout perspective, the uneven regional distribution of modern industries was pronounced, with a strong focus on major cities in coastal areas, where treaty ports played a critical role in industrial development. Compared to inland cities, these coastal cities offered superior environments and favorable conditions for industrial investment. They were the first to break away from the traditional economy, facilitating exports and transportation, and easing access to foreign raw materials and technological equipment. The agglomeration effect in these areas ensured that coastal regions remained at the core of the distribution of national industries. As domestic trade developed, the machine industry penetrated further inland, and there was a trend for the modern industry to expand into more non-port cities [32]. In particular, after the advent of modern railway transportation, cities along railway lines also experienced rapid industrial development, becoming one of the significant factors influencing the layout of modern industry. Figure 2 displays the distribution of enterprise numbers across the eighteen provinces of mainland China in the modern era. It is evident that the industrial layout was highly concentrated in coastal areas, with a trend of spreading to inland cities [33].

4. Research Hypotheses

Urbanization accelerates the concentration of resources such as labor, capital, and technology, stimulating the growth of urban economies and industrial agglomeration and positively affecting industrial transformation and upgrading, thus energizing the momentum for sustainable industrial development. Human resources and transportation infrastructure are critical factors influencing industrial development. Furthermore, the development of human resources and the enhancement of transportation infrastructure are intimately connected with urbanization. The development of modern education and emerging railways in modern China reflects the improvement in human capital levels and expansion of transportation scale, providing an excellent opportunity to observe how urbanization affects industrial development. This paper analyzes the theoretical logic behind how urbanization impacts industrial transformation and upgrading through the lens of human capital effects and transportation scale effects.

4.1. Human Capital Effect

During the process of urbanization in modern China, as the population migrated from rural areas to cities, there was a shift in the demand and supply of education, health, and skills training, which in turn influenced the accumulation of human capital. Firstly, urbanization led to a gradual concentration of the population in cities, which resulted in the centralization of educational resources in urban areas. The superior economic conditions and infrastructure of cities attracted high-quality talent. The concentration of modern Chinese students studying abroad in major cities accelerated the enhancement of educational levels and the accumulation of human capital [35]. Secondly, urbanization fostered diversification in urban educational institutions and the types of education available. The establishment of new schools, church middle schools, and higher education institutions met the educational needs at various levels and contributed to improving overall educational standards. Simultaneously, as the job market diversified, the rich educational resources in cities provided skills training that matched market demands, enhancing workers’ professional skills and competitive edge in employment.

The significant enhancement of human capital levels not only increased the quantity of the labor force but also improved its quality and skill level, thereby driving China’s economic transition from traditional agriculture to a technology- and knowledge-driven modern industry. Historical experience demonstrates that the widespread availability of modern education and skills training provided the necessary talent support for modern industrialization, facilitating the optimization and upgrading of the industrial structure and injecting momentum into sustainable industrial development [36]. Specifically, the improvement in labor force skill levels enhanced the professional skills and work efficiency of the industrial workforce, optimizing the production efficiency and product quality of modern industries that utilized machinery. Moreover, a high-quality labor force effectively applied advanced production technologies and management methods, enhancing the specialization and systematization of industrial production, reducing resource wastage, and strengthening economic performance. Additionally, high-level human capital is crucial for technological innovation; emerging talents nurtured by modern education not only possess scientific knowledge and technical skills but also innovative thinking and problem-solving capabilities, fostering the development of new technologies and products, accelerating the commercialization of scientific achievements, and providing strong momentum for industrial transformation and upgrading. Therefore, through the concentration of educational resources, the generalization of basic education, the development of skills and vocational training, and increased social mobility, urbanization in modern China actively promoted the enhancement of human capital, capable of improving production efficiency and product quality of modern enterprises; advancing industrial technological progress, innovation, and structural change; and playing a crucial role in driving the industrial upgrading and sustainable economic development of modern China. Based on this, the paper proposes the following hypothesis:

Hypothesis 1 (H1).

Urbanization in modern China facilitated industrial transformation and upgrading by enhancing the level of human capital.

4.2. Transportation Scale Effect

Railroads, providing rapid and high-capacity transportation services, met the needs of sustainable societal development. On the one hand, as economic interactions and population movements between urban and rural areas in modern China increased, there was an urgent need for more efficient and convenient transportation, especially for the large-scale transportation of industrial products and raw materials, which spurred the development and expansion of railways. By the 1930s, China’s railway network had connected major economic centers and port cities, playing a crucial role in regional economic integration and the circulation of goods [37]. On the other hand, the level of regional economic development determined the funding and investment capacity for railway construction; economically more developed areas were better able to invest in infrastructure projects. The urbanization process in modern China facilitated investment in and construction of transportation infrastructure, enhancing the transportation network and expanding its coverage. Additionally, the rise in urbanization levels in early 20th century China provided the necessary talent support for engineering technology research and application. Universities, research institutions, and companies in cities became significant sources of technological innovation, accelerating the renewal of engineering technologies and thus driving the expansion and scaling up of the modern railway network.

The scale effects of railway transportation, by enhancing transportation efficiency and reducing per-unit transportation costs, effectively lowered logistics costs for businesses and promoted industrial agglomeration [38]. For modern industries reliant on raw materials for machine production, this meant that they could procure raw materials and transport products to markets at lower costs, thereby enhancing their sustained competitiveness. Additionally, the convenience and cost-effectiveness of railway transport encouraged businesses to cluster around railway lines or transportation hubs, forming industrial clusters. This arrangement not only allowed businesses to share infrastructure, reducing production and operational costs but also facilitated technological exchanges and innovation, driving industrial development. Furthermore, the expansion of railways significantly broadened the market reach of modern enterprises, enabling them to access distant consumer markets and resource supplies, which is conducive to business expansion and market integration, advancing market consolidation and industrial upgrading. The expansion and densification of the railway network also promoted the flow and optimal allocation of resources across a broader area, facilitated the mobility of labor across various industries and regions, and aided in industrial upgrading and sustainable economic growth. This indicates that areas with higher levels of urbanization often possess more developed railway networks. The expansion of railway transportation not only reduced logistics costs but also promoted industrial clustering and market expansion, strongly supporting the scaling and structural optimization of industries and positively impacting modern industrial transformation and upgrading. Based on this analysis, this paper proposes the following hypothesis:

Hypothesis 2 (H2).

Urbanization in modern China facilitated industrial transformation and upgrading by expanding the scale of transportation infrastructure.

5. Methods

5.1. Variable Selection

5.1.1. Independent Variable

In this study, the urbanization rate (lnurban) was used as the independent variable, calculated as the proportion of the urban population to the total population to measure the level of urbanization. Modern China has witnessed significant shifts in its urban–rural structure, with a substantial migration of rural populations to urban areas, greatly increasing the urban population proportion. Historical documents have provided statistics on urban populations across various regions, allowing us to measure urbanization levels effectively. Due to limitations in historical data, the available literature only provides specific individual year data on urban populations at the prefectural level; thus, we could not obtain dynamic, year-over-year prefectural population data. We utilized available data from 1910 to assess the urbanization levels of various regions during the sample period.

5.1.2. Dependent Variable

In this study, the number of modern enterprises (lnindus) in each prefecture was used as a proxy variable for industrial transformation and upgrading in modern China. Industrial transformation and upgrading are pivotal for sustainable economic development. During the late 19th to early 20th centuries in modern China, this transformation involved a shift from traditional agriculture to modern industry, as well as a transition from workshop-based manufacturing to large-scale mechanized production. The emergence and growth of modern industrial and financial enterprises represented a significant evolution from nonexistence to prominence, reflecting the shift in production factors from the agricultural sector to more productive nonagricultural sectors. This movement is a critical component of industrial structural optimization and sustainable economic growth. Due to the scarcity of comprehensive historical data on agricultural development, it was not feasible to calculate indicators such as the proportion of nonagricultural industries. Therefore, using the number of modern enterprises as an absolute metric to reflect the aggregation of modern industries served as a viable proxy for assessing the transformation and upgrading of the industrial structure.

5.1.3. Control Variables and Other Variables

The control variables included in this study were as follows: (1) Terrain slope (lnslope): The slope of the terrain reflects the topographical features of a region, largely determining the direction of land use, which affects business site selection and the circulation of goods. Terrain slope is an important factor in industrial transformation and upgrading, and therefore it was controlled for in this study. (2) Shortest distance to the coastline (lndis): The shortest distance to the coastline can influence a region’s trade convenience, investment attractiveness, and level of economic openness. We further controlled for this geographical factor, calculating the shortest Euclidean distance from the geometric center of the prefecture to the coastline. (3) Drought and flood disasters (disaster): Natural disasters significantly impact regional industrial production and economic development. Extreme weather conditions can directly or indirectly affect business operations and economic activities. We controlled for climatic disaster factors by employing a drought and flood index as the measurement metric, where a higher index value indicates a greater severity of drought or flood. (4) Population density (lnpopdensity): This study used the number of individuals per unit of land area to reflect the population density of a region, affecting local labor supply and the level of economic development. We controlled for this important influencing factor.

Some dummy variables were also controlled, which were as follows: (1) Whether it is a treaty port (port): A value of 1 is assigned if the prefecture is a treaty port; otherwise, it is 0. Modern treaty ports indicate a region’s economic level and degree of openness, significantly impacting industrial development [35]. Therefore, we controlled for the openness factor represented by treaty ports. (2) Whether it is a land border (border): A value of 1 is assigned if the prefecture is located on a land border; otherwise, it is 0. Regions located at land borders typically have geographical advantages for cross-border trade, which positively affects industrial transformation and upgrading. We controlled for this geographical factor. (3) Whether it is a Zhili state (Zhili): Zhili state is directly under the provincial Chief Secretary of the state, if it is a Zhili state, the value is 1 and otherwise 0. (4) Whether it is a provincial capital (capitalcity): A value of 1 is assigned if the prefecture is a provincial capital; otherwise, it is 0. Zhili states and Provincial capitals have significant political advantages, impacting industrial support, resource aggregation, and economic levels, all of which are crucial for industrial transformation and upgrading. Thus, we controlled for this political characteristic.

Additionally, in terms of instrumental variables, we selected the number of postal roads from the Qing dynasty (lnpostroad) to identify the causal relationship between urbanization and industrial transformation and upgrading. The selection was based on the exogenous nature of these roads. For mechanism variables, we measured the human capital effect using “number of church secondary schools” (lnschool) and “number of primary and senior pupils” (lnpupil), as the presence of modern foundational education in a region reflects its human capital level. Furthermore, the criterion “whether the railway has been opened “(rail) was utilized to gauge the effect of transportation scale. The introduction of railways, a new mode of transportation in modern China, significantly transformed the existing transportation scale and network during that period.

5.2. Data Description

We utilized Chinese urban population data and industrial development data, focusing on 246 prefectural-level administrative regions across 18 provinces in China. The period of 1910–1927 was selected as the sample period to identify the impact of population urbanization structure on sustainable industrial development. Due to historical data limitations, data from remote regions such as the three northeastern provinces, Xinjiang, Tibet, and Inner Mongolia, are incomplete. Consequently, we selected administrative regions at the prefecture level from eighteen provinces in mainland China as the sample. These provinces were Zhili, Jiangsu, Anhui, Zhejiang, Fujian, Jiangxi, Shandong, Shanxi, Henan, Hunan, Hubei, Guangdong, Guangxi, Sichuan, Guizhou, Yunnan, Shaanxi, and Gansu.

Our data primarily originated from historical documents and archival materials, which were manually collected and digitized to create the dataset for this study. This dataset is a panel dataset at the prefectural level. The data on the urbanization rate were sourced from “A History of China’s Population: Volume 5 (Qing Dynasty)” [30], which provides the total population and urban population figures for various prefectures in selected years. Modern enterprise data were derived from Du’s “National Capitalism and the Old Chinese Government: 1840–1937” [34], which focuses on the development trajectory of Chinese capitalism and its relationship with the Chinese government. It presents an overview of Chinese civil industrial, shipping, and modern financial enterprises established between 1840 and 1927, providing detailed information on the founding year, name, location, capital, business nature, and founders of the enterprises annually and offering significant data support for our analysis of enterprise numbers in a region.

For control variables, natural disaster data were obtained from “China’s Drought and Flood Distribution Atlas Over the Past Five Centuries,” edited by the Meteorological Science Institute of China Meteorological Administration in 1981 [39]. The geographical data were derived from the “Historical Atlas of China: Qing Dynasty Volume” [40] and the China Historical Geographic Information System CHGIS (2007), specifically the vector maps of administrative divisions in the Qing Dynasty. Population density data were sourced from Cao’s “Population History of China: Volume 5 (Qing Dynasty)” [30], while information on whether a city serves as a provincial capital was derived from “Historical Atlas of China: Qing Dynasty Volume” [40]. The data for the instrumental variable of postal roads were obtained from “History of Road Transportation in Ancient China” [41]. In terms of mechanism variables, the data on the number of church secondary schools and the number of primary and senior pupils were sourced from “Survey Data of Christianity in China from 1901 to 1920” [42]. The number of primary and senior pupils is available only for the single year of 1920. The information on the presence of a railway was compiled from “Selected Statistical Data of Modern Chinese Economic History” [43]. The descriptive statistics of the main variables are presented in

Table 1. Descriptive statistics of variables.

Variable	N	Mean	Std.	Min	Max
lnindus	4428	0.6806	1.0335	0.0000	6.4345
lnurban	4428	4.1115	0.6433	1.7918	6.0684
lnslope	4428	4.5804	0.0653	3.9655	4.6052
lndis	4428	5.5761	1.4351	0.1192	7.4044
disaster	4428	0.8049	0.6906	0.0000	2.0000
lnpopdensity	4428	6.8273	1.0042	0.9646	8.6597
port	4428	0.1341	0.3408	0.0000	1.0000
border	4428	0.0407	0.1975	0.0000	1.0000
Zhili	4428	0.2724	0.4452	0.0000	1.0000
capitalcity	4428	0.0732	0.2604	0.0000	1.0000
lnpostroad	4428	1.6255	0.9169	0.0000	3.6109
lnschool	4428	0.4239	0.6655	0.0000	3.1355
lnpupil	246	4.8101	2.5072	0.0000	9.3944
rail	4428	0.1741	0.3793	0.0000	1.0000

.

5.3. Model Specification

This study utilized the proportion of the urban population as an indicator to identify the impact of urbanization level enhancement on the industrial transformation and upgrading in modern China. The baseline regression model is presented as follows:

lnindus_it = α+ βlnurban_it + γX_it + μ_it + φ_i + ε_it

(1)

where i and t in Equation (1) denote prefecture i and year t, respectively; lnindus_it denotes the number of modern enterprises in each prefecture to measure the industrial upgrading of the area; lnurban_it denotes the urbanization rate; and X_it is a series of control variables, including terrain slope (lnslope); shortest distance to the coastline (lndis); drought and flood disasters (disaster); population density (lnpopdensity); whether it is a treaty port (port); whether it is a land border (border); whether it is Zhili state (Zhili); and whether it is a provincial capital (capitalcity). μ_t denotes the time-fixed effects, φ_i represents the regional fixed effects, and ε_it represents the error term.

6. Results and Analysis

6.1. Empirical Results

6.1.1. Basic Regression Analysis

The level of urbanization, indicating the proportion of urban population within the total population, directly reflects the process and extent of labor concentration in urban areas and also reveals regional economic development levels. This study aimed to explore the impact of urbanization on industrial transformation and upgrading by employing a two-way fixed-effect model for empirical testing.

Table 2. Baseline regression results.

	(1)	(2)	(3)	(4)	(5)
lnurban	0.7130 ***	0.7099 ***	0.6937 ***	0.5157 ***	0.3363 ***
	(0.0285)	(0.0276)	(0.0265)	(0.0259)	(0.0226)
lnslope		−0.3575 ***	−1.3092 ***	−1.2418 ***	−0.6727 ***
		(0.1224)	(0.1672)	(0.1504)	(0.1272)
lndis		−0.2928 ***	−0.2529 ***	−0.1091 ***	−0.1323 ***
		(0.0177)	(0.0175)	(0.0167)	(0.0161)
disaster			0.0344 **	0.0198	0.0146
			(0.0171)	(0.0158)	(0.0147)
lnpopdensity			0.2514 ***	0.2486 ***	0.1726 ***
			(0.0151)	(0.0147)	(0.0138)
port				1.0162 ***	0.8670 ***
				(0.0469)	(0.0468)
border				−0.0733	−0.0946 **
				(0.0538)	(0.0472)
Zhili					−0.2837 ***
					(0.0202)
capitalcity					0.8965 ***
					(0.0590)
Year fixed effect	yes	yes	yes	yes	yes
Area fixed effect	yes	yes	yes	yes	yes
Observations	4428	4428	4428	4428	4428
R2	0.432	0.474	0.496	0.575	0.633

Note: Robust standard errors in parentheses, *** p < 0.01, ** p < 0.05.

reports the results of the baseline regression. Column (1) shows that the coefficient for the urbanization rate is positive and significant at the 1% level, indicating that an increase in urbanization significantly boosts the number of modern enterprises, driving the development of machine industry and modern financial sectors and accelerating the transition from traditional handicraft workshops to powered machinery production, thereby promoting industrial transformation and upgrading. Columns (2) to (5) successively include control variables, with the urbanization rate coefficient remaining significantly positive, underscoring the robustness of our conclusions. This implies that the increase in the proportion of urban population in modern China reflects a significant movement of labor resources from rural to urban areas, substantially increasing the number of industrial workers and providing ample labor for businesses to expand production and make active investments. This movement also promotes labor specialization, enhances productivity, and facilitates the aggregation and structural optimization of industries reliant on machine production. Furthermore, the concentration of the urban population in early 20th century China also helped improve the quality of the workforce, advancing the skills and technical levels of modern industrial workers, preparing for the expansion and structural upgrading of industries, and becoming a critical safeguard for industrial transformation and upgrading in modern China.

6.1.2. Robustness Test

(1)

Replacement of core variable measures, and data sources

Corporate capital also serves as an effective indicator reflecting the industrial development capacity of a region. In this study, we utilized corporate capital as a proxy variable for the dependent variable to circumvent the subjectivity in the selection of the dependent variable method that could affect the robustness of the research findings. Column (1) of

Table 3. Robustness tests: replacement of core variable measures and data sources.

	(1)	(2)	(3)
	Replacement of Dependent Variable Measures	Replacement of Data Sources for the Dependent Variable	Replacement of Data Sources for the Independent Variable
lnurban	0.7044 ***	0.1783 ***	0.3692 ***
	(0.0654)	(0.0316)	(0.0355)
Control variables	yes	yes	yes
Year fixed effect	yes	yes	yes
Area fixed effect	yes	yes	yes
Observations	4428	1722	1380
R2	0.534	0.529	0.624

Note: Robust standard errors in parentheses, *** p < 0.01.

shows the results of the robustness check regression after changing the measure of the dependent variable. The estimated coefficient for the urbanization rate is significantly positive, indicating that an increase in the urbanization proportion in modern China can enhance corporate capital, facilitate the expansion of modern enterprises adopting large-scale machinery production, and promote industrial transformation and upgrading. Our core findings remain intact, and the selection of dependent variable indicators does not alter the conclusions of this study.

To mitigate the influence of data source selection on our conclusions, we conducted robustness checks by changing the data sources for both the dependent and independent variables. The dependent variable was substituted with data on modern enterprises from 1840 to 1916, collated in the 18th issue of the Journal of the Institute of Modern History, Academia Sinica. For the independent variable, the urbanization rate, replacement data were drawn from the Survey Materials of Christianity in China from 1901 to 1920 [41], which provides urban and total population figures for the year 1918. The regression results reported in Columns (2) and (3) of Table 3, with the urbanization rate’s coefficient being significant at the 1% level, indicate that urbanization in modern China significantly promotes the increase in the number of modern enterprises, facilitating industrial transformation and upgrading. This suggests that the findings of this study are robust.

(2)

Replacement sample time span

During World War I (1914–1918), Western capitalist nations, preoccupied with the war, relaxed their economic aggression toward China. There was a sharp decline in the goods exported from China, while the expansion of military needs significantly increased Western demand for Chinese raw materials and military goods. This provided favorable conditions for the development of modern Chinese national capitalism, ushering in a “golden age” for the development of national industry and commerce. To eliminate the impact of this significant historical event, we divided the sample period into two subsamples: pre-WWI (1910–1913) and post-WWI (1919–1927), conducting robustness checks. The regression results are shown in

Table 4. Replacement of the sample time span and excluding samples from provincial capitals and directly governed states.

	(1)	(2)	(3)
	Pre-World War I	Post-World War I	Subsample
lnurban	0.1868 ***	0.4247 ***	0.3439 ***
	(0.0347)	(0.0328)	(0.0258)
Control variables	yes	yes	yes
Year fixed effect	yes	yes	yes
Area fixed effect	yes	yes	yes
Observations	984	2214	2898
R2	0.521	0.687	0.605

Note: Robust standard errors in parentheses, *** p < 0.01.

. The regression results reported in Columns (1) and (2) of Table 4 show that the coefficient of urban population level is significantly positive at the 1% level for both periods. This indicates that urbanization had a noticeable promotional effect on the growth of modern enterprises both before and after WWI, affirming the robustness and credibility of the baseline results of this paper.

(3)

Excluding samples from provincial capitals and Zhili states

To mitigate the potential bias from political factors in our findings, we conducted a robustness check by excluding samples from provincial capitals and directly governed states. As shown in Column (3) of Table 4, the regression coefficients of the urbanization rate are significantly positive at the 1% level. This indicates that a higher rate of population urbanization is conducive to industrial agglomeration, suggesting that enhancing urbanization levels in modern China positively impacts industrial transformation and upgrading. Hence, the selection of sample prefectures does not affect the baseline results of our study, demonstrating that our core conclusions are robust.

6.1.3. Endogeneity Analysis

The potential reverse causality between urbanization and industrial transformation and upgrading represents an endogeneity problem that this paper addresses. The elevation of urbanization levels can facilitate industrial transformation and upgrading; yet, conversely, industrial transformation and upgrading can also contribute to an increase in urbanization levels. We used the instrumental variable method for causal identification to validate the promotive effect of urbanization on industrial transformation and upgrading.

We used the number of postal roads during the Qing dynasty as an instrumental variable to identify the causal relationship between urbanization and industrial transformation and upgrading. The choice of this instrumental variable was primarily based on the following considerations: In traditional China, post stations served as comprehensive institutions integrating message transmission, logistics transportation, military defense, and official reception. During the Ming and Qing dynasties, there was a developed network of postal routes, with post stations, courier stations, and express posts set up along major water and land routes, forming a complete postal delivery system. Areas with a higher number of postal routes had more convenient transportation and higher population density, which significantly contributed to the prosperity of commerce and trade and the emergence of commercial towns, indicating a correlation between the distribution of postal routes and the level of urbanization. Moreover, the establishment of post stations initially aimed to provide places for changing horses and resting for those delivering government documents and had certain military defense purposes. By the Ming dynasty, a postal route network connecting the north and south of the large rivers was formed, and during the Qing dynasty, China experienced an even more comprehensive postal route system. Since the development of modern enterprises has no direct association with the establishment of post stations, using postal routes as an instrumental variable was feasible.

In the first stage, as shown in

Table 5. Treatment of endogeneity issues.

	(1)	(2)
	First Stage	Second Stage
lnIV	0.0504 ***
	(0.0116)
lnurban		2.4762 ***
		(0.5569)
Kleibergen–Paap rk LM statistic	19.362
	[0.0000]
Cragg–Donald Wald F statistic	19.613
Control variables	yes	yes
Year fixed effect	yes	yes
Area fixed effect	yes	yes
Observations	4428	4428

Note: 1. Robust standard errors in parentheses, *** p < 0.01; the p-value is indicated in [ ]; 2. Regression results for R2 are not reported here.

, the regression coefficient for the number of postal roads is positive and significant at the 1% level, indicating that the number of postal roads has a positive impact on the level of urbanization. In the second stage, the urbanization rate’s regression coefficient is significantly positive, implying that an increase in the urbanization rate favors industrial agglomeration and significantly boosts industrial development, thereby affirming that our core conclusions remain robust. Additionally, tests for the validity of the instrumental variable show that the Kleibergen–Paap rk LM statistic value is 19.362, significant at the 1% level, suggesting that the instrumental variable is identifiable. The Cragg–Donald Wald F statistic value is greater than 10, rejecting the null hypothesis that “the instrumental variable is weak,” which indicates that the choice of postal roads as an instrumental variable is appropriate.

6.1.4. Heterogeneity Analysis

Considering the influences of industry type, business operation mode, and company size, the role of urbanization in industrial structure adjustment may differ. Therefore, we conducted heterogeneity tests by distinguishing among industry types, modes of business operation, and company sizes to identify the diverse effects of population urbanization on the upgrading of industrial structure.

(1)

Differentiating industry types

The impact of urbanization on the upgrading of different types of industries may vary. We categorized the sample companies into the secondary industry, represented by the industrial sector, and the tertiary industry, represented by the financial sector, to examine the differential effects of urbanization levels on various industries in early 20th-century China, as shown in

Table 6. Heterogeneity analysis: differentiating industry type.

	(1)	(2)
	Secondary Industry	Tertiary Industry
lnurban	0.3281 ***	0.1713 ***
	(0.0219)	(0.0199)
Control variables	yes	yes
Year fixed effect	yes	yes
Area fixed effect	yes	yes
Observations	4428	4428
R2	0.602	0.474

Note: Robust standard errors in parentheses, *** p < 0.01.

.

It can be observed that the estimated coefficients for urbanization are significantly positive at the 1% level. However, the absolute value of the urbanization regression coefficient in Column (1) is greater than that in Column (2), indicating that the level of urbanization in modern China has a significant promotional effect on industrial upgrading, with a more pronounced impact on the upgrading of the secondary industrial structure. This is likely due to the uneven development of industries in modern China, where the tertiary sector was not yet well established. Although industries such as finance and insurance were emerging, their influence remained weak. In contrast, the secondary industry, predominantly industrial, was flourishing and experiencing a continuous increase in labor demand. The rise in the urban population proportion in modern China had a more notable promotional effect on the development of the secondary industry compared to the tertiary industry.

(2)

Distinguish the nature of enterprises

Modern enterprises can be categorized into four types according to the nature of ownership and management: government-operated, merchant-operated, joint government–merchant, and Sino-foreign joint ventures. Government-operated enterprises are directly established by the government. Merchant-operated enterprises refer to those founded by individuals or commercial entities, either through sole proprietorship or partnerships. Joint government–merchant enterprises, also known as government-supervised and merchant-managed enterprises, involve a cooperative arrangement between government and private merchants. In this model, the government may provide some financial or policy support, while private merchants contribute capital and manage daily operations. Sino-foreign joint ventures are collaborative enterprises established between Chinese and foreign companies. The impact of urbanization on the development of industries with different operational models may vary. We conducted a heterogeneity test on enterprises with these four different operational methods, and the regression results are presented in

Table 7. Heterogeneity analysis: differentiating enterprise management styles.

	(1)	(2)	(3)	(4)
	Government-Operated	Merchant-Operated	Joint Government–Merchant	Sino-Foreign Joint Ventures
lnurban	0.0309 ***	0.3406 ***	0.0323 ***	0.0587 ***
	(0.0088)	(0.0229)	(0.0067)	(0.0084)
Control variables	yes	yes	yes	yes
Year fixed effect	yes	yes	yes	yes
Area fixed effect	yes	yes	yes	yes
Observations	4428	4428	4428	4428
R2	0.454	0.615	0.245	0.143

Note: Robust standard errors in parentheses, *** p < 0.01.

. The results indicate that the coefficient of urbanization is significantly positive for all types, suggesting that an increase in the level of urbanization significantly promotes the development of industries regardless of their operational model. Looking at the magnitude of the impact, the absolute value of the urbanization coefficient in Column (2) is much larger than in other columns, implying that urbanization has the most pronounced promotional effect on merchant-operated enterprises; the absolute value of the coefficient for urbanization in Column (4) is slightly larger than in Columns (1) and (3), indicating that the impact of urbanization in modern China on the development of Sino-foreign joint ventures is greater than on government-operated and joint government–merchant models; the urbanization coefficients’ absolute values in Columns (1) and (3) are very close, reflecting no significant difference in the impact of urbanization on enterprises with a government element in their operation.

This differentiation could be attributed to the fact that privately owned enterprises operate entirely with private capital, employ workers, and use machinery in production, embodying modern national capitalist enterprises with strong flexibility, profitability, and independence. On the other hand, Sino-foreign joint ventures are modern enterprises established and operated through Chinese and foreign capital collaboration, significantly influenced by Western capitalism throughout their growth and development. Government-operated and government–merchant cooperative enterprises, including those supervised by officials but operated by merchants, are heavily imbued with official characteristics. Government bureaucracy plays a dominant role in the development of these enterprises, which possess less autonomy compared to privately owned businesses. Consequently, urbanization in modern China plays a more prominent role in enhancing the development of privately owned enterprises, has a secondary influence on Sino-foreign joint ventures, and exhibits a weaker effect on enterprises with official characteristics.

(3)

Differentiating enterprise size

Capital amount serves as a crucial metric for assessing enterprise size, and the impact of urbanization levels may vary across different scales of enterprises. In this paper, enterprises were categorized based on their capital amounts into four types: capital of 10 to 100 thousand, capital of 100 to 500 thousand (excluding 100 thousand), capital of 500 to 1000 thousand (excluding 500 thousand), and capital of 1000 to 10,000 thousand (excluding 1000 thousand). This categorization allows for an exploration of the differential effects of urbanization levels on enterprises of varying sizes in modern China.

Table 8. Heterogeneity analysis: differentiating enterprise size.

	(1)	(2)	(3)	(4)
	Capital of 10 to 100 Thousand	Capital of 100 to 500 Thousand	Capital of 500 to 1000 Thousand	Capital of 1000 to 10,000 Thousand
lnurban	0.2709 ***	0.2087 ***	0.1068 ***	0.1535 ***
	(0.0196)	(0.0182)	(0.0127)	(0.0146)
Control variables	yes	yes	yes	yes
Year fixed effect	yes	yes	yes	yes
Area fixed effect	yes	yes	yes	yes
Observations	4428	4428	4428	4428
R2	0.612	0.537	0.327	0.251

Note: Robust standard errors in parentheses, *** p < 0.01.

presents the regression results.

The results demonstrate that the regression coefficients of urbanization are significantly positive at the 1% level across all business sizes, indicating a clear promotional effect of urbanization on industry development regardless of the scale of the enterprise. Furthermore, it is observed that the absolute values of the regression coefficients for urbanization in Columns (1) and (2) are larger than those in Columns (3) and (4), suggesting that the positive impact of urbanization is more pronounced for small and medium-sized enterprises with a capital of 500 thousand or less. This implies that small and medium-sized enterprises in modern China, which have more centralized decision-making processes, are more responsive to market changes, possess simpler organizational structures, and exhibit greater production and management flexibility. The contribution of labor in these enterprises is more easily recognized, allowing urbanization to have a more significant effect on the growth and development of small and medium-sized businesses.

(4)

Distinguishing between the eastern, central, and western regions

The eastern, central, and western regions of China exhibit significant differences in resource endowments, levels of economic development, social structures, political characteristics, and degrees of openness to the outside world. Consequently, these regions vary in their urbanization and industrial development outcomes. We categorized the samples based on their geographical location into eastern, central, and western regions (as shown in

Table 9. Division of eastern, central, and western regions of China.

Region	Province
Eastern region	Zhili, Jiangsu, Zhejiang, Fujian, Shandong, and Guangdong
Central region	Shanxi, Anhui, Jiangxi, Henan, Hubei, and Hunan
Western region	Guangxi, Sichuan, Guizhou, Yunnan, Shaanxi, and Gansu

) to examine the impact of urbanization on industrial transformation and upgrading in different areas.

Table 10. Heterogeneity analysis: distinguishing between the eastern, central, and western regions.

	(1)	(2)	(3)
	Eastern	Central	Western
lnurban	0.5903 ***	0.1461 **	−0.0759 **
	(0.0454)	(0.0675)	(0.0360)
Control variables	yes	yes	yes
Year fixed effect	yes	yes	yes
Area fixed effect	yes	yes	yes
Observations	1314	432	774
R2	0.713	0.745	0.465

Note: Robust standard errors in parentheses, *** p < 0.01, ** p < 0.05.

reports the regression results. The results indicate that the regression coefficient for urbanization in the eastern region is significantly positive at the 1% level in Column (1), while for the central region, it is significantly positive at the 5% level in Column (2). In the western region, it is significantly negative at the 5% level in Column (3). This reflects that urbanization in modern China’s eastern and central regions has a positive impact on industrial transformation and upgrading, with the promoting effect being more pronounced in the eastern region. This might be attributed to the eastern region’s earlier opening to trade, higher level of economic development compared to the central and western regions, and the concentration of national industries, making urbanization more effective in promoting industrial transformation and upgrading. In the case of the western region, due to its lower levels of economic prosperity, urbanization, and openness compared to other regions, along with a significant gap in industrial development, urbanization fails to exert a positive effect.

6.2. Mechanism Analysis

The elevation of urbanization levels in early 20th century China, accompanied by an increase in the proportion of the urban population, constitutes a regional aggregation of human resources. It serves as a vital engine for stimulating production vitality and consumer demand, contributing to enhancing the quality and efficiency of economic development, with a significant positive effect on industrial transformation and upgrading. However, the underlying mechanisms of this impact require further exploration. To elucidate the mechanisms through which urbanization influences industrial transformation and upgrading in modern China, we empirically investigated two channels: the human capital effect and the transportation scale effect. The regression equation is as follows:

lnindus_it = α + βlnurban_it + γlnurban_it × M_it + λM_it + δX_it + μ_t + φ_i + ε_it

(2)

where M_it is the mechanism variable, the human capital effect is measured by the number of church secondary schools (lnschool) and the number of primary and senior pupils (lnpupil), and the transportation scale effect is measured by a dummy variable for whether the railway has been opened (rail), and the rest of the variables are defined as before.

6.2.1. Human Capital Mechanism Effect

During the period of significant societal transformation in modern China, the urban–rural structure underwent major changes, with a continuous flow of the rural population toward urban areas. This migration led to a substantial concentration of populations in towns and cities, which, to a certain extent, facilitated the rational allocation of factors such as labor and capital between urban and rural areas. It also promoted the enhancement of knowledge and skills through education and training, contributing to the formation and accumulation of human capital. As a result, this process provided a rich pool of industrial workers, thereby boosting industrial production efficiency and optimizing structural configurations. This, in turn, empowered industrial transformation and upgrading. Considering the effect of human capital and the availability of historical data, we used the number of church secondary schools (lnschool) and the number of primary and senior pupils (lnpupil) as proxy variables to explore the impact pathways of modern China’s urbanization on industrial upgrading. Due to limitations in historical data, the number of primary and senior pupils is available only for the single year of 1920. Therefore, we used cross-sectional data from 1920 to conduct our analysis.

Columns (1) and (2) of

Table 11. Mechanism analysis.

	(1)	(2)	(3)
lnurban	0.1484 ***	−0.1952 *	0.2389 ***
	(0.0204)	(0.1027)	(0.0218)
lnurban × lnschool	0.2389 ***
	(0.0258)
lnschool	−0.6207 ***
	(0.1134)
lnurban × lnpupil		0.1259 ***
		(0.0246)
lnpupil		−0.4273 ***
		(0.0969)
lnurban × rail			0.2719 ***
			(0.0604)
rail			−0.6932 ***
			(0.2532)
Control variables	yes	yes	yes
Year fixed effect	yes	no	yes
Area fixed effect	yes	yes	yes
Observations	4428	246	4428
R2	0.679	0.710	0.658

Note: Robust standard errors in parentheses, *** p < 0.01, * p < 0.1.

report the results of the mechanism tests for the effects of human capital. The results in Column (1) show that the regression coefficient for the interaction term between the urbanization rate and the number of church-affiliated middle schools is significantly positive, indicating that church-affiliated middle schools enhance the positive impact of urbanization on industrial transformation and upgrading. The results in Column (2) demonstrate that the regression coefficient for the interaction term between the urbanization rate and the count of primary and secondary school students is significantly positive at the 1% level, suggesting that regions with a higher number of primary and secondary school students experience a stronger positive effect of urbanization on industrial transformation and upgrading.

This suggests that areas with higher levels of urbanization in modern China also led to a significant increase in demand for education, which could improve basic education and raise the level of human capital. Consequently, this enhances the knowledge and skills of industrial workers, providing strong conditions for businesses to expand production scales, improve efficiency, and achieve technological advancement, thereby having a positive and active impact on industrial transformation and upgrading in modern China. This successfully validates Hypothesis 1, which posits that urbanization in modern China, through the enhancement of human capital levels, empowers improvements in labor quality and industrial technological progress, thereby promoting industrial transformation and upgrading.

6.2.2. Transportation Scale Effect

The inauguration of modern railways transformed terrestrial transportation, enhancing the connectivity and communication between urban and rural areas, stimulating the prosperity of commercial trade, and providing developmental opportunities for cities along the railway. These cities experienced a significant uplift in economic benefits and urban status. The continual expansion of railways in modern China was instrumental in integrating isolated local markets into a unified large market, accelerating the circulation of goods, reducing transportation costs, and greatly benefiting the development of the industrial and mining sectors. We considered whether the railway had been opened (rail) as a mechanism variable to identify the role that urbanization in modern China plays in the process of industrial transformation and upgrading.

Column (3) of Table 11 displays the regression results for the mechanism test of the transportation scale effect. The coefficient for the interaction term between the urbanization rate and the presence of railway access is positive and significant at the 1% level, indicating that the availability of railway transportation enhances the facilitative effect of population urbanization on industrial transformation and upgrading, thereby validating Hypothesis 2. This implies that areas with higher levels of urbanization in modern China possess more developed railway networks. The expansion of railway transportation has accelerated the mobility of rural and urban populations, significantly promoting the circulation of goods and factors across regions, driving trade prosperity, and optimizing resource allocation. This substantially reduces transportation costs and has a more pronounced promotional effect on the industrial transformation and upgrading in modern China, fostering sustainable regional economic development.

7. Conclusions

Since the modern era, China has experienced profound changes deviating from its traditional operational trajectory. The rural economy and society have been significantly impacted, with the rise of modern cities accelerating the urbanization process. A continuous flow of rural populations into cities has provided a rich source of high-quality labor. Improvements in transportation infrastructure have injected vitality into industrial transformation and upgrading, empowering sustainable economic growth. We utilized historical data from 246 prefectural regions from 1900 to 1927 to construct a fixed-effect model to explore the impact and mechanisms of modern Chinese urbanization on industrial transformation and upgrading.

Research demonstrates that the elevation of urbanization levels in modern China has had a significant positive impact on industrial transformation and upgrading. Empirical testing using econometric models reveals that an increase in urbanization rates leads to a rise in the number of modern enterprises, thereby fostering the development of modern industry and finance, which, in turn, actively promotes industrial upgrading. The robustness of this effect is confirmed. An endogeneity test using the number of postal routes as an instrumental variable further verifies the causal relationship between urbanization levels and industrial upgrading. The impact of urbanization on industrial upgrading exhibits heterogeneity: The promotional effect on secondary industry development is stronger than on tertiary industry; urbanization significantly bolsters commercial enterprises but has a weaker influence on state-affiliated businesses; and it more prominently boosts small and medium-sized enterprises. The facilitative effect of urbanization on industrial transformation and upgrading is notably pronounced in the eastern and central regions, while it appears to inhibit these processes in the western region.

Mechanism analysis indicates that urbanization primarily enhances industrial transformation and upgrading through the channels of human capital effects and transportation scale effects. Increases in urbanization rates improve the level of basic education and promote the accumulation of human capital, providing industries with high-quality labor resources, which enhances workers’ skills as well as industrial productivity and technological progress, thereby facilitating industrial transformation and upgrading. Additionally, the expansion of modern Chinese urbanization has driven the growth of railway transportation, significantly enhancing transport capacity and speed, strengthening regional connectivity and personnel movement, reducing transportation costs, fostering the supply of production factors, improving industrial production efficiency, and thereby promoting industrial upgrading and enabling sustainable and robust economic development.

We empirically validated the promoting effect of urbanization on industrial transformation and upgrading in early 20th-century China, enriching our understanding of the economic growth effects of urbanization and providing historical evidence for the relationship between urbanization and industrial upgrading. It also offers valuable references for the urbanization strategies and industrial policies of contemporary nations, particularly developing countries. However, due to limitations in historical data, we used absolute indicators such as the number and capital of modern enterprises to measure industrial transformation and upgrading during the historical period. In future research, we plan to delve deeper into historical and archival materials to measure core variables more precisely, thus providing more comprehensive data support for studies related to urbanization and industrial upgrading.