Land regulating economy as a policy instrument in urban China

Cities 94 (2019) 225–234

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Land regulating economy as a policy instrument in urban China a

b,d,⁎

Jiayu Wu , Qi Guo

, Geoffrey J.D. Hewings

T

b,c

a

College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, Zhejiang Province, China College of Economic and Social Development, Nankai University, Tianjin 300071, China Regional Economics Applications Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA d Collaborative Innovation Center for China Economy, Nankai University, Tianjin 300071, China b c

A R T I C LE I N FO

A B S T R A C T

Keywords: Land regulation Urban economic growth Lagged effect Two-level land supply regime China

The regulation of urban land in China has become more important as a policy instrument, suggesting that land supply may be a catalyst for urban economic growth. Based on official data on land use change for the period 2005 to 2014, an econometric model of urban GDP growth reveals lagged effects of land supply on economic growth. Land supply has a more significant effect on economic growth in prefecture-level cities than in countylevel cities. City size and development stage also shape the effects of land on economic growth; in addition, land plays different roles in economic growth in eastern coastal cities and in cities in the central and western parts of China. Different land use allocations have been successfully used as a tool for fostering economic growth in urban China.

1. Introduction China has been experiencing rapid economic growth due to its institutional transition from a planned economy to a market system and from central authoritarianism to local corporatism with reforms made to the political economy since 1978 (Lin & Ho, 2003). The financial revenue derived from land has been one of most important sources of local government revenue in China since the “paid transfer of land use rights” programme was instituted in 1988. Local governments manage the land market like a company that focuses on its own revenue, in contrast to the central government, which gives top priority to economic and social sustainable development. This institutional design promotes rapid land urbanization at the local level. Over the last ten years, China has announced several urban policies that promote the construction of more and larger cities, on the one hand, to enhance efficiency as suggested by new economic geography and, on the other hand, to help increase domestic demand. As a result, China is beginning to decrease its reliance on export-lead economic growth and strengthen the role of the “home market” effect, as noted in new trade theory. There appears to be increasing consensus around the notion of urbanization-led growth underlying China's plans for urbanization (Wang, Hui, Choguill, & Jia, 2015). This strategy is seen as a way to boost economic growth, as approximately 60% of China's > 1.3 billion people are expected to live in urban areas by 2020 following the move of 100 million people into the nation's cities. According to the government

⁎

plan, all cities with > 200,000 residents will have a rail connection by 2020, and those with > 500,000 residents will have high-speed rail. Approximately 90% of the population will have access to a nearby airport. The Chinese government realizes that domestic demand will become the fundamental driver of the nation's economic development, and increased urbanization provides the most effective strategy to enhance the expansion of domestic consumption. Rapid land urbanization has reversed the trend of under-urbanization that resulted from China's historical policies and stimulated urban development (Au & Henderson, 2006a). However, rapid urban land expansion has brought about social contradictions related to land acquisition patterns and underlying crises of food security (Deng, Huang, Rozelle, & Uchida, 2006; Lin & Ho, 2005). Previous studies have focused on urban land use changes in post-reform China (see, for example, Lin, 2009; Deng, Huang, Rozelle, & Uchida, 2010) and its relationship with economic growth, with an emphasis on how urban land plays a marginal role in economic growth in the neoclassical growth model (Deng, Huang, Rozelle, & Uchida, 2008; Van der Veen & Otter, 2001). However, much less attention has been paid to China's two-level land supply policies, the role of land use regulation and, critically, the role of ownership. In this paper, the focus is on the other side of the coin: how land supply policies influence economic growth in urban China. Urban land expansion in China has been stimulated by local governments that incentivize investments to promote industrialization by

Corresponding author at: College of Economic and Social Development, Nankai University, Tianjin 300071, China. E-mail addresses: [email protected] (Q. Guo), [email protected] (G.J.D. Hewings).

https://doi.org/10.1016/j.cities.2019.06.009 Received 21 November 2018; Received in revised form 2 June 2019; Accepted 5 June 2019 0264-2751/ © 2019 Elsevier Ltd. All rights reserved.

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in less developed cities. Sub-samples are used in our analysis to measure the influence of city size, type and location on land regulation and economic growth and to highlight this important asymmetry. The paper proceeds as follows. Section 2 reviews the literature on the determinants of economic growth in China, with an emphasis on land as an economic engine. In Section 3, we provide background information on the land supply governance in China, with a particular focus on theoretical explanations of how land use changes have incentivized economic growth since land conversion reforms were instituted in the 1990s. In Section 4, our data are described, and the model is specified. Section 5 discusses the estimation results, while in Section 6, we conclude our findings and discuss the policy implications.

regulating land supply (Lin, 2007; Liu, Tao, Yuan, & Cao, 2008; Ping, 2011; Tao, Su, Liu, & Cao, 2010; Wu, Wang, Zhang, Zhang, & Xia, 2019). Consequently, economic growth in urbanized areas has been fuelled by land development. While land development is controlled to facilitate growth in China, the ways land supply has contributed to economic growth, particularly through special land regulation policies, remain underexplored. The studies on economic growth in urbanized areas have largely focused on short-term physical and human capital, the labour force, and technologies (Barro & Sala-i-Martin, 2004). Land has been generally ignored in standard theoretical models with the assumptions that land is perfectly elastically supplied at a market price and that land influences urban economic trends through other factors, the most prominent of which would be land use policies. In China, land is made available for urban use by requisitioning farmland from rural collectives via compulsory purchase decisions made by governments at different levels (Lichtenberg & Ding, 2009). Municipal officials act as land developers to facilitate economic growth and acquire revenues to develop urban and regional infrastructure. In contrast with local governments, the central government has the responsibility to control the pace of urbanization given issues of food security, social unrest in the countryside and overinvestment in industrial zones. To solve or curb these problems, a series of administrative regulations on land use conversion have been promulgated, and as a result, local officials no longer have the right to supply as much construction land as they want to promote investment. Hence, how land influences economic growth in the future will be conditioned on a more limited land supply, just like capital, the labour force, and technological constraints (Ding & Lichtenberg, 2011). However, policy instruments involve a two-level system of land use control and two types of urban areas. Classical urban economic theory offers little guidance for how best to proceed in China since ownership is centralized, and a “classical” land market is not in operation. Therefore, we demonstrate the extent to which administrative regulations on land supply have rendered the availability of land a generator of or constraint on economic growth in cases where supply is constrained. Our study contributes to the literature in two important ways. First, the land supply regime in China, which differs from that in other countries, should be considered when investigating the effects of available land on economic growth. Currently, two levels of land supply are found in China. China's land regulation policy represents a topdown approach to controlling the quantity of newly added construction land to ensure food security, while local municipalities, under strict control from the central government, explore the best allocation of land supply by adjusting land use structures. Our study estimates such contributions based on an exploration of the central government quota control and the land use structural adjustments of local governments. The land management system was initially set up under the Land Administrative Law, which was proposed in 1998 and finalized in 2004. Under this system, the leasing of profit-oriented land was initiated only through bidding, auctioning and listing. Therefore, the study period for this paper runs from 2005 to 2014, and the relevant yearly data are recorded in the most recent statistical yearbooks. We investigate factors influencing the economic growth in the administrative districts of 286 municipal cities and 364 county-level cities from 2005 through 2014 using the system-GMM estimation that can address endogeneity issues. This paper is one of the first attempts to use county-level cities to estimate the effect of land on economic growth in consideration of its active and important role. Second, this paper reveals the heterogeneous effects of land use on economic growth across cities with different characteristics in terms of size, location and development phase. Taking urban location as an example, cities along the eastern coast of China benefit more from per capita urban land than the central and western cities. In addition, administrative regulations launched by the central government on land supply may act as a binding constraint in highly developed cities, while increasing land allocation may not bring about rapid economic growth

2. Literature review 2.1. Productive factors, institutional reforms and economic growth Previous studies on economic growth in urban China have investigated how productive factors (e.g., capital, labour and technology) promote or restrain productivity and institutional reforms. One line of study has examined how agglomeration economies promote economic growth through input-output linkages, labour market skill matching, knowledge spillovers, and demand for variety (Fujita & Thisse, 2002). Lin and Song (2002) conducted a study of 189 Chinese cities over the period of 1991–1998 and found that FDI, infrastructure investment, and investment in human capital contribute positively to per capita GDP growth, while the effects of domestic investment and population growth have been negative. Similar empirical results from Anderson and Ge (2004) on the urban growth rates in 220 Chinese cities confirm that FDI has contributed more to growth, especially since 1990, while population growth has contributed negatively to growth in GDP per capita. Through a long-term analysis covering the period from 1978 to 2000, Zhang (2002) showed that economic growth is generally accompanied by an increase in FDI and in job opportunities in the secondary and tertiary industries. On the other hand, Au and Henderson (2006a, 2006b) exploration of economic growth in urban China from 1990 to 1997 shows that economies of scale have resulted as a consequence of population size in Chinese cities. In addition, the contributions of human capital accumulation to economic growth have been increasing over time (Anderson & Ge, 2004). In such studies, time series (Zhang, 2002) and cross-sectional analyses (Anderson & Ge, 2004; Au & Henderson, 2006b) have been the methods most commonly used. Another line of study has documented how decentralization and the fiscal institutional reforms of the 1990s have contributed to economic growth. The Chinese central government granted more autonomy to local governments and allowed them to retain a larger portion of taxes and other revenues. As a result, local governments became more motivated to attract investment. Empirical studies have investigated the contributions of decentralization to Chinese economic growth based on provincial-level data for 1970–1993 (Lin & Liu, 2000) and 1982–1992 (Jin, Qian, & Weingast, 2005); in both cases, the results showed that decentralization has increased economic growth rates. Studies on the significance of institutional land reforms for economic growth in China have mostly focused on rural areas, with attention, for example, to the role of tenure security in land quality investment and in agricultural productivity more generally (Benjamin & Brandt, 2002; Deininger & Jin, 2003; Jacoby, Li, & Rozelle, 2002). However, economic growth is mostly based on the development of urban rather than rural land. Therefore, the role of urban land is the focus of our study, although the increase in the supply of urban land is primarily derived from the conversion of agricultural land. 2.2. Land as an economic growth engine A large number of studies have highlighted the prevailing trend of 226

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such as state-owned enterprises, collectives, and army organizations, engaged in land leasing by illegally transferring freely allocated land to developers. This created chaotic land markets and weakened the government control over the land supply. To strengthen government intervention, Hangzhou established a land banking centre in 1997 that has been regarded as successful in terms of preventing land speculation. By 2009, > 2000 cities and counties had established their own land banking organizations (Liu, 2003) in response to a policy encouraging local governments to establish their own land banks. As a consequence, governments have achieved more control over land markets as sole suppliers of land in the primary market, allocating land free of charge. In the early 2000s, the Chinese economy entered a new period of development. The central government addressed illegal land supply from runaway investments and announced that land policies would be applied as a major facet of national economic macro-control measures beginning in September 2003. Currently, two levels of land supply have been formed, and these levels are critical for understanding land supply policies in China (Wu et al., 2018). The central government and local governments have different objectives in regard to land supply. The central government adopts a strict approach towards sprawl (Zhang, 2000): food security is the primary concern, with urban development being a secondary goal. Local municipalities, under tightened quantity control from the central government, explore the best use of the land supply by adjusting land use structures. Hence, based on the land supply conditions in China, our analysis is divided into two parts: the central government allocates a construction land quota, and the local government arranges urban land use allocations.

land supply as an outcome of urban economic growth (Lin & Ho, 2003; Wu, Su, & Zhang, 2006; Wu & Zhang, 2012). For instance, Ho and Lin (2004) show that agricultural land conversion is affected by urbanization, industrialization, rapid economic growth and increased investment in transport infrastructure. Economic growth has significantly increased the land resource demand, increasing the amount of agricultural land to be converted for non-agricultural purposes, such as for residential use, industrial facilities, and transportation infrastructure (Ho & Lin, 2004; Lin, 2007). However, land serves as a means of economic leverage in China as much as it acts as a factor of production. Land supply has been found to fuel local urban growth (Liu et al., 2008). Urban land for industrial and commercial activity increases local budget revenues through value added, income and business taxes (Liu et al., 2008; Tao et al., 2010). Lichtenberg and Ding (2009) showed that land development activities have facilitated urban economic incentives in China. Ding and Lichtenberg (2011) demonstrated that land availability has a stronger impact on economic growth than domestic and foreign investment, labour supply, and government spending, as indicated by the elasticities calculated from estimated coefficients. He, Huang, and Wang (2014) confirmed that land, when used as a development tool, successfully attracts foreign investment and sustains infrastructure investments, indirectly triggering economic growth. The existing literature does not show how different forms of land leasing (for residential, industrial and commercial use) have contributed to economic growth, although the impacts of land conversion to industrial or urban uses on economic growth are estimated in He et al. (2014). Regional differences and urban characteristics influence land regulation and economic growth, but they are ignored in the existing literature. Most importantly, few studies have explored how the two-level land supply regime regulates economic growth in China. This issue is elaborated in the next section.

3.2. The central government's land quota allocation As the loss of arable land became a serious problem not only economically but also politically, the central government initiated a new policy to control over-expansion in order to preserve cultivated land and ensure an adequate provision of food. China's land regulation policy applies a top-down approach to controlling the quantity of newly added construction land. First, no farmland could be converted for non-agricultural use until April 1997 due to an administrative order issued by the central government to gain time to redesign the national-level land use policies. Second, a land quota system was established through the 1998 Land Administrative Law that grants regulatory authority under the control of the central government. Each level of government from the central government to the township governments must formulate land master plans and annual land use plans in conformity with the plans of a higher administrative level (i.e., municipal land use plans must be approved by provincial governments, while provincial land use plans must be approved by the State Council). The land master plan sets long-term regulations on the quantity of newly added construction land in a locality, and these long-term objectives are broken down by the annual land use plan for each year. Based on quantitative measures referred to as “newly added construction land quotas”, these land use plans regulate construction land that can be converted from agricultural uses over an entire planning period. The annual plan further specifies land use regulations for each individual lot. For any increase in urban construction land, newly added construction land quotas must be acquired through the master plan and annual plan before conversion can occur. Third, a local government that has used all of its “newly added construction land quotas” must recreate the same amount of farmland if it still wishes to convert farmland into non-agricultural land. Land that can be developed into new farmland includes vacant land previously used as urban space and idle land in rural areas. In sum, the central government uses newly added construction land quotas to control the land supply. The effects of such quantity control over land conversion vary across urban development stages, city sizes, and geographic locations. China's eastern coastal provinces have

3. Two-level land supply regime: study background 3.1. Land supply regime in China Since the establishment of the People's Republic of China in 1949, land policies have changed drastically and frequently through several phases (Tian & Ma, 2009). During the pre-reform era (from 1949 to 1978), China nationalized urban land, as all land was considered publicly owned due to the political promise to use land as common property. This created two serious problems. First, economic and social opportunities were not exploited, as land was assigned free of charge (Dowall, 1993). Second, the approach caused serious free rider problems and low productivity, as, for instance, state-owned enterprises not only claimed more land than they needed but also wasted and misused land (Tang, 1989). The “paid transfer of land use rights” whereby “land use rights can be transferred in conformity with concerned laws” was officially instituted through a constitutional amendment made in 1988 (Wu, Song, Lin, & He, 2018). Urban land markets were divided into three levels based on the transfer of land use rights. The primary market makes up the first level, in which collective land is converted into state land, while in the second level market, land use rights are allowed to be transferred between the state and individuals or corporations (Xia, Zhang, Wang, Zhang, & Zhang, 2019). The third level of the land market refers to the partial transfer of land use rights between individuals and corporations in line with government regulations (e.g., the rental or mortgaging of land use rights). With the establishment of the paid transfer of land use rights, China's real estate market started to emerge, directly resulting in “real estate fever.” In 1993, the government announced measures to strengthen its control over the country's overheated real estate market, tighten monetary policies and accelerate banking system reforms. Soon after the establishment of land use rights, various landholders, 227

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experienced high levels of development but also have the most productive farmland, while its western provinces have experienced less development and have relatively poor farmland. Thus, Eastern China is likely to experience constraints imposed by restrictions on land supply for economic growth, while Western China is much less likely to experience such constraints. We first estimate the effects of these central government quantity controls on urban economic growth. Then, we reflect on how land supply as a policy instrument of the central government triggers or constrains the urban economy.

3.3. Local government urban land use structures Fig. 1. The analysis framework.

Local governments acquire annual newly added construction land quotas from higher levels of government and divide these quotas into different forms of land use (e.g., residential, industrial, commercial and other infrastructure). In other words, local governments have the power and responsibility to design land use layouts based on the central government's quotas. The urban land use master plan and urban master plan are two major instruments used to adjust the land use structure in consideration of the demands of economic growth. Article 17 of the Urban and Rural Planning Law stipulates that the master plans of cities and towns shall include functional zones, land use layouts, comprehensive traffic systems, regions restricted from or appropriate for construction, plans for various forms of special land use, etc. The 1998 Land Administrative Law states that land use plans must increase land utilization (Article 19-2) and organize the overall use of land of various kinds and in various areas (Article 19-3). The land use patterns of each city are a product of China's longstanding national policies. Adjustments of the land use structure through the land policy instruments used by local governments regulate urban economic growth differently in different development stages. Different from the governments of Western countries, the Chinese Communist Party considered industrialization a top priority in the early stage of the regime, and the urbanization process was strictly regulated. Specifically, the expansion of urban areas lagged behind industrialization, and the housing and real estate sectors grew more slowly than the manufacturing sectors, a process different from that observed in developed countries. A lack of investment in urban areas and especially in the urban housing sector resulted in inadequate infrastructure, an overcrowded population, poor housing conditions, and substandard urban environments. Hence, to promote land urbanization processes and develop the real estate market, local governments, especially in Eastern China, are currently seeking to rearrange the land use structure, with more emphasis on other forms of land use in addition to industrial land, and thereby foster economic growth (Yeh, Yang, & Wang, 2015). However, cities in Western China continue to experience much less economic growth and greater poverty-related issues, so local governments allocate more land to the manufacturing sector to trigger urban economic growth and industrialization. Local governments generally weigh the costs and benefits of each land use form and lease land to the most profitable markets. For instance, the real estate market is a prime investment area that brings the most fiscal revenue for cities. Local governments supply a considerable amount of residential land to meet market demand. However, the residential housing market has experienced a sharp decline since the initiation of the house purchase restriction that aims to contain speculative demand by restricting the qualifications of purchasers and the number of houses one family owns. As a result, new home prices reduced in the country's largest cities and recorded slower increases in other major cities monitored by the government. In summary, as Fig. 1 shows, local governments can regulate urban economic growth by adjusting land use structures based on urbanization stages and economic conditions, although they do not engage in quantity control in the same fashion as the central government.

4. Data and model specification Land supply can trigger local economic growth, which in turn spurs more land development. Land in China not only represents economic leverage as a productive factor (He et al., 2014) but also is the result of economic development. In addition, land as an input of production might be correlated with unobserved factors that influence outputs (Ding & Lichtenberg, 2011). Therefore, we use the system generalized method of moments (GMM) that is designed to estimate dynamic panel models (Blundell & Bond, 1998). The system-GMM model sets a system of equations in differences and in levels and uses lagged levels and the first lag of the first differences as instruments (Arellano & Bover, 1995; Blundell & Bond, 1998). The advantage of this model, in addition to ensuring the consistency of estimates, is its flexibility in generating instruments and the ability to address the endogeneity issues that may be present in the model. The results of the Sargan test and tests for under-identification and weak identification show that there is no correlation between the instruments and the residuals and validate the use of lagged variables as instruments. The econometric model is constructed as follows:

∆GDPi, t = α1 ∆GDPi, t − 1 + β1 ∆LANDi, t + γ1 Xi, t + εi, t

(1)

where ΔGDPi, t and ΔLANDi, t are the differences between corresponding values in year t and year t-1 for GDP growth and newly added land use in the urban area of city i, respectively. ΔGDPi, t−1 is the lagged variable of ΔGDPi, t. Xi, t denotes all control variables, including employment growth (ΔLABOR), physical capital growth (ΔCAPITAL), growth of human capital (ΔEDU), the spatially lagged variable of ΔGDPi, t (Wy) and industrial structure (STRUCTURE). Using dummy variables, we also control for prefecture-level cities (PREFECTURE), cities located in Eastern China (EAST) and cities located in Central China (CENTRAL). We estimate the parameters of the panel data models on the districts of 286 Chinese prefecture-level cities and on 364 county-level cities1 for 2005–2014, accounting for a total of 5753 observations. Depending on whether residential, industrial, commercial or infrastructural facilities require a certain amount of time to be constructed after land is made available, land newly made available for various uses may have a lagged effect on urban economic growth. The econometric model of the lagged effect of land is as follows.

1

The administrative region of Chinese prefecture-level cities covers three types of regions, including prefecture-level district, county-level city and county. The county is generally a rural region, while the prefecture-level district is an urban region. Some counties whose industrialization and urbanization development are well advanced are set up as county-level cities that have more independent political, economic and social management authority than prefecture-level cities. The Chinese prefecture-level cities that are considered by most previous studies cover a large rural area. To exclude the effect of rural areas on the results, this study attempts to use more detailed data, considering the prefecture-level district and county-level city. 228

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Table 1 Variables and measures. Variable

Definition

△GDP △LANDt-n △LABOR △CAPITAL △EDU Wy PREFECTURE EAST CENTRAL STRUCTURE

Difference between GDP for year t and year t-1 Newly-added land use in lagged n-th year; n = 0,1,…,4. Difference between employment for year t and year t-1 Difference between capital for year t and year t-1 Difference between number of college students for year t and year t-1 The spatial lagged variable of △GDP; the spatial matrix W is defined as 1 if city A belongs to the same province with the city and 0 if not. Dummy variable, 1 for prefecture-level cities, 0 for county-level cities Dummy variable, 1 for cities located in eastern China, 0 otherwise Dummy variable, 1 for cities located in Central China, 0 otherwise The ratio of value-added of secondary and tertiary industries in GDP

∆GDPi, t = α1 ∆GDPi, t − 1 +

t

∑t−n

βn ∆LANDi, t − n + γ1 Xi, t + εi, t

Chinese province-level GDP deflator and reported in million RMB; employment and population levels for each year measured in 10,000 persons; fixed assets investment levels deflated by the provincial fixed assets investment deflator and reported in million RMB; the number of college students; and the ratio of value added of the secondary and tertiary industries in GDP. Descriptive statistics of the sample used in the analysis are given in Table 1. According to the theoretical and realistic analysis above, we expect that land supply can boost urban economic growth in China but that a lagged effect may exist. In addition, different types of land have different effects on the urban economy; hence, it is important to explore the heterogeneous effects of land use on economic growth across cities with different characteristics in terms of size, location and development phase.

(2)

where n denotes the lagged year and where βn is the effect of land made available for use in year t-n on the urban economic growth in year t. In addition, the effect varies across urban administrative levels, locations, sizes and development stages, so we separate the overall samples into subsamples based on different characteristics. First, all of the samples are divided into prefecture-level districts and county-level cities because they differ in terms of urbanization level, city size, function and other aspects. Second, we estimate models for Eastern, Central and Western China to investigate differences in the productivity of urban land in areas experiencing markedly different economic growth rates and land availability pressures. Eastern China (including the provinciallevel cities of Beijing, Tianjin, and Shanghai and the provinces of Liaoning, Hebei, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Guangxi, and Hainan) has experienced very rapid economic growth. Central China (the provinces of Shanxi, Inner Mongolia, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, and Hunan) has experienced less rapid economic growth, while Western China (the provinces of Chongqing, Sichuan, Guizhou, Yunnan, Xizang, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang) has experienced the lowest levels of economic growth overall. Third, the percentile approach is used to investigate the effects of city size and development stage on land growth. The top 25% of cities in terms of urban population are defined as large cities, while the lowest 25% are defined as small cities. Cities in the top 25% in terms of non-agricultural outputs in urban areas are defined as high-level urbanized cities, while those in the lowest 25% are defined as low-level urbanized cities. To estimate how adjustments of the land use structure by local governments affect urban economic growth, we divide land uses into four types: (1) residential land (LAND_RES); (2) industrial land (LAND_IND); (3) land used for administration, public services, and public facilities, including commercial and business facilities (LAND_PUB); and (4) other land used for logistics, warehouses, roads, green spaces and squares, and municipal utilities (LAND_OTHERS). Land use change is still lagged by n years. The econometric model is constructed as follows. In the model, the influence of city size and development stage on land growth effects is investigated via the percentile approach.

5. Results Simple correlation analysis was conducted to compute the relationship between GDP increment and different lag orders of land supply newly made available. The results show that GDP growth and land supply are significantly correlated, with a correlation coefficient ranging from 0.0408 to 0.238 (Table 2). The correlation analysis suggests no serious problem of multi-collinearity, especially among different lag orders of land supply newly made available. The estimated parameters of all of the models are given in Tables 3–6. Overall, the models fit the data well. Almost all of the coefficients are significantly different from zero and have signs that conform with the expectations both for quota control by the central government and for adjustments of the land use structure by local governments regardless of city location, size and development stage. The relative magnitudes of the estimated coefficients are in accordance with the existing literature and with our expectations. 5.1. The impacts of quota control on urban economic growth The most important discovery gleaned from our study is the lagged effect of land supply on economic growth. As shown in Table 3, we find that the R2 changes from 0.1443 to 0.7340 when the lagged variable that documents the area of land supply is included in the model for each year and peaks in Eq. (3). The parameters are standardized to compare the differences among the lagged effects of land supply. The coefficient of urban land in the central government model is significantly different from zero. It is clear that land supply has the strongest influence on economic development after the third year, as lagged effects may result from abnormally low levels of administrative efficiency. For example, for the city of Guangzhou, the launch of a project involves the coordination among > 20 departments in terms of development and reform, planning, and land use and the completion of > 200 administrative steps of assessment and approval. Each department serves as a prerequisite for another, with adjustment and approval involving a series of consultations that can take 300–500 working days and extends

∆GDPi, t = α1 ∆GDPi, t − 1 + INDi, t − n +

t

t

∑t−n

∑t−n

β1n ∆LAND _RESi, t − n +

β3n ∆LAND _PUBi, t − n +

OTHERSi, t − n + γ1 Xi, t + εi, t

t

t

∑t−n

∑t−n

β2n ∆LAND _

β4n ∆LAND _ (3)

We obtained data from two sources. The data for the urbanized land area in each city were drawn from the China Urban Construction Statistical Yearbook that documents land conversions between urban and nonurban areas in detail. Economic and demographic data, derived from city statistical yearbooks, include information on overall and sector-specific GDP (primary, secondary, and tertiary) deflated by the 229

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1 0.2106 −0.0126 0.0135 0.056 0.0603 0.0395 −0.0121 0.0515 3180 3.777998 53.01316 −994.2 2429.08 1 −0.1568 0.0232 0.0312 0.0202 0.0592 0.068 0.0339 −0.0153 0.053 3816 3.81146 51.44097 −994.2 2429.08

1 0.1677 0.0625 −0.0462 −0.0436 0.1477 −0.041 0.1145 5724 2.081718 9.528823 −189.523 263.8

1 0.0801 0.1879 0.1854 0.0725 −0.0232 0.1407 5647 34.21384 98.30753 −2720.5 1819.156

1 0.0047 0.0071 −0.0027 0.0116 0.0528 5724 0.353333 1.864341 −53.7043 63.0977

1 0.9895 −0.1003 0.0504 0.0654 5724 13,690.86 8028.052 5277.425 27,605.49

1 −0.0979 0.0494 0.0688 5724 0.446541 0.497177 0 1

1 −0.4405 0.1784 5724 0.358491 0.479599 0 1

1 0.011 5724 0.257862 0.437496 0 1

1 5724 0.908886 0.272157 6.91E−07 2.158537

the approval period to 2–3 years.2 These results are in accordance with the current nature of land development in China, and it is meaningful to understand the mechanisms of the land regulation economy as a policy instrument. Land supply has a positive effect on prefecture districts and countylevel cities (see Table 4). However, it has a more significant effect on economic growth in prefecture cities than in county-level cities according to a comparison of coefficients, as the land in the prefecture districts is used more efficiently than that in county-level cities. The regionally disaggregated models show that land has a more marked influence on urban economic growth in China's rapidly growing coastal provinces, and the coefficient of urban land is significantly different from zero for the first three years for the central or western provinces (see Table 4). The results shown in Tables 5 and 6 illustrate that city size and development stage affect the economic growth pattern fostered by land features. We find that land plays a more important role in larger and more developed cities. In the lower quartile cities defined in terms of development stage (see Table 5), land influences growth negatively. We suggest that this output relates to land use efficiency. These results suggest that land supply has catalysed economic growth in China, albeit primarily in the developed coastal region. This finding suggests that relaxing quota control constraints on requisitions of rural land has been an important contributor to economic growth in China's coastal provinces. In other words, land is equally a cause and a result of economic growth. The lower significance found for the estimated coefficients for most years for Central and Western China implies that land supply has simply not stimulated economic growth in these regions. The results of our econometric analysis suggest that land supply in the western region controlled by the central government has been more than adequate to accommodate urban economic growth; the growth rates in these provinces are determined by a relaxation of the constraints on physical capital and labour force rather than by land. The negative signs of the two coefficients may be attributed to the fact that the local governments of Central and Western China have engaged in excessive levels of speculative land conversion and have reserved land conversion quotas in suburban areas (e.g., economic development zones) for the purpose of attracting more investment. As noted earlier, there has been substantial speculative land conversion of this form. This explanation seems most applicable to central and western cities. 5.2. The impacts of land structure adjustments on urban economic growth Local governments acquire an annual newly added construction land quota from higher levels of government and divide this quota into different forms of land use. Different types of land use changes affect economic growth in different ways. This study explores the relationships between changes in residential, commercial, industrial and other land use and economic growth in urban China. We separately examine the land use change-growth relationship for different types of land use. The results shown in Table 6 reveal that, in general, residential land supply fosters economic growth. The estimated results need to be viewed with some caution, as the significance of the coefficients varies when the lagged factors are added. However, the coefficients of residential land supply in the sub-models of columns 3 through 6 are almost always significant. Residential land plays different roles in the largest and smallest cities. The two- or three-year lagged effects generate a prominent impact for economic growth in larger cities, while land supply unexpectedly restrains the GDP growth of smaller cities. In recent decades, the urban economies of China have developed rapidly as a result of the prosperous real estate markets in metropolitan areas (Shun & Kangping, 2004). The reform of China's urban land supply policy has encouraged the formation of various land production

△GDP LANDt △LANDt-1 △LANDt-2 △LANDt-3 △LANDt-4 △LABOR △CAPITAL △EDU Wy PREFECTURE EAST CENTRAL STRUCTURE Obs Mean Std. Dev. Min Max

1 0.0545 0.0408 0.0634 0.2475 0.2308 0.3054 0.4169 0.0965 0.2225 0.2359 0.1891 −0.0788 0.2022 5724 45.73384 125.8366 −1020.82 2035.751

1 −0.487 0.007 0.0111 0.0019 −0.0045 0.0303 0.0302 0.0265 0.026 0.0045 −0.0025 0.0152 5724 3.458126 77.54663 −3448.7 3454.17

1 −0.6392 −0.0061 0.0207 0.0371 0.023 −0.0163 0.0247 0.0238 0.0055 −0.0026 0.0131 5088 3.344544 81.99563 −3448.7 3454.17

1 −0.0978 −0.0114 0.0016 0.0299 0.0122 0.0193 0.0245 −0.0039 0.0232 0.0383 4452 4.294352 70.44116 −994.2 3454.17

△LANDt-4 △LANDt △GDP

Table 2 Correlation analysis and descriptive statistics.

△LANDt-1

△LANDt-2

△LANDt-3

△LABOR

△CAPITAL

△EDU

Wy

PREFECTURE

EAST

CENTRAL

STRUCTURE

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2 Contrast this with the analysis reported in Kim and Hewings (2013) of the top 40 metropolitan regions in the US.

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Table 3 The effect of newly-added land use in year t-n on urban economic growth. (1) △LANDt

(2)

(3)

(4)

−0.007*** (0.002)

0.003*** (0.001) 0.006*** (0.001)

0.035*** (0.001) 0.071*** (0.001) 0.110*** (0.001)

0.038*** (0.002) 0.081*** (0.002) 0.123*** (0.002) 0.077*** (0.002)

0.032*** (0.003) 0.150*** (0.003) 0.007*** (0.002) 0.169*** (0.008) −0.024** (0.012) 3.182*** (0.253) 1.429*** (0.250) −0.010 (0.474) 0.002 (0.003) −1.835*** (0.235) 5030 636 0.1462 0.000

0.030*** (0.003) 0.150*** (0.003) 0.008*** (0.002) 0.175*** (0.008) −0.024** (0.012) 3.089*** (0.251) 1.610*** (0.241) 0.740** (0.314) 0.004 (0.003) −2.013*** (0.222) 5030 636 0.1443 0.000

0.038*** (0.003) 0.143*** (0.004) 0.008*** (0.002) 0.129*** (0.010) −0.020 (0.015) 3.266*** (0.255) 0.397 (0.249) −0.933*** (0.227) 0.000 (0.003) −1.210*** (0.207) 4413 636 0.1656 0.000

0.036*** (0.004) 0.110*** (0.006) 0.007*** (0.002) −0.003 (0.012) −0.033 (0.029) 5.263*** (0.465) 0.836** (0.400) −0.032 (0.398) −0.002 (0.003) −2.384*** (0.364) 3796 636 0.7340 0.001

△LANDt-1 △LANDt-2 △LANDt-3 △LANDt-4 △LABOR △CAPITAL △EDU △GDPt-1 Wy PREFECTURE EAST CENTRAL STRUCTURE Constant Observations Number of city AR2 Sargan

(5) 0.039*** (0.003) 0.078*** (0.005) 0.114*** (0.006) 0.075*** (0.003) 0.053*** (0.004) 0.026*** (0.005) 0.115*** (0.015) 0.004 (0.003) −0.074*** (0.019) −0.013 (0.034) 4.817*** (0.632) −0.047 (0.657) −0.433 (0.497) 0.085** (0.041) −1.860*** (0.426) 3179 636 0.1948 0.076

Standard errors in parentheses and *p-value < 0.10; **p-value < 0.05; ***p-value < 0.01. All results are based on system GMM. In all GMM instrumented estimations, newly-added land use are treated as potentially endogenous. The values for AR2 are the p-values for the 2-order autocorrelation test proposed by Arellano and Bond (1991). The autocorrelation test AR2 indicates that instruments cannot be considered invalid due to autocorrelation, and the Sargan test for joint validity of the instruments always accepts the null hypothesis that instruments are valid. In the GMM instrumented estimations, △LANDt is treated as potentially endogenous.

not robust. We speculate that the reason is complex. The other forms of land supply contain warehousing land, land for transportation networks, administrative land, etc., that are likely to have different impacts on economic growth. The logistics industry in China has grown rapidly as the country's economy boomed. The development of manufacturing industries and e-commerce and improvements in infrastructure have driven robust year-on-year growth of 9.8% in the logistics industry in China. Land supply for transportation may be positively related to urban economic growth. More land converted into highways, railways and streets is likely to improve regional transportation networks by enhancing both internal connectivity within the city and interregional connectivity between cities. The expansion of land for transportation might limit the land available for industrial activities that are still a crucial pillar of urban development; however, without enhanced connectivity, industrial development might be limited.

elements, promoting the development of China's real estate market. Over the last decade, China's real estate market has become a driving force of national economic development (Zhang, 2008). We must recognize that the residential land supply effectively stimulates economic growth in larger and more developed cities, while it has a negative effect on the urban economies of smaller cities. A positive effect similar to that found for residential land supply is also found for industrial and commercial land supply (see Table 6). Industrial and commercial land supply triggers development in the manufacturing and service industries. Local governments have metamorphosed into tax collectors with the 1994 fiscal reform and have since paid more attention to expanding businesses in their jurisdictions, with a focus on two forms of business, i.e., manufacturing and services (Tao et al., 2010). As a result, numerous “industrial parks” and “development zones” were created across China's urban and rural landscapes. Land as a key input of any industrial or commercial project is still not fully marketed, and local governments are allowed under the current land administration system to supply low-cost land to attract investment from industrial and commercial investors. Therefore, since the second half of the 1990s, the additional supply of land has become a key instrument of inter-regional competition for investment in China. In larger and more developed cities, however, commercial and industrial land areas significantly affect economic growth, while in smaller and less developed cities, such land may have a negative effect. Lower land costs appear to be ineffective in attracting investors, especially in lagging regions (see Table 6). As shown in Table 6, other forms of land supply are highly negatively correlated with the urban economy. Nevertheless, the results are

6. Summary and discussion Our study examines the role of land supply in urban economic growth by estimating a dynamic panel model based on the data for the districts of 286 Chinese prefecture-level cities and 364 county-level cities for 2005–2014. The model provides empirical evidence for the importance of land supply for urban economic growth in China. The importance of land supply to urban economic growth is especially pronounced in eastern coastal cities. In contrast, urban economic growth is not affected by land availability in the central and western regions. We also find that the land supply in larger and more developed cities fosters economic growth, while that in smaller and less developed 231

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Table 4 The effect of city administrative level and urban location on newly-added land influencing economic growth. Variables

△LANDt △LANDt-1 △LANDt-2 △LABOR △CAPITAL △EDU △GDPt-1 Wy PREFECTURE EAST CENTRAL

City administrative level

Urban location

Prefectural city

County-level city

0.152*** (0.007) 0.125*** (0.002) 0.172*** (0.002) 0.698*** (0.034) 0.202*** (0.005) 0.563*** (0.118) 0.267*** (0.009) −0.000 (0.000) 13.700 (18.182) −391.150*** (40.545) −0.883 (1.407)

0.007*** (0.001) 0.007*** (0.003) 0.012** (0.005) −0.011 (0.022) 0.074*** (0.007) −0.033 (0.149) −0.124*** (0.014) 0.001*** (0.000) 32.767*** (7.196) 1.297 (9.601) 11.545 (15.656)

153.887*** (15.058) 1988 284 0.1088 0.0350

−11.922 (13.045) 2425 352 0.5848 0.0089

East

STRUCTURE Constant Observations Number of city AR2 Sargan

Central

West

0.233*** (0.010) 0.118*** (0.001) 0.201*** (0.002) 0.944*** (0.019) 0.209*** (0.003) 1.327*** (0.431) 0.216*** (0.004) 0.001*** (0.000)

0.031*** (0.002) 0.060*** (0.004) 0.090*** (0.007) 0.036 (0.045) 0.141*** (0.004) 3.867*** (0.209) 0.056*** (0.008) 0.001*** (0.000)

0.037*** (0.001) 0.009*** (0.001) 0.030*** (0.001) 0.121*** (0.012) 0.189*** (0.002) −0.487*** (0.025) 0.103*** (0.003) 0.000 (0.000)

−3.384*** (1.026) 370.040*** (19.063) −88.331*** (14.922) 1568 228 0.3317 0.0000

−6.150*** (0.634) 308.244*** (13.775) −132.618*** (10.101) 1143 164 0.6227 0.0130

2.942*** (0.586) 273.174*** (21.298) −96.594*** (16.771) 1702 244 0.2731 0.0045

Note: Standard errors in parentheses; ***p < 0.01, **p < 0.05, *p < 0.1; in the GMM instrumented estimations, △LANDt is treated as potentially endogenous. Table 5 The effect of urban size and urban development stage on newly-added land influencing economic growth. Urban size

△LANDt △LANDt-1 △LANDt-2 △LABOR △CAPITAL △EDU △GDPt-1 Wy PREFECTURE EAST CENTRAL STRUCTURE Constant Observations Number of city AR2 Sargan

Urban development stage

Lower quartile

Upper quartile

Lower quartile

Upper quartile

0.329*** (0.041) 0.075*** (0.026) 0.088*** (0.028) 0.249*** (0.032) 0.007** (0.003) −0.023 (0.097) −0.183*** (0.007) 0.000*** (0.000) −1.697 (3.724) −15.563*** (3.133) −6.147** (3.018) 4.570*** (1.140) 8.671*** (1.670) 1090 159 0.5538 0.0514

0.098*** (0.007) 0.117*** (0.002) 0.161*** (0.001) 0.732*** (0.023) 0.202*** (0.005) 0.487*** (0.090) 0.159*** (0.007) −0.000 (0.000) 11,403.594 (8175.243) 83.586*** (24.719) −303.204*** (44.865) −1.488 (1.739) −11,117.392 (8174.373) 1113 159 0.2150 0.0581

0.027** (0.011) −0.124*** (0.009) −0.291*** (0.008) −0.004 (0.026) 0.084*** (0.002) 0.091 (0.183) −0.140*** (0.006) 0.001*** (0.000) −21.432*** (2.034) 8.617*** (2.947) 11.112*** (2.887) −1.614*** (0.471) 8.134*** (1.400) 1106 159 0.3019 0.0479

0.053*** (0.001) 0.096*** (0.001) 0.154*** (0.001) 0.174*** (0.008) 0.184*** (0.003) 1.133*** (0.303) 0.187*** (0.003) 0.002*** (0.000) 366.868*** (18.628) 306.960*** (34.031) 152.201*** (40.508) −8.565*** (1.409) −303.098*** (40.860) 1105 159 0.1617 0.0079

Note: Standard errors in parentheses; ***p < 0.01, **p < 0.05, *p < 0.1; in the GMM instrumented estimations, △LANDt is treated as potentially endogenous.

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Table 6 The effect of different forms of land use on urban economic growth. Variables

All cities

Size smallest

Size biggest

Development stage lowest

Development stage highest

Residential land supply △LAND_RESt △LAND_RESt-1 △LAND_RESt-2 △LAND_RESt-3 △LAND_RESt-4

−0.377*** 0.014 0.622*** 0.536*** −0.025

−0.461*** 0.466*** 0.597*** −0.192*** −0.200***

−0.885*** 0.059** 0.697*** 0.633*** 0.101***

−0.154*** −0.527*** −0.806*** −1.822*** −0.761***

2.400*** 1.198*** 0.578*** 1.881*** −0.136***

Industrial land supply △LAND_INDt △LAND_INDt-1 △LAND_INDt-2 △LAND_INDt-3 △LAND_INDt-4

2.313*** 2.146*** 1.567*** −0.052 2.527***

1.367*** 0.930*** 0.292*** 2.354*** 0.637***

2.431*** 1.716*** 1.038*** −0.149*** 2.432***

−0.272*** −0.302*** −0.423*** −1.332*** 0.988***

0.829*** 0.706*** 0.580*** −1.837*** 1.679***

Commercial land supply △LAND_PUBt △LAND_PUBt-1 △LAND_PUBt-2 △LAND_PUBt-3 △LAND_PUBt-4

1.257*** 1.102*** 1.139*** 2.067*** −0.023

1.115*** −1.064*** −2.204*** −3.316*** −2.392***

2.152*** 2.135*** 2.345*** 3.027*** 0.750***

−1.013*** −2.312*** −5.182*** 4.571*** −0.095

2.866*** 3.148*** 3.367*** 1.177*** 1.773***

−0.529*** −0.976*** −0.884*** 0.372*** −0.116*** Yes 3179 636 0.6151 0.0209

0.544*** −0.107** 0.216*** 0.453*** 0.829*** Yes 794 159 0.3092 0.1001

−0.350*** −1.119*** −0.907*** 0.312*** −0.170*** Yes 795 159 0.4171 0.0473

0.628*** −0.208*** −0.454*** −0.276*** −0.250*** Yes 794 159 0.2637 0.1556

−0.411*** −1.339*** −0.685*** 1.888*** −0.102*** Yes 795 159 0.1998 0.0439

Other forms of land supply △LAND_OTHERSt △LAND_OTHERSt-1 △LAND _OTHERSt-2 △LAND_OTHERSt-3 △LAND_OTHERSt-4 Other control variables Observations Number of city AR2 Sargan

Note: Standard errors in parentheses; ***p < 0.01, **p < 0.05, *p < 0.1; in the GMM instrumented estimations, △LAND_RESt, △LAND_INDt, △LAND_PUBt and △LAND_OTHERSt are treated as potentially endogenous.

The significant relationship between land use change and economic growth is rooted in China's land ownership and land use right systems. Land owned by the government can be used as a powerful macroeconomic intervention tool. The long-term leasing of land use rights creates incentives for local governments to supply land to generate lump sum revenues, which are then used to finance better social security and infrastructure provisions. Land has indirectly played a critical role in sustaining and driving China's rapid economic growth (Lin, 2009), especially in Eastern China. However, the local governments of central and western cities primarily focus on the provision of industrial development zones and industrial parks, bringing about an enormous waste of resources since many of these projects have low occupancy rates. This paper has several policy implications related to land regulation and economic growth. First, the central government needs to temper local authorities' impetus to sell land, as this form of land-centred urbanization and industrialization has already spurred serious social tensions, environmental degradation and economic fluctuations (Lin, 2009). Lump-sum revenues generated through land leases are not sustainable given that Chinese cities will eventually face land supply limits. The significant land-growth nexus is conditioned on the current institutional framework. Second, the local government should pay more attention to the optimization of land use structure. As China's growth model changes and industrial structures are upgraded, the role of the land supply in economic growth may be reduced as well, with greater focus on its allocation to different functions (land uses). However, the results in Kim and Hewings (2013) for the US show that land use controls can limit the ability of population and employment adjustments to achieve equilibrium. Land use allocation also plays an important role in the environmental quality of Chinese cities, a subject not addressed in this analysis. In many cases, the negative externalities generated by some industrial developments have created significant problems that must be assessed against the positive gains in

cities does not. Taken together, these results suggest that land management is more efficient when tailored to reflect regional differences. This finding contradicts the current policy, which imposes universal strict quota control. A shift to centralized regulation and to inter-provincial “quota” trading nationwide will no doubt facilitate efficient and intensive land use. From the perspective of land structure adjustments by local governments, different types of land have different effects on the urban economy. The supply of residential land triggers economic growth in the initial years after land is made available for use, while the effects of other types of land become significant 2–3 years later. Larger and more developed cities generally utilize land more efficiently and thus successfully stimulate economic growth through land structure adjustments. These results provide additional evidence for the influence of decentralization reforms on economic growth in China. These reforms have fostered economic growth by incentivizing local officials to provide land for business development directly and for infrastructure that supports business development indirectly. China has followed a resource-intensive growth path for a long time, so land has played a critical role in sustaining the country's rapid economic growth. Land is an essential factor of production in the process of economic growth, and some officials act on the belief that land supply can spur additional investment. Following the fiscal reforms of the mid1990s, profits from land conversion have become important sources of local government revenue, resulting in the rapid conversion of farmland for urban uses, at least in areas experiencing significant economic growth. However, such rapid growth has brought about a number of problems, such as limits on food production (and implications for food security) and excess production in many industries. In response, the central government has attempted to impose more strict administrative control over land allocation measures by limiting the rate of farmland conversion and strengthening central government oversight on land transactions. 233

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employment. In addition, there are some interesting parallels (and differences) between the way urban governments fund their operations in China and the US, for example, generating outcomes that continue to challenge the efficient allocation of resources at different spatial scales.

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