The effect of land use planning (2006–2020) on construction land growth in China

Cities 68 (2017) 37–47

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The effect of land use planning (2006–2020) on construction land growth in China

MARK

Yan Zhoua, Xianjin Huanga,b,⁎, Yi Chena, Taiyang Zhonga,⁎⁎, Guoliang Xuc, Jinliao Hea, Yuting Xud, Hao Menga a

School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China The Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry of Land and Resources, Nanjing 210023, China c School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330013, China d School of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241000, China b

A R T I C L E I N F O

A B S T R A C T

Keywords: Land use planning Implementation effect Cities Construction land growth China

Land use planning is a comprehensive instrument for managing non-agricultural land growth in China, and the evaluation of its implementation effect on growth control is of great significance for policy improvement. However, little empirical research has been done to estimate its implementation effect at the city level of the whole country. This study aims to evaluate the effectiveness of land use planning on construction land growth control at the city level in China. Taking 288 cities as the research object, an econometrics model was built to estimate the effect based on socioeconomic and land use data from 2006 to 2012. The results show that the implementation of land use planning has a certain effect in curbing the expansion of construction land, and that the incremental amount of construction land decreases by 107,449 ha due to the planning implementation. In addition, the implementation effect of land use planning presented significant differences among cities, which shows that there is a weaker effect in megacities and large cities than in medium-small cities. Besides, the implementation effect of land use planning also shows temporal differences: its effect is better in 2007–2009 than in 2010–2012. Furthermore, considering both planned goals and effectiveness, planning implementation is judged to be able to slow but not fully prevent the rapid expansion of construction land. Finally, to further improve efficiency and success, this research puts forward some suggestions such as improving the existing quota system, delineation of the urban development boundary and integrating the special plan system.

1. Introduction Conversion of natural and agricultural land to non-agricultural use has become the major feature of land-use change in most urbanized areas of the world, especially in developing countries (Liu, Wang, & Long, 2008; Angel, Parent, Civco, Blei, & Potere, 2011; Lambin & Meyfroidt, 2011; Liu, et al., 2014; Zhong, Huang, Ye, & Scott, 2014). With its unprecedented economic development since 1978, China's urbanization level increased to 52.57% in 2012 from only 17.92% in 1978, which made China one of the fastest urbanizing countries (CSSB[a], 2013). The quick boost of urbanization caused a high rate and massive scale of construction land expansion, and the area of built districts increased by 7.73% annually from 13,148 km2 to 35,633 km2 during the 1990–2012 period (CSSB[b], 1991, 2013). It is estimated that China's urbanization level will reach 70% in 2035 (CSSB[c], 2008), which will further

⁎

promote the expansion of urban land. The rapid increase of nonagricultural land and quickly shrinking natural ecological space have led to serious socio-economic and environmental consequences (Foley et al., 2005), such as ecological environment deterioration, land erosion, arable land loss, traffic congestion, and housing shortages (Sarzynski, Wolman, Galster, & Hanson, 2006; Zhao et al., 2006; Kim & Pauleit, 2007; Schetke, Haase, & Kötter, 2012;), which are threats to regional sustainable development. To mitigate these negative effects and promote regional sustainable development, many countries have applied policy tools such as land use planning (Smith & Giraud, 2006; Halleux, Marcinczak, & van der Krabben, 2012), master plan (Sharifi, Chiba, Okamoto, Yokoyama, & Murayama, 2014), green belts (Keil &Macdonald, 2016), urban growth boundaries (Dempsey & Plantinga, 2013; Tannier & Thomas, 2013), zoning (Bourgoin, Castella, Pullar, Lestrelin, & Bouahom, 2012), market regulation (Brueckner, 1990), and

Corresponding author at: School of Geography and Oceanography Sciences, Nanjing University, Xianlin Avenue No. 163, Nanjing, Jiangsu, China. Corresponding author. E-mail addresses: [email protected] (Y. Zhou), [email protected] (X. Huang), [email protected] (Y. Chen), [email protected] (T. Zhong), [email protected] (G. Xu), [email protected] (J. He), [email protected] (Y. Xu), [email protected] (H. Meng). ⁎⁎

http://dx.doi.org/10.1016/j.cities.2017.04.014 Received 7 October 2016; Received in revised form 14 March 2017; Accepted 23 April 2017 0264-2751/ © 2017 Published by Elsevier Ltd.

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Fig. 1. Analysis framework for land use planning's effect on controlling construction land growth in China.

fiscal and taxation policies (James & Windsor, 1976; Anderson, 2005) to manage non-agricultural land growth (Fig. 1). As one of China's growth management policies, land use planning plays an important role in controlling the expansion of construction land by regulating land use from the outset. Land use planning is formulated to coordinate the scheduling, spatial distribution, and scale of land growth, aiming to guide sustainable, healthy, and orderly urban development. Since the State Land Administration was established in 1986, three land use plannings have been implemented to control construction land growth and protect arable land. The first planning was not effectively implemented (Cai, Zhang, Zhao, & Shi, 2009); therefore, the second planning was put forward to replace it in 1999. However, the second planning could not effectively curb the rapid increase of non-agricultural land and prevent the rapid loss of arable land (Zhong, Mitchell, & Huang, 2014). In 2006, the third land use planning (2006–2020) was implemented, and it further enforced the controlling of the total scale of construction land. With the third planning implemented, although it was designed to rigorously control construction land growth, the actual amount of newly-added construction land increased by 3.43 million ha from 2006 to 2012, which exceeded the planned goal of The Outline of National General Land Use Plan in China (2006–2020) in the same period (SCC, 2008). Therefore, it is vital to assess the implementation effect of land use planning in this midterm period. As a land use management tool, land use planning plays a comprehensive role in controlling construction land, and its effect has attracted scholars' attention. Till now, most research on the effect of land use planning has concentrated on housing and land markets (White & Allmendinger, 2003), housing supply and prices (Bramley, 1993; Monk, Pearce, & Whitehead, 1996), land fragmentation (Kim & Pauleit, 2007), exurbanization (Esparza & Carruthers, 2000), and so on. Only a few studies focus on the evaluation of land use planning's effectiveness on construction land growth management, while they always study a single city or several cities (Qian, 2013; Long, Han, Tu, & Shu, 2015). Therefore, it is necessary to provide general recognition of city implementation across a whole country, which can not only provide insight into the effect discrepancy among cities but also provide evidence for improving the effectiveness of planning and management. Thus, taking 288 cities as the research object and using econometric models, this study aims to assess the

implementation effect of land use planning in different cities. There are three crucial questions solved: (1) whether land use planning has an effect in curbing construction land growth; (2) if so, to what extent it can effectively control the expansion of construction land; and (3) whether differences in effect exist among cities, and what those differences are. 2. Theoretical framework China has established a top-down land use planning system. Currently, it is divided into five levels: nation, province, prefecture, county, and township. National planning is the guideline for other land use planning, and the lower-level government planning should conform to the upper-level government planning. The quota-based and zoning models are the core of China's current land use planning management system, and always work together to regulate land use and control farmland conversion (Cai et al., 2009). The quota system acts as a basic management method through which national land use planning determines the total quotas of land for a planned period (usually 15 years), mainly including the maximum amount quota of construction land, the minimum amount quota of cultivated land protection, and the quota of farmland permitted to be converted to newly-added construction land (Tan & Beckmann, 2010). All these quotas are allocated by central government to lower levels of government and then divided gradually down to the township. The land use planning is implemented through the annual land use plan, which regulates the annual quota of farmland conversion and non-agricultural land according to land use planning (Wang, Tao, Wang, & Su, 2010). In addition to the quota system, zoning is also used in land regulations. The national and provincial zoning determine the strategies and guidelines of land use zoning. The specific zonings, such as ordinary agriculture, settlement, and prime farmland protection, are regulated by municipal-county-town planning. The prime farmland protection zoning is exclusive and strictly restricts construction land in its coverage. Since municipal land use planning is on the scale of 1:100,000, land use zoning is difficult to implement directly. Land use zoning—especially the permanent basic farmland protection zoning—is further delineated and implemented by the county-town level land use planning, which determine the usages for each piece of land and rigorously restricted the conversion of farmland (Zeng, Shao, & Xie, 2016; Chen et al., 2017; Ma et al., 2017). Therefore, 38

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Wang & Scott, 2008). This illegal land use to some extent weakens the effect of land use planning on non-agricultural land control. To prevent the extensive expansion of construction land and protect farmland, a series of institutions, laws, and regulations have been implemented and issued by the central government (Zhang, 2000; Ding, 2003; Lin & Ho, 2005; Liu, Zhan, & Deng, 2005; Lichtenberg & Ding, 2008; Wang, Chen, Shao, Zhang, & Cao, 2012). China has implemented its strictest arable land protection system, and the prime farmland protection institution and the dynamic equilibrium of total arable land institution are the major ways to guarantee its implementation (Lichtenberg & Ding, 2008; Liu, Fang, & Li, 2014). A series of laws was also issued to secure arable land protection; for example, the National Protection of Prime Farmland regulations were issued in 1994, and the Land Management Law was revised in 1998 to further strengthen cultivated land protection and farmland conversion control. Since 2006, the central government issued the “1.8 billion mu” arable land preservation policy. The Outline of National General Land Use Plan in China (2006–2020) further proposed that arable land occupy no less than 1.82 billion mu by 2010 and 1.81 billion mu by 2020. This “1.8 billion mu” policy powerfully restricts the arable land conversion to non-agricultural land. In order to guarantee the goals of the implementation of land use planning, the central government supervises local land use, especially arable land protection through top-down evaluations of the local governors. In addition, new techniques such as remote sensing are also utilized to dynamically monitor land use, especially illegal conversion of arable land (Zhang & Zhang, 2007; Zhong, Huang, Ye, & Scott, 2014). In 2007, land supervision system was implemented to further strengthen the supervision of local government land use and management, which plays a positive role in suppression of illegal land use and restriction of construction land expansion (Tan, Zhang, & Rao, 2013). Other regulations have also been implemented, such as the “measures for annual land use plan”, “regulations on land markets” (Ding, 2007), and “economical and intensive land use” (Liu, Fang, & Li, 2014). All of above measures work together to ensure that the planning land quotas could not be easily exceeded and make the actual land use closely conform to the goals of land use planning. In short, in China, the expansion of construction land and agricultural land conversion not only influenced by land use planning, but also affected by institutions, laws, and regulations. They work together to regulate land use and non-agricultural land growth.

although municipal land use planning for construction land control is enacted through the “quota with zoning” mode, zoning is more a matter of form and it is more based on the land quota system. In China, the increase of no-agricultural land is largely achieved through conversion of agricultural land, especially cultivated land (Tan, 2005; Tan, Li, Xie, & Lu, 2005; Liu et al., 2014). The cultivated land accounts for approximately 60% of the construction land over the past two decades (Liu et al., 2014). The developed regions occupy a larger proportion, for example, in 145 major cities about 70% construction land was converted from cultivated land from 1990 to 2000 (Tan, 2005). The quota of farmland conversion is strictly restricted by land use planning and the annual land use plan. For agricultural land, especially cultivated land converted to non-agricultural use legally, both planning quota and annual plan quota of land conversion must be acquired (Wang, Tao, & Tong, 2009). On the basis of the Constitution of China, there are two kinds of land ownership: state ownership and collective ownership. Urban land is stated-owned, rural and suburban land is collectively owned. Currently, the major channels that agricultural land converted to construction land are the “agricultural land conversion and requisition” for urban use and “agricultural land conversion” for rural use. For the agricultural land used for construction, the first step is agricultural land conversion. After land conversion, then it varied by its ownership. For the urban land use, the way to proceed is land acquisition by the government so that the land ownership can be transformed from collective-owned to state-owned (Ding, 2007; Tan, Beckmann, van den Berg, & Qu, 2009); For rural construction land, it can be directly used. Agricultural land conversion must be approved by the government. However, this right belongs to the central and provincial governments; the former has the right to approve ordinary arable land expropriation of more than 35 ha and other land more than 70 ha; land areas below these values are approved by the provincial government. China's fast economic development and urbanization have created great demand for land supply (Deng, Huang, Rozelle, & Uchida, 2010; Ding & Lichtenberg, 2011). However, the quotas of land conversion and land supply are strictly restricted by the land use planning and annual land use plan. To meet the land demand for economic development and conform to the dynamic balance of arable land, the local governments implement some policies to acquire increased land conversion quotas. One is the policy of “increasing vs. decreasing balance of urban-rural built land” (Tan & Beckmann, 2010; Liu, Fang, & Li, 2014). Local governments can legally obtain increased farmland conversion under this policy; that is, the urban area gains extra conversion of farmland, while the rural area reclaims the same scale of farmland through rural construction land transformation in the same city. Besides, the central government assigns arable land preservation quotas to all local governments, but the ability to meet this quota varies among cities. Those faced by shortage of farmland available for future conversion and development can also occupy land through land development rights trade with cities that have plenty of arable land in the same province. This market mechanism includes compensatory arable land supplement by others (yidi buchong gengdi), compensatory preservation of basic cropland by others (jiben nongtian yidi daibao), and trading of rewarded land conversion quotas (tudi zhengli zhedi zhibiao) (Wang et al., 2009; Wang et al., 2010; Zhang, Wang, Li, & Ye, 2014; Chien, 2015). These methods of acquiring and exchanging land quotas are to some extent relaxing the rigid control of land for construction use. When these legal acquisition measures still cannot meet the demand of land for industrialization and urbanization, the local governments will break the quotas assigned by central government to seek land illegally (Deng, 2005; Chen, Wang, & Huang, 2015). Moreover, to pursue more land finance revenue, local governments also seek to supply more land beyond the quotas allocated, always by avoiding legal approval (Cao, Feng, & Tao, 2008; Lichtenberg & Ding, 2009). Illegal conversion of agricultural land occurs in the urban periphery, thereby evading the formalities of land expropriation approval (Tang & Chung, 2002;

3. Methodology and data 3.1. Data The research object of this study comprises two types of cities: municipal-level cities and municipalities directly under the Central Government. Because of the data limitations in Lhasa and Sansha, they are not included in this study; therefore, a total of 288 cities are used for analysis. According to the “Adjustment of Urban Scale Division Standard” stipulation issued by the State Council in 2014, cities are divided into five grades: super megacities (population ≥ 10 million), megacities (5 million < population < 10 million), large cities (1 million < population ≤ 5 million), medium cities (0.5 million < population ≤ 1 million) and small cities (population ≤ 0.5 million). As there are fewer cities with a population more than five million, these cities are defined as megacities in this study. Since the scale hierarchy of the 288 cities remained stable and little changed during the study period of 2006–2012, this paper analyzes them based on the urban scale hierarchy in 2012 (CSSB[b]). The economic and social data are mainly collected from the China City Statistical Year Book (2007–2013) (CSSB[b]). These data include population, average wages of staff and workers, GDP per capita, and investment in fixed assets. All economic data, such as GDP per capita and investment in fixed assets, are transformed as comparable prices. The data on land supply are collected from the China Land and Resources 39

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system, the conversion of arable land to non-agricultural use has been specially highlighted and strictly restricted through land use planning (Wang et al., 2010; Liang, et al., 2015). Therefore, this study selects the ratio between the planned arable land quota to be converted to construction use and the actual converted amount as an index to represent the effect of land use planning on construction land control. That is, when the allocation quota of arable land for conversion is smaller than the actual amount converted, land use planning control is stricter; otherwise, land use planning is relaxed. This study assumes that there is negative correlation between planned arable land conversion and the dependent variable. In other words, the stricter the conversion of arable land control, the lesser the growth of newly-increased construction land; otherwise, there is more growth. In addition to land use planning, other policy documents and regulations are enacted by the government to reinforce land growth control, which made the actual rigidity different every year. This indicates that the model has a time effect that is difficult to quantify. To solve this problem, we use the universal method of a dummy variable. For instance, the value of “1” is used for 2006 and “0” for other years; this setting is applied to other years in the same way (Zhong, Huang, Zhang, Scott, & Wang, 2012; Xu et al., 2015).

Table 1 Variable meaning and expected signs. Explanatory variable

Variable meaning

Expected signs

Y

Newly-added construction land during every year Constant Total population at year-end GDP per capita Investment in fixed assets Average wages of staff and workers Proportion of second and third sector

/

C pop pgdp inv aws idu pl lsp year2006–year2012 ε

Planned arable land quota converted to non − agricultural use Actual arable land converted to non − agricultural use

Land supply Dummy variable Residual error

+/− + + + + + − + +/−

Year Book (2007–2013) (MLR). The land use data are gathered from national land surveys from the Administrative Authority on Land and Resources (MLR, 2006-2012).

3.2. Variables

3.3. Methodology

Land use planning is an important tool for land use management; one of its tasks is to strictly restrict the expansion of construction land. Thus, this study uses newly-increased construction land as the dependent variable. Socioeconomic factors are the main driving forces affecting construction land growth (Serra, Pons, & Saurí, 2008; Eric F. Lambin & Meyfroidt, 2010). In China, in particular, the expansion of construction land is mainly driven by population growth and economic development (Deng, Huang, Rozelle, & Uchida, 2008; Liu et al., 2010; Liu, et al., 2014). An impressive body of literature has proven that China's fast-growing economy and urbanization mainly depend on land supply with low cost, which is usually used as an important tool to attract investment and stimulate economic growth (Ding, 2007). The literature also shows that urban expansion is prominently influenced by increase in per capita income, which usually promotes land growth (Tan, 2005; Ma & Xu, 2010). In addition, some scholars have proven that industrial restructuring can cause industry to transfer from central urban spaces to the outskirts and sub-developed areas of cities, and further affect urban land expansion (Li, Wei, Liao, & Huang, 2015). Considering data accessibility and continuity, this study selects population, GDP per capita, investment in fixed assets, industrial structure, and average wages of staff and workers as the independent variables. In China, construction land expansion is also affected by land institutions and land policies (Tian & Ma, 2009; Wang et al., 2012). Land supply, an important aspect of land institutions and policies, is largely influenced by land use planning and annual land use plan. Under China's current land system, land supply plays an important role in construction land growth (Tian & Ma, 2009; Chen et al., 2015). Therefore, this study selects the scale of newly-increased state-owned land supply for construction use as the independent variable to analyze the impact of policy factors on construction land expansion. China faces serious arable land protection challenges, and its arable land per capita is below the 50% world average. With fast economic development and urbanization, a large proportion of cultivated land was converted to non-agricultural land. From the 1980s through 2010, the construction land area increased 5.52 × 106 hm2, of which nearly 3.18 × 106 hm2 was produced from arable land conversion, which accounts for nearly 60% (Liu, et al., 2014). In the 145 major cities, this proportion occupies up to about 70% during 1990–2000 (Tan, 2005). Further, from 2006 to 2012, more than 51% of construction land was acquired through arable land conversion in the 288 cities. Cultivated land has become the main source for construction land, which further aggravates the scarcity of arable land. As a core indicator of the quota

3.3.1. Model This study aims to assess the implementation effect of land use planning on curbing non-agricultural land growth. Let Yit represent the newly-increased construction land variable at the city-level region i in period t; the study established the basic model as follows:

Yit = c + ∂plit + βXit + μit

(1)

where plit represents the indicators reflecting land use planning's effect on construction land growth control; Xit denotes the factors affecting the dependent variable, except plit; c is the constant; ∂ and β are the coefficients of the variables plit and Xit, respectively; and μit is the residual error. According to Table 1, considering both the dependent variable and its mainly influenced factors based on the above discussion, the specific model is as follows.

Yit = c + ∂plit + β1 popit + β2 pgdpit + β3 invit + β4 awsit + β5 iduit + β6 lspit + β 7y2006 + β8y2007 + β9 y2008 + β10 y2009 + β11y2010 + β12 y2011 + β13y2012 + εit (2) wherein β1, β2, β3, β4, β5, and β6 are the coefficients of variables pop, pgdp, inv., aws, idu, and lsp respectively, and β6 to β12 are the coefficients of y2006 to y2012 respectively. The meanings of the other variables are the same as in model (1). In the model, the variable inv. (investment in fixed assets) has a high correlate coefficient with the variables pdgp (GDP per capita) and lsp (land supply); the correlate coefficients are 0.53 and 0.68, respectively. Since a high correlate coefficient always results in multicollinearity, the investment in fixed assets was excluded to avoid this phenomenon. Further analysis with the regression model and the result indicates that the variable of aws (average wages of staff and workers) (t = −1.06, p = 0.29 > 0.05) and idu (proportion of second and third sector) (t = 0.03, p = 0.97 > 0.05) are not expressed significantly at the 1% level. Therefore, the variables aws and idu were removed to obtain a better statistical significance model. The final model is as follows.

Yit = c + ∂planit + β1popit + β2 pgdpit + β3lspit + β4 y2006 + β5y2007 + β6 y2008 + β 7y2009 + β8y2010 + β9 y2011 + β10 y2012 + εit (3) 40

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cities. During 2006–2012, the total amount of construction land increased by 4829 km2 annually and reached 33,806 km2, with a growth rate of 11.69%. The expansion of construction land happened in all different scales of cities. Among the cities, megacities have the most rapid land growth rate at over 15.00%, followed by large cities at the rate of 14.49%. By contrast, medium cities and small cities have relatively slower land growth rate at 10.26% and 10.11%, respectively, while the average rate for all cities is 11.69%. As a whole, the growth rate of construction land in megacities and large cities is faster than in the small-medium cities. Fig. 2 further presents details of the construction land growth for all scales of cities. The cities with large construction land expansion are mainly centralized in the Yangtze River Delta, Jing-Jin-Ji, and Chengdu-Chongqing megalopolises, especially in megacities such as Chongqing, Tianjin, Chengdu, Shanghai, Hangzhou, and Beijing, with the average increase of construction land exceeding 370 km2, while the average increase of all cities was 117 km2 during 2006–2012. The cities with smaller construction land expansion are mainly distributed in the northeast and northwest regions. From the perspective of land growth rate, the cities with a faster growth rate are mainly concentrated in China's southeast coastal region, such as Xiamen, Zhoushan, and Jiaxing, and southwest and northwest China, such as Kunming, Guiyang, Yinchuan, and Erdos, while the cities distributed in the northeast region and central area of China show relatively slow growth. The above analysis indicates that most eastern coastal developed cities in China still have strong demand for construction land, while in most western underdeveloped cities, economic development and urbanization rely more on land input and investment (Liu et al., 2010; Kuang, Liu, Dong, Chi, & Zhang, 2016).

Table 2 Urban land expansion hierarchy from 2006 to 2012. Cities scale

Change of construction land (km2)

Growth rate (%)

Megacities Large cities Medium cities Small cities All cities

3182 1,1053 9352 1,0219 3,3806

15.41 14.49 10.26 10.11 11.69

3.3.2. Methods for evaluating the implementation effect 3.3.2.1. The effectiveness of land use planning. This study aims to examine the effectiveness of land use planning at the city level. Its effectiveness can be judged by the estimated coefficient ∂, whose sign is expected to be negative in Table 1. If the estimated coefficient ∂ has the expected sign with significance at 1% level, it can be concluded that land use planning is effective in controlling construction land expansion. Otherwise, it can be described as not effective. 3.3.2.2. Absolute effect. Using the estimated model above, this study can obtain the coefficients of all variables. Then, the value of planning unimplemented can be calculated by defining ∂ as zero (Eq. (4)). Furthermore, this study calculated the deviation between the planning that has been implemented and not implemented, which is defined as “absolute effect.” This represents the differences among the 288 cities in the implementation of land use planning. t

Absolute effectit =

∑ yit − yicl̂ =0

(4)

i =1

wherein, yit represents the true value of newly-added construction land, yicl=0 indicates the assumption value of planning unimplemented, and t represents the year during 2007–2012.

4.2. The effectiveness of land use planning The panel data of 288 cities for 2006–2012 was analyzed using Stata13.0 to estimate the model. Three models—the fixed effects (FE) model, random effects (RE) model, and OLS model—were used to analyze the estimation difference. The F test shows the FE model and RE models are more suitable than the OLS model. Further analysis using the Hausman test shows the FE model (F = 42.24, p = 0.0000) is best

4. Results 4.1. The expansion of construction land during 2006–2012 Table 2 shows the construction land increase for different scales of

Fig. 2. Construction land growth in cities during 2006–2012.

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the non-agricultural land growth. In this study, the crucial question is whether the implementation of land use planning is effective in controlling the expansion of construction land. The coefficient of plit can be used to represent the effect. Table 3 shows that the sign of ∂ is negative and significant at the 1% level, indicating that the implementation of land use planning is effective in controlling the non-agricultural land growth. The value of ∂ suggests that the increment of construction land decreases 44.27 ha in each city annually on average when growth control is enhanced by 1%.

Table 3 Regression estimate results. Variable

C pop pgdp P lsp y 2007 y 2008 y 2009 y 2010 y 2011 y 2012

Fixed effect Coefficient

Std. Error

t-Statistic

Prob.

867.4522 1.6960 0.0083 -44.2697 0.1335 − 469.2607 − 553.4775 − 548.2154 320.8721 213.7055 − 88.9460

327.2760 0.7583 0.0024 7.6769 0.0493 81.8002 82.6878 85.4213 87.8368 95.7284 100.9451

2.65 2.24 3.39 − 5.77 2.70 − 5.74 − 6.69 − 6.42 3.65 2.23 − 0.88

0.0080 0.0250 0.0010 0.0000 0.0070 0.0000 0.0000 0.0000 0.0000 0.0260 0.3780

4.3. Temporal differences in implementation effect The results of Table 3 show that the signs of dummy variables are negative from 2007 to 2009 and in 2012, while the signs are positive in 2010–2011, and the absolute value of variables in 2007–2009 are higher than in 2010–2012. This indicates that temporal differences existed in the implementation effect of land use planning during study period; the implementation effect shows two phases: 2007–2009 versus 2010–2012. The results for absolute effect of land use planning calculated using Eq. (4) further confirm this conclusion. Construction land was effectively controlled, and the incremental amount decreases by 107,449 ha because of land use planning implementation from 2007 to 2012. Specially, the amounts are 79,486.59 ha for 2007–2009 and

for the analysis and refuse RE model. Therefore, this study adopts the result of the FE model for analysis (Table 3). The estimated results in Table 3 indicate that the coefficients of variables pop, pgdp, and lsp are positive and significant at the 0.05 level, and the signs are consistent with the expected signs in Table 1. This result suggests that economic development, the increasing urban population, and land supply have played a prominent role in promoting

Fig. 3. Absolute effects among cities of every scale.

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average approval of land for construction use in 2007-2009 40000

average approval of land for construction use in 2010-2012

35000 30000 25000

ha

20000 15000 10000 5000 Ningxia

Xinjiang

Gansu

Qinghai

Shanxi

Yunnan

Sichuan

Guizhou

Hainan

Chongqing

Guangxi

Guangdong

Hubei

Hunan

Henan

Jiangxi

Shandong

Anhui

Fujian

Jiangsu

Zhejiang

Shanghai

Jilin

Heilongjiang

Liaoning

Inner Mongolia

Hebei

Shanxi

Tianjin

Beijing

0

Fig. 4. The average approval of land for construction use in 2007–2009 and 2010–2012.

tion effects of most larger scale cities are weaker than that of medium cities and small cities.

33,535.29 ha for 2010–2012, accounting for 7.08% and 1.75% of the actual increased rate of construction land in the two stages respectively. The above analysis suggests that the implementation effect in the previous stage was better than in the last phases.

5. Discussion 5.1. Positive effect of land planning in controlling construction land growth

4.4. Absolute effect difference between cities According to the results of evaluation and the standards of effectiveness given in the previous section, the implementation of land use planning produced a positive effect; that is, the planning implementation did curb the increase of non-agricultural land in China. Some policies make the planning implementation effective. In China, land use planning is a top-down way and lower-level government planning should be in compliance with upper-level government planning. The non-agricultural land growth in local planning is strictly controlled by upper-level planning, and the amount of construction land is required not to exceed that of upper-level planning. In addition, some relevant policies, laws, and regulations, along with the planning implementation, are usually enacted by higher-level governments and specially implemented by the lower-level governments, which plays an important role in making planning implementation effective. Furthermore, in order to restrict the increase of illegal conversion of farmland to nonagricultural use and control the rapid expansion of construction land, the central government reinforced its supervision by using remote sensing technology to dynamically monitor land use change in 2000 and annually in the following years (Li et al., 2013; Zhong, Huang, Ye, & Scott, 2014). The land supervision system was established and implemented in 2007 to further strengthen the suppression of illegal land use and restrict the expansion of construction land (Tan et al., 2013). All these policies work together to make land use planning implementation more effective.

The distribution of absolute effects of planning implementation shows differences among cities. Cities with absolute effect between 200 ha and 400 ha represent the largest proportion at 50.35% of the 228 cities, followed by absolute effect below 200 ha and between 400 and 600 ha, which account for 24.31% and 10.77%, respectively; absolute effect between 600 and 1000 ha and more than 1000 ha represent only a very small proportion. From Fig. 3, the cities with absolute implementation effects more than 600 ha are mainly located in the northwest, northeast, and southwest regions of China. More specifically, the cities with higher values are primarily distributed in Shaanxi Gansu, Xinjiang, and Inner Mongolia in northwest China; Heilongjiang and Jilin in the northeast; and Guangdong in the south. The cities with absolute effect between 200 ha and 400 ha are widely distributed in every province. In contrast, cities with absolute effects less than 200 ha are mainly distributed in several urban agglomerations such as the Yangtze River Delta, the mid-southern Liaoning agglomeration, the Chengdu-Chongqing agglomeration, the Shandong peninsula agglomeration, and the Guanzhong agglomeration (Fig. 4). The proportion of absolute effect in newly-added construction land can reflect the performance of planning implementation. This result also exhibits the differences among different scales of cities. As shown in Table 4, the absolute effect of all megacities and 82.76% of large cities is less than 5% for newly-added construction land; among small cities, the proportion is 47.33%. Proportions greater than 5% are found in 52.67% of small cities and 25.27% of medium cities, but only 17.24% of larger cities and no megacities. This suggests that the planning implementation effects in medium and small cities have better performance, and in large cities and megacities have weaker performance. Based on the above analysis, we found that the planning implementa-

5.2. The absolute effect has periodic features The above analysis indicates that the effect of planning implementation shows an apparent phase difference, with the effect in 2007–2009 better than that in 2010–2012. The following reasons could contribute to this result. First, the change in land use control policy may affect the implementation of land use planning. Since the early 2000s, China has experienced a new stage of quick or even overheated economic growth. To curb this overheat, the central government undertook a series of measures including credits, taxes, and land supply for regulation. In 2003, the state council announced that the land policies would work with fiscal and monetary policies together in the macroregulation (Tian & Ma, 2009). Later, China tightened the land supply

Table 4 The detailed proportions of absolute effect in cities. City hierarchy

≤ 5%

5%–10%

10%–15%

≥ 15%

Total

Megacities Large cities Medium cities Small cities

100 82.76 74.73 47.33

0.00 12.07 12.09 25.19

0.00 3.45 5.49 9.92

0.00 1.72 7.69 17.56

100 100 100 100

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(SCC, 2008), the actual growth rate of newly-added construction land is 11.69%, which is higher than the expected rate of 7.65%. Among the 288 cities analyzed, 237 (82.29%) showed a higher growth rate than expected, while only 51 cities have a relatively lower growth rate than expected (Fig. 5). Therefore, the implementation of land use planning is judged to be able to slow but not prevent the rapid expansion of nonagricultural land when considering both effectiveness and goal achievement together. There are several reasons for this result. First, land use planning is hardly adapted to the elasticity of economic development. Land use planning is a management system from the top down to control land growth with rigid targets, while economic and social development is always unpredictable. This conflict creates a mismatch between the planned quotas allocated and the region's economy for the demand of land, and this phenomenon is especially prominent in regions with fast industrialization and urbanization, resulting in many cities using more land illegally by breaking though the quotas permitted by land use planning. Second, inconsistency of land management goals exists between the central and local governments. The central government needs to balance food supply safety and economic growth in addition to regional balance (Lichtenberg & Ding, 2008). However, for the local government, economic growth and land finance are the priorities, so they always emphasize land supply and even ignore the regulation to use land by breaking the land quotas assigned by the central government (Deng, 2005; Qian, 2013). Third, ambiguity among different spatial plans also makes things difficult in practice. There are four major spatial plan systems in China: land use planning, urban master planning, major function–oriented zoning, and environmental protection planning. These plans have their own systems and always vary in terms of the time, context, and goals, sometimes even conflicting with each other, and this makes the implementation of land use planning much more complicated and difficult in terms of effectively controlling the scale of urban land.

and implemented more rigorous land management, this directly influenced the land supply that the 2004 has decreased by 23.3% to 219,670 ha compared to 2003 and further reduced to 180,326 ha in 2005 (Tian & Ma, 2009). However, this situation changed when the 2008 global financial crisis broke out. In response to the financial crisis, the government started a financial investment of 4 trillion (RMB) to prevent economic recession (Yao, Luo, & Wang, 2014); accordingly, the land policy was adjusted from “tighten the land supply” to “guarantee economic development” to fit the new situation. Then, in 2010, the Ministry of Land and Resources put into practice the “Ensure Economic Growth and Warning Limit of Arable Land” policy to guarantee reasonable demand for development land. This discrepancy can be easily seen from the land supply scale, which averaged 937,807.39 ha during 2007–2009 and increased to 1,737,127.30 ha during 2010–2012. This variation in land policies greatly affected the land supply and resulted in a temporary difference in land use planning implementation. Second, the annual plan for approved conversion of cultivated land to construction land from Administrative Authority on Land and Resources could impact the planning implementation. For 2007–2009 and 2010–2012, the amount of arable land approved to be converted to non-agricultural use are 464,187.94 ha and 587,895.55 ha respectively (MLR, 2007–2013), an increase of 26.65% more than previously. This phenomenon can also be seen at the provincial level. Among the total 31 provinces, 77% show that the amount of approval of construction land conversion from arable land in 2010–2012 greater than that in 2007–2009 (MLR, 2007–2013). From this phenomenon, a conclusion can be drawn that strictly controlling land approval is an important means to improve land use planning implementation. 5.3. Different policies for controlling urban growth The implementation effect varied among different scales of cities; overall, the effect was relatively weaker in larger-scale cities than in their smaller counterparts. From the city development policy in China, both the policy and guideline of city development always emphasize “controlling the scale of larger cities,” which is usually achieved by means such as strict control of urban registered residences, urban land scale of urban planning, and industrial evacuation (Abramson, 2006; Chan, 2010), while supporting and encouraging the development of small-medium cities. However, the sharp expansion of metropolises and the shrinkage of small and medium cities, evidence that these policies have not achieved the expected effect and that the scale control policy in metropolises is unsuccessful (Wei, 2014). In addition, the administrative hierarchy can always affect the growth of urban land scale (Li et al., 2015; Wei, 2015). In China, influenced by administration-center bias, the government is usually partial to bigger cities with higher administrative levels of resource allocation, authority levels, and policy support (Deng, 2011; Wei, 2015). These priorities make the bigger cities superior for development, and they attract a greater concentration of population, economy, and industry. Take 2012, for example: although the large scale and above cities account for only 22.92% of the 288 cities, more than 65.00% of the population and 56.34% of the GDP is aggregated in them. With this concentration of population and economy, megacities and larger cities will expand further in the future, which in turn accelerates urban land expansion. Therefore, it is difficult to effectively control the construction land expansion in bigger cities through the implementation of land use planning.

6. Conclusions Currently, China is in the stage of fast industrialization and urbanization, and the urban areas are developing quickly along with the rapid expansion of construction land. Land use planning is an important mean to control non-agricultural land growth reasonably, and its effectiveness needs to be assessed. To evaluate the implementation effect of the third plan, this study takes 288 cities as research subjects and analyzes them using econometrics models. The results show that the implementation of land use planning can effectively control non-agricultural land growth, and that the incremental sum of construction land was reduced 107,449 ha owing to the planning implementation during the study period. In addition, the implementation effects present significant spatial differences among cities, which show that the effects in megacities and large cities are weaker than those in medium and small cities; meanwhile, the implementation effect also shows a temporal difference: the effect in 2007–2009 is better than that in 2010–2012. Finally, considering both planned goals and effectiveness, land use planning can be judged as being able to slow but not fully prevent the rapid expansion of construction land. Some reasons for this phenomenon are the conflict between the rigidity of land use planning and the elasticity of economic development, the conflict in the goals for land management between the central government and local governments, and non-coordination of the various spatial planning systems. To improve the effectiveness of planning compilation and implementation, some policy suggestions could be adopted in future. First, the existing quotas system in China should be improved. The allocation of construction land quota and control of the city scale should be based on socioeconomic development, resource and environment carrying capacity, and human–land linking rather than emphasis on population growth and economic development. For the developed cities in eastern coastal China, the quota of newly-increased construction land should be

5.4. Slow but not fully prevent the rapid expansion of construction land The estimated result suggests that the increment of construction land can be reduced by 44.27 ha in every city with growth control increased by 1%, indicating that land use planning can slow the expansion of construction land. Compared with the planned goal of The Outline of National General Land Use Plan in China (2006–2020) 44

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Fig. 5. Differences between actual and expected annual rate of construction land growth.

land growth is not only driven by social and economic development but also influenced by natural factors and geographical location (Deng et al., 2008; He, Okada, Zhang, Shi, & Li, 2008; Ye, Zhang, Liu, & Wu, 2013). However, limited by data continuity and availability, it is difficult to acquire detailed natural and geographical location variables for all 288 cities. This research can be improved by using more detailed variables if those become available in the future. Second, land use planning is generally compiled and implemented based on both land quotas and land use zoning. However, owing to the limited data availability, this study only evaluates the effect of quota control of planning implementation. Whether the actual spatial distribution of construction land is consistent with the space layout of land use planning is not under consideration; this should be taken into account, and remote sensing data with GIS methods should be used to comprehensively evaluate the effect of planning implementation on growth control in future studies.

reduced and more emphasis should be placed on activating urban stock land and promoting the efficiency of urban utilization; for the relatively economically lagging developing cities in the western and central regions, the quota of newly-added construction land should have a moderate increase in the future to support industrialization and urbanization. Second, China's urban growth management strategy should be strengthened through delineation of the urban development boundary. In a situation in which the rapid expansion and uncontrolled development of urban land use, delineate the urban development boundary based on urban land per capita and other factors such as basic arable land protection and ecological redlines. Then, guarantee more formal and strict execution through the legislation form, which can prevent urban land sprawl. Third, promote multiple plan integration. Currently, the land use regulations are complicated and not as effective as supposed. In order to enhance the implementation effects of land use planning, it is urgent to promote multiple plan integration, based on the spatial planning system of basic data, planning objectives, planning period, and other aspects of unity and coordination. In particular, land use planning, national economic and social development programs, urban master planning, and environmental protection planning to coordinate the spatial plan system and strengthen the implementation effect in the future (Long, Liu, Li, & Wan, 2014; Zhu, Deng, & Pan, 2015). Two aspects can be improved in future study. First, non-agricultural

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