The Drag Effect of Water Resources on China's Regional Economic

water

Article The Drag Eﬀect of Water Resources on China’s Regional Economic Growth: Analysis Based on the Temporal and Spatial Dimensions

Yao Zhang 1, Wenxin Liu 1 and Minjuan Zhao 1,*

College of Economics and Management, Northwest A&F University, Taicheng Road, Yangling 712100, China; [email protected] (Y.Z.); [email protected] (W.L.) * Correspondence: [email protected]

Received: 4 December 2019; Accepted: 16 January 2020; Published: 17 January 2020

Abstract: Studying the influencing factors of the drag effect of water resources and its temporal–spatial variation can help governments to solve the problem of water resource constraints on the economic growth of different regions. Based on Romer’s hypothesis, this paper uses panel data to empirically analyze the drag effect of water resources in China’s 31 provinces from 1987 to 2017. The research shows that: (1) Water resources have certain constraints on the economic growth of each region. Regional economic growth has declined by 0.23% (eastern), 0.07% (western), 0.43% (central) and 0.09% (northeastern) annually. (2) In provinces with rapid labor growth, water resources have a greater impact on economic growth. In provinces with low labor growth rates, the drag effect of water resources on economic growth is affected by the capital stock of the region. (3) Through the analysis of the water drag effect in different time periods, this paper finds that in some periods, the government’s mobilization of water resources for the economic growth in some regions will not only promote the transfer of labor between regions, but also cause changes in the regional water resources. According to the results of this paper, the following conclusions can be drawn: (1) It is necessary to vigorously develop water-saving agriculture, improve technical efficiency, and reduce the strong dependence of economic growth on water resources in the provinces which has a strong water drag effect on economic growth; (2) Provinces with moderate water resource constraints should take the lead in deploying strategic emerging industries, and accelerate the development of the tertiary industry; (3) Provinces with weakly water resource restrictions can promote the development of capital-based industries. Not only can the development of the economy be rational, but it can also reduce the economy’s dependence on resources, thereby achieving the sustainable use of water resources and sustainable economic growth.

Keywords: drag eﬀect; regional economic growth; virtual water; Solow Growth model

1. Introduction Water resources are an important material basis for human survival and a necessary strategic resource for social and economic growth [1]. In recent years, China’s economy has developed rapidly, with an average annual growth rate of nearly 10% [2]. In 2017, China’s total GDP exceeded 80 trillion yuan, accounting for 15% of the world economy. China’s economic growth miracle has been coupled with the increasing pressures of limited resources [3]. While China has a vast territory, its population accounts for 22% of the world’s total population. The per capita water resources are only 27% of the world’s per capita level, which is far below the world average [4]. The lack of water and the uneven distribution of water resources in time and space are China’s basic national conditions and water conditions. Water shortages, serious water pollution, and the deterioration of water ecology are

Water 2020, 12, 266; doi:10.3390/w12010266 www.mdpi.com/journal/water Water 2020, 12, 266 2 of 19 prominent issues and have become the main bottleneck restricting sustainable economic and social development [5]. There is a contradiction between limited water resources and economic growth. At the same time, the high consumption of water resources and the high dependence of economic growth on water resources have also affected stable economic growth [6]. Nowadays, the regional differences in economic growth in China are becoming more and more obvious, and the imbalance in regional development has become a realistic problem in the process of regional economic growth in China [7]. In this context, studying the drag effect of water resources on the economic growth of various regions in China in order to allow for a balance between the maximum economic growth and minimum water consumption is of great significance in connection with achieving the sustainable use of water resources, improving the quality of economic growth, and narrowing regional disparities. The “drag effect model” is used to analyze the impact of water resources on economic growth [8] The earliest research on the “drag effect” mainly involved introducing economic growth models or production functions to analyze the impact mechanism of resource constraints on the economy [9–11]. Dasgupta et al. [8,9] suggest that non-renewable resources will have a drag effect on economic growth and that economic growth can only achieve steady growth when non-renewable resources are not important for production. Nordhaus [10] uses the extended Cobb–Douglas production function to study the drag effect. This production function study found that the US economy is reduced by about 0.24% per year due to the constraints of various resources, such as land. Bruvoll et al. [11] found that the resources’ drag effect caused some losses to Norwegian social welfare. The constraints of resources and environment on economic growth are increasingly evident and hinder the promotion of sustainable economic growth and social welfare [10–12]. Over the past 30 years, the inputs of water resources have been the engine of China’s economic growth and have made important contributions to sustainable and rapid economic growth in the country’s metropolitan areas. Some scholars also analyzed and studied the drag effect of water resources on China’s economic growth based on the Romer’s [8] hypothesis and found that the constraints of water resources on China’s economic growth are widespread. Based on this study, this article poses the following questions: What is the extent of the drag effect of water resources on economic growth in China’s eastern, western, central, and northeastern regions? What is the difference between the provinces in each region? How did the drag effect of water resources on the economic growth in different regions change from 1987 to 2017? Does the change in the drag effect in different periods have a certain relationship with the implementation of policies in this period? By combing the relevant literature, it was found that the existing research on the drag effect of water resources on economic growth has three main aspects. Firstly, due to the different perspectives and focus of the indicators, the existing research on the measurement of the drag effect of water resources results shows different results [6,13–16]. Water resources include agricultural water (water from agricultural products), consumption water (water for household use), industry water (water for industry use), and ecological water (water for ecological use). Among them, agricultural water accounts for 65% of the total water, but the current statistical methods for agricultural water use are too rough. Virtual water can accurately measure and express agricultural water use, which has been recognized by most scholars [17,18]. Based on this, this paper uses the crop virtual water [19], consumption water, industry water, and ecological water consumption to assess the amount of water resources in order to more accurately evaluate the drag effect of water resources on economic growth. Secondly, the existing research on the drag effect of water resources on China’s economic growth is divided into the national level [6,20,21] and, to some extent, the regional level [16]. Does the uneven distribution of water resources in different regions of China lead to different economic growth speeds in different regions? If so, what is the difference between the impacts of water resources on the economic growth in different regions? What is the reason? Answers to these questions will provide useful guidance for economic growth in different regions. Thirdly, the existing research focuses on the drag effect of water resources on China’s economic growth mainly during a certain period of time [2,6,20], and research on the dynamic drag effect of different time periods is lacking. Economic growth and the Water 2019, 11, x FOR PEER REVIEW 3 of 20 Water 2020, 12, 266 3 of 19 [2,6,20], and research on the dynamic drag effect of different time periods is lacking. Economic growth and the utilization of water resources constitute a dynamic process. The measurement of the utilizationdrag effect ofat watera specific resources time is constitute not conducive a dynamic to exploring process. the The long-term measurement dynamic of the development drag effect atlaw a specificof the drag time effect. is not Therefore, conducive toin exploringorder to accurately the long-term evaluate dynamic the changes development in the law drag of effect the drag of water effect. Therefore,resources in in different order to accuratelyperiods of evaluateeconomic the growth changes in different in the drag regions, effect ofthis water paper resources will use inpanel different data periodsto measure of economic the degree growth of the in constraints different regions, and change this paper trends will of useChina’s panel water data toresources measure in the different degree ofperiods the constraints from 1987 and to 2017. change trends of China’s water resources in different periods from 1987 to 2017. The objectiveobjective of of this this paper paper is to is use to theuse panel the datapanel to analyzedata to theanalyze spatial the and spatial temporal and dimensions temporal ofdimensions the drag e offfect the of drag water effect resources of water on resources China’s economic on China’s growth economic based growth on the “Growthbased on Drag”the “Growth model ofDrag” Romer model [8]. Theof Romer true extent [8]. The of China’s true extent regional of Ch economicina’s regional growth economic and its changing growth trends and its will changing also be studied.trends will The also research be studied. results will The answer research relevant result questionss will answer associated relevant with questions China’s regional associated economic with growthChina’s underregional the economic constraints growth of water under resources the constr on theaints empirical of water level resources and provide on the empirical empirical evidence level forand governments provide empirical at all levels evidence to formulate for governments relevant policies. at all levels We believe to formulate that the relevant research inpolicies. this paper We willbelieve provide that athe valuable research reference in this for paper the studywill pr ofovide water a resources valuable in reference other countries, for the andstudy it is of of water great significanceresources in for other the promotioncountries, ofand the it stable is of and great sustainable significance development for the promotion of the world’s of the economy, stable withand minimumsustainable water development resources of constraints. the world’s economy, with minimum water resources constraints. The paperpaper isis organizedorganized asas follows. follows. SectionSection2 2introduces introduces the the two two models models used used in in the the study. study. Section Section3 introduces3 introduces the the division division of of the the study study area, area, the the selection selection and and calculation calculation ofof variables,variables, andand thethe stabilitystability and robustnessrobustness ofof the the data. data. Section Section4 uses 4 uses the the model model to analyze to analyze the dragthe drag e ffect effect of water of water resources, resources, from bothfrom timebothand time space and perspectives.space perspectives. Section Section5 discusses 5 discusses the main the findings main findings relating torelating the drag to etheffect drag of watereffect resourcesof water resources on economic on economic growth in growth China’s in four China’s major four sub-districts, major sub-districts, then summarizes then summarizes them and drawsthem and some draws conclusions. some conclusions.

2. Theoretical Framework Factors drivingdriving economic economic growth growth include include capital, capita labor,l, labor, technology, technology, and natural and resources natural (Figureresources1). Natural(Figure 1). resources Natural referresources to the refer materials to the thatmaterials human that beings human can beings directly can obtain directly from obtain nature from and nature use forand production use for production and living. and They living. mainly They include mainly land include resources, land resources, water resources, water resources, climate resources, climate biologicalresources, resources,biological resources, mineral resources mineral resources and energy and [ 22energy]. Natural [22]. Natural resources resources are the are material the material basis ofbasis economic of economic development development [6]. The [6]. unsustainableThe unsustainabl usee ofuse natural of natural resources resources is closely is closely related related to the to principlesthe principles or principles or principles followed followed in the in the course course of human of human economic economic activities activities [7]. [7]. The The speciﬁc specific way way of combiningof combining human human and and natural natural resources resources fundamentally fundamentally determines determines the the speciﬁc specific pathpath ofof socialsocial andand economic development.development.

Economic growth

Capital Resources

Labor Technology

Figure 1.1. Factors of economic growth.

2.1. Economic Growth Theory Ignores the Contribution of Natural ResourcesResources InIn economiceconomic growth theory, economiceconomic growthgrowth isis generallygenerally considered to be justjust aa functionfunction ofof capital, technology,technology, employment, employment, etc. etc. Resources Resources are are often often be replaced be replaced by each by othereach orother by “otheror by factors“other offactors production”. of production”. Adam Smith Adam [23 Sm] believesith [23] thatbelieves the core that role the in core wealth role growth in wealth is the growth improvement is the ofimprovement “labor productivity”, of “labor productivity”, which is mainly which achieved is mainly through: achieved the through: improvement the improvement of human skillsof human and tools,skills theand accumulation tools, the accumulation of capital, andof capital, the system. and the Ricardo system. [24 ]Ricardo believes [24] that believes a reasonable that a distribution reasonable Water 2020, 12, 266 4 of 19 system and incentives can increase people’s enthusiasm for production, and then promote economic growth. Marshall [25] emphasized the role of capital accumulation, investment, and entrepreneurial management activities in promoting economic growth. Keynes [26] analyzed the reasons for economic growth from a macro perspective, and he believes that by stimulating eﬀective consumer demand and investment demand, economic growth can be promoted. Solow [27] developed a neo-classical economic growth model, arguing that long-term economic growth comes from technological progress. From classical economics to neoclassical economics, from neoclassical economic growth theory to endogenous growth theory, it can be seen that resources are not considered as the determinants of economic growth, and can always be replaced. The theory of economic growth translates the “resource problem” into a simple “production cost problem”, and regards natural resources as “independent production factors” extracted from nature. For economic development, the reduction in the amount of resources is only a matter of increasing costs. The fact is that resources are used as factors of production to promote economic growth. Water resources, as basic natural resources and strategic economic resources, are the irreplaceable and indispensable core elements of productivity of human economic and social development [6,7].

2.2. Sustainable Economic Growth Must Consider Natural Resource Constraints When the amount of resources is decreasing, people have begun to realize that resources will be the limiting factors of economic growth and development, seeing the limits of growth and development, and also causing theoretical debates about the limits of growth [28]. Due to changes in quantity, the overall characteristics of natural resources in the ecosystem will also change accordingly, which will affect the structure and function of the natural resource system in which they are located. Due to the mutual restraint relationship, the natural environment system in which the economic system is located has changed and become fragile, which further shakes the foundation of the entire economic growth [29]. Therefore, starting from the resources themselves, economic growth is limited by natural resources. The new growth theory proposes that for any country or region, it is inevitable to consume resources in the process of economic growth [8]. Due to the limitation of resources, the economic growth rate will be lowered to a certain extent than the growth rate without resource constraints. This reduction is called “drag effect” of resources on economic growth [8]. With the rapid economic development and increasing population, the supply and demand relationship of water resources is mostly unstable [5]. Water resources are limited, and the contradiction between supply and demand is growing due to the increasing demand of economic growth [6]. In addition, the problem of water pollution is becoming more and more serious, resulting in a serious shortage of water resources, which has become a bottleneck restricting social and economic development [20]. However, economic growth also provides conditions for investment in water development and utilization and governance, which is related to the pattern of water resources development, utilization and management [17]. In view of this, this paper considers the interaction between water resources and the socio-economic composite system in a coordinated manner, and studies the drag effect of water resources on economic growth and its changing trends deeply. So as to provide theoretical basis for the development and utilization of water resources and socio-economic development.

3. Model and Data

3.1. Improved Solow Growth Model The classic model for measuring economic growth is the Solow Growth Model [8]. It has four main variables, namely, the output (Y), capital (K), labor (L) and “knowledge or labor validity” (A). The production function expression is as follows:

Y(t) = F[K(t),A(t)L(t)] (1) Water 2020, 12, 266 5 of 19

This paper analyzes the drag eﬀect of water resources on China’s economic growth, following Romer’s [8] Cobb–Douglas production function. Equation (1) becomes:

α β 1 α β Yt = K(t) W(t) [A(t)L(t)] − − , (α > 0, β > 0, α + β < 1) (2) where the dependent variable Y is the economic output, and the independent variables are K(t), W(t) and A(t)L(t), which indicate the ﬁxed capital stock, water resources and labor force. α is the elasticity of the capital production, β is the elasticity of the water resources [8]. Taking the natural logarithm of both sides of Equation (2), the following can be obtained:

ln Yt = α ln K(t) + β ln W(t) + (1 α β)[ln A(t) + ln L(t)] (3) − − Hence, the growth rate can be represented by Equation (4), after taking time as a derivative on both sides of Equation (3), as follows [30,31]: h i g (t) = αg (t) + βg (t) + (1 α β) g (t) + g (t) (4) Y K W − − A L where gY(t), gK(t), gW(t), gA(t), and gL(t) represent the growth rates of Y, K, W, A, and L, respectively. Assuming that labor, knowledge, water resources, and land all increase at a constant rate, the capital and output needed to balance the growth path increase at a constant rate [8]. The Equation for . the motion of capital is K(t) = sY(t) δK(t), from which the growth rate of capital is: − . K(t)/K(t) = s[Y(t)/K(t)] δ (5) − In order to keep the growth rate of K constant, Y/K must be constant; that is, the growth rates of Y and K must be equal. In addition, there is a balanced growth path, which is gY(t) = gK(t) [8]. The growth rate of Y on the path of balanced economic growth under constraints can then be obtained [22,23]: h i sgbgp = βg (t) + (1 α β)(g + n) /(1 α) (6) Y W − − − bgp where g Y represents the growth rate of Y on the balanced growth path, n represents the labor growth rate, and g represents the knowledge growth rate. From this, the average output growth rate of the unit labor force on the balanced growth path can be derived as:

gbgp = gbgp gbgp nh Y/L Y − i L o = βg (t) + (1 α β)(g + n) /(1 α) n (7) h W − − i − − = (1 α β)g + βg (t) βn /(1 α) − − W − − The drag eﬀect of water resources equals the value of water resources that are unconstrained, subtracting the value of the water resources that are constrained [30,31]. When water resources are unconstrained in economic growth and increase with the growth of labor, the growth rate of water resources is equal to the growth rate of labor (growth rate is n) [30,31]. When water resources are constrained, the growth rate of water resources is 0 [30,31]. Based on this:

bgp bgp Drag = eg Y/L g Y/L water − = [(1 α β)g + βn βn]/(1 α) [(1 α β)g + β 0 βn]/(1 α) (8) − − − − − − − ∗ − − Drag = βn/(1 α) water − 3.2. Virtual Water Model At present, the internationally authoritative software for virtual water measurement is CROPWAT, as recommended by the UN Food and Agriculture Organization [17,18]. Therefore, this paper also uses CROPWAT software to calculate the virtual water content of China’s agricultural products. Water 2020, 12, 266 6 of 19

The CROPWAT software is a computer program, established by FAO for irrigation planning and management. The CROPWAT software is developed based on the revised Penman formula, which calculates the water demand of a reference crop based on the climate and soil parameters of each region [32]. For the benchmark, the Penman formula is used to correct the values based on diﬀerent crop coeﬃcients. The meteorological data, which are required by the CROPWAT software, are derived from FAO’s CLIMATAT database. The unit virtual water content of each crop can be calculated as follows: SWD = CWR/CY (9) where SWD is the virtual water content per unit weight of the crop (m3/kg); CWR is the water requirement per unit area of the crop (m3/hm2); and CY is the yield per unit area of the crop (kg/hm2). Additionally, the data of CY are obtained from the China Statistical Yearbook (1987–2017). The crop water requirement (CWR) can be obtained by calculating the amount of soil evaporation (ETc) accumulated during the whole growth period of the crop [32]:

Xnd Xnd CWR = 10 ET = 10 Kc ET (10) × C × 0 i=1 i=1 where ETc is the soil evaporation; ET0 is the daily potential evaporation (mm/d) during the crop growth period; Kc is the corresponding crop coeﬃcient; and nd is the total number of days in the crop growth period. Using the meteorological data for each site in the CLIMWAT database to select the soil type of the study area, the value of ETc can be directly obtained using the CROPWAT software, and then the virtual water content per unit weight of the crop can be obtained using Equation (9). The Equation for calculating the total amount of crop virtual water is shown in Equation (11):

TVW = SWD TCY (11) × where TVW is the total amount of virtual water (t) of a crop; and TCY is the total yield (kg) of the crop in that year.

3.3. Study Area and Data Sources In order to scientifically reflect the social and economic development of different regions of China, according to the criteria of the National Bureau of Statistics, China’s economic region is divided into the eastern region (Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Guangdong, Shandong, and Hainan), western region (Neimenggu, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Xizang, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang), central region (Shanxi, Anhui, Jiangxi, Henan, Hubei, and Hunan) and the northeast region (Liaoning, Jilin, and Heilongjiang). Hong Kong, Macao and Taiwan are not within the scope of this study. The main variables in this paper are the output (Y), water resources (W), labor force (L), and fixed capital stock (K). The selection criteria are listed in Table1. Water 2020, 12, 266 7 of 19

Table 1. Variable Selection.

Variable Variable Interpretation References and Data Sources The economic output is expressed in terms of the gross Output domestic product (GDP), and the GDP is adjusted at a [6,30,31,33–35] constant price based on the figures from 1978. The labor force is represented by the data on social Labor force [20,30,31,33–35] workers at the end of the year in each region. The water resources are represented by the sum of the virtual agricultural water (water from agricultural products), consumption water (water for household use), Water resources industry water (water for industry use), and ecological [20,34,35] water (water for ecological use), where virtual agricultural water is the sum of the calculated virtual water of crops and the virtual water of animal products. The fixed capital stock refers to the total amount of fixed capital in the economic society at a certain point in time. The fixed capital was calculated using a depreciation rate Fixed capital stock [30,31,33–35] of 0.06 with the perpetual inventory method, and the fixed capital stock is adjusted at a constant price based on the figures from 1978.

The measurement results concerning the virtual water content of major agricultural product units (SWD) in various provinces of China are shown in Tables2 and3 (the blank in the table indicates that the crop is not grown in the area). Water 2020, 12, 266 8 of 19

Table 2. Virtual water content of major agricultural product units in various provinces of China (unit: m3/kg).

Sugar Tobacco Cities Paddy Wheat Corn Beans Potato Cotton Oil Hemp Beet Tea Apple Citrus Pear Grape Banana Cane Leaf China 1.29 1.26 0.80 1.94 1.20 4.69 1.59 3.32 0.19 0.32 2.13 12.43 0.61 0.66 0.91 0.53 0.53 Beijing 1.25 0.95 0.73 2.22 0.88 5.34 2.25 5.07 4.83 0.84 0.67 0.60 Tianjin 1.05 0.74 0.75 2.29 0.65 3.18 1.14 5.46 0.49 0.54 0.20 Hebei 1.11 0.67 0.77 2.05 1.20 5.27 1.07 2.50 0.10 1.77 0.40 0.27 0.27 Shanxi 1.28 1.07 0.85 5.76 2.41 4.09 3.10 6.84 0.09 1.61 31.34 0.29 0.39 0.23 Neimenggu 1.76 1.21 0.64 2.65 1.61 3.67 1.77 1.80 0.11 1.11 0.84 0.57 0.40 Liaoning 1.10 1.11 0.75 1.98 0.34 4.38 1.73 4.60 0.11 4.27 0.47 0.65 0.25 Jilin 0.98 0.95 0.53 2.19 0.59 2.96 1.19 4.37 0.11 1.24 0.76 0.83 0.44 Heilongjiang 1.50 1.21 0.69 2.29 1.02 1.85 0.97 0.13 1.63 0.45 0.56 0.27 Shanghai 1.06 1.19 0.68 1.38 0.98 2.13 1.66 5.32 0.18 0.13 0.45 0.34 Jiangsu 0.97 0.89 0.71 1.09 0.73 4.98 1.11 2.05 0.15 0.33 1.81 18.34 0.42 0.53 0.38 0.28 Zhejiang 1.12 1.16 0.84 1.06 0.87 3.56 1.48 1.50 0.12 1.47 7.58 0.32 0.40 0.18 Anhui 1.26 0.88 0.79 2.59 2.16 6.03 1.23 1.86 0.26 0.12 1.51 12.12 0.30 0.98 0.28 0.22 Fujian 1.40 1.82 0.97 1.15 0.91 7.68 1.30 2.10 0.17 1.83 4.26 0.29 0.67 0.25 0.28 Jiangxi 1.64 2.86 1.11 1.78 1.08 4.72 2.30 4.38 0.24 1.96 11.85 0.68 1.40 0.58 Shandong 0.95 0.75 0.64 1.31 0.61 4.70 0.81 3.04 0.19 1.49 6.77 0.21 0.25 0.17 Henan 1.38 0.90 0.94 2.37 1.78 6.90 1.17 1.07 0.17 2.09 17.00 0.34 2.41 0.45 0.32 Hubei 1.16 1.39 1.00 1.47 1.72 7.10 1.71 2.58 0.27 0.95 2.16 6.65 0.96 0.41 0.56 0.26 Hunan 1.27 1.34 0.81 1.27 1.10 5.32 2.16 2.70 0.20 1.78 5.06 0.55 1.70 0.73 Guangdong 1.23 1.49 0.82 1.12 0.86 1.02 2.23 0.12 1.43 4.71 0.49 0.43 1.00 0.30 Guangxi 1.57 3.00 0.95 2.00 1.78 5.77 1.40 2.30 0.14 2.36 8.57 0.56 0.57 0.37 0.39 Hainan 2.37 1.12 1.50 1.33 1.44 1.05 0.21 7.93 14.70 1.10 0.38 Chongqing 0.97 1.31 0.71 1.35 1.06 8.22 1.67 3.31 0.20 1.83 5.84 0.98 0.52 0.59 0.39 0.39 Sichuan 0.73 0.90 0.56 1.01 0.87 3.81 1.11 2.32 0.17 0.63 1.34 5.81 0.32 0.38 0.42 0.30 0.34 Guizhou 1.24 1.18 0.84 2.11 1.28 4.67 1.72 2.95 0.15 1.25 1.93 12.51 1.40 1.05 1.05 0.57 1.70 Yunnan 1.05 1.43 0.58 0.99 1.16 3.23 1.32 3.71 0.16 0.29 1.31 8.56 0.82 0.71 0.70 0.15 0.47 Xizang 1.99 0.98 0.94 0.92 0.81 1.34 0.68 0.50 Shaanxi 1.17 1.05 0.98 1.75 1.95 2.05 1.90 4.47 0.36 0.57 2.25 11.49 0.43 0.39 0.35 0.36 Gansu 1.56 1.18 0.80 2.11 0.60 3.88 1.71 3.92 0.09 1.39 43.04 0.57 0.38 0.64 0.45 Qinghai 1.44 0.72 1.43 1.41 1.97 7.19 0.21 1.00 1.30 9.37 4.82 Ningxia 0.88 1.71 0.64 5.58 2.43 2.00 5.62 0.29 1.18 0.54 0.55 0.98 Xinjiang 1.79 0.99 0.81 1.33 0.99 3.70 1.72 2.29 0.10 3.09 0.44 0.45 0.34

Table 3. Animal product quality virtual water content (unit: m3/kg).

Pork Beef Lamb Milk Egg Aquatic Products Virtual water 2.522 12.596 5.948 5.982 6.165 5.000 Water 2020, 12, 266 9 of 19

4. Results and Analysis

4.1. Data Stationarity and Cointegration Test This paper uses a panel data model to analyze the drag effect of water resources in the four major economic zones (East, Central, West, and Northeast China) based on data from 1987 to 2017 for 31 provinces (municipalities and autonomous regions). The stability and co-integration of the data will have an impact on the analysis of the drag effect of economic growth [3,8,20,21]. At the same time, due to the two-dimensional nature of the panel data, the stability of the data directly determines the credibility of the results, so a panel data model is adopted. Before the regression analysis, the data should be tested for stationarity and co-integration. The most common method is the unit root test [8,20,21]. In this paper, two-unit root test methods are used, the same-root LLC (Levin–Lin–Chu) test and different-root Fisher-ADF test. If the hypothesis of the existence of a unit root is rejected in both tests, the data is considered to be stationary. If the hypothesis of the existence of a unit root is accepted, the data is considered to be unstable. Based on formula 3, the logarithms of GDP, Water, Labor, and Capital are calculated—ln Y(t), ln W(t), ln L(t), and ln K(t), respectively. The unit root tests were performed using STATA software. By testing the first-order difference values of ln Y(t), ln W(t), ln L(t), and ln K(t), it is found that there are no unit roots at the significance level of 1%, indicating that these four variables are all first-order single integer I (1) (Table A1). Co-integration refers to the sequence of a linear combination of two or more non-stationary variables; that is, the sequence of these variables has a long-term equilibrium co-integration relationship [8,20,21]. The unit root test results show that the variables are the same order and single, so the co-integration test can be performed. Through the data stability and co-integration tests, it is found that ln Y(t), ln W(t), ln L(t), and ln K(t) are an unstable sequence (Table A2). However, there is at least one co-integration relationship between them, indicating that there is a long-term stable equilibrium relationship between the variables, and the regression residuals of the equations are stable. Therefore, further regression analysis can be done.

4.2. Analysis of the Spatial Dimension of the Drag Effect of Water Resources According Equation (8), Drag = βn/(1 α) . α is the elasticity coefficient of the capital, β water − is the elasticity coefficient of the water resources, n is the labor growth rate. Based on the results of Variable coefficient panel model in Table4, we can get the second column (Water) is equal to β, the third column (Capital) is equal to α, and the seventh column (N-Labor) is equal to n. Therefore, we can get the growth drag of water resources, and the results is in the ninth column (D-Water). Under water resource constraints, China’s overall economic growth rate dropped by 0.15%. The average annual growth rate of the eastern, western, central and northeastern regions declined by 0.23%, 0.07%, 0.43%, and 0.09% (Table4). That is to say, the economic growth of the central region is more affected by water resources, followed by the east, west and northeast. It can be seen that the drag effect of water resources on the central region, which is affected by rapid economic growth (a GDP growth rate of 10.61%), cannot be ignored. Water resources constrain the economic growth of the central region at a rate of 0.43% per year. If this rate continues, the economic growth rate in the central region will be reduced to 91.34% in 2040. From the perspective of regional characteristics, Henan Province in the central region is a large grain province, and Hunan Province is a land of rice. The economic growth of these provinces is highly dependent on water resources, so there is a large water drag effect on the economic growth of the central region. The eastern region is a coastal city with a developed aquaculture industry and a high degree of dependence on water resources. Therefore, the economic growth of the region is also constrained by there being less available water. The economic growth of the western and northeastern regions is less constrained by water resources, which is mainly related to the development direction of the region. The economic growth in the northeast region mainly relies on the development of energy, such as oil and coal. The labor force growth rate in the Water 2020, 12, 266 10 of 19 western region is small (1.22%), and the capital stock accumulation rate is relatively fast (13.06%). The economic growth is mainly related to the accumulation of capital stock and has little dependence on water resources. Therefore, the water resources efficiency of the economic growth in the western region is lower than that in other parts of the country.

Table 4. Variable coeﬃcient panel model and “Drag” measurement results for China’s 31 provinces.

Cities and Regions Water Capital Labor N-GDP N-Capital N-Labor N-Water D-Water Entire Country 0.06 0.42 0.07 11.11 13.11 1.54 3.06 0.1478 Beijing 0.02 0.19 0.11 10.03 11.22 2.58 1.38 0.0596 Tianjin 0.10 0.63 0.01 11.72 12.92 2.21 3.78 0.6198 Hebei 0.12 0.44 0.41 10.77 13.28 1.48 4.65 0.3269 Shanghai 0.01 0.50 0.01 10.18 10.91 1.86 0.25 0.0420 − Jiangsu 0.07 0.95 0.14 12.04 14.74 1.10 2.00 1.4693 − Zhejiang 0.06 0.90 0.12 12.28 13.90 0.86 1.42 0.5024 Fujian 0.25 0.29 0.35 12.34 14.10 2.77 2.84 0.9762 Shandong 0.19 0.67 0.17 11.65 13.22 1.92 3.78 1.1040 Guangdong 0.03 0.76 0.73 13.35 14.54 2.63 1.65 0.3364 − − Hainan 0.03 0.52 0.07 10.99 12.83 2.47 6.63 0.1603 Eastern Region 0.05 0.61 0.06 11.80 13.47 1.83 2.69 0.2316 Neimenggu 0.07 0.52 0.07 11.98 16.72 1.58 6.56 0.2249 − Guangxi 0.07 0.30 0.35 10.68 13.74 1.24 2.37 0.1201 Chongqing 0.01 0.58 0.68 11.68 14.09 0.43 4.70 0.0128 Sichuan 0.03 0.49 0.60 10.53 10.73 0.69 1.40 0.0350 − − Guizhou 0.01 0.29 0.22 10.15 11.80 1.15 2.82 0.0092 − − − Yunnan 0.02 0.21 0.40 10.13 14.09 1.82 4.30 0.0450 Xizang 0.05 0.37 0.10 11.29 13.27 3.16 3.52 0.2650 Shaanxi 0.05 0.55 0.39 11.04 12.63 1.20 3.22 0.1270 Gansu 0.04 0.25 0.06 10.00 11.61 1.06 3.04 0.0622 Qinghai 0.02 0.31 0.01 9.60 13.13 1.76 1.99 0.0586 − − Ningxia 0.06 0.24 0.05 9.81 12.54 2.29 6.79 0.1772 − Xinjiang 0.01 0.20 0.09 9.71 13.26 2.78 5.48 0.0506 Western Region 0.04 0.34 0.05 10.72 13.06 1.22 3.45 0.0741 Shanxi 0.12 0.29 0.05 9.78 10.82 1.50 3.40 0.2430 − Anhui 0.18 0.52 0.29 10.93 11.87 1.80 2.12 0.6814 Jiangxi 0.06 0.36 0.10 10.49 13.11 1.64 2.45 0.1490 − Henan 0.11 0.31 0.25 10.73 14.32 1.98 3.72 0.3202 − Hubei 0.21 0.50 0.08 10.87 13.58 1.44 2.32 0.5960 − Hunan 0.02 0.45 0.45 10.34 11.86 0.95 2.00 0.0385 Central Region 0.17 0.37 0.13 10.61 12.98 1.60 2.62 0.4341 − Liaoning 0.01 0.52 0.26 9.13 11.52 0.59 4.84 0.0075 − − Jilin 0.03 0.44 0.02 10.02 13.70 1.30 3.47 0.0587 − Heilongjiang 0.05 0.35 0.18 8.98 9.99 1.59 5.08 0.1251 Northeast Region 0.04 0.46 0.15 9.28 11.65 1.11 4.64 0.0863 “Water” is the elasticity coefficient of water resources; “Capital” is the elasticity coefficient of capital; “Labor” is the elasticity coefficient of labor; “N-GDP” is the growth rate of GDP; “N-Capital” is the growth rate of capital; “N-Labor” is the growth rate of labor; “N-Water” is the growth rate of water resources; and “D-Water” is the “Growth Drag” of water resources. N-GDP; N-Capital; N-Labor; N-Water; D-Water; unit: %. The same abbreviation definitions apply to the table below.

There is a large regional imbalance in China’s water resources, and there are also serious regional imbalances in economic growth [36]. Therefore, there are also differences in resource constraints to economic growth in different regions. In order to more fully reveal the impact of water resources in different regions of China on the economic growth of the region, this paper conducts regression analysis on 31 provinces and cities, based on panel data from 1987 to 2017 (Table4). At the same time, according to the size of D-Water and N-GDP, 31 provinces and cities are divided into weak, medium and strong, which constitute three “Growth Drag” constraint levels (Figure2), and low, medium and high, which constitute three economic growth types (Figure3). Water 2019, 11, x FOR PEER REVIEW 12 of 20 Water 2019, 11, x FOR PEER REVIEW 12 of 20 different regions of China on the economic growth of the region, this paper conducts regression analysisdifferent on regions 31 provinces of China and on cities, the basedeconomic on panel growth da taof from the 1987region, to 2017this (Tablepaper conducts4). At the sameregression time, accordinganalysis on to 31 the provinces size of D-Water and cities, and based N-GDP, on panel 31 provinces data from and 1987 cities to 2017 are divided (Table 4). into At weak, the same medium time, andaccording strong, to which the size constitute of D-Water three and “Growth N-GDP, Drag” 31 provinces constraint and levels cities (Figure are divided 2), and into low, weak, medium medium and and strong, which constitute three “Growth Drag” constraint levels (Figure 2), and low, medium and Waterhigh,2020 which, 12, 266 constitute three economic growth types (Figure 3). 11 of 19 high, which constitute three economic growth types (Figure 3).

Figure 2. Water resources drag effect level for China’s 31 provinces. FigureFigure 2.2. WaterWater resourcesresources drag effect eﬀect level for for China’s China’s 31 31 provinces. provinces.

FigureFigure 3.3. EconomicEconomic growth mode fo forr China’s China’s 31 31 provinces. provinces. Figure 3. Economic growth mode for China’s 31 provinces. The drag eﬀect of water resources in Beijing, Gansu and other provinces are weakly constrained.

There are two main reasons for why water resources are less constrained by the economic growth of these provinces: the economic growth rate of provinces, such as Beijing, Shanghai, and Chongqing, ranks in the top 10 in the country, the labor growth rate is medium-speed, and the accumulation of capital stock is fast, indicating that it is local. The greater degree of economic growth is related to the accumulation of capital, so water resources are relatively less restrictive to these areas. In the central and western regions of Hunan and Gansu, the economic growth rate is slow, and the labor growth Water 2020, 12, 266 12 of 19 rate is lower than the national average. The current situation of sparsely populated land has largely alleviated the pressure of water resources on economic growth. The water resources of Hebei, Shaanxi, Henan and other provinces have moderate constraints on the economy. The reasons are mainly divided into two categories: In Tibet, Guangxi, Henan and other large and medium-sized land areas, the capital stock growth rate is higher than 13.5%, and the labor growth rate is higher than 1.20%. The high-speed accumulated capital and increasing labor force have led to an increasing demand for water resources in these areas, which has led to a moderate constraint on water resources growth. Hainan and Hebei have developed coastal cities with a medium-speed growth. The growth rate of the labor force is remarkable, and the increasing demand for water resources by the labor force is also increasing. Therefore, the water resources in these areas have a moderate constraint on economic growth. Water resources are strongly constrained in economically developed areas, such as Tianjin and Jiangsu, mainly because the region attracts a large amount of high-quality labor, resulting in an increase in the labor growth rate. At the same time, the demand for water resources in aquaculture and high-speed industries is increasing, so water resources have created strong constraints on the fast-growing economy of the region. There are two main reasons for the strong constraints on the economic growth of Anhui and Hubei. On the one hand, the fast-growing agriculture in these two provinces is heavily dependent on water resources. At the same time, these areas have a large area, but the available water resources are limited. Therefore, the per capita water resources are low, which leads to the drag eﬀect of water resources on economic growth being higher than that in other provinces. On the other hand, the elasticity coeﬃcient of water resources in these areas is greater than that in most provinces, that is, the contribution of water resources to economic growth is very high. In the case of low water resources, a high dependence on water resources has a strong constraint on economic growth.

4.3. Analysis of the Temporal Dimensions of the Drag Eﬀect of Water Resources Economic growth is a dynamic process, and the impact of water resources on economic growth is also a dynamic process. In order to further study the impact degree and dynamic change process of water resources in regional economic growth, this paper uses the time variation method of the panel data to examine the changes of the drag eﬀect of water resources on China’s eastern, western, central andWater northeastern 2019, 11, x FOR regions PEER REVIEW from1987–2017 (Figure4, Table A3). 14 of 20

Figure 4. Tendency of the drag eﬀect of water resources in diﬀerent regions of China. Figure 4. Tendency of the drag effect of water resources in different regions of China.

4.3.1. Analysis of the Drag Effect in the Eastern Region of China From 1991 to 1999, the economic growth rate and the accumulation rate of fixed capital in the eastern region were the fastest in the past 30 years (averages of 16.81% and 15.04%, respectively). A large influx of labor and rapid capital accumulation caused the demand for resources to increase rapidly. The drag effect of water resources on economic growth became greater. During the period of 1999–2003, the strategy of developing the western region introduced water resources from the central and western regions into the eastern region, which alleviated the restrictions on water resource growth in the eastern region to some extent. Between 1987 and 2017, the economic growth in the eastern region consistently ranked first in the country. The water-end effect of economic growth in the region presents the dynamic characteristics of “obstruction–promotion–obstruction– promotion–obstruction” and gradually approaches a zero value, indicating that the dependence of economic growth on water resources in the eastern region is gradually decreasing. The slowdown in regional agricultural development is mainly related to the transformation of the economy by means of technological progress and capital accumulation. It shows that the economy of the eastern region is gradually entering a stage of sustainable development.

4.3.2. Analysis of the Drag Effect in the Western Region of China Between 1987 and 2017, the trend of water resources in the western region on economic growth was “obstruction–promotion–obstruction–promotion–obstruction”. Since 2000, China has implemented the strategy of developing the western region. This policy has also accelerated the economic growth of the western region. At the same time, it has also attracted some labor backflow. The return of labor to drive production and living in the western region has increased the demand for water resources, further leading to water shortages. The water resources drag effect became larger. To achieve sustainable development in the western region, it is necessary to optimize the industrial structure, improve technical efficiency, promote the development of green agriculture, reduce the dependence of economic development on water resources, and gradually achieve sustainable economic development.

Water 2020, 12, 266 13 of 19

4.3.1. Analysis of the Drag Effect in the Eastern Region of China From 1991 to 1999, the economic growth rate and the accumulation rate of fixed capital in the eastern region were the fastest in the past 30 years (averages of 16.81% and 15.04%, respectively). A large influx of labor and rapid capital accumulation caused the demand for resources to increase rapidly. The drag effect of water resources on economic growth became greater. During the period of 1999–2003, the strategy of developing the western region introduced water resources from the central and western regions into the eastern region, which alleviated the restrictions on water resource growth in the eastern region to some extent. Between 1987 and 2017, the economic growth in the eastern region consistently ranked first in the country. The water-end effect of economic growth in the region presents the dynamic characteristics of “obstruction–promotion–obstruction–promotion–obstruction” and gradually approaches a zero value, indicating that the dependence of economic growth on water resources in the eastern region is gradually decreasing. The slowdown in regional agricultural development is mainly related to the transformation of the economy by means of technological progress and capital accumulation. It shows that the economy of the eastern region is gradually entering a stage of sustainable development.

4.3.2. Analysis of the Drag Effect in the Western Region of China Between 1987 and 2017, the trend of water resources in the western region on economic growth was “obstruction–promotion–obstruction–promotion–obstruction”. Since 2000, China has implemented the strategy of developing the western region. This policy has also accelerated the economic growth of the western region. At the same time, it has also attracted some labor backflow. The return of labor to drive production and living in the western region has increased the demand for water resources, further leading to water shortages. The water resources drag effect became larger. To achieve sustainable development in the western region, it is necessary to optimize the industrial structure, improve technical efficiency, promote the development of green agriculture, reduce the dependence of economic development on water resources, and gradually achieve sustainable economic development.

4.3.3. Analysis of the Drag Effect in the Central Region of China Between 1987 and 2017, the drag effect of water resources in the central region was second only to that of the eastern region. The main reasons are as follows: First, the labor growth rate in the central region has been declining year-by-year, and the situation of labor loss in the eastern region is more serious. The demand for water resources is reduced. Second, the growth rate of capital stock is “growth-decrease-growth-decrease”, which is basically consistent with the law of economic growth, indicating that economic growth in the central region is mainly related to the accumulation of capital. Third, the growth rate of water consumption in the central region of each period is greater than that of other regions, that is, its economic growth relies heavily on water resources. Fourth, water resources have always imposed constraints on economic growth in the central region and particularly in Henan and Hunan. The agricultural development of Shanxi and other provinces is mainly dependent on water resources. Therefore, water resources have a continuous drag effect on the economic growth of the central region. In response to this problem, the central region should promote water-saving irrigation technology, improve the efficiency of agricultural technology, and reduce the constraints of water resources on economic growth.

4.3.4. Analysis of the Drag Effect in the Northeast Region of China Between 1987 and 2017, the drag effect of water resources in Northeast China gradually increased. The main reasons are as follows: First, it is related to the industrial layout of the Northeast. From 1987 to 2007, the exploitation of oil fields and coal mines in the three provinces constituted the main economic growth initiatives. Since 2010, the state has gradually controlled the development of small coal mines in the northeast region, banned some small coal mines, transformed the industry in the northeast Water 2020, 12, 266 14 of 19 region, and rapidly developed ice and snow tourism. Therefore, the drag effect of water resources on economic growth in Northeast China during 2012–2017 declined. Second, after 2000, the labor force increased year-by-year, and capital stock was rapidly accumulated. The demand for water resources for living production in Northeast China has been increasing, making the consumption rate of water resources significantly higher than that in other regions, further leading to water resource constraints in the northeast region. The dependence is much higher than that in other regions.

5. Conclusions and Discussions

5.1. Conclusions According to Romer’s [8] hypothesis, it is inevitable to consume resources in the process of economic growth. Due to the limitation of resources, the economic growth rate will be lowered to a certain extent than the growth rate without resource constraints. Therefore, this paper uses panel data to calculate both the time and space dimensions of the drag effect of water resources on China’s economic growth. By measuring the drag effect of water resources on different regions, we can compare and analyze the dependence of the economic growth of different regions on water resources. By analyzing the trends of the drag effect of water resources in different regions from 1987 to 2017, corresponding policy recommendations can be proposed for different regions. This paper aims to answer questions relating to China’s economic growth under water resource constraints and provide empirical evidence for governments at all levels to formulate relevant policies, with a view to promoting the stable, sustainable development of the Chinese economy and achieving minimum water resource constraints. This paper studies the drag effect of water resources on the economic growth of China’s eastern, western, central and northeastern regions. Find and answer the questions from the beginning of the article. (1) Water resources have certain constraints on the economic growth of each region. And regional economic growth has declined by 0.23% (eastern), 0.07% (western), 0.43% (central), and 0.09% (northeastern) annually. (2) In provinces with rapid labor growth, water resources have a greater impact on economic growth (for example, in Fujian, Tianjin, etc.). In provinces with low labor growth rates, the drag effect of water resources on economic growth is affected by the capital stock of the region. In provinces with fast capital stock growth (for example, in Zhejiang and Guangxi), the water resources have a great drag effect on economic growth. In provinces with low capital stock growth (for example, in Sichuan, Guizhou, etc.), the water resources have a low drag effect on economic growth. (3) Through the analysis of the water drag effect of different time periods, this paper finds that the drag effect of water resources in different regions has changed a lot in different periods. The change in the drag effect in different periods have a certain relationship with the implementation of policies in this period. In some periods, the government’s mobilization of water resources for economic growth in some regions will not only promote the transfer of labor between regions, but also cause changes in the regional water resources.

5.2. Discussions According to the results provided in this paper, only under the conditions of good government supervision, a reasonable allocation of existing water resources, the simultaneous strengthening of physical and human capital inputs for growth, and other aspects can the water resources have a good role in promoting economic growth. Therefore, in order to achieve the coordinated development of water resources and economic growth, future macro policies should focus on: (1) For the provinces with strongly water resources constraints (such as Jiangsu and Shandong, etc.), as the population of these provinces continues to grow, and the size of cities continues to expand, water resources will constraint economic growth more and more. It is necessary to vigorously develop water-saving agriculture, improve technical eﬃciency, and reduce the strong dependence of economic growth on water resources. To further utilize internal and external resources to ease water resource constraints by adjusting the market. Water 2020, 12, 266 15 of 19

(2) Provinces with moderate water resources constraints (such as Hebei, Shaanxi, etc.) have relatively low economic growth rates, but the rate of water consumption is far above the national average. These provinces should take the lead in deploying strategic emerging industries, and accelerate the development of the tertiary industry to reduce water consumption. So as to achieve the goal of reducing the drag effect of water resources on economic growth. (3) Provinces with weakly water resources constraints (such as Guangdong, Qinghai, etc.) are mostly located in coastal water-rich areas. The labor growth rate in these provinces is low, but the capital stock is growing faster, so these provinces can promote the development of capital-based industries. Not only can the development of the economy be rational, but it can also reduce the economy’s dependence on water resources, thereby achieving the sustainable use of water resources and sustainable economic growth. In this paper, the evaluation of the “growth drag effect” of regional water resources is only a preliminary study, and there are some problems that must be considered in further research: (1) Water resources are the premise and foundation of economic growth. The difference in water resource endowment determines the direction of regional economic growth and its development speed. At the same time, regional economic growth is a dynamic process. The drag effect of water resources in different regions varies greatly with time, and the water elasticity coefficient, capital elasticity coefficient and labor growth rate affect the drag effect of water resources. The changes in different regions, as well as the influence of multiple factors, such as the statistics and caliber, have been greater in different periods, so the research in this paper has certain difficulties, and the solution to these problems needs to be continuously improved in further research. (2) This paper only calculates the drag effect of water resources on the overall economy, but water resources are not only the lifeblood of agricultural production, but also an indispensable resource in industrial production. The drag effect of water resources on the development of industry and agriculture has not yet been answered.

Author Contributions: Data curation, Y.Z.; funding acquisition, M.Z.; methodology, W.L.; resources, Y.Z.; writing—review and editing, Y.Z. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Soft Science Project of the State Forestry and Grassland Administration (2019131039): Evaluation and optimization of grassland ecological restoration management system incorporated into the full value. Acknowledgments: We would like to thank MDPI to edit this paper. We also appreciate the constructive suggestions and comments on the manuscript from the reviewer(s) and editor(s). Conﬂicts of Interest: The authors declare no conﬂict of interest. Water 2020, 12, 266 16 of 19

Appendix A

Table A1. Unit root test results.

LLC Test Fisher-ADF Test Regions Inverse Inverse Inverse Modiﬁed inv. Adjusted t chi-squared normal logit t chi-squared LnY(t) 2.3614 *** 58.1872 *** 4.5777 *** 4.8404 *** 6.0379 *** − − − Eastern LnL(t) 6.8928 *** 55.2886 *** 4.1441 *** 4.4513 *** 5.5796 *** − − − Region LnW(t) 16.4979 *** 55.5169 *** 4.5330 *** 4.6324 *** 5.6157 *** − − − LnK(t) 2.1354 ** 62.8900 *** 5.0898 *** 5.3508 *** 6.7815 *** − − − LnY(t) 3.7450 *** 70.1643 *** 4.8760 *** 5.0960 *** 6.6632 *** − − − Western LnL(t) 9.2896 *** 53.9717 *** 3.9194 *** 3.8922 *** 4.3260 *** − − − Region LnW(t) 15.3768 *** 62.7292 *** 4.7308 *** 4.7477 *** 5.5901 *** − − − LnK(t) 2.3007 ** 60.9894 *** 4.5402 *** 4.5705 *** 5.339 *** − − − LnY(t) 1.4489 ** 32.8865 *** 3.4768 *** 3.5722 *** 4.2634 *** − − − Central LnL(t) 6.6827 *** 29.9360 *** 2.6454 *** 2.7659 *** 3.6612 *** − − − Region LnW(t) 16.8324 *** 33.5124 *** 3.3366 *** 3.5270 *** 4.3912 *** − − − LnK(t) 2.1286 ** 32.0596 *** 3.4153 *** 3.4867 *** 4.0946 *** − − − LnY(t) 5.1730 *** 14.3247 ** 2.0435 ** 2.1126 ** 2.4031 *** − − − Northeast LnL(t) 2.6477 *** 15.1747 ** 2.2596 ** 2.3185 ** 2.6485 *** − − − Region LnW(t) 5.9413 *** 14.5111 ** 2.3115 ** 2.2761 ** 2.4570 *** − − − LnK(t) 2.1952 ** 20.2018 *** 2.6094 *** 3.0787 *** 4.0997 *** − − − LnY(t) 5.1558 *** 154.1801 *** 6.9654 *** 7.0112 *** 8.278 *** − − − Entire LnL(t) 13.8978 *** 145.2444 *** 6.3203 *** 6.2978 *** 7.4756 *** − − − Country LnW(t) 23.9241 *** 152.1200 *** 7.0760 *** 7.0231 *** 8.0930 *** − − − LnK(t) 2.8927 *** 162.3613 *** 7.4548 *** 7.5328 *** 9.0127 *** − − − ***, ** and *, respectively, represent that the signiﬁcant is under the level of 1, 5 and 10%. The same below. Water 2020, 12, 266 17 of 19

Table A2. Co integration test results. − Kao Test Pedroni Test Regions Modiﬁed Dickey-Fuller Dickey-Fuller Augmented Dickey-Fuller Modiﬁed Phillips-Perron Phillips-Perron Augmented Dickey-Fuller Eastern Region 4.5345 *** 5.3641 *** 6.5600 *** 0.9164 1.9340 ** 3.1989 *** − − − − − Western Region 7.2003 *** 5.7966 *** 5.2559 *** 0.1312 5.9060 *** 4.4322 *** − − − − − Central Region 4.8577 *** 4.0680 *** 5.7364 *** 1.9139 ** 0.3784 1.5683 ** − − − − − Northeast Region 2.1379 *** 2.8561 *** 4.3306 *** 0.7748 1.2143 2.5258 ** − − − − − Entire Country 8.5806 *** 8.8069 *** 10.9698 *** 0.9116 5.4188 *** 6.0502 *** − − − − −

Table A3. Drag eﬀect of water resources and policies of water project.

Drag and Water Projects 1987–1991 1991–1995 1995–1999 1999–2003 2003–2007 2007–2011 2011–2014 2014–2017 Eastern 1.7095 0.0726 0.0846 0.0575 0.4065 0.0244 0.1210 0.0890 − − Western 0.4622 0.0347 0.0200 0.0881 0.0179 0.0051 0.1112 0.0049 D-Water − − − − Central 0.0809 1.2132 0.2783 0.2247 0.1537 0.0501 0.6112 0.0299 − Northeast 0.1849 0.2862 0.0070 0.0034 0.0168 0.0156 0.2909 0.2376 − − − − − Project 1 Water Diversion Project from Luanhe River to Tianji City (Run since 1983) Project 2 Water Diversion Project from Luanhe River to Tangshan City (Run since 1984) Policies of Project 3 Water Diversion Project from Yellow River to Qingdao City (Run since 1986) Water Project Project 4 Water Diversion Project from Datong River to Qinwangchuan (Run since 1994) Project 5 East Line Project of South-to-North Water Diversion (Run since 2012) Project 6 Central Line Project of South-to-North Water Diversion (Run since 2014) Water 2020, 12, 266 18 of 19

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