Comparative Evaluation between Water Parallel Pricing System and Water Pricing System in China: A Simulation of Eliminating Irrigation Subsidy

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1 July, 2016 Journal of Resources and Ecology Vol. 7 No.4 J. Resour. Ecol ( DOI: /j.issn x Comparative Evaluation between Water Parallel Pricing System and Water Pricing System in China: A Simulation of Eliminating Irrigation Subsidy SHEN Ming 1,2, ZHONG Shuai 1,*, SHEN Lei 1, LIU Litao 1, ZHANG Chao 1,2 1 Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing , China; 2 University of Chinese Academy of Sciences, Beijing100101, China Abstract: The reform in water pricing plays a critical role in agricultural production, which is believed to have great water savings potential. We consider eliminating irrigation subsidies as a simulation and conduct a comparative evaluation between the water parallel pricing system (WPPS and the water pricing system (WPS, which are incorporated into two computable general equilibrium (CGE models, respectively. The results prove that, compared with WPPS, WPS would contribute higher capacities for water savings with more farming imports and less loss in farming output; households in rural and urban areas would benefit from more income and food consumption, which would be matched by increasing farming imports. A policy recommendation is that eliminating the irrigation subsidy should pay more concerns on alleviating the negative effects on farming outputs. Moreover, improvements in agricultural labor mobility and water demand elasticity are needed to enable more focus on the water conservation policy, particularly in WPS. Key words: water pricing reform in China; eliminating irrigation subsidy; factor mobility; computable general equilibrium model, farming production sectors 1 Introduction Water price in China is determined politically and by topdown administrative commands rather than by the market. Moreover, the fragmented institutional framework and overlapping functions of various agencies has generated a water parallel pricing system, in which the main division of water resources is between irrigation water and pipe water (Nitikin et al. 2012; Shen and Liu 2008; Xie 2009; Zhong et al. 2015a, 2015b. The water parallel pricing system leads to an inefficient water distribution between agricultural sectors and non-agricultural sectors because of a serious price distortion between irrigation water and pipe water (Dudu and Chumi There are three main differences between pipe water and irrigation water in the water parallel pricing system: (1 origination from different suppliers: the supply of pipe water is operated by the pipe water production sectors, and the supply of irrigation water is regulated by the local government; (2 delivery to different users: the pipe water is mainly consumed by non-agricultural sectors, and irrigation water is used in agricultural sectors; and (3 formulated by different pricing methods: the pricing of pipe water is volumetric (CNY m 3 and is based on the marginal opportunity cost (MOC, covering direct cost of resources, user or depletion cost and environment cost (Warford and Xie Irrigation water is collected by the area pricing method (CNY mu 1, 1 ha=15 mu, and the payment for it covers the operating cost; the fixed infrastructure cost acts as an irrigation subsidy supported by the local government, which is the main reason for the price distortion (Huang et al. Received: Accepted: Foundation: National Natural Science Foundation of China ( , and , the 57th China Postdoctoral Science Foundation (2015M *Corresponding author: ZHONG Shuai. Tel: ; zhongshuai@igsnrr.ac.cn. Citation: SHEN Ming, ZHONG Shuai, SHEN Lei, et al Comparative Evaluation between Water Parallel Pricing System and Water Pricing System in China: A Simulation of Eliminating Irrigation Subsidy. Journal of Resources and Ecology, 7(4:

2 238 Journal of Resources and Ecology Vol. 7 No. 4, ; Zhang and Li 2012; Zhong et al. 2015b, 2015c. In 1993, in Shenzhen, Guangdong province, China began to promote water pricing reform to construct a water pricing system in which the irrigation water and pipe water are volumetrically priced together according to the MOC (Nitikin et al. 2012; Shen and Liu 2008; Xie However, many regions have not implemented this reform due to the complicated socio-economic and environmental affairs of water use, such as unclear responsibilities, poor collection rates and institutional capacities (Zhong and Mol In the regions in which the integrated pricing reform has been implemented, the water price utilized by farmers for irrigation still contains irrigation subsidies (Huang et al. 2010; Zhang and Li By simulating a water pricing policy option in which the irrigation subsidy is eliminated, our goal is to indicate whether reforming the water pricing system has the potential to encourage more water conservation with less loss in the agricultural and rural economy compared with that of the water parallel pricing system. Moreover, we will determine which factor mobility limitation has a significant influence on the farming sectors and their water savings potential, considering that water pricing reform significantly depends on the degree of factor mobility (Wittwer The CGE (Computable General Equilibrium model simplifies the entire economic system in which the price mechanism plays an important role (Ge et al Therefore, a CGE analysis involving water issues assumes that water distribution would be regulated by a price mechanism within the process of achieving market equilibrium. Such a policy assessment needs to discuss the more complex structure of the factor mobility condition from the demand perspective. The nested constant elasticity of substitution (CES production functions usually employed to present non-linear relations between water and other inputs because water demand elasticities strongly influence model results (Qin et al. 2013; van Heerden et al. 2008; Zhan et al A more detailed discussion about the water parallel pricing system and the water pricing system as well as their setting within the CGE models can be found in Zhong (2014; Modeling framework and data Two CGE models are applied to follow the modeling strategy of one system one model : the CGE model with WPPS (CGE-WPPS and the CGE model with WPS (CGE-WPS. 2.1 Modeling improvement The WPPS and WPS are set in CGE-WPPS and CGE-WPS, respectively. In CGE-WPPS, the MOC level of irrigation water and pipe water are assumed to be equal. The irrigation water supply is regulated by the government (Shi et al The irrigation price is set under the MOC level using the irrigation subsidy rate. The supply of pipe water is operated by pipe water production sector; thus, the pipe water price is determined by the market process. In CGE-WPS, all water, called the integrated water, is supplied by the integrated water production sector; therefore, the integrated water price depends on the changes in market demand and supply. However, the actual price of water utilized by farmers still contains the irrigation subsidy. Consequently, the irrigation subsidy in this study is represented by the difference between irrigation water price and pipe water price, regarding an assumption that water quality is the same for both of irrigation water and pipe water. This assumption is acceptable because of two reasons: (1 we do not propose that irrigation water and pipe water should be priced at the same level, instead of that, we support that both of their prices should be determined by the volumetric pricing method according to MOC level, which is so called the water pricing system. The difference between the actual prices of irrigation water and pipe water is obviously significant due to the remarkable diversities in supply costs and demand factors, and thus estimation on the actual prices of them is beyond the scope of this study. The setting of irrigation subsidy is for convenient calculation to deal with the data limitation on the information about the water quality of sectoral irrigation water inputs. (2 As described by previous studies, eliminating irrigation subsidy would significantly raise the price of irrigation water input, and then the production costs of farming sectors would be increased. And so farming sectors would have to reduce their water inputs and cut down their output. Also, the prices of farming products would be higher, farming exports would be less and farming imports would be more. We use CGE-WPPS and CGE-WPS to simulate this process, and aims to investigate the relative changes of the farming indexes derived from WPPS and WPS, respectively, which are resulted by relative changes in the water prices. Water price variance itself because of water quality might insignificantly affect the values of simulation results, but the relative changes and their trends in different scenarios within WPPS and WPS would not be affected. This study focuses on farming sectors, including paddy, wheat, corn, vegetable, fruit, oil seed, sugarcane, potato, sorghum and other ps. Farming sectors employ irrigation land, non-irrigation land, irrigation water and pipe water (solely in CGE-WPPS, integrated water (solely in CGE-WPS, agricultural labor, non-agricultural labor and capital. Pipe water and integrated water, as the intermediate inputs, are defined in CGE-WPPS and CGE-WPS, respectively, through a CES production function. It should be noted that a very small quantity of pipe water is also consumed by farming sectors in CGE-WPPS. In this study, we introduce irrigation subsidy rate into the water demand function of farming sectors. The modifications of production functions basically place in water demand functions within the two CGE models, while other functions in production sectors are not changed and thus omitted. In CGE-WPPS, the relationship between irrigation water and pipe water is shown by equation (1-(3, and that be-

3 SHEN Ming, et al.: Comparative Evaluation between Water Parallel Pricing System and Water Pricing System in China: A Simulation of Eliminating 239 tween the compose water and irrigation land are by equation (4-(6, in the nested CES production function. WARP WARP WARP WAR awarp PWR WARP WARP (1 WARP (1 WARP PWR WARP (1 WARP P " WAP" WARP WARP 1 WARP WARP (1 WARP WAP awarp P" WAP" (1 WARP WARP (1 WARP (1 WARP PWR WARP (1 WARP P " WAP" WARP (1 WARP (2 PWRP WARP PWR WAR P" WAP " WAP (3 LW LW LW WARP alw (1 tswr PWRP (1 LW (1 LW (1 LW LW LW tswr PWRP LW (1 LW (1 LW PLR (4 LW LW 1LW LR alw PLR LW (1 LW LW (5 (1 LW LW (1 tswr PWRP LW (1 LW (1 LW PLR PLW LW (1 tswr PWRP WARP PLR LR (6 where the set represents farming sectors; WAP represents pipe water production. WAR is irrigation water input in the th production; WAP is pipe water input; WARP is the compose water input; LR is irrigation land input; PWR is irrigation water price; P "WAP" is the price of pipe water as the product provided by pipe water production; PWRP is the compose water price, respectively. tswr is the irrigation subsidy rate, which is given in a negative value. PLR is the return of irrigation land; awarp and alw are the efficiency parameters; γwarp and γlw are the share parameters; σwarp is the CES between irrigation water and pipe water; and σlw is the CES between compose water and irrigation land. In CGE-WPS, the relationship between the integrated water and irrigation land are presented by equation (7-(9, which are modified from the equation (4-(6, respectively; the distinction between irrigation water and pipe wateris not defined, and so equation (1-(3 are deleted. WAT LW LW LW alw (1 tswr P" WAT " LW LW (1 LW (1 LW (1 " WAT " LW (1 LW LW PLR LW tswr P (1 LR LW 1 LW alw PLR (1 LW (1 LW (1 LW tswr P (1 LW LW " WAT " LW (1 LW LW PLR PLW LW (1 tswr P WAT PLR LR " WAT " LW where WAT indicates the integrated water production. WAT is the integrated water input in the th production; P WAT is the price of integrated water. Other variables and parameters are not changed. China is assumed to be a small open economy as usual, and the trading between the foreign and domestic markets is imperfectly substitutable. The exchange rate is fixed as the price numeraire. The total supplies of the factors, including capital, agricultural labor, non-agricultural labor, irrigation land, non-irrigation land, and irrigation water (solely in CGE-WPPS were fixed. Households income originated from the factors returns, and their consumption behaviors were defined by the Stone-Geary utility function. Moreover, in CGE-WPPS, the payments of irrigation water supply and irrigation subsidy are collected by the government s revenue account; and in CGE-WPS, The integrated water is supplied by the integrated water production, and then only irrigation subsidy is supported by the government. 2.2 Simulation design and closure condition A simulation under multiple scenarios was conducted to estimate the impacts of eliminating the irrigation subsidy on farming sectors and households. In CGE-WPPS, we fixed the irrigation water price to match the current pricing policy, which means that eliminating the irrigation subsidy would raise the irrigation water price to the full-cost level. Furthermore, the total quantity of irrigation supply became flexible as an endogenous variable; thus, we can investigate the water-savings capacity by examining the decline in water demand. In CGE-WPS, both the price and the supply of integrated water were endogenous variables; thus, eliminating the irrigation subsidy would raise the price of integrated water to the market price level, which was endogenously determined by a market process. Five scenarios were designed to different factor mobility settings for the two systems (refer to Table 1. The first (7 (8 (9

4 240 Journal of Resources and Ecology Vol. 7 No. 4, 2016 column of Table 1 lists the factors input in farming sectors, including water (irrigation water and pipe water in CGE-WPPS; and integrated water in CGE-WPS, irrigation land, non-irrigation land, agricultural labor, non-agricultural labor and capital. The second column indicates the condition setting to factor mobility, divided into two conditions of Mobile and Fixed with regard to whether or not factor inputs can freely flow ass among farming production sectors. Mobile means that factor mobility was able to move a factor ass different sectoral production processes. In contrast, Fixed means that sectoral factor inputs were fixed; thus, the factor return would vary within different sectors. Therefore, conducting a comparative analysis from S1 to S5 incorporated an assumption of an improvement in the factors mobility. For instance, Scenario 1 (S1 illustrates a most strict situation, in which the irrigation land, non-irrigation land, and agricultural labor that were used to cultivate one p could not cultivate other ps. Scenario 2 (S2, Scenario 3 (S3, and Scenario 4 (S4 fixed one factor, respectively. Scenario (S5 tested the free-will factor mobility, which was assumed as the first rationale to market efficiency. A similar study about this setting and discussion can be found in Wang et al. ( Data WPPS and WPS are also defined in the dataset, Social Accounting Matrix (SAM, respectively (called SAM-WPPS and SAM-WPS, which provides a benchmark for the simulation. The initial versions of SAM-WPPS and SAM-WPS were presented by Zhong et al. (2015a. In this study, we estimate the equilibrium irrigation water input costs and irrigation subsidies for each farming sector and introduce them into the new version of SAM-WPPS to present the given price distortion between irrigation water input and pipe water input. The estimated values of sectoral irrigation water inputs are assigned by the equilibrium irrigation water input costs. The estimated value of the irrigation subsidy rate, which is equal to 0.91 at the ma level means that irrigation subsidy accounts for 91% in each unit of water price, is consistent with that provided by Zhang and Li (2012. The pipe water is a production sector and is represented by the sector, Water Production and Distribution, which is recorded in the Input-Output Tables of China 2007 (NBSC, The detailed estimation of the equilibrium irrigation water input costs and irrigation subsidies can be found in Zhong et al. (2015b, and that of the irrigation water input costs without subsidies is in Zhong et al. (2016. In the new version of SAM-WPS, each farming sector s integrated water input is equal to the sum of the irrigation water input and the pipe water input. For other sectors and households, the values provided for the integrated water are the same as those for the pipe water in SAM-WPPS. Moreover, because the input information of irrigation water production is not available in the official database, we must assume that the input coefficients of irrigation water production are the same as that of pipe water production; we then estimated the input structure of integrated water production and entered it into SAM-WPS. Finally, the RAS approach, which was introduced by Stone (1961 and widely used in many studies, is used to balance the SAM-WPS. In a CGE analysis, nothing will change without external shock, such as a drought, economic growth or a water pricing policy like the eliminating irrigation subsidy as in this study. That is because if there is not water scarcity caused by drought (a change in supply-side, economic growth (a change in demand-side, or an increase in water price, WPPS and WPS might not be different in the efficiency of water distribution. Moreover, SAM plays as the dataset and the benchmark of simulation in CGE models (Zhong and Tokunaga In this study, SAM-WPPS and SAM-WPS act as the dataset and benchmark of simulation in CGE-WPPS and CGE-WPS, respectively. Furthermore, the values of the parameters used in CGE-WPPS and CGE-WPS were empirically determined in accordance with Zhong et al. (2015a and Zhong et al. (2015b. Specifically, we set 0.2 LW Table 1 Closure conditions of factor mobility in the five scenarios Farming factors Conditions Scenario 1 (S1 Scenario 2 (S2 Scenario 3 (S3 Scenario 4 (S4 Scenario 5 (S5 Irrigation water Mobile Pipe water Mobile Integrated water Mobile Irrigation land Mobile Fixed Non-irrigation land Mobile Fixed Agricultural labor Mobile Fixed Non-agricultural labor Mobile Capital Mobile

5 SHEN Ming, et al.: Comparative Evaluation between Water Parallel Pricing System and Water Pricing System in China: A Simulation of Eliminating 241 to represent the fact that, in China, the irrigation water demand is price inelastic to the water pricing policy (Aregay et al. 2013; Mamitimin et al. 2015; Zhong et al. 2015b. 3 Simulation results 3.1 Impacts on farming sectors and households Results in Table 2 proved that there was great potential for promoting water conservation, and WPS improved with more water savings and less farming output loss under all scenarios: water demand decreased by more than 84% in WPPS and by more than 86% in WPS; and farming output declined by more than 2.35% in WPPS and by more than 2.15% in WPS. Moreover, in both WPPS and WPS, the results derived from S2, S3 and S5 were similar, and those from S1 and S4 were also similar, which means that the changes were more dependent on agricultural labor mobility than on land mobility. For instance, under S5 in WPPS, improving both the mobility of agricultural labor and land would contribute more water saving (86.61%, fewer losses in output (2.15% and exports (3.08%, and thus higher producer prices (5.29% as well as more imports (0.40%, compared with the results derived from S1 and S4. Furthermore, rural and urban households income and food consumption would be improved due to higher returns from most factors, except irrigation land, in both WPPS and WPS. The increasing food consumption was basically from additional farming imports because domestic farming outputs suffer losses, as noted above. WPS would cause households to benefit from more income and food consumption, which were due to a higher return from most factors; in addition, households would benefit from more farming imports and less farming output losses. Conversely, it was not difficult to imply that promoting factor mobility would lower its return (refer to Table 2. The sectoral changes under the S1, S2, S3, S4 and S5 of WPPS and WPS provided a detailed understanding of specific farming sectors; more significant changes continued to be found in WPS for each farming sector (refer to Fig.1. Among all farming sectors, the greatest capacity for water savings (refer to Fig.1a were found for vegetables and fruits, whereas the worst losses in output (refer to Fig.1b and the exports (refer to Fig.1d with the highest increase in producer prices (refer to Fig.1c and imports (refer to Fig.1e were from sorghum. 3.2 Sensitivity analysis In the sensitivity analysis, we designed three cases with different values of water demand elasticity (LM; these were 0.2, 0.5, 0.8, respectively. These cases were based on the free-will factor mobility of S5 for both WPPS and WPS. Overall, the empirical results are robust under different cases. The results also indicated that higher water demand elasticity would play an important driving role in promoting more water savings. Fewer losses in output and exports as well as smaller increases in producer price and imports were also identified. Rural and urban households would benefit from more income and food consumption due to the further increase in the factors returns (refer to Table 3. In comparison with WPPS, WPS further extends these effects; a greater improvement in farming production would Table 2 Changes in the agricultural economic indexes Unit: % Water Parallel Pricing System (WPPS Water Pricing System (WPS S1 S2 S3 S4 S5 S1 S2 S3 S4 S5 Farming Sector as a Whole Water demand Output Producer Price* Export Import Households Factors Return Urban Rural Irrigation Land 99.75** 99.77** ** 99.81** Non-Irrigation Land 3.56** ** ** ** Agricultural Labor 4.94** ** ** ** 1.07 Non-Agricultural Labor Capital Income Food Consumption Income Food Consumption Note: *it is the change in average price of farming products; **it is the change in average return of farming factors; values with minus denote decline.

6 242 Journal of Resources and Ecology Vol. 7 No. 4, 2016 Fig.1 Changes in the farming sectors of WPPS and WPS in different scenarios be achieved, including more water conservation, fewer declines in output and exports, and relatively lower producer prices and exports. In addition, household income and food consumption improved because the factors returns in WPS were higher than that in WPPS (refer to Table 3. Fig.2 shows that the ordering of all farming sectors was not changed in the different cases of water demand elasticity. Furthermore, although vegetables and fruits continued to be identified as that with the greatest capacities in water savings, and the capacities of other farming sectors could be improved more significantly when the water demand elasticity increased, particularly for sugarcane and potato (refer to Fig.2a. In addition, the losses in the farming outputs (refer to Fig.2b and exports (refer to Fig.2d were reduced; thus, the increases in producer prices (refer to Fig.2c and imports (refer to Fig.2e decreased. The most significant changes in output, export, producer price, and import remain in sorghum. When the comparative evaluation was conducted between WPPS and WPS, the findings were the same; WPS continually improved the capacity of water savings of all farming sectors to a higher degree, then the de creases in farming outputs and exports were lower, and thus the increases in producer prices and imports decreased. 4 Conclusions and policy recommendation In general, WPS is better than WPPS because WPS would further improve water conservation and reduce the loss in output. Moreover, if the mobility in agricultural labor were to improve, water savings could continue to be promoted, and the decline in output could also be narrowed. WPS improved household income and food consumption compared with WPPS. Sensitivity analysis offered robustness testing for this simulation, and indicated that higher water demand elasticity, particularly in WPS, would contribute a better condition for water conservation, and output in the farming sectors as well as in household income and food consump-

7 SHEN Ming, et al.: Comparative Evaluation between Water Parallel Pricing System and Water Pricing System in China: A Simulation of Eliminating 243 Table 3 Testing in the agricultural economic indexes Households Farming Sector as a Whole Factors Return Rural Urban Unit: %; Water Parallel Pricing System (WPPS Water Pricing System (WPS LW LW Water demand Output Producer price* Export Import Irrigation Land Non-irrigation Land Agricultural Labor Non-agricultural Labor Capital Income Food Consumption Income Food Consumption Note:*it is the average price of farming products; values with minus denote decline. LW LW LW LW Fig.2 Testing in the farming sectors in different water demand elasticity cases

8 244 Journal of Resources and Ecology Vol. 7 No. 4, 2016 tion. Therefore, one of policy recommendations is to continue promoting the reform on WPS by eliminating the irrigation subsidy, and another one is to increase the water demand elasticity by improving water-saving technology and water management. Indeed, eliminating the irrigation subsidy should be gradual, with more focus on the changes in farming outputs to avoid applying excessive pressure on food security. Moreover, the strategies for expending water-saving technology should focus more on the changes in the prices of water and farming commodities, which can create incentives for farmers to cultivate higher-value ps. Additional technical support to improve the mobility of agricultural labor is necessary in the policy framework, including providing training in multi-cultivation, expanding pping options and improving the working ability ass farming sectors. This study is limited to the ma level, and the more detailed effects still need to be identified concerning the regional uneven conditions of water distribution and economic development, in consideration of a country as large as China. Moreover, the water savings derived from the simulation appears to be excessively optimistic because the simulation setting was unrealistic, where the time factor, policy feasibility, improvement in farming technology, and other changes, and so on were not taken into account. In other words, we supposed the remove of irrigation subsidy as a short-term event, and provided a perfect market solution to achieve an optimal resources allocation without considering any obstruction against the pricing mechanism. In addition, this study predicted that households food consumption could be increased by rising farming imports under an assumption that the international food price remains constant. 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9 SHEN Ming, et al.: Comparative Evaluation between Water Parallel Pricing System and Water Pricing System in China: A Simulation of Eliminating c.Simulation of the Impacts of Different Pricing Systems of Water Resources on the Ma-Economy Based on CGE model on a Background of Urbaniation.Resources Science, 37(12: Zhong, S., Sha, J.H., Shen, L., Okiyama, M., Tokunaga, S., Yan, J.J., Liu, L.T Measuring drought based on a CGE Model with multiregional irrigation water. Water Policy, on publishing. Available online: (accessed on 8 February DOI: /wp Zhong S Impact of Water Resources on Agricultural Economy and Rural Households in China: A Computable General Equilibrium Analysis. PhD diss., University of Tsukuba. Zhong S A Study on the Impacts of the Pricing Systems of Water resources on Agricultural Economy Based on a CGE model. PhD diss., China University of Geosciences (Beijing. 沈 明 1,2, 钟帅 1, 沈镭 1, 刘立涛 1, 张超 1,2 1 中国科学院地理科学与资源研究所, 北京 ; 2 中国科学院大学, 北京 摘要 : 中国水资源定价改革对农业生产有重要影响, 而中国农业生产具有很大的节水潜力 本研究将取消灌溉补贴作为模拟背景, 将中国水资源平行定价系统和统一定价系统分别引入可计算一般均衡 (CGE 模型进行模拟实验及比较评估 结果显示, 与平行定价系统相比, 统一定价系统将促进农业进口增加, 减少农业产出损失, 且更有利于促进水资源节约利用, 同时城乡居民也可以实现收入增长和食物消费需求增加, 而增加的食物消费主要来源于进口 然而, 取消灌溉补贴作为一项政策建议需考虑如何降低乃至抵消其对农业产出的负面影响 此外, 为进一步改善节水政策实施效果, 特别是在统一定价系统下, 提高农业劳动力流动性和水资源需求弹性需要得到更多关注 关键词 : 中国水资源定价改革 ; 取消灌溉补贴 ; 要素流动 ; 可计算一般均衡模型 ; 农业生产部门