Multiplier Decomposition Analysis for Water management in Shanghai and otherregions, China: based on two-regional Social Accounting Matrix

University of TSUKUBA, Graduate School of Life and Environmental Science
Shuai, ZHONG
University of TSUKUBA, Graduate School of Life and Environmental Science
Suminori, TOKUNAGA

1. Introduction

In general specking, Shanghai, lying at the mouth of the Yangtze River, which is also thetop 3 largest river in the world, seems impossible to face the problem of water shortage. Butthe fact is just the reverse.

2006年

2007年

2008年

2009年

China's level

Shanghai

China's level

Shanghai

China's level

Shanghai

China's level

Shanghai

China's level

Shanghai

General background of water consuntion

2010

the amount of water available per person
water use by per ten thousand GDP
water use by per ten thousand value added in industry
water consumption by the irrigation in each Mu of farmland
water consumption by each household per capita day life

Figure 1, General background of water consumption
Data source: water resources bulletin, Shanghai 2007-2011;
Water resources bulletin, China 2007-2011.

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From the figure 1, it can be prove: within the whole period of observation, the amountavailable of water person in Shanghai is much larger than China general level. Even in 2010,
China face a comprehensive water shortage because of weather change, Shanghai was also
responsible for high degree of water available (548 cubic meters (Cm) per person, Shanghai;
450 Cm per person, China’s level).
But household in Shanghai was standing much difficulty comparing with other regions,because the index “water consumption by each household per capita day life” is always lower
than the China’s general level, and in 2010, this situation became more serious (117 litre (L.),
Shanghai; 276 L.). It can be found also at the index of “water using by per ten thousand GDP”:
such a low value according to China’s general level: in 2010, this value came the half ofChina’s level, (75 Cm use by per ten thousand GDP, Shanghai; 150 Cm use by per tenthousand GDP).
So the next question is where those waters have gone. This could be answered by theother two indexes. In 2010, water used by ten thousand value-added in industries in Shanghai(131 Cm, industry; 529 Cm, irrigation) and water consumption by the irrigation in each Mu offarmland are obviously larger than China’s general value (90 Cm, industry; 421 Cm,irrigation).
So based on the above discussion, we can have an initial observation: Shanghai facing aserious water shortage problem, especially for household and GDP growing. And it is possiblethat industry and agriculture would responsible for this situation.

2. Methodology: Multiplier Model based on Two-Regional SAM

In this paper, exogenous accounts and endogenous accounts were as following:(1) Endogenous account: activities (primary industry, secondary industry, and tertiaryindustry), factors (water, capital, and labor), and sectors (household and enterprises).
(2) Exogenous account: government (local government, central government, and taxes),
investment (savings), and the rest of world.

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A41*

Production activities
income Y1 (reg 1)

Production activities

A14*

A21*Y2 (region 1)
A13*

Factors income

income Y4 (reg 2)

Y2 (region 1)

A54*

A46*

Factors income
Y5 (reg 2)

Y2 (reg 1)

A43*

A32*

A16*

A65*

Sectors income

Sectors income

Y3 (reg 1)

Y6 (reg 2)

Ma3
Ma1(Omitted) Ma2

Source: Made by Author
Fig. 2 Decomposed multiplier effects and the closured cycle of income flow

Figure 2 describe the all of options for income flows, although cross multiplier effects(Ma2) was omitted because of graph limitation. Especially, we can understand how theclosed-loop multiplier effect (Ma1) be represented as a cycle system based on two-regional
SAM in the whole multiplier model.

3. Results and analysis

We began our discussion by the analysis of the shock on Non-water account.

0.00400.00200.0000(0.0020)

wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2
wat1
wat2

Total effects on water accounts in two regions

sec11 sec21 sec12 sec22 sec13 sec23 cap1 cap2 lab1 lab2 hou1 hou2 ent1 ent2
Total effects on water account in two regions

Source: Made by Author.
Fig. 3 Total multiplier effects on water account in two regions when non-water accounts shocked

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From figure 3, we can understand that, if other non-water accounts were shocked by oneunit, it would not raise any more influence on water accounts, no matter on Shanghai or otherregions, because none of those total multiplier effect passed even 0.4%. This result justdescribes the fact in China that all of water industries belong to government, and sogovernment would be respected to guarantee the sustainable of water supply and it would not
be impact by any other account shocked, so the issues about water demand and supply would
stand the significant purpose of policy design.
Another finding in figure 3 is that, when other accounts were shocked, water account inother regions express relatively higher values of multiplier effect than water account inShanghai, but it actually the summation of other regions in China, so it may not have any
meaning for policy.

Total multiplier effect when water accounts in both regions
were shocked
1.5
1
0.5
0-0.5
-1

sec11sec13 cap1 hou1 sec21sec23 cap2 hou2 sec11sec13 cap1 hou1 sec21sec23 cap2 hou2
wat1wat2

Total multiplier effect when water accounts in both regions were shocked

Source: Made by Author.
Fig. 4 Total multiplier effects on water account in two regions when water accounts shocked

The figure 4 demonstrates this point: Water supply as one of public services in China
does not make profit as the purpose of operation, so that shock from exogenous working on
itself would not let it get any multiplier effect, so that the multiplier effect of water accounts
in both two regions approximately equal one unit.
Figure 4 actually includes two results: water accounts in Shanghai and in other regions

4were shocked signally. If this case happened in Shanghai, the household seems to undertakethe most of negative total multiplier effect (-60.91%) and much worse than production
activities accounts (primary, -1.72%; secondary, -26.03%; tertiary, -22.79%) which can beexplain the water management for production is better than it service for livelihood.
The similarly situation also emerges in other regions, but the loss in household (52.10%)
is litter smaller than the secondary industry 53.20%, which is also playing as worse one inother regions.
It also should be noticed from figure 4 that when water account in Shanghai was shocked,
the worse one is not Shanghai household, and it is secondary industry in other regions(-81.93%), also tertiary industry suffer huge loss in multiplier effect (32.80%).

One unit exogenous demand for Shanghai’s water
0-0.2
-0.4
-0.6
-0.8-1
open-loop effectclosed-loop effectSource: Made by Author.
Fig. 5 One unit exogenous demand happened at Shanghai’s water accountAs mentioned above, if one unit from exogenous demand takes a pressure on Shanghai
supply, the worse one, which is suffering the most of income loss, is the secondary industry ofother regions, and then is the household of Shanghai, and the tertiary industry of other regions.
And open-loop and closed-loop effects would let us know more clearly. Considering about
open-loop effect, among the all of accounts of other accounts, when Shanghai’s water wasshocked, income earned from open-loop effect would be contributed more negative impact.
For example, secondary industry in other regions might suffer the loss of -70.63%, and forhousehold in Shanghai, this value is -60.51%, then also tertiary industry in other regions,5-25.24%. But we should not ignored that, there also many income losses coming fromclosed-loop system happening at the all of other region’s account, such as secondary industry(-11.19%), and tertiary industry (-7.56%).
So it acceptable that through open-loop effect and closed-loop system, Shanghai could
transfer the most of losses to other regions, and let itself be little better. And also, insider therelationship between Shanghai and other regions, the income linkages are secondary andtertiary industry, but Shanghai was contributed more efficiency for connection to otherregions than that connection from other regions to Shanghai, because at the same accounts,
the losses in Shanghai are much less than other regions.

4. Conclusion

In this paper, we discuss the multiplier model with two-regional SAM. The case is that if
the all of other non-water accounts were shocked, water supply as one of public service
managed by government almost didn’t suffer any influence.
When the case turned around to let water account be “inject” at one unit, water accounts
for themselves in both two regions actually didn’t get any multiplier effect. But When wateraccount in Shanghai shocked, then the worse three (first, second, third) accounts refer tosecondary industry in other regions, household in Shanghai, and tertiary industry. So it seems
acceptable that the most significant relationship between Shanghai and other regions locatesat secondary industry, and then tertiary industry.
In detail of open-loop effect, Shanghai suffered less than other regions, among thoseaccounts, which suffer the most loss of income is secondary industry belonging to otherregions, and then is the household and secondary industry in Shanghai, next is the tertiaryindustry in both Shanghai and other regions.
By the observation of result on closed-loop system, the worse one, which might suffer
the most of income loss, is also the secondary industry of other regions, and then is household
and labor in other regions. But those accounts locating in Shanghai would not suffer muchincome loss.
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