Interactive comment on “ Modeling economic costs of disasters and recovery involving positive effects of reconstruction : analysis using a dynamic CGE model ”

This paper presents a methodology for analyzing the macroeconomic impacts of disasters, with an emphasis on the impacts f post-disaster reconstruction investment. The method is applied to a case study of major earthquake in China. The mo el is well crafted and reasonably well present d, and the application to the Wenchuan earthquake carried out adeptly. The paper makes a significant contribution to the literature,


Introduction
Natural disasters not only cause serious direct losses, such as house collapse or infrastructure damage, but also have strong impacts on the development of the macro economy, such as economic decline and unemployment (FEMA, 2011;Przyluski and Hallegatte, 2011).After every large-scale disaster, government institutions, insurance markets, and the media have primarily focused on the resulting direct losses but have Figures hardly announced the economic impacts.However, during post-disaster reconstruction periods, the governments of various nations used to use economic indicators to define the goals of their recovery.For example, in the aftermath of the 2008 Wenchuan Earthquake, the Chinese government set the goal of pushing employment in every family and promoting economic development within approximately 3 yr (NDRC, 2008).In the "Road to Recovery" report regarding the Great East Japan Earthquake, the Japanese government designated a 10 yr period for reconstruction.The budget scale for the next 10 yr is JPY 23 trillion (the exchange rate of JPY to USD was 0.01157 in 2012), and the average real growth rate of the economy is expected to be approximately 2 % (Government of Japan, 2012).After Hurricane Katrina in 2005, Louisiana faced a 766 % increase in initial unemployment claims.The local government developed new industries or assisted their proven, dominant industries to recover its employment and stabilize its economic base within two years of the storm (Kates et al., 2006).Therefore, if scientists can assess the impact of disasters on economic indicators shortly following a disaster, governments would have a solid theoretical basis for developing reconstruction and recovery policies.
The economic costs of natural disasters are often measured by indicators such as value added, gross output, or employment status (ECLAC, 2003).The ways in which natural disasters affect economies are complex: after a disaster, the damage to plants and factory facilities lead to the suspension of operation or slashing production, which are considered the direct impacts of disasters on the economy.The shortage of raw material and workers is another effect, and the disruption of industrial chains also induces production losses.Moreover, there are also "induced effects", such as unemployment resulting in low income, and terrible production activity resulting in low taxes, which are another impact of disasters on the demand side of the economy.In addition, unlike the impact of social policy on an economic system which is concentrated sectoral event, the impact of natural disasters cut a wide swath across a range of regional economic activities.Thus, when evaluating the impact of natural disasters, avoiding under-estimates or over-estimates resulting from double counting is a difficult task.Another matter that needs to be emphasized is the fact that disasters have not only negative but also positive impacts on the economy (IPCC, 2012), for example, government aid, paired-assistance policy, special finance policy, tax and fee preference, social donations, mutual help and assistance, etc (Shi, 2012;Xie et al., 2012;Shi et al., 2013).Overall, if we could model the economic costs of disasters and recovery from all types of conduits and consider both the positive and negative effects of reconstruction when assessing the impacts, we would reach more objective conclusions and predict the trends of economic development under different reconstruction policies, which is beneficial for policy makers.
To date, there has been a great amount of research on the impact of natural disasters on the economy based on the input-output (I-O) model, econometric model and computable general equilibrium (CGE) model.These studies have made significant contributions in this respect but still require further improvement, i.e., the positive effects of natural disasters such as reconstruction investment need to be incorporated into the assessment framework.For example, in the case of estimating economic impact from damaged transportation system due to disasters, freight transport and labor force maybe reduced, which further affected the regional economy.However, the model did not take into account positive aspects, such as the increase in capital stock during reconstruction period.Thus, the model only indicates the maximum potential losses due to natural disasters (Tirasirichai and Enke, 2007;Xie et al., 2012).Rose et al. (2007) evaluated the economic costs of an electricity blackout using the CGE model, incorporating the positive effects of resilience, including substitution, efficiency enhancement and price signals, but he did not model the rebuilding procedures that also exerted positive effects on the economy.Sue Wing (2010) performed an assessment on the economic cost of a storm scenario based on the dynamic CGE model, in which the recovery of capital stock was simplified.In fact, the recovery of capital stock is mainly investment-driven, and investment will affect the demand side of the economy.Hallegatte (2008) assessed the economic costs of the 2005 Hurricane Katrina disaster in America using the adaptive regional input output (ARIO) model, whose Introduction

Conclusions References
Tables Figures

Back Close
Full greatest advantage was that it could model the monthly changes in the economy after the disaster.In terms of the positive effects of natural disasters, this model incorporated a parameter called overproduction capacity, which was difficult to relate to the real aid that the government provided for reconstruction in the aftermath of the disaster, such as the tremendous investments, tax benefits, and technical support.In this case, the ARIO model evaluated the impacts of the disaster by assuming the overproduction capacity to be 120 %.Haimes et al. (2005a, b) and Jung et al. (2009) designed the inoperability input output (IIM) model which was effective in assessing the impacts on the supply side of the economy.But it does not consider any positive effects of natural disasters.Moreover, Okuyama (2007), Tatano and Tsuchiya (2008), Santos et al. (2012), Wu et al. (2012) and Xie et al. (2012) have all assessed the economic costs of natural disasters based on regional economic models.Their studies have resolved the contradictions between the requirement of highly precise data input regarding direct loss and the imperfect methodology used when assessing direct economic losses due to natural disasters.However, most studies have focused on the negative impacts of disasters and have neglected or simplified positive impacts or have used contextual assumptions to address positive impacts.
The aim of this study was to assess the objective economic impacts of disasters incorporating the positive effects of reconstruction, and contributions of reconstruction actions (e.g., government aid, tax and fee preference, special finance policy, pairedassistance policy, social donations, mutual help and assistance) in a comprehensive manner.This article is organized in five sections.Section 2 discusses how the standard CGE model can be modified into a new model capable of simulating the negative and positive effects of disasters after examining the mechanism and channels of positive and negative impacts induced by disasters.Section 3 is the introduction of 2008 Wenchuan Earthquake in China, ensuing reconstruction and data needed.Section 4 constructs three scenarios: S 0 (no disaster occurs), S 1 (disaster occurs with reconstruction investment), and S 2 (disaster occurs without reconstruction investment) within CGE model framework.S 0 is taken as a business as usual (BAU) scenario, and Introduction

Conclusions References
Tables Figures

Back Close
Full the difference between S 1 and S 0 and that between S 2 and S 0 are defined as economic loss including reconstruction and excluding reconstruction, respectively.The difference between the two types of losses is considered the contribution of reconstruction.Finally, Sect. 5 summarizes our findings and proposes directions for further research.

The mechanism of the impacts that natural disasters exerted on the social economy
The impacts that earthquakes exert on economic activities are both negative and positive (Fig. 1).
Regarding negative impacts, earthquakes lead to a decline of population, manifested by large quantities of sudden death or injuries which reduce working ability, and a reduction of capital stock, manifested by the destruction of infrastructures, machinery equipment and plants causing a leftward shift of the aggregate supply curve and a slump in the supply capacity of the economy.Regarding positive impacts, there are both demand-and supply-side shocks.From the perspective of the supply side, current reconstruction investments form the capital stocks in the following periods, and damaged capital stock are supplemented and recovered, leading to a rightward shift of the aggregate supply curve.From the perspective of the demand side, during reconstruction period, to recover the capital stock of the economy and satisfy the need for normal investing activities, there will be great acceleration and rise in the demand for investment in disaster areas.Meanwhile, disaster victims must decorate their newly built houses and purchase indoor facilities, which accelerate the recovery of consumption needs to some extent.Moreover, the government will pour necessary public funds into reconstruction.Altogether, the effects on consumption should be positive, resulting in a rightward shift of the aggregate demand Introduction

Conclusions References
Tables Figures

Back Close
Full curve.The two forces of supply and demand exert positive effects on the economy.Moreover, tax benefits also have a great positive effect on the economy.The CGE model can simulate both the positive and negative impacts of disasters on the social economy within a unified framework and thus avoid the underestimation, overestimation or double-counting problem of economic losses.Also CGE models provide an ex ante simulation laboratory for conducting counterfactual analysis.This allows us to establish different scenarios.Ex post methods are able to make assessments within real context, but the assessment of the losses caused by a disaster requires a comparison of the discrepancies between two different scenarios.Thus the CGE model is one of the most employed modeling approaches in the literature to account for the effects of natural disasters on the economy (Wittwer and Griffith, 2011;Horridge et al., 2005;Greenberg et al., 2007Greenberg et al., , 2012;;Pauw et al., 2011).For example, the CGE model has been widely used in the evaluation of the impacts of water or electricity disruption on the economy (Rose and Liao, 2005;Rose et al., 2007), but few studies have focused on the economic impact of reduced capital stock resulting from natural disasters (i.e., the destruction of plants, equipment and infrastructures) using the CGE model, even though that is the source of the impact and is the major target of post-disaster reconstruction.Moreover, the process of recovering capital stock consists in making investments in the first period; in the next period, these investments will form the capital stock with the aid of reconstruction action.To assess the negative impacts of reduced capital stock and the positive impact of post-disaster reconstruction based on the CGE model, it is necessary to develop the static CGE model into a dynamic CGE model.The traditional CGE model is suggested to refer Appendix.The following parts mainly introduce our improvement of traditional CGE model to simulate negative disaster shocks and the positive effects of reconstruction within a unified framework.

Improvement of traditional CGE model
During post-disaster reconstruction, governments provide some benefits regarding the production tax.Tax benefits are achieved by reducing the tpc and tpr parameter values Introduction

Conclusions References
Tables Figures

Back Close
Full in the traditional CGE model.Based on this model, some improvements that reflect disaster shocks and reconstruction investment are indicated by the dotted line box in Fig. 2. Specifically, the market clearing block, macro-closure block and dynamic block are improved.

Improvement of market clearing
Equation (A11) for traditional market clearing and macro-closure block is improved with Eq. (1).Firstly, total investment is divided into normal investment and reconstruction investment.Secondly, direct loss from damaged houses is the main component of total direct loss; thus, house investment accounts for a relatively large proportion of the total reconstruction investment.Nevertheless, the capital stock formed from house investment hardly contributes to expanded production in the next period (Hallegatte, 2008).Thus, house investment mainly exerts a positive impact on the demand side of the economy.Accordingly, reconstruction investment is further divided into house investment and other reconstruction investments.
Traditional CGE models close the labor market under either the "Neoclassical" assumption of full employment (perfectly inelastic supply) or "Keynesian" assumption of variable employment (perfectly elastic supply at a fixed wage).However, these two models cannot capture the impacts of disasters on the economy adequately because disasters also have significant effects on employment and incomes (Sue Wing, 2010).Thus, in our model, labor flow among different sectors through the use of constant elasticity of transformation (CET) functions.Accordingly, we model labor as a variable factor Introduction

Conclusions References
Tables Figures

Back Close
Full whose endowment is price-responsive, which is achieved by specifying a short-run labor supply curve with elasticity ω L , which scales the labor supply from its benchmark level LS (Eq.2).Moreover, all industries suffer stock losses greatly from a catastrophe, then they all increase investments in the reconstruction period.To incorporate this special aftermath into model, sector-specific capital is assumed within short time in our model.
where LS indicates the labor supply, LS indicates the labor supply in a base period, W is salary and ω L indicates the price elasticity of the labor supply.

Improvement of macro-closure rules
The investment amount in each industry is exogenous, and the total amount saved is determined by the total investment endogenously.The exchange rate is endogenous, and foreign savings are exogenous.It should be noted that the model used in this study assumes the savings in the rest of country to be endogenous because most investments are offered by the central government, other provincial governments, enterprises and residents.

Improvement of dynamic module
The total investments, excluding reconstruction investments, are roughly counted as normal investments.In this model, normal investments are distributed among various industries based on the industry investment structure in base year, and then transformed into the capital stock (XCn) in the following period according to the investment coefficient matrix (Eq. 3) (Miller and Blair, 1985).The disaster-proof investments can also be transformed into capital stock (XCd).And the distribution of transformed capital stocks among industries are determined by the proportion of the direct losses suffered Introduction

Conclusions References
Tables Figures

Back Close
Full by those industries; then the disaster-proof investments of various industries can be achieved according to the investment coefficient matrix (Eq.4).The model presumes that there is a housing sector.The damage to housing inventory will bring newly increased investments but no contribution to the capital stock of other industries.In each period, the housing capital stock (XCh) is calculated by multiplying the total investments in that period by the ratio of direct losses in the housing sector accounting for total direct losses.Then, according to the investment coefficient matrix, the housing capital stock (XCh) can be converted to the investments of various industries (Eq.5).
Only in that year disaster occurred did natural disasters cause a decline in capital stock in various industries (Damage).Considering the actual circumstances of reconstruction in China, to accelerate the process, most of the damaged floating assets, such as excavators used in the architecture industry, were imported from other areas, instead of waiting for local production.Hence, the model presumes that part of the disasterproof investments can be directly transferred to current capital formation (Eq. 6).The earthquake had a magnitude of M s = 8.0 (earthquake magnitude is usually measured on the popular M s scale, which ranges from 0 to 10; an M s = 8.0 earthquake can destroy an area measuring 100 square miles) and a maximum intensity of 11  , 2008).There were 10 counties covering an area of 26 400 km 2 that were labeled as extremely damaged areas and 26 counties covering 61 500 km 2 that were labeled seriously damaged areas.These counties accounted for 20 % of the total 181 counties, and the sum area represented 18 % of the total 485 000 km 2 of Sichuan province (NCDR, 2008;Sichuan Bureau of Statistics, 2012).
In 2006 and 2007, before the earthquake, the GDP of those disaster areas accounted for 26 % of the total GDP of Sichuan province (Sichuan Bureau of Statistics, 2012).

Introduction to Post-earthquake Reconstruction
The government implemented many active policies to accelerate reconstruction and to mitigate the effects of the Wenchuan Earthquake.In September 2008, 4 months after the earthquake, the government introduced a plan called "The State Overall Plan for Post-Wenchuan Earthquake Restoration and Reconstruction" to accelerate the reconstruction process.The government also implemented active fiscal policies: central finance established reconstruction funds for post-quake reconstruction (approximately CNY 300 billion, i.e., 30 % of total direct losses), and these funds will be released over the 3 yr following the earthquake.The local government of Sichuan also established comparable funds.These funds were collected through various channels: local government allocation, counterpart assistance, social donations, domestic bank loans, foreign emergency loans on favorable terms, urban and rural self-possessed and selfcollected capital, etc.In addition, 18 assistance provinces (cities) offered assistance Introduction

Conclusions References
Tables Figures

Back Close
Full with no less than 1 % of their last ordinary budget revenues to their 18 counterpart counties (or districts) in Sichuan, respectively.Moreover, the government provided various preferential policies for local enterprises and investors.These policies included alleviating the tax burden on individuals, deducting partial administrative charges, supporting key enterprises and medium-and small-sized enterprises, and adjusting industry entrance permission (NDRC, 2008).These preferential policies eased the burden on local reconstruction and accelerated reconstruction to some degree.For more detailed data regarding reconstruction investments, please refer to Table 2 (Sichuan Bureau of Statistics, 2012), where "-" indicates that the data for that year are unavailable.

Data needed
The model implemented in this study contains 17 sectors: 1 agricultural sector, 10 manufacturing sectors, 1 architecture sector and 5 service sectors; the merger of the sectors is based on the industry classification of available direct loss data.A substantial amount of the data processed by the model was obtained from the detailed 2007 Social Accounting Matrix (SAM) for Sichuan Province, derived from the SAM database compiled by the Development Research Center of the State Council (DRC-SAM) (DRC, 2000), which is the most widely used database for generating SAMs in China.In the CGE model, some elasticity parameters must be derived from the literature.These include the elasticities of transformation between export and domestic production and, in the second nest, between in-province and out-of-province production, as well as the elasticities in the Armington functions of the import block and elasticities in the CES functions of the production block.These parameters are based on a synthesis of the literature (Oladosu, 2000;Rose et al., 2007;Vennemo et al., 2009), and other major parameters were specified during the model calibration process.
Using the traditional CGE model, a dynamic block was incorporated into this study.
Capital stocks in the benchmark year were estimated using a standard perpetual inventory approach (Goldsmith, 1951;Christensen and Jorgenson, 1973) (Liao and Ma, 2009;Zhang et al., 2004).
The impacts of a disaster and ensuing reconstruction on an economy can be reflected by adjusting some parameters or exogenous variables in the CGE model.Then, the economic system can achieve a new equilibrium.With the help of GAMS software, the CGE model can calculate a set of prices and quantities in a new equilibrium after a series of iteration operations.By comparing the two prices and quantities, we can assess the impacts of the disaster and ensuing reconstruction on the economy.

Three Scenario
In a rapidly growing economy such as that of China, the post-disaster social and economic aggregate levels may surpass the pre-disaster level within one year.However, this does not mean that social and economic conditions are recovered because this economy experiences some economic growth.Therefore, pre-disaster conditions cannot serve as a benchmark to assess the social and economic effects of a disaster.In this study, a non-disaster scenario was advised to be a baseline to assess the social and economic effects of disasters.Though it is a counterfactual simulation, the dynamic CGE model used in this study can assess social and economic conditions under this scenario.Three scenarios were constructed in this study (Table 3): a non-disaster scenario in which capital stock was not reduced and there was only normal investment but not reconstruction investment (S 0 ); a disaster scenario with reconstruction investment, in which the capital stock is reduced due to disaster and there is normal investment and reconstruction investment, including housing and other investment (S 1 ); and a disaster Introduction

Conclusions References
Tables Figures

Back Close
Full scenario without reconstruction in which the capital stock is reduced due to disaster and there is normal investment but not reconstruction investment (S 2 ).S 0 was taken as a business as usual (BAU) scenario, and the differences between S 1 and S 0 and that between S 2 and S 0 can be interpreted as economic losses including reconstruction and excluding reconstruction, respectively.The difference between the two types of losses is then defined as the contribution of reconstruction.

The trend of economic development in three different scenarios
The GDP before and after the Sichuan Earthquake disaster (2007)(2008)(2009)(2010)(2011) in the three scenarios is shown in Fig. 3.The disaster occurred in 2008, and the government-led reconstruction investment occurred over the period 2008-2010.Figure 3 shows that reconstruction investment moves the GDP (S 1 ) closer to the baseline scenario of no disaster (S 0 ), but if there is no investment, the GDP (S 2 ) would be much lower than the baseline scenario of no disaster (S 0 ).Thus, the disaster economic assessment methods that do not involve the positive effects of reconstruction overestimated evaluation results.In 2008, the year of the disaster, major efforts were made in post-disaster emergency rescue, reconstruction planning etc. Meanwhile" reconstruction work advanced slowly and only part of the reconstruction investment was used to aid damaged plants, equipment and infrastructure.Moreover, the sudden occurrence of disaster went against the planned government expenditure, and government investment in that year was lower compared to investments made in the following years.Thus, in 2008, the GDP values under the reconstruction scenarios (S 1 ) and non-reconstruction scenarios (S 2 ) are not very different.After 2009, with a large amount of reconstruction work to start and due to the rapid reconstruction of the whole country, part of the investment in that year will be able to be dedicated to plants, equipment, etc. so that industry recovers its production capacity.In the meantime, the government has obviously been increasing investment to reach a GDP (S 1 ) that is close to that under the no-disaster scenario, especially in the years 2010 and 2011.Under the no-reconstruction scenario (S 2 ) with only normal investment, economic growth is far lower than that in the Introduction

Conclusions References
Tables Figures

Back Close
Full no-disaster scenario.Therefore, rapid reconstruction work, making investments forming capital stock to supplement disaster-damaged plants, equipment, etc., and raising as much funds as possible for reconstruction by the government and market are effective channels for reducing disaster losses.
It is believed that differences of GDP between the reconstruction scenario (S 1 ) and no-disaster scenario (S 0 ) are disaster losses, and that between the no-reconstruction scenario (S 2 ) and no-disaster scenario (S 0 ) are overestimated disaster losses.Generally, over the period spanning from 2008 to 2011, under the reconstruction scenario (S 1 ), the toll of GDP loss in Sichuan Province amounted CNY 283.56 billion (the GDP loss rate is 4.0 %), and the average annual loss was CNY 70.89 billion, accounting for 10 % of direct economic losses; Under the no-reconstruction scenario (S 2 ), the toll of GDP loss in Sichuan Province was CNY 425 billion (the GDP loss rate is 5.9 %), with an average annual loss of CNY 141.44 billion, accounting for 19 % of direct economic losses.It can be seen that disaster economic loss assessment methods that do not involve reconstruction in the wake of the Wenchuan Earthquake will overestimate the GDP loss by approximately two times that under S 1 .

Recovery period
In Fig. 4, GDP variations are measured on the ordinate axis to illustrate the economic recovery under the reconstruction scenario (S 1 ) and no-reconstruction scenario (S 2 ).Under the reconstruction scenario (S 1 ), compared with that in 2006, the economic growth rate in 2007 was 14.2 %; compared with that in 2007, the economic growth rate in 2008 was 9.5 %; and compared with that in 2008, the economic growth rate in 2009 was 14.5 %.It appears that the economic loss in the year of earthquake was the greatest.The Chinese government aimed to provide funding and technological support to Sichuan Province for three years (from 2008 to 2010) in its Plan of Post-Disaster Restoration and Reconstruction after the Wenchuan Earthquake.We selected 2011 as the end of the restoration and reconstruction period in Sichuan because the investment in 2010 was vital to economic performance in 2011.Figure 4 shows that the difference of GDP in Sichuan in 2011 between the reconstruction scenario (S 1 ) and the no-disaster scenario (S 0 ) is less than 3 %.The GDP of Sichuan will not reach that level again until 2015 if the government does not support restoration and reconstruction (S 2 ).Thus, it is concluded that reconstruction investment shortened the economic restoration period following the Wenchuan Earthquake by approximately 4 yr.

Economic impacts of natural disasters
The above comparison of recovery periods shows that the no-reconstruction scenario (S 2 ) will not catch up with the reconstruction scenario (S 1 ) until 2015.Therefore, the year 2015 was selected as an end point to analyze four indicators on which the government usually focuses, namely, sector effects, employment status, residents' income and government's revenue under two different scenarios (SCIO, 2011).industries suffered loss in scenario S 2 , whereas in scenario S 1 , because reconstruction demands more products and services from the construction and building material industries.Thus, from 2008 to 2010, the output of these two industries increased by 25 % and 1 %, respectively, compared with those in the S 0 scenario (see Fig. 5a).Overall, in terms of the entire industrial sector, reconstruction will alleviate economic losses.

Employment status
Although employment is increasing gradually every year under S 1 , the unemployment rate still exists, in contrast to the non-disaster scenario (S 0 ) (see Fig. 5b).The reduction in output from 15 of the 17 industries will lead to unemployment, which is why all governments focus on employment after disasters.However, the construction and building material industries need a greater labor force due to growing outputs driven by reconstruction.After every earthquake, the building industry observes rising wages but labor shortages.Following the Wenchuan Earthquake, labor inputs have been provided by other provinces and the return of local labor has supported reconstruction.Thus, reconstruction will promote employment unlike under the non-reconstruction scenario.
More than 2 million workers will recover their jobs from 2008 to 2011, averaging 5 million people annually, due to reconstruction.

Residents' income
Compared with IO models, CGE models not only depict the interaction among industries but also the changes in the income and spending of residents, companies and governments, etc.Under S 1 scenario, residents' income has gained a steady increase, but compared with the no-disaster scenario, the income loss rate was the highest in 2009 (the reason is the same as that explaining why the highest GDP loss rate was observed in 2009).With continuing reconstruction, the loss rate began to decrease, except minor disturbance when reconstruction was finished at the end of 2010.Later, with the gradual recovery of economy, residents' income returned to the no-disaster level Introduction

Conclusions References
Tables Figures

Back Close
Full (see Fig. 5c).Overall, reconstruction enhanced employment and further increased residents' income.From 2008 to 2010, the income loss rates under the S 1 and S 2 scenarios were 5 % and 10 %, respectively.

The fiscal revenue of Sichuan Province
Under S 1 scenario, the fiscal revenue of local government maintained small increase each year; nevertheless, compared with no-disaster scenario, there were some losses and the loss rate reached its lowest level in 2010 when the reconstruction guided by the government was terminated.Then, with the gradual recovery of economy, the fiscal revenue of the local government recovered to the no-disaster level (see Fig. 5d).Fortunately, compared with S 2 scenario, reconstruction promoted the total output of all industries further as well as the fiscal revenue of the local government.From 2008 to 2010, the loss rate of the fiscal revenue of local government under S 1 was less than 1 %, whereas the rate under S 2 was more than 2 %.To summarize, reconstruction exerts positive effects on economic development; hence, the assessment of economic losses sustained after disasters must consider the positive effects of reconstruction.

Model test
The CGE model implemented in this study used reconstruction data published by the government, such as reconstruction investment, tax preference, donation and pairedassistance, as model inputs.The model does not require data processing so that evaluation results are much more objective.In fact, the reconstruction scenario (S 1 ) is the same as real situation after a disaster.In Fig. 6, to test the accuracy of the model, GDP under reconstruction scenario (S 1 ) is compared with GDP published by NBS.As indicated, the model and NBS data are quite similar from 2007 to 2011.The differences in certain years may be attributed to the fact that during the simulation period, the distribution of normal investment in different sectors was assumed to be roughly same as Introduction

Conclusions References
Tables Figures

Back Close
Full that observed in 2007.However, there may be some differences in reality.And more detailed investment data classified by sectors at the provincial level were unavailable.
The reliability of the model results can be verified from another perspective.Sichuan Province was divided into extremely hard-hit areas, hard-hit areas and the rest of Sichuan, whose post-disaster GDP trends from 2007 to 2011 (solid lines in Fig. 7) were then analyzed.In Fig. 7, a decreasing trend for GDP was observed in extremely hard-hit areas between 2008 and 2010 (the dotted line in Fig. 7a).Thus, extremely hard-hit areas lost a three-year opportunity for economic growth.A similar situation was faced by hard-hit areas, which experienced a moderate decrease in GDP in 2008 and a minor increase in GDP in 2009 (the dotted line in Fig. 7b).Hard-hit areas also missed an opportunity for economic growth.Conversely, GDP in the rest of Sichuan and Sichuan Province showed a growth trend.If the GDP growth rate in extremely hard-hit areas and hard-hit areas is assumed to be the same as that of the rest of Sichuan (the dotted line in Fig. 7c), the GDP under the non-disaster scenario in Sichuan can be estimated (the dotted line in Fig. 7d).As a result, the difference between the solid line available from NBS and the dotted line at the bottom right of Fig. 7 embodies the GDP loss rate, i.e. 5.2 % in 5 yr total.According to published literatures (Okuyama, 2004), the post-disaster GDP growth rate of the unaffected areas in Sichuan should be accelerated due to their role in supplying raw material to affected areas.Thus, this simple method overestimated the GDP loss.The dynamic CGE model in this study assessed the GDP loss rate as 4.0 %, just slightly lower than the results of above simple method.Therefore, there is reliability about the dynamic CGE model applied in this study.

Conclusions
In this study, a popular regional economic impact assessment tool CGE model was improved by incorporating the positive effects of reconstruction in order to model the Introduction

Conclusions References
Tables Figures

Back Close
Full economic costs of disasters and recovery.Unlike IO model, CGE not only assesses regional economic variations resulting from disruptions in industrial supply chains but also assesses regional economic variations resulting from "induced effects", such as the impact of employment on income, the impact of investment on savings, and taxes on government consumption.The dynamic CGE model implemented in this study has taken the advantage of assessing both industry chain effects and "induced effects".
The improvement made to the model include the following: (1) most of the negative impacts of natural disasters are supply-side impacts; therefore, the model sets direct losses, such as losses due to damaged facilities, equipment or infrastructure, as the amounts by which capital stock is reduced, thus improving the common practices employed in regional economic models (multiplier model, IO model and Traditional CGE model) by incorporating shocks into the demand side of the economy.( 2) The effects of natural disasters on the economy are not only negative, such as production reduction and halt, but also positive, such as the reconstruction efforts of governments (support for technology, capital and policy), markets (insurance compensation) and households

NHESSD Introduction Conclusions References
Tables Figures

Back Close
Full This study suggests that the reference standard for post-disaster economic recovery cannot be set as the pre-disaster level.A rapidly growing economy such as that of China is easy to recover to pre-disaster level within one year, but this does not indicate the real recovery of the economy.Therefore, three scenarios were established in this study: S 0 (no disaster occurs), S 1 (disaster occurs with reconstruction and disasterproof investment), and S 2 (disaster occurs without reconstruction and disaster-proof investment).Taking S 0 as a business as usual scenario, under S 1 or S 2 scenario the opportunity for businesses to gain profits, the opportunity for residents to gain welfare and the opportunity for the government to gain tax revenues and increase public consumption and investment will disappear.It is believed that differences between S 1 and S 0 or differences between S 2 and S 0 , rather than differences between post-disaster and pre-disaster economy, represent the real economic loss.
Reconstruction will stimulate an economy by recovering the damaged capital to resume the production of industries and by increasing investment to positively affect the economy from the demand side.During the reconstruction period from 2008 to 2011 for the Wenchuan Earthquake, which hit China in 2008, under the reconstruction scenario (S 1 ), the GDP loss incurred by Sichuan is CNY 283.5 billion, and the annual average loss is CNY 70.89 billion, which represents 10 % of the direct economic loss.Under the non-reconstruction scenario (S 2 ), the GDP loss incurred by Sichuan is CNY 425.00 billion, and the annual average loss is CNY 141.4 billion, which represents 19 % of the direct economic loss.It can be concluded that the assessment ignoring the reconstruction effects in the wake of the Wenchuan Earthquake roughly overestimate the GDP loss by one time.
In the initial recovery period, reconstruction effects are not obvious.However, as reconstruction expands, the economy in the reconstruction scenario rapidly recovers.
In the year when reconstruction is concluded, the gap in economic growth between the reconstruction and non-disaster scenarios is reduced to 3 %, a level that should take another four years to achieve under the non-reconstruction scenario.Therefore, in the case of the Wenchuan Earthquake, reconstruction reduces the recovery period by

Conclusions References
Tables Figures

Back Close
Full Bureau with the GDP simulated in the model under the reconstruction scenario reveals that the two are extremely similar.In addition, the economic growths of the extremely hard-hit areas and hard-hit areas are assumed to be equal to the growth of the rest of Sichuan such that the difference between the non-disaster GDP and the real GDP is calculated to be 5.2 %, which is the maximum economic loss (the rest of Sichuan witnesses rapid disaster-related growth).The economic loss estimated by this model is 4 %.It can be concluded that the model is found consistent with available data.
Turning to the effects on other social and economic indicators with which governments are concerned, on one hand the production of construction and building material industries, for example, will gain profits, higher than those under the non-disaster scenario.However, with the other 15 industries suffering loss from the disaster, the positive effects induced by disasters cannot be always concluded.On the hand the real post-disaster data for employment, residents' income and fiscal revenue is shown increasing trends.However, this three indicators suffer losses to different degrees when comparing with non-disaster scenario.Compared with economic status under the nonreconstruction investment scenario, reconstruction investment reduces economic loss by a large margin.The contribution of reconstruction to economic loss of disasters is closely related to the investment amount and reconstruction progress.In general, the model established in this study combines the negative and positive effects into one framework and assesses the economic effect of disasters from a more objective perspective to provide a scientific basis for reconstruction planning and implementation.This model is expected to be applied in other disasters and areas in addition to the disaster in question.

Discussion
Some published literatures have indicated that if we model post-disaster economic growth trends on a quarterly, monthly or weekly basis, we can model the short-term characteristics of a given disaster (Dixon et al., 2010); while the yearly model tends to Introduction

Conclusions References
Tables Figures

Back Close
Full smooth the extreme effects of disasters.The CGE model used in this paper operates on a yearly basis.We did not include short-term impacts because the economy tended to achieve equilibrium on a yearly basis (Narayan, 2003;Cooper et al., 1984).Further studies may focus on constructing hybrid models (intermediate between econometric models and CGE or IO models) to reflect short character of disaster impact.On the other hand, the post-disaster social and economic goals that governments set are all designed on a yearly basis; therefore, it is necessary to construct a yearly based model to evaluate the impacts of disasters on the social economy.In addition, the long-term sustainable development after disasters is worth noting.For example, after 3 yr of reconstruction, there is much high-tech equipment being used in newly built schools.The teachers who formerly used blackboards as teaching media may find it difficult to master the use of this new equipment, which induces negative effects on teaching.In some remote regions, people may organize large-scale vegetable planting, which usually exceeds the needs of that region and leads to agriculture losses.Also, during restoration, people focus too much on tourism, despite the fact that there is insufficient demand in this respect.From this perspective, it is necessary to construct a model based on a 5 yr or 10 yr period.In conclusion, the yearly based model employed in this paper can serve as a supplement for short-term and longer-term models and contribute to the reconstruction efforts of governments.Many research institutions have assessed the impacts of the Wenchuan Earthquake on China, and most of the results indicate that the earthquake did not affect China to a large extent.In this study, Sichuan Province was selected as a research area, and a CGE model was constructed on the provincial level.It was discovered that economic development after the disaster showed a growth trend, and compared with the no-disaster scenario, the rate of economic growth only declined by approximately 5 % in that year.For the extremely damaged areas, the economy suffered negative growth over three consecutive years.Assuming that the economic growth rates of extremely damaged areas were the same as those observed before the disaster, economic productivity was reduced by approximately 40 %.In general, models established at the Introduction

Conclusions References
Tables Figures

Back Close
Full national level or provincial level always cover the true impacts of disasters.Only social and economic assessments made in disaster areas provide results that reflect what victims feel.Furthermore, disasters such as floods or droughts, usually affect not only one isolated province but also the borders of several administrative areas.Therefore, further studies should take these borders into consideration when constructing a model for evaluating the impact of disasters on social and economic development.
There are both positive and negative effects of natural disasters on the society and economy of disaster areas.However, the effects also extend to other areas, also including positive and negative effects.These other areas will provide donations as well as technical support to disaster areas, which leads to the chance loss of consumption and investment for these unaffected areas and thus induces negative impacts.During restoration and reconstruction, some products must be imported from other areas because most industries suffer great damages and cannot product necessity, which results in excess production in other areas and stimulates economic development in these unaffected areas, which represents a positive impact.Constructing a model that can assesses the social and economic impacts on multiple areas surrounding disaster areas is essential to develop a comprehensive bank of social and economic assessment models for natural disasters.

A1 Production block
Every sector adopts the technology of constant returns to scale and makes decisions based on the principle of cost minimization.The production process is described by the four-tier, nested constant elasticity of substitution (CES) production function.The multiple tiers allow for the use of different substitution elasticities for different pairs of inputs.In addition, it is considered that there are intermediate input substitution possibilities for the energy sources, such as electricity, oil, etc.In the first tier, according to the CES production function, the gross output (XP) is determined by the capital, energy, labor aggregate (KEL) and other intermediate inputs (ND) (Eq.A2).In the second tier, the capital, energy, and labor aggregate (KEL) is disaggregated into labor (LD) and capital and energy aggregate (KE) (Eq.A3).In the same tier, the non-energy intermediate inputs are disassembled by the Leontief structure into the need for various non-energy products (XAp nf ) (Eq.A4); in other words, there is no substitution possibility among them.In the third tier, the capital and energy aggregate (KE) is further divided into energy (E) and capital (KD) based on the CES structure (Eq.A5).In the fourth tier, the energy aggregate is further disaggregated into different types of energy inputs, Introduction

Conclusions References
Tables Figures

Back Close
Full such as electricity, gas, coal and oil (XAp e ) (Eq.A6).
where A is the transfer parameter, λ is the efficiency parameter corresponding to each input, α is the share parameter, ρ = σ − 1/σ, and σ is the elasticity of substitution production function of the two inputs.The lower-case superscripts represent different tiers of the production process and correspond to different parameter values and the lower-case subscripts i represent different industrial sectors.
During the production process, in addition to the aforementioned input, the central government as well as the local government will levy various production taxes (Eq.12).
where PX represents the unit cost of the product without tax, PP represents the cost including tax, and tpc and tpr represent the production tax rates levied by the central government and local government, respectively.

A2 Trade block
The company describes the sales of the products with the two-tier nested constant elasticity of transformation (CET) function.In the first tier, the company chooses the Introduction

Conclusions References
Tables Figures

Back Close
Full optimal combination of domestic sale and export sale (Eq.13) that maximizes revenues.In the second tier, the domestic sale is divided according to the CET function into local sales and the rest of the country (Eq.14).
In terms of the sources of the products, the model adopts the Armington hypothesis, that is, the products within or outside the region are assumed to be of different qualities so that they cannot serve as substitutions for each other.Here, they are represented by the two-tier nested CES function.In the first tier, consumers from different regions select the optimal combination of domestic products and import products that minimize costs (Eq.15).In the second tier, the demand for domestic products is divided, according to the CET function, into the demand for products from local areas and that for products from other areas in the country (Eq.16).
This model uses the assumption of "small country"; that is, the imports, exports and transfer of the local products will not affect other areas in the country or the international market.The model includes tariff and export rebates; that is, it is considered that there are discrepancies between the international and domestic prices of the products.

A3 Demand block
Residents' incomes come from the labor supply and transfer payments from enterprises.The disposable incomes of residents are composed of the incomes after deducting personal income tax and the transfer payments of the local government.One part of the disposable incomes is saved at a fixed deposit rate, and the rest of the incomes are all spent on commodities and services.Residents choose the optimal combinations of commodities within budget constraints that maximize utility.The corporate revenues come from the return on capital employed and transfer to the residents after deducting corporate income tax.The central government revenues are derived from the production tax, personal income tax, corporation income tax, tariff, and transfer payments from local governments, while the local government's revenues stem from the production tax, personal income tax, corporation income tax, and transfer payments from the central government.The consumptive quantity of the commodities and services by the central and local governments is exogenously fixed.

A4 Market clearing and macro closure block
The standard CGE model contains three types of balances in commodity markets: the balances between supply and demand of commodities and services in the local markets (Eq.17), in the international markets and in the interprovincial markets.Due to the similar notation of supply and demand in the latter two markets, their market clearing equations will not be displayed.

A5 Dynamic block
The dynamic feature of the model derives from the accumulation of capital.The current capital amount (KStock) is composed of the capital stock in the previous period (KStock −1 ), depreciation excluded (δ is depreciation rate), plus the fixed capital formation (XC Inv,−1 ) in the previous period (Eq.18). KStock Labor supply and technology parameters are given exogenously.Introduction

Conclusions References
Tables Figures

Back Close
Full  Full Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | The Wenchuan Earthquake occurred on 12 May 2008, with the epicenter located at Yingxiu Town, Wenchuan County, Sichuan Province of China (31.01•N, 103.40 • EDiscussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Figure 4, however, shows that regardless of reconstruction scenario (S 1 ) or no-reconstruction scenario (S 2 ), the GDP loss in 2009 was the greatest when nodisaster scenario is set as business as usual scenario.The reason is that on one hand the reconstruction work performed in 2008 advanced slowly.Meanwhile, major reconstruction efforts were focused on emergency relief and reconstruction planning.Discussion Paper | Discussion Paper | Discussion Paper |So the damage amount of capital stock in 2008 was much the same as that in 2009.On the other hand the destruction of plants, equipment and infrastructure by the Wenchuan Earthquake, which hit China on 12 May 2008, only affected about six months of the economic period in 2008.The earthquake's effects on the economy spread throughout the year of 2009.Therefore, the economic loss in 2009 was the greatest when nodisaster scenario is set as business as usual scenario.
Compared with econometric models, the CGE model can not only demonstrate the change in aggregate economic quantities but also the loss and restoration states of different industrial sectors in an economic system.According to the CGE model, all 17 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

(
donations).The model used in this study describes the positive effects of reconstruction mainly in the form of reconstruction investments, tax preference and technical support.The major channels of reconstruction funds are from the government (government savings), enterprises (enterprise saving) and residents' donations (savings of residents who live outside the affected areas).The improvements made to the traditional CGE model in this study were achieved by setting a part of reconstruction investment forming capital stock in the existing period and the remaining part forming capital stock in the next period to reflect rapid reconstruction in the post-disaster reconstruction period.With respect to macro closure, the dynamic CGE model was formulated as an investment-driven model due to the relatively reliable data obtained for reconstruction investment.Most investments are offered by the central government, other provincial governments, enterprises and residents in addition to the small portion obtained from affected areas.Thus, in the model, the rest of China's save was set as an endogenous variable.
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | four years.Comparing the GDP indicated by statistics released by National Statistics Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | The traditional CGE model usually includes several sectors.The essential productive factors entail capital and labor.The accounts of institutions involve residents, companies, governments, and trading.The government accounts are distinguished between the central government and local governments, while the trading accounts are differentiated among local, the rest of the country and the rest of the world.The dynamic version of the CGE model is a recursive dynamic model, which means that the current Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | A11) The traditional CGE model features the following balance: demand/supply factor balance; investment/savings balance; central and local government accounting balance; and external balance.There are different closures in every balance.For the disasterspecific closures in each balance, see Sect.3.2.Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Fig. 7 .
Fig. 7. Variations in Sichuan GDP, in percent of S 0 (no-disaster scenario) GDP based on NBS data and CGE model.
It was the most destructive and widespread earthquake since the founding of the P.R.C., with 69 226 dead and 17 923 missing.The economic cost reached approximately CNY 845.2 billion (the exchange rate of CNY to USD was 0.14 in 2008), 91.3 % of which represented the direct economic losses of Sichuan Province, which was equivalent to 74 % of its GDP in 2007.For the direct economic losses of specific industries, please refer to Table1(NCDR • . Province, and the investment data after 2011 were estimated depending on the average investment amount from 2003 to 2007.Reconstruction investments were made only from 2008 to 2010 (please refer to Sect.2.2).The average rates of depreciation of sectors and capital coefficients matrix were derived from authoritative reports or literature in China . The investment data from 2007 to 2011 were obtained from the Statistical Yearbook of Sichuan Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | capital amount is composed of the capital stock, depreciation excluded, plus investments in the previous period.The traditional CGE model is composed of a production block, trade block, demand block, market clearing block and macro closure block.The structure of the standard CGE model is depicted in Fig.2(part that is out of box).With the aid of this framework, we will elaborate on the essential features of the CGE model:

Table 1 .
Direct economic loss due to Wenchuan Earthquake distributed by sectors in Sichuan (Unit CNY 100 million).

Table 3 .
Description of scenarios.The disaster reduced capital stock.Because the disaster occurred in Jun 2008, the reduced amount is assumed to be half of the direct loss.Since 2009, the reduced amount of capital stock has been calculated according to aggregate direct loss; -TFP is set as an exogenous variable, and its value is set based on S 0 ; -There is normal investment and reconstruction investment.The distribution of normal investment among different sectors maintains its' 2007 level.Reconstruction investment, except for that spent on housing, goes to different sectors with reference to the distribution of direct loss among sectors;