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DISASTER RISK REDUCTION INVESTMENTS ACCOUNTS FOR DEVELOPMENT

(DR2AD MODEL)

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Muneta Yokomatsu, Kyoto University

The 7th GEOSS Asia-Pacific Symposium Tokyo, Japan, 26-28 May 2014

What is the macroeconomic benefit of the investment on disaster risk reduction (DRR) that mitigates negative impact on national economy? Wide recognition in general public of the necessity of DRR Lack of quantitative assessment of economic value of the investment in DRR

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Hyogo Framework for Action (2005) • The United Nations World Conference on Disaster Reduction 1st conference at Yokohama in 1994 2nd conference at Kobe (Hyogo) in 2005 3rd conference at Sendai (in Tohoku) in 2015 • Hyogo Framework for Action (2005) 1. Making disaster risk reduction a priority; 2. Improving risk information and early warning; 3. Building a culture of safety and resilience; 4. Reducing the risks in key sectors; 5. Strengthening preparedness for response. Leading to awareness, emphasis on communities’ mutual help, etc…

Post-Hyogo Framework from 2015 • “Mainstreaming of Disaster Risk Reduction (DRR)” Initiative taken by Japan International Cooperation Agency (JICA), Japan Institute of Country-ology and Engineering (JICE), Pacific Consultants Co., Ltd, etc. Whereas Millennium Development Goals (MDG) does not provide an explicit perspective for DRR, in the Mainstreaming, DRR should be placed a high value in every process of development policies, poverty reduction, countermeasures for climate change, etc.

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Divergent views on economic impact of natural disasters • Macroeconomic research on natural disasters and their consequences is limited.

• Some consensus is reached that natural disasters have a negative impact on the short-term economic growth.

(e.g. Albara-Bertrand, 1993; Raddatz, 2007; Noy, 2009; Hochrainer, 2009)

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Divergent views on economic impact of natural disasters • The literature on the long-run effects of natural disasters is scant and inconclusive. The expansionary disaster effects caused by Schumpeterian “creative destruction”

(e.g. Skidmore and Toya, 2002; Cuaresma et al., 2008) The limited effect of creative destruction in developing countries

(Cuaresma et al., 2008)

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• Okuyama, Y. (2003) “Productivity Effect”: Destructions can foster a more rapid turn-over of capital, which could yield positive outcomes through the more rapid embodiment of new technologies.

• Stewart and Fitzgerald (2001) , Benson and Clay(2004) The increase in GDP growth is due to a catching-up effect and to the reconstruction-led Keynesian boom.

• Hallegatte S. and Dumas, P. (2009) Productivity Effect can introduce a bifurcation that includes poverty trap.

Reference: Earlier studies on disasters effect on economic growth

Divergent views on economic impact of natural disasters Negative long-term impact (e.g. Noy and Nualsri, 2007; Raddatz, 2009)

Greater magnitude of damage in the long term in developing countries

(UNISDR, 2009) The long-term effect of the DRR investments is a question that remains unanswered. We develop the DR2AD model!

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Disaster Risk Reduction Investments Accounts for Development: DR2AD Model • Macroeconomic growth model : national or regional

• Quantitative valuation of the effect of a large-scale disaster

and DRR investments on the dynamic processes of the economy that is consistent with the rational behavior of representative households with an infinite time horizon (Framework of Real Business Cycle model of Neo-classical economics)

• Comparison of DRR benefits among income classes, which finally implies the effect of DRR on the socio-economic equality of the society

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GD

P

without disaster

Disaster Event

With DRR Investment （with disaster）

Without DRR Investment （with disaster）

Time

Sketch of the model: economic growth

Effect of DRR

Gap expanding!

Multiple aspects of effects of DRR

Evaluation on entire economy

- Ramsey-type macroeconomic growth model with subsistence constraint and income distribution

Income

Demographic composition

Evaluation on each income class

Effect of DRR on development of GDP, GRP, capital stock, etc.

Effect of DRR on consumption process of each class, change of poverty rate, Gini coefficient, etc.

Sketch of the model: growth and distribution

Disaster, poverty, and inequality A disaster-triggered poverty trap and human capital investment • Decreased income after disaster

The consumption of households of the lowest income class dropping to the subsistence level. Decrease in saving and investment in human capital Deceleration of income increase and economic growth: Disaster-triggered “Poverty Trap”:

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Disaster and human capital formation • Knowledge and skills stay undamaged. • Provision of labor is temporally decreased because of

morbidity and mortality.

• Negative impact on the educational investments by destroying school buildings and access roads (e.g. Baez et al., 2010; Petal, 2008), increasing child work participation rates that results in the removal of children from schools (e.g. Jacoby et al., 1997; Baez et al., 2007; de Janvry et al., 2006), causing nutritional deficiencies that interrupt continuous learning (e.g. Alderman et al., 2006; Alderman et al., 2009).

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Potentiality of redistributive effect of DRR • Disasters bring more severe damage to lower income

households, resulting in expansion of disparity. Larger benefit of disaster prevention for lower-income people

DRR has the potential to achieve both GDP growth and equality improvement by ensuring educational opportunities (unlike financial vehicles that often attain regressive distribution).

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Characteristics as an economic model • Unique in different disaster responses of the two capital stocks:

physical and human

• Simulation model for a practical use (Cf. IIASA’s CATSIM) based on macroeconomic equilibrium

• General equilibrium framework with rational expectations that is

associated with Pareto efficiency (unlike EnBC models of Hallegatte et al. (2007, 2008) etc.) , implying that further improvements can only be attained through public provisions for DRR infrastructure

DR2AD model figures out the optimal growth path and evaluates the value of DRR investments that is consistent with the normative solution of the economy and therefore regarded as the indicator of significance.

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Model: definition of disaster Vector of the damage rates: 𝑗 : household group (classified by income level) 𝑙 : disaster scale 𝑙 = 0,1,⋯ , 𝐿 𝜇𝑙 : probability of occurrence of scale-l-disaster 𝜔𝑗𝑙: the damage rates of labor 𝜑𝑗𝑙 : physical (household) assets 𝜓𝑙: physical (production) capital 𝜏𝑙: land (as a factor production) Identification of disaster is possible by collaboration with meteorologists and hydrologists!

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𝜔𝑗𝑙 ,𝜑𝑗𝑙 ,𝜓𝑙 , 𝜏𝑙

�𝜇𝑙

𝐿

𝑙=0

= 1

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3) Damage of stocks Financial assets −𝜓𝑙 ∙ 𝑏, Physical assets −𝜑𝑙 ∙ 𝑧, Human capital −𝜔𝑙 ∙ ℎ, Land area −𝜏𝑙 ∙ 𝛵.

Period 𝑡 Period 𝑡 + 1

2) Physical assets investment

Financial assets 𝑏(𝑡), Physical assets 𝑧(𝑡).

5) Update of stocks ℎ(𝑡 + 1), 𝑏−(𝑡 + 1), 𝑧−(𝑡 + 1).

3) Arrival of disaster 𝑙 (𝑙=0,1,･･･,L)

1) Identification of stocks

ℎ(𝑡 + 1), 𝑏−(𝑡 + 1), 𝑧−(𝑡 + 1).

1) Identification of stocks Human capital ℎ(𝑡), Financial assets 𝑏−(𝑡), Physical assets 𝑧−(𝑡).

Time

4) Depreciation of stock Production capital −𝛿𝑘 ∙ �1 −𝜓𝑙�𝑘, Physical assets −𝛿𝑧 ∙ �1 −𝜑𝑙�𝑧.

4) Ex-post decision of households Consumption 𝑐𝑙, Human capital investment 𝑚𝑙, Savings.

4) Determination of product volume 𝐹�𝐵, �1− 𝜔𝑙�𝐻, �1 −𝜓𝑙�𝐾, (1 − 𝜏𝑙)𝑇��.

Event Sequence

Households’ assets and capital • Financial assets, b j(t): Provided to firms

• Physical assets, z j(t): Durable household goods

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capital income

labor income consumption

physical asset investment cost of human

capital investment

physical asset investment

depreciation loss by disaster

b t+1 =w(t)ℎ𝑙(t)+r(t)𝑏𝑙(t)+𝜋𝑙 𝑡 𝑇𝑙 + 1－𝛿𝑘－𝜓𝑙 b t − 𝑐𝑙－ξ − 𝜂𝑙 𝑚𝑙

𝑧 𝑡 + 1 = 1 − 𝛿𝑧 − 𝜑𝑙 𝑧 𝑡 + 𝜉

rent depreciation

loss by disaster

Households’ assets and capital • Total household asset,

• Human capital, ℎ𝑗(t)

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𝑎𝑗 𝑡 : = 𝑏𝑗(𝑡) + 𝑧𝑗(𝑡)

human capital formation in terms of time

Depreciation: obsolescence of knowledge and skill, retirement of workers

ℎ 𝑡 + 1 = (1 − 𝛿ℎ) ∙ ℎ(𝑡) + 𝜄 ∙ 𝑚𝑙(𝑡)

• Stone-Geary Utility function with subsistence constraint

The closer the level of consumption, 𝑐𝑙 to 𝑐̅ , the larger the marginal utility, which results in prioritizing consumption over saving, that finally decelerates the asset formation process and leaves households in poverty trap.

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𝜃：degree of relative risk aversion

Utility Function

consumption physical asset

Subsistence level of consumption

𝑢 𝑐𝑙 , 𝑧𝑙 =𝑐𝑙 − 𝑐̅ 𝛾1 (1 − 𝜑𝑙) ∙ 𝑧 𝛾2 1−𝜃 − 1

1 − 𝜃

𝑉 𝑎,ℎ,𝐵 = max 𝐸 �𝑢(𝑐𝑙(𝑡), (1 − 𝜑𝑙)𝑧(𝑡))1

1 + 𝜌

𝑡∞

𝑡=0

Objection function

Production • Production function

• Exogenous TFP growth

• Ex-post profit

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𝑌 𝑡 = 𝐹 𝐵 𝑡 , 1 − 𝜔𝑙 𝐻 𝑡 , 1 − 𝜓𝑙 𝐾 𝑡 , 1 − 𝜏𝑙 𝑇� , human capital physical capital land TFP

−𝑤𝑙 𝑡 ∙ 1 − 𝜔𝑙 𝐻 𝑡 − 𝑟𝑙 𝑡 + 𝛿𝑘 ∙ 1 − 𝜓𝑙 𝐾 𝑡 .

Π�𝑙 𝑡 = 𝐹 𝐵 𝑡 , 1 − 𝜔𝑙 𝐻 𝑡 , 1 − 𝜓𝑙 𝐾 𝑡 , 1 − 𝜏𝑙 𝑇�

Maximize

𝐵 𝑡 = 𝐵0 ∙ 1 + 𝑔𝑏 𝑡−1

Economic valuation of DRR • Benefit as summation of Willingness-To-Pay for DRR of

each household

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𝑉 𝑎𝑗 𝑡 −𝑊𝑇𝑊𝑗 ,ℎ𝑗 𝑡 ,𝐾 𝑡 ,𝐻 𝑡 ,𝜙𝑗1,𝜓1

= 𝑉 𝑎𝑗 𝑡 ,ℎ𝑗 𝑡 ,𝐾 𝑡 ,𝐻 𝑡 ,𝜙𝑗0,𝜓0

Benefit = �𝑛𝑗 𝑡 𝑊𝑇𝑊𝑗𝑗

For each household,

Damage rates decreased by DRR projects

Damage rates without DRR

For entire society,

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Case Study of Pakistan: Sample path of Large Scale Disasters with Low Frequency

Sample path of the disaster scales, Development of GDP and Gini coefficient

Consumption per capita of each income group

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Physical assets per capita of each income group

Human capital development per capita of each income group

Ratio of GDP with DRR to that without DRR Ratio of Gini coefficient with DRR to that without DRR

Summary • We are developing DR2AD model that simulates

economic growth under disaster risk.

• The model introduces multiple indices of the effects of DRR investment such as the economic benefit, the increase of GDP growth, change in the Gini coefficient.

• With natural scientific results supported by data collection, we obtain the quantitative analysis that is meaningful for policy decision making.

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Present tasks • Find and apply more suitable functions. • Identify better proxy variable for human capital and revise

calibration. • Improve the simulation algorithm. • Deliver as a computer software.

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Expansion in future The DR2AD model should be customized to each country and region by taking its inherent and essential issues into account. E.g. Dual economy and migration between rural and urban

area Trade and capital inflow from oversea Financial commodity like insurance Disaster recovery aid, grant, loan and optimal allocation

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Thank you very much.