Similar documents

Development and Recovering From Disaster

Long-term Recovery from Recent Disasters in Japan and the United States

ADDITIONAL RESOURCES. Duration of resource: 24 Minutes. Year of Production: Stock code: VEA12059

Date, Time and Place: Presented by: Presented to: 22 August 2013, 0900 hrs, Pier 1 The Embarcadero, San Francisco

Flood Management in Japan

Project Management Capacity Building for Planning and Implementing for Tsunami Development Projects in Sri Lanka

A trusted partner to insurance adjusters. Fast, accurate, claims solutions 24 hours a day, 365 days a year.

The Economic Impact of Fire Damage on Wyoming s Economy from a Business Perspective

Sustainable Recovery and Reconstruction Framework (SURRF)

Learning from Disaster Recovery Ian Davis Visiting Professor, Cranfield, Coventry and Kyoto Universities

Pacific Catastrophe Risk Assessment and Financing Initiative. Better Information for Smarter Investments

5-2. Dissemination of Earthquake Risk Reduction and Recovery Preparedness Model Programme

Catastrophe risk and the cost of real estate insurance

The Economists Voice

CHAPTER 7. EMERGENCY SERVICES

EMERGENCY-RESPONSE CAPACITY OF LIFELINES AFTER WIDE-AREA EARTHQUAKE DISASTERS

PLANNING FOR DISASTER DEBRIS MANAGEMENT

Session 7a Life Insurance Product Trends in Japan. Tom Burke

Faced with the Great Eastern Japan Earthquake Disaster What can the Japanese Association of Rehabilitation Medicine (JARM) do?

PACIFIC CATASTROPHE RISK ASSESSMENT AND FINANCING INITIATIVE

HYOGO PREFECTURE. Hyogo Prefectural Government

Storms Assessment LESSON

Earthquake Risk Modelling. Dr. Dirk Hollnack GeoRisks Research Group Munich Reinsurance Company

Long Term Recovery and Rehabilitation. Issues for discussion. Recovery

Draft 8/1/05 SYSTEM First Rev. 8/9/05 2 nd Rev. 8/30/05 EMERGENCY OPERATIONS PLAN

Presentation Notes for the 41 st Annual AIFA Conference

WATER QUALITY AND STANDARDS Vol. I -Management of Water Supplies After A Disaster - Yasumoto Magara, Hiroshi Yano

13.8% Inflation-adjusted GDP (billions) Cumulative growth 2009 to Q Exhibit 1 Steady U.S. Economic Growth After a Severe Recession $17,000

INSURANCE AND REINSURANCE ISSUES ARISING OUT OF NATURAL CATASTROPHES

HEALTH INFORMATION MANAGEMENT In Emergency

The 2014 International Training Workshop on Natural Disaster Reduction

Natural Disaster Impact on Business and Communities in Taiwan. Dr. Chung-Sheng Lee. NCDR Chinese Taipei

Guidelines for Conducting a Special Needs

Market Analysis for Padre Boulevard Initiative in the Town of South Padre Island, TX

THE SEARCH FOR T RENDS IN A GLOBAL CATALOGUE

Post-Disaster Recovery: Restoring Economic Growth through Urban Redevelopment

Naoki Ikegami, MD, MA, PhD Professor & Chair Dept. of Health Policy & Management Keio University, Tokyo nikegami@a5.keio.jp

Is Your Port Prepared to Recover from a Disaster? Can you keep the cash register ringing when bad things happen?

Chapter 7: Japan s humanitarian assistance

The Japan Society of Mechanical Engineers C 2010

Categorizing Smart cities and Big data foci of Japan

The Realities of Disaster Recovery: How the Japan Data Center Council is Successfully Operating in the Aftermath of the Earthquake

Summer Disaster Institute. PLAN 740 Disaster Recovery: Concepts, Policies and Approaches. Overview

Hurricane Sandy: The Challenges and Opportunities to Link Disaster Management and Climate Change Adaptation*

ASSOCIATION OF CARIBBEAN STATES (ACS) 19th MEETING OF THE SPECIAL COMMITTEE FOR DISASTER RISK REDUCTION. Bogotá, Colombia, August

The Impact of an Earthquake in Canada

Niigata as a temporary water works relay base: support for teams in a major seismic disaster

Earthquake Disaster Recovery Plan in TMG

Natural Disasters and Plant Survival: The Impact of the Kobe Earthquake

Inter cloud computing: Use cases and requirements lessons learned 3.11

Progress of Collaboration in Disaster Preparedness for Cultural Properties after the Great East Japan Earthquake

Together We Are The CSI Group, LLC (4CSI)

California s Construction Cost Outlook

ENGINEERING-BASED EARTHQUAKE RISK MANAGEMENT

Response, Recovery, and Resilience

GAO DISASTER RECOVERY. Experiences from Past Disasters Offer Insights for Effective Collaboration after Catastrophic Events

Peace of mind that no earthquake can shake.

Superstorm Sandy. Lessons learned: A risk management perspective. Risk Bulletin

Third United Nations World Conference on Disaster Risk Reduction Working Session 2: Risk Identification and Assessment. Speakers

How To Get A Home Insurance Policy On The Gulf Coast

Transcription:

Long-Term Recovery After a Disaster: International Comparisons Ilan Noy EQC-MPI Chair in the Economics of Disasters Professor of Economics Victoria Business School

The build-back back-better better tale

The Vision At CDC we remain fully focused on our vision that in 2031 Christchurch is recognised as the best place for business, work, study and living in Australasia. Tom Hooper, CEO, Canterbury Development Corporation (from the Canterbury Report, Autumn 2014, p. 3)

Good comparisons? Galveston, TX 1900 San Francisco 1906 Messina 1908 Tokyo 1923 Kobe 1995 New Orleans 2005 Smaller places? (Napier?)

Kobe: What Happened?

Kobe s decline (per capita income) 4.5 4 3.5 3 2.5 Hyogo Synthetic Hyogo 2 1.5 1 1976 1981 1986 1991 1996 2001 2006

Looking at Kobe s wards and towns Example results: Population for Nishinomiya 1.2 115 1.15 1.1 105 1.05 1 095 0.95 0.9 Synthetic Nishinomiya 0.85 0.8 1980 1985 1990 1995 2000 2005 2010

Kobe: Population (% deviations from synthetic counterfactual)

Kobe: Taxable Income (% deviations from synthetic counterfactual)

Kobe: Unemployed (% deviations from synthetic counterfactual)

Conclusions about Kobe s EQ impact Long ong-run negative impact on Kobe s economy Population and income are all below the counterfactual, while the number of unemployed is above. This varies by Wards: The central and most devastated wards were negatively affected. Those less devastated, or near Osaka were not affected, or even benefited. This despite of a massive government investment and a quick reconstruction period.

Other cases? Dustbowl Katrina Hilo tsunami Man made events?

What s happening in Canterbury?

Any warning signs?

The cost of rebuilding %GDP %GDP 2.0 June 2011 1.8 Dec 2011 1.6 June 2012 1.4 Dec 2012 12 1.2 June 2013 1.0 0.8 0.6 0.4 0.2 0.0 10 11 12 13 14 15 16 2.0 1.8 1.6 1.4 12 1.2 1.0 0.8 0.6 0.4 0.2 0.0

Insurance

Legal Complications

Population - Canterbury Females Males -4,000-3,000-2,000-1,000 0 1,000 2,000 3,000 4,000 5,000

Business migration - Canterbury

More recent warning signs? The commercial rebuilding in the CBD area has slowed down recently. Volume of building consents is increasing, but fairly slowly. Residential housing pressures are mounting. Very low unemployment rate without corresponding increase in migration. University in trouble.

Why hurry? What can prevent a bad outcome? Speed Post-reconstruction employment A functioning CBD What can speed up the rebuild? Insurance The courts

Central vs. Local Gov t

The bigger picture? Cavallo et al. (2013): No long-run adverse impact of catastrophic natural disasters on national GDP. Do we care about Christchurch? h h?

Two more observations

MY BIBLIOGRAPHY Cavallo & Noy (2011). Natural disasters and the economy A Survey. International Review of Environmental and Resource Economics. Cavallo, Galiani, Noy & Pantano (2013). Catastrophic Natural Disasters and Economic Growth. Review of Economics and Statistics. Coffman & Noy (2012). Hurricane Iniki: Measuring the Long-Term Economic Impact of a Natural Disaster Using Synthetic Control. Environment and Development Economics. dupont, Yokohama, Noy, & Sawada (2014). The (Non) Recovery of Kobe. Working paper. dupont & Noy (2014). What happened to Kobe? A reassessment of the impact of the 1995 earthquake. Economic Development and Cultural l Change. Lynham, Noy & Page (2013). The 1960 Tsunami in Hawaii: Long Term Consequences of a Coastal Disaster. Working gpaper. p

THANK YOU

The synthetic counterfactual Model: Suppose there is a set of optimal weights(ŵ (w 2,...,ŵ,...,w J 1 1 ) such that J 1 1 wy ˆ 2 j jt Y1 t, t {1, 2,..., T0} j and J 1 wˆ j 2 jz j Z 1

The synthetic counterfactual Model: Then (as shown by Abadie et al. (2010) ): Y J 1 N ˆ 1t jyjt j 2 This suggests using: ˆ as an estimator for J 1 ˆ Y 1t 1 t w j Y 2 j jt 1t

Data City/Town/Ward data for 1980-2010 System of Social and Demographic Statistics of Japan Census Geospatial Information Authority of Japan Ministry of Economy o Trade and Industry Ministry of Internal Affairs and Communications Minis