Lab Simulation Studies of Response to Natural Hazards

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Lab Simulation Studies of Response to Natural
Hazards

• Robert Meyer
• Wharton Center for Risk and Decision Processes

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• September, 2004 Category-4 Hurricane Ivan
  threatens New Orleans

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Mayor Nagin said he would "aggressively
recommend" people evacuate, but that it would be
difficult to order them to, because at least
100,000 in the city rely on public transportation
and have no way to leave. Despite the potential
need for emergency housing, no shelters had been
opened in the city as of Tuesday night. Nagin
said the city was working on setting up a shelter
of "last resort" and added that the Superdome
might be used, but a spokesman for the stadium
said earlier Tuesday that it was not equipped as
a shelter.
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Good News the storm never hits.

• Q What did New Orleans and FEMA conclude from
  this close call with Ivan?
• a) That the city was fortunate to have averted a
  catastrophe, hence immediate steps should be
  taken to remedy the evacuation problems
• b) The city would be safe for another 40 years
• c) The city is inherently lucky
• d) Actions should be taken, but since the next
  hurricane season is months off, whats the hurry?

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Hurricane Katrina, 2005
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Thena month later

• Houston Braces for Hurricane Rita

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This time, a prepared city

• 1.5 million Texans in Galveston/Houston ordered
  to evacuate via a careful staged plan developed
  and refined in the 80s.

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Unexpected problem 2.8 million, not 1.5 million,
try to leave.

• Result a human catastrophe worse than the storm

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Why do we have such a hard time learning?

• Problem with real-world analyses Natural hazards
  occur with in sufficient frequency to allow
• longitudinal panel analysis
• Control that would allow one to tease apart
  alternative explanations for apparent mitigation
  errors

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Example Hurricane Wilma

• October 2006 For the sixth time in 2 years
  Hurricane warnings were posted in extreme South
  Florida
• Public awareness of storms and basic preparations
  could not be higher (e.g., the need to stock up
  on gas and water)
• Q How prepared were residents?

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The answer
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The Multitude of Explanations

• People underestimated the odds that the storm
  would actually hit
• People figured the government would bail them out
  if things got bad
• Lack of knowledge, lack of funds
• Recent near-misses taught them that storms are
  quite survivable without preparations

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The Hurricane Simulation

• Respondents were endowed with a residence of
  known value, and were paid at the end of the
  simulation the difference between this endowment
  and the cost of mitigation and storm repairs.
  Mitigation measures do not improve the value of
  the home--they only reduce storm losses.
• At the start respondents are told their expected
  length of tenure in the home and its location
• Respondents can gather information about
  hurricanes, mitigation, and make mitigation
  purchases by clicking control buttons in the
  simulation

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The Optimal Policy

• In almost all cases its all or nothing
• Learning should have been easy
• Ss could make decisions up the last second
• Ss were given full-information about what would
  have happened had they not invested in protection

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The result like in the real world, subjects
under-invested in mitigation, and investments
were cyclical
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The Learning Process

• In the absence of an unambiguous correct course
  of action, mitigation decisions were driven by
  short-run negative feedback.
• The lack of damage at time t caused a reduction
  in mitigation in time t1even when the cause of
  reduced damage was investments in mitigation!
• In time these lag-damage effects vanished and
  investments reached an equilibriumbut well below
  optimum.

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Other research

• Community effectsdoes living with and observing
  others naturally improve mitigation decisions
  (answer no)
• Third-party decisionswhat happens when one is
  making decisions for others (the FEMA game
  answer even lower mitigation investments)
• The dynamics of information search in advance
  (and after) hurricanes
• Hurricane Katrina case study
• Hourly web-surfing habits of 65,000 residents of
  Fla, La, and Miss in August, 2005