Household evacuation decision making and the benefits of improved hurricane forecasting: Developing a framework for assessment

Weather and Forecasting

Volumn 25, Issue 1, 2010, Pages 207-219

  Lazo, Jeffrey K ^a   Waldman, Donald M ^b   Morrow, Betty Hearn ^c   Thacher, Jennifer A ^d  

^a NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^b UNIVERSITY OF COLORADO   (United States)

^c SocResearch Miami   (United States)

^d UNIVERSITY OF NEW MEXICO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ECONOMIC VALUES; FORECAST INFORMATION; HURRICANE FORECASTING; HURRICANE WARNING; IMPROVED FORECAST; NATIONAL WEATHER SERVICES; PRIMARY SOURCES; PUBLIC INVESTMENTS; SURVEY RESEARCH; VALUATION METHODS; WARNING SYSTEMS; WILLINGNESS TO PAY;

DECISION MAKING; ECONOMICS; HURRICANES; INVESTMENTS; RISK ASSESSMENT; SURVEYS;

WEATHER FORECASTING;

CLIMATE PREDICTION; CONTINGENT VALUATION; DECISION MAKING; EARLY WARNING SYSTEM; HURRICANE; RISK ASSESSMENT; WEATHER FORECASTING; WILLINGNESS TO PAY;

EID: 77953604087     PISSN: 08828156     EISSN: None     Source Type: Journal    
DOI: 10.1175/2009WAF2222310.1     Document Type: Article

References (34)

1. Adamowicz, W., P. Boxall, M. Williams, and J. Louviere, 1998: Stated preference approaches for measuring passive use values: Choice experiments and contingent valuation. Amer. J. Agric. Econ., 80, 64-75.
2. Allison, P. D., 1999: Logistic Regression Using the SAS System: Theory and Application. SAS Publishing, 308 pp.
3. Baker, E. J., 1993: Empirical studies of public response to tornado and hurricane warnings in the United States. Prediction and Perception of Natural Hazards, J. Nemec, J. M. Nigg, and F. Siccardi, Eds., Kluwer, 65-74.
4. Ballinger, G. A., 2004: Using generalized estimating equations for longitudinal data analysis. Organ. Res. Methods, 7, 127-150.
5. Ben-Akiva, M., and S. Lerman, 1985: Discrete Choice Analysis: Theory and Application to Travel Demand. The MIT Press, 416 pp.
6. Dash, N., and H. Gladwin, 2007: Evacuation decision making and behavioral responses: Individual and household. Nat. Hazards Rev., 8 (3), 69-77.
7. Dow, K., and S. L. Cutter, 1998: Crying wolf: Repeat responses to hurricane evacuation orders. Coast. Manage., 26, 237-252. EIDS, cited 2008: Miami-Dade County (FL), December 2008. Economic Intelligence Data Service. [Available online at https://edis.commerce.state.nc.us/docs/countyProfile/FL/12086.pdf.]
8. Ericsson, K. A., and H. A. Simon, 1993: Protocol Analysis: Verbal Reports as Data. The MIT Press, 496 pp.
9. Gladwin, C. H., H. Gladwin, and W. G. Peacock, 2001: Modeling hurricane evacuation decisions with ethnographic methods. Int. J. Mass Emergencies Disasters, 19, 117-143.
10. Gladwin, H., and W. G. Peacock, 1997: Warning and evacuation:A night for hard houses. Hurricane Andrew: Ethnicity, Gender and the Sociology of Disasters, W. G. Peacock, B. H. Morrow, and H. Gladwin, Eds., Routledge, 52-74.
11. Gladwin, H., J.K. Lazo, B. Morrow, W. G. Peacock, and H. E. Willoughby, 2007: Social science research needs for the hurricane forecast and warning system. Nat. Hazards Rev., 8 (3), 87-95.
12. Gladwin, H., J.K. Lazo, B. Morrow, W. G. Peacock, and H. E. Willoughby, 2009: Social science research needs for the hurricane forecast and warning system. Bull. Amer. Meteor. Soc., 90, 25-29.
13. Greene, W. H., 2003: Econometric Analysis. 5th ed. Prentice-Hall, 806 pp.
14. Huber, J., and K. Zwerina, 1996: The importance of utility balance in efficient choice designs. J. Marketing Res., 33, 307-317.
15. Kuhfeld, W. F., 2005: Marketing research methods in SAS: Experimental design, choice, conjoint, and graphical techniques. SAS Institute TS-722, 49 pp.
16. Lazo, J. K., 2002: Assessment of total household benefits of improved hurricane forecasting: First interim report. SC10111, Stratus Consulting Inc., Boulder, CO, 213 pp.
17. Lazo, J. K., 2004: Draft summary on Miami one-on-one cognitive interviews-Hurricane forecast valuation study. Societal Impacts Program, National Center for Atmospheric Research, 24 pp.
18. Letson, D., D. Sutter, and J. K. Lazo, 2007: The economic value of hurricane forecasts: An overview and research needs. Nat. Hazards Rev., 8 (3), 78-86.
19. Lindell, M. K., and C. S. Prater, 2007: Critical behavioral assumptions in evacuation time estimate analysis for private vehicles: Examples from hurricane research and planning. J. Urban Planning Development, 133, 18-29.
20. Louviere, J. J., D. A. Hensher, and J. D. Swait, 2001: Stated Choice Methods: Analysis and Application. Cambridge University Press, 418 pp.
21. Manski, C., 1977: The structure of random utility models. Theory Decision, 8, 229-254.
22. McFadden, D., 1976: The revealed preferences of a government bureaucracy: Empirical evidence. Bell J. Econ. Manage. Sci., 7, 55-72.
23. Morrow, B. H., 2009: Risk behavior and risk communication: Synthesis and expert interviews. SocResearch Rep. for NOAA/Coastal Services Center. [Available online at http://www.csc.noaa.gov/Risk_Behavior_&_Communication_Report.pdf.]
24. Morrow, B. H., and H. Gladwin, 2005: Hurricane Ivan Behavioral Analysis. Report prepared for FEMA and U.S. Army Corps of Engineers, 66 pp. [Available online at http://chps.sam.usace.army.mil/USHESDATA/Assessments/2004Storms/PDFfiles/Ivan%20Final%20Behave%20download.pdf.]
25. NOAA, cited 2008: Proposed framework for addressing the National Hurricane Research and Forecast Improvement Initiatives: NOAA's Hurricane Forecast Improvement Project. [Available online at http://www.nrc.noaa.gov/plans_docs/HFIP_Plan_073108.pdf.]
26. O'Connell, A. A., 2005: Logistic Regression Models for Ordinal Response Variables. Sage Publications, 120 pp.
27. Phillips, B. D., and B. H. Morrow, 2007: Social science research needs: Focus on vulnerable populations, forecasting, and warnings. Nat. Hazards Rev., 8 (3), 61-68.
28. Savage, S., and D. M. Waldman, 2008: Learning and fatigue during choice experiments: A comparison of online and mail survey modes. J. Appl. Econ., 23, 351-371.
29. U.S. Department of Housing and Urban Development-U.S. Department of Commerce, 2003: American housing survey for the Miami-Ft. Lauderdale metropolitan area: 2002. Current Housing Reports, Series H170/02-28, U.S. Census Bureau, 232 pp. 1 appendixes. [Available online at http://www.census.gov/prod/2003pubs/h170-02-28.pdf.]
30. Whitehead, J. C., 2005: Environmental risk and averting behavior: Predictive validity of jointly estimated revealed and stated behavior data. J. Environ. Resource Econ., 32, 301-316.
31. Whitehead, J. C., B. Edwards, M. Van Willigen, J. R. Maiolo, K. Wilson, and K. T. Smith, 2000: Heading for higher ground: Factors affecting real and hypothetical hurricane evacuation behavior. Environ. Hazards, 2, 133-142.
32. Willoughby, H. E., 2002: Improvements in observations, models and forecasts. HURRICANE! Coping with Disaster, R. H. Simpson, R. A. Anthes, and M. Garstang, Eds., Amer. Geophys. Union, 205-216.
33. Yin, R., and D. H. Newman, 1999: An intervention analysis of Hurricane Hugo's price effect in South Carolina. Can. J. For. Res., 29, 779-786.
34. Zhang, F., and Coauthors, 2007: An in-person survey investigating public perceptions of and response to Hurricane Rita forecasts along the Texas coast. Wea. Forecasting, 22, 1177-1190.