Is Flood Risk Capitalised in Property Values? A Meta-Analysis Approach from the Housing Market

1. Introduction Theory Meta-analysis Meta-regression analysis Publication bias Is Flood Risk Capitalised in Property Values? A Meta-Analysis Approach from the Housing Market Allan Beltran, David Maddison, Robert Elliott • Allan Beltran • University of Birmingham • Department of Economics • aib902@bham.ac.uk Meta-Analysis of Economics Research Network 8th annual Colloquium University of Athens, Greece September 11th – 13th , 2014.

2. Introduction • Introduction: • Floods are the leading cause of natural disaster deaths worldwide (CRED, 2012). • Globally economic losses from flooding exceeded $19 billion in 2012 (Munich Re, 2013). • The frequency of floods have risen rapidly and will continue as consequence of climate change (IPCC, 2012; UNISDR, 2011; Visser et al., 2012). • Estimated losses by 2050 are expected to exceed $1 trillion annually (The World Bank, 2013). • Flood risk is now a significant policy issue. • What are the benefits of flood risk reduction? HousingMarket (Why?) Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

3. Theory • Theory: • Rational consumer will choose to live in a location which maximizes his expected utility. • Are individuals willing to accept the risk? • Flood risk is capitalized in property values. • To what extent is flood risk capitalized in property prices? Hedonic Price Model Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

4. Theory • Hedonic Price Function (HPF): • where: • Individual’s Utility Function: • where: and: • Maximizing (1) with respect to ; s.t. homeowner’s budget yields: (1) Implicitprice of floodrisk Estimateit ! Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

5. Meta-analysis • Evidence: • 37 studies, 349 Point estimates (1987 - 2013) • -75 – 61 % • 70% Negative, 30% Positive Meta-analysis To what extent is flood risk capitalized in property prices? Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

6. Meta-analysis 1. Define the theoretical relationship of interest • Different proxy of flood risk: • Elevation (Barnard, 1978) • Flood depth (Tobin and Montz, 1994) • Flood insurance cost (Shilling, Benjamin and Sirmans, 1985; Speyrer and Ragas, 1991) • Dummy variable for floodplain location (100 and 500-year floodplain) • Effect size: relative price differential for floodplain location. • Different type of econometric approach: • Standard hedonic price models (what is the implicit price of risk?) • DND hedonic price models (does the implicit price of risk increases after a flood?) Standard hedonic DND hedonic DND hedonic + changes in FR perception P P P Functionalform? Bin and Landry (2013) Atreya, Ferreira and Kriesel (2013) NR NR NR RA RA RA URA URA decay T T T MacDonald, Murdoch and White (1987) Bin and Polasky (2004) Atreya and Ferreira (2011) F1 F1 Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

7. Meta-analysis 2. Collect the population of studies that provides data on the relationship • Systematic literature review. • Comprehensive computer search of relevant databases and careful study of references. • (Flood* OR Hurricane* OR Inundat*) AND (Propert* OR Resident* OR Hous* OR "Real Estate")  • Update of the literature review on May 2014. Chronological summary of literature review Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

8. Meta-analysis Rules for inclusion: Use of Hedonic Price Model: standard or DND. Estimate can be expressed as a percentage of average price of house. Proxy of flood risk: dummy variable indicating location at either 100-year or 500-year floodplain. Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

9. Meta-analysis 3. Code the studies and compute the effect sizes Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

10. Meta-analysis 4. Examine the distribution of effect sizes and analyse the impact of moderator variables Different levels of risk 100-year floodplain 500-year floodplain Different type of risk River flood risk Coastal flood risk Effectsizes: 100 and 500-year floodplain Effectsizes: River and Coastalfloodrisk Flood risk is correlated with proximity to water. Proximity to water is also closely related to the existence of amenity values. Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

11. Meta-analysis • Meta-analysis: Weights according to the sample size (divided by the number of point estimates each primary study contributes to the meta-sample). Notes: 1 H0: the summary effect size is not statistically different from zero. 2 H0: all studies in the sample share a common effect size. *, ** and *** means rejection of the null hypothesis at the 90%, 95% and 99% confidence level. BF= Before flood event, AF= After flood event. What is driving the heterogeneity in effect sizes? Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

12. Meta-analysis • Conclusions • Overall significant discount around 2.7% [-3.2% - 2.2%] • Coastal regions: more research is needed. • → Especial attention should be devoted to the issue of endogeneity. • River regions: • → Evidence supports the widespread idea that the occurrence of floods provides new . . . . information to homeowners to update their flood risk perception. • → Before: 100-year 3% → After: 100-year 7% (-4%) • 500-year 0% 500-year 6% (-6%) • → Pre-flood information available appears to play a role in the extent of the update. • There is a great deal of dispersion in these results which deserves further research. Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

13. Meta-regressionanalysis Meta-regression analysis The Model: (weights) 6 groups of moderator variables. Total of 18 variables + regional fixed effects. Flood risk perception. (Difference in perception along time) Flood risk level. (100-year or 500-year floodplain) Context of primary study. (Region, income, size of house, etc.) Control variables included in primary studies. (Control for amenity values? Inflation?) Characteristics of econometric model. (Functional form, type of hedonic model) Characteristics of primary study. (Quality, sample year) Regional fixed effects. (US States, UK, NL, AUS, NZ) Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

14. Meta-regressionanalysis • Regression results • 4 different functional forms of the time variable (Atreya, Ferreira and Kriesel, 2013). • Linear: • Natural logarithm: • Ratio: • Square root: • 5 different regressions: • Full sample (349 observations) • River flood risk (314 observations) • Coastal flood risk (35 observations) • Standard hedonic models (138 observations) • DND hedonic models (211 observations) Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

15. Meta-regressionanalysis Full sample Note: 1 The omitted region is Georgia, US. The dependent variable is the effect size . Standard errors in parenthesis; for results using sample size weights they correspond to Huber-White robust standard errors. *, ** and *** means rejection of the null hypothesis at the 90%, 95% and 99% confidence level Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

16. Meta-regressionanalysis Riverfloodrisk Standard hedonicmodels DND hedonicmodels Coastalfloodrisk No significantresults. Only 35 observations. Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

17. Meta-regressionanalysis • What is the persistence of the post-flood price discount? • Only two major flood events: • 1994 Tropical storm Alberto, Doughtery County, Georgia. (worst disaster to ever hit southwest Georgia) • 1999 Hurricane Floyd, Pitt County, North Carolina. (worst modern disaster in North Carolina by 1999) Post flood discount: 100-year: 15 – 56% 500-year: 20 – 37% Persistence: 100-year: 8 – 14 years 500-years: 7 – 11 years Post flood discount: 100-year: 38 – 57% 500-year: No significant Persistence: 100-year: 8 – 10 years Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

18. Meta-regressionanalysis • What is the persistence of the post-flood price discount? • From meta-analysis: • Post-flood price differential for floodplain location: • 100-year: 6.9% • 500-year: 5.9% Persistence of the post-flood discount: 100-year: 9 – 17 years 500-year: 1 – 3 years Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

19. Meta-regressionanalysis • Decay path Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

20. Meta-regressionanalysis • Conclusions • In all cases the coefficients support the idea that the price differential for floodplain location vanishes as the time with respect to the previous flood increases. (flood risk perception) • → This is true across areas with different level of risk. • → The effect is more persistent in areas exposed to more frequent and more intense flooding. (100-year floodplain) • → Evidence suggests that the square root functional form of the time variable is the one that better fits the data. • → The average post-flood discount vanishes in: 9 – 17 years in 100-year floodplain • 1 – 3 years in 500-year floodplain • Regional differences are also highly significant. (different flooding history) • After controlling for differences in flood risk perception along time and across regions, differences in the level of risk are not significant. (problem with proxy of flood risk?) • Kuminoff and Pope (2012) and Klaiber and Smith (2013): How to interpret the evidence of DND models? Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

21. Publicationbias • Graphical examination • Type I publication bias: Tendency to report/publish negative impacts of flood risk on property prices. • No clear evidence of Type II publication bias. Funnel plot Galbraith plot However: • Studies with more than one observation are overrepresented. • Visual interpretation is subjective. Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

22. Publicationbias Egger regression Note: Standard errors in parenthesis correspond to Huber-White robust standard errors. The number in brackets correspond to the p-value for the one-tail t-test. *, ** and *** means rejection of the null hypothesis at the 90%, 95% and 99% confidence level • Conclusions: • Publication bias in the flood risk literature: • Tendency to under-report positive coefficients for the implicit price of flood risk in: • 500-year floodplains and coastal regions • Evidence suggests there is a significant empirical effect of flood risk on property prices beyond publication bias. Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

23. Meta-regressionanalysis • Areas of further research • Geographical scope of the studies. (outside the US) • Coastal flood risk. Especial attention the issue of endogeneity. • Flood risk perception vs objective flood risk (spatially delineated risk) • To what extent is objective risk perceived? • Are reductions in objective risk perceived and capitalised in property prices? Is Flood Risk Capitalised in Property Values? A Meta-analysis Approach from the Housing Market

24. Introduction Theory Meta-analysis Meta-regression analysis Publication bias Is Flood Risk Capitalised in Property Values? A Meta-Analysis Approach from the Housing Market Allan Beltran, David Maddison, Robert Elliott THANK YOU!! Allan Beltran University of Birmingham Department of Economics aib902@bham.ac.uk

25. Description of the variables Exploring Difference in the Implicit Price of Flood Risk: A Meta-Analysis Approach from the Housing Market

26. Summary statistics Exploring Difference in the Implicit Price of Flood Risk: A Meta-Analysis Approach from the Housing Market

27. Introduction Motivation Literature Review Research Proposal Different type and different level of risk Coastal flooding River flooding • Why?Bin and Kruse (2006) • Differenteconometricmodels. Bin and Polasky (2004) Allan Beltran Estimating the Economic Benefits of Flood Risk Reduction

28. Introduction Motivation Literature Review Research Proposal Difference in difference models: Different type and different level of risk Coastal Why? Bin and Kruse (2006) Why? Information Kousky (2010) Atreya and Ferreira (2011) Why? Lamond and Proverbs (2006) River ? Atreya and Ferreira (2011) Atreya and Ferreira (2012a) Atreya and Ferreira (2012b) Atreya, Ferreira and Kriesel (2012) Standard HedonicModels? Atreya and Ferreira (2012) Bin and Landry (2013) Allan Beltran Estimating the Economic Benefits of Flood Risk Reduction

29. Introduction Motivation Literature Review Research Proposal Standard hedonic models : Different type and different level of risk Coastal ? Kousky (2010)? River Allan Beltran Estimating the Economic Benefits of Flood Risk Reduction