EWE Socio-Economic Model(Winner of the ERES JPR Best Paper Prize in Real Estate Economics 2011)

Estimate the impact on society of anticipated increases in the frequency & severity of floods:

• Impact on a range of sectors - house prices, employment, deprivation

• Grounded in empirical evidence from past EWEs• Updatable as more evidence becomes available• Incorporate potential spatial-spillovers and interactions

between sectors

The socio-economic consequences of EWE’s

Prof. G.Pryce Dr Y.Chen University of Glasgow

Downscaled Climate Change & Flood Risk Estimates

EWESEM Model

(Based on impact of

past floods & risk)

Simulate Socio-Economic

Impacts for Case Study Area

Digimap terrain, SWERVE 2008

Stakeholder Engagement

(PP2)

+

Web Interface

(WISP)

From SWERVE

… a pioneering joined-up approach

Hypothetical House Price Surface Post-Flood (t=2) with Spatial Effects

Parameter on spatial lag 1 = 0.3; Parameter on spatial lag 2 = 0.2; Flood impact parameter = 0.1

Local Effects of Global Climate Change

• Local implies an interest in the spatial– Existing approaches tend to be non-spatial

macro models or GIS layering• Important, but what will the market

response to flood risk be?– How will employment change?– How will house prices change?

• Current socio-economic geography could be transformed by shifts in the pattern of flood risk as climate changes – What will the future socio-econ geography be?

Hypothetical House Price Surface Post-Flood (t=2) with Spatial Effects

Parameter on spatial lag 1 = 0.3; Parameter on spatial lag 2 = 0.2; Flood impact parameter = 0.1

• House prices important:– Measure of wellbeing– Major source of collateral for lenders– Major source of saving for retirement– Sorting effects

• Employment important:– Generates HH income & local tax

revenue– Agglomeration effects:

• Firms locate near other firms• Virtuous circles and downward spirals

Inte

ract

ion

Existing Evidence?

Good news and bad news…

Major Problems & Omissions:

(i) Measurement of Flood Risk

(ii) Spatial Scale of Employment

(iii) Agglomeration Effects

(iv) Feedback effects from house prices

Inertia & Bounce-Backs:

(i) Measuring Flood Risk• Employment Models: none consider flood risk effect

– Only consider particular flood events– But what about long run impact of flood risk?

• Single event may be seen as a one-off event• Different prospect entirely if flood risk set to rise inexorably…

• Housing Models: tend to use crude flood-plain categorisation– But in reality flooding tends to be highly spatially specific– Risk not just about frequency: = f(severity, frequency)– Flood risk not just about fluvial floods: pluvial flooding a major concern.

• Climate Change Need to simulate of future flood impacts– Currently, no robust statistical models of either employment or housing that

simulate future increases in flood risk at the local level.

(ii) Spatial Scale

• Previous studies tend to look at regional employment effects– Confuses wider benefits of investment from

remediation & repair following a particular flood event with long term effects of flood risk• Fails to distinguish between impact on the specific

locality worst affected and the wider economic impact.

– Really need fine-grained employment data.

(iii) Agglomeration Effects

• If firms are repelled by flood risk – then we might conclude that those areas

predicted to have increases in flood risk will gradually lose employment over time, other things being equal.

• A critical qualifying factor, however, is the extent to which agglomeration economies mitigate these effects. – A big unknown in the literature on the socio-

economic modelling of the effect of flood risk

(iv) Feedback Effects

• No existing employment model of flood risk allows for endogenous house price effects Flood risk

Land Price Employment

We take advantage of recent developments in spatial econometric modelling to estimate a variety of 2SLS spatial models…

Advances by CREW/EWESEM:• (i) Measurement of Flood Risk

– High-resolution CREW estimates of pluvial flood risk, incorporates severity, & allows future projections.

• (ii) Spatial Scale of Employment– Lower super output areas, location and

number employed• (iii) Agglomeration Effects

– (a) Distance decay gravity function plus lagged spatial effects

– (b) Spatially Lagged Employment.• (iv) Endogenous house price effects

Key Findings• Statistically significant negative impacts on

employment location as a result of flood risk– Sensitivity to flood risk likely to increase over time due to:

• improvements flood risk communication • Changes in insurance & mortgage risk premiums

• Significant mitigating effects from agglomeration– agglomeration economies mitigate the effect of flood risk on

employment location

Important Implications• Flood risk may have a more deleterious effect

on employment in areas where economic agglomeration is weak. – cannot assume a uniform effect of future changes

to flood risk as a result of climate change. • Two areas could experience identical increases in flood

risk but very different economic consequences because agglomeration economies are different.

Important Implications

• Complicates considerably the calculations for comparing the relative costs and benefits of flood defense interventions across different locations – agglomeration effects need to be taken into

account

• House price impacts also affected by feedback effects from employment and deprivation– Potentially important

issues for housing wealth, equity withdrawal, mortgage default, council tax revenues etc.

Flood Risk

Local House Prices

Deprivation

Jobs

Important Implications