Implications of rising flood-risk for employment location: a GMM spatial model with agglomeration and endogenous house price effects

被引:7
|
作者
Chen, Yu [1 ]
Fingleton, Bernard [2 ]
Pryce, Gwilym [3 ]
Chen, Albert S. [4 ]
Djordjevic, Slobodan [4 ]
机构
[1] Univ Sheffield, Sch East Asian Studies, Sheffield, S Yorkshire, England
[2] Univ Cambridge, Dept Land Econ, Cambridge, England
[3] Univ Glasgow, Sch Social & Polit Sci, Urban Studies, Glasgow, Lanark, Scotland
[4] Univ Exeter, Coll Engn Math & Phys Sci, Exeter, Devon, England
基金
英国工程与自然科学研究理事会;
关键词
house prices; employment; firm location; agglomeration; flood-risk; climate change; insurance;
D O I
10.1080/09599916.2013.765499
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
The impact of flood-risk on local employment has been almost entirely neglected in the empirical urban economics literature. This omission is particularly anomalous in the context of climate change. We extend the literature in four ways. First, we argue that competition for land between firms and households will generate an endogenous role for house prices, which we estimate using a generalised method of moments two-stage least squares spatial econometric model. Second, we model interaction effects between agglomeration and flood-risk using a gravity-based agglomeration measure. Third, we utilise a high-resolution flood-risk measure which incorporates both flood frequency and severity. Fourth, we use a high-resolution measure of employment to capture local effects. We find that agglomeration economies have a significant mitigating effect on flood-risk. This is potentially important because it suggests that flood-risk may have a more deleterious effect on employment in areas where economic agglomeration is weak. Policy-makers, insurers and planners cannot, therefore, assume a uniform effect of future changes to flood-risk as a result of climate change, and this needs to be taken into account when estimating the costs and benefits of interventions to reduce or underwrite flood-risk at particular locations. Our model offers a robust methodological basis for such estimation.
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页码:298 / 323
页数:26
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