Distributional effects of floods and flood policies: Microeconomic evidence from Germany

11:15 Tuesday 28 May

OC019

Room S11

 

Miguel Tovar Reanos (Germany) 1; Daniel Osberghaus (Germany) 1

1 - Centre for European Economic Research (ZEW)

Objectives

In recent years, floods caused significant economic damage in Germany. As insurance penetration is low, the government has repeatedly bailed out affected households by tax-funded compensation schemes. Against this background, we analyse the expected effects of flooding on total welfare and inequality in Germany. Furthermore, we estimate welfare and inequality effects of different government programs such as flood insurance subsidies, damage compensation funded by income tax, and compensation funded by energy taxes, following the ‘polluter pays’ principle. This is the first study attempting to analyse welfare effects of floods and flood policies on a national level.

Methods

Welfare and inequality analyses are based on a microeconomic demand system model, the exact affine Stone index model. The model, which is consistent with economic theory, estimates budget shares for consumption goods and derives measures of household welfare. The underlying data set (EVS – ‘income and consumption sample’) contributes detailed consumption and expenditure data of 26,000 households in Germany. As relevant variables related to flooding are missing in the EVS, we impute flood risk, insurance, mitigation and other relevant parameters from another survey, the Eval-MAP household panel. Eval-MAP covers more than 10,000 households in the period of 2012 to 2015. We estimate probabilities of being insured, objective flood risk, etc. for well-defined household types in the Eval-MAP data, and transfer these probabilities to the same household types in the EVS dataset. This allows us to estimate an expected flood damage for the households in the EVS sample and ultimately derive welfare changes due to flooding and flood policies.

Results and conclusions

High-income households tend to be flood insured, to mitigate, and to reside in relatively safe areas. Hence, they have a relatively high adaptive capacity. On the other side, they are more flood-sensible, due to larger dwelling sizes and home ownership. In sum, expected flood damage measured in € per year, increases with income levels. In relative terms, however, poorer households face flood damages amounting to much higher shares of income. This implies that floods have a slightly regressive effect on the income distribution in Germany. Tax-funded compensation schemes reduce this regressive effect, and can even reduce inequality compared to the pre-flood situation – hence they have a progressive effect. Subsidies for the purchase of insurance is no cost-effective policy as the demand for insurance is found to be inelastic, hence a significant amount of resources would be needed to stimulate substantial demand.