Commuting patterns of Czech households exposed to flood risk from the Bečva river
Bibliographic Data
| ID | 12962912 |
|---|---|
| Authors | Dmytro Vikhrov (Czech Academy of Sciences, Global Change Research Institute, corresponding author), R Stojanov (0000-0002-0471-7055, Czech Academy of Sciences, Global Change Research Institute), Barbora Duží (0000-0003-4250-0196, Czech Academy of Sciences, Global Change Research Institute), David Juřička (0000-0002-7895-589X, Mendel University in Brno) |
| Year | 2014 |
| Volume | 13 |
| Issue | 1 |
| Pages | 58-72 |
| Publication date | 2014-01-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Environmental Hazards (JOURNAL) |
| Journal identifiers | ISSN: 1878-0059 • E-ISSN: 1747-7891 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/17477891.2013.864593 |
| OpenAlex | W2119952791 |
| Language | EN |
| Citations received | 1 |
| References cited | 13 |
Using unique data collected in October–December 2012 we estimate the link between commuting for work and level of individual exposure to floods. We find that commuters on average have higher earnings than non-commuters. Individuals affected by one flood commute by 11.2% more than unaffected individuals. We conjecture that the increase is linked to intentions to cover flood-related losses, decrease households' vulnerability to flood risk or out-migrate from the risk areas. Individuals affected by at least two floods are by 20.2% less likely to commute relative to those unaffected. We explain this non-linear effect by the fact that many households out-migrate after the first flood. Stayers commute less, because they are different from non-stayers in some underlying characteristics related to education, employment and family circumstances, which strongly affect commuting behaviour. We further find that in a commuting family an individual is by 53.8% more likely to commence commuting relative to a non-commuting family. Choice of commuting destination is often similar to that of other family members
Business · Demographic economics · Earnings · Economics · Flood myth · Geography · Socioeconomics · Sociology · Vulnerability (computing · Demography · Disaster Management and Resilience · Evacuation and Crowd Dynamics · Flood Risk Assessment and Management
Efficient estimation of limited dependent variable models with endogenous explanatory variables
Coping with floods
Sample Selection Bias as a Specification Error
Distribution of impacts of natural disasters across income groups
Willingness of homeowners to mitigate climate risk through insurance
Flash flood forecasting, warning and risk management
| Citations per year | 0.08 |
|---|---|
| Citation span | 2014 - 2014 (1) |
| Highly cited | No |