Tanaka Laboratory

Environmental Economics · Climate and Disaster Risk · Data Science

Research

What has to change for societies to adapt to climate risk? We approach this question from four areas. For each, this page introduces key papers and what we found. The figures were drawn for this page from the estimates reported in the papers.

Disaster risk communication and evacuation Climate adaptation and urban resilience Green infrastructure and environmental policy Sustainable mobility and urban space

Disaster risk communication and evacuation

Even when warnings and evacuation orders reach people, relatively few actually evacuate. Using survey experiments built on hypothetical disaster scenarios, we study what happens between receiving information and acting on it, and what kind of information moves people.

The same warning splits residents into those who respond and those who barely do
Rating of information clarityResponsive 67.0%33.0%
Evacuation intentionResponsive 80.7%19.3%

Responsive to how warnings are designed Non-responsive

Factorial survey experiment with 1,671 residents of flood-prone areas. Class shares from two-class finite mixture beta regression models.

Source: based on Tanaka, Kito, & Tanaka (2026), International Journal of Disaster Risk Reduction, 137, 106075

Key papers

Climate adaptation and urban resilience

Preparing for extreme heat, floods and major earthquakes involves deciding where to direct limited budgets. We study what residents prioritize, how those priorities relate to support for paying the costs, and how residents’ views change through repeated deliberation.

For heat measures, residents put life-saving measures first
Strengthening emergency medical services2.66
Expanding public cooling shelters1.81
Disseminating clear real-time heat information1.28
Promoting urban greening1.19
Creating shaded areas0.78
Installing public water refill stations0.46
Public education on heat prevention0.39
Refining heat alert systems0 (reference)

Best–worst scaling (BWS) with 1,819 residents of Yokohama. Mean parameters from a mixed logit model, relative to “refining heat alert systems” (= 0).

Source: based on Tanaka & Akaishi (2026), Risk Analysis, 46(8), e70315

Key papers

Green infrastructure and environmental policy

Green infrastructure — rain gardens, street trees, green spaces and other features that use natural processes to soften the impacts of heavy rain and heat — is one way of adapting to climate change. We test its effects at the regional level and study the conditions under which firms and residents who own land choose to adopt it.

Firms’ adoption choices were most strongly associated with subsidies for maintenance costs
Maintenance cost subsidy1.03
Technical support for installation0.75
Installation subsidy0.74
Technical support for maintenance0.72
Rainwater storage and infiltration0.70
Support for environmental certification0.25 (n.s.)
Ecologically oriented greening0.20 (n.s.)
Landscape-oriented greening−0.20 (n.s.)
Installation cost (¥20,000/m² or more)−0.65

Conditional logit estimates for the 78 firms in Sapporo that completed the choice experiment. Dark bars are statistically significant at the 10% level; light bars (n.s.) are not. Installation cost is a dummy for ¥20,000/m² or more, relative to ¥10,000/m². Labels are translated from Japanese.

Source: based on Wang, Tanaka, & Mukoyama (2026), Journal of the City Planning Institute of Japan, 61(3), 840–847 (in Japanese)

Key papers

Sustainable mobility and urban space

Traffic calming and better sidewalks make streets safer and more walkable, but they often divide opinion over car access and cost. We study which treatments residents prefer and how much of the cost they are willing to bear.

Among traffic-calming treatments, median refuge islands were preferred most
Median refuge islands1.92
Mini roundabouts1.67
Shared streets1.58
Gateway treatments1.49
Pavement materials and appearance1.11
Diverters0.48
Speed humps0.37
Pinchpoints (curb extensions)0 (reference)

Best–worst scaling (BWS) with 1,717 residents living along 19 corridors in Portland, Oregon. Mean parameters from a mixed logit model, relative to pinchpoints (= 0).

Source: based on Tanaka et al. (2027), Transportation Research Part A, 215, 105293

Key papers

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