Results 271 to 280 of about 2,754,541 (342)

(Dis)trust in Digital Insurance: How Datafied Practices Shift Uncertainties and Reconfigure Trust Relations

open access: yesThe British Journal of Sociology, EarlyView.
ABSTRACT Trust is both a prerequisite and a product of insurance, as insurance contracts are built on and create trust relations that enable a risk‐averse perspective towards the future. At the same time, insurer‐policyholder relationships are characterised by a persistent distrust, rooted in insurance economics and industry reputation. In this article,
Maiju Tanninen, Gert Meyers
wiley   +1 more source

Estimating Causal Effects With Observational Data: Guidelines for Agricultural and Applied Economists

open access: yesJournal of Agricultural Economics, EarlyView.
ABSTRACT Most research questions in agricultural and applied economics are causal in nature: they study how changes in one or more variables (such as policies, prices or weather) affect one or more other variables (e.g., income, crop yields or pollution).
Arne Henningsen   +6 more
wiley   +1 more source

Environmental Information or Social Norm? A Ladder Toward Environmentally Sustainable Food Choices

open access: yesJournal of Agricultural Economics, EarlyView.
ABSTRACT Agricultural production and the food supply chain have a significant impact on the environment. To foster an environmentally sustainable food system, it is vital to change consumers' food choice patterns to be more environmentally sustainable.
Ryosuke Inoue, Kentaro Kawasaki
wiley   +1 more source

Dutch dilemma: Housing prices and flood risk exposure

open access: yesReal Estate Economics, EarlyView.
Abstract This article studies the impact of flood risk exposure on housing prices in a major river delta. Analyzing 1.8 million property transactions from 1998 to 2023 in the Netherlands, we find an average price discount of 1.1%. We observe considerable heterogeneity in price effects driven by exposure intensity, institutional settings that vary ...
Piet Eichholtz   +2 more
wiley   +1 more source

Explainable spatial machine learning for hedonic real estate modeling

open access: yesReal Estate Economics, EarlyView.
Abstract Accurately modeling rents and prices is a key challenge in real estate analysis. Traditional linear models may fail to capture complex non‐linear relationships, and spatial dependencies are often ignored in existing machine‐learning approaches.
Tim Gyger   +5 more
wiley   +1 more source

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