- Tytuł:
- Accounting for Spatial Heterogeneity of Preferences in Discrete Choice Models
- Autorzy:
-
Budziński, Wiktor
Czajkowski, Mikołaj - Powiązania:
- https://bibliotekanauki.pl/articles/2075414.pdf
- Data publikacji:
- 2021
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
discrete choice experiment
discrete choice models
individual-, region- and population-level parameter estimates
spatial preference heterogeneity - Opis:
- There are reasons researchers may be interested in accounting for spatial heterogeneity of preferences, including avoiding model misspecification and the resulting bias, and deriving spatial maps of willingness-to-pay (WTP), which are relevant for policy-making and environmental management. We employ a Monte Carlo simulation of three econometric approaches to account for spatial preference heterogeneity in discrete choice models. The first is based on the analysis of individual-specific estimates of the mixed logit model. The second extends this model to explicitly account for spatial autocorrelation of random parameters, instead of simply conditioning individual-specific estimates on population-level distributions and individuals’ choices. The third is the geographically weighted multinomial logit model, which incorporates spatial dimensions using geographical weights to estimate location-specific choice models. We analyze the performance of these methods in recovering population-, region- and individual-level preference parameter estimates and implied WTP in the case of spatial preference heterogeneity. We find that, although ignoring spatial preference heterogeneity did not significantly bias population-level results of the simple mixed logit model, neither individual-specific estimates nor the geographically weighted multinomial logit model was able to reliably recover the true region- and individual-specific parameters. We show that the spatial mixed logit proposed in this study is promising and outline possibilities for future development.
- Źródło:
-
Central European Journal of Economic Modelling and Econometrics; 2021, 1; 1-24
2080-0886
2080-119X - Pojawia się w:
- Central European Journal of Economic Modelling and Econometrics
- Dostawca treści:
- Biblioteka Nauki
Artykuł