CHOICE AND TEMPORAL WELFARE IMPACTS: DYNAMIC GEV DISCRETE CHOICE MODELS

Welfare economics is often employed to measure the impact of economic policies or externalities. When demand is characterized by discrete choices, static models of consumer demand are employed for this type of analysis because of the difficulty in estimating dynamic discrete choice models. In this paper we provide a tractable approach to estimating dynamic discrete choice models of the Generalized Extreme Value (GEV) family that addresses many of the problems identified in the literature and provides a rich set of parameters describing dynamic choice. We apply this model to the case of recreational fishing site choice, comparing dynamic to static versions. In natural resource damage assessment cases, static discrete choice models of recreational site choice are often employed to calculate welfare measures, which will be biased if the underlying preferences are actually dynamic in nature. In our empirical case study we find that the dynamic model provides a richer behavioral model of site choice, and reflects the actual choices very well. We also find significant differences between static and dynamic welfare measures. However, we find that the dynamic model raises several concerns about the specification of the policy impact and the subsequent welfare measurement that are not raised in static cases.Demand and Price Analysis,

Stochastic models of evidence accumulation in changing environments

Organisms and ecological groups accumulate evidence to make decisions. Classic experiments and theoretical studies have explored this process when the correct choice is fixed during each trial. However, we live in a constantly changing world. What effect does such impermanence have on classical results about decision making? To address this question we use sequential analysis to derive a tractable model of evidence accumulation when the correct option changes in time. Our analysis shows that ideal observers discount prior evidence at a rate determined by the volatility of the environment, and the dynamics of evidence accumulation is governed by the information gained over an average environmental epoch. A plausible neural implementation of an optimal observer in a changing environment shows that, in contrast to previous models, neural populations representing alternate choices are coupled through excitation. Our work builds a bridge between statistical decision making in volatile environments and stochastic nonlinear dynamics.Comment: 26 pages, 7 figure

Methodological and empirical challenges in modelling residential location choices

The modelling of residential locations is a key element in land use and transport planning. There are significant empirical and methodological challenges inherent in such modelling, however, despite recent advances both in the availability of spatial datasets and in computational and choice modelling techniques. One of the most important of these challenges concerns spatial aggregation. The housing market is characterised by the fact that it offers spatially and functionally heterogeneous products; as a result, if residential alternatives are represented as aggregated spatial units (as in conventional residential location models), the variability of dwelling attributes is lost, which may limit the predictive ability and policy sensitivity of the model. This thesis presents a modelling framework for residential location choice that addresses three key challenges: (i) the development of models at the dwelling-unit level, (ii) the treatment of spatial structure effects in such dwelling-unit level models, and (iii) problems associated with estimation in such modelling frameworks in the absence of disaggregated dwelling unit supply data. The proposed framework is applied to the residential location choice context in London. Another important challenge in the modelling of residential locations is the choice set formation problem. Most models of residential location choices have been developed based on the assumption that households consider all available alternatives when they are making location choices. Due the high search costs associated with the housing market, however, and the limited capacity of households to process information, the validity of this assumption has been an on-going debate among researchers. There have been some attempts in the literature to incorporate the cognitive capacities of households within discrete choice models of residential location: for instance, by modelling households’ choice sets exogenously based on simplifying assumptions regarding their spatial search behaviour (e.g., an anchor-based search strategy) and their characteristics. By undertaking an empirical comparison of alternative models within the context of residential location choice in the Greater London area this thesis investigates the feasibility and practicality of applying deterministic choice set formation approaches to capture the underlying search process of households. The thesis also investigates the uncertainty of choice sets in residential location choice modelling and proposes a simplified probabilistic choice set formation approach to model choice sets and choices simultaneously. The dwelling-level modelling framework proposed in this research is practice-ready and can be used to estimate residential location choice models at the level of dwelling units without requiring independent and disaggregated dwelling supply data. The empirical comparison of alternative exogenous choice set formation approaches provides a guideline for modellers and land use planners to avoid inappropriate choice set formation approaches in practice. Finally, the proposed simplified choice set formation model can be applied to model the behaviour of households in online real estate environments.Open Acces

On linking microsimulation and applied GE by exact aggregation of heterogeneous discrete-choice making agents

Our paper contributes to bridge the gap between the microsimulation’s approach and applied GE models, by making use of exact aggregation results from the discrete choice literature: heterogeneous individuals choosing (possibly continuous amounts) within a set of discrete alternatives may be aggregated into a representative agent with CES/CET preferences/technologies. These results therefore provide a natural link between the two policy evaluation approaches. We illustrate the usefulness of these results by evaluating potential effects of population ageing on the dynamics of income distribution and inequalities, using a simple OLG model when individuals have to make leisure/work decisions, and choose a profession among a discrete set of alternatives.Microsimulation; Applied OLG models; Exact aggregation; Discrete choice; Population ageing; Income inequality

Farmers’ preferences for cotton cultivation characteristics : a discrete choice experiment in Burkina Faso

While a fierce debate about the advantages and disadvantages of genetically modified crops is ongoing, it is surprising that farmers are often not consulted. In Burkina Faso, where insect resistant Bollgard II (R) cotton (further termed Bt cotton) was commercially released in 2008, studies highlight that cotton producers are in general satisfied with the reduction in insecticide use while the economic benefits are a source of controversy. To gain insight into farmers' preferences towards attributes in cotton cultivation, a discrete choice experiment (DCE) was developed. Five key attributes were identified to describe improved cotton varieties: seed development and provenance, seed costs, yield, required number of insecticide sprays, and preservation of agricultural practices. Farm-gate surveys were conducted among 324 cotton farmers in Western Burkina Faso. The results show that overall, farmers have a positive preference towards yield improvements and a negative preference towards pure private seed development and towards an increase in the requested number of insecticide applications or in the seed costs. According to their varieties at the time of the surveys (Bt and non-Bt), a difference was observed regarding their preferences for a status quo situation, indicating that those growing Bt had a stronger preference to keep the status quo than non-Bt farmers. When dividing the sample in segments based on the farm size, it was shown that there were different preferences with respect to the development of the variety and the required number of insecticide applications. Overall, it can be concluded from this study that economic benefits (linked to higher yields, lower seed costs, or reduced pesticide use) shape farmer's preferences

Understanding Household Preferences For Alternative-Fuel Vehicle Technologies

This report explores consumer preferences among four different alternative-fuel vehicles (AFVs): hybrid electric vehicles (HEVs), compressed natural gas (CNG) vehicles, hydrogen fuel cell (HFC) vehicles, and electric vehicles (EVs). Although researchers have been interested in understanding consumer preferences for AFVs for more than three decades, it is important to update our estimates of the trade-offs people are willing to make between cost, environmental performance, vehicle range, and refuel¬ing convenience. We conducted a nationwide, Internet-based survey to assess consumer preferences for AFVs. Respondents participated in a stated-preference ranking exercise in which they ranked a series of five vehicles (four AFVs and a traditional gasoline-fueled vehicle) that differ primarily in fuel type, price, environmental performance, vehicle range, and refueling conve¬nience. Our findings indicate that, in general, gasoline-fueled vehicles are still preferred over AFVs, however there is a strong interest in AFVs. No AFV type is overwhelmingly preferred, although HEVs seem to have an edge. Using a panel rank-ordered mixed logit model, we assessed the trade-offs people make between key AFV characteristics. We found that, in order to leave a person’s utility unchanged, a $1,000 increase in AFV cost needs to be compensated by either: (1) a$300 savings in driving cost over 12,000 miles; (2) a 17.5 mile increase in vehicle range; or (3) a 7.8-minute decrease in total refueling time (e.g. finding a gas station and refueling)