Advances in Choice Experiment for the evaluation of environmental goods and services

Over the last years, Choice Experiment (CE) methodology has increased its diffusion in several environmental contexts. Despite the increasing popularity of the method, there are still aspects that are not fully explored yet. In particular, the research areas explored in the thesis are: i) the analysis of the effect of information treatments in CEs; ii) the development of frameworks to include spatial variables in discrete choice models; iii) the analysis of the effect of individuals’ psychological traits on preferences towards environmental goods and services; iv) the comparison of existing model specifications which allow to account for preference heterogeneity. Most of the research questions were investigated by applying discrete choice modeling to data collected in two case studies: i) the analysis of social demand for landslide protection in Val del Boite (Veneto region), ii) the analysis of the demand of different heating system of households of the Veneto region. The remaining part of the analysis, instead, involved data generated by means of a simulation study. The thesis is organized in five chapters. Chapter 1 introduces the Choice Experiment method, outlines the research objectives and illustrates the case studies. Chapter 2 focuses on the exploration of the effect of information treatments on the stability of preference estimates and it is based on data analysis carried out from the first case study. Preferences were retrieved before and after providing respondents with scientific-based information, based on visual simulations of possible landslide events. This enabled to measure information effects. Choice data were used to estimate a Mixed Logit model (MXL) in WTP space to obtain robust estimates of marginal willingness-to-pay estimates and control for the effect of information. Overall, it was found that mWTP estimates are dependent on information. The geographical distribution of such effects was illustrated by means of maps of willingness to pay values. Chapters 3-4 illustrate analysis carried out on data retrieved from the second case study. Chapter 3 aims to analyze how geographical variables influence individuals’ sensitivity to key features of heating systems. A MXL model was estimated to spatially characterize preference heterogeneity. The results showed that geographical variables are in fact significant sources of variation of individual’s sensitivity to the investigated attributes of heating systems. Thematic maps were produced to illustrate the distribution of willingness to pay to avoid CO2 emissions across the region and to validate the estimates ex-post. Chapter 4 roots on previous theoretical evidence which suggests that beliefs and attitudes of individual consumers play a crucial role in the diffusion of innovative products. A Latent Class-Random Parameter (LC-RPL) model was estimated to analyze preferences of households for key features of ambient heating systems. The model specification allowed to evaluate the coherence of the underlying preference structure using as criteria psychological constructs from the Theory of Diffusion of Innovation by Rogers. The results broadly support this theory by providing evidence of segmentation of the population consistent with the individuals’ propensity to adopt innovations. It was also found that preferences for heating systems and respondents’ willingness to pay for their key features vary across segments. Chapter 5 illustrates the results of a Monte-Carlo experiment aimed at retrieving the required number of parameters and sample sizes to obtain good approximations of true distributions with Logit-mixed logit (LML) models. These models were recently introduced by Train (2016) and are a key advancement in methods to represent the random taste heterogeneity in logit-type models as they generalize many previous parametric and seminonparametric specifications. The performance of LML models are also compared with those of parametric specifications based on normal mixing distributions. The results suggest that LML models outperform parametric models only at large sample sizes. LML Mmdel specifications with large number of parameters outperformed those with small number parameters only at large sample sizes as well. Finally, chapter 6 draws the conclusions of the thesis

Advances in Choice Experiment for the evaluation of environmental goods and services

Over the last years, Choice Experiment (CE) methodology has increased its diffusion in several environmental contexts. Despite the increasing popularity of the method, there are still aspects that are not fully explored yet. In particular, the research areas explored in the thesis are: i) the analysis of the effect of information treatments in CEs; ii) the development of frameworks to include spatial variables in discrete choice models; iii) the analysis of the effect of individuals’ psychological traits on preferences towards environmental goods and services; iv) the comparison of existing model specifications which allow to account for preference heterogeneity. Most of the research questions were investigated by applying discrete choice modeling to data collected in two case studies: i) the analysis of social demand for landslide protection in Val del Boite (Veneto region), ii) the analysis of the demand of different heating system of households of the Veneto region. The remaining part of the analysis, instead, involved data generated by means of a simulation study. The thesis is organized in five chapters. Chapter 1 introduces the Choice Experiment method, outlines the research objectives and illustrates the case studies. Chapter 2 focuses on the exploration of the effect of information treatments on the stability of preference estimates and it is based on data analysis carried out from the first case study. Preferences were retrieved before and after providing respondents with scientific-based information, based on visual simulations of possible landslide events. This enabled to measure information effects. Choice data were used to estimate a Mixed Logit model (MXL) in WTP space to obtain robust estimates of marginal willingness-to-pay estimates and control for the effect of information. Overall, it was found that mWTP estimates are dependent on information. The geographical distribution of such effects was illustrated by means of maps of willingness to pay values. Chapters 3-4 illustrate analysis carried out on data retrieved from the second case study. Chapter 3 aims to analyze how geographical variables influence individuals’ sensitivity to key features of heating systems. A MXL model was estimated to spatially characterize preference heterogeneity. The results showed that geographical variables are in fact significant sources of variation of individual’s sensitivity to the investigated attributes of heating systems. Thematic maps were produced to illustrate the distribution of willingness to pay to avoid CO2 emissions across the region and to validate the estimates ex-post. Chapter 4 roots on previous theoretical evidence which suggests that beliefs and attitudes of individual consumers play a crucial role in the diffusion of innovative products. A Latent Class-Random Parameter (LC-RPL) model was estimated to analyze preferences of households for key features of ambient heating systems. The model specification allowed to evaluate the coherence of the underlying preference structure using as criteria psychological constructs from the Theory of Diffusion of Innovation by Rogers. The results broadly support this theory by providing evidence of segmentation of the population consistent with the individuals’ propensity to adopt innovations. It was also found that preferences for heating systems and respondents’ willingness to pay for their key features vary across segments. Chapter 5 illustrates the results of a Monte-Carlo experiment aimed at retrieving the required number of parameters and sample sizes to obtain good approximations of true distributions with Logit-mixed logit (LML) models. These models were recently introduced by Train (2016) and are a key advancement in methods to represent the random taste heterogeneity in logit-type models as they generalize many previous parametric and seminonparametric specifications. The performance of LML models are also compared with those of parametric specifications based on normal mixing distributions. The results suggest that LML models outperform parametric models only at large sample sizes. LML Mmdel specifications with large number of parameters outperformed those with small number parameters only at large sample sizes as well. Finally, chapter 6 draws the conclusions of the thesis.Negli ultimi anni, la metodologia degli Esperimenti di Scelta (CE) si è diffusa in diversi contesti ambientali. Nonostante la crescente popolarità del metodo, vi sono ancora alcuni aspetti non del tutto esplorati. Tra questi, il presente lavoro di tesi si concentra su: i) L’analisi dell’effetto di trattamenti di informazione nei CE; ii) L’inclusione di variabili spaziali nei modelli a scelta discreta; iii) L’analisi dell’effetto dei tratti psicologici degli individui sulle preferenze verso beni e servizi ambientali; iv) Il confronto tra diversi modelli a scelta discreta. La maggior parte delle domande di cerca sono state investigate applicando il metodo a dati raccolti in due casi di studio: i) l’analisi della domanda di sistemi di protezione dalle frane in Val del Boite (regione Veneto); ii) l’analisi della domanda di diversi sistemi di riscaldamento in Veneto. La rimanente parte delle analisi è stata condotta su dati generati con una simulazione. La tesi è strutturata in sei capitoli. Il primo capitolo introduce il metodo degli Esperimenti di Scelta ed illustra gli obiettivi della tesi e i casi di studio. Il secondo capitolo si focalizza sull’esplorazione dell’effetto di trattamenti di informazione ed è basato sull’analisi dei dati raccolti nel primo caso di studio. I risultati ottenuti supportano l’evidenza di un effetto dei trattamenti di informazioni sulle stime ottenute da modelli a scelta discreta. I capitoli 3 e 4 illustrano i risultati delle analisi condotte nel secondo caso di studio. Il capitolo 3 si concentra sull’effetto di variabili geografiche sulle preferenze verso diversi sistemi di riscaldamento, analizzato tramite la stima di un modello Mixed Logit. I risultati evidenziano un effetto significativo delle variabili geografiche incluse nel modello. Nel capitolo 4, un modello Latent Class-Random parameters è stato stimato per analizzare le preferenze degli individui verso i diversi sistemi di riscaldamento. Tale modello ha permesso di valutare la coerenza delle stime con la teoria della diffusione delle innovazioni formulata da Rogers. I risultati supportano tale teoria, mostrando una segregazione della popolazione coerente con la propensione individuale ad adottare prodotti innovativi. Inoltre, i risultati suggeriscono una variazione delle preferenze tra i diversi segmenti. Il capitolo 5 illustra i risultati di una simulazione Monte Carlo condotta per confrontare risultati ottenuti con diversi modelli a scelta discreta. Infine, il capitolo 6 riporta le conclusioni della tesi

Investigating determinants of choice and predicting market shares of renewable-based heating systems under alternative policy scenarios

Fostering the uptake of heating technologies based on renewable resources is an important part of the EU energy policy. Yet, despite e!orts to promote their dif-fusion, heating systems based on fossil fuels are still predominant. In order to better tailor energy policies to citizens preferences, it is crucial to collect accurate informa-tion on their determinants of heating choices. At this purpose, we adopted a choice experiment and a latent class model to analyze preferences of householders in the Veneto region (North-East Italy) for di!erent heating systems and their key features. We focused on three devices based on biomass and three on fossil fuels, and account-ed for technical, economic and environmental characteristics of such systems. Model estimates highlight the presence of substantial preference heterogeneity among the population, which can be partially explained by citizens socio-demographics. We also use model outputs to simulate market shares for heating systems under alternative policy scenarios. Results provide interesting suggestions to inform the design of poli-cies aimed at fostering the adoption of biomass-based heating systems

Antecedent Volition and Spatial Effects: Can Multiple Goal Pursuit Mitigate Distance Decay?

The estimation of choice models that explicitly incorporate economic agents’ goal-related information has yet to receive focused attention from practitioners. Despite recent advances on spatial analysis in stated preference studies, there is still no evidence on how spatial effects interact with goal pursuit. In this study we propose a modelling framework to analyse how goal pursuit influences choices and query whether pursuit of important goals makes individuals less distance-sensitive. We estimate a hybrid choice model with latent variables to investigate the role of goals and distance on preferences for recreational site attributes. We use data from a choice experiment involving selection among different sites in Dolomiti Bellunesi National Park (Italy). Our results show that goal pursuit has a significant effect on site choice probability and that distance disutility is decreased when individuals visit recreational sites due to pursuit of important goals. This result indicates that willingness to pay inferences concerning spatially distributed activities depend crucially on the spatial distribution of motivations for participation

Framework Proposal to Quantify the Contribution of Non-Wood Forest Products to the European Union Forest-Based Bioeconomy

Forest ecosystems provide numerous services that contribute to the wellbeing of societies. However, the lack of knowledge about the benefits of non-wood forest ecosystem services, such as non-wood forest products (NWFPs), hinders efficient forest policy decision-making processes. This study proposes a new extension of the Social Accounting Matrices (SAMs) to capture both the private and the social component of NWFPs. By means of a literature review, we show how extended SAMs can be a suitable approach to explain the causal relationship between the supply of forest ecosystem services, forest-based value chains, and the European bioeconomy. The literature analysis shows that the number of research studies calibrating or using SAMs has been increasing over the last decades. Recent extensions of the SAMs made it possible to evaluate the relationship between human wellbeing and the environment. Moreover, we found applications to the forest sector (limited to timber) and to the supply of some non-wood ecosystem services. We believe the extended SAMs will support decision-makers to design forest strategies that properly account for the benefits NWFPs provide to both the economy and the society

Determinants of Recreational Activities Choice in Protected Areas

Conciliating nature conservation and tourism development is an increasingly important task for authorities in charge of managing protected areas and requires an adequate knowledge of visitors′ preferences and recreational behavior. In this light, we used data collected by means of a choice experiment to investigate recreational preferences at Dolomiti Bellunesi National Park, a protected area located in Northeastern Italy. More specifically, we analyzed the determinants of visitors’ decisions to engage with different activities in the park. This is important information for park managers, as different recreational activities have both different impact on the natural heritage and different capability to generate revenue for nature conservation and for enhancing the quality of life of local communities. The findings of our study suggest that the choice of recreational activities is mainly driven by the features of recreational sites and by visitors’ personal characteristics. Concerning park features, visitors’ choices seem to be mostly driven by features directly related to each activity, such as thematic trails for hiking and climbing routes for rock climbing. Among visitors′ characteristics, we found that both previous experience with the activity and socio-demographic characteristics had a significant effect on activity choice. Overall, the results of our study can help park authorities in developing management plans aimed specifically at attracting a larger number of visitors of a certain type, which is an important tool to foster the more sustainable forms of tourism

Is local and organic produce less satiating? Some evidence from a field experiment

We investigate consumers’ preferences towards local and organic food via a framed field experiment involving revealed multiple discrete–continuous choices. Participants were endowed with a cash amount as a budget to purchase any desired quantity of different products. We modelled choices via the multiple discrete–continuous nested extreme value model. Central to our investigation is the test of the hypothesis of the constant effect of attitudes across consumption doses, which is normally an assumption invoked a priori and without testing in discrete choice analyses. Our results support the hypothesis and reveal a strong preference towards organic and local products, associated with both the highest baseline utility and the lowest satiation effect