80 resultados para random utility model


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Data from a large-scale contingent valuation study are used to investigate the effects of forest attributes on willingness to pay for forest recreation in Ireland. In particular, the presence of a nature reserve in the forest is found to significantly increase the visitors' willingness to pay. A random utility model is used to estimate the welfare change associated with the creation of nature reserves in all the Irish forests currently without one. The yearly impact on visitors' economic welfare of new nature reserves approaches half a million pounds per annum, exclusive of non-recreational values. (C) 2000 Elsevier Science B.V. All rights reserved.

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In recent years, Russia has experienced significant economic growth. The wine industry is among those most affected by increases in disposable income. As a consequence, Russian wine importers have widened the range at the upper end of the quality spectrum. In the current scenario, some key questions arise concerning consumer attitudes toward wine and the way it is perceived in this evolving market. This article attempts to investigate such concerns through a choice experiment approach conducted by means of a questionnaire-based survey submitted to 388 Russian households located in the country's three largest cities (Moscow, Saint Petersburg, and Novosibirsk). In the experiment, respondents were asked to choose their favorite wine among seven dry red wines. The stated choices are analyzed using a random utility model to obtain an estimation of the price effect through a triangular distribution. Our results indicate the presence of three distinct market segments in the Russian wine market: a segment with only high-quality, highly priced Italian and French wines, a medium-quality segment currently limited to Spanish wines, and a much lower quality segment of wines in which demand for alcohol is essentially satisfied.

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The likelihood of smallholder farmers not participating in agroforestry agri-environmental schemes and payments for ecosystem services (PES) may be due to limited farmland endowment and formal credit constraints. These deficits may lead to an ‘exclusive club’ of successful farmers, which are not necessarily poor, enjoying the benefits of agri-environmental schemes and PES although agrienvironmental schemes and PES have been devised as a means of fostering rural sustainable development and improving the livelihood of poor smallholder farmers. Smallholder farmers in parts of rural Kenya continue to enroll in ‘The International Small Group Tree Planting Programme’ (TIST), an agri-environmental scheme, promoting agroforestry, carbon sequestration and conservation agriculture (CA). The question remains if these farmers are really poor? This study examines factors that determine the participation of smallholder farmers in TIST in parts of rural Kenya. We use survey data compiled in 2013 on 210 randomly selected smallholder farmers from Embu, Meru and Nanyuki communities; the sample consists of TIST and non-TIST members. A random utility model and logit regression were used to test a set of non-monetary and monetary factors that influence participation in the TIST. The utility function is conceptualized to give non-monetary factors, particularly the common medium of communication in rural areas – formal and informal – a central role. Furthermore, we investigate other factors (incl. credit accessibility and interest rate) that reveal the nature of farmers participating in TIST. The findings suggest that spread of information via formal and informal networks is a major driver of participation in the TIST program. Furthermore, variables such credit constrains, age and labour supply positively correlate with TIST participation, while for education the opposite is true. It is important to mention that these correlations, although somewhat consistent, were all found to be weak. The results indicate that participation in the TIST program is not influenced by farm size; therefore we argue that the TIST scheme is NOT an ‘exclusive club’ comprising wealthy and successful farmers. Older farmers’ being more likely to join the TIST is an argument for their long- rather than widely assumed short-term planning horizon and a new contribution to the literature. Given the importance of poverty alleviation and climate smart agriculture in developing countries, sustainable policy should strengthening the social and human capital as well as informal networks in rural areas. Extension services should effectively communicate benefits to less educated and credit constrained farmers.

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This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.

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This paper compares the Random Regret Minimization and the Random Utility Maximization models for determining recreational choice. The Random Regret approach is based on the idea that, when choosing, individuals aim to minimize their regret – regret being defined as what one experiences when a non-chosen alternative in a choice set performs better than a chosen one in relation to one or more attributes. The Random Regret paradigm, recently developed in transport economics, presents a tractable, regret-based alternative to the dominant choice paradigm based on Random Utility. Using data from a travel cost study exploring factors that influence kayakers’ site-choice decisions in the Republic of Ireland, we estimate both the traditional Random Utility multinomial logit model (RU-MNL) and the Random Regret multinomial logit model (RR-MNL) to gain more insights into site choice decisions. We further explore whether choices are driven by a utility maximization or a regret minimization paradigm by running a binary logit model to examine the likelihood of the two decision choice paradigms using site visits and respondents characteristics as explanatory variables. In addition to being one of the first studies to apply the RR-MNL to an environmental good, this paper also represents the first application of the RR-MNL to compute the Logsum to test and strengthen conclusions on welfare impacts of potential alternative policy scenarios.

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This paper proposes a discrete mixture model which assigns individuals, up to a probability, to either a class of random utility (RU) maximizers or a class of random regret (RR) minimizers, on the basis of their sequence of observed choices. Our proposed model advances the state of the art of RU-RR mixture models by (i) adding and simultaneously estimating a membership model which predicts the probability of belonging to a RU or RR class; (ii) adding a layer of random taste heterogeneity within each behavioural class; and (iii) deriving a welfare measure associated with the RU-RR mixture model and consistent with referendum-voting, which is the adequate mechanism of provision for such local public goods. The context of our empirical application is a stated choice experiment concerning traffic calming schemes. We find that the random parameter RU-RR mixture model not only outperforms its fixed coefficient counterpart in terms of fit-as expected-but also in terms of plausibility of membership determinants of behavioural class. In line with psychological theories of regret, we find that, compared to respondents who are familiar with the choice context (i.e. the traffic calming scheme), unfamiliar respondents are more likely to be regret minimizers than utility maximizers. © 2014 Elsevier Ltd.

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Many studies have shown that with increasing LET of ionizing radiation the RBE (relative biological effectiveness) for dsb (double strand breaks) induction remains around 1.0 despite the increase in the RBE for cell killing. This has been attributed to an increase in the complexity of lesions, classified as dsb with current techniques, at multiply damaged sites. This study determines the molecular weight distributions of DNA from Chinese hamster V79 cells irradiated with X-rays or 110 keV/mu m alpha-particles. Two running conditions for pulsed-field gel-electrophoresis were chosen to give optimal separation of fragments either in the 225 kbp-5.7 Mbp range or the 0.3 kbp to 225 kbp range. Taking the total fraction of DNA migrating into the gel as a measure of fragmentation, the RBE for dsb induction was less than 1.0 for both molecular weight regions studied. The total yields of dsb were 8.2 x 10(-9) dsb/Gy/bp for X-rays and 7.8 x 10(-9) dsb/Gy/bp for a-particles, measured using a random breakage model. Analysis of the RBE of alpha-particles versus molecular weight gave a different response. In the 0.4 Mbp-57 Mbp region the RBE was less than 1.0; however, below 0.4 Mbp the RBE increased above 1.0. The frequency distributions of fragment sizes were found to differ from those predicted by a model assuming random breakage along the length of the DNA and the differences were greater for alpha-particles than for X-rays. An excess of fragments induced by a single-hit mechanism was found in the 8-300 kbp region and for X-rays and alpha-particles these corresponded to an extra 0.8 x 10(-9) and 3.4 x 10(-9) dsb/bp/Gy, respectively. Thus for every alpha-particle track that induces a dsb there is a 44% probability of inducing a second break within 300 kbp and for electron tracks the probability is 10%. This study shows that the distribution of damage from a high LET alpha-particle track is significantly different from that observed with low LET X-rays. In particular, it suggests that the fragmentation patterns of irradiated DNA may be related to the higher-order chromatin repealing structures found in intact cells.

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In studies of radiation-induced DNA fragmentation and repair, analytical models may provide rapid and easy-to-use methods to test simple hypotheses regarding the breakage and rejoining mechanisms involved. The random breakage model, according to which lesions are distributed uniformly and independently of each other along the DNA, has been the model most used to describe spatial distribution of radiation-induced DNA damage. Recently several mechanistic approaches have been proposed that model clustered damage to DNA. In general, such approaches focus on the study of initial radiation-induced DNA damage and repair, without considering the effects of additional (unwanted and unavoidable) fragmentation that may take place during the experimental procedures. While most approaches, including measurement of total DNA mass below a specified value, allow for the occurrence of background experimental damage by means of simple subtractive procedures, a more detailed analysis of DNA fragmentation necessitates a more accurate treatment. We have developed a new, relatively simple model of DNA breakage and the resulting rejoining kinetics of broken fragments. Initial radiation-induced DNA damage is simulated using a clustered breakage approach, with three free parameters: the number of independently located clusters, each containing several DNA double-strand breaks (DSBs), the average number of DSBs within a cluster (multiplicity of the cluster), and the maximum allowed radius within which DSBs belonging to the same cluster are distributed. Random breakage is simulated as a special case of the DSB clustering procedure. When the model is applied to the analysis of DNA fragmentation as measured with pulsed-field gel electrophoresis (PFGE), the hypothesis that DSBs in proximity rejoin at a different rate from that of sparse isolated breaks can be tested, since the kinetics of rejoining of fragments of varying size may be followed by means of computer simulations. The problem of how to account for background damage from experimental handling is also carefully considered. We have shown that the conventional procedure of subtracting the background damage from the experimental data may lead to erroneous conclusions during the analysis of both initial fragmentation and DSB rejoining. Despite its relative simplicity, the method presented allows both the quantitative and qualitative description of radiation-induced DNA fragmentation and subsequent rejoining of double-stranded DNA fragments. (C) 2004 by Radiation Research Society.

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This paper introduces the discrete choice model-paradigm of Random Regret Minimisation (RRM) to the field of health economics. The RRM is a regret-based model that explores a driver of choice different from the traditional utility-based Random Utility Maximisation (RUM). The RRM approach is based on the idea that, when choosing, individuals aim to minimise their regret–regret being defined as what one experiences when a non-chosen alternative in a choice set performs better than a chosen one in relation to one or more attributes. Analysing data from a discrete choice experiment on diet, physical activity and risk of a fatal heart attack in the next ten years administered to a sample of the Northern Ireland population, we find that the combined use of RUM and RRM models offer additional information, providing useful behavioural insights for better informed policy appraisal.

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This study is the first to compare random regret minimisation (RRM) and random utility maximisation (RUM) in freight transport application. This paper aims to compare RRM and RUM in a freight transport scenario involving negative shock in the reference alternative. Based on data from two stated choice experiments conducted among Swiss logistics managers, this study contributes to related literature by exploring for the first time the use of mixed logit models in the most recent version of the RRM approach. We further investigate two paradigm choices by computing elasticities and forecasting choice probability. We find that regret is important in describing the managers’ choices. Regret increases in the shock scenario, supporting the idea that a shift in reference point can cause a shift towards regret minimisation. Differences in elasticities and forecast probability are identified and discussed appropriately.

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As part of its single technology appraisal (STA) process, the National Institute for Health and Care Excellence (NICE) invited the company that manufactures cabazitaxel (Jevtana(®), Sanofi, UK) to submit evidence for the clinical and cost effectiveness of cabazitaxel for treatment of patients with metastatic hormone-relapsed prostate cancer (mHRPC) previously treated with a docetaxel-containing regimen. The School of Health and Related Research Technology Appraisal Group at the University of Sheffield was commissioned to act as the independent Evidence Review Group (ERG). The ERG produced a critical review of the evidence for the clinical and cost effectiveness of the technology based upon the company's submission to NICE. Clinical evidence for cabazitaxel was derived from a multinational randomised open-label phase III trial (TROPIC) of cabazitaxel plus prednisone or prednisolone compared with mitoxantrone plus prednisone or prednisolone, which was assumed to represent best supportive care. The NICE final scope identified a further three comparators: abiraterone in combination with prednisone or prednisolone; enzalutamide; and radium-223 dichloride for the subgroup of people with bone metastasis only (no visceral metastasis). The company did not consider radium-223 dichloride to be a relevant comparator. Neither abiraterone nor enzalutamide has been directly compared in a trial with cabazitaxel. Instead, clinical evidence was synthesised within a network meta-analysis (NMA). Results from TROPIC showed that cabazitaxel was associated with a statistically significant improvement in both overall survival and progression-free survival compared with mitoxantrone. Results from a random-effects NMA, as conducted by the company and updated by the ERG, indicated that there was no statistically significant difference between the three active treatments for both overall survival and progression-free survival. Utility data were not collected as part of the TROPIC trial, and were instead taken from the company's UK early access programme. Evidence on resource use came from the TROPIC trial, supplemented by both expert clinical opinion and a UK clinical audit. List prices were used for mitoxantrone, abiraterone and enzalutamide as directed by NICE, although commercial in-confidence patient-access schemes (PASs) are in place for abiraterone and enzalutamide. The confidential PAS was used for cabazitaxel. Sequential use of the advanced hormonal therapies (abiraterone and enzalutamide) does not usually occur in clinical practice in the UK. Hence, cabazitaxel could be used within two pathways of care: either when an advanced hormonal therapy was used pre-docetaxel, or when one was used post-docetaxel. The company believed that the former pathway was more likely to represent standard National Health Service (NHS) practice, and so their main comparison was between cabazitaxel and mitoxantrone, with effectiveness data from the TROPIC trial. Results of the company's updated cost-effectiveness analysis estimated a probabilistic incremental cost-effectiveness ratio (ICER) of £45,982 per quality-adjusted life-year (QALY) gained, which the committee considered to be the most plausible value for this comparison. Cabazitaxel was estimated to be both cheaper and more effective than abiraterone. Cabazitaxel was estimated to be cheaper but less effective than enzalutamide, resulting in an ICER of £212,038 per QALY gained for enzalutamide compared with cabazitaxel. The ERG noted that radium-223 is a valid comparator (for the indicated sub-group), and that it may be used in either of the two care pathways. Hence, its exclusion leads to uncertainty in the cost-effectiveness results. In addition, the company assumed that there would be no drug wastage when cabazitaxel was used, with cost-effectiveness results being sensitive to this assumption: modelling drug wastage increased the ICER comparing cabazitaxel with mitoxantrone to over £55,000 per QALY gained. The ERG updated the company's NMA and used a random effects model to perform a fully incremental analysis between cabazitaxel, abiraterone, enzalutamide and best supportive care using PASs for abiraterone and enzalutamide. Results showed that both cabazitaxel and abiraterone were extendedly dominated by the combination of best supportive care and enzalutamide. Preliminary guidance from the committee, which included wastage of cabazitaxel, did not recommend its use. In response, the company provided both a further discount to the confidential PAS for cabazitaxel and confirmation from NHS England that it is appropriate to supply and purchase cabazitaxel in pre-prepared intravenous-infusion bags, which would remove the cost of drug wastage. As a result, the committee recommended use of cabazitaxel as a treatment option in people with an Eastern Cooperative Oncology Group performance status of 0 or 1 whose disease had progressed during or after treatment with at least 225 mg/m(2) of docetaxel, as long as it was provided at the discount agreed in the PAS and purchased in either pre-prepared intravenous-infusion bags or in vials at a reduced price to reflect the average per-patient drug wastage.

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New radiocarbon calibration curves, IntCal04 and Marine04, have been constructed and internationally ratified to replace the terrestrial and marine components of IntCal98. The new calibration data sets extend an additional 2000 yr, from 0–26 cal kyr BP (Before Present, 0 cal BP = AD 1950), and provide much higher resolution, greater precision, and more detailed structure than IntCal98. For the Marine04 curve, dendrochronologically-dated tree-ring samples, converted with a box diffusion model to marine mixed-layer ages, cover the period from 0–10.5 cal kyr BP. Beyond 10.5 cal kyr BP, high-resolution marine data become available from foraminifera in varved sediments and U/Th-dated corals. The marine records are corrected with site-specific 14C reservoir age information to provide a single global marine mixed-layer calibration from 10.5–26.0 cal kyr BP. A substantial enhancement relative to IntCal98 is the introduction of a random walk model, which takes into account the uncertainty in both the calendar age and the 14C age to calculate the underlying calibration curve (Buck and Blackwell, this issue). The marine data sets and calibration curve for marine samples from the surface mixed layer (Marine04) are discussed here. The tree-ring data sets, sources of uncertainty, and regional offsets are presented in detail in a companion paper by Reimer et al. (this issue).