Tree diameter distribution modelling: introducing the logitlogistic distribution

Johnson's SB distribution is a four-parameter distribution that is transformed into a normal distribution by a logit transformation. By replacing the normal distribution of Johnson's SB with the logistic distribution, we obtain a new distributional model that approximates SB. It is analytically tractable, and we name it the "logitlogistic" (LL) distribution. A generalized four-parameter Weibull model and the Burr XII model are also introduced for comparison purposes. Using the distribution "shape plane" (with axes skew and kurtosis) we compare the "coverage" properties of the LL, the generalized Weibull, and the Burr XII with Johnson's SB, the beta, and the three-parameter Weibull, the main distributions used in forest modelling. The LL is found to have the largest range of shapes. An empirical case study of the distributional models is conducted on 107 sample plots of Chinese fir. The LL performs best among the four-parameter models.

Bivariate distribution modeling with tree diameter and height data

The Logit-Logistic (LL), Johnson's SB, and the Beta (GBD) are flexible four-parameter probability distribution models in terms of the (skewness-kurtosis) region covered, and each has been used for modeling tree diameter distributions in forest stands. This article compares bivariate forms of these models in terms of their adequacy in representing empirical diameter-height distributions from 102 sample plots. Four bivariate models are compared: SBB, the natural, well-known, and much-used bivariate generalization of SB; the bivariate distributions with LL, SB, and Beta as marginals, constructed using Plackett's method (LL-2P, etc.). All models are fitted using maximum likelihood, and their goodness-of-fits are compared using minus log-likelihood (equivalent to Akaike's Information Criterion, the AIC). The performance ranking in this case study was SBB, LL-2P, GBD-2P, and SB-2P

The Richit-Richards family of distributions and its use in forestry

Johnson's SB and the logit-logistic are four-parameter distribution models that may be obtained from the standard normal and logistic distributions by a four-parameter transformation. For relatively small data sets, such as diameter at breast height measurements obtained from typical sample plots, distribution models with four or less parameters have been found to be empirically adequate. However, in situations in which the distributions are complex, for example in mixed stands or when the stand has been thinned or when working with aggregated data, then distribution models with more shape parameters may prove to be necessary. By replacing the symmetric standard logistic distribution of the logit-logistic with a one-parameter “standard Richards” distribution and transforming by a five-parameter Richards function, we obtain a new six-parameter distribution model, the “Richit-Richards”. The Richit-Richards includes the “logit-Richards”, the “Richit-logistic”, and the logit-logistic as submodels. Maximum likelihood estimation is used to fit the model, and some problems in the maximum likelihood estimation of bounding parameters are discussed. An empirical case study of the Richit-Richards and its submodels is conducted on pooled diameter at breast height data from 107 sample plots of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.). It is found that the new models provide significantly better fits than the four-parameter logit-logistic for large data sets.

Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment

Scepticism over stated preference surveys conducted online revolves around the concerns over “professional respondents” who might rush through the questionnaire without sufficiently considering the information provided. To gain insight on the validity of this phenomenon and test the effect of response time on choice randomness, this study makes use of a recently conducted choice experiment survey on ecological and amenity effects of an offshore windfarm in the UK. The positive relationship between self-rated and inferred attribute attendance and response time is taken as evidence for a link between response time and cognitive effort. Subsequently, the generalised multinomial logit model is employed to test the effect of response time on scale, which indicates the weight of the deterministic relative to the error component in the random utility model. Results show that longer response time increases scale, i.e. decreases choice randomness. This positive scale effect of response time is further found to be non-linear and wear off at some point beyond which extreme response time decreases scale. While response time does not systematically affect welfare estimates, higher response time increases the precision of such estimates. These effects persist when self-reported choice certainty is controlled for. Implications of the results for online stated preference surveys and further research are discussed.

Factores determinantes del uso de Internet en la comercialización del aceite de oliva. Análisis del sector en Cataluña

Las cooperativas son entidades con una gran presencia económica y social en España, y tienen una gran influencia en la economía rural de las zonas donde están ubicadas. El principal objetivo del presente trabajo es el análisis del uso de las nuevas tecnologías por parte de las cooperativas agroalimentarias, centrándose en las productoras de aceite de oliva para determinar los principales factores que condicionan su comportamiento en la Red. En el presente estudio se analizan sus sitios web y se determina qué tipo de información aporta, tanto datos generales como datos de comercialización. A partir de los resultados obtenidos, se busca la relación que pueda existir entre el tamaño de la cooperativa, su actividad exportadora o la actividad de comercio electrónico con la presencia online, mediante una regresión logística. De esta manera podremos conocer si realmente la implantación de nuevas tecnologías en las cooperativas permite desarrollar una óptima actividad económica.

Determining factors of the innovative behavior of cooperatives: an analysis of the case of Castilla y León

Cooperatives have a long historical experience in the Spanish economy and have demonstrated their ability to compete against traditional firms in the market. To maintain this capability, while taking advantage of the competitive advantages associated with their idiosyncrasies as social economy enterprises, they should take into consideration that the economy is increasingly globalized and increasingly knowledge-based, especially with regards to technological content. As a consequence, the innovative capacity appears to be a key aspect in order to be able to challenge competitors. This article characterizes the innovative behavior of cooperatives in the region of Castile and Leon and analyses the internal and external factors affecting their innovative performance, based on data from a survey of 581 cooperatives. The results of the empirical analysis, which is performed by multivariate binary logistic regression on various types of innovation, lead us to identify the size of the organizations, the existence of planning, the R & D activities and the human capital as the main determining factors.

Using choice experiments to explore the spatial distribution of willingness to pay for rural landscape improvements

We report findings from a choice experiment survey designed to estimate the economic benefits of policy measures to improve the rural landscape in the Republic of Ireland. Using a panel mixed logit specification to account for unobserved taste heterogeneity we derived individual-specific willingness-to-pay (WTP) estimates for each respondent in the sample. We subsequently investigated the spatial dependence of these estimates. Results suggest the existence of positive spatial autocorrelation for all rural landscape attributes. As a means of benefit transfer, kriging methods were employed to interpolate WTP estimates across the whole of the Republic of Ireland. The kriged WTP surfaces confirm the existence of spatial dependence and illustrate the implied spatial variation and regional disparities in WTP for all the rural landscape improvements investigated.

Determinants of long-distance investing by business angels in the UK

The business angel market is usually identified as a local market, and the proximity of an investment has been shown to be key in the angel's investment preferences and an important filter at the screening stage of the investment decision. This is generally explained by the personal and localized networks used to identify potential investments, the hands-on involvement of the investor and the desire to minimize risk. However, a significant minority of investments are long distance. This paper is based on data from 373 investments made by 109 UK business angels. We classify the location of investments into three groups: local investments ( those made within the same county or in adjacent counties); intermediate investments ( those made in counties adjacent to the 'local' counties); and long-distance investments ( those made beyond this range). Using ordered logit analysis the paper develops and tests a number of hypotheses that relate long-distance investment to investment characteristics and investor characteristics. The paper concludes by drawing out the implications for entrepreneurs seeking business angel finance in investment-deficient regions, business angel networks seeking to match investors to entrepreneurs and firms ( which are normally their primary clients), and for policy-makers responsible for local and regional economic development.

Cheap and expensive alternatives in stated choice experiments: are they equally considered by respondents?

When analysing choice experiments respondents are assumed to attend all attributes and alternatives in the same way. However, because of the important role that the price of the alternatives can play in the decision-making process, the level of price of a specific alternative may have consequences on the level of consideration given to the remaining attributes of the alternative. In this article, we propose the use of a discrete mixtures logit approach to accommodate respondents ignoring alternatives in stated choice experiments. Our results indicate a higher propensity for respondents to ignore attributes when they face cheap rather than expensive alternatives. We also find that allowing for this leads to substantial improvements in the model performance.

Site choices in recreational demand: a matter of utility maximization or regret minimization?

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.

Random Regret Minimization: Exploration of a New Choice Model for Environmental and Resource Economics

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.

Exploring Scale Effects of Best/Worst Rank Ordered Choice Data to Estimate Benefits of Tourism in Alpine Grazing Commons

In many environmental valuation applications standard sample sizes for choice modelling surveys are impractical to achieve. One can improve data quality using more in-depth surveys administered to fewer respondents. We report on a study using high quality rank-ordered data elicited with the best-worst approach. The resulting "exploded logit" choice model, estimated on 64 responses per person, was used to study the willingness to pay for external benefits by visitors for policies which maintain the cultural heritage of alpine grazing commons. We find evidence supporting this approach and reasonable estimates of mean WTP, which appear theoretically valid and policy informative. © The Author (2011).

Choice of contracts in the British National Health Service: An empirical study

Following major reforms of the British National Health Service (NHS) in 1990, the roles of purchasing and providing health services were separated, with the relationship between purchasers and providers governed by contracts. Using a mixed multinomial logit analysis, we show how this policy shift led to a selection of contracts that is consistent with the predictions of a simple model, based on contract theory, in which the characteristics of the health services being purchased and of the contracting parties influence the choice of contract form. The paper thus provides evidence in support of the practical relevance of theory in understanding health care market reform. © 2008 Elsevier B.V. All rights reserved.

SOCIAL-CLASS, CLASS ORIGINS AND POLITICAL PARTISANSHIP IN THE REPUBLIC-OF-IRELAND

As Laver (1992) notes, people who write about Irish politics frequently describe Ireland as a rather peculiar place. One aspect of this peculiarity is that voters in the Republic of Ireland do not behave like their European counterparts. In particular, Irish voting patterns appear to be only weakly structured by social class. Recent contributions to the debate employing a more sophisticated categorisation of classes have led to some qualification of the 'politics without social bases' description, but still lead to the broad conclusion that any relationship which does exist between social divisions, on the one hand, and party preference, on the other, is, at most, quite marginal. In this paper we draw on data from the 1990 European Values Study to re-examine this issue. We apply a variety of models to the data, including logit regression and diagonal reference models (Sobel 1981, 1984) to explore the complex fashion in which class and political preferences are related in Ireland. We argue that the relationship between such preferences and social divisions are, in fact, greater than has been hitherto thought. In particular, we show the importance of taking into account not only social class but also class origins and class mobility in understanding the nature of political partisanship in the Republic of Ireland.

Preferences for a third-trimester ultrasound scan in a low-risk obstetric population: a discrete choice experiment

Objective: Establish maternal preferences for a third-trimester ultrasound scan in a healthy, low-risk pregnant population.

Design: Cross-sectional study incorporating a discrete choice experiment.

Setting: A large, urban maternity hospital in Northern Ireland.

Participants: One hundred and forty-six women in their second trimester of pregnancy.

Methods: A discrete choice experiment was designed to elicit preferences for four attributes of a third-trimester ultrasound scan: health-care professional conducting the scan, detection rate for abnormal foetal growth, provision of non-medical information, cost. Additional data collected included age, marital status, socio-economic status, obstetric history, pregnancy-specific stress levels, perceived health and whether pregnancy was planned. Analysis was undertaken using a mixed logit model with interaction effects.

Main outcome measures: Women's preferences for, and trade-offs between, the attributes of a hypothetical scan and indirect willingness-to-pay estimates.

Results: Women had significant positive preference for higher rate of detection, lower cost and provision of non-medical information, with no significant value placed on scan operator. Interaction effects revealed subgroups that valued the scan most: women experiencing their first pregnancy, women reporting higher levels of stress, an adverse obstetric history and older women.

Conclusions: Women were able to trade on aspects of care and place relative importance on clinical, non-clinical outcomes and processes of service delivery, thus highlighting the potential of using health utilities in the development of services from a clinical, economic and social perspective. Specifically, maternal preferences exhibited provide valuable information for designing a randomized trial of effectiveness and insight for clinical and policy decision makers to inform woman-centred care.