Vertical differentiation via multi-tier geographical indications and the consumer perception of quality: The case of Chianti wines

We derive and estimate a model of demand for Geographical Indications allowing for subjective and heterogeneous quality perceptions, and study vertical differentiation based on multi-tier quality labels within the context of the strategy adopted by the Chianti Consortium. Quality perceptions and wine choices are elicited in an online experiment where the number of quality tiers is augmented incrementally in a between-subject design. The empirical model includes subjective quality perceptions as an (endogenous) explanatory variable, and unexplained heterogeneity in WTP for quality as a random parameter. We find that quality perceptions are endogenous to the labeling regime, and adding a high-quality label (Chianti Classico Gran Selezione) decreases the perceived quality of all other Chianti wines, but not the competitor wines. However, the market shared lost to perception restructuring is small compared to the benefits of increased vertical differentiation.     

Optimal portfolios under worst-case scenarios

In standard portfolio theories such as Mean–Variance optimization, expected utility theory, rank dependent utility heory, Yaari’s dual theory and cumulative prospect theory, the worst outcomes for optimal strategies occur when the market declines (e.g. during crises), which is at odds with the needs of many investors. Hence, we depart from the traditional settings and study optimal strategies for investors who impose additional constraints on their final wealth in the states corresponding to a stressed financial market. We provide a framework that maintains the stylized features of the SP/A theory while dealing with the goal of security in a more flexible way. Preferences become state-dependent, and we assess the impact of these preferences on trading decisions. We construct optimal strategies explicitly and show how they outperform traditional diversified strategies under worst-case scenarios.     

The cost of capital and optimal financing policy in a dynamic setting

This paper revisits the Modigliani–Miller propositions on the optimal financing policy and cost of capital in a dynamic setting. In an environment without taxes and bankruptcy costs, the results are generally consistent with the Modigliani–Miller Propositions 1 and 2. However, the first proposition should be presented and interpreted more carefully, as given firm characteristics, there is only one optimal capital structure. Thus, a firm’s capital structure is relevant. A relaxation of assumptions about either taxes or bankruptcy costs leads to conclusions that are generally different from those in Modigliani and Miller (1958). The model predicts that leverage and sales-to-capital ratios decrease but firm size and capital stock increase with the subjective discount factor of the firm’s manager if there are taxes and bankruptcy costs. The empirical analysis supports these predictions.     

Examining dynamic currency linkages amongst South Asian economies: An empirical study

In this paper, we examine the currency market linkages of South Asian member countries using daily data from 6 January 2004 to 31st March 2016. Time invariant and varying Copula GARCH models show that South Asian countries, except for India and Nepal/Bhutan, have low levels of currency market linkages which can be ascribed to poor levels of intra-regional trade intensity and portfolio flows. We reconfirm the copula results through Diebold and Yilmaz methodology and document that currency market connectedness is very limited in the South Asian region. The trends of the fundamental determinants of currency co-movements for the South Asian member countries were compared with its neighbouring regional economic bloc in Asia which has a much longer history and a wider membership base i.e ASEAN + 6. From a comparative analysis, it was found that South Asia member states have to work on their governance parameters, improve on their trade linkages and trade tariffs and work towards greater degree of capital account convertibility with adequate safeguards to achieve higher levels of currency market linkages.     

Personality and older consumers’ green behaviour in the UK

The UK government has set an ambitious target of reducing greenhouse gas emissions by 80% before 2050. An interesting segment that could help to achieve this is older consumers, due to their growing numbers. There seems to be a lack of attention, in the research looking specifically at different age categories of older consumers’ green behaviour, and whether their level of greenness can be explained by their personality. Using Socioemotional Selectivity Theory and Time Perspective, the research presented here was designed to provide an exploratory analysis of how the green behaviour of older consumers is explained by their personality types. Based on the responses of 204 older consumers in the UK, our results find the openness personality trait to be positively linked to green behaviour, whilst the extraversion personality trait is negatively related to green behaviour. Although the level of green behaviour increased with older consumers’ age, this did not reach significance.     

Preference purification and the inner rational agent: a critique of the conventional wisdom of behavioural welfare economics

Neoclassical economics assumes that individuals have stable and context-independent preferences, and uses preference satisfaction as a normative criterion. By calling this assumption into question, behavioural findings cause fundamental problems for normative economics. A common response to these problems is to treat deviations from conventional rational choice theory as mistakes, and to try to reconstruct the preferences that individuals would have acted on, had they reasoned correctly. We argue that this preference purification approach implicitly uses a dualistic model of the human being, in which an inner rational agent is trapped in an outer psychological shell. This model is psychologically and philosophically problematic.     

Addressing the social landscape dimensions: The need for reconciling cross scale assessments for capturing Cultural Ecosystem Services (CES)

This special issue integrates eleven papers focussing on indicators able to convey the multiple expectations that society has concerning agricultural land. As scale issues have been so far overlooked within this research topic, a particular focus of this themed issue is to highlight the need for reconciling assessments across scales. The shared purpose of the contributions is to examine how the multiple societal expectations concerning agrarian landscapes might be incorporated into land use policy at different governance levels.A core set of these papers were presented in the symposium “Linking social indicators across scales”, to the European Congress of the International Association of Landscape Ecology (IALE) in September 2013 in Manchester, UK. This symposium was organized to create the time and space for a discussion on the issues of scale when capturing societal preferences concerning agrarian landscapes. While the landscape scale was specifically addressed by four papers, seven papers examined broader geographic units in addition to up-scaling and downscaling issues.     

The contribution of implicit cognition to the Theory of Reasoned Action Model: a study of food preferences

Abstract

Attitudes are at the heart of the Theory of Reasoned Action (TRA), but problems in defining and measuring attitudes have contributed to typically low ability to predict behaviour. This article investigates the impact of potential disjuncture between evaluations that an individual externally verbalises (explicit attitudes), and evaluations that are internally held and may exist outside of conscious awareness (implicit attitudes), on the predictive ability of TRA. We study consumers’ attitudes towards eating healthy food and subsequent behaviour in a context of socially consensual behaviour. An Implicit Association Test (IAT) is used to measure implicit attitudes, and these scores are contrasted with self-reported explicit attitude scores. Ninety one participants took part in the study. We found, surprisingly, that implicit attitude has no significant effect on behavioural intention. However, a disjuncture between an individual’s implicit and explicit attitudes, reflecting internal psychological conflict, affected behaviour.     

Effects of Label on Consumer Preferences: Focus on Hawaiian Avocado Industry

This study examines market challenges facing a local agriculture industry in a small island setting. Examination of the Hawai‘i local avocado industry indicates labeling can address the product information gap between consumers and producers, improve market share, and increase import substitution by local products. Currently, local avocados occupy only 33% of market share, compared with 67% captured by imports. Consumer preferences among local labeled, local unlabeled, and imported avocados were analyzed using multinomial logistic regression. Statistical results showed that labels influence consumers’ decisions to buy local or imported avocados, and their preferences were also influenced by sociodemographic variables, avocado characteristics, and purchasing behavior. Key market segments to target and policy implications are also discussed.     

Forecasting accuracy evaluation of tourist arrivals

This paper evaluates the use of several parametric and nonparametric forecasting techniques for predicting tourism demand in selected European countries. We find that no single model can provide the best forecasts for any of the countries in the short-, medium- and long-run. The results, which are tested for statistical significance, enable forecasters to choose the most suitable model (from those evaluated here) based on the country and horizon for forecasting tourism demand. Should a single model be of interest, then, across all selected countries and horizons the Recurrent Singular Spectrum Analysis model is found to be the most efficient based on lowest overall forecasting error. Neural Networks and ARFIMA are found to be the worst performing models.