Mental Accounting in the Housing Market

We use a survey to identify a consumer bias with regard to different sources of debt-financing. Less salient debt may generate psychological benefits. This should be weighed against the possible economic costs of a sub-optimal capital structure; but low levels of financial literacy make it unlikely that all households perceive the full economic costs. As a result there is a bias in favour of less salient debt. In a market with limited scope for arbitrage this consumer bias is likely to generate inefficiencies. We examine such a market in both theory and practice. The predictions of our model are given strong support by market data.Household Finance; Mental Accounting; Co-op; Capital Structure

Prototypes and Strategy: Assigning Causal Credit Using Fuzzy Sets

Strategies often are stylized on the basis of particular prototypes (e.g. differentiate or low cost) whose efficacy is uncertain often due to uncertainty of complex interactions among its elements. Because of the difficulty in assigning causal credit to a given element for an outcome, the adoption of better practices that constitute strategies is frequently characterized as lacking in causal validity. We apply Ragin\u27s (2000) fuzzy logic methodology to identify high performance configurations in the 1989 data set of MacDuffie (1995). The results indicate that discrete prototypes of practices are associated with higher performance, but that the variety of outcomes points to experimentation and search. These results reflect the fundamental challenge of complex causality when there is limited diversity in observed experiments given the large number of choice variables. Fuzzy set methodology provides an approach to reduce this complexity by logical rules that permit an exploration of the simplifying assumptions. It is this interaction between prototypical understandings of strategy and exploration in the absence of data that is the most important contribution of this methodology

Service Quality and Customer Loyalty in a Post-Crisis Context. Prediction-Oriented Modeling to Enhance the Particular Importance of a Social and Sustainable Approach

Research into the influence of service quality on customer loyalty has typically focused on confirming isolated direct causal influences regarding particular dimensions of quality, usually undertaken in the context of positive, firm-customer relations. The present study extends analysis of these factors through a new lens. First, the study was undertaken in a market context following a crisis that has had far-reaching consequences for customers’ relational behaviors. We explore the case of the Spanish banking industry, a sector that accurately reflects these new relational conditions, including a rising demand for more socially responsible banking. Second, we propose a holistic model that combines the effects of four key factors associated with service quality (outcome, personnel, servicescape and social qualities). We also apply an innovative predictive methodological technique using partial least squares (PLS) and qualitative comparative analysis (QCA) that enables us not only to determine the direct causal effects among variables, but also to consider different scenarios in which to predict customer loyalty. The results highlight the role of outcome and social qualities. The novelty of the social qualities factor helps to underscore the importance of social, ethical and sustainable practices to customer loyalty, although personnel and servicescape qualities must also be present to improve the predictive capability of service quality on loyalty

Designing an expert knowledge-based Systemic Importance Index for financial institutions

Defining whether a financial institution is systemically important (or not) is challenging due to (i) the inevitability of combining complex importance criteria such as institutions’ size, connectedness and substitutability; (ii) the ambiguity of what an appropriate threshold for those criteria may be; and (iii) the involvement of expert knowledge as a key input for combining those criteria. The proposed method, a Fuzzy Logic Inference System, uses four key systemic importance indicators that capture institutions’ size, connectedness and substitutability, and a convenient deconstruction of expert knowledge to obtain a Systemic Importance Index. This method allows for combining dissimilar concepts in a non-linear, consistent and intuitive manner, whilst considering them as continuous –non binary- functions. Results reveal that the method imitates the way experts them-selves think about the decision process regarding what a systemically important financial institution is within the financial system under analysis. The Index is a comprehensive relative assessment of each financial institution’s systemic importance. It may serve financial authorities as a quantitative tool for focusing their attention and resources where the severity resulting from an institution failing or near-failing is estimated to be the greatest. It may also serve for enhanced policy-making (e.g. prudential regulation, oversight and supervision) and decision-making (e.g. resolving, restructuring or providing emergency liquidity).Systemic Importance, Systemic Risk, Fuzzy Logic, Approximate Reasoning, Too-connected-to-fail, Too-big-to-fail. Classification JEL: D85, C63, E58, G28.

Framing China: Transformation and Institutional Change

The paper offers a frame for investigating the extent to which decentralisation, and subsequent locally chosen institutions shape private organisational and institutional innovation. To include the numerous locally based “economic regimes†matters as the resulting business system reflects political institution setting and private organisational innovation. Such a frame is a necessary first step for empirical studies attempting to explain the heterogeneity of China’s business systems, the emergence of hybrid organisations, and last but none the least, the different growth rates that can be observed across China.Transition Economy;Institutional Change in China;Private Business Sector

Multilateralising Regionalism: Spaghetti Bowls as Building Blocs on the Path to Global Free Trade

This paper addresses the final steps to global free trade -- the political economy forces that might drive them, and the role the WTO might play in guiding them. Two facts form the departure point: 1) Regionalism is here to stay; 2) the motley assortment of regional trade agreements is not the best way to organise world trade. Moving to global duty-free trade will require a multilateralisation of regionalism. The paper presents the political economy logic of trade liberalisation and uses it to structure a narrative of world trade liberalisation since 1947. The logic is then used to project the world tariff map in 2010, arguing that the pattern will be marked by fractals – fuzzy, leaky trade blocs made up of fuzzy, leaky sub-blocs (fuzzy since the proliferation of FTAs makes it impossible to draw sharp lines around the 3 big blocs, and leaky since some FTAs create free trade ’canals’ linking the blocs). The paper then presents a novel political economy mechanism – spaghetti bowls as building blocs – whereby offshoring creates a force that encourages the multilateralisation of regionalism. Finally, the paper suggests three things the WTO could do to help multilateralise regionalism.

Measuring the shadow economy and its drivers: the case of peripheral EMU countries

We adopt a long-run perspective to investigate the size of the shadow economy and explore the trends in this area. The analysis is based on a panel of peripheral EMU countries over the period 1965-2015. Our empirical approach relies on a multiple indicators and multiple causes (MIMIC) framework. This approach is a variant of structural equation modelling (SEM). We used two sets of variables, (i.e. potential determinants and indicator variables) to estimate an underlying (unobserved) index that measures the evolution of the shadow economy. Ascertaining the relative importance of the shadow economy enabled analysis of its relationship with other institutional and social issues (e.g. corruption, productivity and economic growth), and helped identify the channels through which the shadow economy might negatively influence the performance of different economies. In the sampled countries, shadow activity increased over the study period. It also seemed to be affected by the economic cycle