A Reduced Rank Regression Approach to Tests of Asset Pricing

Both the Arbitrage Pricing Theory (APT) and the Capital Asset Pricing Model (CAPM) place restrictions of the cross-sectional variation of conditional expectations of asset returns and of macro indicators. We show that these restrictions imposed on the reference statistical models lead to special cases of the reduced rank regression model. The maximum likelihood problem is solved by canonical correlation analysis. Likelihood ratio tests about the number of factors underlying stock returns are straightforward to calculate, thus allowing discrimination between competing financial theories. Moreover LR tests on the relevance of each macroeconomic indicator within a chosen model can be implemented. Some of the tests are illustrated by an application to Italian stock market data.     

Dimensions of self-selected leisure activities,trait coping and their relationships with sleep quality and depressive symptoms

Although leisure is presumed to be beneficial, certain profiles of leisure may be especially good. This paper tests whether dimensions of self-selected leisure activities (SSLAs) differentially relate to depressive symptoms and poor sleep quality, including (a) positivity (SSLA-PO), (b) difficulty (SSLA-DF), (c) distraction (SSLA-DI) and (d) thinking about negative events (SSLA-TN). Furthermore, it tests whether those low in perseverative cognitions (PCs) and high in ‘John Henryism’ active coping are equally likely to benefit from leisure. Participants (n = 362, 76% female) at a large university in Wisconsin rated two SSLAs on the dimensions above and completed measures of depression, sleep quality, PCs and active coping. Regression analyses showed that SSLA-TN predicted greater depression and poor sleep quality. For the moderators, more SSLA-DI and SSLA-TN each predicted greater depression for those more prone to PCs, and more SSLA-DI predicted more depression and worse sleep quality at lower active coping levels. Results suggest that not all leisure is equally beneficial, and have implications for the design of leisure-based interventions.     

Does bank capital affect lending behavior?

This paper investigates the existence of cross-sectional differences in the response of lending to monetary policy and GDP shocks owing to differences in bank capitalization. It adds to the literature by using the excess capital-to-asset ratio, which can better control the riskiness of banks' portfolios, and by disentangling the effects of the “bank lending channel” from those of the “bank capital channel.” The results, based on a sample of Italian banks, indicate that bank capital matters in the propagation of different types of shocks to lending, owing to the existence of regulatory capital constraints and imperfections in the market for bank fund-raising.     

The new Capital Accord and banks’ lending decisions

Capital requirements (‘pillar one’ of the new Capital Accord) rising with the increase in borrowers’ PDs were thought as being likely: (i) to have a serious impact on the financing of small and medium-sized enterprises (usually riskier than large corporates) and (ii) to increase the procyclicality of the supply of credit.

The aim of this paper is to provide an empirical evaluation of the possible impact of the new Accord proposals on the lending policies of Italian banks. We compare the interest rate charged to a large set of Italian firms with the cost brought about by the change in the calculation of capital requirements. Since the two variables move together in response to an increase in borrowers’ PDs, we conclude that the new regulatory approach to measuring capital adequacy appears consistent with banks’ own risk evaluations. This result is supported by a ‘stress testing’ exercise: the relationship also holds in a distressed economic scenario, which replicates the financial conditions of the Italian corporate sector in the 1993–1994 recession.     

Network valuation in financial systems

We introduce a general model for the balance‐sheet consistent valuation of interbank claims within an interconnected financial system. Our model represents an extension of clearing models of interdependent liabilities to account for the presence of uncertainty on banks' external assets. At the same time, it also provides a natural extension of classic structural credit risk models to the case of an interconnected system. We characterize the existence and uniqueness of a valuation that maximizes individual and total equity values for all banks. We apply our model to the assessment of systemic risk and in particular for the case of stress testing. Further, we provide a fixed‐point algorithm to carry out the network valuation and the conditions for its convergence.     

ROBUST PORTFOLIOS AND WEAK INCENTIVES IN LONG‐RUN INVESTMENTS

When the planning horizon is long, and the safe asset grows indefinitely, isoelastic portfolios are nearly optimal for investors who are close to isoelastic for high wealth, and not too risk averse for low wealth. We prove this result in a general arbitrage‐free, frictionless, semimartingale model. As a consequence, optimal portfolios are robust to the perturbations in preferences induced by common option compensation schemes, and such incentives are weaker when their horizon is longer. Robust option incentives are possible, but require several, arbitrarily large exercise prices, and are not always convex.     

The Service Sector in Planned Economies of Eastern Europe: Past Experiences and Future Perspectives

The widely shared view of service sector growth in Centrally Planned Economices (CPEs) is that it was hampered by the tremendous industrialisation effort which ‘crowded out ‘service sector employment and investment. After a brief discussion of western and eastern service sector theories, the authors try to show that while the crowding-out thesis is valid for the period of accelerated industrialisation, it cannot be so easily applied to the behaviour of all CPE countries during the post-war period as a whole. They show differentiated time-pattern of employment and investment growth.     

Social Change: Measurement and Theory*

Societal change, which takes a variety of directions and forms and in no way can be assimilated or reduced to a single dimension, is often accompanied by a perception of insufficient understanding and lack of control. There is a frustrated need for mastering complexity and instability, separating the voluntary from the involuntary, the intended from the unintended, opportunities from risks, getting to the real causes and dominating the uncertain implications of social change. Social change catches us unprepared and confused. In this context statistics are generally considered a fundamental instrument of knowledge, but also part of the problem! In the public debate and in the specialized literature, the ability to measure social phenomena through current statistics and indicators is increasingly questioned. Data-it is claimed-are lacking, particularly longitudinal data; their quality (accuracy, relevance, timeliness, comparability, etc.) should be improved; indicators do not provide early warning signals, policy performance evaluation, and a precise indication of outcomes. Statistics cannot be used as a reliable and timely basis for decision making by individuals, organizations, governments, and for understanding these decisions. In some cases, statistics have been accused of giving a misleading and false picture of reality: do we measure the real extent of social exclusion and unemployment? Do we fully capture the quality of life and the degradation of the environment? Mismeasurement has been deemed by some commentators as being responsible for the wrong focus in inflation and stabilization policies, science and technology, unemployment and poverty. The productivity paradox, the informal economy, failure to measure welfare and the quality of urban life are instances where statistics do not seem to provide complete and satisfactory answers to the demand for information and knowledge. Our paper illustrates how, quite independently of measurement techniques and data production processes, the inadequacy of the conceptual framework may explain mismeasurement in relation to complex (multidimensional) and dynamic social phenomena. It is then to social theories, explanations and interpretations that statisticians need to turn, in order to come to grips with the new challenges in social measurement. We will develop this thesis looking at a few cases where measurement issues can be connected to both theoretical and empirical difficulties. The statistical gap which reveals itself in the mismeasurement or difficult measurement of social phenomena is closely interconnected with the social science gap. Only close collaboration between statisticians and social scientists can bring about continuous advancement in social science and quality improvement in social statistics.     

Exploring Postconsumption Guilt and Pride in the Context of Sustainability

This research explores the feelings of guilt and pride experienced by consumers after a purchase decision that involves issues of environmental and social sustainability. Through a multi‐method design, the authors examine key dimensions that influence the process of emotional appraisal, illustrate the characteristics of appraisals of guilt/pride and investigate the consequences that emotions have on future choices. In this exploratory research, when a purchase decision includes an ethical dilemma, consumers were found to express guilt or pride even when the purchase is not intentional, i.e. forced by circumstances. Moreover, the study explores how emotions experienced after decisions may have a positive influence on the future purchase of sustainable alternatives. Finally, the paper proposes a new model that describes the process of emotional appraisal and reports on a number of dimensions that were found to lead to guilt and pride. The insights presented extend knowledge of two key consumer emotions and present important implications for practitioners promoting ethical products.