Statistical properties of returns: Financial assets versus commercial real estate

This study examines the distribution of commercial real estate returns by region (east, midwest, south, and west), by property type (office, retail, R&D office, and warehouse) and in the aggregate, and compares their distributions to those of financial assets. Nominal and real returns are examined for quarterly, semiannual, and annual periods. The quarterly nominal returns on the financial assets are mostly normal with very little indication of autocorrelation. In contrast, non-normality and autocorrelation are present in most of the nominal quarterly real estate series. The non-normality is greatly reduced when semiannual or annual returns are considered or when the quarterly series are corrected for autocorrelation. The non-normality is also lower for real returns than it is for nominal returns.     

Household Saving in Developing Countries: First Cross-Country Evidence

Although most studies have relied on domestic or private sectorsaving data, this article uses household data available fromthe U.N. System of National Accounts for a sample of 10 countries.Household saving functions are estimated using combined time-seriesand cross-country observations in order to test households'responses to income and growth, rates of return, monetary wealth,foreign saving, and demographic variables. The results showthat income and wealth variables affect saving strongly andin ways consistent with standard theories. Inflation and theinterest rate do not show clear effects on saving, which isalso consistent with their theoretical ambiguity. Foreign savingand monetary assets have strong negative effects on householdsaving, which suggests the importance of liquidity constraintsand monetary wealth in developing countries.     

Economic, Demographic, and Institutional Determinants of Life Insurance Consumption across Countries

Life insurance has become an increasingly important part ofthe financial sector over the past 40 years, providing a rangeof financial services for consumers and becoming a major sourceof investment in the capital market. But what drives the largevariation in life insurance consumption across countries remainsunclear. Using a panel with data aggregated at different frequenciesfor 68 economies in 1961–2000, this article finds thateconomic indicators—such as inflation, income per capita,and banking sector development—and religious and institutionalindicators are the most robust predictors of the use of lifeinsurance. Education, life expectancy, the young dependencyratio, and the size of the social security system appear tohave no robust association with life insurance consumption.The results highlight the importance of price stability andbanking sector development in fully realizing the savings andinvestment functions of life insurance in an economy.     

Accounting for optimism and pessimism in expected utility

We provide a preference foundation for decision under risk resulting in a model where probability weighting is linear as long as the corresponding probabilities are not extreme (i.e., 0 or 1). This way, most of the elegance and mathematical tractability of expected utility is maintained and also much of its normative foundation. Yet, the new model can accommodate the extreme sensitivity towards changes from 0 to almost impossible and from almost certain to 1 that has widely been documented in the experimental literature. The model can be viewed as “expected utility with the best and worst in mind” as suggested by Chateauneuf, Eichberger and Grant (Chateauneuf, Alain, Eichberger, Jürgen, Grant, Simon, 2007. Choice under uncertainty with the best and worst in mind: NEO-Additive capacities. Journal of Economic Theory 137, 538–567) or, following our preference foundation, interpreted as “expected utility with consistent optimism and pessimism”.     

Social Exclusion—New Language, New Challenges for Local Authorities

National policy initiatives such as the establishment of the Social Exclusion Unit and the new government strategy, 'Opportunity for All', have provided a new stimulus to local authorities to develop more effective local strategies to promote social inclusion. The major features of current local initiatives are described, and the leadership and management challenges presented to local authorities are discussed. However, for local government to tackle social exclusion and poverty more effectively it is also necessary for the structural and regional dimensions of social exclusion to be taken more into account by central government, and for a new equilibrium between central, regional and local initiative to be achieved.     

Developing parsimonious retailer equity indexes using partial least squares analysis: a method and applications

The information that a retailer’s name communicates to consumers can be a source of competitive advantage for many retailers. Indeed, retailers develop a kind of brand equity, which we refer to as “retailer equity.” To aid both practitioners and researchers, we outline a method, using partial least squares (PLS) analysis for developing parsimonious measures for retailer equity. In addition, we provide four illustrations of possible ways that the index can be used by retailers: (1) as a benchmarking tool, (2) as an indicator of the success (failure) of marketing strategies and tactics, (3) as a means to evaluate the attractiveness of market segments, and (4) as an instrument to examine the relative importance of the various components of retailer equity for specific retailers. The index also provides a means for marketing researchers to examine potential antecedents and outcomes of retailer equity.