Airline mergers and multimarket contact

This paper examines changes in the pricing behavior of airline firms around mergers that occurred during 1985–8. We find that the changes in concentration, a measure of contact within a market, and changes in multimarket contact, a measure of contact with the same firms outside of that market, significantly affect airfares. Further, increases in multimarket contact alone are sufficient to effect an increase in fares. Antitrust policy must consider changes not only in concentration but also in multimarket contact to evaluate more fully the effect of consolidations on consumers.     

Role of Shopping Values and Web Atmospherics in E-Satisfaction and Repurchase Intention

Expected to touch US$55 billion in 2016, the e-commerce market in India presents an unprecedented growth opportunity for retailers. Existing studies have identified factors influencing shoppers’ online behaviour pertaining to the developed economies. Hence, it becomes pertinent to validate these antecedents for the economies like India. The article addresses this gap by examining the role of shopping values and web atmospherics, on e-satisfaction of Indian shoppers. Using multiple regression analysis, it also examines the influence of e-satisfaction on repurchase intention. The findings suggest that effectiveness of information content has the most significant impact on e-satisfaction. Web entertainment, utilitarian values and web informativeness are the other influencing factors. Contrary to the earlier studies, this study didn’t find any influence of hedonic shopping values on shoppers’ satisfaction. Also, e-satisfaction was found to have a positive influence on repurchase intention of e-shoppers. The article suggests select strategies that can be adopted by e-retailers.     

An Approach to Assess the Importance of Brand Equity in Acquisition Decisions

Many firms acquire other firms with well-known and proven brands to hedge against the high costs and risks of new product development. A critical question in these acquisition decisions involves the assessment of the importance of brand equity to the acquiring firm. Since the brand equity benefits can vary by firm (and also by the decision maker within a firm) a critical question is how can one systematically decipher the effect of brand equity in acquisition decisions. Using the balance model [8,15], Vijay Mahajan, Vithala Rao, and Rajendra Srivastava present a methodology to determine the importance of brand equity in acquisition decisions. By capturing the idiosyncratic perceived importance of brand equity of every decision maker involved in acquisition decisions, the methodology enables members of a committee within a firm to understand and reconcile their differences in evaluating potential acquisitions. This methodology is applied in a pilot study for the all-suites segment of the hotel industry with data collected from senior executives of five major hotel chains. The authors also discuss benefits, limitations, and further extensions of the suggested approach.     

Simplified Jackknife Variance Estimates for Fuzzy Measures of Multidimensional Poverty

In this paper, we present a practical methodology for variance estimation for multi‐dimensional measures of poverty and deprivation of households and individuals, derived from sample surveys with complex designs and fairly large sample sizes. The measures considered are based on fuzzy representation of individuals' propensity to deprivation in monetary and diverse non‐monetary dimensions. We believe this to be the first original contribution for estimating standard errors for such fuzzy poverty measures. The second objective is to describe and numerically illustrate computational procedures and difficulties in producing reliable and robust estimates of sampling error for such complex statistics. We attempt to identify some of these problems and provide solutions in the context of actual situations. A detailed application based on European Union Statistics on Income and Living Conditions data for 19 NUTS2 regions in Spain is provided.     

Policy Determinants of School Outcomes under Model Uncertainty: Evidence from South Africa

In this paper, we assess the determinants of secondary school outcomes in South Africa. We use Bayesian model averaging techniques to account for uncertainty in the set of underlying factors that are chosen among a very large pool of explanatory variables in order to identify the subset of explanatory variables most strongly associated with the dependent variable. Our analysis indicates that the socio‐economic background of pupils, demographic characteristics such as population groups (Black and White), as well as geographical locations account for a significant variation in pupils’ achievement levels. We also find that the most robust policy determinants of pupils’ test scores are the availability of a library at school, the use of IT in the classroom as well as school climate.     

Portfolio choice and equilibrium in capital markets with safety-first investors

This paper develops optimal portfolio choice and market equilibrium when investors behave according to a generalized lexicographic safety-first rule. We show that the mutual fund separation property holds for the optimal portfolio choice of a risk-averse safety-first investor. We also derive an explicit valuation formula for the equilibrium value of assets. The valuation formula reduces to the well-known two-parameter capital asset pricing model (CAPM) when investors approximate the tail of the portfolio distribution using Tchebychev's inequality or when the assets have normal or stable Paretian distributions. This shows the robustness of the CAPM to safety-first investors under traditional distributional assumptions. In addition, we indicate how additional information about the portfolio distribution can be incorporated to the safety-first valuation formula to obtain alternative empirically testable models.     

The effect of estimation risk on optimal portfolio choice

This paper determines the effect of estimation risk on optimal portfolio choice under uncertainty. In most realistic problems, the parameters of return distributions are unknown and are estimated using available economic data. Traditional analysis neglects estimation risk by treating the estimated parameters as if they were the true parameters to determine the optimal choice under uncertainty. We show that for normally distributed returns and ‘non-informative’ or ‘invariant’ priors, the admissible set of portfolios taking the estimation uncertainty into account is identical to that given by traditional analysis. However, as a result of estimation risk, the optimal portfolio choice differs from that obtained by traditional analysis. For other plausible priors, the admissible set, and consequently the optimal choice, is shown to differ from that in traditional analysis.