Wavelet Analysis of the Bombay Stock Exchange Index

The fluctuations in the rate of returns of the Bombay stock exchange are analyzed through wavelet transform. The fluctuations, in various time scales, naturally separated by the wavelets, are subjected to statistical analysis. The localization and multiresolution properties of the wavelets enable one to identify collective behaviour in the stock market and the extent of their influence at various time scales. The Gaussian nature of the rate of returns at certain scales and the periodic nature of the same, at other scales, are clearly brought out by this analysis. The utility of this approach for modeling purpose is also elucidated.

     

THE RELATIONSHIP BETWEEN THE BLACK MARKET AND OFFICIAL EXCHANGE RATES: AN EXAMINATION OF LONG-RUN DYNAMICS IN INDIA

This study is the first to use Johansen's cointegration approach for India in the analysis of the long‐term dynamics between the black and official exchange rates for the period 1953–1993. The study also estimates the long‐run elasticity of the official rate with respect to the black market rate. As monthly data over 40 years are used, and a more robust methodology is employed, the results are likely to be more reliable as compared with the earlier work on India. The results of our study suggest that while there is a long‐term relationship between the two rates, the direction of causality is from the black rate to the official exchange rate. This is plausible in the Indian context where policy has generally lagged behind events in the black market. The hypothesis of a constant black market premium is rejected, implying that there is a mismatch between the percentage change in the official exchange rate and the percentage change in the black market rate.     

Knowledge Management in Supply Chains: The Role of Explicit and Tacit Knowledge

We theorize, building on the knowledge‐based view and the theoretical distinction between explicit and tacit knowledge, that knowledge management capability across the supply chain manifests itself in explicit and tacit knowledge, which in turn effectuates supply chain performance. The model is tested with survey data from 195 small‐ and medium‐sized enterprises reporting on their primary supply chain. The results indicate that the supply chain's knowledge management capability manifests itself in both explicit and tacit knowledge, with the latter being influenced more strongly. Moreover, it was found that while both explicit and tacit knowledge influence supply chain performance, the latter exerts a significantly greater impact than the former. Exploratory post hoc analyses add robustness to these findings and investigate mechanisms inherent to the transformation of tacit into explicit knowledge. Overall, this research contributes to academic theory development in logistics and supply chain management by the dichotomization of knowledge types and the demonstration of their differential magnitude of effects, and to managerial practice by providing important guidance for logistics managers structuring their knowledge management efforts across supply chains.     

The Effect of Probability Distribution Functions of Economic Life on Retirement Alternatives

Economic analysis, supported by computer hardware and software, can easily overwhelm a decision maker with data. However, this data can be organized in a readily understandable way using well-designed graphs. Some simple guidelines suggest substantial improvements over available examples from papers and textbooks. Although these graphs and sensitivity analyses are useful in many quantitative problems, the long-range focus of engineering economy and its concomitant uncertainty dramatically increase their value.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.     

Role of quality management capabilities in developing market-based organisational learning capabilities: Case study evidence from four Indian business process outsourcing firms

Business-to-business marketing literature acknowledges the value firms, including business process outsourcing firms, realise through their supplier networks. Such value realisation is often possible through a dynamic exchange of complementary organisational capabilities between a firm and its network partners. However, little is known about how outsourcing firms develop these capabilities and thus realise value. This paper addresses an unexplored theoretical gap of developing market-based organisational learning capabilities in business process outsourcing firms. Using a capabilities lens, this study assesses the impact of quality management capabilities in developing market-based organisational learning capability. Findings from a case study of four business process outsourcing firms in India suggest that effective knowledge transfer, diffusion and the development of market-based organisational learning capabilities are contingent upon the strength of a firm's quality management capabilities. Implications for theory and practice are discussed.     

Optimal trade policy with quality-differentiated goods

In this article we apply the model of vertically differentiated products to international trade. A foreign firm competes with a domestic firm in the latter's market, producing products of varying quality. We examine the nature of the equilibrium in this case, assuming the firms compete in prices. Contrary to the popular belief, we show that a protectionist policy of imposing a tariff on the foreign firm raises overall welfare in the domestic economy, as well as induces the domestic firm to upgrade the quality of its product, if it produces the lower quality product. Furthermore, if minimum quality standards are imposed on the foreign firm, the domestic firm upgrades quality, and overall welfare in the domestic economy is higher.     

Fair welfare maximization

We consider the general problem of finding fair constrained resource allocations. As a criterion for fairness we propose an inequality index, termed “fairness ratio,” the maximization of which produces Lorenz-undominated, Pareto-optimal allocations. The fairness ratio does not depend on the choice of any particular social welfare function, and hence it can be used for an a priori evaluation of any given feasible resource allocation. The fairness ratio for an allocation provides a bound on the discrepancy between this allocation and any other feasible allocation with respect to a large class of social welfare functions. We provide a simple representation of the fairness ratio as well as a general method that can be used to directly determine optimal fair allocations. For general convex environments, we provide a fundamental lower bound for the optimal fairness ratio and show that as the population size increases, the optimal fairness ratio decreases at most logarithmically in what we call the “inhomogeneity” of the problem. Our method yields a unique and “balanced” fair optimum for an important class of problems with linear budget constraints.