Do men and women really shop differently? An exploration of gender differences in mall shopping in India

‘Men Buy and Women Shop’ proclaims a new Wharton Research on shopping habits of the American consumer (2007). There is found to be considerable difference in the way men and women shop in the West. Is this true across cultures? Indian retailing is generating considerable interest within the country and abroad. India has been rated as the fifth most attractive emerging retail market and was ranked first in a Global Retail Development Index of 30 developing countries drawn up by A T Kearney. Organized retail, best represented by the mushrooming malls, has come to play a defining role in building and supporting this veritable base of retail consumers. Therefore, it is of utmost interest to retailers and academia alike to understand the consumer dynamics behind the newly evolving consumption culture. This study explores mall‐shopping habits in India and attempts to identify and contrast possible differences between genders using a sample of 2721 mall consumers across seven cities. While the findings suggest that in India there are significant differences in shopping behaviour that can be ascribed to gender, there are fundamental questions about stereotyping of shopping as a feminine activity. To do this, discriminant analysis has been used to study whether shopping orientation and mall‐shopping attitudes can discriminate between male and female shoppers.     

Demand-side factors in optimal land conservation choice

The dominant paradigm of conservation-reserve planning in economics is to optimize the provision of physical conservation benefits given a budget constraint, implicitly assuming the value of biodiversity and ecosystem function is not affected by human proximity to that natural capital. There is evidence, however, that human willingness to pay (WTP) for conservation declines with distance—a phenomenon we call “spatial value decay”. This paper begins a new strand of the conservation planning literature that takes demand-side factors – location of people in the landscape, the degree to which WTP for conservation depends on proximity – into account. We use theoretical models of linear abstract landscapes to explore the impact of demand-side factors on two facets of conservation choices: siting of a single reserve when conservation potential is greatest near a critical site, and siting of multiple reserves when fragmentation reduces physical conservation services produced. Our results show how planners should sometimes employ increased fragmentation to capture value when people's preferences are not very highly localized, and how optimal policy balances proximity to the ecologically critical site with proximity to people. In some scenarios, the payoff to using a reserve design approach that considers demand-side factors is large, but we find that spatial value decay reduces the benefits that can be gained from any conservation-planning approach.     

A comment on Mendeş and Yiğit (2013), ‘Type I error and test power of different tests for testing interaction effects in factorial experiments’, Statistica Neerlandica, 67:1–26

In their advocacy of the rank‐transformation (RT) technique for analysis of data from factorial designs, Mende? and Yi?it (Statistica Neerlandica, 67, 2013, 1–26) missed important analytical studies identifying the statistical shortcomings of the RT technique, the recommendation that the RT technique not be used, and important advances that have been made for properly analyzing data in a non‐parametric setting. Applied data analysts are at risk of being misled by Mende? and Yi?it, when statistically sound techniques are available for the proper non‐parametric analysis of data from factorial designs. The appropriate methods express hypotheses in terms of normalized distribution functions, and the test statistics account for variance heterogeneity.     

Price expectations of sheep and goats by producers and intermediaries in Quetta market,Pakistan

Analysis of producers' and intermediaries' livestock price expectations was used to describe the market in Quetta, the largest livestock market in the highlands of Balochistan Province, Pakistan, and to identify factors that determine price expectations of small ruminants. A total of 4800 expected prices for sheep and goats were collected from producers and market intermediaries at monthly intervals between January 1991 and December 1992. In addition to the expected price of the animal, liveweight, species, sex, breed, body condition (fatness), calendar day and month were recorded, and whether data were collected on a meat or meatless day. Monthly rainfall data were also collected. Models of goat and sheep price expectations were built to compare the similarity of the behaviour of producers and intermediaries. Results indicated that producers and intermediaries expected high prices from November to January and during religious holidays. They expected premiums and discounts related to animals' attributes. Liveweight and seasonality had the strongest effect on prices. Rainfall in the current and previous month was positively related to seller's expected prices suggesting that livestock are retained to take advantage of favourable grazing conditions. The models of price expectations showed that producers adjusted expected goat prices (P ≤ 0.10) for seasonality, liveweight, body condition, age, sex and breed, while they adjusted sheep prices for seasonality and liveweight only. High pay-offs could be expected if extension efforts focused on factors that determine sheep meat quality; however, the retail ceiling price of meat and the lack of grading are a disincentive to work in this direction. Seasonality of supply and demand is important in determining prices and this study provides baseline information for market scheduling; however, scheduling of sales of transhumant pastoralists may be difficult to achieve. Further investigation is justified to understand the gap in marketing knowledge between producers who sell in the villages and those who sell in Quetta.     

An empirical analysis of self-employment in the U.K.

The paper formulates a self-employment/paid-employment choice problem that draws upon Knight's notion that the individual responds to the risk-adjusted relative earnings opportunities in each sector. Based on a development of such choice-theoretic considerations, an econometric model is developed with the purpose of empirically examining the determinants of self-employment. The model features simultaneous determination of employment status and earnings, which allows for self-selectivity. The model is estimated using a sample of 4762 individuals from the General Household Survey for 1978. The estimation of the earnings equation enables a calculation of the self-employment/paid-employment earnings differential and the estimated probit equation for self-employment/paid-employment status facilitates the prediction of the probability of self-employment. The paper finds that there is positive selection bias in the observed earnings of employees, that the probability of self-employment depends positively on the earnings difference between the two sectors and that education and age are significant determinants of self-employment.     

The predictive power of yield spread: evidence from wavelet analysis

This paper examines whether the spread between long- and short-terminterest rates contains information about future economic activity in India. Using the yields on securities with maturities ranging from three months to ten years, we construct five different yield spreads at shorter end, longer end, and policy relevant area of the yield curve. We study the predictive power of each of these spreads for output growth within aggregate and time scale framework using wavelet methodology. We find that predictive power holds only at lower frequencies for the spreads which are constructed at shorter end and policy relevant areas of yield curve. However, spreads which are constructed at the longer end of the yield curve do not seem to have predictive information for output growth.     

Asian Financial Crisis and the Evolution of Korean Banks Efficiency: A DEA Approach

Abstract

In the mid-1990s, the East Asian countries experienced severe financial crisis that were followed by deep economic downturns. A variety of methodologies have been used to understand the nature of the Asian financial crisis. However, the impact of the 1997 Asian financial crisis on the efficiency of the financial industry has yet to be critically examined. By employing the Data Envelopment Analysis (DEA) approach the present study attempts to examine for the first time the impact of the 1997 Asian financial crisis on the efficiency of the Korean banking sector. The study focuses on three major approaches, namely, intermediation, value added, and operating approaches. The results clearly bring forth the high degree of inefficiency in the Korean banking sector, particularly a year after the Asian financial crisis. We find that the Korean banking sector has consistently exhibit higher technical efficiency levels under value added approach, while technical efficiency seems to be lowest under intermediation approach.     

Foreign exchange exposure and impact of policy switch – the case of Malaysian listed firms

This article undertakes an in-depth study of the foreign exchange exposure of Malaysian listed firms. We examine several issues related to firm-specific and overall exposure, including an evaluation of the efficacy of adopting a hard-peg on such exposure. Our sample consists of 158 listed firms and spans the 16 year period, 1990–2005. A multivariate model using four bilateral exchange rates is used to determine firm level exposure while panel data analysis using a random-effects Generalized Least Squares (GLS) model is used to determine system-wide or aggregate sample exposure. We find a total 71% of our sample firms to have significant exchange rate exposure, a rate substantially higher than that reported for most countries, especially developed ones. The US$ is by far the single most important source of exposure with 63% of sample firms exposed to it. The sign of the beta coefficient for three of the four currencies are negative, implying that our sample firms are largely net importers in these currencies. We find exposure to be time variant and dependent on the sector within which a firm operates. Interestingly, the panel data analysis which measures aggregate exposure, shows the US$ to be a significant source of exposure even with the adoption of the hard peg. The change in policy regime to a fixed peg following the crisis appears to have had no impact at either firm-level exposure or overall system-wide exposure.