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This paper examines the impact of the assassination of Mexico’s leading presidential candidate on Mexican Brady bonds and its spillover effects to other emerging financial markets. On the day of the assassination, Mexican Brady bonds declined by a significant 0.97 percent and continued to experience significant declines over the following three trading sessions. However, with the naming of Ernesto Zedillo as the ruling party’s presidential candidate, Mexican Brady bonds recovered over 75 percent of the losses incurred during the previous four trading days. The assassination did not significantly affect other emerging financial markets. The availability of a $6 billion swap facility, holding of large foreign reserves, selection of Ernesto Zedillo, and well managed responses by the Mexican government all served to attenuate spillover effects from the Mexican political crisis.

When faced with a financial crisis, debtor countries rarely choose to default on their international financial obligations. Instead, they typically choose to renegotiate their debt service obligations. According to a number of economists, the main motivating factor behind borrowers' and creditors' willingness to restructure is the benefit associated with preserving international trade ties. This raises an interesting question: is the benefit associated with maintaining international trade ties shared equally between the borrower and creditor banks? Or is the outcome dependent on a so-called ‘bargaining game’ between the borrower and creditor banks, and if so, can we identify these variables? According to our analysis, as a borrower's trade ties with developed countries strengthen, the borrower's (and/or creditor's) bargaining power diminishes (strengthens) and it thereafter agrees to restructure at less favourable terms. However, even after controlling for trade ties, we found that major borrowers were able to extract more concessions from the lenders.

This paper examines the determinants of corporate dividend policy in Jordan. The study uses a firm‐level panel data set of all publicly traded firms on the Amman Stock Exchange between 1989 and 2000. The study develops eight research hypotheses, which are used to represent the main theories of corporate dividends. A general‐to‐specific modeling approach is used to choose between the competing hypotheses. The study examines the determinants of the amount of dividends using Tobit specifications. The results suggest that the proportion of stocks held by insiders and state ownership significantly affect the amount of dividends paid. Size, age, and profitability of the firm seem to be determinant factors of corporate dividend policy in Jordan. The findings provide strong support for the agency costs hypothesis and are broadly consistent with the pecking order hypothesis. The results provide no support for the signaling hypothesis.

The fact that stocks going ex‐dividend decline in price by less than the dividend amount is theoretically attributed to the differential taxation of dividend and capital gains or the differential taxation of investor groups. NYSE, Amex and Toronto Stock Exchange listed stocks, and stocks interlisted on these three exchanges, are examined to infer the tax jurisdiction of the marginal investor. The stock price changes relative to the dividends are consistent with a tax clientele effect. Further, the stock price changes are plausible given the tax rates. Ex‐dividend day behavior is different for non‐interlisted stocks on all three exchanges, suggesting each exchange has a different tax clientele. Canadian firms interlisted on US exchanges exhibit ex‐dividend day behavior consistent with the appropriate US exchange’s non‐interlisted stocks, suggesting that the marginal investors in these stocks are American.

The purpose of this paper is to address the potential impact of need for touch (NFT) on perceived product quality and the possible roles of purchasers’ social (subjective norms), personal (buying impulsiveness) and epistemic (e-commerce orientation) factors, as well as the likely interaction effect of the shopping channel.

The empirical study is based on 540 observations, analysed in a partial least squares structural equation model.

The link between the NFT and perceived quality tends to be negative, especially for online purchases. E-commerce orientation reduces the need to touch products, but subjective norms and buying impulsiveness have no significant effects.

The NFT scale might be improved by adding more items. Some of the structural model coefficients indicate a low effect size. Finally, the results are limited to Spanish purchasers of the focal product.

Firms should appeal to purchasers’ e-commerce orientation to reduce the negative implications of a need to touch products among consumers shopping online.

The need to touch a product may be an obstacle to online purchases, yet few studies deal with its impact in online, relative to offline, contexts to evaluate product quality. This study also integrates personal, social and epistemic factors.

Emerging financial markets have largely proven resilient to the consequences of the Global Financial Crisis. While this owes much to the bitter experience and economic strategies developed and implemented following the Asian Financial Crisis of 1997–1998, providence also played a hand in that relatively few of its financial institutions were exposed to the complex structured products that underpinned the demise of many financial intermediaries in the United States and Europe. The objective of this volume is to investigate and assess the impact and response to the crisis in emerging markets from a number of perspectives. These include asset pricing, contagion, financial intermediation, market structure and regulation. Our hope is that the assembled chapters offer clear insights into the complex financial arrangements that now link emerging and developed financial markets in the current economic environment. The volume spans four dimensions: first, a series of background studies offer explanations of the causes and impacts of the crisis on emerging markets more generally; then, implications are considered. The third and final sections provide insights from regional and country-specific perspectives.

Presents a special issue, enlisting the help of the author’s students and colleagues, focusing on age, sex, colour and disability discrimination in America. Breaks the evidence down into manageable chunks, covering: age discrimination in the workplace; discrimination against African‐Americans; sex discrimination in the workplace; same sex sexual harassment; how to investigate and prove disability discrimination; sexual harassment in the military; when the main US job‐discrimination law applies to small companies; how to investigate and prove racial discrimination; developments concerning race discrimination in the workplace; developments concerning the Equal Pay Act; developments concerning discrimination against workers with HIV or AIDS; developments concerning discrimination based on refusal of family care leave; developments concerning discrimination against gay or lesbian employees; developments concerning discrimination based on colour; how to investigate and prove discrimination concerning based on colour; developments concerning the Equal Pay Act; using statistics in employment discrimination cases; race discrimination in the workplace; developments concerning gender discrimination in the workplace; discrimination in Japanese organizations in America; discrimination in the entertainment industry; discrimination in the utility industry; understanding and effectively managing national origin discrimination; how to investigate and prove hiring discrimination based on colour; and, finally, how to investigate sexual harassment in the workplace.

Considers the factors which influence Taiwanese decisions to buy Japanese or US refrigerators, basing the conclusions on the results of a survey of 586 respondents drawn from Taiwan’s four largest cities – Taipei, Kaoshiung, Taichung and Tainan. Describes how the questionnaires were constructed and pretested, and explains how the data was recorded (using a 5‐point Likert‐type scale) and analysed (using factor analysis and t‐tests). Tests particularly for cultural values of the Chinese, consumer ethnocentrism, openness to foreign culture, country image, and consumer sophistication. Finds that, despite the longer presence of Japanese goods in Taiwan, Japan’s proximity to Taiwan, and more cultural similarities between the Japanese and Taiwanese, Taiwanese consumers rate the USA’s country image factor higher than Japan’s, with consequent implications regarding intention to buy US goods. Recommends that US marketers build on their advantageous country image when they promote US appliances in foreign markets. Cautions against making too much of this snapshot data but concedes that further research into different foreign markets, different appliances, and with a longitudinal approach, would ascertain if findings are consistent with this survey, which has obvious benefits as new markets, such as China and India, open up to western goods and appliances.

Gene selection is considered as the fundamental process in the bioinformatics field. The existing methodologies pertain to cancer classification are mostly clinical basis, and its diagnosis capability is limited. Nowadays, the significant problems of cancer diagnosis are solved by the utilization of gene expression data. The researchers have been introducing many possibilities to diagnose cancer appropriately and effectively. This paper aims to develop the cancer data classification using gene expression data.

The proposed classification model involves three main phases: “(1) Feature extraction, (2) Optimal Feature Selection and (3) Classification”. Initially, five benchmark gene expression datasets are collected. From the collected gene expression data, the feature extraction is performed. To diminish the length of the feature vectors, optimal feature selection is performed, for which a new meta-heuristic algorithm termed as quantum-inspired immune clone optimization algorithm (QICO) is used. Once the relevant features are selected, the classification is performed by a deep learning model called recurrent neural network (RNN). Finally, the experimental analysis reveals that the proposed QICO-based feature selection model outperforms the other heuristic-based feature selection and optimized RNN outperforms the other machine learning methods.

The proposed QICO-RNN is acquiring the best outcomes at any learning percentage. On considering the learning percentage 85, the accuracy of the proposed QICO-RNN was 3.2% excellent than RNN, 4.3% excellent than RF, 3.8% excellent than NB and 2.1% excellent than KNN for Dataset 1. For Dataset 2, at learning percentage 35, the accuracy of the proposed QICO-RNN was 13.3% exclusive than RNN, 8.9% exclusive than RF and 14.8% exclusive than NB and KNN. Hence, the developed QICO algorithm is performing well in classifying the cancer data using gene expression data accurately.

This paper introduces a new optimal feature selection model using QICO and QICO-based RNN for effective classification of cancer data using gene expression data. This is the first work that utilizes an optimal feature selection model using QICO and QICO-RNN for effective classification of cancer data using gene expression data.