Small and Medium Enterprise Financing in Transition Economies

This paper studies the financing status of small and medium enterprises (SMEs) in transition economies. Factors causing financing obstacles are indentified and further analyzed to determine their influence over financing patterns. Bank regulatory practices relevant to SMEs’ access to bank loans and their influence over loan structures are identified. This study contributes to the existing body of knowledge by exploring the impact of specific bank regulatory practices on credit lending to SMEs in transition economies.     

Financial Globalization and Banking Crises in Emerging Markets

Bank crises in emerging economies have been a feature of the recent global crisis, and their incidence has increased in the post-Bretton Woods era. This paper investigates the impact of financial globalization on the incidence of systemic bank crises in 20 emerging markets over the years 1976–2002 using measures of de facto and de jure financial openness. An increase in foreign debt liabilities contributes to an increase in the incidence of crises, but foreign direct investment and portfolio equity liabilities have the opposite effect. A more liberal de jure capital regime lowers the incidence of banking crises, while a regime of fixed exchange rates increases their frequency. The results of the econometric analysis is consistent with the experience of East European and central Asian emerging markets, which attracted a relatively large proportion of capital flows in the form of debt in recent years and have been particularly hard hit by the global financial crisis.     

Inflation and Welfare in Latin America

This paper follows Bailey (J Polit Econ 64:93–110, 1956) and Lucas (Econometrica 68:247–274, 2000) and estimates the welfare cost of inflation for 17 Latin American economies. We use annual data, from 1955 to 2000, and recent advances in the field of applied econometrics to estimate the inflation rate elasticity of money demand and report significantly high and differential welfare cost estimates for these economies.     

Defect Detection Using Unanimous Vote Among Mahalanobis Classifiers for Each Color Component

In manufacturing industries, product inspection is automated and the use of image data is increasingly being employed for defect detection. A manufacturing company in Japan produces an item and inspects the produced products using image data. Reducing the error rate is important in product inspection because poor inspection of products might lead to the delivery of defective products to consumers (consumer’s risk) and strict inspection increases production cost (producer’s risk). To reduce the error rate, we highlighted fault points using a two-dimensional moving range filter and discriminated defect production through a unanimous vote among Mahalanobis classifiers for each color component. For results, we achieved a lower error rate than the current system. This research is an empirical study of how to use image data in defect detection.     

Black–white differences in beliefs about the U.S. restaurant tipping norm: Moderated by socio-economic status?

A re-analysis of two national telephone surveys found that black–white differences in awareness that it is customary to tip a percentage of the bill declined as socio-economic status increased. However, black–white differences in awareness that is customary to tip 15–20 percent in restaurants was unrelated to socio-economic status. The practical as well as theoretical implications of these findings are discussed along with directions for future research.     

Broadband Demand Analysis for Network Building

An increase of broadband demand is forecasted by transitional methods that consider the effect of this increase through many factors, such as customer requirement diversification, and new service introduction and deployment under competition. Broadband demand forecasting has become important for closing the digital divide, promoting regional developments, and constructing networks economically; therefore, a demand forecast model that considers the mechanisms of market structure is necessary. In this paper, a demand analysis method for broadband access combining macro- and micro-data mining is proposed, and the service choice behaviour of customers is introduced as a customer model not only to express the macro trend of market structure, but also to consider area marketing. The proposed method can estimate the potential demand, determine the point at which broadband demand growth peaks in a specified area, and support a decision for ultra high-speed broadband access facility installation.