Measuring Integrated Market and Credit Risk in Bank Portfolios: An Application to a Set of Hypothetical Banks Operating in South Africa

The banking crises of the ‘90s emphasize the need to model the connections between financial environment volatility and the potential losses faced by financial institutions resulting from correlated market and credit risks. Due to the number of variables that must be modeled and the complexity of the relationships an analytical solution is not feasible. We present here a numerical solution based on a simulation model that explicitly links changes in the relevant variables that characterize the financial environment and the distribution of possible future bank capital ratios. This forward looking quantitative risk assessment methodology allows banks and regulators to identify potential risks before they materialize and make appropriate adjustments to bank portfolio credit qualities, sector and region concentrations, and capital ratios on a bank by bank basis. It also has the potential to be extended so as to assess the risks of correlated failures among a group of financial institutions (i.e., systemic risk analyses). This model was applied by the authors to the study of the risk profile of the largest South African Banks in the context of the Financial System Stability Assessment program undertaken by the IMF in 1999. In the current study, we apply the model to various hypothetical banks operating in the South African financial environment and assess the correlated market and credit risks associated with business lending, mortgage lending, asset and liability maturity matches, foreign lending and borrowing, and direct equity, real estate, and gold investments. It is shown to produce simulated financial environments (interest rates, exchange rates, equity indices, real estate price indices, commodity prices, and economic indicators) that match closely the assumed parameters, and generate reasonable credit transition probabilities and security prices. As expected, the credit quality and diversification characteristics of the loan portfolio, asset and liability maturity mismatches, and financial environment volatility, are shown to interact to determine bank risk levels. We find that the credit quality of a bank's loan portfolio is the most important risk factor. We also show the risk reduction benefits of diversifying the loan portfolio across various sectors and regions of the economy and the importance of accounting for volatility shocks that occur periodically in emerging economies. Banks with high credit risk and concentrated portfolios are shown to have a high risk of failure during periods of financial stress. Alternatively, banks with lower credit risk and broadly diversified loan portfolios across business and mortgage lending are unlikely to fail even during very volatile periods. Asset and liability maturity mismatches generally increase bank risk levels. However, because credit losses are positively correlated with interest rate increases, banks with high credit risk may reduce overall risk levels by holding liabilities with longer maturities than their assets. Risk assessment methodologies which measure market and credit risk separately do not capture these various interactions and thus misestimate overall risk levels.     

Global marketing of industrial products: Are interpersonal relationships always critical?

The present paper examines the issue of whether interpersonal relationships are critical for global marketing of industrial products. The fields of relationship marketing, IMP group research, sales research, and network theory have stressed the importance of interpersonal relationships in the business-to-business or industrial marketing context. In contrast to this emphasis on interpersonal relationships, we argue that industrial firms can both conceive and enhance marketing strategies based on developing high quality and consistent processes, products, services or outcomes (consistent processes and outcomes). Such strategies are especially important given the fact that developing interpersonal relationships is expensive due to their reliance on frequent and/or face-to-face communications. In this paper, we examine industry and country contexts that lead to the choice of alternative industrial product marketing strategies and highlight some future research directions and managerial implications.     

Consumer Trial,Continuous Use,and Economic Benefits of a Retail Service Innovation: The Case of the Personal Shopping Assistant

Service innovations in retailing have the potential to benefit consumers as well as retailers. This research models key factors associated with the trial and continuous use of a specific self‐service technology (SST), the personal shopping assistant (PSA), and estimates retailer benefits from implementing that innovation. Based on theoretical insights from prior SST studies, diffusion of innovation literature, and the technology acceptance model (TAM), this study develops specific hypotheses and tests them on a sample of 104 actual users of the PSA and 345 nonusers who shopped at the retail store offering the PSA device. Results indicate that factors affecting initial trial are different from those affecting continuous use. More specifically, consumers' trust toward the retailer, novelty seeking, and market mavenism are positively related to trial, while technology anxiety hinders the likelihood of trying the PSA. Perceived ease of use of the device positively impacts continuous use while consumers' need for interaction in shopping environments reduces the likelihood of continuous use. Importantly, there is evidence on retailer benefits from introducing the innovation since consumers using the PSA tend to spend more during each shopping trip. However, given the high costs of technology, the payback period for recovery of investments in innovation depends largely upon continued use of the innovation by consumers. Important implications are provided for retailers considering investments in new in‐store service innovations. Incorporation of technology within physical stores affords opportunities for the retailer to reduce costs, while enhancing service provided to consumers. Therefore, service innovations in retailing have the potential to benefit consumers as well as retailers. This research models key factors associated with the trial and continuous use of a specific SST in the retail context, the PSA, and estimates retailer benefits from implementing that innovation. In so doing, the study contributes to the nascent area of research on SSTs in the retail sector. Based on theoretical insights from prior SST studies, diffusion of innovation literature, and the TAM, this study develops specific hypotheses regarding the (1) antecedent effects of technological anxiety, novelty seeking, market mavenism, and trust in the retailer on trial of the service innovation; (2) the effects of ease of use, perceived waiting time, and need for interaction on continuous use of the innovation; and (3) the effect of use of innovation on consumer spending at the store. The hypotheses were tested on a sample of 104 actual users of the PSA and 345 nonusers who shopped at the retail store offering the PSA device, one of the early adopters of PSA in Germany. Data were analyzed using logistic regression (antecedents of trial), multiple regression (antecedents of continuous use), and propensity score matching (assessing retailer benefits). Results indicate that factors affecting initial trial are different from those affecting continuous use. More specifically, consumers' trust toward the retailer, novelty seeking, and market mavenism are positively related to trial, while technology anxiety hinders the likelihood of trying the PSA. Perceived ease of use of the device positively impacts continuous use, while consumers' need for interaction in shopping environments reduces the likelihood of continuous use. Importantly, there is evidence on retailer benefits from introducing the innovation since consumers using the PSA tend to spend more during each shopping trip. However, given the high costs of technology, the payback period for recovery of investments in innovation depends largely upon continued use of the innovation by consumers. Important implications are provided for retailers considering investments in new in‐store service innovations. The study contributes to the literature through its (1) simultaneous examination of antecedents of trial and continuous usage of a specific SST, (2) the demonstration of economic benefits of SST introduction for the retailer, and (3) contribution to the stream of research on service innovation, as against product innovation.     

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Die vernetzte Pflegeplanung – Medikamentenblatt, ?rztliche Verordnung, der Basis-Status, die Status-Planungs-B?gen, das Ressourcen-F?higkeiten-Blatt – an Formularen ist in der Pflege kein Mangel. Doch immer neue Formulare machen aus einem ursprünglich guten Dokumentationssystem oftmals eine Loseblatt-Sammlung. Im Rahmen eines Projektes in der station?ren Altenpflege versuchte man, Doppeldokumentationen auf ein Minimum zu reduzieren und den Verlauf der Anamnese auf einen Blick zu erm?glichen.     

Inflation und Schuldenabbau

The European Central Bank (ECB) recently announced its willingness to do whatever is needed to save the euro. This has raised the question whether such a role of the ECB must lead to higher rates of infl ation. Under current recessive macroeconomic conditions in the eurozone, the ECB’s expansionary monetary policy will not lead to higher infl ation. On the contrary, there is a serious danger of defl ation. Higher infl ation would likely occur only if a permanent stabilisation function were assigned to the ECB. Yet historical examples show that mistakes can be made. During the stagnation in Japan, US economists heavily criticised the Bank of Japan’s timid monetary policy response. But in some sense, current Fed policy seems to be a direct copy of that strategy, caused by uncertainty about the proper communication channel. An infl ation tax could help to bring down the mounting public debt in the wake of the fi nancial crisis, but higher wealth taxes have more transparent distributional effects.     

Trans‐Tasman Transmission of Government Spending Shocks

This paper investigates the international transmission of fiscal shocks between two closely‐linked, open economies. We estimate impulse response functions using a semi‐structural vector auto regressive (VAR) model and quarterly data from Australia and New Zealand for the period 1973:3–2008:4. We compare our empirical results with impulse response functions from a calibrated two‐country international real business cycle model with habit formation and adjustment costs to investment. We show that a positive shock to Australian government consumption leads to an increase in Australian output initially and then to a decline in the medium term, while the New Zealand output is negatively affected both in the short and medium term. This result is in line with the recent literature that reports beggar‐thy‐neighbour effect of positive government spending shocks.     

Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP*

In this article, we merge two strands from the recent econometric literature. First, factor models based on large sets of macroeconomic variables for forecasting, which have generally proven useful for forecasting. However, there is some disagreement in the literature as to the appropriate method. Second, forecast methods based on mixed‐frequency data sampling (MIDAS). This regression technique can take into account unbalanced datasets that emerge from publication lags of high‐ and low‐frequency indicators, a problem practitioner have to cope with in real time. In this article, we introduce Factor MIDAS, an approach for nowcasting and forecasting low‐frequency variables like gross domestic product (GDP) exploiting information in a large set of higher‐frequency indicators. We consider three alternative MIDAS approaches (basic, smoothed and unrestricted) that provide harmonized projection methods that allow for a comparison of the alternative factor estimation methods with respect to nowcasting and forecasting. Common to all the factor estimation methods employed here is that they can handle unbalanced datasets, as typically faced in real‐time forecast applications owing to publication lags. In particular, we focus on variants of static and dynamic principal components as well as Kalman filter estimates in state‐space factor models. As an empirical illustration of the technique, we use a large monthly dataset of the German economy to nowcast and forecast quarterly GDP growth. We find that the factor estimation methods do not differ substantially, whereas the most parsimonious MIDAS projection performs best overall. Finally, quarterly models are in general outperformed by the Factor MIDAS models, which confirms the usefulness of the mixed‐frequency techniques that can exploit timely information from business cycle indicators.