Search results

Standard market risk optimization tools, based on assumptions of normality, are ineffective for evaluating credit risk. In this article, the authors develop three scenario optimization models for portfolio credit risk. They first create the trading risk profile and find the best hedge position for a single asset or obligor. The second model adjusts all positions simultaneously to minimize the regret of the portfolio subject to general linear restrictions. Finally, a credit risk‐return efficient frontier is constructed using parametric programming. While scenario optimization of quantile‐based credit risk measures leads to problems that are not generally tractable, regret is a relevant and tractable measure that can be optimized using linear programming. The three models are applied to optimizing the risk‐return profile of a portfolio of emerging market bonds.

Uses recently developed techniques in the estimation of non‐stationary time series to construct money demand functions for four African economies, using quarterly data. Finds that money demand depends not only on income, inflation and interest rates, but also on variability of inflation and interest rates: the more variable the return to an asset, the lower its demand. Reports the first quarterly models of money demand (as far as we are aware) in Cameroon, Nigeria and Ivory Coast. Finds that the model for Kenya encompasses existing models. The estimated models have important policy implications. Since high inflation tends to be associated with highly variable inflation, any calculation of the seignorage‐maximizing rate of inflation which ignores the variability effect will overestimate the optimal rate of inflation. Insofar as membership of a monetary union reduces not only the rate of inflation but also its variability, there are extra gains from membership of such a union (Cameroon and Ivory Coast are Franc Zone members; Nigeria and Kenya are not). However, the heter‐ogeneity of the estimated functions suggests that it would be very difficult to have an effective monetary policy were the four countries considered members of the same monetary union.

The standard approach in measuring demand responses and consumer preferences assumes particular parametric models for the consumer preferences and demand functions, and subsequently fits these models to observed data. In principle, the estimated demand models can then be used (i) to test consistency of the data with the theory of consumer behavior, (ii) to infer consumer preferences, and (iii) to predict the consumer's response to, say, new prices following a policy reform. This chapter focuses on an alternative, nonparametric approach. More specifically, we review methods that tackle the earlier issues by merely starting from a minimal set of so-called revealed preference axioms. In contrast to the standard approach, this revealed preference approach avoids the use of parametric models for preferences or demand. The structure of the chapter is as follows. First, we introduce the basic concepts of the revealed preference approach to model consumer demand. Next, we consider issues like goodness-of-fit, power, and measurement error, which are important in the context of empirical applications. Finally, we review a number of interesting extensions of the revealed preference approach, which deal with characteristics models, habit-formation, and the collective model.

The purpose of this paper is to identify the level of natural gas consumption that can be adjudged as capable of improving the growth of the Nigerian economy, to investigate whether natural gas consumption is at optimal level in Nigeria and to examine the nature and rate to which natural gas consumption affects economic growth in Nigeria at low and high regimes.

The tool used to achieve the objectives of the paper is the smooth transition regression (STR) model.

The findings of the paper are that the relationship between natural gas consumption and economic growth in Nigeria is asymmetric, where the natural gas consumption threshold value in the country is 9085.36 standard cubic meters, whereas the level of its consumption in the country is below the optimal level. Further, in both low and high regimes, natural gas consumption has been found to have a positive and significant impact on economic growth in Nigeria.

The policy implication of the paper is that natural gas consumption in Nigeria should not be less than 9085.36 standard cubic meters and the country should intensify efforts to increase the level of natural gas consumption, as it is below the optimal level and its consumption bolsters the growth of Nigerian economy.

What is new in this paper is its ability to use the STR model. To the best of the authors’ knowledge, such methodology has not been adopted before in such a relation.

This chapter presents the differential approach to applied demand analysis. The demand systems of this approach are general, having coefficients that are not necessarily constant. We consider the Rotterdam parameterization of differential demand systems and derive the absolute and relative price versions of the Rotterdam model, due to Theil (1965) and Barten (1966). We address estimation issues and point out that, unlike most parametric and semi-nonparametric demand systems, the Rotterdam model is econometrically regular.

The aim of this paper is to engage with the translation and linking of the “scientific knowledge” of theory on local economic growth with the “practical knowledge” of, on the one hand, local economic policy formulation and, on the other hand, entrepreneurship and entrepreneurship education. The paper uses theoretically informed empirical modelling to identify and prioritise the drivers of local economic growth using data for Australia. The analyses demonstrate the significance of human capital and an enterprise culture in promoting local employment growth. From these results it is suggested that “bottom up” entrepreneurial education and related, but more “top down”, enterprise facilitation are practical mechanisms for achieving such local growth. These results suggest the great importance of translating “scientific knowledge” into “practical knowledge” to allow communities to engage with the knowledge economy.

Develops a finite element analysis and solution strategy for the augmented drift‐diffusion equations in semiconductors device theory using a multilevel scheme. Decouples the drift‐diffusion equations using Gummel iteration with incremental continuation in the applied voltage. Includes augmentation of the carrier mobility to address the issue of non‐local electric field effects (velocity overshoot) within the framework of the drift‐diffusion formulation. Gives comparison results with hydrodynamic and Monte Carlo models and sensitivity studies with respect to the augmentation parameter. Discretizes the equations with a special finite element method using bases of variable polynomial degree. Accomplishes solution of the resulting linear systems with a multilevel method using the basis degree as the grid level. Presents performance results and comparison studies with direct elimination.