Unfavorable weather currently ranks among the major challenges facing agricultural development in many African countries. Impact mitigation through access to reliable and timely weather forecasts and other adaptive mechanisms are foremost in Africa’s policy dialogues and socio-economic development agendas. This paper analyzed the factors influencing access to forecasts on incidence of pests/dis...

We describe the use of the wavelet transform for multivariate data analysis problems. In prediction, a multiscale transform of time-varying data can allow forecasts of each scale, followed by combining of the individual forecasts. The use of a wavelet transform with noise modeling for point pattern clustering can lead to the result, which initially appears counter-intuitive, of clustering in co...

Modeling nominal interest rates requires to take into account the effective lower bound (ELB). We propose a flexible time-series approach that includes “shadow rate”—a notional rate identical actual except when ELB binds . apply this trend-cycle decomposition of and macro-economic variables generates competitive interest-rate forecasts. Our estimates real-rate trend have edged down somewhat in ...

The yield curve, which plots the yield of Treasury bonds against their maturity, is one of the most closely watched financial indicators.1 Many market observers carefully track the yield curve’s shape, which is typically upward sloping and somewhat convex. At times, however, it becomes flat or slopes downward (“inverts,” in Wall Street parlance), configurations that many business economists, fi...

Morphisms are widely used in several branches of scienti c inquiry, but not so much economics. Nevertheless, many conceptual advan- tages the economic modeling from using a categorical setting exist. In this paper, we discuss why morphisms could be successfully injected into and, particular, that allomorphisms, i.e., structure- altering maps re-shape processes, can useful for letting economics ...

We consider forecasting the latent rate profiles of a time series of inhomogeneous Poisson processes. The work is motivated by operations management of queueing systems, in particular, telephone call centers, where accurate forecasting of call arrival rates is a crucial primitive for efficient staffing of such centers. Our forecasting approach utilizes dimension reduction through a factor analy...

conventionally, regression and time series analyses have been employed in modeling water demand forecasts. in recent years, the relatively new technique of neural networks (nns) has been proposed as an efficient tool for modeling and forecasting. the objective of this study is to investigate the relatively new technique of gmdh – type neural networks for the use of forecasting long – term urban...