Urban bioclimatology in developing countries

A brief review of the literature on urban human bioclimatology in the tropics is undertaken. Attempts to chart human bioclimatic conditions on the regional/local scale have been made in several developing countries. The effective temperature scheme (with all its limitations) is the one that has been most frequently applied. The possibilities of application of bioclimatic models based on human heat balance for the tropical urban environment are discussed.     

The use of non-time series information in sales forecasting: A case study

The contribution of product and industry knowledge to the accuracy of sales forecasting was investigated by examining the company forecasts of a leading manufacturer and marketer of consumable products. The company forecasts of 18 products produced by a meeting of marketing, sales, and production personnel were compared with those generated by the same company personnel when denied specific product knowledge and with the forecasts of selected judgemental and statistical time series methods. Results indicated that product knowledge contributed significantly to forecast accuracy and that the forecast accuracy of company personnel who possessed industry forecasting knowledge (but not product knowledge) was not significantly different from the time series based methods. Furthermore, the company forecasts were more accurate than averages of the judgemental and statistical time series forecasts. These results point to the importance of specific product information to forecast accuracy and accordingly call into question the continuing strong emphasis on improving extrapolation techniques without consideration of the inclusion of non-time series knowledge.     

Integrating time-series and end-use methods to forecast electricity sales

Two types of forecasting methods have been receiving increasing attention by electric utility forecasters. The first type, called end-use forecasting, is recognized as an approach which is well suited for forecasting during periods characterized by technological change. The method is straightforward. The stock levels of energy-consuming equipment are forecast, as well as the energy consumption characteristics of the equipment. The final forecast is the product of the stock and usage characteristics. This approach is well suited to forecasting long time periods when technological change, equipment depletion and replacement, and other structural changes are evident. For time periods of shorter duration, these factors are static and variations are more likely to result from shocks to the environment. The shocks influence the usage of the equipment. A second forecasting approach using time-series analysis has been demonstrated to be superior for these applications. This paper discusses the integration of the two methods into a unified system. The result is a time-series model whose parameter effects become dynamic in character. An example of the models being used at the Georgia Power Company is presented. It is demonstrated that a time-series model which incorporates end-use stock and usage information is superior—even in short-term forecasting situations—to a similar time-series model which excludes the information.     

发达国家的国家创新战略对我国的启示

本文探讨了发达国家的国家创新战略比较注重、而我国比较忽视的五个方面.一、加强中小学科学教育,从小培养国民的创新思维和创新能力;二、积极支持中小企业在创新活动中发挥关键作用;三、设立具体明确、具有可检验性的创新战略目标;四、注重发挥产业界在创新战略制定中的作用;五、将公众的支持和消费者的参与视为创新成功的重要因素.     

From the editors

Political forecasting provides the contextuality needed for decision-making and for forecasting ‘non-political’ trends. To gear political forecasting to these needs, rather than mimicking approaches in other areas, requires recognition of the distinctive nature of political trends, and realism regarding forecast uses, which generally do not benefit from ‘precise’ probabilities, predictions of only major events, or ‘sophisticated’ methodology that sacrifices comprehensiveness for explicitness. Approaches borrowed from other forecasting disciplines have been counterproductive, although contextual approaches, including cross-impact analyses and developmental constructs that integrate political and non-political trends, are promising. Explorations of the consistency of scenario dynamics, taking into account policy responses and non-formalizable complexity, are also useful. Thus the separation of political forecasting from political analysis should be minimized, calling for a redirection of effort away from developing methodology uniquely geared to forecasting, and towards organizing more comprehensive and systematic analytical efforts.     

Predicting small region sectoral responses to changes in aggregate economic activity: A time series approach

The purpose of this paper is to investigate the applicability of a contemporary time series forecasting technique, transfer function modeling, to the problem of forecasting sectoral employment levels in small regional economies. The specific sectoral employment levels to be forecast are manufacturing, durable manufacturing, non-durable manufacturing and non-manufacturing employment. Due to data constraints at the small region level, construction of traditional causal econometric models is often very difficult; thus time series approaches become particularly attractive. The results suggest that transfer function models using readily available national indicator series as drivers can provide more accurate forecasts of small region sectoral employment levels than univariate time series models.