Demand Forecasting: Evidence-based Methods

We looked at evidence from comparative empirical studies to identify methods that can be useful for predicting demand in various situations and to warn against methods that should not be used. In general, use structured methods and avoid intuition, unstructured meetings, focus groups, and data mining. In situations where there are sufficient data, use quantitative methods including extrapolation, quantitative analogies, rule-based forecasting, and causal methods. Otherwise, use methods that structure judgement including surveys of intentions and expectations, judgmental bootstrapping, structured analogies, and simulated interaction. Managers' domain knowledge should be incorporated into statistical forecasts. Methods for combining forecasts, including Delphi and prediction markets, improve accuracy. We provide guidelines for the effective use of forecasts, including such procedures as scenarios. Few organizations use many of the methods described in this paper. Thus, there are opportunities to improve efficiency by adopting these forecasting practices.Accuracy, expertise, forecasting, judgement, marketing.

Hartlepool College of Further Education: report from the Inspectorate (FEFC inspection report; 97/95 and 27/98)

Comprises two Further Education Funding Council (FEFC) inspection reports for the periods 1994-95 and 1997-98

Bayesian and Non-Bayesian Approaches to Scientific Modeling and Inference in Economics and Econometrics

After brief remarks on the history of modeling and inference techniques in economics and econometrics , attention is focused on the emergence of economic science in the 20th century. First, the broad objectives of science and the Pearson-Jeffreys' "unity of science" principle will be reviewed. Second, key Bayesian and non-Bayesian practical scientific inference and decision methods will be compared using applied examples from economics, econometrics and business. Third, issues and controversies on how to model the behavior of economic units and systems will be reviewed and the structural econometric modeling, time series analysis (SEMTSA) approach will be described and illustrated using a macro-economic modeling and forecasting problem involving analyses of data for 18 industrialized countries over the years since the 1950s. Point and turning point forecasting results will be summarized. Last, a few remarks will be made about the future of scientific inference and modeling techniques in economics and econometrics.

Forecasting the demand for privatized transport - What economic regulators should know, and why

Forecasting has long been a challenge, and will remain so for the foreseeable future. But the analytical instruments and data processing capabilities available through the latest technology, and software, should allow much better forecasting than transport ministries, or regulatory agencies typically observe. Privatization brings new needs for demand forecasting. More attention is paid to risk under privatization, than when investments are publicly financed. And regulators must be able to judge traffic studies done by operators, and to learn what strategic behavior influenced these studies. Many governments, and regulators avoid good demand, modeling out of lack of conviction that theory, and models can do better than the"old hands"of the sector. This is dangerous when privatization changes the nature of business. For projects amounting to investments of $100-200 million, a cost of$ 100,000-200,000 is not a reason to reject a reasonable modeling effort. And some private forecasting firms are willing to sell guarantees, or insurance with their forecasts, to cover significant gaps between forecasts, and reality.Markets and Market Access,Environmental Economics&Policies,Economic Theory&Research,Decentralization,Banks&Banking Reform,Markets and Market Access,Economic Theory&Research,Banks&Banking Reform,Access to Markets,Environmental Economics&Policies

Do fiscal councils impact fiscal performance?

In order to improve fiscal policy process and budget transparency, the European Union (EU) stated more stringent fiscal rules monitored by Independent Fiscal Bodies, that have the capacity to “tie the hands” of policymakers tempted by deviations from socially optimal choices according to the academic circles.The present paper aims at empirically verifying if Fiscal Councils (FCs) in Europe (as a complement or substitute for the Fiscal Rules - FRs) have an impact on Governments’ fiscal decisions and if this impact exists and is positive which feature of their functioning is relevant for their effectiveness

Ocean services user needs assessment. Volume 1: Survey results, conclusions and recommendations

An interpretation of environmental information needs of marine users, derived from a direct contact survey of eight important sectors of the marine user community is presented. Findings of the survey and results and recommendations are reported. The findings consist of specific and quantized measurement and derived product needs for each sector and comparisons of these needs with current and planned NOAA data and services. The following supportive and reference material are examined: direct contact interviews with industry members, analyses of current NOAA data gathering and derived product capabilities, evaluations of new and emerging domestic and foreign satellite data gathering capabilities, and a special commercial fishing survey conducted by the Jet Propulsion Laboratory (JPL)

Time Series Event Forecasting in Consumer Electronic Markets using Random Forests

Consumers are price-sensitive and opportunistic about the place of purchase when buying electronic goods. However, services that advise customers on their purchase time decisions for those products are missing. Given the objective to provide a binary signal to customers to either wait or purchase immediately, classification algorithms are a direct methodological choice. Approaches like random forests allow for the derivation of a probability and class prediction but are usually not used in time series contexts. This is due to missing or time-invariant regressors and unclear prediction settings. We show how classification methods can be used to generate reliable predictions of price events and analyze if they are subject to common market dependencies. Pooling univariate random forests and enhancing them with multivariate features shows that our approach generates stable and valuable recommendations. Because dependency structures between products are transferable, multivariate forecasting increases accuracy and issues recommendations where univariate approaches fail

The development of an integrated sales forecasting and production planning system for the brewing industry

Bibliography: pages 129-132.Considerable imminent in change on the this country. political and economic front is There is constant demand on businesses to improve productivity in the face of rising inflation, a trend that is unlikely to reverse given expected high wage demands. The liquor market is consider-ably influenced by government legislation and the state of the economy, hence companies operating within the liquor market are challenged with improving productivity in a changing environment. In order to facilitate productivity improvement, sales and production requirements need to be ascertained. The objective of this thesis is to design personal computer- based sales forecasting planning system that will aid a brewery productivity and minimise costs, through an integrated and production to maximise an ability to accurately forecast beer sales and translate such forecasts into efficient production plans. Fundamental to ensuring that the optimum production scenario is achieved is the need to generate a number of production scenarios for comparative purposes. To this end, the sales forecasting and production planning systems must be fully integrated, thereby allowing for the efficient generation of "what if" type analyses