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Quantitative methods are very successful for producing baseline forecasts of time series; however these models fail to forecast neither the timing nor the impact of special events such as promotions or strikes. In most of the cases the timing of such events is not known so they are usually referred as shocks (economics) or special events (forecasting). Sometimes the timing of such events is known a priori (i.e. a future promotion); but even then the impact of the forthcoming event is hard to estimate. Forecasters prefer to use their own judgment for adjusting for forthcoming special events, but humans' efficiency in such tasks has been found to be deficient. This study after examining the relative performance of Artificial Neural Networks, Multiple Linear Regression and Nearest Neighbor approaches proposes an expert method which combines the strengths of regression and artificial intelligence.

PurposeOnce a policy proposed by the European Commission is approved by European Parliament or Council, its implementation strategy is the responsibility of the member states. Often, there will be several parallel strategies shaped by a series of incentives financed by the government and naturally, the aim is to choose the most cost effective one. For strategy and planning as well as budgeting purposes, forecasts of the adoption rate of these policy implementation strategies will be an indicator as to their effectiveness. A new hybrid approach combining structured analogies and econometric modelling is proposed for producing such forecasts.Design/methodology/approachWith every different policy, there will be different qualitative and quantitative data available for producing such implementation strategy adoption rate forecasts. Hence, the proposed hybrid approach, which combines the strengths and reduces the weaknesses of each of its constituents, can be adjusted to match the quantity and nature of the available data.FindingsThis paper reveals a lack of emphasis on such a forecasting application in the existing literature, while stressing its importance to governmental decision makers. What is more, the paper reveals a lack of documentation of this forecasting process in large governmental structures.Practical implicationsIf shown to improve the ability to produce such forecasts, the proposed approach could be very beneficial to decision makers when faced with several possible implementation strategies.Originality/valueThe use of expertise is quite common in forecasting policy impact but in an unstructured way. The advanced model proposes structuring the use of analogies in an objective manner. Furthermore, combining with econometric modelling, the incorporation of valuable quantitative information is made possible.

PurposePolicy implementation strategies (PIS) are schemes designed by a government with an aim of hitting targets or attaining objectives set out by a policy. Forecasting by analogies (FBA) has been shown to be successful in situations of high uncertainty and low quantitative data as is that of PIS effectiveness forecasts. What is more, a structured approach to FBA helps the expert structure his thoughts in an organized manner before making a prediction, which is hypothesized to improve accuracy. This paper aims to discuss these issues.Design/methodology/approachThis research suggests a semi‐structured analogies (S‐SA) approach for such a task. A pilot experiment was carried to test the performance of the S‐SA approach in the hands of semi‐experts when compared with unaided judgment (UJ).FindingsThe results of the experiment showed that for this level of expertise, there is no statistical evidence to suggest any approach is better than the other. Possible explanations of this result is that analogy recall of experts was hindered by four constructs: information, complexity, worldview, and expertise. It was concluded that the structured analogies approach for forecasting PIS effectiveness must be investigated further by means of a study involving "true experts".Research limitations/implicationsThe sample sizes were small.Practical implicationsForecasting PIS effectiveness is seen as an important tool for deciding upon which PIS to ultimately adopt (as there may be many available!) and this then has important implications for governmental budgeting.Originality/valueThe paper offers further insight into the performance of a structured analogies approach to forecasting PIS effectiveness in the hands of individuals with a mid‐level of expertise.

The first book to be published on the Theta method, outlining under what conditions the method outperforms other forecasting methods This book is the first to detail the Theta method of forecasting - one of the most difficult-to-beat forecasting benchmarks, which topped the biggest forecasting competition in the world in 2000: the M3 competition. Written by two of the leading experts in the forecasting field, it illuminates the exact replication of the method and under what conditions the method outperforms other forecasting methods. Recent developments such as multivariate models are also included, as are a series of practical applications in finance, economics, and healthcare. The book also offers practical tools in MS Excel and guidance, as well as provisional access, for the use of R source code and respective packages. Forecasting with the Theta Method: Theory and Applications includes three main parts. The first part, titled Theory, Methods, Models & Applications details the new theory about the method. The second part, Applications & Performance in Forecasting Competitions, describes empirical results and simulations on the method. The last part roadmaps future research and also include contributions from another leading scholar of the method - Dr. Fotios Petropoulos. First ever book to be published on the Theta Method Explores new theory and exact conditions under which methods would outperform most forecasting benchmarks Clearly written with practical applications Employs R - open source code with all included implementations Forecasting with the Theta Method: Theory and Applications is a valuable tool for both academics and practitioners involved in forecasting and respective software development.

"This book offers a comprehensive guide to modern day taxation issues. It presents a thorough overview of many of the crucial aspects of applied taxation and current tax systems, and presents evidence that supports taxation as an important policy issue requiring immediate address globally. Contributions seek to address the core question of how to design a tax policy mix that can serve primarily efficiency, growth and possibly equity goals at a time where fiscal spending, for many economies, is not a viable option. Chapters provide a historical perspective on taxation, then go on to cover aspects of the modern theory of optimal taxation and tax design and provide valuable international perspectives on current tax practices and much required tax reforms. Empirical analysis on taxation and related economic data help the readers to understand how data-based observations and results are linked to the theory of taxation, and more importantly economic growth, before offering appropriate policy prescriptions. This book will be of interest to scholars and practitioners interested in learning more about taxation and why it matters today in the global economy."--