The tourism forecasting competition

We evaluate the performances of various methods for forecasting tourism data. The data used include 366 monthly series, 427 quarterly series and 518 annual series, all supplied to us by either tourism bodies or academics who had used them in previous tourism forecasting studies. The forecasting methods implemented in the competition are univariate and multivariate time series approaches, and econometric models. This forecasting competition differs from previous competitions in several ways: (i) we concentrate on tourism data only; (ii) we include approaches with explanatory variables; (iii) we evaluate the forecast interval coverage as well as the point forecast accuracy; (iv) we observe the effect of temporal aggregation on the forecasting accuracy; and (v) we consider the mean absolute scaled error as an alternative forecasting accuracy measure. We find that pure time series approaches provide more accurate forecasts for tourism data than models with explanatory variables. For seasonal data we implement three fully automated pure time series algorithms that generate accurate point forecasts, and two of these also produce forecast coverage probabilities which are satisfactorily close to the nominal rates. For annual data we find that Naïve forecasts are hard to beat.     

The econometric forecasting model of Czechoslovakia

Conclusion The result of the construction, estimation, testing and forecasting uses of the VVS-2 model testify to the expediency of using comprehensive econometric models in socialist economy. The VVS-2 model expresses at a satisfying rate of accuracy the quantitative relations between the fundamental indicators of Czechoslovak economy and has produced satisfactory results also in calculating short-term forecasts. Some new methods and computer programs that have been developed and employed for model estimation may be considered a contribution towards the development of applied econometrics in socialist countries.At the Computing Research Centre, United Nations D.P. in Bratislava, research work has continued on the development and improvement of further comprehensive econometric models. Within this framework the VVS-2 model will be permanently reestimated and possibly also extended and re-specificated according to the practical needs of macroeconomic analysis and planning.Authors are indebted to Professor Anton Klas, director of the Computing Research Centre, United Nations D.P., for creating very favourable conditions for the research work.     

The value of feedback in forecasting competitions

In this paper we challenge the traditional design used for forecasting competitions. We implement an online competition with a public leaderboard that provides instant feedback to competitors who are allowed to revise and resubmit forecasts. The results show that feedback significantly improves forecasting accuracy.     

A topological approach to Wilson’s impossibility theorem

We will present a topological approach to Wilson’s impossibility theorem [Wilson, R.B., 1972. Social choice theory without the Pareto principle. Journal of Economic Theory 5, 478–486] that there exists no non-null binary social choice rule which satisfies transitivity, independence of irrelevant alternatives, non-imposition and has no dictator nor inverse dictator. Our research is in line with the studies of topological approaches to discrete social choice problems initiated by [Baryshnikov, Y., 1993. Unifying impossibility theorems: a topological approach. Advances in Applied Mathematics 14, 404–415]. This paper extends the result about the Arrow impossibility theorem shown in [Tanaka, Y., 2006. A topological approach to the Arrow impossibility theorem when individual preferences are weak orders. Applied Mathematics and Computation 174, 961–981] to Wilson’s theorem.     

On the impossibility of insider trade in rational expectations equilibria

Existing no trade results are based on the common prior assumption (CPA). This paper identifies a strictly weaker condition than the CPA under which speculative trade is impossible in a rational expectations equilibrium (REE). As our main finding, we demonstrate the impossibility of speculative asset trade in an REE whenever an insider is involved who knows the asset's true value. To model insider trade as an equilibrium phenomenon an alternative equilibrium concept than the REE is thus required.     

日本FANCL打造快速准确的物流系统

苏宁电器连锁集团股份有限公司的前身是江苏苏宁交家电有限公司,于1990年12月26日诞生于南京宁海路,最初专营空调。1999年底,苏宁电器新街口店开业,标志着其开始全面进军综合电器零售领域。如今,苏宁电器已成为中国家电连锁企业的代表。     

柏瑞安精确的物流运作与管理

为了降低产品生产成本、提高生产效率,从国外到国内,电子企业不断地将生产任务外包给专门的生产服务商(EMS),这已成为电子行业发展的一种趋势.北京柏瑞安科技有限责任公司就是近年来异军突起的EMS企业之一.     

On the efficient estimation methods for the macro-economic models nonlinear in variables

All the macro-economic models have the nonlinearity in variables within their simultaneous equations systems. I propose a full information estimation method for such models. The method is (i) asymptotically efficient, (ii) feasible in the contemporary computer technology as it consists of calculations very much like the nonlinear multipliers, and (iii) hopefully applicable to the undersized sample case which prevails in the macro-economic model building. Though two other methods are also investigated, one is found to be asymptotically inefficient, and another turns out to be inapplicable to the undersized sample case.     

Value-added forecasting

Long ago, the emphasis shifted away from forecasting as a competitive weapon when it became apparent that forecast error could never be eliminated. Forecasts became a necessary evil that no one wanted to claim responsibility for. It's time to clear up some of the misconceptions about forecasts and to seize the opportunity inherent in the forecasting process. It is not forecast accuracy but rather improved understanding and use of forecasting as a tool for reducing both costs and lead times that will add real value to an enterprise and can improve the results from any and all other initiatives.     

Theory-coherent forecasting

We consider a method for producing multivariate density forecasts that satisfy moment restrictions implied by economic theory, such as Euler conditions. The method starts from a base forecast that might not satisfy the theoretical restrictions and forces it to satisfy the moment conditions using exponential tilting. Although exponential tilting has been considered before in a Bayesian context (Robertson et al. 2005), our main contributions are: (1) to adapt the method to a classical inferential context with out-of-sample evaluation objectives and parameter estimation uncertainty; and (2) to formally discuss the conditions under which the method delivers improvements in forecast accuracy. An empirical illustration which incorporates Euler conditions into forecasts produced by Bayesian vector autoregressions shows that the improvements in accuracy can be sizable and significant.     

The use of advance order data in demand forecasting

This paper uses advance order data and historical demand data from a manufacturing shop and from a service operation to develop and test a forecasting methodology for predicting customer demand over a forecast horizon. The proposed methodology uses simple linear regression to model the relationship between a total demand ratio and a partial demand ratio. Comparison of the proposed model to a standard regression approach and a commonly used multiplicative model showed that the proposed model exhibited the greatest forecast accuracy.     

The performance of alternative forecasting methods for SETAR models

We compare a number of methods that have been proposed in the literature for obtaining h-step ahead minimum mean square error forecasts for self-exciting threshold autoregressive (SETAR) models. These forecasts are compared to those from an AR model. The comparison of forecasting methods is made using Monte Carlo simulation. The Monte-Carlo method of calculating SETAR forecasts is generally at least as good as that of the other methods we consider. An exception is when the disturbances in the SETAR model come from a highly asymmetric distribution, when a Bootstrap method is to be preferred.An empirical application calculates multi-period forecasts from a SETAR model of US gross national product using a number of the forecasting methods. We find that whether there are improvements in forecast performance relative to a linear AR model depends on the historical epoch we select, and whether forecasts are evaluated conditional on the regime the process was in at the time the forecast was made.     

Short-term forecasting of crime

The major question investigated is whether it is possible to accurately forecast selected crimes 1 month ahead in small areas, such as police precincts. In a case study of Pittsburgh, PA, we contrast the forecast accuracy of univariate time series models with naïve methods commonly used by police. A major result, expected for the small-scale data of this problem, is that average crime count by precinct is the major determinant of forecast accuracy. A fixed-effects regression model of absolute percent forecast error shows that such counts need to be on the order of 30 or more to achieve accuracy of 20% absolute forecast error or less. A second major result is that practically any model-based forecasting approach is vastly more accurate than current police practices. Holt exponential smoothing with monthly seasonality estimated using city-wide data is the most accurate forecast model for precinct-level crime series.     

A characterization and an impossibility of finite length anonymity for infinite generations

In the context of ranking infinite utility streams, the impartiality axiom of finite length anonymity requires the equal ranking of any two utility streams that are equal up to a finite length permutation ( Fleurbaey and Michel, 2003). We first characterize any finite length permutation as a composition of a fixed step permutation and an “almost” fixed step permutation. We then show that if a binary relation satisfies finite length anonymity, then it violates all the distributional axioms that are based on a segment-wise comparison. Examples of those axioms include the weak Pareto principle and the weak Pigou-Dalton principle.     

On forecasting of innovations

The forecasting of basic technological innovations is focused. Clarification of the involved key concepts and an analytical framework are given. The forest industry serves as a background and illustration to the discussion. Considerable uncertainty prevails with respect to strategic investments in production in this industry. Industries, technological products, etc. have empirically been shown to pass similar phases of development over time. This life cycle starts with a basic innovation following on a previous invention. Due to competetion from more recent basic innovations the final phase is one of decline. Basic innovations are suggested to be exogenously determined and to cause structural change. The choice of forecasting strategy is suggested to be made dependent on the type of innovation, knowledge base, and life cycle position.     

Stochastic demographic forecasting

"This paper describes a particular approach to stochastic population forecasting, which is implemented for the U.S.A. through 2065. Statistical time series methods are combined with demographic models to produce plausible long run forecasts of vital rates, with probability distributions. The resulting mortality forecasts imply gains in future life expectancy that are roughly twice as large as those forecast by the Office of the Social Security Actuary....Resulting stochastic forecasts of the elderly population, elderly dependency ratios, and payroll tax rates for health, education and pensions are presented."     

Fundamental impossibility theorems on voluntary participation in the provision of non-excludable public goods

Groves and Ledyard (Econometrica 45:783–809, 1977) constructed a mechanism attaining Pareto efficient allocations in the presence of public goods. After this path-breaking paper, many mechanisms have been proposed to attain desirable allocations with public goods. Thus, economists have thought that the free-rider problem is solved, in theory. Our view to this problem is not so optimistic. Rather, we propose fundamental impossibility theorems with public goods. In the previous mechanism design, it was implicitly assumed that every agent must participate in the mechanism that the designer provides. This approach neglects one of the basic features of public goods: non-excludability. We explicitly incorporate non-excludability and then show that it is impossible to construct a mechanism in which every agent has an incentive to participate.     

The asymmetry of judgemental confidence intervals in time series forecasting

In forecasting a time series, one may be asked to communicate the likely distribution of the future actual value, often expressed as a confidence interval. Whilst the accuracy (calibration) of these intervals has dominated most studies to date, this paper is concerned with other possible characteristics of the intervals. It reports a study in which the prevalence and determinants of the symmetry of judgemental confidence intervals in time series forecasting was examined. Most prior work has assumed that this interval is symmetrically placed around the forecast. However, this study shows that people generally estimate asymmetric confidence intervals where the forecast is not the midpoint of the estimated interval. Many of these intervals are grossly asymmetric. Results indicate that the placement of the forecast in relation to the last actual value of a time series is a major determinant of the direction and size of the asymmetry.