ARIMA models of the price level: An assessment of the multilevel adaptive learning process in the USA

This paper estimates the ARIMA processes for the observed and expected price level corresponding to the three-level adaptive expectations model proposed by Jacobs and Jones (1980). These univariate processes are then compared with the best-fit ARIMA model. The results indicate that the best-fit model for the observed price level is a restricted version of the two-level adaptive learning process specified in terms of prices, suggesting a simple adaptive rule in the inflation rate. A comparison of the time-series forecasts from the best-fit model with the mean responses to the ASA-NBER survey shows no significant difference in their accuracy. The time-series forecasts are, however, conditionally efficient. The best-fit ARIMA model for expected prices measured by the ASA-NBER consensus forecasts does not correspond to any version of the Jacobs and Jones model.     

Assessing the forecasting accuracy of alternative nominal exchange rate models: the case of long memory

This paper presents an autoregressive fractionally integrated moving‐average (ARFIMA) model of nominal exchange rates and compares its forecasting capability with the monetary structural models and the random walk model. Monthly observations are used for Canada, France, Germany, Italy, Japan and the United Kingdom for the period of April 1973 through December 1998. The estimation method is Sowell's (1992) exact maximum likelihood estimation. The forecasting accuracy of the long‐memory model is formally compared to the random walk and the monetary models, using the recently developed Harvey, Leybourne and Newbold (1997) test statistics. The results show that the long‐memory model is more efficient than the random walk model in steps‐ahead forecasts beyond 1 month for most currencies and more efficient than the monetary models in multi‐step‐ahead forecasts. This new finding strongly suggests that the long‐memory model of nominal exchange rates be studied as a viable alternative to the conventional models. Copyright © 2006 John Wiley & Sons, Ltd.     

The role of time series analysis in the evaluation of econometric models

This paper compares the properties of a structural model—the London Business School model of the U.K. economy—with a time series model. Information provided by this type of comparison is a useful diagnostic tool for detecting types of model misspecification. This is a more meaningful way of proceeding rather than attempting to establish the superiority of one type of model over another. In lieu of a better structural model, the effects of inappropriate dynamic specification can be reduced by combining the forecasts of both the structural and time series models. For many variables considered here these provide more accurate forecasts than each of the model types alone.     

知识创新的Markov控制模型研究

本文在已有的知识创新的相关理论基础上研究知识创新问题。完善了知识创新的机理模型,并对其进行了理论说明,指出知识创新的原理和作用;在对其机理分析的基础上,用Markov模型描述了企业的知识创新过程,分析了影响知识创新的关键因素——隐性知识;并提出了有关知识创新的相应策略框架。     

Identifying the time‐effect factors of multiple time series

The Peña–Box model is considered for finding the time‐effect factors of a multiple time series. This paper first establishes the connection between the Peña–Box model and the vector ARMA model. According to the Peña–Box model, some series can be ignored while modelling the vector ARMA model. A consistent estimator is then proposed to identify the model for nonlinear and nonstationary time series. Finally, the finite‐sample behaviour of the estimator is illustrated via simulations. Copyright © 2005 John Wiley & Sons, Ltd.     

21世纪初辐射防护的几个基本问题

辐射防护已有近百年的历史。20世纪下半叶随着核能和核技术应用的发展，辐射防护得到了较大的发展。但仍然有许多基本问题有待进一步研究。作为辐射防护基础的线性无阈理论受到挑战。从辐射防护观点出发，基于当前的科学水平，应该认为选择线性无阈模式是合理的。但从科学上说辐射剂量效应模式尚有待进一步研究。辐射环境影响是辐射防护面临的一个新问题。其生物学终点、参考生物和剂量评价模式等都有待深入研究。利益相关者的参与是解决放射性废物管理和核安全困境的重要途径，其参与方式和时机等值得进一步研究。     

层次分析法评价降雨对滑坡稳定性的影响

利用层次分析法建立了万塘滑坡危险度评价模型,综合考虑降雨、地震、人类工程活动、库水位、地形地貌、地层岩性和岩层组合结构七个方面的因素,对三峡库区万塘滑坡进行危险度评价,并与传统的刚体极限平衡法相比较验证。通过重点定量分析降雨对万塘滑坡稳定性的影响程度,验证了降雨在滑坡稳定性中所起的关键作用,为滑坡灾害预防提供依据。     

Maxwell's role in turning the concept of model into the methodology of modeling

This is a contribution towards a history and philosophy of modeling in its early stages in electromagnetism. In 1873, James Clerk Maxwell (1831–1879) hinted at the methodology of modeling at the end of his Treatise on Electricity and Magnetism. We focus on Maxwell's impact on physicists who immediately followed him, specifically Oliver Lodge (1851–1940) and George Francis FitzGerald (1851–1901). We begin with the role that the scientific concept of model played in the late nineteenth century, as assessed by Ludwig Boltzmann (1844–1906). We then discuss the role of hypothesis as a methodology, the appeal to (dynamical) illustration, and the way Maxwell applied model and working model in his studies of electromagnetism. We show that for Maxwell these key terms were kept distinct, but Lodge did not maintain these distinctions and, in this regard, FitzGerald followed Lodge. Notwithstanding Lodge's influence, Fitzgerald modified Maxwell's theory based on the mechanical model he designed, thereby implicitly taking the first step towards modeling. This methodology consists in drawing consequences from the (mechanical) model to the (electrodynamic) theory and modifying the latter in light of the functioning of the former. At the core of our argument is the thesis that it was a methodological novelty to move from the concept of model to the methodology of modeling. The introduction of modeling as a new methodology into physics in the late nineteenth century was a major event which deserves proper recognition.     

History of the Lenz–Ising model 1965–1971: the role of a simple model in understanding critical phenomena

This is the last in a series of three papers on the history of the Lenz–Ising model from 1920 to the early 1970s. In the first paper, I studied the invention of the model in the 1920s, while in the second paper, I documented a quite sudden change in the perception of the model in the early 1960s when it was realized that the Lenz–Ising model is actually relevant for the understanding of phase transitions. In this article, which is self-contained, I study how this realization affected attempts to understand critical phenomena, which can be understood as limiting cases of (first-order) phase transitions, in the epoch from circa 1965 to 1970, where these phenomena were recognized as a research field in its own right. I focus on two questions: What kinds of insight into critical phenomena was the employment of the Lenz–Ising model thought to give? And how could a crude model, which the Lenz–Ising model was thought to be, provide this understanding? I document that the model played several roles: At first, it played a role analogous to experimental data: hypotheses about real systems, in particular relations between critical exponents and what is now called the hypothesis of scaling, which was advanced by Benjamin Widom and others, were confronted with numerical results for the model, in particular the model’s so-called critical exponents. A positive result of a confrontation was seen as positive evidence for this hypothesis. The model was also used to gain insight into specific aspects of critical phenomena, for example that diverse physical systems exhibit similar behavior close to a critical point. Later, a more systematic program of understanding critical phenomena emerged that involved an explicit formulation of what it means to understand critical phenomena, namely, the elucidation of what features of the Hamiltonian of models lead to what kinds of behavior close to critical points. Attempts to accomplish this program culminated with the so-called hypothesis of universality, put forward independently by Robert B. Griffiths and Leo P. Kadanoff in 1970. They divided critical phenomena into classes with similar critical behavior. I also study the crucial role of the Lenz–Ising model in the development and justification of these ideas.     

Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank

The main focus of this paper is to model the daily series of banknotes in circulation. The series of banknotes in circulation displays very marked seasonal patterns. To the best of our knowledge the empirical performance of two competing approaches to model seasonality in daily time series, namely the ARIMA‐based approach and the Structural Time Series approach, has never been put to the test. The application presented in this paper provides valid intuition on the merits of each approach. The forecasting performance of the models is also assessed in the context of their impact on the liquidity management of the Eurosystem. Copyright © 2008 John Wiley & Sons, Ltd.     

The metaphysics of D-CTCs: On the underlying assumptions of Deutsch׳s quantum solution to the paradoxes of time travel

I argue that Deutsch׳s model for the behavior of systems traveling around closed timelike curves (CTCs) relies implicitly on a substantive metaphysical assumption. Deutsch is employing a version of quantum theory with a significantly supplemented ontology of parallel existent worlds, which differ in kind from the many worlds of the Everett interpretation. Standard Everett does not support the existence of multiple identical copies of the world, which the D-CTC model requires. This has been obscured because he often refers to the branching structure of Everett as a “multiverse”, and describes quantum interference by reference to parallel interacting definite worlds. But he admits that this is only an approximation to Everett. The D-CTC model, however, relies crucially on the existence of a multiverse of parallel interacting worlds. Since his model is supplemented by structures that go significantly beyond quantum theory, and play an ineliminable role in its predictions and explanations, it does not represent a quantum solution to the paradoxes of time travel.     

Estimation and testing of time-varying coefficient regression models in the presence of linear restrictions

A linear regression model with random walk coefficients is extended to allow for linear restrictions between the coefficients to be satisfied at each point in time. Estimation in this model is shown to be no more involved than estimation in the standard model. It is also demonstrated how, after a slight modification to the testing problem, classical test procedures may be applied to the problem of testing for such restrictions. The performance of the Lagrange Multiplier test for a variety of different restrictions is then investigated via simulation. An empirical application involving testing for homogeneity in a random walk coefficient version of the AIDS model is given.     

软弱围岩下小净距隧道中岩柱加固方法分析

建立基于Drunker-Prager本构模型小净距隧道弹塑性三维模型,进行室内比尺模型试验的数值模拟。比较数值模拟和室内试验之间的结果,验证数值模型试验的有效性。通过对围岩的位移、塑性区、整体塑性能释放、最大塑性应变分析,比较上、中、下岩盘等不同加固工况的优劣,为实际施工加固方案择提供技术参考。     

A flexible model of technological diffusion incorporating economic factors with an application to the spread of colour television ownership in the UK

In this paper a new encompassing flexible diffusion model of the epidemic type is proposed and its properties explored. Economic factors are incorporated directly into the model. The new model allows freer interaction between exogenous and endogenous factors in the diffusion process than existing models of this type. The model is applied to the diffusion of colour television ownership in the UK and outperforms the existing models in the literature. The exogenous factors are shown to play a more dominant role in the diffusion of colour television in the UK than existing models allow.     

On the stability of cognitive processes

An empirical and mathematical model for self-organization is proposed, based on elemental properties, on unique interaction and on the combination of hierarchical elements. In the model, higher elements are stabilized by the 'cognitive' (strong) interaction of subelements, disregarding intermediate elements. This is called 'elementary reductionism' and is illustrated by the sequence quarks-elementary particles-atoms-molecules-cells-organisms- societies. Optimal dynamic interaction of nonidentical elements is called 'cognitive stability'. This is compared with thermodynamic equilibrium. The principal differences are outlined.     

Computing the variance of the forecast error for the holt-winters seasonal models

This paper presents expressions for the variance of the forecast error for arbitrary lead times for both the additive and multiplicative Holt-Winters seasonal forecasting models. It is shown that even when the smoothing constants are chosen to have values between zero and one, when the period is greater than four, the variance may not be finite for some values of the smoothing constants. In addition, the regions where the variance becomes infinite are almost the same for both models. These results are of importance for practitioners, who may choose values for the smoothing constants arbitrarily, or by searching on the unit cube for values which minimize the sum of the squared errors when fitting the model to a data set. It is also shown that the variance of the forecast error for the multiplicative model is nonstationary and periodic.     

Mortality effects of temperature changes in the United Kingdom

Temperature changes are known to affect the social and environmental determinants of health in various ways. Consequently, excess deaths as a result of extreme weather conditions may increase over the coming decades because of climate change. In this paper, the relationship between trends in mortality and trends in temperature change (as a proxy) is investigated using annual data and for specified (warm and cold) periods during the year in the UK. A thoughtful statistical analysis is implemented and a new stochastic, central mortality rate model is proposed. The new model encompasses the good features of the Lee and Carter (Journal of the American Statistical Association, 1992, 87: 659–671) model and its recent extensions, and for the very first time includes an exogenous factor which is a temperature‐related factor. The new model is shown to provide a significantly better‐fitting performance and more interpretable forecasts. An illustrative example of pricing a life insurance product is provided and discussed.     

A case illustrating the importance of adequate model criticism

A case is discussed where a failure to adequately criticize an ARIMA model led to erroneous inferences about the process underlying the data. A follow-up analysis, which permitted model criticism, suggested a different interpretation. The case is suggested for classroom presentation.     

A stochastic proportional hazard model for the force of mortality

In order to avoid ‘frailty’ in deterministic assumptions concerning survival law, in this paper stochastic volatility in the force of mortality is considered. In particular, mortality rates are studied by means of a stochastic model of CIR type. A method for estimating its parameters is presented and an example of application, based on simulations of the process, is shown. Empirical results and comparison with a traditional model illustrate predictive performance and the flexibility of the model. Copyright © 2006 John Wiley & Sons, Ltd.     

Analysis and forecasting of income statement account balances the dynamic interdependency and ARIMA approaches

This paper develops a dynamic simultaneous-equations model for analyzing and forecasting the account balances in the income statement of a firm. In the model, the income statement accounts play the role of the dependent variables that are jointly determined and explained by three types of exogenous variables: non-controllable, performance, and controllable. The model is estimated by the three-stage least-squares method using annual series of data for six firms during the period from 1936 or 1950 to 1981. The immediate, delayed, and cumulated impacts of an exogenous shock on the income accounts are analyzed and the implications for managerial decisions and strategies discussed. To run as a standard of comparison for the dynamic interdependency model, the Box-Jenkins approach is also used to develop an autoregressive integrated moving average (ARIMA) model for each of the accounts. Assessing the forecasting performance of the dynamic model against a naive model and the ARIMA and Elliott-Uphoff models for the 1982-4 period beyond the estimation period, we conclude that the dynamic model is a better representation of income statement accounts of the firm and increases forecasting accuracy.