Population,labour force and unemployment in Andalusia: prospects for 1993

"This paper is concerned with forecasting population, employment, labour force and unemployment in Andalusia [Spain] to 1993. For this purpose, a block-recursive demoeconomic model is presented. The demographic submodel is based on the component-cohort method of forecasting population by age and sex. The economic submodel uses econometric and time series analysis to forecast employment both in the medium and short-term. In the labour market part, the labour force is forecasted taking into account the encouraged-discouraged worker effects of changes in the demand for labour."     

Modelling metropolitan population growth and change: The IIPS simulator

This paper describes selected aspects of a large scale urban simulation project (IIPS). Emphasis is on design and empirical evaluation of a model of metropolitan population growth and change. Functions for determining ‘behavior’ of fertility and net-migration are specified and an important linkage between the IIPS population and land use models is illustrated. In a final section, the reader is introduced to a relatively unique computer sumulation-supervisor.     

The problem of population and growth: a review of the literature from Malthus to contemporary models of endogenous population and endogenous growth.

This review traces the evolution of literature on population and economic growth through the main paradigms suggested to explain the observed covariation of per capita income and population levels (or their rates of growth) over time and space, and determine which public policies will improve the human condition. As the main paradigms evolved, key variables were progressively treated as endogenous (instead of exogenous) to the growth process. After the introduction, section 2 looks at the "classical model" of Malthusian population theory and its refinements. Section 3 identifies empirical data that bears on the secular and cross-sectional association between levels of rates of growth of population and per capita income. The inconsistency of these data with the classical model helps explain declining interest in this model over time and increased interest in a more systematic type of population and growth theory. The beginning of this new interest is traced in section 4 with a look at the "neo-classical growth model" and the reformulated theory of population, which was based on Becker's work on fertility behavior. The first line of inquiry branching from these theoretical works (section 5) treats population as an endogenous variable in static and dynamic settings. The second line of inquiry (section 6) analyzes population and growth within a unified model of growth and development. In section 7, recent studies of key policy issues (population control policies, mandatory social security schemes) are surveyed. The concluding section notes that contemporary research must face the challenge of providing additional insights into longevity as an aspect of economic growth and development and of developing a model of endogenous population and economic growth based on heterogeneous agents.     

What Determines Managers' Perceptions of Cash Flow Forecasting Quality? Evidence From a Multinational Corporation

In this article, we develop and test a model of the determinants of managers' perceptions of cash flow forecasting quality in nonfinancial companies. We expect and find that managers' perceptions of the quality of cash flow forecasts are determined by the perceived quality of the input data, the effort invested in forecasting, and the efficiency of the related processes, and ultimately by a company's orientation toward financial goals. Our empirical analysis is based on data from a worldwide questionnaire survey at a multinational industrial company. While we find that managers assess forecasting effort lower and forecasting efficiency higher for direct cash flow forecasting than for indirect method forecasting, our analyses reveal that the variables in our model, the postulated relationships between them, and the estimated effect sizes are equally valid for both forecasting methods.     

Forecasting U.S. population totals with the Box-Jenkins approach

"The use of the Box-Jenkins approach for forecasting the population of the United States up to the year 2080 is discussed. It is shown that the Box-Jenkins approach is equivalent to a simple trend model when making long-range predictions for the United States. An investigation of forecasting accuracy indicates that the Box-Jenkins method produces population forecasts that are at least as reliable as those done with more traditional demographic methods."     

灰色理论在城市总体规划中的应用研究

在编制城市总体规划时收集的资料和信息往往是不完全和不对称的，很多数据需要通过科学的理论去建立合理的模型来推算，本文采用灰色理论建模，以GDP预测为例详细说明了灰色预测模型GM（1，1）的建模过程。该模型对于预测城市总体规划中水文、人口、用地规模、城市化水平、交通运输发展、公共交通以及客货运量等具有普遍指导意义。     

Forecasting and turning point predictions in a Bayesian panel VAR model

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model, which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for hierarchical and for Minnesota-type priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.     

Benchmarking robustness of load forecasting models under data integrity attacks

As the internet’s footprint continues to expand, cybersecurity is becoming a major concern for both governments and the private sector. One such cybersecurity issue relates to data integrity attacks. This paper focuses on the power industry, where the forecasting processes rely heavily on the quality of the data. Data integrity attacks are expected to harm the performances of forecasting systems, which will have a major impact on both the financial bottom line of power companies and the resilience of power grids. This paper reveals the effect of data integrity attacks on the accuracy of four representative load forecasting models (multiple linear regression, support vector regression, artificial neural networks, and fuzzy interaction regression). We begin by simulating some data integrity attacks through the random injection of some multipliers that follow a normal or uniform distribution into the load series. Then, the four aforementioned load forecasting models are used to generate one-year-ahead ex post point forecasts in order to provide a comparison of their forecast errors. The results show that the support vector regression model is most robust, followed closely by the multiple linear regression model, while the fuzzy interaction regression model is the least robust of the four. Nevertheless, all four models fail to provide satisfying forecasts when the scale of the data integrity attacks becomes large. This presents a serious challenge to both load forecasters and the broader forecasting community: the generation of accurate forecasts under data integrity attacks. We construct our case study using the publicly-available data from Global Energy Forecasting Competition 2012. At the end, we also offer an overview of potential research topics for future studies.     

生育政策对我国人口总量影响的干预ARIMA模型分析

本文利用干预时序模型方法,简明扼要地对我国建国以来的人口发展趋势建立了动态模型,并预测了未来几年我国人口发展的趋势。结果表明,此模型很好地解释了我国人口发展的动态结构,可为促进我国人口政策的调整与扩展提供较好的参考依据。     

Residual value forecasting using asymmetric cost functions

Leasing is a popular channel for marketing new cars. However, the pricing of leases is complicated because the leasing rate must embody an expectation of the car’s residual value after contract expiration. This paper develops resale price forecasting models in order to aid pricing decisions. One feature of the leasing business is that different forecast errors entail different costs. The primary objective of this paper is to identify effective ways of addressing cost asymmetry. Specifically, this paper contributes to the literature by (i) consolidating prior work in forecasting on asymmetric functions of the cost of errors; (ii) systematically evaluating previous approaches and comparing them to a new approach; and (iii) demonstrating that forecasting using asymmetric cost of error functions improves the quality of decision support in car leasing. For example, if the costs of overestimating resale prices are twice those of underestimating them, incorporating cost asymmetry into forecast model development reduces costs by about 8%.     

公路工程施工现场管理应注意的问题

针对公路工程施工现场管理的重要性,从施工准备、配置施工资源、做好试验段、调整机械组合、治理质量通病、进度控制、成本管理等方面进行了探讨,公路工程施工的现场管理是施工管理的核心,现场管理效果的好坏直接影响工程的质量、进度与效益。加强现场管理,从而实现公路建设项目的快速、优质、低耗。     

Statistical survival analysis of male larynx-cancer patients - a case study

Abstract  This paper deals with a concrete case: Of 90 male larynx-cancer patients, diagnosed and treated in the period 1970–1978, either the survival time or, if the patient was still alive at the end of the study, an appropriate lower bound on it was recorded. One factor (stage of the cancer) and one covariate (age of the patient) were a priori selected as important variables possibly influencing the survival function.
After an elementary analysis of the 3 and 5 year survival fractions in section 2, a nonparametric estimation of the survival functions ignoring the effect of age is presented in section 3. In the last section COX'S (1972) proportional hazards model is used for a one dimensional regression on age which leads to the estimation of S_i(t z ), the survival function of patients with stage i and age z . This allows for a graphical comparison with the normal population. Finally some checks on the proportional hazard assumption are performed.
The emphasis in this paper is on adequately applying and adapting (mostly existing) techniques, including the use of some generally available computer programs, to a practical case. Care has been given to model assumptions and theoretical foundations of the relevant methods.     

黄冈遗爱湖公园建设施工探究

随着生活水平的提高,顺应宜居城市建设的需要,地级城市公园建设显现火热态势。结合黄冈遗爱湖公园部份标段工程建设的实践,交流、探究城市公园建设施工质量管理问题。     

A generalized non-linear forecasting model for limited overs international cricket

This paper proposes a generalized non-linear forecasting model (GNLM) for forecasting the number of runs remaining to be scored in an innings of cricket. The proposed model takes into account the numbers of overs left and wickets lost. The GNLFM can be used to build a model for any format of limited-overs international cricket. However, the purpose of its use in this paper is for building a forecasting model for projecting second innings total runs in Twenty-20 International cricket. Our model makes it possible to estimate the runs differential of the two competing teams whilst the match is in progress. The runs differential can be used not only to gauge the closeness of a game, but also to estimate the ratings of cricket teams that take into account the margin of victory. Furthermore, the well-known original Duckworth/Lewis (DL) model and the McHale/Asif version of it for revising targets in interrupted matches are special cases of our proposed generalized non-linear forecasting model.     

Automatic ARIMA modeling including interventions, using time series expert software

This article has three objectives: (a) to describe the method of automatic ARIMA modeling (AAM), with and without intervention analysis, that has been used in the analysis; (b) to comment on the results; and (c) to comment on the M3 Competition in general. Starting with a computer program for fitting an ARIMA model and a methodology for building univariate ARIMA models, an expert system has been built, while trying to avoid the pitfalls of most existing software packages. A software package called Time Series Expert TSE-AX is used to build a univariate ARIMA model with or without an intervention analysis. The characteristics of TSE-AX are summarized and, more especially, its automatic ARIMA modeling method. The motivation to take part in the M3-Competition is also outlined. The methodology is described mainly in three technical appendices: (Appendix A) choice of differences and of a transformation, use of intervention analysis; ( Appendix B) available specification procedures; ( Appendix C) adequacy, model checking and new specification. The problems raised by outliers are discussed, in particular how close they are from the forecast origin. Several series that are difficult to deal with from that point of view are mentioned and one of them is shown. In the last section, we comment on contextual information, the idea of an e−M Competition, prediction intervals and the possible use of other forecasting methods within Time Series Expert.     

Decision making and planning under low levels of predictability

This special section aims to demonstrate the limited predictability and high level of uncertainty in practically all important areas of our lives, and the implications of this. It summarizes the huge body of solid empirical evidence accumulated over the past several decades that proves the disastrous consequences of inaccurate forecasts in areas ranging from the economy and business to floods and medicine. The big problem is, however, that the great majority of people, decision and policy makers alike, still believe not only that accurate forecasting is possible, but also that uncertainty can be reliably assessed. Reality, however, shows otherwise, as this special section proves. This paper discusses forecasting accuracy and uncertainty, and distinguishes three distinct types of predictions: those relying on patterns for forecasting, those utilizing relationships as their basis, and those for which human judgment is the major determinant of the forecast. In addition, the major problems and challenges facing forecasters and the reasons why uncertainty cannot be assessed reliably are discussed using four large data sets. There is also a summary of the eleven papers included in this special section, as well as some concluding remarks emphasizing the need to be rational and realistic about our expectations and avoid the common delusions related to forecasting.     

Stochastic methods in population forecasting

"This paper presents a stochastic version of the demographic cohort-component method of forecasting future population. In this model the sizes of future age-sex groups are non-linear functions of random future vital rates. An approximation to their joint distribution can be obtained using linear approximations or simulation. A stochastic formulation points to the need for new empirical work on both the autocorrelations and the cross-correlations of the vital rates. Problems of forecasting declining mortality and fluctuating fertility are contrasted. A volatility measure for fertility is presented. The model can be used to calculate approximate prediction intervals for births using data from deterministic cohort-component forecasts. The paper compares the use of expert opinion in mortality forecasting with simple extrapolation techniques to see how useful each approach has been in the past. Data from the United States suggest that expert opinion may have caused systematic bias in the forecasts."     

Quantile regression for the qualifying match of GEFCom2017 probabilistic load forecasting

We present a simple quantile regression-based forecasting method that was applied in the probabilistic load forecasting framework of the Global Energy Forecasting Competition 2017 (GEFCom2017). The hourly load data are log transformed and split into a long-term trend component and a remainder term. The key forecasting element is the quantile regression approach for the remainder term, which takes into account both weekly and annual seasonalities, such as their interactions. Temperature information is used only for stabilizing the forecast of the long-term trend component. Information on public holidays is ignored. However, the forecasting method still placed second in the open data track and fourth in the definite data track, which is remarkable given the simplicity of the model. The method also outperforms the Vanilla benchmark consistently.     

Population forecasting theory,methods and assessments of accuracy. The magnitude of error due to different vital processes in population forecasts

The accuracy of population forecasts depends in part upon the method chosen for forecasting the vital rates of fertility, mortality, and migration. Methods for handling the stochastic propagation of error calculations in demographic forecasting are hard to do precisely. This paper discusses this obstacle in stochastic cohort-component population forecasts. The uncertainty of forecasts is due to uncertain estimates of the jump-off population and to errors in the forecasts of the vital rates. Empirically based of each source are presented and propagated through a simplified analytical model of population growth that allows assessment of the role of each component in the total error. Numerical estimates based on the errors of an actual vector ARIMA forecast of the US female population. These results broadly agree with those of the analytical model. This work especially uncertainty in the fertility forecasts to be so much higher than that in the other sources that the latter can be ignored in the propagation of error calculations for those cohorts that are born after the jump-off year of the forecast. A methodology is therefore presented which far simplifies the propagation of error calculations. It is noted, however, that the uncertainty of the jump-off population, migration, and mortality in the propagation of error for those alive at the jump-off time of the forecast must still be considered.     

An open-city model with nonmalleable housing

Previous city and housing models are extended to allow for the nonmalleability of housing and two classes of residents. The model, which is framed in the context of a monocentric circular city, assumes an individual housing unit to be defined in terms of attributes (quality and residential density). The quality of a given housing unit can be varied without adjustment costs, but changes in residential density on a particular site require prior demolition of the existing structure on the site. Producers of housing and consumers are assumed to be myopic. By assuming that the city is in short-run equilibrium at each point of time, it is shown that the pattern of land use observed at any stage depends on the past history of the city and the current rates of population growth. The possibilities for filtering of houses from one income group to another are also discussed briefly.