Virtual special issue on urban development

This virtual special issue of Spatial Economic Analysis marks the keynote lecture at the 47th Annual Conference of the Regional Science Association International – British and Irish Section in Harrogate by Professor Bob Stimson of the University of Queensland, Australia. With over half the world’s population now living in urban areas, which according to the United Nations is expected rise to 66% by 2050, the theme of Professor Stimson’s lecture – urban development – is of critical importance. Cities provide significant opportunities for economic growth and development as long as urban design models are not only effective but also sustainable, inclusive and equitable. This virtual special issue draws together 10 articles from earlier issues of the journal, which inform a successful urban design agenda.     

Recent advances in financial networks and agent-based model validation

We introduce the papers appearing in the special issue of this journal associated with the WEHIA 2015. The papers in issue deal with two growing fields in the in the literature inspired by the complexity-based approach to economic analysis. The first group of contributions develops network models of financial systems and show how these models can shed light on relevant issues that emerged in the aftermath of the last financial crisis. The second group of contributions deals with the issue of validation of agent-based model. Agent-based models have proven extremely useful to account for key features economic dynamics that are usually neglected by more standard models. At the same time, agent-based models have been criticized for the lack of an adequate validation against empirical data. The works in this issue propose useful techniques to validate agent-based models, thus contributing to the wider diffusion of these models in the economic discipline.     

Econometric modelling in finance and risk management: An overview

This paper gives an overview about the sixteen papers included in this special issue. The papers in this special issue cover a wide range of topics. Such topics include discussing a class of tests for correlation, estimation of realized volatility, modeling time series and continuous-time models with long-range dependence, estimation and specification testing of time series models, estimation in a factor model with high-dimensional problems, finite-sample examination of quasi-maximum likelihood estimation in an autoregressive conditional duration model, and estimation in a dynamic additive quantile model.     

Global imbalances and dynamics of international financial markets

We provide an overview of the special issue “Global Imbalances and dynamics of international financial markets”. This special issue, which is associated with the 7th International Finance Conference, features research papers dealing with the impact of global imbalances, market complexity, and the impact of the recent global financial crisis on the conduct of monetary policies, financial market dynamics, financial stability, and risk management models.     

Oil supply projection techniques: Past developments and future requirements

This paper presents a critical assessment of the development of economic models of oil supply projection over the last two decades. The survey illustrates the fact that although most models have stressed the significance of the economic variables in the supply function, few attempts have been made to incorporate technology as a variable. Although such an approach can be justified under certain special circumstances, it is considered unsuitable as a supply forecaster in the increasingly numerous marginal fields where operations approach the technology frontier. In this connection, the latter part of the paper discusses the possibility of and problems associated with incorporating technology as a variable in the projection of supply.     

Evaluation of the best M4 competition methods for small area population forecasting

The ‘M4’ forecasting competition results were featured recently in a special issue of the International Journal of Forecasting and included projections for demographic time series. We sought to investigate whether the best M4 methods could improve the accuracy of small area population forecasts, which generally suffer from much higher forecast errors than regions with larger populations. The aim of this study was to apply the top ten M4 forecasting methods to produce 5- and 10-year forecasts of small area total populations using historical datasets from Australia and New Zealand. Forecasts were compared against the actual population numbers and forecasts from two simple benchmark models. The M4 methods were found to perform relatively well compared to our benchmarks. In the light of these findings, we discuss possible future directions for small area population forecasting research.     

Solving the multi-country Real Business Cycle model using a monomial rule Galerkin method

I propose a Galerkin projection method for solving dynamic economic models with many state variables. This method employs non-product monomial integration formulas for the computation of weighted residuals, and its computational cost therefore increases only polynomially in the model's dimensionality. I illustrate the practical implementation of the proposed algorithm by solving several specifications of the multi-country Real Business Cycle model described in Den Haan et al. [2010. Computational suite of models with heterogeneous agents: multi-country Real Business Cycle models. Journal of Economic Dynamics and Control, this issue], and briefly discuss two possible routes for further improving its numerical accuracy.     

Meta‐Analytic Research in Management: Contemporary Approaches,Unresolved Controversies,and Rising Standards

Early meta‐analyses in management research sought primarily to resolve seemingly conflicting findings by estimating a relationship’s population‐level effect size. Since then, management researchers have adopted increasingly sophisticated approaches that permit new theorizing, testing and comparing sophisticated models, and identifying boundary conditions. We summarize three of these approaches – i.e., qualitative meta‐analysis (QMA), meta‐analytic structural equation modeling (MASEM), and meta‐analytic regression analysis (MARA) – along with the special issue papers that adopt each approach. We conclude by raising three unresolved controversies that we believe deserve more attention and by offering our thoughts about how to maximize a meta‐analytic study’s chances for publication and impact.     

Robustness of normal theory statistics in structural equation models*

A condition is given by which optimal normal theory methods, such as the maximum likelihood methods, are robust against violation of the normality assumption in a general linear structural equation model. Specifically, the estimators and the goodness of fit test are robust. The estimator is efficient within some defined class, and its standard errors can be obtained by a correction formula applied to the inverse of the information matrix. Some special models, like the factor analysis model and path models, are discussed in more detail. A method for evaluating the robustness condition is given.     

Using Medicare data for short-run projections of the elderly population.

As the elderly population of the United States grows in absolute number and as a proportion of total population, accurate projections of that population become increasingly important for sound policy decisions. Cohort component techniques are typically used for state and local projections of the elderly population, but are often outdated or even nonexistent for many local areas. This paper suggests an alternative approach, based on Medicare data and simple projection techniques. Projections for several base periods and projection horizons are made for all states and for counties in Florida and are compared with actual Medicare enrollment. On the basis of these comparisons it appears that Medicare data and simple projection techniques can produce very useful short-run projections of the elderly population for states and local areas.     

Employment predictions in social impact assessment: An analysis of some unexplored variables

Social scientists investigating the impacts of energy development are increasingly searching for predictive models of the employment benefits to locals. This issue is of extreme importance not only because of the benefits to locals but because of the issue of local benefits as well as the connection with population growth and boom town development. Unfortunately, some of the recent investigations and predictive models are of little utility as a result of certain analytical and methodological faults, including improper assumptions about local labor supply and local preferences. In addition to the assessment of previous investigations, a framework for predicting local employment impacts is suggested. This framework utilizes characteristics and preferences of the local population.     

Spatial dynamics and metropolitan change

"This special issue presents contributions to a collaborative effort to analyze 'the dynamics of metropolitan processes and policies'....[It] contains four papers which focus on industrial change and economic restructuring; two papers deal with population relocation and migration processes; one paper contains a study of economic cycles in space and one paper treats the assessment of urban investment and urban renewal projects." The geographic focus is on the developed countries.     

Upcoming picture of ageing population: Pakistan

Ageing of population may have its implications at individual, family, community and economic level. This paper explains how ageing population will behave in the future based on projection assumptions. Future prospects and issues are identified and categorized alongwith relevance of ageing population trend examined in a survey. The findings demonstrate that ageing population of Pakistan will increase in the forthcoming years. Among several reasons for increase in ageing population, the most important is decline in death rate. The overall sex ratio indicates a better coverage of female in coming decades. For the next 50 years, the life expectancy may rise to 70.7 years. The old age dependency ratio may also increase in the times to come. Married elderly females may be less in number as compared to married elderly males. The high prevalence of other-than-married elderly females deserves special consideration in policy-making and planning. There exists much variation in the literacy rate of both elderly male and female. As the study reflects future pattern of ageing population, its findings may be of interest for researchers and practitioners.     

Modeling demographic-economic interactions: Micro, macro and linked micro/macro strategies

The inherent limitations of group-based macro modeling preclude a realistis behavioral representation of regional demographic-economic interactions. Such a harsh assessment is unwelcome news to regional modelers, who for the most part have been relying on group-based macro strategies. This paper addresses the issue of choosing the most appropriate approach to regional demographic-economic modeling by emphasizing once again the severe limitations of group-based macro models for representing population behavior, advocating instead the use of sample-based micro models for representing population behavior and suggesting that a linked macro/micro strategy for modeling demographic-economic interactions might combine the advantages of both modeling methodologies.     

Knowledge spillover-based strategic entrepreneurship

Research on knowledge spillovers (KS) has each been the subject of much scholarly attention, but has mostly been considered independently rather than in combination with each other important issue – strategic entrepreneurship (SE). The purpose of this special issue is to integrate these two approaches and to develop theory in addition to empirically investigate the phenomenon inspiring future research on the topic. This paper draws on the knowledge spillover-based strategic entrepreneurship in a multilevel context, examines the logic of the approach, and introduces the special issue by summarizing the papers contributions. Future research suggestions from the papers included in the special journal issue are also discussed and explained.     

Introduction to internally consistent modeling,aggregation, inference,and policy

This special issue of the Journal of Econometrics honors William A. Barnett’s exceptional contributions to unifying economic theory with rigorous statistical inference to interpret economic data and inform public policy. It is devoted to papers that advance microeconometrics, macroeconometrics, and financial econometrics to build models to interpret evidence.     

Copula-based multivariate GARCH model with uncorrelated dependent errors

Multivariate GARCH (MGARCH) models are usually estimated under multivariate normality. In this paper, for non-elliptically distributed financial returns, we propose copula-based multivariate GARCH (C-MGARCH) model with uncorrelated dependent errors, which are generated through a linear combination of dependent random variables. The dependence structure is controlled by a copula function. Our new C-MGARCH model nests a conventional MGARCH model as a special case. The aim of this paper is to model MGARCH for non-normal multivariate distributions using copulas. We model the conditional correlation (by MGARCH) and the remaining dependence (by a copula) separately and simultaneously. We apply this idea to three MGARCH models, namely, the dynamic conditional correlation (DCC) model of Engle [Engle, R.F., 2002. Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics 20, 339–350], the varying correlation (VC) model of Tse and Tsui [Tse, Y.K., Tsui, A.K., 2002. A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations. Journal of Business and Economic Statistics 20, 351–362], and the BEKK model of Engle and Kroner [Engle, R.F., Kroner, K.F., 1995. Multivariate simultaneous generalized ARCH. Econometric Theory 11, 122–150]. Empirical analysis with three foreign exchange rates indicates that the C-MGARCH models outperform DCC, VC, and BEKK in terms of in-sample model selection and out-of-sample multivariate density forecast, and in terms of these criteria the choice of copula functions is more important than the choice of the volatility models.     

总体应计利润模型计量偏差分析

总体应计利润法是计量盈余管理水平最常用的方法。本文对总体应计利润具体模型进行了全面梳理,对其计量偏差存在的证据与产生原因进行了详细分析,指出了产生计量偏差的主要原因。针对国内研究现状,提出开发更优的总体应计利润模型、修正现有模型以及扩大总体应计利润法运用范围的建议。     

交互效应面板模型的EM算法和MCMC算法

交互效应面板模型是目前计量经济学前沿研究的热点,有着广阔的应用空间。但是对很多应用者而言,模型内的参数估计是一个非常棘手的问题。通常的Newton-Raphson算法在优化似然函数的过程中,常常会出现优化失败的情况。本文依据EM算法和MCMC算法理论,为应用研究者提供了一套获得参数估计值的流程。计算机上的试验证实两种估计方法都非常稳健可靠,并在很多情况下,差异不是很大。     

Managerial third party dispute resolution: An overview and introduction to the special issue

In this article I review each of the five articles included in the special issue on managerial third party dispute resolution. This review is followed by a brief listing of the goals for this special issue and three suggestions for future research. These suggestions include the need for more focus on the nonunion sector, a call for interdisciplinary research, and a plea for research concentrating on managerial third party dispute resolution in other cultures.