Traces of the Iron Curtain: A multivariate analysis of regional cohesion in Europe

The present study aims to test relative welfare differences among regions in Europe, so as to examine whether the post-communist era has led to more socio-economic cohesion in Europe. The performance of European regions is analysed, compared, and assessed by using the Regional Competitiveness Index (RCI) and stylised fixed nominal categories. The current status of regional cohesion is tested on the basis of detailed data on 268 NUTS 2 European regions by using a robust methodology oriented towards univariate comparison of location parameters, multivariate classification by the decision tree and CHAID algorithm, and comparison of nominal variables with four values based on density plots.Multivariate classification appears to offer statistically excellent results with an overall correct prediction rate for post-socialist and capitalist regions in Europe of 99.6%. The research results from the Higher education and Innovation pillars, reveal a convergence of capitalist and post-socialist regions with capital cities and a divergence of regions with administrative capitals and other regions. Relatively, the two groups which perform best are both groups with capitals, while the group of capitalist regions with a capital city is significantly better in almost all pillars.The key message is that the transition of post-socialist regions is not yet over. Capitalist regions in Europe perform better than post-socialist regions in eight of the nine pillars of regional competitiveness. Our research results also reveal that the group of post-socialist regions without capital cities are significantly lagging behind the rest of the regions in Europe, and thus form the most vulnerable group of European regions. As there is data continuity in the official RCI classification and measurement, policy makers will be able to compare the performance of their own regions over time and to design appropriate concerted strategies accordingly. From this perspective, our study draws several interesting lessons and results for policy makers at various levels. Place-based regional planning and policy based on our analysis framework may be helpful in developing effective measures to cope with the socio-economic legacy of the “Iron Curtain” and get closer to regional cohesion in Europe.     

From univariate- to multivariate analysis

This paper is intended for those who are interested in the didactics of multivariate analysis. The problem studied is: how can the transition from univariate - to multivariate analysis be made as simple as possible? Here we provide a simple “codingkey”, which works logically and is easy to remember and to handle. Some of the notations are adopted from lecture-notes by L. C. A. Corsten .     

经济法教学中如何运用任务驱动法

经济法课程内容不像应用技术类课程一样具备很强的操作性,但同样适合项目导向和任务驱动法的教学运用。文章以高职《经济法》为例,阐述了"任务驱动法"教学过程设计步骤,同时,以其中的一个子项目"公司法——有限责任公司"为例,着重阐述任务驱动法在课程单元设计中的应用。     

The use of economics in urban travel demand modelling: A survey

This paper attempts to survey the recent innovations in urban transport planning and in particular to demonstrate the increasing importance being attached to economic analysis in the travel forecasting procedures employed. The article begins by setting out traditional economic notions as they relate to travel, progresses to illustrate their practical limitations for planners and then considers the applied work which has been attempted in this field. The paper is critical of the traditional sequential forecasting procedures and attempts to present a balanced picture of the current state of explicit demand modelling which has a firmer foundation in economic theory.     

The use of control groups in evaluating regional economic policy

A major difficulty in measuring the impact of regional policy is the identification of what would have happened in the absence of the policy. Regional science may benefit from the use of quasi-experimental approaches. The specific method presented here combines the concept of control groups with the widely used shift-share framework for evaluating regional policy. Control areas are selected on the basis of their similarity to the aided region in the pre-policy period. The resulting method is sensitive to changing cyclical conditions and other exogeneous factors and traces out the time pattern of impacts.     

The production economics of economics production

How is new economic knowledge produced over time? That depends on how the expertise of authors is managed within economic journals. Using data from 41 major economics journals spanning 21 years (1994–2014), we find that both the intensive margin (article length) and extensive margin (article number) of the discipline have been growing. In particular, the extensive margin has outgrown the intensive margin, such that each article produces absolutely more but relatively less knowledge. This pattern is highly consistent with a model of within‐journal specialization. As predicted by the model, the share of an individual article shrinks less in general interest journals and in more prestigious journals, where expertise is less substitutable across topics.     

Practical estimation of multivariate densities using wavelet methods

This paper describes a practical method for estimating multivariate densities using wavelets. As in kernel methods, wavelet methods depend on two types of parameters. On the one hand we have a functional parameter: the wavelet Ø (comparable to the kernel K ) and on the other hand we have a smoothing parameter: the resolution index (comparable to the bandwidth h ). Classically, we determine the resolution index with a cross-validation method. The advantage of wavelet methods compared to kernel methods is that we have a technique for choosing the wavelet Ø among a fixed family. Moreover, the wavelets method simplifies significantly both the theoretical and the practical computations.     

The use (and abuse) of governance indicators in economics: a review

The relatively recent increase in empirical work on the relationship between governance and economic performance has come about largely as a result of the development of a series of indicators that has allowed this relationship to be quantified. For the researcher, it is important to understand the advantages and disadvantages of these indicators, both to ensure the appropriate indicator is chosen, and to be aware of the limitations each entail. To that end, this paper reviews the common indicators used in empirical analysis, as well as some of the other estimation problems that can arise when using these measures.      

关于审计失真治理非完全有效的经济学分析

注册会计师出具的审计意见是市场监管的主要手段分,但由于信息偏在和“免费乘车者”等经济学原因,在现实生活中,审计失真治理非完全有效的事例经常发生。本文认为,借鉴成熟市场经济国家经验,结合我国实际情况,强化信息沟通机制和完善“搭便车”抑制机制,寻找法律监督、政府监管、行业自律的相对较佳结合点以趋近完全有效性成为我国审计失真治理的现实选择。     

The use of spectral analysis to validate peanning models

Statistical fit of model predictions to empirical evidence is found to be an insufficient condition for establishing the validity of a planning model where the dynamic behavior is of particular importance. The paper describes a spectral analysis statistical test that can be used to validate the structure of a planning model by comparing the time series generated by the model with the actual time series of events for the real system under study. Validation of an ambulance simulation model is reported in which the model apparently was valid based on classical goodness of fit tests of aggregate data. However, following a spectral analysis of the simulation results, an entirely new method of generating incidents was found to be necessary. The resulting model then was able to duplicate realistically the essential cyclical nature of hourly demand for emergency care observed in the real system which periodically created excessive busy and idle periods not realized in the structure of the original model.     

Measurement of development and regional disparities in Greek periphery: A multivariate approach

The identification of regional disparities and regional growth patterns is an important factor affecting policy formulation. Single indicator, usually GDP-based, approaches have revealed significant shortcomings. In this work we provide a methodology and the respective tools to analyse regional disparities and development patterns. Aiming at capturing the different aspects of development and quality of life our approach is multi-dimensional: we, first, develop a composite index; we, then, apply multivariate clustering for identifying regions with similar socio-economic profiles. The methodology is applied to examine Greek regions. The results do not provide strong evidence for convergence of Greek regions during the period 1995–2007.     

Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis

The literature on mixed-frequency models is relatively recent and has found applications across economics and finance. The standard application in economics considers the use of (usually) monthly variables (e.g. industrial production) for predicting/fitting quarterly variables (e.g. real GDP). This paper proposes a multivariate singular spectrum analysis (MSSA) based method for mixed-frequency interpolation and forecasting, which can be used for any mixed-frequency combination. The novelty of the proposed approach rests on the grounds of simplicity within the MSSA framework. We present our method using a combination of monthly and quarterly series and apply MSSA decomposition and reconstruction to obtain monthly estimates and forecasts for the quarterly series. Our empirical application shows that the suggested approach works well, as it offers forecasting improvements on a dataset of eleven developed countries over the last 50 years. The implications for mixed-frequency modelling and forecasting, and useful extensions of this method, are also discussed.     

Performance of methods to conduct mediation analysis with time-to-event outcomes

Previous studies have discouraged the use of the Cox proportional hazards (PH) model for traditional mediation analysis as it might provide biased results. Accelerated failure time (AFT) models have been proposed as an alternative for Cox PH models. In addition, the use of the potential outcomes framework has been proposed for mediation models with time-to-event outcomes. The aim of this paper is to investigate the performance of traditional mediation analysis and potential outcomes mediation analysis based on both the Cox PH and the AFT model. This is done by means of a Monte Carlo simulation study and the illustration of the methods using an empirical data set. Both the product-of-coefficients method of the traditional mediation analysis and the potential outcomes framework yield unbiased estimates with respect to their own underlying indirect effect value for simple mediation models with a time-to-event outcome and estimated based on Cox PH or AFT.     

The regional variations of entrepreneurial dynamism: a mixed methods study

ABSTRACT

Given that added knowledge and deeper understanding are needed with regard to regional variations in the creation of new firms, this study seeks to answer the following two research questions: What are the variables that explain entrepreneurial dynamism and how may they be apprehended under the four necessary and complementary dimensions of this phenomenon, namely the demand, supply, institutional and spatial dimensions? And how should the nature and interrelatedness of these dimensions and their associated variables influence regional policymakers and other regional stakeholders in their efforts to stimulate entrepreneurship in their region? In order to do so, we used mixed methods to collect and analyze regional data, first doing a regression analysis of quantitative data on 97 small regions in Canada’s province of Québec, followed by a qualitative survey of regional stakeholders on eight matched pairs of regions. A phenomenological qualitative analysis was then effectuated in order to gain a deeper understanding of the research variables’ effects and thus grasp the complex socio-economic reality of entrepreneurial dynamism in a region. The results of the study confirm the importance and interrelatedness of the four dimensions of entrepreneurial dynamism in providing new insights into these questions. Moreover, the findings that results from these quantitative, qualitative and holistic analyses have implications for the policies of regional authorities and for the actions of other regional stakeholders.     

On the use of grouping methods in the analysis of residential housing markets

In this article we employ four different statistical techniques (geographic, AID, cluster and discriminant analysis) to define homogeneous groupings of houses within an urban area. Analysis of a sample of data from Fayette Country, Kentucky indicates that each of these methods produces distinguishable homogeneous groupings of properties. Predictions of house values are compared using data from Lane County, Oregon, San Mateo County, California, and Fayette County. The major conclusions of the study are that there are no discernible differences among the four methods and that predictions made ignoring the grouping information are as accurate as those obtained by grouping.     

Studying co-movements in large multivariate data prior to multivariate modelling

For non-stationary vector autoregressive models (VAR hereafter, or VAR with moving average, VARMA hereafter), we show that the presence of common cyclical features or cointegration leads to a reduction of the order of the implied univariate autoregressive-integrated-moving average (ARIMA hereafter) models. This finding can explain why we identify parsimonious univariate ARIMA models in applied research although VAR models of typical order and dimension used in macroeconometrics imply non-parsimonious univariate ARIMA representations.