A toolkit in SAS for the evaluation of multiple imputation methods

This paper outlines a strategy to validate multiple imputation methods. Rubin's criteria for proper multiple imputation are the point of departure. We describe a simulation method that yields insight into various aspects of bias and efficiency of the imputation process. We propose a new method for creating incomplete data under a general Missing At Random (MAR) mechanism. Software implementing the validation strategy is available as a SAS/IML module. The method is applied to investigate the behavior of polytomous regression imputation for categorical data.     

List augmentation with model based multiple imputation: a case study using a mixed-outcome factor model

This study concerns list augmentation in direct marketing. List augmentation is a special case of missing data imputation. We review previous work on the mixed outcome factor model and apply it for the purpose of list augmentation. The model deals with both discrete and continuous variables and allows us to augment the data for all subjects in a company's transaction database with soft data collected in a survey among a sample of those subjects. We propose a bootstrap-based imputation approach, which is appealing to use in combination with the factor model, since it allows one to include estimation uncertainty in the imputation procedure in a simple, yet adequate manner. We provide an empirical case study of the performance of the approach to a transaction data base of a bank.     

我国收入分配差距扩大对经济运行的影响

现阶段,我国的城乡居民、东西部地区收入差距呈现拉大的形势,收入分配问题已成为不可忽视的重要性议题,党和政府高度重视收入分配问题并提出了一系列改革措施。文中主要是分析了收入分配现状及其产生的相关原因,收入差距扩大对中国经济的影响及所采取的基本对策。     

Utilising Recent Advancements in Techniques for the Analysis of Incomplete Multivariate Data to Improve the Data Quality Management of Current Academic Research

This paper discusses the importance of managing data quality in academic research in its relation to satisfying the customer. This focus is on the data completeness objectivedimension of data quality in relation to recent advancements which have been made in the development of methods for analysing incomplete multivariate data. An overview and comparison of the traditional techniques with the recent advancements are provided. Multiple imputation is also discussed as a method of analysing incomplete multivariate data, which can potentially reduce some of the biases which can occur from using some of the traditional techniques. Despite these recent advancements in the analysis of incomplete multivariate data, evidence is presented which shows that researchers are not using these techniques to manage the data quality of their current research across a variety of academic disciplines. An analysis is then provided as to why these techniques have not been adopted along with suggestions to improve the frequency of their use in the future. Source-Reference. The ideas for this paper originated from research work on David J. Fogarty's Ph.D. dissertation. The subject area is the use of advanced techniques for the imputation of incomplete multivariate data on corporate data warehouses.     

Unveiling Urban Sprawl in the Mediterranean Region: Towards a Latent Urban Transformation?

The relationship between form and function in European Mediterranean cities has been widely addressed from various perspectives. A number of studies indicate that, until the 1980s, compactness was a key trait of several cities of the Northern Mediterranean. However, after the ‘compact growth’ period, these cities experienced patterns of urbanization that differed from their traditional trends. Since the 1990s, sprawl, coupled with population decline in the inner cities, has become the main pattern of urban development. This article explores the key features of exurban development in the Mediterranean region in order to provide material for a discussion based on the differences and similarities in the characteristics of sprawl processes originating in the US and Northern Europe. It concludes that any debate on policy responses to sprawl must be specifically formulated according to the scope, administrative level, housing and planning system, territorial and socioeconomic characteristics of the urban system under examination. It is our belief that sprawl requires site‐specific analyses and policy strategies for the region being studied if the process is to be effectively controlled.     

会计信息与股票价格关系分析

一直以来会计界试图通过会计信息解释股票价格。本文在总结国内外理论与实证研究的基础上,分析了这一研究领域的发展,并通过引入剩余收益模型,探讨会计信息与股票价格之间的关系。     

Multiple imputation of incomplete zero‐inflated count data

Empirical count data are often zero‐inflated and overdispersed. Currently, there is no software package that allows adequate imputation of these data. We present multiple‐imputation routines for these kinds of count data based on a Bayesian regression approach or alternatively based on a bootstrap approach that work as add‐ons for the popular multiple imputation by chained equations (mice ) software in R (van Buuren and Groothuis‐Oudshoorn , Journal of Statistical Software, vol. 45, 2011, p. 1). We demonstrate in a Monte Carlo simulation that our procedures are superior to currently available count data procedures. It is emphasized that thorough modeling is essential to obtain plausible imputations and that model mis‐specifications can bias parameter estimates and standard errors quite noticeably. Finally, the strengths and limitations of our procedures are discussed, and fruitful avenues for future theory and software development are outlined.     

Local Labour Markets and the Interregional Mobility of Italian University Students

Abstract

This paper looks at a little-explored role that universities can play: that of representing a channel for brain gain, enabling regions to attract bright students who may decide to stay after they have graduated. In this way, universities can be a source of selective migration processes and possibly of diverging development paths, by augmenting the capability of economically dynamic regions to attract bright people from the lagging regions. In this paper, we argue that student mobility behaviour is a function not only of the quality of universities, but also of local labour market conditions in the destination locations. The paper relies on a gravity model, and shows that graduate migrations respond to several determinants, among which graduate job vacancies (that is, the dynamism of the local labour market) appear to be essential.     

收入增长的俱乐部效应

本文通过选取1993—2013年省域面板数据,基于俱乐部收敛的视角对收入增长和中等收入陷阱的关系进行实证研究。分析结果表明中国自改革开放以来尤其是20世纪90年代初市场经济体制确立后,各省域经济出现了明显的俱乐部趋同现象,分为东部地区的富裕省份俱乐部和中、西部地区相对落后省份俱乐部。这种长期的地区经济发展失衡不利于中国收入分配改革的有效实施。本文进一步选取教育、科研、制度、收入差距等条件变量,实证结果显著表明它们是影响地区间俱乐部效应的主要因素。跨越“中等收入陷阱”成功和失败的国家都离不开同以上四要素的联系,也正符合中国供给侧改革的政策内涵。     

Income and Expenditure Switching Among the Impoverished During Structural Adjustment in India1

The impoverishment during 1991–1993 was largely a result of policy reforms. In the absence of income switching, the impoverishment would have been greater. The patterns of income switching differed among the three Indian states, viz. Andhra Pradesh, Maharashtra and Karnataka. Confining the analysis to household expenditure on food, medical care and education, however, little, if any, expenditure switching occurred. To some extent, the effects of household expenditure cuts were compounded by cuts in public expenditure. But, given the aggregate expenditure categories, there is a risk of overstating the effects on the poor. A more fundamental concern nonetheless remains. Given the acute deprivation of a large segment of the rural population, it is imperative that public provision of basic goods and services is strengthened. A case in point is the public distribution system for food (PDS). Despite the revamping, the benefits to the poor have not increased while the subsidy has. Short of drastic reforms, it is unlikely that the cost-effectiveness of the PDS will improve.     

我国各省区生产集中度演变实证研究

威廉姆森(Williamson)提出了一个著名的有关一国生产空间分布演变的倒U型假说,即一国或地区的生产集中度会随着经济发展水平的提高而呈现先增大后减小的变化趋势。本文运用我国1996-2009年省际面板数据对该假说进行了实证检验。实证研究的结果支持了这一假说:随着经济发展水平的提高,我国生产集中度呈现出先上升后下降的倒U型演变过程。     

Rethinking Regional Disparity in China

Income disparities in China decreased both across provinces and across three transprovincial areas from 1978 through 1984. After 1984 there was an increase in disparity across the three areas, but there was no change across provinces. The faster growth of the coastal area can be attributed to the growth of the previously relatively poorer areas of the eastern seaboard. But this was not realised at the cost of growth in other areas; instead it contributed to overall national economic growth. International trade and foreign direct investment are the main driving forces behind the changes in regional disparity. The reasons for the concentration of trade and foreign investment in the coastal area are its inherent comparative advantage in terms of lower labour costs, better infrastructure facilities, close relations with overseas Chinese, favourable geographic location, as well as national industrial policies that protect the domestic market from foreign investment. The central government's preferential policies towards the coastal area were a necessary, but not sufficient, condition for such a concentration of foreign trade and investment.     

金融集聚、区域房价如何影响产业结构升级：双轮驱动还是双向抑制？

金融集聚和区域房价对产业结构升级的影响机制可以从地理角度和经济角度运用空间杜宾模型来考察。研究结果显示,金融集聚、区域房价及产业结构升级存在较强的正向空间自相关性,呈现出较强的扩散效应和示范效应。金融集聚通过资源配置效应、规模经济效应、创新激励效应和风险管理效应等路径来影响产业结构升级,区域房价通过成本效应和劳动力供给效应等路径来影响产业结构升级。金融集聚、区域房价对产业结构升级均有显著的正向促进作用;两者互动对产业结构升级有显著抑制作用,但存在明显的地区差异性。科技创新、外商直接投资及教育水平对产业结构升级有积极的促进作用,政府干预程度对产业结构升级有明显的阻碍作用。     

A Non-Iterative Bayesian Approach to Statistical Matching

Data fusion or statistical matching techniques merge datasets from different survey samples to achieve a complete but artificial data file which contains all variables of interest. The merging of datasets is usually done on the basis of variables common to all files, but traditional methods implicitly assume conditional independence between the variables never jointly observed given the common variables. Therefore we suggest using model based approaches tackling the data fusion task by more flexible procedures. By means of suitable multiple imputation techniques, the identification problem which is inherent in statistical matching is reflected. Here a non-iterative Bayesian version of Rubin's implicit regression model is presented and compared in a simulation study with imputations from a data augmentation algorithm as well as an iterative approach using chained equations.