Exploratory data structure comparisons: three new visual tools based on principal component analysis

Datasets are sometimes divided into distinct subsets, e.g. due to multi-center sampling, or to variations in instruments, questionnaire item ordering or mode of administration, and the data analyst then needs to assess whether a joint analysis is meaningful. The Principal Component Analysis-based Data Structure Comparisons (PCADSC) tools are three new non-parametric, visual diagnostic tools for investigating differences in structure for two subsets of a dataset through covariance matrix comparisons by use of principal component analysis. The PCADCS tools are demonstrated in a data example using European Social Survey data on psychological well-being in three countries, Denmark, Sweden, and Bulgaria. The data structures are found to be different in Denmark and Bulgaria, and thus a comparison of for example mean psychological well-being scores is not meaningful. However, when comparing Denmark and Sweden, very similar data structures, and thus comparable concepts of well-being, are found. Therefore, inter-country comparisons are warranted for these countries.     

Carbon dioxide emissions and economic growth: A structural approach

This paper uses data for 44 countries from 1970-1990, to investigate the relationship between economic growth and carbon dioxide emissions. Empirical results are obtained from a structural model from the empirical growth literature modified to include environmental 'bads'. Results suggest that richer countries exhibit technical progress in a way that economizes on carbon dioxide emissions but that poorer countries do not. Furthermore, there is no indication that the growth process is leading poorer countries to move towards the adoption of the same pollution-ameliorating technology as characterizes richer countries.     

Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence

This article investigates the possibility, raised by Perron and by Rappoport and Reichlin, that aggregate economic time series can be characterized as being stationary around broken trend lines. Unlike those authors, we treat the break date as unknown a priori. Asymptotic distributions are developed for recursive, rolling, and sequential tests for unit roots and/or changing coefficients in time series regressions. The recursive and rolling tests are based on changing subsamples of the data. The sequential statistics are computed using the full data set and a sequence of regressors indexed by a “break” date. When applied to data on real postwar output from seven Organization for Economic Cooperation and Development countries, these techniques fail to reject the unit-root hypothesis for five countries (including the United States) but suggest stationarity around a shifted trend for Japan.     

国际资本约束与顺周期财政政策

本文首次建立理论模型证明了国际资本约束是发展中国家顺周期财政政策形成的重要动因。同时基于125个发展中国家1960-2016年的面板数据，得到了与理论预期一致且稳健的经验证据：发展中国家呈现出顺周期财政政策的典型事实。在充分考虑内生性问题，引入加权的贸易伙伴实际GDP增长率和加权的美国国债实际收益率作为有效工具变量后，这一结论仍然成立；主权信用评级每下调1个级别，顺周期财政政策倾向将会增加5.83%。这种国际资本市场的劣势地位所引致的国际资本强约束，是发展中国家采用顺周期财政政策的关键原因。本文的研究在经验上丰富了关于发展中国家顺周期财政政策成因的讨论，为深化发展中国家之间的国际合作与互助提供了政策启示。     

中美CPI数据质量的比较分析

 本文在国际货币基金组织提出的消费者价格指数数据质量评估框架下，着重从四个维度分析了中美两国CPI数据质量方面存在的差异，并在此基础上提出了相关结论和建议。     

Which countries will follow the Scandinavian lead in taking a register-based census of population?

"During the past twenty years Scandinavian countries have made changes in the methods of taking population and housing censuses that are more fundamental than any seen since modern census methods were first introduced two hundred years ago. These countries extract their census data in part or in whole from administrative registers. If other countries in Western Europe were to adopt this approach, most of them would have to make major improvements to their administrative records. But the primary reasons for making such improvements are concerned with administration and policy rather than statistics, namely, the need to secure a more effective and fairer system of public administration and to enable governments to exercise a wider range of policy options."     

Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53-78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L-F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199-225] are extended to higher-order dynamic panel data models with general covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I-1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are sometimes considerable.     

Determinants of Contraceptive Use in Egypt: A Multilevel Approach

The increasing use of family planning methods seems to be the intermediate determinant which mostly influences the fertility decline in developing countries, and in particular in those countries which are in an advanced phase of demographic transition such as Egypt. Moreover large countries, like Egypt, are characterized by very different geographical realities and even by strong regional heterogeneities. The aim of this study is the analysis of the determinants of contraceptive use in Egypt, with particular reference to the differentials due to the socio-economic context and to the area of residence. To estimate each individual and regional factors’ effect on contraceptive use, a logistic two-level random intercept model is fitted to EDHS 2000 data; the use of a multilevel analysis is suggested by the two-level data structure: the first level units are the women, the second level units are their regions of residence.     

“一带一路”倡议背景下中国高新技术产品对阿拉伯国家出口流量及潜力分析

"一带一路"倡议规划了中国向西开放的格局,地处"一带一路"西端交汇地带的阿拉伯国家成为中国天然和重要的合作伙伴。通过分析中国高新技术产品对阿拉伯国家的出口现状,发现出口结构不合理;采用引力模型,通过面板数据实证检验了影响中国高新技术产品对阿拉伯国家出口的不同因素,并从高新技术产品总量层面和大类层面上分别测算了中国对部分阿拉伯国家的出口潜力;根据实证检验结果提出了政策建议。     

OECD国家能源消费、经济增长与碳排放关系研究

基于面板数据模型,分析1971--2006年间28个OECD国家能源消费、经济增长和碳排放之间的关系,再根据面板数据的单位根检验和协整性检验,确定三者之间存在长期的均衡关系。通过固定影响变系数模型的估计发现：碳排放与能源消费呈显著的正相关关系,各国碳排放的能源消费弹性系数存在明显的差异;从长期看,部分国家碳排放与GDP的关系呈现倒“U”形,部分国家呈“U”形。     

金砖国家经济增长源泉的异质性及强度研究——基于互联网、金融发展和法治水平的视角

国家的异质性导致了各国经济增长源泉具有较强的差异性。运用2003年至2013年金砖国家经济发展数据,构建面板数据门槛回归模型,研究互联网、金融发展及法治水平对金砖国家经济增长的影响。实证结果表明:互联网对金砖国家经济增长促进作用并不显著,现阶段金融发展对经济增长推动作用有限。但随着法治水平的提高,金融发展对经济增长的推动作用呈J字型增长,法治水平的提高有利于推动金砖国家金融发展。加强互联网、金融及法治建设将为金砖国家经济增长注入新的动力。     

An empirical investigation into the effect of childbearing on economic wellbeing in Europe

This paper investigates the extent childbearing among couples in Europe affects their level of economic well being. We do so by implementing a propensity score matching procedure in combination with a difference-in-difference estimator. Using data from European Community Household Panel Survey (ECHP), we compare how the impact of childbearing on wellbeing varies among countries. We use several measures for wellbeing, including poverty status and various deprivation indices that take into account the multidimensionality of individuals‘ assessment of wellbeing. Not unexpected we find childbearing tend to worsen the economic wellbeing of households, but with important differences in magnitude across countries. In Scandinavian countries the effect is small and rarely significant, it is strong in the UK and also significant in Mediterranean countries. Depending on the measure of wellbeing, we find important differences among countries that are similar in terms of welfare provision.     

Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Abstract

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53–78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L‐F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199–225] are extended to higher‐order dynamic panel data models with general covariance structure. The focus is on estimation of both short‐ and long‐run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I–1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long‐run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross‐correlation patterns between countries are sometimes considerable.     

不同收入水平国家能源库兹涅茨曲线走势分析

 本文根据世界银行2008年高收入、中等收入和低收入的划分标准,选择了22个高收入国家、17个中等收入国家和13个低收入国家,结合这些国家1980-2009年人均GNI和能源消耗数据,利用能源库兹涅茨曲线分析法,分别拟合了这些国家的能源库兹涅茨曲线,并确定了各自的拐点,归纳了不同收入水平国家的能源库兹涅茨曲线的变动特征,得出了随着收入水平的提高,各国EyKC由“倒U型”左半部上升通道逐步向顶部趋近,直至进入EyKC的下降通道的结论。     

Modeling Technology as a Dynamic Error Components Process: The Case of the Inter-country Agricultural Production Function

In this paper, we propose a dynamic error-components model to represent the unobserved level of technology. This specification implies a well-defined common factor dynamic model for per capita output that can be tested explicitly. The model is applied to data on aggregates of agricultural inputs and outputs for groups of countries from the OECD, Africa (AF), Latin America (LA) as well as centrally planned countries, over a period of 31 years. We find that the proposed model fits the data better than alternative static specifications and satisfies the implied common factor restrictions in two of the samples. The results suggest that although technological change seems to have been a faster process for less developed countries relative to the OECD countries, it has not been fast enough to reduce appreciably the enormous differences in average technological levels that still persist between them.     

A fortran subroutine for computing indicators of the nutritional status of children and adolescents

For the nutritional status of children in developing countries the anthropometric standardized scores (SD-scores) WEHE, WEAG, HEAG based on an international reference population are recommended. The evaluation of data in terms of SD-scores are widely used. This paper provides the FORTRAN-subroutine SDSC for the calculation of those scores directly refering to the reference data. The application of this subroutine is demonstrated.     

Penalized least squares smoothing of two-dimensional mortality tables with imposed smoothness

This paper presents a method to estimate mortality trends of two-dimensional mortality tables. Comparability of mortality trends for two or more of such tables is enhanced by applying penalized least squares and imposing a desired percentage of smoothness to be attained by the trends. The smoothing procedure is basically determined by the smoothing parameters that are related to the percentage of smoothness. To quantify smoothness, we employ an index defined first for the one-dimensional case and then generalized to the two-dimensional one. The proposed method is applied to data from member countries of the OECD. We establish as goal the smoothed mortality surface for one of those countries and compare it with some other mortality surfaces smoothed with the same percentage of two-dimensional smoothness. Our aim is to be able to see whether convergence exists in the mortality trends of the countries under study, in both year and age dimensions.     

Some statistical analysis issues at the World Fertility Survey

"The World Fertility Survey carried out cross-sectional probability surveys of fertility in more than 40 developing countries between 1972 and 1984. Statistical issues in regression analysis of the data are reviewed, including treatment of interactions, the selection of regressor variables, and appropriate linear models for rate variables. Similar issues arise in many other applications of regression to observational data."