Entry into Consensual Unions and Marriages Among Finnish Women Born Between 1938 and 1967

This study, based on a survey undertaken in 1989, clearly illustrates the dramatic changes in family formation behaviour that have occurred in Finland. Whereas only about one-tenth of the first unions of women born between 1938 and 1942 began as consensual unions, after the cohort of 1962 only one-tenth were formal marriages. These changes lagged some ten years behind the corresponding ones in Sweden, but were about five years ahead of Norway. In Finland, up to the present, most consensual unions have constituted a temporary state which precedes proper family life. Most couples married in connection with the birth of the first child. Consensual union as a permanent lifestyle is generally connected with a low level of education of women.     

十年来中国抗争运动研究评述

上世纪90年代以来,中国的抗争运动爆发的频度和影响力不断增长,吸引了越来越多研究者的关注,海内外关于这一题域的研究也日渐兴起。这一研究题域在概念谱系上呈现出多元化的状态,以过程分析、结构分析和机制分析作为其主要的分析路径,以集体行动、日常抵抗、社会动员以及政治过程等理论为指导,并特别关注抗争运动与民主政治的关系;在研究方法上,规范性实证研究的比例正在上升,定量研究和比较研究是未来的发展方向。     

HT模型在健康人力资本对个人收入影响中的应用研究

由于在收入—健康模型中健康具有内生性,导致OLS估计结果有偏,但目前国内对此问题研究不足。采用HT模型,在有效控制健康等变量的内生性后,分析健康人力资本对个人收入的影响。通过比较发现：HT模型是比传统的FE模型更为有效的模型,能够更为精确地反映健康对个人收入的影响。     

进口需求函数选择及弹性分析——以美国苹果汁进口需求为例

运用2002年1月至2010年12月间,共108组美国苹果汁进口月度数据,比较分析Barten（1993）发展的一般化需求模型与其交错的四种可微分的需求模型,探寻和检验适合美国苹果汁进口需求数据资料的模型形式;对模型的加总性、齐次性、对称性、自变量内生性、需求系统的拟合优度进行检验,结果显示：一般化需求模型更符合数据资料。美国对中国苹果汁进口需求的支出弹性显著为正;受中国苹果汁自价格影响不显著;中国苹果汁对美出口的主要竞争国家是加拿大。     

A robust test of exogeneity based on quantile regressions

In this paper, we propose a robust test of exogeneity. The test statistics is constructed from quantile regression estimators, which are robust to heavy tails of errors. We derive the asymptotic distribution of the test statistic under the null hypothesis of exogeneity at a given quantile. The finite sample properties of the test are investigated through Monte Carlo simulations that exhibit not only good size and power properties, but also good robustness to outliers.     

Welfare gains of the poor: An endogenous Bayesian approach with spatial random effects

We introduce a Bayesian instrumental variable procedure with spatial random effects that handles endogeneity, and spatial dependence with unobserved heterogeneity. We find through a limited Monte Carlo experiment that our proposal works well in terms of point estimates and prediction. We apply our method to analyze the welfare effects generated by a process of electricity tariff unification on the poorest households. In particular, we deduce an Equivalent Variation measure where there is a budget constraint for a two-tiered pricing scheme, and find that 10% of the poorest municipalities attained welfare gains above 2% of their initial income.     

Near exogeneity,weak identification and specification testing: Some asymptotic results

The paper studies the asymptotic size property of various specification tests in linear structural models where instrumental variables may locally violate the exclusion restrictions. Our results provide some new insights and extensions of earlier studies. In particular, we derive an explicit formula of the asymptotic size of the tests which shows clearly the factors that influence their size under instrument endogeneity. We show that all tests have correct asymptotic size when the usual orthogonality condition holds, but their asymptotic size can be arbitrary large even if only one instrument is slightly correlated with the error term. We present a Monte Carlo experiment that confirms our theoretical findings.     

Correlated discrete and continuous outcomes with endogeneity and lagged effects: past season yield impact on improved corn seed adoption

Farmers in Sub-Saharan Africa have lower agricultural technology adoption rates compared to the rest of the world. It is believed that the past season yield affects a farmer''s capacity to take on the riskier improved seed variety; but this effect has not been studied. We quantify the effect of past season yield on improved corn seed use in future seasons while addressing the impact of the seed variety on yield. We develop a maximum likelihood method that addresses the fact that farmers self-select into a technology resulting in its effect on yield being endogenous. The method is unique since it models both lagged and endogenous effects in correlated discrete and continuous outcomes simultaneously. Due to the prescence of the lagged effect in a three year dataset, we also propose a solution to the initial conditions problem and demonstrate with simulations its effectiveness. We used survey longitudinal data collected from Kenyan corn farmers for three years. Our results show that higher past season yield increased the likelihood of adoption in future seasons. The simulation and empirical studies indicate that ignoring the self selection of improved seed use biases the results; we obtain a different sign in the covariance.     

农民工收入与村庄网络 基于多重模型识别策略的因果效应分析

以往基于家庭网和社交网的实证研究表明,社会网络对农民工的工资收入没有影响。这些结论的得出,很大程度上是由于对农民工个人网的范围界定不准,且对内生性问题解决不够。本文采用22个省份的农户调查数据,针对中国农民工频繁返乡的特点,证实同村打工网的规模与农民工在城市中的收入具有正向因果关系。为解决影响因果判断的内生偏误问题,本文采取赫克曼二阶段法和工具变量方法组合使用的多重模型识别策略,把村庄遭受的自然灾害强度作为工具变量。     

Solving endogeneity problems in multilevel estimation: an example using education production functions

This paper explores endogeneity problems in multilevel estimation of education production functions. The focus is on level 2 endogeneity which arises from correlations between student characteristics and omitted school variables. Theses correlations are mainly the result of student stratification between schools. From an econometric point of view, the correlations between student and school characteristics imply that the omission of some variables may generate endogeneity bias. Therefore, an estimation approach based on the Mundlak [20 Mundlak, Y. 1978. On the pooling of time series and cross-sectional data. Econometrica, 46: 69–86. [Crossref], [Web of Science ®] , [Google Scholar]] technique is developed in order to tackle bias and to generate consistent estimates. Note that our analysis can be extended to any multilevel-structured data (students nested within schools, employees within firms, firms within regions, etc). The entire analysis is undertaken in a comparative context between three countries: Germany, Finland and the UK. Each one of them represents a particular system. For instance, Finland is known for its extreme comprehensiveness, Germany for early selection and the UK for its liberalism. These countries are used to illustrate the theory and to prove that the level of bias arising from omitted variables varies according to the characteristics of education systems.