中国人口因素对寿险需求影响的实证分析

应用双对数线性回归模型、岭回归模型对中国寿险需求进行实证分析。着重分析了人口因素对寿险需求的影响，在分析中引入了虚拟变量，并对多重共线性问题利用岭回归加以改善。研究表明：人口的城乡结构对中国寿险需求起着决定性的作用；城镇居民年人均可支配收入与寿险需求有显著的正相关性；少儿负担系数及银行实际利率与寿险需求有显著的负相关关系；受教育程度对寿险需求有显著的正面作用；而老年负担系数显示了对寿险需求正面的但不十分显著的影响。     

养老保险个人账户参数设定错误与纠正

我国基本养老保险采取统账结合的制度模式。其中，个人账户采用记账方式建立了参保缴费与养老待遇之间的直接联系。理论上，公平和长期可持续的个人账户模式在记账利率、计发系数、余额继承等方面应遵循精算原则，但我国的个人账户参数设定存在不少违背精算公平和精算平衡原则的错误。本文结合国际经验，在剖析我国养老保险个人账户参数设定错误的基础上，基于精算平衡原理，探讨参数设定方法，检验纠正方案对制度精算公平和精算平衡性的效果，最后提出参数改革的具体建议。主要结论是：个人账户的记账利率应该是制度的内含回报率；名义账户的记账利率不是银行存款利率，而应随缴费工资增长率、人口预期寿命的变动等定期调整；养老金计发系数应基于动态生命表、养老金调整指数和个人账户内含回报率的变动而调整。由此确定的参数纠正方案将有效改善制度的精算公平与精算平衡性。因而建议我国基本养老保险个人账户应尽早明确现收现付的筹资模式和账户余额的权益归属，采用动态的记账利率和计发月数，引入自动平衡机制，实现制度的长期精算平衡。     

生命不确定性的跨期最优消费行为研究

 本文首先根据中国收入分配制度的特点将消费者的生命周期区分为退休前和退休后，分别设置新古典经济学生命周期消费(Life-Cycles)理论的跨期预算约束；在生命不确定性的假设下，推导出了消费者的最优消费路径。而且，依据1988年1月-2008年12月天津市的城市住户调查数据，利用动态伪面板数据模型的实证分析为理论结果提供了经验证据。另外，实证研究发现，（1）对于户主出生于1965年前的家庭，他们依然延续了传统的消费习惯，完善社会保障机制、转变他们的消费观念是拉动内需的必由之路；（2）跨期替代弹性接近于零（0.008），即城镇居民更倾向于即期消费；（3）期望通过货币政策的利率工具刺激城镇居民消费的作用很有限。     

Factor Multivariate Stochastic Volatility via Wishart Processes

This paper proposes a high dimensional factor multivariate stochastic volatility (MSV) model in which factor covariance matrices are driven by Wishart random processes. The framework allows for unrestricted specification of intertemporal sensitivities, which can capture the persistence in volatilities, kurtosis in returns, and correlation breakdowns and contagion effects in volatilities. The factor structure allows addressing high dimensional setups used in portfolio analysis and risk management, as well as modeling conditional means and conditional variances within the model framework. Owing to the complexity of the model, we perform inference using Markov chain Monte Carlo simulation from the posterior distribution. A simulation study is carried out to demonstrate the efficiency of the estimation algorithm. We illustrate our model on a data set that includes 88 individual equity returns and the two Fama–French size and value factors. With this application, we demonstrate the ability of the model to address high dimensional applications suitable for asset allocation, risk management, and asset pricing.     

基于OR分析框架的人民币汇率评估

本文在Obstfeld和Rogoff (1995) （OR）标准模型的分析框架下,构建出了基于分部门的、微观的、动态的、居民跨期消费效应最大化的均衡汇率决定模型。根据该理论模型的非线性和动态特点,设计了一个向量自回归（VAR）模型,实证分析了历年来人民币对美元的名义汇率是否合理。     

Factor Multivariate Stochastic Volatility via Wishart Processes

This paper proposes a high dimensional factor multivariate stochastic volatility (MSV) model in which factor covariance matrices are driven by Wishart random processes. The framework allows for unrestricted specification of intertemporal sensitivities, which can capture the persistence in volatilities, kurtosis in returns, and correlation breakdowns and contagion effects in volatilities. The factor structure allows addressing high dimensional setups used in portfolio analysis and risk management, as well as modeling conditional means and conditional variances within the model framework. Owing to the complexity of the model, we perform inference using Markov chain Monte Carlo simulation from the posterior distribution. A simulation study is carried out to demonstrate the efficiency of the estimation algorithm. We illustrate our model on a data set that includes 88 individual equity returns and the two Fama-French size and value factors. With this application, we demonstrate the ability of the model to address high dimensional applications suitable for asset allocation, risk management, and asset pricing.     

我国农村贫困的动态转化、持续时间与状态依赖研究——基于收入贫困与多维贫困的双重视角

本文使用中国健康与营养调查2000—2015年跟踪数据,比较分析了农村家庭收入贫困与多维贫困的长期变动情况。在此基础上,使用Cox比例风险与动态Probit模型实证研究了跨期贫困的动态转化概率、状态依赖及其影响因素等问题。研究发现,农村多维贫困发生率下降幅度比收入贫困发生率下降幅度高出近20个百分点,但未脱贫的多维贫困家庭比收入贫困家庭具有更明显的贫困适应性。随着贫困持续时间的增加,无论是收入贫困还是多维贫困,中断当前贫困状态的可能性都下降了。进一步分析发现,子代职业地位、子代教育、城镇化水平和交通便捷度等因素显著降低了贫困家庭的贫困适应性与状态依赖,而贫困补贴对部分贫困家庭产生了补贴依赖效应,从而一定程度上促进了其贫困适应性。本研究在理论上丰富了有关贫困动态性的探讨,为有效破解低收入群体的贫困状态依赖提供了经验证据。     

DGM（1，1）模型的改进与高校毕业生的供求预测

一、序言高等教育人才总需求是指各部门、单位和厂商等对高等学校应届毕业生的总体需求。近年来我国大学毕业生就业问题凸现,引起了社会各方面的广泛关注,2005年大学毕业生的就业问题更为突出。事实上,社会对大学毕业生的需求所反映出的主要问题是高等教育办学规模和专业结构的     

万能寿险保单盈利能力分析

与传统寿险相比,万能寿险保单具有保障和投资功能、提供最低收益保证、保险利益直接与投资收益相连、保单变更灵活和产品透明等特点,进而万能保单的盈利模式也与传统寿险不同。本文对万能寿险保单的个人账户投资资产构建对数正态分布模型,计算账户价值,利用现金流法计算万能寿险保单公司账户责任准备金,进而计算公司利润水平指标,然后通过随机模拟对影响万能寿险保单盈利能力的个人账户收益率、留存收益率、公司账户投资收益率、贴现利率、生存和死亡概率等因素进行了分析。     

社会保障支出与拉动内需——对农村养老保障问题的深入探讨

本文通过实证分析,探讨了农村养老保障问题与拉动内需之间的关系。结果认为农村居民消费水平与抚恤和社会福利救济费、养老保险、行政事业单位离退休经费呈显著正相关,并且社会保障支出项目对农村居民消费的作用存在地区差异,农村居民养老保险对消费的促进作用存在区域差异。由此提出建立健全农村养老保险制度,可以作为我国拉动内需、促进经济增长的突破口。     

Private Insurance,Selection, and Health Care Use

Observed differences in medical utilization between the privately insured and uninsured reflect the combined effects of self-selection and insurance incentives (moral hazard). This article provides a Bayesian framework for decomposing the disparity into incentive and selection components. The effect of self-selection in private insurance on the number of doctor visits is estimated using a multiyear sample of the U.S. adult non-Medicare population obtained from the Medical Expenditure Panel Survey. We use a flexible econometric framework based on the “Roy model” and develop a Markov chain Monte Carlo algorithm. We estimate the distribution of treatment effects and find strong evidence indicating selection, which accounts, on average, for 50% or more of the observed disparity in doctor visits.     

A Comparison of Alternative Models for the Demand for Medical Care

We have tested alternative models of the demand for medical care using experimental data. The estimated response of demand to insurance plan is sensitive to the model used. We therefore use a split-sample analysis and find that a model that more closely approximates distributional assumptions and uses a nonparametric retransformation factor performs better in terms of mean squared forecast error. Simpler models are inferior either because they are not robust to outliers (e.g., ANOVA, ANOCOVA), or because they are inconsistent when strong distributional assumptions are violated (e.g., a two-parameter Box-Cox transformation).     

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.     

A copula regression model for estimating firm efficiency in the insurance industry

This article considers the estimation of insurers’ cost-efficiency in a longitudinal context. The current practice ignores the tails of the cost distribution, where the most and least efficient insurers belong to. To address this issue, we propose a copula regression model to estimate insurers’ cost frontier. Both time-invariant and time-varying efficiency are adapted to this framework and various temporal patterns are considered. In our method, flexible distributions are allowed for the marginals, and the subject heterogeneity is accommodated through an association matrix. Specifically, when fitting to the insurance data, we perform a GB2 regression on insurers total cost and employ a t-copula to capture their intertemporal dependencies. In doing so, we provide a nonlinear formulation of the stochastic panel frontier and the parameters are easily estimated by likelihood-based method. Based on a translog cost function, the X-efficiency is estimated for US property-casualty insurers. An economic analysis provides evidences of economies of scale and the consistency between the cost-efficiency and other performance measures.     

Nonparametric kernel estimation of the impact of tax policy on the demand for private health insurance in Australia

This paper is motivated by our attempt to answer a policy question: how is private health insurance take‐up in Australia affected by the income threshold at which the Medicare Levy Surcharge (MLS) kicks in? We propose a new difference deconvolution kernel estimator for the location and size of regression discontinuities. We also propose a bootstrapping procedure for estimating the confidence interval for the estimated discontinuity. Performance of the estimator is evaluated by Monte Carlo simulations before it is applied to estimating the effect of the income threshold of MLS on the take‐up of private health insurance in Australia, using contaminated data.     

中国经济增长路径中稳定状态推移的政策模拟 ——基于拉姆齐模型的实证研究

 本文基于拉姆齐模型的动态分析框架，借助于对其中若干重要参数的分析，对中国经济增长中的稳定状态及其推移问题进行了实证研究；并利用研究结论对中国经济增长的最优路径进行了模拟。初步结论为：①中国经济增长路径中存在稳定状态且随其参变量的变化而移动；②此稳定状态可以通过政策优化参数而向后推移；③可调控参数分别为消费跨期替代弹性、人均消费增长率、资本份额、技术进步速率、社会平均折旧率、人口自然增长率。     

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.     

中国农村民间借贷市场融资约束环境下利率定价模型分析——以广东农村实地调查数据为例

通过对广东农户民间借贷行为实地调查的问卷进行数据分析,了解农村民间借贷中的资金供求关系,发现存在的融资约束问题,进而对融资约束环境下民间借贷资金利率定价过程进行实证分析;着重考察农村民间借贷利率受公共信息和私人信息影响的程度,从借款人和贷款人的角度分别建立定价模型进行经验分析。结果显示,定价模型在F检验1%水平上显著,其他模型具有R2的统计显著性;反映借款用途的变量在10%水平上显著,其他变量均在5%水平上显著。这说明该市场利率能够反映公共信息的影响,借款人和贷款人的利率定价也反映了各自私人信息中相关风险和财务能力因素的影响,得到的经验结论主要是:第一,农村民间借贷市场是自主交易的金融市场;第二,其利率定价过程基本市场化。     

DYNAMIC FACTOR MODELS

This paper introduces nonlinear dynamic factor models for various applications related to risk analysis. Traditional factor models represent the dynamics of processes driven by movements of latent variables, called the factors. Our approach extends this setup by introducing factors defined as random dynamic parameters and stochastic autocorrelated simulators. This class of factor models can represent processes with time varying conditional mean, variance, skewness and excess kurtosis. Applications discussed in the paper include dynamic risk analysis, such as risk in price variations (models with stochastic mean and volatility), extreme risks (models with stochastic tails), risk on asset liquidity (stochastic volatility duration models), and moral hazard in insurance analysis.

We propose estimation procedures for models with the marginal density of the series and factor dynamics parameterized by distinct subsets of parameters. Such a partitioning of the parameter vector found in many applications allows to simplify considerably statistical inference. We develop a two- stage Maximum Likelihood method, called the Finite Memory Maximum Likelihood, which is easy to implement in the presence of multiple factors. We also discuss simulation based estimation, testing, prediction and filtering.     

Rank Tests at Jump Events

We develop a dynamic discrete-choice model of teen sex and pregnancy that incorporates habit persistence. Habit persistence has two sources here. The first is a “fixed cost” of having sex, which relates to a moral or psychological barrier that has been crossed the first time one has sex. The second is a “transition cost,” whereby once a particular relationship has progressed to sex, it is difficult to move back. We estimate significant habit persistence in teen sex, implying that the long-run effects of contraception policy may be different from their short-run counterparts, especially if the failure rate of contraception is sufficiently large. Programs that increase access to contraception are found to decrease teen pregnancies in the short run but increase them in the long run.