Pooling data for the analysis of dynamic marketing systems

Vector autoregressive (VAR) models have become popular in marketing literature for analyzing the behavior of competitive marketing systems. One drawback of these models is that the number of parameters can become very large, potentially leading to estimation problems. Pooling data for multiple cross-sectional units (stores) can partly alleviate these problems. An important issue in such models is how heterogeneity among cross-sectional units is accounted for. We investigate the performance of several pooling approaches that accommodate different levels of cross-sectional heterogeneity in a simulation study and in an empirical application. Our results show that the random coefficients modeling approach is an overall good choice when the estimated VAR model is used for out-of-sample forecasting only. When the estimated model is used to compute Impulse Response Functions, we conclude that one should select a modeling approach that matches the level of heterogeneity in the data.     

公司债定价：首中时模型的蒙特卡罗实现

论文借鉴信用风险度量的首中时结构模型,通过该模型的蒙特卡罗模拟对我国公司债进行定价,同时探讨了拟合公司债价值最佳的违约回复率设定和动态波动率的模型选择问题。研究表明首中时模型用于公司债定价是可行的,且不同的债券确实存在不同的回复率,并且对同一公司的不同债券使用同样的回复率也是不准确的,另外论文也进一步肯定了GARCH（1,1）模型在估计波动率方面的适用性。     

A macroeconomic model of direct investment in foreign affiliates of Japanese firms

This paper analyses the operations of the Japanese multinational corporations in the world economy by constructing and estimating a Japanese foreign direct investment system. This system models the determinants of manufacturing foreign direct investment (FDI), the trade between Japan and her overseas affiliates as well as the sales of the manufacturing subsidiaries and those of the trading subsidiaries. The error-correction modelling techniques are adopted for estimation in order to capture both the short- and long-run adjustment processes. Finally, simulations are conducted on the model to analyse the effects of changes in the world economy.     

Spillovers in Exchange Rates and the Effects of Global Shocks on Emerging Market Currencies

This paper provides an investigation into the spillover effects of exchange rate returns and volatility for developed and emerging market currencies, using data from 1997 to 2011. The results suggest that spillovers in exchange rate returns have increased steadily over time, in moderate reaction to economic events. In contrast, spillovers in total observed volatility (measured by squared returns) react more strongly to economic events, and this transmission has remained at a relatively high level since the global financial crisis. Furthermore, over the course of time, global shocks would appear to account for a larger proportion of aggregate exchange rate volatility (and the relative importance of domestic shocks has declined). The paper also considers whether the increase in volatility spillover is due to sudden shocks, or whether it is due to changes in the stochastic trend of the underlying volatility process. The results suggests that in most cases, this increase is due to sudden shocks, however, in certain instances country‐specific events may perpetuate changes to the trend of the underlying volatility spillover.     

基于福州市降水量数据研究降水期权定价

为应对干旱、洪涝等降水事件给相关经济主体带来的风险,基于1953年1月至2016年12月福州市月均累积降水量数据,运用威尔克斯法对降水量进行建模,利用蒙特卡罗模法对降水期权进行定价从而得到降水期权价值,并提出发展我国降水期权的政策建议。     

Bayesian inference in cointegrated systems

In this paper I deal with Bayesian methods for conducting inference on important features of (potentially) cointegrated VAR models involving I(1) variables. Firstly, (informal) inference is made on the cointegrating rank of the system. Secondly, posterior analysis is used to verify the validity of over-identifying restrictions on the cointegration parameters. Thirdly, posterior distributions are obtained for impulse response functions and predictive densities at different horizons. The relevant posterior distributions are obtained by means of Monte Carlo integration. The analysis is based on the use of simple weakly informative priors. Two applications on simulated data and on the Danish money demand data are presented.     

引入土地流转因素的新型农村社会养老保险基金预测

本文以政策外部性关联与协同效应为切入点,通过陕西省西安市新农保试点区县农民问卷调查,对引入土地流转因素的新型农村社会养老保险基金预测进行精算建模和政策仿真研究。结果表明：土地流转因素对新农保参保率、缴费率具有显著影响,基金收支呈现由盈余转向缺口、并逐年扩大的趋势,基金、制度存在双重失衡风险。通过关键制度因素的单一、组合调整结果分析对比,提出促进土地流转与新农保制度良性融合与可持续发展的对策建议。     

基于多标度分形理论的金融资产收益非对称性测度方法研究

基于多标度分形理论,提出了一种新的更适用于实际金融资产收益数据的非对称性测度方法——两阶段非对称性检验法（Two-step asymmetry testing,TAT）,并运用Monte Carlo模拟考察了其与传统的偏度系数检验法的非对称性判定结论差异。实证结果表明：总体来讲,本文提出的两阶段非对称性检验法在常用检验水平下取得了较偏度系数法更为准确的金融资产收益非对称性判定结论,且两阶段非对称性检验法较偏度系数法更适用于具有非独立、非正态特性数据的非对称性检验。     

空间加权矩阵设置与空间面板参数估计效率

总结了常用的空间加权矩阵的一般构建方法和研究领域内新提出的空间加权矩阵的构建方法,从宏观与微观层面,量化分析了空间加权矩阵设置对于空间面板参数估计效率、空间效应识别的影响效应。结论表明：宏观数据层面,随着空间加权矩阵复杂程度的提高,无论是空间面板固定效应模型还是空间面板随机效应模型,参数估计的有效性与一致性都显著提高并且广义矩参数估计方法优于拟极大似然估计方法,复合的空间加权矩阵条件下,拉格朗日乘子检验方法的功效更高;微观数据层面,回归结果表明四种不同类型的空间加权矩阵的设置,对于聚集外部性引致的企业全要素生产率增长的空间边界的识别具有显著影响,复合的空间加权矩阵更有效。