战略与复杂双重维度下商业生态系统形成机理研究

基于战略和复杂双重维度，剖析阿里巴巴商业生态系统形成逻辑。结果发现：较强的战略控制力有利于强化平台商业模式，催生跨行业多样化平台，继而推进生态内信息化不断深入发展；随后，商业生态系统积蓄丰富的共享数据资源，打开资源交易和创造边界，提升生态主体能力的同时重塑生态系统属性；有着更强复杂应配力的生态主体不断探索商业模式创新，生态内外的创新扩散催化商业生态系统竞争，进一步强化复杂应配力。在核心企业战略控制力和生态主体复杂应配力的双重作用下，商业生态系统呈现前生态状态、生态内卷、生态扩散和生态共生4种不同状态。     

农民工教育与职业的匹配及其工资效应——基于城市规模视角

农民工教育与职业的匹配状况对提高劳动力资源利用、增加劳动供给质量具有重要意义。本文使用中国流动人口动态监测调查2011~2016年微观数据,基于城市规模视角分析了农民工教育与职业的匹配状况对工资效应的差别。研究发现:人口规模越大的城市,农民工教育与职业的错配比例越高;中小城市农民工教育过度对工资的影响呈现工资嘉赏效应,大城市农民工教育过度对工资的影响以工资惩罚为主;而教育不足对农民工工资则普遍存在负向影响。农民工教育与职业不匹配对工资影响的理论机制表明,中小城市支持人力资本理论模型,而大城市和特大城市则支持分配理论模型。这意味着,农民工在中小城市表现出学历越高人力资本回报越高的特点;而在大城市,教育与职业适配则更为重要。因此,改善城市层面的教育-职业的适配性,让农民工在城市劳动力市场上自由流动和工作转换,进一步增强城市间劳动力资源的流动是相关政策调节的重点。     

Antecedents of the propensity to learn management practices and their impacts on firm outcomes in emerging markets: A Bayesian Model Averaging approach

This article explores the factors that motivate firms to learn new management practices. The hypotheses are empirically tested using a representative sample of 3676 small, medium and large firms from four South Asian countries and across all main sectors of economic activity. Given that we know little about the antecedents of the propensity to learn management practices in emerging markets, the study employs Bayesian Model Averaging approach to overcome the potential issue of model uncertainty. The results reveal that market competition, resource allocation towards internal and external R&D, good quality mobile network coverage and the use of external certified financial auditors have all positive and significant effects on the propensity to learn management practices. The results also suggest that private intellectual property rights protection in the context of inefficient legal systems can deter firms from learning, perhaps in fear of legal ramifications. Finally, the study shows that firms with a higher propensity of learning management practices are more likely to become profitable while exhibiting higher levels of both potential and actual innovation.     

Paired comparison models with age effects modeled as piecewise quadratic splines

We propose new models for analyzing pairwise comparison data, such as that relating to sports. We focus on changes in players’ strengths and the prediction of future results. Our models are based on the Thurstone-Mosteller and Bradley–Terry models, and make use of the time variation in the parameters. Furthermore, we apply our models to data from the Japanese traditional sport sumo, and analyze this data. The proposed models perform better than the standard Thurstone-Mosteller and Bradley–Terry models according to both the Akaike information criterion and the Brier score. We compare the proposed models in detail by focusing on individual sumo wrestlers.     

预期寿命、生育率变动与基本养老保险统筹账户调整

在构建三期世代交叠模型的基础上，通过选取相关制度指标来模拟分析在未来预期寿命和生育率变动下，基本养老保险统筹账户如何基于参数调整来维持收支平衡。研究结果表明：（1）我国居民预期寿命增长过快，统筹账户收支平衡受预期寿命变化影响较大；（2）在现阶段的预期寿命和生育率条件下，统筹账户能实现自身收支平衡，而且可在短期内通过阶段性降低缴费率来促进制度长远发展；（3）在长期内需通过提高缴费率或降低养老金替代率来保证统筹账户收支平衡，预期寿命为87.828岁且总和生育率为1.79作为参数调整临界点；（4）以现有制度设计为基准，参数调整临界点之前保证35%的基础养老金平均替代率不降，临界点之后保证20%的缴费率不升可以最大程度促进经济和社会发展。     

Objective methods for graphical structural learning

Graphical models are used for expressing conditional independence relationships among variables by the means of graphs, whose structure is typically unknown and must be inferred by the data at hand. We propose a theoretically sound Objective Bayes procedure for graphical model selection. Our method is based on the Expected-Posterior Prior and on the Power-Expected-Posterior Prior. We use as input of the proposed methodology a default improper prior and suggest computationally efficient approximations of Bayes factors and posterior odds. In a variety of simulated scenarios with varying number of nodes and sample sizes, we show that our method is highly competitive with, or better than, current benchmarks. We also discuss an application to protein-signaling data, which wieldy confirms existing results in the scientific literature.     

FX Intervention in the New Keynesian Model

We develop an open-economy New Keynesian Model with foreign exchange (FX) intervention in the presence of a financial accelerator and shocks to risk appetite in international capital markets. We obtain closed-form solutions for optimal monetary and FX intervention policies assuming the central bank cannot commit to future policies, and we compare the solution to that under policy commitment. We show how FX intervention can help reduce the volatility of the exchange rate, of inflation, and of the output gap, thus mitigating welfare losses associated with shocks in the international capital markets. We also show that, when the financial accelerator is strong, there is a risk of indeterminacy (self-fulfilling currency and inflation movements) although FX intervention can reduce this risk and thus reinforce the credibility of the inflation targeting regime. Model simulations match well the impact of a VIX shock obtained by local projections on a panel of inflation targeting emerging markets.     

Forecasting Foreign Exchange Markets Using Google Trends: Prediction Performance of Competing Models

Abstract

Foreign exchange markets affect a variety of humans and businesses worldwide and there is a wide array of literature aimed at providing more accurate forecasts of their movement. In an attempt to quantify human expectations, Google query search terms related to foreign exchange markets are used to help explain and predict foreign exchange rates between the United States’ dollar and ten other currencies during the time period of January 2004 and August 2018. We find evidence that, while Google Trends can be helpful in prediction, it is necessary to implement some sort of shrinkage or sparsity scheme on the coefficients.     

中国对虾出口贸易的影响因素及潜力分析——基于贸易引力模型

选取中国与主要对虾出口市场 2003-2017年的对虾贸易面板数据。运用引力模型对各影响因素进行回归分析。结果表明。出口市场的经济水平、中国的对虾产量以及 APEC成员对中国对虾的出口有着促进作用。中国与各出口市场的地理距离以及对虾疾病 EMS对对虾的出口有着较弱的阻碍作用。并根据引力模型测算了各出口市场的贸易潜力。其中美国等 12个国家和地区属于潜力再造型出口市场。加拿大属于潜力开拓型出口市场。日本、澳大利亚等15个国家和地区属于潜力巨大型出口市场。根据分析及测算结果分别从企业和政府的角度提出了促进对虾出口贸易发展的政策建议。     

城市轨道交通相邻多车站动态协同限流研究

为应对城市轨道交通车站高峰期客流压力,限流已经成为常态应对措施,而经常采用的限流策略大多针对单个车站,缺少对相邻多个车站的协同考虑。基于客流在车站间的传播效应,以乘客总延误时间最小为目标,以站台及列车能力为约束条件,构建城市轨道交通相邻多车站协同限流决策模型,同时为实现实时动态控制,引入滚动时域控制方法,优化多车站动态协同限流流程。以北京地铁8号线为例,经过相邻若干车站运营数据进行限流策略计算。结果表明,该模型限流可以在不造成车站服务人数损失的同时,将乘客总延误时间降低21%。