An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.     

Forecasting value at risk and expected shortfall with mixed data sampling

I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence on short-horizon returns to directly forecast the tail dynamics of the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially in terms of multi-day forecast horizons. My analysis advocates models that feature asymmetric conditional quantiles and the use of the Asymmetric Laplace density to jointly estimate VaR and ES.     

Transitions between equilibria in bilingual games under logit choice

We study the effect of introducing a bilingual option on the long run equilibrium outcome in a class of two-strategy coordination games with distinct payoff and risk dominant equilibria under the logit choice rule. Existing results show that in the class of two-strategy games under consideration, the inefficient risk dominant equilibrium is selected in the long run under noisy best response models. We show that if the cost of the bilingual option is sufficiently low then the efficient payoff dominant equilibrium will be selected in the long run under the logit choice rule.     

外商直接投资、区域创新与城市化发展研究

基于2000—2017年省际面板数据,运用静态面板与门限面板模型,通过建立以政府干预、市场化进程为门限变量的回归模型,实证分析了外商直接投资与区域创新对我国城市化发展的影响。研究结果表明:外商直接投资、区域创新对城市化发展有积极的带动作用,同时,外商直接投资对区域创新的作用由替代效应向互补效应转变;政府干预对外商直接投资存在双重门限效应,对区域创新存在单一门限效应;市场化对外商直接投资存在单一门限效应,但对区域创新存在双重门限效应。基于以上结论,进一步提出促进城市化发展的建议。     

网络强度、组织冗余与创新模式——对200家样本企业问卷调研数据的实证检验

通过社会网络带来资源冗余进而对创新选择产生影响，这一机制已成为当今企业可持续发展的重要路径。运用200份企业样本调研数据，对网络强度、不同类型组织冗余及两种创新模式进行实证检验，结果发现，网络强度显著正向直接影响利用式创新和探索式创新;网络强度还通过正向影响未吸收冗余对两种创新产生正向间接影响作用;未吸收冗余与创新模式间具有显著正向影响关系,而吸收冗余在三者影响路径关系中检验结果不显著，可能是受企业自身因素或条件影响所致。最后，根据研究结论提出3点重要管理启示。     

产军协同、政府科技支持与技术创新效率研究

运用空间数据分析方法，检验产军协同、政府科技支持与技术创新效率在我国省域间的分布格局。研究表明，三者均存在显著的正向空间相关性，即正向空间溢出效应，并且在不同地区形成局部空间集聚，存在高低非均衡的“俱乐部”现象。基于空间误差模型和空间滞后模型，实证检验产军协同、政府科技支持对技术创新效率的影响。结果发现，从全国和分地区看，产军协同、政府科技支持均能够显著促进技术创新效率提升，并且二者存在显著的交互作用，能够发挥彼此间的互补效应，进一步促进技术创新效率提升；不同地区产军协同、政府科技支持对技术创新效率的影响程度存在较大差异，西部地区产军协同、政府科技支持对技术创新效率的促进作用比东部和中部地区显著。     

农民宅基地退出差异性受偿意愿及其影响因素分析

研究目的:宅基地退出工作能否顺利推进与退地补偿息息相关,研究宅基地退出中农民差异性受偿意愿及其影响因素,以服务决策。研究方法:基于重庆市890份农民实地调查数据,应用多元离散选择模型(Logit)进行定量研究。研究结果:(1)传统农区的农民更愿意选择货币补偿;城乡结合部(街道办)的农民更愿意选择安置补偿;农民修建补偿选择率总体偏低,区位差异并不明显;(2)农民货币受偿意愿影响因素主要包括受教育程度、家庭主要成员是否定居城镇、非农务工收入、新居住地适应性;(3)农民安置受偿意愿影响因素主要包括年龄、农房是否自住、退地补偿是否有截留、村基础设施状况;(4)农民修建受偿意愿影响因素主要包括农房造价、农房是否新建、退地补偿是否有截留;(5)影响农民受偿意愿的因素存在较大差异,同一因素可能对农民选择受偿意愿产生不同的影响,但没有一个自变量同时对三个因变量产生显著影响。研究结论:应针对农民受偿意愿差异及其影响因素,实行产异化的补偿措施,在经济发展相对滞后的传统地区,强化村落基础设施建设的同时,加大现金补偿力度。对于经济较为发达、区位条件较好的城乡结合部地区,应加大安置补偿力度,以保障退地农民的居住权。     

Population ageing and inflation with endogenous money creation

This paper models a mechanism through which population ageing may induce a deflationary process. We propose an overlapping-generations model (OLG) with money created by credits (inside money) and intergenerational trade. The model links demographic factors, such as fertility rates and longevity, to prices. We show that lower fertility rates lead to smaller demand for credit and lower money creation, which in turn cause a decline in prices. Changes in longevity affect prices through real savings and the capital market. Furthermore, a few links between interest rates and inflation are addressed; they arise in the general equilibrium and are not thoroughly discussed in literature. Long-run results are derived analytically; short-run dynamics are simulated numerically.     

创业企业何以提高创新绩效——基于创业学习与商业模式创新协同联动视角的QCA方法

以150个创业企业为样本，基于创业学习和商业模式创新理论，运用模糊集定性比较分析方法（fsQCA），探究经验学习、认知学习、新颖型商业模式创新和效率型商业模式创新对创新绩效的影响路径及机制。研究发现，存在新颖型商业模式创新等4条创新绩效产出关键路径；相较于效率型商业模式创新，新颖型商业模式创新在关键路径中更容易提高创新绩效；利用QCA方法证实了影响创业企业创新绩效的组态内部各要素之间的替代性。结论丰富了创新绩效产出内部机制，可为创业企业提高创新绩效提供指导和借鉴。     

基于CE模型的河南省耕地生态补偿额度研究

[目的]基于生态补偿利益主体的需求和支付意愿,充分考虑区域经济发展状态,测算具有弹性的生态补偿标准,确保生态补偿机制顺利运行。[方法]以河南省457份实地调查问卷为基础,采用选择实验法,建立由4个属性水平、7个选择集组成的生态价值属性集,测算受访对象生态补偿的支付意愿。[结果]城乡居民对于耕地资源景观与生态环境关注度最高,其次是耕地质量和耕地面积;农民和市民对于耕地生态价值属性满足的支付意愿存在显著差异性,农民支付意愿为2 060.55元/hm~2,市民支付意愿为3 396.15元/hm~2,两者相差近1 335.60元/hm~2,收入水平、环保意识是影响受访对象生态补偿支付意愿的最直接因素,但两者均认为耕地面积不变、耕地质量改善和耕地景观生态环境改善为最优选择。[结论]补偿额度应充分考虑相关利益主体的支付能力和意愿,将农民的支付意愿作为生态补偿下限,市民的支付意愿作为生态补偿上限,可建立具有一定弹性的生态补偿机制。