产业互联下基于双循环的供应链合作稳定性研究

以一条由制造商和零售商组成的二级供应链为研究对象,通过测算产业互联度与双循环程度,研究对供应链合作稳定性的影响.研究发现:在国内环境中,产业互联度与内循环程度呈正比关系,产业互联度越高,内循环程度越高;内循环度程度提高,内需扩大,供应链上的企业选择合作时的整体收益要大于不合作时的收益,因此达到供应链长期稳定合作.通过从国内角度寻找出的规律应用于国际供应链中,为企业参与全球经济提供启示.     

Unemployment and econometric learning

We apply well-known results of the econometric learning literature to the Mortensen and Pissarides real business cycle model. Agents can always learn the unique rational expectations equilibrium (REE), for all possible well-defined sets of parameter values, by using the minimum-state-variable solution to the model and decreasing gain learning. From this perspective the assumption of rational expectations in the model could be seen as reasonable. But using a parametrisation with UK data, simulations show that the speed of convergence to the REE is slow. This type of learning dampens the cyclical response of unemployment to small structural shocks.     

2种不同来源的黑牛肝菌SOD酶活稳定性研究

本研究分别对野生种PH-16与栽培种PH-20黑牛肝菌进行SOD酶活稳定性研究,通过SOD酶对H2O2及乙醇-氯仿的化学敏感性差异,确定SOD酶类型,以没食子酸自氧化法测定酶活,通过温度、pH以及4℃保藏时间梯度对其SOD酶稳定性进行了探究.结果表明,硫酸铵-丙酮复合沉降法,SOD酶活性最高,PH-20菌丝体蛋白含量是PH-16的1.32倍,而PH-16 SOD比活力最高可达PH-20的1.42倍.两种黑牛肝菌SOD酶活性均对H2O2浓度变化敏感,对乙醇-氯仿浓度变化保持活性稳定,确定SOD酶类型为Cu,Zn-SOD酶.PH-16 SOD酶最高酶活条件为pH=5.5,温度25℃,活性平均衰退速率16.2 U·mL-1·d-1.PH-20 SOD酶最高酶活条件为pH=6.5,温度30℃,活性平均衰退速率8.5 U·mL-1·d-1.     

基于空间视角下的高管团队稳定性与企业技术创新

基于企业技术创新存在空间效应,使用传统的多元线性回归模型进行实证研究可能会存在有偏估计,本文以我国2004-2016 年沪深两市A 股上市公司为研究样本,通过构建绝对地理距离和相对时间距离的空间权重矩阵,运用空间计量分析技术,实证考察了高管团队稳定性与空间关联对企业技术创新绩效的影响。研究发现,一方面,高管团队稳定性越强的企业在技术创新绩效方面越好。另一方面,高管团队稳定性与技术创新绩效存在区域内的空间溢出效应,同一地区的高管团队稳定性对本地区的技术创新绩效有显著的提升作用,本地区的高管团队稳定性受到相邻地区高管团队稳定性的影响,而高铁的开通使得该空间效应更为显著,即使绝对距离较远的地区也能对本地区高管团队稳定性产生空间作用。本文的研究结果对全面认识高管团队稳定性的重要性,促进地方企业技术创新具有重要的政策含义。     

New development: Evaluating state revenue portfolio stability—a case of commercial casino taxes

State governments in the USA are searching for new ways to diversify their tax structure’s stability without raising existing taxes. Taxing commercial casinos on non-American Indian reservations has received significant attention to increase state revenue capacities. This article explains the impact of commercial casino tax revenue on state revenue stability.     

Too big to fail: Measures,remedies, and consequences for efficiency and stability*

This paper evaluates whether reform efforts addressing “too big to fail” actually enhance the stability of the financial system, and whether trade‐offs exist between stability and efficiency. We also present and discuss various measures of bank size and complexity since such measures are essential for implementing appropriate corrective remedies. As we will show, there are no unambiguous measures of size or complexity that can fully capture a bank's contribution to systemic risk. Their effects on efficiency are also impossible to capture with certainty. While we recognize the need for additional research and empirical evidence, we do identify weaknesses and strengths of proposed and implemented reforms that could have consequences for bank stability and efficiency.     

Parameter risk in time-series mortality forecasts

The projection of mortality rates is an essential part of valuing liabilities in life insurance portfolios and pension schemes. An important tool for risk management and solvency purposes is a stochastic projection model. We show that ARIMA models can be better representations of mortality time-series than simple random-walk models. We also consider the issue of parameter risk in time-series models from the point of view of an insurer using them for regulatory risk reporting – formulae are given for decomposing overall risk into undiversifiable trend risk (parameter uncertainty) and diversifiable volatility. Particular attention is given to the contrasts in how academic researchers might view these models and how insurance regulators and practitioners in life offices might use them. Using a bootstrap method we find that, while certain kinds of parameter risk are negligible, others are too material to ignore. We also find that an objective model selection criterion, such as goodness of fit to past data, can result in the selection of a model with unstable parameter values. While this aspect of the model is superficially undesirable, it also leads to slightly higher capital requirements and thus makes the model of keen interest to regulators. Our conclusions have relevance to insurers using value-at-risk capital assessments in the European Union under Solvency II, but also territories using conditional tail expectations such as Australia, Canada and Switzerland.     

Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model

This paper uses a time-varying parameter-panel vector autoregressive (TVP-PVAR) model to analyze the role played by domestic and US news-based measures of uncertainty in forecasting the growth of industrial production of 12 Organisation for Economic Co-operation and Development (OECD) countries. Based on a monthly out-of-sample period of 2009:06 to 2017:05, given an in-sample of 2003:03 to 2009:05, there are only 46% of cases where domestic uncertainty can improve the forecast of output growth relative to a baseline monetary TVP-PVAR model, which includes inflation, interest rate and nominal exchange rate growth, besides output growth. Moreover, including US uncertainty does not necessarily improve the forecasting performance of output growth from the TVP-PVAR model which includes only the domestic uncertainty along with the baseline variables. So, in general, while uncertainty is important in predicting the future path of output growth in the 12 advanced economies considered, a forecaster can do better in majority of the instances by just considering the information from standard macroeconomic variables.     

Services inflation dynamics and persistence puzzle in Brazil: a time-varying parameter approach

This article analyses services inflation dynamics in Brazil, focusing on the Services Inflation Persistence Puzzle, for monthly data from January 2004 to February 2016. We apply a time-varying parameter (TVP) approach, via a Kalman filter, to estimate hybrid Phillips curves and compare inflation inertia for tradable goods and services inflation. Aggregate Brazilian Extended Consumer Price Index inflation serves as a benchmark. To justify the TVP analysis, parameter instability and structural change tests are implemented, based on OLS and Generalized Method of Moments (GMM) frameworks. The main results are as follows: (i) the TVP approach is relevant due to observed instability in some parameters estimated; (ii) inflation expectation coefficients are higher than lagged inflation in all calculations, but inflation inertia is not negligible at all; (iii) services inflation persistence ranges from 27 to 36%, whereas tradable goods inflation persistence ranges from 36 to 47%, providing evidence of the Services Inflation Persistence Puzzle in Brazil; (iv) from 2009 onwards an increase in one percentage point in real wages raises monthly services inflation rate by 0.02 to 0.03 percentage point; (v) there is evidence that cost-push pressures, due to wage increases in the service sector, are more important to explain services inflation than demand pressures from early 2009 to mid-2014.