碳中和目标导向的省域消费端碳排放减排模式研究——基于多区域投入产出模型

文章以多区域投入产出模型为基础,研究了中国省级和行业层面基于消费端的碳排放及碳转移,并解析了碳中和导向下的碳减排模式。结果表明:23个省份本地消费碳排放大于外地输入碳排放;资本形成是碳排放最大贡献者;能源生产和供应业以及非金属和金属业是碳转移的主要行业,能源生产和供应业输出碳排放量最大的内蒙古主要输出给北方地区,非金属和金属业输出碳排放量最大的河北主要输出给江苏等省份;中国30个省份可以根据消费端碳排放的来源特征和净碳转移方向分为四类。在碳中和目标导向下,本研究有助于倒逼各省份绿色发展和绿色低碳产品的输出,绿色低碳也将是未来贸易市场趋向。     

Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.     

Using artificial neural network and multivariate analysis techniques to evaluate road operating conditions

Regional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1).     

Equity market neutral hedge funds and the stock market: an application of score-driven copula models

In this article, we study the time-varying market neutrality of equity market neutral hedge funds. We use data from the Hedge Fund Research? Equity Market Neutral Index (HFRX EH), which represents the performance of a portfolio of individual equity market neutral hedge funds. For each day, we measure different levels of association of the Standard and Poor’s 500 (S&;P 500) index and the HFRX EH. We use non-linear dynamic conditional score models of location, scale and copula that, to the best of our knowledge, have not yet been applied in the body of literature on hedge funds. We study whether the neutrality of the HFRX EH that is evidenced in the body of literature for the period of April 1993–April 2003 also holds for the following decade, for the period of May 2003–December 2016. We estimate different average levels of association for the pre-, during- and post-periods of the US financial crisis of 2008. We find that the association of the S&;P 500 and the HFRX EH, on average, is significantly positive for the pre- and post-periods of the financial crisis, and it is significantly negative for the period during the financial crisis.     

What caused Japan’s Great Stagnation in the 1990s? Evidence from an estimated DSGE model

Despite the widespread belief that Japan’s “Great Stagnation” in the 1990s is due to the financial dysfunction after the collapse of asset price bubbles, Hayashi and Prescott (2002) argue that its main cause is a slowdown in total factor productivity growth, using a calibrated neoclassical growth model. The present paper aims to fill this gap by estimating a New Keynesian dynamic stochastic general equilibrium model augmented with a financial accelerator mechanism and associated financial shocks. Our estimation results show that even in the presence of the financial shocks an adverse neutral technology shock mainly induced the Great Stagnation and that the rate of neutral technological change is strongly correlated with all enterprises’ financial position in the Tankan. Based on these findings, the paper argues that the Great Stagnation was caused by an adverse neutral technology shock that is likely to represent a tightening of firms’ financing, which induced reduction of R&D investment and misallocation of resources as indicated in previous literature.     

Debt monetization,inflation, and the ‘neutral’ interest rate

The main purpose of this study is to explore the potential expansionary effect stemming from the monetization of debt. We develop a simple macroeconomic model with Keynesian features and four sectors: creditor and debtor households, businesses, and the public sector. We show that such expansionary effect stems mainly from the reduction in the financial cost to servicing the public debt. The efficacy of the channel that operates allegedly through the compression of the risk/term premium on securities is found to be ambiguous. Finally, we show that countries that issue their own currency can avert getting stuck in a structural ‘liquidity trap’ provided their central banks are willing to monetize the debt created by a strong enough fiscal expansion.     

Forward-neutral valuation relationships for options on zero coupon bonds

This paper extends the literature on Risk-Neutral Valuation Relationships (RNVRs) to derive valuation formulae for options on zero coupon bonds when interest rates are stochastic. We develop Forward-Neutral Valuation Relationships (FNVRs) for the transformed-bounded random walk class. Our transformed-bounded random walk family of forward bond price processes implies that (i) the prices of the zero coupon bonds are bounded below at zero and above at one, and (ii) negative continuously compounded interest rates are ruled out. FNVRs are frameworks for option pricing, where the forward prices of the options are martingales independent of the market prices of risk. We illustrate the generality and flexibility of our approach with models that yield several new closed-form solutions for call and put options on discount bonds.     

供应链中甄别契约设计与信息共享激励

针对供应链中上下游企业的委托-代理问题,委托人可以设计出某种甄别契约以区分不同类型的代理人在不同的市场需求状况下的努力程度。在完全信息的条件下,委托人采取固定佣金方案及承担全部风险为最优选择。在信息不完全的条件下,若代理人为风险规避者则委托人只承担部分销售风险但需付出额外的风险补偿成本,若代理人为风险中性者则委托人不需付出额外的风险补偿成本。     

保护接地与保护接零应用分析

保护接地与保护接零是预防电气设备产生漏电时造成外壳带电而发生危险所采取的有效措施。当前，不少人对保护接地和保护接零在实际使用时不加区分，因此普及保护接地和保护接零知识，以实现安全用电很有必要。     

房地产价格与通货膨胀预期

文章通过构建房地产均衡市场模型,在风险中性的假设前提下,利用无套利均衡定价原理,发展了从房地产价格波动中分离出市场通货膨胀预期的新方法.在此基础上,通过对中国房地产市场的实证研究发现,房地产预期收益率与通货膨胀预期之间确实存在稳定的函数关系.最后,文章提出将房地产价格纳入到居住类消费价格指数中去以减少货币政策认识时滞的政策建议.