20kV及以下配电网工程造价的确定与有效控制方法分析

随着我国电网逐渐向智能电网迈进,信息技术在电能传输、转换、分配、调度等方面的应用,使电力企业可以进行结构调整,提高电力系统管理水平。据统计,2011年,我国电力信息化投资达220亿元,2012-2015年,电力工程建设稳步推进。为了促进电力企业全面开展项目成本核算和有效控制,提高电力工程项目的效益,确定了典型方案设计模块,通过定额规则库与典型方案设计相匹配的方法,解决了安装过程中定额第一版遗留的一些问题,并通过设计选型等措施加强了成本控制。     

关于企业成本管理的探讨

成本管理是预算管理和绩效管理的前提,企业需要正确地将成本进行分类、计量和归集。恰当的成本管理制度可以帮助企业提升运营效率和业务绩效,同时企业的流程改善、突破和优化与成本管理密不可分。另外,管理者需要令客户对产品和服务满意,并且有效控制各项成本。企业成本管理不是单纯地降低成本,而是通过利用成本分析工具,有效地管理和规划资源,进而提高总体运营效率,保证企业总体绩效的持续改善。论文通过成本计算制度的制定方法和业务流程改善分析技术两方面对成本管控进行探讨。     

Large scale infrastructure investment and economic performance – a case study of Oresund

We analyse the effect of a large scale infrastructure investment, namely the construction of the Oresund bridge, on the local and supra-regional economy. We employ the synthetic control method to construct counterfactual regions that mimic the trajectory of Malmo and Southern Sweden without treatment. Our results point to a positive effect. However, placebo tests in space and time only reveal statistical significance at a larger regional level. The results suggest that spillover effects are eminent.     

Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?

This paper investigates not only the question of whether there is exchange rate pass‐through (ERPT) but also the extent to which the pass‐through is asymmetric or state‐dependent in the BRICS countries. Using monthly data from 1999:M1 to 2019:M12 and non‐linear smooth transition vector autoregressive (STVAR) model, our results provide evidence of period‐specific ERPT between the upper and lower regime periods, governed by the selected transition variables. The results further suggest that the pass‐through of exchange rate is higher when the economy is experiencing large appreciations and expansions as well as large depreciations and recessions. Theimplication for these findings is that ERPT is strongly affected by the state of the economy.     

A Statistical Model to Investigate the Reproducibility Rate Based on Replication Experiments

The reproducibility crisis, that is, the fact that many scientific results are difficult to replicate, pointing to their unreliability or falsehood, is a hot topic in the recent scientific literature, and statistical methodologies, testing procedures and p‐values, in particular, are at the centre of the debate. Assessment of the extent of the problem–the reproducibility rate or the false discovery rate–and the role of contributing factors are still an open problem. Replication experiments, that is, systematic replications of existing results, may offer relevant information on these issues. We propose a statistical model to deal with such information, in particular to estimate the reproducibility rate and the effect of some study characteristics on its reliability. We analyse data from a recent replication experiment in psychology finding a reproducibility rate broadly coherent with other assessments from the same experiment. Our results also confirm the expected role of some contributing factor (unexpectedness of the result and room for bias) while they suggest that the similarity between original study and the replica is not so relevant, thus mitigating some criticism directed to replication experiments.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Health screening strategies for international air travelers during an epidemic or pandemic

Air travelers can carry an infectious disease's pathogenic microorganism in their bodies and spread the disease from one country to another in a few days. To delay the spread, health screening stations may be set up at airport terminals to screen travelers. This research tested three different health screening strategies, each with a different combination of screening stations at trip origins, destinations and connecting airports. Discrete event simulations were performed, based on the 2014 to 2016 Ebola virus epidemic, with special focus on travelers from the West African countries traveling to the United States, including travelers who transferred flights at airports in European Union member states. The effectiveness of the screening strategies was analyzed in terms of correct detection, missed detection and false alarm rate. The results showed that exit screening at trip origins brought big improvements in the performance measurements compared to no screening. However, additional screening at the destinations and connecting airports contributed marginal benefits.     

Sources of Productivity Growth Dynamics: Is Japan Suffering From Baumol's Growth Disease?

This study examines the sources of labor productivity growth dynamics in Japan (1970–2010) and investigates the extent to which Japanese economic performance has been affected by Baumol's growth disease (BGD). We find that BGD silently undermines Japanese economic growth. However, the magnitude is miniscule, and consequently the aggregate labor productivity growth rate has not been decreasing monotonically. We also explore how BGD is arising and why it is small in the Japanese economy. BGD is weak because (1) the positive Baumol growth effect is also working in certain services sectors and (2) BGD is not a durable phenomenon: even if a sector begins to suffer from BGD, it is likely to recover quickly.     

Optimal investment with vintage capital: Equilibrium distributions

The paper concerns the study of equilibrium points, or steady states, of economic systems arising in modeling optimal investment with vintage capital, namely, systems where all key variables (capitals, investments, prices) are indexed not only by time but also by age. Capital accumulation is hence described as a partial differential equation (briefly, PDE), and equilibrium points are in fact equilibrium distributions in the variable of ages. A general method is developed to compute and study equilibrium points of a wide range of infinite dimensional, infinite horizon, optimal control problems. We apply the method to optimal investment with vintage capital, for a variety of data, deriving existence and uniqueness of equilibrium distribution, as well as analytic formulas for optimal controls and trajectories in the long run. The examples suggest that the same method can be applied to other economic problems displaying heterogeneity. This shows how effective the theoretical machinery of optimal control in infinite dimension is in computing explicitly equilibrium distributions. To this extent, the results of this work constitute a first crucial step towards a thorough understanding of the behavior of optimal paths in the long run.     

Periodic strategies in optimal execution with multiplicative price impact

We study the optimal execution problem with multiplicative price impact in algorithmic trading, when an agent holds an initial position of shares of a financial asset. The interselling decision times are modeled by the arrival times of a Poisson process. The criterion to be optimized consists in maximizing the expected net present value of the gains of the agent, and it is proved that an optimal strategy has a barrier form, depending only on the number of shares left and the level of the asset price.