梯形明渠正常水深和临界水深的迭代计算法

图解法和试算法是计算正常水深和临界水深通常采用的方法,但计算精度欠佳且计算步骤繁杂。文章提出了一个新的迭代方程用于上述2种水深的计算,并用代数方法严格地证明了该方程具有收敛性。     

企业需求、企业能力与企业社会责任的匹配探讨——一种新的企业履行社会责任的理论分析框架

本文首先研究了企业履行社会责任的模式并提出了企业社会责任的层次模型;其次,将企业需求与个人需求在企业生态学的范畴下进行了类比,提出了企业需求层次模型,并将企业需求归纳为企业履行社会责任的动力;再次,本文运用企业生命周期原理,将企业成长状况看作是衡量企业具有一定的履行社会责任能力的体现;最后,通过将企业需求、企业能力与企业社会责任进行匹配探讨,揭示了企业履行社会责任的动力和能力原理及其可能的行为,并得出了一些有意义的结论。     

Forecast quality improvement with Action Research: A success story at PharmaCo

There is a gap in the forecasting research surrounding the theory of integrating and improving forecasting in practice. The number of academically affiliated consultancies and knowledge transfer projects that there are around, due to a need for improvements in forecast quality, would suggest that many interventions and actions are taking place. However, the problems that surround practitioner understanding, learning and usage are rarely documented. This article takes the first step toward trying to rectify this situation by using the specific case study of a fully engaged company. A successful action research intervention in the Production Planning and Control work unit improved the use and understanding of the forecast function, contributing to substantial savings, enhanced communication and improved working practices.     

Forecasts in times of crises

Financial crises pose unique challenges for forecast accuracy. Using the IMF’s Monitoring of Fund Arrangements (MONA) database, we conduct the most comprehensive evaluation of IMF forecasts to date for countries in times of crises. We examine 29 macroeconomic variables in terms of bias, efficiency, and information content to find that IMF forecasts add substantial informational value, as they consistently outperform naive forecast approaches. However, we also document that there is room for improvement: two-thirds of the key macroeconomic variables that we examine are forecast inefficiently, and six variables (growth of nominal GDP, public investment, private investment, the current account, net transfers, and government expenditures) exhibit significant forecast biases. The forecasts for low-income countries are the main drivers of forecast biases and inefficiency, perhaps reflecting larger shocks and lower data quality. When we decompose the forecast errors into their sources, we find that forecast errors for private consumption growth are the key contributor to GDP growth forecast errors. Similarly, forecast errors for non-interest expenditure growth and tax revenue growth are crucial determinants of the forecast errors in the growth of fiscal budgets. Forecast errors for balance of payments growth are influenced significantly by forecast errors in goods import growth. The results highlight which macroeconomic aggregates require further attention in future forecast models for countries in crises.     

Forecasting GDP growth with NIPA aggregates: In search of core GDP

In addition to GDP, which is measured using expenditure data, the U.S. national income and product accounts (NIPAs) provide a variety of measures of economic activity, including gross domestic income and other aggregates that exclude one or more of the components that make up GDP. Similarly to the way in which economists have attempted to use core inflation—which excludes volatile energy and food prices—to predict headline inflation, the omission of GDP components may be useful in extracting a signal as to where GDP is going. We investigate the extent to which these NIPA aggregates constitute “core GDP.” In an out-of-sample forecasting exercise using a novel real-time dataset of NIPA aggregates, we find that consumption growth and the growth of GDP excluding inventories and trade have historically outperformed a canonical univariate benchmark for forecasting GDP growth, suggesting that these are promising measures of core GDP growth.     

关于增列审计学一级学科的设想

审计是党和国家、各类组织监督体系中的重要组成部分，是一种依法监督经济权力行使的制度安排，具有鲜明的法学学科属性。推进国家治理体系和治理能力现代化，迫切需要构建中国特色社会主义审计学科体系、学术体系和话语体系，构建现代审计人才培养体系。审计学具有确定的研究对象，形成了相对独立、自成体系的理论、知识基础和研究方法，已经具备设置为一级学科的条件，应该在法学学科门类下增列审计学一级学科。     

腐败与金融包容性国际经验研究

金融包容性是指提高低成本的金融服务的广泛可得性。金融服务普及的深度和广度对国民经济的发展起到了至关重要的作用。而腐败会影响金融包容性,将贫困弱势群体排除在外,客观上形成金融排斥,加重小微企业贷款难、贷款贵等问题,降低金融服务实体经济的能力和质量。本文选取1995—2016年170个国家和地区建立非平衡面板数据模型,经过实证研究发现：腐败会显著降低金融服务的包容性,但会提高金融服务的可得性。并且腐败会通过提高银行贷款利率,增加贷款规模以及提高企业融资难度传导到金融包容性。此外,本文还进行了内生性检验,并按时间、经济发展速度、人口规模和地区划分进行异质性分析。本研究填补了腐败对金融包容性影响机制研究的空白,从而丰富了腐败对金融市场影响的研究,也为普惠金融的发展提供了重要补充。     

Optimizing the credit term decisions in supply chain finance

We study a credit term determination problem in the context of a supplier-buyer supply chain. The supplier's credit term decision is simultaneously made with its production and inventory decisions, and most importantly, it is impacted by the buyer's order quantity. We present a new game-theoretic framework to model this problem, which captures the interaction between the supplier's credit term decision and the buyer's order decision in a multi-period setting. An exact method based on nonlinear programming is implemented to obtain the optimal solutions. We apply our methodologies on a real world case. The computational results show that our approach significantly outperforms the heuristics with fixed credit terms, and either a short or a long credit term can be sub-optimal for the supplier in profitability. Our work offers the first data-driven model and solution approach that assists purchasing and supply managers to make optimal dynamic credit term decision in conjunction with production, ordering and inventory decisions in a game-theoretic setting.     

Advancing environmental productivity: Organizational mindfulness and strategies

This study investigates the importance of mindfulness‐based organization systems and policies on the organization's continuous efforts to become a greener company. The study is devised as a pooled cross‐sectional time series analysis of productivity in energy consumption, water utilization, and waste generation and recycling of U.S. companies. The data set taken from U.S. Newsweek 500 recorded 600 companies dispersed into 63 industries during the period of 2012–2014 and provided 1,498 company–industry–year observations. The study found that systems and policies (e.g., deployment of third‐party auditors for its environmental metrics report; linkage of the remuneration of company's senior executive team with the achievement of environmental performance targets; and establishment of a committee at the Board of Directors' level whose mandate includes sustainability of the company in environment‐ and resource‐related matters) connect the company's mindfulness to its effort in improving the environmental quality through the company's productivity in energy consumption, water utilization, and waste generation and recycling. The relationships are positive and significant. Also, systems and policies serve as a motivator for the firm to continue to improve upon the current achievements. The study emphasizes the importance of translating organizational and individual mindfulness into organization policies and systems in order to motivate the organization to continuously improve its productivity in energy consumption, water utilization, and waste generation and recycling leading to improvements in environmental quality.     

Distribution of residual autocorrelations for multiplicative seasonal ARMA models with uncorrelated but nonindependent error terms

In this paper, we consider portmanteau tests for testing the adequacy of multiplicative seasonal autoregressive moving‐average models under the assumption that the errors are uncorrelated but not necessarily independent. We relax the standard independence assumption on the error terms in order to extend the range of applications of the seasonal autoregressive moving‐average models. We study the asymptotic distributions of residual and normalized residual empirical autocovariances and autocorrelations under weak assumptions on noise. We establish the asymptotic behavior of the proposed statistics. A set of Monte Carlo experiments and an application to monthly mean total sunspot number are presented.