On the real-time predictive content of financial condition indices for growth

We provide evidence on the real-time predictive content of the National Financial Conditions Index (NFCI), for conditional quantiles of U.S. real GDP growth. Our work is distinct from the literature in two specific ways. First, we construct (unofficial) real-time vintages of the NFCI. This allows us to conduct out-of-sample analysis without introducing the kind of look-ahead biases that are naturally introduced when using a single current vintage. We then develop methods for conducting asymptotic inference on tests of equal tick loss between nested quantile regression models when the data are subject to revision. We conclude by evaluating the real-time predictive content of NFCI vintages for quantiles of real GDP growth. While our results largely reinforce the literature, we find gains to using real-time vintages leading up to recessions—precisely when policymakers need such a monitoring device.     

基于碳排放量的机型排班优化

绿色低碳是当今的发展要求。航空公司可以从优化机型排班工作作为突破口，实现减少碳排放量的目的。为计算多条航班计划碳排放量，采用国际民用航空组织（ICAO）碳排放量计算公式，针对某航A320和B737两种机型，以碳排放量最小为约束条件，使用CPLEX软件求出某个航段上机型的最优解，最终实现整个航段的碳排放量最小。结果显示，在航段上使用两种混合机型比使用单一机型可节约更多的碳排放量，碳排放的减少区间为0.6%~2.9%，证明从碳排放量优化航空公司机型具备一定的合理性。     

区域经济发展与吸引外资能力耦合互动关系——基于耦合协调度与PVAR模型的实证分析

利用2006—2019年中国 30 个省区市的相关数据对区域经济发展水平系统和吸引外资能力系统进行综合评价，通过耦合协调度和 PVAR模型实证分析两系统间的耦合与互动发展特征。研究发现：2006—2019年经济发展水平和吸引外资能力均有明显改善，各省区市的系统耦合协调度为 0.11—0.61，呈平稳上升的态势；在空间上，耦合协调度的局部莫兰散点主要分布在一、三象限，说明大部分地区呈现“高?高”或“低?低”聚集的空间特征；在互动关系上，吸引外资能力受到区域经济发展水平的影响程度较大，而区域经济发展水平受到吸引外资能力的影响程度则相对较小。     

Real-time macroeconomic projection using narrative central bank communication

Unlike the central banks of most developed economies, the People's Bank of China (PBC) does not release its macroeconomic forecasts to the public but instead carries out narrative communication. We apply a hurdle distributed multinomial regression to PBC communication texts in real time, addressing the ultrahigh dimensionality, sparsity, and look-ahead biases. In addition, we embed text-based indices into mixed-data sampling (MIDAS)-type models and conduct forecast combinations for prediction. Our results argue that the predictive information from communication texts improves the real-time out-of-sample prediction performance. We connect textual analysis and real-time macroeconomic projection, providing new insights into the value of central bank communication.     

考虑公平性的客舱乘务员排班研究

针对由于排班不公平导致客舱乘务员流失的情况，为降低排班问题复杂度，首先生成符合航班运行基本规则的任务环，在此基础上同时考虑飞行小时、过早过晚航班、客舱乘务员人数三种因素，建立公平性排班数学模型，采用遗传算法求解。对比客舱乘务员随机排班和公平性模型排班两种方案下的结果。实验结果表明，运用优化后的乘务员公平性排班模型的方差更小，此模型对于客舱乘务员排班提供更公平的方案，具有一定的有效性。     

Home care routing and scheduling problem with teams’ synchronization

The demand for home care (HC) services has steadily been growing for two main types of services: healthcare and social care. If, for the former, caregivers' skills are of utter importance, in the latter caregivers are not distinguishable in terms of skills. This work focuses social care and models caregivers' synchronization as a means of improving human resources management. Moreover, in social care services, several visits need to be performed in the same day since patients are frequently alone and need assistance throughout the day. Depending on the patient's autonomy, some tasks have to be performed by two caregivers (e.g. assist bedridden patients). Therefore, adequate decision support tools are crucial for assisting managers (often social workers) when designing operational plans and to efficiently assign caregivers to tasks. This paper advances the literature by 1) considering teams of one caregiver that can synchronize to perform tasks requiring two caregivers (instead of having teams of two caregivers), 2) simultaneously modelling daily continuity of care and teams' synchronization, and 3) associating dynamic time windows to teams' synchronizations introducing scheduling flexibility while minimize service and travel times. These concepts are embedded into a daily routing and scheduling MIP model, deciding on the number of caregivers and on the number and type of teams to serve all patient tasks. The main HC features of the problem, synchronization and continuity of care, are evaluated by comparing the proposed planning with the current situation of a home social care service provider in Portugal. The results show that synchronization is the feature that most increases efficiency with respect to the current situation. It evidences a surplus in working time capacity by proposing plans where all requests can be served with a smaller number of caregivers. Consequently, new patients from long waiting lists can now be served by the “available” caregivers.     

基于LSM-GM预测的高速公路工程施工进度动态控制

高速公路在促进区域经济发展中发挥着重要的作用。传统的施工进度管理方法不能满足高速公路等线性工程施工建设工期管理的需要，常常导致施工进度管理失控。研究发现，线性计划法有利于提高线状工程施工进度计划和控制的科学性和有效性。通过将GM预测模型与线性计划法优势互补，联合使用，以达到施工进度动态控制的目标，确保施工工期内顺利完成施工任务，从而提高施工单位的市场竞争力。     

Density forecasting with Bayesian Vector Autoregressive models under macroeconomic data uncertainty

Macroeconomic data are subject to data revisions. Yet, the usual way of generating real-time density forecasts from Bayesian Vector Autoregressive (BVAR) models makes no allowance for data uncertainty from future data revisions. We develop methods of allowing for data uncertainty when forecasting with BVAR models with stochastic volatility. First, the BVAR forecasting model is estimated on real-time vintages. Second, the BVAR model is jointly estimated with a model of data revisions such that forecasts are conditioned on estimates of the ‘true’ values. We find that this second method generally improves upon conventional practice for density forecasting, especially for the United States.     

Does Real-Time Macroeconomic Information Help to Predict Interest Rates?

We analyze the predictive ability of real-time macroeconomic information for the yield curve of interest rates. We specify a mixed-frequency macro-yields model in real time that incorporates interest rate surveys and treats macroeconomic factors as unobservable components. Results indicate that real-time macroeconomic information is helpful to predict interest rates, and that data revisions drive a superior predictive ability of revised macro data over real-time macro data. We also find that interest rate surveys can have significant predictive power over and above real-time macroeconomic variables.