The impact of the COVID-19 pandemic on business expectations

We document and evaluate how businesses are reacting to the COVID-19 crisis through August 2020. First, on net, firms see the shock (thus far) largely as a demand rather than supply shock. A greater share of firms report significant or severe disruptions to sales activity than to supply chains. We compare these measures of disruption to their expected changes in selling prices and find that, even for firms that report supply chain disruptions, they expect to lower near-term selling prices on average. We also show that firms are engaging in wage cuts and expect to trim wages further before the end of 2020. These cuts stem from firms that have been disproportionally negatively impacted by the pandemic. Second, firms (like professional forecasters) have responded to the COVID-19 pandemic by lowering their one-year-ahead inflation expectations. These responses stand in stark contrast to that of household inflation expectations (as measured by the University of Michigan or the New York Fed). Indeed, firms’ one-year-ahead inflation expectations fell precipitously (to a series low) following the onset of the pandemic, while household measures of inflation expectations jumped markedly. Third, despite the dramatic decline in firms’ near-term inflation expectations, their longer-run inflation expectations have remained relatively stable.     

Foreign investment regulation and firm productivity: Granular evidence from Indonesia

When regulating foreign direct investment (FDI), countries often face a trade-off between pursuing national policy interests and suffering efficiency losses due to FDI restrictions. We demonstrate the presence of this trade-off in the case of a protectionist FDI policy in Indonesia. Using a yearly census of Indonesian manufacturing firms from 2000 to 2015, we link product-level changes in binding FDI regulation due to major regulatory tightening to changes in firm-level productivity. Controlling for an extensive set of fixed effects as well as potential political economy drivers of regulation, we show that a tightening of the regulatory environment was successful in reducing foreign capital reliance among regulated firms, and led to increases in FDI among non-regulated firms producing the same product. Despite compensating increases in domestic capital, regulated firms experienced relative productivity losses. This points towards either a less efficient allocation of domestic capital or a general inferiority of domestic capital as compared to foreign investments.     

Drivers and barriers to cross-border e-commerce: Evidence from Spanish individual behavior

This paper explores the determinants of the individual's decision to perform cross-border e-commerce (CBeC). The European Union (EU) is especially interested in the promotion of CBeC because it is an important tool in its strategy to achieve the Digital Single Market in Europe. In this paper official data is used from a representative survey of 16,209 individuals on ICT usage by households and individuals that was carried out in Spain by the National Institute of Statistics (INE) for the year 2016. Using a standard neoclassical utility maximization framework, and logistic regression techniques, the results show that being a male is positively related to the probability of practicing CBeC. Education is positively and significantly related to the probability of being involved in CBeC with EU countries. Computer and Internet Skills are significant and positive factors in explaining CBeC (either with EU countries or with the rest of the world). The variable “how often the consumer sees other customer reviews before buying online”, has a positive effect. Foreign nationality also increases the likelihood of using CBeC. To promote CBeC in Spain measures towards developing digital skills, Internet trust and use of online information reviews of goods and services are discussed.     

Do capital flows drive credit growth and consumption in Central and Eastern Europe?

Domestic credit expansion in CEE economies, fuelled in part by foreign capital inflows, helped increase household welfare before the 2008 financial crisis caused a contraction across the region. How strong are the linkages between the current account, domestic credit and consumer spending? This study compiles a quarterly dataset of domestic credit as a share of GDP for 11 CEE European Union members and isolates structural breaks in the series’ growth rates that often align with the 2008 crisis. Vector autoregressive methods, particularly impulse response functions, show that increased current-account deficits lead to increased consumption in six of the 11 countries and increased credit growth in three, and that shocks to credit growth increase consumption in six countries. Capital inflows significantly increase consumption through domestic credit in Slovenia, while the Baltics show a large share of significant effects.     

Long-term forecasting of fuel demand at theater entry points

Managing the distribution of fuel in theater requires Army fuel planners to forecast demand at the strategic level to ensure that fuel will be in the right place, at the right time, and in the amounts needed. This work presents a simulation approach to forecasting that accounts for the structure of the supply chain network when aggregating the demand of war fighters across the theater over the forecasting horizon. The resulting empirical distribution of demand at the theater entry point enables planners to identify forecast characteristics that impact their planning process, including the amplitudes and temporal positions of peaks in demand, and the estimated lead time to the point of use. Experimentation indicates that the forecasts are sensitive to the pattern of war fighter demand, the precise structure of the in-theater supply chain network, and the constraints and uncertainty present in the network, all of which are critical planning considerations.     

我国出口汇率传递的非对称性:来自中日贸易的证据

文章扩展了Yang（2007）的厂商定价模型，对汇率传递非对称性、特点和成立条件进行理论分析，发现对称传递需要满足严格的条件，而现实中更常见的是非对称汇率传递。在一定条件下，商品需求弹性越大，越可能呈现出口国货币贬值传递率高而升值传递率低的特点。利用2000年1月至2011年12月我国出口日本的966种商品价格数据，发现汇率波动向价格传递具有非对称性：（1）人民币升值时，日元价格上涨较少；而贬值时，价格下降较多。我国出口商品的需求弹性较大，在日本市场上面对的是一个强竞争结构。（2）若月度升值超过一定幅度（测算约为2.43%），传递率又会有所上升，说明尽管日元价格易跌难涨，但在升值导致成本上涨较多、明显挤压利润时，厂商不得不适当提高日元售价。采用2000年至2018年9月日本从中国进口单位价值指数进行稳健性检验，得出类似结论。现阶段稳定的人民币名义汇率对我国出口企业是更为有利的。     

A hybrid machine learning model for forecasting a billing period’s peak electric load days

Many models have been studied for forecasting the peak electric load, but studies focusing on forecasting peak electric load days for a billing period are scarce. This focus is highly relevant to consumers, as their electricity costs are determined based not only on total consumption, but also on the peak load required during a period. Forecasting these peak days accurately allows demand response actions to be planned and executed efficiently in order to mitigate these peaks and their associated costs. We propose a hybrid model based on ARIMA, logistic regression and artificial neural networks models. This hybrid model evaluates the individual results of these statistical and machine learning models in order to forecast whether a given day will be a peak load day for the billing period. The proposed model predicted 70% (40/57) of actual peak load days accurately and revealed potential savings of approximately USD $80,000 for an American university during a one-year testing period.     

M5 competition uncertainty: Overdispersion,distributional forecasting,GAMLSS, and beyond

The M5 competition uncertainty track aims for probabilistic forecasting of sales of thousands of Walmart retail goods. We show that the M5 competition data face strong overdispersion and sporadic demand, especially zero demand. We discuss modeling issues concerning adequate probabilistic forecasting of such count data processes. Unfortunately, the majority of popular prediction methods used in the M5 competition (e.g. lightgbm and xgboost GBMs) fail to address the data characteristics, due to the considered objective functions. Distributional forecasting provides a suitable modeling approach to overcome those problems. The GAMLSS framework allows for flexible probabilistic forecasting using low-dimensional distributions. We illustrate how the GAMLSS approach can be applied to M5 competition data by modeling the location and scale parameters of various distributions, e.g. the negative binomial distribution. Finally, we discuss software packages for distributional modeling and their drawbacks, like the R package gamlss with its package extensions, and (deep) distributional forecasting libraries such as TensorFlow Probability.     

Forecasting upon a star: Forecasting or wishful thinking?

The purpose of this paper was to perform a detailed analysis of the challenges faced while developing and using econometric models to forecast future transportation demand. To this end, a comparative analysis of the state of practice and state of the art was undertaken on a concrete example – Viracopos Airport in Brazil. A review of relevant technical and scientific literature identified a number of approaches and each representative example was synthesized into a specification “template”. We then compared the performance of each “template” with the observed demand, through an intra-series forecast. A general finding was that econometric model specifications proved to be somewhat homogenous and simpler in nature, with results indicating a relatively small difference in fit and forecast capability across models. Even with the elimination of what is typically considered the main culprit for deviations – the forecast uncertainty of the explanatory (input) variables – the forecast is still subject to sizeable deviation. To address this issue, we proposed developing some sanity check indexes, particularly relevant for long-term forecasts. We conclude that the challenges faced at the Viracopos Airport Concession were far from econometric ones, that the success of the demand forecast and the concession itself required more than a well estimated econometric model. Finally, regarding investment obligations within the concession agreement, we strongly recommend making them conditional to meeting demand milestones, given the inherent unpredictability in forecasts.     

工业体系和民营企业兴起——基于252家中国最大民营制造业企业的经验研究

主流经济学家把改革开放后民营企业的大规模兴起，主要归因为市场经济条件下发挥企业家精神和遵循比较优势的必然结果。但是这无法解释为什么民营企业在兴起之初就广泛和快速地进入到各个工业，尤其是技术和资本密集型工业。基于中国工业史和252家中国最大民营制造业企业创业发展史的历史证据，文章找回"工业体系"这一被主流所忽略的重大历史现象和学术概念，从而首次提出一种理解中国民营企业发展独特性的结构性解释。文章发现：从计划经济时期继承而来的门类齐全和独立完整的工业体系，是解释民营企业创业和发展独特性的关键变量；已有的由国有企业和科研院所组成的工业体系，从市场机会、技术能力和组织资源等方面塑造了民营企业的创业选择和发展路径。所以，中国民营企业的快速发展不是仅凭自由市场就会自动出现的普遍现象，而是在市场条件下充分利用工业体系提供的技术和市场条件才得以出现的特殊现象。