Initial coin offerings (ICOs) to finance new ventures

In an initial coin offering (ICO), new ventures raise capital by selling tokens to a crowd of investors. Often, this token is a cryptocurrency, a digital medium of value exchange based on the distributed ledger technology. Both the number of ICOs and the amount of capital raised have exploded since 2017. Despite attracting significant attention from ventures, investors, and policy makers, little is known about the dynamics of ICOs. This initial study therefore assesses the determinants of the amount raised in 423 ICOs. Drawing on signaling theory, the study explores the role of signaling ventures' technological capabilities in ICOs. The results show that technical white papers and high-quality source codes increase the amount raised, while patents are not associated with increased amounts of funding. Exploring further determinants of the amount raised, the results indicate that some of the underlying mechanisms in ICOs resemble those found in prior research into entrepreneurial finance, while others are unique to the ICO context. The study's implications are multifold and discussed in detail. Importantly, the results enable investors to more accurately understand crucial determinants of the amount raised (e.g., technical white papers, source code quality, token supply, Ethereum-standard). This reduces the considerable uncertainty that investors face when investing in ICOs and enables more informed decision-making.     

Heteroskedasticity-consistent covariance matrix estimators for spatial autoregressive models

In the presence of heteroskedasticity, conventional test statistics based on the ordinary least squares (OLS) estimator lead to incorrect inference results for the linear regression model. Given that heteroskedasticity is common in cross-sectional data, the test statistics based on various forms of heteroskedasticity-consistent covariance matrices (HCCMs) have been developed in the literature. In contrast to the standard linear regression model, heteroskedasticity is a more serious problem for spatial econometric models, generally causing inconsistent extremum estimators of model coefficients. This paper investigates the finite sample properties of the heteroskedasticity-robust generalized method of moments estimator (RGMME) for a spatial econometric model with an unknown form of heteroskedasticity. In particular, it develops various HCCM-type corrections to improve the finite sample properties of the RGMME and the conventional Wald test. The Monte Carlo results indicate that the HCCM-type corrections can produce more accurate results for inference on model parameters and the impact effects estimates in small samples.     

ALICE: Composite leading indicators for euro area inflation cycles

This paper develops Area-wide Leading Inflation CyclE (ALICE) indicators with the aim to provide early signals for turning points in the euro area headline and core inflation cycles. The headline (core) ALICE leads the reference cycle by three (four) months and the lead times extend to five (nine) months based on longer-leading series. Both ALICE indicators signalled turning points in the inflation cycles ex post and also performed well in a simulated real-time exercise. Moreover, in particular the headline ALICE also appeared to be useful for quantitative forecasting of the direction and level of inflation.     

An Exploratory analysis of flight delay propagation in China

Delay propagation is the flight departure delay caused by the arrival delay of pre-segment flight. Chinese airline market has suffered very poor on-time performance (OTP) in recent years. It is, however, unclear whether delay propagation prevails as one major source for such problem. This study first aims to empirically quantify delay propagation in the Chinese airline market. Specifically, we shed light on heterogenous levels of delay propagations across different airports and airlines. Then, the distinct delay propagation patterns in China are also discussed and compared with other developed airline markets (e.g., the US and Europe). Our estimation is based on OTP data for over 12 million Chinese flights covering the 2015–2017 period. Specifically, it is found that 10 min arrival delay of pre-segment flight within 1 hr before the departure lead to an average of 7.49 mins delay propagation for subsequent departure flight. Arrival delay of earlier pre-segments (1–2 and 2–3 hr before the departure) leads to much less delay propagation, due to longer ground buffer. Chinese airlines arrange longer ground and flight buffer than that of the US airlines to prevent the delay propagation from accumulating along the subsequent flights in a day. Thus, unlike the US market, delay propagation is not the major reason for poor OTP in China. In addition, delay propagation is less prevailing at the Chinese hub airport. This is because China has relied on point-to-point network, which does not require sophisticated schedule coordination. And the local passengers at these Chinese hub airports have higher time value such that the Chinese airlines also try to improve OTP at these hub airports to better serve these lucrative but time-sensitive local passengers. Unlike the European LCCs, Spring Airlines, the largest low-cost carrier (LCC) in China, outperforms major full-service carriers (FSCs) in controlling delay propagation. This finding may also apply to other Northeast Asian LCCs sharing common operational characteristics as Spring Airlines. Last, we find that airlines purposely tolerate moderate departure delays of up to 15 min, which is the threshold that defines delays, no matter whether the pre-segment flight arrives late or on-time. The relevant policy and managerial implications are also discussed.     

Beyond classical van Westendorp: Assessing price sensitivity for variants of algae-based meat substitutes

Food product innovations are characterized by high flop rates. In an early development stage, manifold product formulations seem feasible. To determine the most promising product option, market research can help, but is frequently considered too costly and complex. We assess the applicability of the van Westendorp approach, an inexpensive and simple method, for guiding early product design and pricing decisions for novel foods. Findings from a between-subject experiment for meat substitutes consisting of different shares of micro-algae indicate that micro-algae, while a cost driver, has little effect on price preferences. Implications for novel food product design, market research, and retailing are discussed.     

Revising price history: consumer price index for Norway 1492–2018

ABSTRACT

The paper presents a new combined annual cost of living and consumer price index for Norway covering 1492–2018, indicating that Norwegian price history has to be revised. The new historical price index is constructed on a significantly richer data material, which also makes it cover a longer period of price history than the existing one. This is made possible by the compilation of quantitative data from numerous sources, mostly originating from the eighteenth, nineteenth and early twentieth centuries, with grain prices stretching back to 1492. The new combined cost of living and consumer price index is constructed by a Laspeyres approach with shifting baskets for commodities and expenditure groups.

The index makes it possible to follow annual inflation and deflation in Norway for a period of 526 years. When comparing to existing indices, the new series reveals that revisions are needed in Norwegian price history. These make the historical price development more in line with those of the neighbouring countries and more in line with the pattern of wholesale prices.     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

针对车辆AEB系统失效和误作用场景的研究

本文基于预期功能安全,采用功能分解方法,总结出部分车辆自动紧急制动(AEB)系统失效和误作用场景,并从中选取典型场景作为测试场景,开展不同车型的实车道路试验,总结出AEB系统的缺陷与隐患分类。希望此类研究能为AEB系统失效和误作用测试标准的制定提供参考。     

环境公平感知、社会信任与农户低碳生产行为*——以农膜、秸秆处理为例

［目的］研究旨在探讨环境公平感知和社会信任与农户低碳生产行为之间的关系，为促进农户生产行为向低碳化方向转变提供对策建议。［方法］基于陕西和甘肃两省的村域调查数据，以农膜和秸秆处理为例，运用二元logistic模型探讨环境公平感知和社会信任对农户低碳生产行为的影响，并结合分层回归分析了社会信任在环境公平感知和农户低碳生产行为间的调节效应。［结果］（1）在环境公平感知维度中，人际公平感知正向影响农户的农膜和秸秆处理行为； （2）对社会信任来讲，人际信任对农户农膜和秸秆处理行为均有显著的促进作用，而制度信任仅对农户秸秆处理行为具有正向影响； （3）人际信任在种际公平感知和农户农膜处理行为之间具有显著的正向调节效应，而制度信任在两者之间具有显著的负向调节效应； 同样，人际信任在人际公平感知和农户秸秆处理行为之间具有正向调节效应，而制度信任弱化了人际公平感知对农户秸秆处理行为的影响。［结论］环境公平感知和社会信任是影响农户低碳生产行为的关键因素，且社会信任在种际公平感知和农户农膜处理行为之间以及在人际公平感知和农户秸秆处理行为之间具有显著的调节作用。     

Past,present, and future of green product innovation

Firms are under constant pressure from various governmental and nongovernmental agencies to switch from conventional environmentally polluting products to green product innovations (GPIs). However, the relevant research pertaining to GPI has been published in a diverse set of journals that vary in their scope and readership and, therefore, the scholarly contribution to the topic remains largely fragmented. This study has utilised a systematic literature review approach to examine the literary corpus on GPI to paint a holistic picture of its different aspects. The content and thematic analysis of 85 studies resulted in the extraction of seven key research themes: organisational capabilities, organisational learning, institutional pressures, barriers, structural changes, benefits of GPI, and methodological choices. This study's findings further highlight the various gaps in the GPI literature and raise some research questions that warrant scholarly investigation in the future. Likewise, our study has important implications for practitioners who are likely to benefit from a holistic understanding of the different aspects of GPI. Similarly, policymakers can use this study's findings to introduce policy interventions, especially in countries where GPI adoption is low.