Economic development,food demand and the consequences for agricultural resource requirements: an application to Indonesia

We analyse food demand patterns of Indonesian households from a resource intensity perspective and quantify the impact of changed demand patterns on the use of three major resource inputs: fossil fuel; land; and water in agricultural production. Using Indonesian Family Life Survey data, 13 major food items (which constitute 70 per cent of food expenditure) are categorised into low, moderate and high resource intensity, and income elasticity and Engel curves are estimated for the period from 1997 to 2007. Our results show that income growth in Indonesia is associated with demand patterns that are more resource intensive. By 2007, per capita requirements of fossil fuel, land and water increased by 42.7 per cent (3.13 MJ), 44.9 per cent (1.24 m²) and 50.4 per cent (2.1 kL), respectively, relative to 1997. The results imply that, at least for Indonesia, changed food demand patterns resulting from economic development will increase the demand for natural resources substantially.     

Eco-labels and product longevity: The case of whitefish in UK grocery retailing

In recent years, eco-labeling has become an increasingly used tool to signal sustainable sourcing of (sea-) food. While the literature has focused on price premiums associated with the labels, it is noted in this paper that eco-labels can also contribute to profitability by reducing cost, e.g. through longer product lifespans. Hence, eco-labels can be beneficial in a supply chain even without a price premium. This study applies duration analysis to explore whether two eco-labels (the MSC label of the Marine Stewardship Council and a line-caught label) influence product longevity of whitefish products in eight different grocery retailers in the UK. The results show that MSC labeled products have a 64.7% lower risk of being withdrawn from the shelves compared to non-MSC products, while products with the line-caught label have a 32.8% lower risk of being withdrawn than products without this label. The results also indicate that the influence of the eco-labels on product longevity vary considerably between the retailers.     

Status of brands in children’s consumption: What letters to Santa posted on La Poste website tell us

The purpose of the research is to identify different consumption styles based on a large collection of letters to Santa written by some children and/or their families and submitted to the French Post website (La Poste). One of our main interests focuses on the presence and weight of brands and licenses in children’s wish lists. We have had access to all the anonymous posts sent to Santa Claus through La Poste’s website during the 2013 and 2014 Christmas holidays. We analyzed the nature of the wish lists as shown in the 43,000‐post database using several textual data analysis techniques. Extensive heterogeneity was found among children’s and families’ postures regarding that specific ritual. The different types of emails reflect the meaning families associate with Christmas time but also their different consumption styles or attitudes toward consumption: reasoned, educational, hedonistic, or materialistic, for example. When focusing on brands and licenses, we can also observe significant differences in the way families and children include them in their consumption decisions. Brands could have a very different weight in Christmas wish lists and their natures reflect different value transmission modes. The French market for Christmas children brands is rather stable and focuses on a few top leading global brands such as Playmobil, Barbie, or Lego. At least one of the ten leading brands is mentioned in half of evaluated Christmas wish lists. The analysis confirms that brands are very clearly gendered and associated with the children’s ages. Peak time for brand desire is alleged to be reached between the age of 7 and 9. To our knowledge, our research is the first to analyze a large sample of spontaneous data to capture children’s consumption styles and attitudes toward brands. Because of our classification, a first typology of parental consumption styles has also been identified.     

The determinants of austerity in the European Union 2010–16

This paper aims at decteting what drove the adoption of austerity policies over the period 2010–16 in a panel of 28 European countries. Austerity is identified by year increases in the ratio between the structural primary balance and potential GDP. By means of principal component factor analysis we select the aggregate factors that might affect austerity, namely (i) fiscal consolidation (correction of high deficits and debts), (ii) market discipline (high sovereign spreads, low ratings), (iii) rule-based fiscal discipline (compliance with the Eurozone rules), and macroeconomic stabilisation (consideration for the cyclical position of the economy). Then we estimate a dynamic panel model with the system-GMM method. Results show that the most important contributions to austerity are provided by the market discipline and fiscal consolidation factors together with Excessive Deficit Procedures, with no significant role played by concomitant macroeconomic conditions. Overall, governments complied with orthodox fiscal principles and rules.     

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.     

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.     

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.     

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。     

基于神经网络的建筑业碳排放强度预测——以京津冀为例

通过统计分析得出影响建筑业碳排放强度的13个影响因素,基于收集的京津冀相关数据,运用逐步回归分析找出其中6个关键因素.借鉴五折交叉验证解决数据稀缺问题,采用神经网络对京津冀建筑业碳排放强度进行预测.利用敏感性分析简化模型,筛选出4个核心因素.结果表明,此模型预测精度高达99％,同时根据挖掘出的核心因素和关键因素,提出建筑业节能减排的建议.     

Media-Based Sentiment Indices as an Alternative Measure of Consumer Confidence

In this paper, we consider the feasibility of constructing online sentiment indices, using large amounts of media data, as an alternative to the conventional survey method used to create the consumer confidence index in South Africa. A clustering framework is adopted to provide an indication of possible candidate sentiment indices constructed from a combination of different text sources and dictionaries that best mimic the traditional survey-based consumer confidence index from the South African Bureau for Economic Research (BER). The results conclude that it is possible to create an index using sentiment analysis using online editorial data that does resemble the BER’s consumer confidence index. The different media-based sentiment indices (MSI) show a significant level of correlation and co-movement with the BER’s CCI. Impulse responses and cross-correlation functions indicate that the MSI could potentially lead the survey-based method up to two quarters. Furthermore, Granger-causality tests show that the media-based indices are good predictors of future consumer confidence index values. The results provide motivation for further study on the use of sentiment-based techniques and online media data sources to track consumer confidence within an emerging market such as South Africa.