Spurious principal components

The principal component regression (PCR) is often used to forecast macroeconomic variables when there are many predictors. In this letter, we argue that it makes sense to pre-whiten the predictors before including these in a PCR. With simulation experiments, we show that without such pre-whitening, spurious principal components can appear and that these can become spuriously significant in a PCR. With an illustration to annual inflation rates for five African countries, we show that non-spurious principal components can be genuinely relevant in empirical forecasting models.     

Consumer Preferences for ‘Localness’ and Organic Food Production

While organic food is based on well-defined production criteria, the criteria for ‘local’ food are less clear. This study investigates the preferences and trade-offs of distinct consumer segments relative to organic production and several dimensions of local food (sales channel, size of company, and geographical location of animals used in the production). The analysis is based on a quantitative survey of 505 Danish consumers and a choice experiment involving beef salami. Data were analyzed in a principal component and a latent class analysis. We identify five consumer segments whose preferences for organic and local product attributes differed substantially. Most respondents considered geographical proximity in the raising of cattle to be the most important attribute and a third of the consumers were willing to pay a premium for organic salami. The segmentation provides more detailed information about stated consumer behavior than what is typically elicited when considering only average consumer behavior.     

Chinese banking reforms in perspective: towards global alignment or national specificity?

The reforms of the banking sector in China conducted so far have been seeking to accomplish, simultaneously, two conflicting goals. On the one hand, the objective was to prepare Chinese banks for international competition and put them at the pace with the transformations observed in its overall economy. On the other, there is a social-driven agenda concerning employment and regional inequalities. Using principal component analysis, this article explores the impact of the ongoing reforms in the Chinese banking sector on the performance of individual banks. The results show that despite identical regulation, business practices can be dissimilar at the individual level. Taken collectively, the results also show the increasing influence of Western management standards in the Chinese banking sector.     

稻鳅共生种养模式试验研究

[目的]稻鳅共生是典型的稻田综合利用模式,符合生态农业发展方向。通过对稻鳅共生生态系统的生理生态学机制开展试验研究,为进一步推广稻鳅共生种养模式提供科学依据。[方法]采用田间试验方法,以水稻单作为对照,研究了不同泥鳅养殖密度下的稻鳅共生对水稻农艺性状、土壤理化性质、水稻产量构成的影响,并对稻鳅共生种养模式进行了经济效益分析。[结果]与对照处理相比,水稻长势在株高、有效分蘖率、根长等方面有一定提高。养殖田水稻株高增高了3%,有效分蘖率提高了8%~11%,根长提高了8.8%~31.3%。在土壤理化性质方面,与对照相比,土壤容重降低了7.1%~21.2%,孔隙度增加了4.1%~14.7%。实验前后养殖田内土壤有机质增加了3.5%~26.5%,对照田降低了2.5%~5.8%。土壤肥力(氮、磷、钾)减少,但减少幅度小于对照处理。稻鳅共生种养模式下水稻产量提高了5%~25%,同时稻田增收泥鳅1 725~3 375kg/hm2,净收入为1.836 0万~2.307 0万元/hm2,经济效益提高了3.65~4.84倍。稻鳅共生种养模式中泥鳅的养殖密度为30万尾/hm2时稻田的生态效益和经济效益最佳。[结论]稻鳅共生有效改善了土壤理化性质,促进了水稻的生长,提高了稻田产量和产值。     

水源地突发水污染政府应急预留水量需求预测

近年来,随着工业化和产业化的快速发展,水源地突发水污染事件频发。为应对紧急情况下的水资源非常规需求,保障经济社会稳定发展,政府需要安排一部分应急预留水量。如何合理预测政府应急预留水量的规模是一个值得探讨的课题。提出了一种基于案例推理技术的政府应急预留水量需求预测方法,具体思路是:借助于案例库,利用主成分分析法从众多影响水源地突发水污染事件的因素中提取出两两不相关的因子,以此作为案例的特征属性,基于加权曼哈顿距离测算相似度,依此得到匹配案例,进而测算政府应急预留水量。以太湖流域常州地区水源地为例,进行政府预留水量需求量的预测与分析。该方法可以为政府应急预留水量的配置、储备等提供相关理论知识。     

Are they telling the truth? Revealing hidden traits of satisfaction with a public bike-sharing service

Public bike-sharing systems (BSSs) are an emerging mode of transportation introduced by municipalities to solve congestion problems in metropolitan areas, especially when integrated with other types of transportation. In the last years, the number of public bike-sharing services has been constantly on the rise all over the world, and generally the overall satisfaction with them is high. However, satisfaction with public services is driven by mechanisms that can differ from those in the private sector. It is important to establish to what extent a high satisfaction is genuine or simply ephemeral. Even “old” public services (like public transportation) become “gold” when accompanied by the introduction of new technologies. In this paper we analyze this phenomenon using data from a satisfaction web-survey conducted among customers of the public BSS “BikeMi” in Milan, Italy, in a period when mobile technologies have been introduced to speed up the service. On analyzing the responses to satisfaction questions using simple summary statistics, the level of satisfaction resulted very high. However, our aim was to look for potential “darker” sides of the service by detecting possible hidden satisfaction components. For this purpose, we used the Nonlinear Principal Components Analysis, which is particularly powerful in this context. A simple textual analysis was also performed as a validating test. Results from our analysis indicated that satisfaction is flawed by a set of factors like the mechanics of the bikes, the picking and dropping system, and the apps used to organize the service. Less concern was detected for more general aspects of the service.     

Developing a financial conditions index for a post-transition country: the case of Croatia

The interconnection between financial and business cycles and the importance of surveillance over financial markets emphasise the need for the development of indicators that could trace financial conditions in a country. In this paper, we focus on developing a financial conditions index for a post-transition country – Croatia. Since financial conditions indices for post-transition markets differ from those for developed markets due to differences in the development of their financial systems and the availability of data, we show that financial conditions indices constructed for post-transition markets need to be tailored to the specifics of such markets.     

Why principals tolerate biases of inaccurate agents

Some agents are more accurate than others in estimating the best policy. The more accurately an agent estimates a policy's effects, the more he will resist biases, such as bribes from a special interest. Thus, a special interest needs to pay a larger bribe to an accurate agent than to an inaccurate agent. The accurate agent who is biased will then more likely cause harm than does an inaccurate agent who favors the special interest. Therefore, the principal may gain more from controlling biases of an accurate agent than of an inaccurate one. Thus, high ability of public officials may be associated with little corruption.     

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.     

国有林场改革成效评价——职工获得感的统计分析

利用国有林场职工监测数据,基于物质维度和精神维度,从改革后职工自身的收益情况、职工对林场的整体评价、职工对林场管理方式的评价等方面,采用比较分析法和主成分分析法对国有林场改革职工获得感进行分析。研究结果表明:国有林场改革后职工获得感有所提升,改革进程与职工获得感呈强正相关性,改革促进了林场的可持续发展。但林场整体基础设施环境一般,场部相对较好,管护站点则较差。同时,在领导班子建设方面应注重自主、公平,仍需提高领导水平。