International evidence on the relative importance of the determinants of earnings forecast accuracy

We analyze earnings forecasting errors made by financial analysts for 18 developed countries over the 1990–2006 period. We use the Heston–Rouwenhorst approach to unravel country-, industry-, and firm-specific effects as a source of variation in financial analysts’ earnings forecast errors. We first estimate each effect with a dummy variable regression, and then decompose the variance of forecast errors into different effects. We provide evidence that the differences between countries, industrial sectors, and analyst-following offer a weak explanation for differences in forecast errors. Country effects however largely dominate industry and analyst-following effects. By contrast, the type of earnings (profits or losses)—and variations in earnings (increases or decreases) play a significant role in the forecast accuracy of financial analysts.     

A Four-Country Study of the Associations Between Bribery and Unethical Actions

The purpose of this research is to extend prior research testing the premise that small deviations from ethical behavior lead to even larger deviations from ethical behavior. This study examines the association between a person’s willingness to bribe a police officer to avoid being issued a speeding ticket with their views on inappropriate behavior of corporate executives. Our sample of 528 participants comes from Colombia (90), Ecuador (70), South Africa (131) and the United States (237). As part of our data gathering, we controlled for social desirability response bias in the responses of the students who participated in our study. Our data indicate significant differences between the views of the students from Colombia, Ecuador, and South Africa when compared to the views of the students from the United States. The analysis indicates that, for all four dilemmas, the most significant variable was the belief about how ethical it was to pay a bribe to avoid a traffic ticket. In addition, in three of our four dilemmas, Paulhus’ Impression Management Subscale, which measures social desirability response bias, was the second most significant variable. Finally, in three of the four dilemmas, the students from Colombia, Ecuador and South Africa thought the actions described in the dilemmas were less ethical than the students from the United States.

Researcher Interaction Biases and Business Ethics Research: Respondent Reactions to Researcher Characteristics

The potential for biased responses that occur when researchers interact with their study participants has long been of interest to both academicians and practitioners. Given the sensitive nature of the field, researcher interaction biases are of particular concern for business ethics researchers regardless of their preference for survey, experimental, or qualitative methodology. Whereas some ethics researchers may inadvertently bias data by misrecording or misinterpreting responses, other biases may occur when study participants’ responses are systematically influenced by the mere introduction of researchers into the participants’ environment. Although substantial empirical research has been conducted on the general topic of researcher interaction biases, none has focused specifically on business ethics research. In order to remedy this lack of empirical substantiation in the field, we review the related literature on researcher interaction biases, present an empirical example of how such biases can influence research results in an experiment assessing reactions to insurance fraud, and discuss the implications for business ethics research.     

Economic Benefits Resulting From Irrigation Water Use: Theory and an Application to Groundwater Use

Traditional economic analysis using a crop production function approachhas assumed that all variable factors, including irrigation water, arefully employed in the crop production process. However, this paper firstdemonstrates that economic benefits of irrigation water areoverestimated when the crop production function, and therefore theirrigation water demand function, is expressed in terms of irrigationwater supplied, rather than consumptive irrigation water use. Second,the paper demonstrates that the magnitude of the estimation bias isproportional to the rate of irrigation water losses through leaching,runoff and evaporation. Consequently, the model misspecification problemwould lead to increased irrigation water use and reduce incentives forfarmers to adopt improved irrigation technologies.     

从贸易条件改善看技术进步的产业政策导向

技术进步与贸易条件之间存在着密切的关联,传统理论和实践往往从出口商品结构调整和提高出口品技术含量方面去研究改善贸易条件途径,却忽略了技术进步的类型与偏向性选择对贸易条件的影响。本文从开放经济条件下技术进步偏向性出发,分析不同类型技术进步对一国贸易条件产生的影响。其基本结论是,我国长期采取出口偏向型技术进步已成为我国贸易条件恶化的根本原因,并提出我国鼓励技术进步的政策应该倾向于进口偏向型的中高级技术。     

Individual risk tolerance and herding behaviors in financial forecasts

Financial analysts tend to demonstrate herding behavior, which sometimes compromises accuracy. A number of explanations spanning rational economic logic, cognitive biases, and social forces have been suggested. Relying on an experimental setting where participants forecast future earnings from a rich information set, we posit and obtain support for individual risk tolerance (or lack thereof) as an explanatory variable for herding behaviors. Specifically, less risk‐tolerant individuals forecast with less boldness and instead issue forecasts in agreement with the consensus forecast. The results are argued to be at least partially a product of cognitive biases and an intuitive reaction to uncertainty.     

The impact of XBRL adoption on local bias: Evidence from mandated U.S. filers

This paper investigates how eXtensible Business Reporting Language (XBRL) adoption affects the information advantage of local investors relative to their non-local counterparts. By employing the recent staggered SEC mandates of XBRL as a natural shock, we show that institutional investors’ local bias decreases after firms adopt XBRL when preparing their financial statements. These results hold in a difference-in-difference research design with firm and year fixed effects or using matched nonadopting firms as controls, as well as a regression discontinuity design. The impact of XBRL adoption on reducing local bias can be explained by three economic channels: decreased information processing costs, increased corporate disclosures, and improved analyst coverage. We further find that institutions’ superior stock returns in geographic proximate equity investments significantly reduces after the XBRL mandate. The observed reduction in institutional investors’ local bias within U.S. companies following the XBRL mandate also applies to the international setting. Overall, our findings support regulators’ claim that XBRL adoption levels the playing field between local and non-local investors.     

When does an ethical attribute matter for product evaluation? The role of warm-glow feelings for low-rated products

Research on the effects of ethical attributes has recently gained traction. However, limited research has addressed consumer response to ethical attributes in the current context where product ratings have become of primary importance to make decisions. Specifically, this study examines the relative effect of ethical attributes on product evaluations across different product ratings. Building on cue consistency theory and the negativity bias, we suggest that ethical attributes gain weight when consumers evaluate a low-rated product. This process leads consumers to anticipate more warm-glow feelings, generating better evaluations for such low-rated products featuring an ethical attribute (vs. another type of attribute). Two experiments provide consistent empirical support for this prediction, and demonstrate that, compared to other attributes or no attribute, an ethical attribute increases product evaluations to a larger extent when the product received low (vs. higher) ratings. We show that this effect occurs because of warm-glow feelings: when product ratings are low, consumers anticipate more warm-glow feelings from purchasing a product with an ethical attribute (vs. another type of attribute), leading to better product evaluations. These findings have direct managerial and ethical implications for practitioners.     

The perils of working with big data,and a SMALL checklist you can use to recognize them

The use of big data to help explain fluctuations in the broader economy and key business performance indicators is now so commonplace that in some instances it has even begun to rival more traditional measures. Big data sources can very often provide advantages when compared with these more traditional data sources, but with these advantages also come potential pitfalls. We lay out a checklist called SMALL that we have developed in order to help interested parties as they navigate the big data minefield. Based on a set of five questions, the SMALL checklist should help users of big data draw justifiable conclusions and avoid making mistakes in matters of interpretation. To demonstrate, we provide several case studies that demonstrate the subtle nuances of several of these new big data sets and show how the problems they face often closely relate to age-old concerns that more traditional data sources are also forced to tackle.     

Trust and the don't‐want‐to‐complain bias in peer‐to‐peer platform markets

This paper addresses peer‐to‐peer (P2P) digital platform markets, often associated with the “sharing economy” or the “collaborative economy”. Such digital platforms, facilitating new purchasing channels for consumers by matching P2P supply and demand, can be considered new market places challenging the conventional markets. How are P2P platform markets evaluated by the consumers? Based on a comprehensive survey‐data material, five different P2P service markets are considered by peer buyers and the results compared to consumers’ evaluations from similar conventional service markets according to trust, comparability and consumers’ satisfaction with the transactions. Comparability seems to be one advantage for the platform markets, while trust could become a problem. Conditions for trust in P2P platform markets is particularly interesting to study because contrary to conventional markets P2P transactions cannot rely on governmental laws, regulations and security net. This trust problem has been solved by a trust‐generating rate and review system. Our data material, however, distinguishes a mechanism that we have coined as the don't‐want‐to‐complain bias. More precisely, people do not like to complain, hence buyers of P2P services often hesitate to give negative ratings when they are discontent with a service or a supplier. Therefore, positive ratings become overestimated. If consumers recognize this bias, ratings and reviews will lose credibility and no longer be considered trustworthy. Eventually, this may threaten the well‐functioning of P2P markets.