Reference points for measuring social performance: Case study of a social business venture

We present a longitudinal qualitative case study to elaborate on how a social venture forms reference points for social performance. Although organizations increasingly use various social performance targets to direct their operations, the scholarly knowledge on social performance reference points remains limited. We make use of the prior accounting literature and draw on the idea of compromising accounts to discuss how provisional and performative metrics can have a significant role in how organizations develop new ways to evaluate their social performance. Given that the social performance reference point criteria are ambiguous and the corresponding referents malleable, performative accounts are helpful as they can intervene in the organizational life by making particular things visible, providing space for interpretations, and facilitating discussion, thus creating temporary settlements and enabling opportunities for productive compromises between different organizational groups and evaluative principles. The recursive feedback loops between reference point referents, criteria and accounting artefacts help the organization to make sense of its own social performance and interpret the associated performance feedback, and thereby provide ground for organizational decisions on further action. Moreover, we discuss how imperfect accounts can be useful for social businesses in their pursuit of developing their activities and achieving social impact.     

Does educational diversity of managers matter for the performance of team‐managed funds?

We study the effect of the educational diversity of managers on the performance of team‐managed mutual funds using a large sample of U.S. equity funds from 1994 to 2013. We consider diversity in terms of both final educational degree and field of educational specialisation. We find that, in general, both types of diversity have a positive impact on fund performance, and our results are robust over a wide range of performance metrics and changes in market conditions.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Testing the Empirical Relevance of the ‘Saving for a Rainy Day’ Hypothesis in US Metro Areas

The joint implication of the consumption Euler equation and cointegration between income and consumption is that savings predict future income declines, the ‘saving for a rainy day’ hypothesis. The empirical relevance of this hypothesis plays a key role in discussions of fiscal policy multipliers, and it holds under the null that the permanent income hypothesis is true. We find little support for this hypothesis using time series data for the 100 largest US Metropolitan Statistical Areas for the period 1980q1–2015q4. Our approach is to test for cointegration and weak exogeneity between income and consumption, and by exploring the direction of Granger causality between the two time series. We find that income more often predicts consumption and saving than the converse. We also give evidence that house price changes played a role in US income and consumption dynamics, before, during and after the Great Recession.     

How capital markets assess the credibility and accuracy of CSR reporting: Exploring the effects of assurance quality and CSR restatement issuance

This research examines how the credibility and accuracy of corporate social responsibility (CSR) disclosures enhance market confidence by exploring their effect on the cost of capital. How do capital markets react to higher-quality assurance of CSR reporting? Can the hypothetical reduction in the cost of capital that assurance quality produces be explained by restatements of previous information given in these CSR reports? We explore the relationship between assurance quality, as a proxy for credibility and market confidence, and the mediating effect of CSR restatements as indicators of accuracy. We propose regression models with a sample of CSR reports issued by European companies. Building upon the signalling and legitimacy theories, the results support the positive effect of higher assurance quality statements on market confidence by confirming a decrease in the cost of capital; assurance quality gives an indication of credibility to the capital market and restatements related to methodological updates signal accuracy. The reduction in the cost of capital brought on by higher assurance quality appears to be determined by the issuance of CSR restatements, which create legitimacy for both client companies and assurance providers. CSR reporting and assurance have reached a greater level of maturity as demonstrated by the evolution of these practices and financial market perceptions.     

Magic mirror in my hand … How trade mirror statistics can help us detect illegal financial flows

Misreporting tricks of different sorts applied to the transfer of goods between different countries are typically exploited by criminals worldwide for money laundering ends. The main international anti‐money laundering organisations started paying attention to this phenomenon, dubbed “trade‐based money laundering” (TBML), a long time ago, but the failure to develop appropriate analytical tools has reportedly dogged preventive actions. Nonetheless, literature has widely advocated the possibility that the analysis of inconsistencies in mirrored bilateral trade data could provide some help. By building on previous contributions in the field, this work sets up a model factoring in the main structural determinants of discrepancies between mirrored data concerning Italy's 2010 to 2013 external trade at a highly detailed (6‐digit) level of goods classification for each partner country. Point estimates of freight costs are used to net each observation of the corresponding cif/fob discrepancy. The regression estimates are then deployed in order to compute TBML risk indicators at a country/4‐digit product level. Based on the indicators, rankings of countries and product lines can be compiled, which may be used for a risk‐driven search of potential illegal commercial transactions.     

Revisiting the expatriate failure concept: A qualitative study of Scandinavian expatriates in Hong Kong

This article advances the understanding of expatriate failure, which remains a contested social phenomenon in international work life as well as scholarly research. The study challenges the definition of expatriate failure and its inherent biases, i.e., the epistemological primacy of the firm level and the failure/success binary. We argue that this qualitative study of 51 Scandinavian expatriates in Hong Kong can contribute to advancing theory on the expatriate failure concept by asking individual expatriates what constitutes failure to them. By applying social constructionist and social anthropological ideas to the expatriate failure concept debate, we develop the internationality thesis which demonstrates a discrepancy between the expatriates’ perceptions of successful international assignments and the actual nature of their lived lives; many expatriates desire to enrich their lives through experiencing an international/intercultural and adventurous lifestyle, but, in fact, living lives with limited intercultural exposure and interaction. We conclude by proposing a reconceptualisation of expatriate failure in terms of offering both a new definition and approach to researching expatriate failure in which time/duration, context, and geographical location need to be taken into account. We believe the new approach can overcome some of the empirical unsoundness of mainstream definitions.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

It is not a flat world after all: Tax repatriation costs and cash value

US corporations have accumulated record‐high amounts of cash, and most of it is trapped in foreign accounts. This study tests the hypothesis that the marginal value of cash decreases in the presence of tax repatriation costs, as these costs are a strong indication that part of the cash is trapped abroad. Cash abroad is not readily available to the company because it is subject to an additional layer of tax before it can be used or distributed. Moreover, uncertainty surrounds the potential use of foreign cash, and research documents that firms holding high amounts of cash abroad are likely to invest in negative net present value activities. Finally, possible changes in tax regulation are an additional source of uncertainty. Consequently, foreign cash should be worth less than domestic cash. Using a large sample of US firms drawn from COMPUSTAT during the 1991–2012 period, the analysis suggests that shareholders value an extra dollar of cash at $1.086. However, this result changes dramatically when the change in cash is interacted with the tax cost of repatriating the earnings. That is, the marginal value of cash decreases significantly in the presence of tax repatriation costs, and shareholders discount cash when it is likely to be held abroad. This study contributes to the literature on cash holding by investigating whether tax repatriation costs affect the value of corporate cash. Moreover, the findings show that there are important economic consequences linked to the phenomenon of cash accumulation in foreign countries and therefore provide regulators with a sound foundation on which to take additional actions to require more disclosure of and transparency in the actual location of firms’ cash holdings.