Preface to Intertwingled: The Work and Influence of Ted Nelson

This is the preface to Intertwingled: The Work and Influence of Ted Nelson , which examines and honors the work and influence of the computer visionary and re-imagines its meaning for the future. Emerging from a conference held in 2014 at Chapman University, it includes contributions from world-renowned computer scientists and media figures. The full text of this book is available on an open access basis at Springer. The blog for the Intertwingled Conference can be read here.https://digitalcommons.chapman.edu/scs_books/1023/thumbnail.jp

The Interrelation between Audit Quality and Managerial Reporting Choices and Its Effects on Financial Reporting Quality

Two distinct lines of research have been dedicated to empirically testing how financial reporting quality (measured as the earnings response coefficient or ERC) is associated with management's choice of reporting bias and with audit quality. However, researchers have yet to consider how ERCs are affected by either the auditor's reaction to changes in the manager's reporting bias or the manager's reaction to changes in audit quality. Our study provides theoretical guidance on these interrelations and how changes in the manager's or the auditor's incentives affect both reporting bias and audit quality. Specifically, when the manager's cost (benefit) of reporting bias increases (decreases), we find that expected bias decreases, inducing the auditor to react by reducing audit quality. Because we also find that the association between expected audit quality and ERCs is always positive, changes in managerial incentives for biased reporting lead to a positive association between ERCs and expected reporting bias. When the cost of auditing decreases or the cost of auditor liability increases, we find that expected audit quality increases, inducing the manager to react by decreasing reporting bias. In this case, changes in the costs of audit quality lead to a negative association between ERCs and expected reporting bias. Finally, we demonstrate the impact of our theoretical findings by focusing on the empirical observations documented in the extant literature on managerial ownership and accounting expertise on the audit committee. In light of our framework, we provide new interpretations of these empirical observations and new predictions for future research

The growth companies puzzle: can growth opportunities measures predict firm growth?

While numerous empirical studies include proxies for growth opportunities in their analyses, there is limited evidence as to the validity of the various growth proxies used. Based on a sample of 1942 firm-years for listed UK companies over the 1990-2004 period, we assess the performance of eight growth opportunities measures. Our results show that while all the growth measures show some ability to predict growth in company sales, total assets, or equity, there are substantial differences between the various models. In particular, Tobin's Q performs poorly while dividend-based measures generally perform best. However, none of the measures has any success in predicting earnings per share growth, even when controlling for mean reversion and other time-series patterns in earnings. We term this the 'growth companies puzzle'. Growth companies do grow, but they do not grow in the key dimension (earnings) theory predicts. Whether the failure of 'growth companies' to deliver superior earnings growth is attributable to increased competition, poor investments, or behavioural biases, it is still a puzzle why growth companies on average fail to deliver superior earnings growth

Validating soil denitrification models based on laboratory N2 and N2O fluxes and underlying processes: evaluation of DailyDayCent and COUP models

Denitrification is an anaerobic key process by microbes where the NO3- is step-by-step reduced and emitted as NO, N2O and finally N2 gas from the soil. Accurate knowledge on denitrification dynamics is important because the N2O is further reduced to N2 and constitutes the main emission source of this greenhouse gas from agricultural soils. Hence, our understanding and ability to quantify soil denitrification is crucial for mitigating nitrogen fertilizer loss as well as for reducing N2O emissions. Models can be an important tool to predict mitigation effects and help to develop climate smart mitigation strategies. Ideally, commonly used biogeochemical models could provide adequate predictions of denitrification processes of agricultural soils but often simplified process descriptions and inadequate model parameters prevent models from simulating adequate fluxes of N2 and N2O on field scale. Model development and parametrization often suffers from limited availability of empirical data describing denitrification processes in agricultural soils. While in many studies N2O emissions are used to develop and train models, detailed measurements on NO, N2O, N2 fluxes and concentrations and related soil conditions are necessary to develop and test adequate model algorithms. To address this issue the coordinated research unit „Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales (DASIM)” was initiated to more closely investigate N-fluxes caused by denitrification in response to environmental effects, soil properties and microbial communities. Here, we present how we will use these data to evaluate common biogeochemical process models (DailyDayCent, Coup) with respect to modeled NO, N2O and N2 fluxes from denitrification. The models are used with different settings. The first approximation is the basic “factory” setting of the models. The next step would show the precision in the results of the modeling after adjusting the appropriate parameters from the result of the measurement values and the “factory” results. The better adjustment and the well-controlled input and output measured parameters could provide a better understanding of the probable scantiness of the tested models which will be a basis for future model improvement

Earnings Management: The Effect of Ex Ante Earnings Expectations

Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Return Predictability: The Dual Signaling Hypothesis of Stock Splits

This paper aims to differentiate between optimistic splits and overoptimistic/opportunistic splits. Although markets do not distinguish between these two groups at the split announcement time, optimistic (over-optimistic/opportunistic) splits precede positive (negative) long-term buy-and-hold abnormal returns. Using the calendar month portfolio approach, we show that the zero-investment, ex-ante identifiable, and fully implementable trading strategy proposed in this paper can generate economically and statistically significant positive abnormal returns. Our findings indicate that pre-split earnings management and how it relates to managers’ incentives, is an omitted variable in the studies of post-split long-term abnormal returns

Association between hyperketolactia and production in early-lactating dairy cows

Study aims were to investigate associations of hyperketolactia (HYKL) status of Holstein dairy cows between 6 and 60 d in milk (DIM), defined by milk acetone (mACE) and β-hydroxybutyrate (mBHB) content, with daily milk yield and composition. Milk samples (∼5.0 million) were collected over a 5-yr period (2014–2019) within the milk recording system in Poland. Concentrations of mACE and mBHB determined by Fourier-transform infrared spectroscopy were used to categorize samples into 4 ketolactia groups. Based on threshold values of ≥0.15 mmol/L mACE and ≥0.10 mmol/L mBHB, ketolactia groups were normoketolactia (NKL; mACE <0.15 mmol/L and mBHB <0.10 mmol/L), BHB hyperketolactia (HYKLBHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), ACE hyperketolactia (HYKLACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L), and ACE and BHB hyperketolactia (HYKLACEBHB; mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L). To investigate ketolactia association with production outcomes, a linear model was developed, including ketolactia group, DIM, parity, their interactions, year-season as fixed effects, and random effects of herd and cow. Among all milk samples, 31.2% were classified as HYKL, and of these, 52.6%, 39.6%, and 7.8% were HYKLACEBHB, HYKLBHB, and HYKLACE, respectively. Ketolactia groups differed for all traits studied in all parities and DIM. Among HYKL groups, lowest milk yield was found in HYKLACEBHB cows, except for 6 to 30 DIM in first- and second-lactation cows. Milk yield of HYKLBHB cows was higher than that of NKL cows until 20 to 30 DIM, and then it was lower than NKL cows. Milk yield of HYKLACE cows was mostly lower than NKL cows. Energy-corrected milk (ECM) yield of HYKLACEBHB cows was higher than that of NKL cows until 30 to 35 DIM for second lactation and third lactation or greater, and in the whole study period for first lactation. The yield of ECM for HYKLBHB cows was mostly higher than that of NKL cows, whereas HYKLACE cows had higher ECM than NKL cows until 15 to 25 DIM and then was lower for the HYKLACE group. Milk composition differed among HYKL groups. Highest milk fat (MF) and lowest milk lactose (ML) contents were observed in HYKLACEBHB cows. Cows in HYKLACEBHB and HYKLBHB groups had higher MF and lower milk protein (MP; except in 6–8 DIM in first lactation) and ML content than NKL cows. Milk fat content was higher in HYKLACE than NKL cows in first lactation and during the first 30 to 40 DIM in older cows. Lactose content was lower in HYKLACE than in NKL cows within 30 to 40 DIM; afterward it was higher in NKL cows. Lower MP content was found in HYKLACE than in NKL cows, except during 6 to 9 DIM for cows in first lactation and third lactation or greater. In conclusion, HYKL is associated with altered milk production in all parities, but a range of these negative relations depends on ketone status addressing both ACE and BHB contents. Further research is needed to ascertain underpinning biochemical defects of HYKL from elevated ACE, alone or in combination with BHB, during early lactation

Where do firms manage earnings?

Despite decades of research on how, why, and when companies manage earnings, there is a paucity of evidence about the geographic location of earnings management within multinational firms. In this study, we examine where companies manage earnings using a sample of 2,067 U.S. multinational firms from 1994 to 2009. We predict and find that firms with extensive foreign operations in weak rule of law countries have more foreign earnings management than companies with subsidiaries in locations where the rule of law is strong. We also find some evidence that profitable firms with extensive tax haven subsidiaries manage earnings more than other firms and that the earnings management is concentrated in foreign income. Apart from these results, we find that most earnings management takes place in domestic income, not foreign income.Arthur Andersen (Firm) (Arthur Andersen Faculty Fund

Applying Benford’s law to detect accounting data manipulation in the banking industry

We utilise Benford’s Law to test if balance sheet and income statement data broadly used to assess bank soundness were manipulated prior to and also during the global financial crisis. We find that all banks resort to loan loss provisions to manipulate earnings and income upwards. Distressed institutions that have stronger incentives to conceal their financial difficulties resort additionally to manipulating loan loss allowances and non-performing loans downwards. Moreover, manipulation is magnified during the crisis and expands to encompass regulatory capital