Accounting for the economic risk, caused by variation in disease severity, in fungicide dose decisions: exemplified for Mycosphaerella graminicola on winter wheat

A method is presented to calculate economic optimum fungicide doses accounting for the risk-aversion of growers responding to variability in disease severity between crops. Simple dose-response and disease-yield loss functions are used to estimate net disease-related costs (fungicide cost, plus disease-induced yield loss) as a function of dose and untreated severity. With fairly general assumptions about the shapes of the probability distribution of disease severity and the other functions involved, we show that a choice of fungicide dose which minimises net costs on average across seasons results in occasional large net costs caused by inadequate control in high disease seasons. This may be unacceptable to a grower with limited capital. A risk-averse grower can choose to reduce the size and frequency of such losses by applying a higher dose as insurance. For example, a grower may decide to accept ‘high loss’ years one year in ten or one year in twenty (i.e. specifying a proportion of years in which disease severity and net costs will be above a specified level). Our analysis shows that taking into account disease severity variation and risk-aversion will usually increase the dose applied by an economically rational grower. The analysis is illustrated with data on septoria tritici leaf blotch of wheat caused by Mycosphaerella graminicola. Observations from untreated field plots at sites across England over three years were used to estimate the probability distribution of disease severities at mid-grain filling. In the absence of a fully reliable disease forecasting scheme, reducing the frequency of ‘high loss’ years requires substantially higher doses to be applied to all crops. Disease resistant cultivars reduce both the optimal dose at all levels of risk and the disease-related costs at all doses.

Understanding complexities in international accounting standard setting: agenda entry and the case of IFRS for SMEs

Earlier accounting works have shown that an understanding of agenda entry is critical to better understanding the accounting standards setting process. Consider Walker and Robinson (1993; 1994) and Ryan (1998); and more generally agenda entrance as theorized in Kingdon (2011). In 2003, the IASB placed on its agenda a project to promulgate a standard for small and medium-sized entities (SMEs). This provides our focus. It seemed to be a departure from the IASB’s constitutional focus on capital market participants. Kingdon’s three-streams model of agenda entry helps to identify some of the complexities related to politics and decision making messiness that resulted in a standard setting project for simplified IFRS, misleadingly titled IFRS for SMEs. Complexities relate to the broader international regulatory context, including the boundaries of the IASB’s standard-setting jurisdiction, the role of board members in changing those boundaries, and such sensitivities over the language that the IASB could not agree on a suitably descriptive title. The paper shows similarities with earlier agenda entrance studies by Walker and Robinson (1994) and Ryan (1998). By drawing on interviewees’ recollections and other material it especially reinforces the part played by the nuanced complexities that influence what emerges as an international accounting standard.

An essay about the effect of vague accounting standards on the decision making process of auditors

Vague words and expressions are present throughout the standards that comprise the accounting and auditing professions. Vagueness is considered to be a significant source of inexactness in many accounting decision problems and many authors have argued that the neglect of this issue may cause accounting information to be less useful. On the other hand, we can assume that the use of vague terms in accounting standards is inherent to principle based standards (different from rule based standards) and that to avoid vague terms, standard setters would have to incur excessive transaction costs. Auditors are required to exercise their own professional judgment throughout the audit process and it has been argued that the inherent vagueness in accounting standards may influence their decision making processes. The main objective of this paper is to analyze the decision making process of auditors and to investigate whether vague accounting standards create a problem for the decision making process of auditors, or lead to a better outcome. This paper makes the argument that vague standards prompt the use of System 2 type processing by auditors, allowing more comprehensive analytical thinking; therefore, reducing the biases associated with System 1 heuristic processing. If our argument is valid, the repercussions of vague accounting standards are not as negative as presented in previous literature, instead they are positive.

Economic growth in Latin America: the role of investment and other growth sources

Includes bibliography

Dentistry scientometric analysis: A comparative study between Brazil and other most productive countries in the area

This research aims at performing a comparative study between the Brazilian scientific production in Dentistry, from 2000 to 2009 and countries that contribute with at least 2 % of the world's scientific production indexed in the Scopus database. More specifically, we intend to assess the annual Brazilian scientific production by comparing it to the other countries', analyze the Brazilian and other countries' publications in journals with higher impact factors, as well as to highlight the scientific production from these countries and its international visibility, measured by its total and by its average of citations and normalized citation index per year, by comparing the countries, and to compare the index h of such countries. As work procedure, the SCImago Journal and Country Rank was used as source, identifying the group of producing countries in the Dentistry area from 1996 to 2009. From a total of 136 countries, 13 were highlighted as the most productive, each one of them accounting for at least 2 % the worldwide scientific production in the area. The following indicators were raised for each country: number of produced documents, total of citations, self-citations, average of citations per document and index h. We verified that Brazil is the only country in Latin America that is pictured among the most productive ones in the Dentistry area. We observed that Brazil presents a growing visibility and impact in the international scenery, what suggests that its production is constantly consolidating, with Brazilian scientific recognition in the main vehicles of dissemination in the area. © 2012 Akadémiai Kiadó, Budapest, Hungary.

A multi-regional view on aging societies accounting for the existence of non-tradable goods

This thesis assesses the question, whether accounting for non-tradable goods sectors in a calibrated Auerbach-Kotlikoff multi-regional overlapping-generations-model significantly affects this model’s results when simulating the economic impact of demographic change. Non-tradable goods constitute a major part of up to 80 percent of GDP of modern economies. At the same time, multi-regional overlapping-generations-models presented by literature on demographic change so far ignored their existence and counterfactually assumed perfect tradability between model regions. Moreover, this thesis introduces the assumption of an increasing preference share for non-tradable goods of old generations. This fact-based as-sumption is also not part of models in relevant literature. rnThese obvious simplifications of common models vis-à-vis reality notwithstanding, this thesis concludes that differences in results between a model featuring non-tradable goods and a common model with perfect tradability are very small. In other words, the common simplifi-cation of ignoring non-tradable goods is unlikely to lead to significant distortions in model results. rnIn order to ensure that differences in results between the ‘new’ model, featuring both non-tradable and tradable goods, and the common model solely reflect deviations due to the more realistic structure of the ‘new’ model, both models are calibrated to match exactly the same benchmark data and thus do not show deviations in their respective baseline steady states.rnA variation analysis performed in this thesis suggests that differences between the common model and a model with non-tradable goods can theoretically be large, but only if the bench-mark tradable goods sector is assumed to be unrealistically small.rnFinally, this thesis analyzes potential real exchange rate effects of demographic change, which could occur due to regional price differences of non-tradable goods. However, results show that shifts in real exchange rate based on these price differences are negligible.rn

Evaluating Faculty Publications in Accounting Ph.D. Programs: The Author Affiliation Index as an Alternative

We propose a new model, the Author Affiliation Index (AAI), for examining journal quality, explain how the AAI is calculated, and report the resulting scores for 35 accounting and accounting-related journals. Next, we compare AAI journal rankings with those from other published studies and examine the correlations between them to show how the AAI can be used to evaluate relatively new journals, such as Accounting and the Public Interest, that are not included in extant ranking lists. By explaining its flexibility, we demonstrate that the AAI model can serve as a valuable tool for measuring journal quality and for meeting AACSB accreditation requirements for faculty groups as well as individual faculty. The AAI is based on the principle that as the percentage of authors in a journal who are accounting faculty at doctoral-granting institutions increases, the perceived value of that journal in terms of quality to Ph.D.-granting accounting programs also increases. Although our illustrations focus on the construction of this measure for use by Ph.D.-granting institutions, we describe how it can be adapted for use by other faculty groups.

Accounting for Fetal Death: Vital Statistics and the Medicalization of Pregnancy in the United States

Recent reports by the Centers for Disease Control and Prevention have decried the high rate of fetal mortality in the contemporary United States. Much of the data about fetal and infant deaths, as well as other poor pregnancy outcomes, are tabulated and tracked through vital statistics. In this article, I demonstrate how notions of fetal death became increasingly tied to the surveillance of maternal bodies through the tabulating and tracking of vital statistics in the middle part of the twentieth century. Using a historical analysis of the revisions to the United States Standard Certificate of Live Birth, and the United States Standard Report of Fetal Death, I examine how the categories of analysis utilized in these documents becomes integrally linked to contemporary ideas about fetal and perinatal death, gestational age, and prematurity. While it is evident that there are relationships between maternal behavior and birth outcomes, in this article I interrogate the ways in which the surveillance of maternal bodies through vital statistics has naturalized these relationships. Copyright 2013 Elsevier Ltd. All rights reserved.

Analysts' Forecast Accuracy in Germany: The Effect of Different Accounting Principles and Changes of Accounting Principles

This paper assesses the influence of an adoption of IAS/IFRS or US GAAP on the financial analysts’ forecast accuracy in a homogenous institutional framework. Our findings suggest that the forecast accuracy is higher for estimates based on IFRS or US GAAP data than for forecasts based on German GAAP data.Moreover, in the year of switching from German GAAP to US GAAP the forecast accuracy is lower than in other years. The paper contributes to prior research by providing evidence about the usefulness of international accounting data and about the adoption effects of a change to such accounting principles.

Accounting for baseline differences and measurement error in the analysis of change over time

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy.

Debate over Fair Value Accounting: Should we allow Politics to take an active role in setting accounting standards or should we trust that the SEC knows best?

In light of the recent economic downfall, there has been significant media coverage on the topic of fair value accounting. There are many critics of the accounting rule, who place blame on it for the destruction of billions of dollars in capital between financial institutions. Other commentators, however, see the rule as necessary and applaud its ability to bring the turmoil in the economy into the spotlight promptly so that it could be addressed effectively. This paper will begin by conducting a study of fair-value accounting from its inception in previous standards and then follow it through to Statement No. 157. I will then discuss the SEC’s most recent study of FAS157 and their decision as a result of the study.

Electricity price forecasting accounting for renewable energies: optimal combined forecasts

Electricity price forecasting is an interesting problem for all the agents involved in electricity market operation. For instance, every profit maximisation strategy is based on the computation of accurate one-day-ahead forecasts, which is why electricity price forecasting has been a growing field of research in recent years. In addition, the increasing concern about environmental issues has led to a high penetration of renewable energies, particularly wind. In some European countries such as Spain, Germany and Denmark, renewable energy is having a deep impact on the local power markets. In this paper, we propose an optimal model from the perspective of forecasting accuracy, and it consists of a combination of several univariate and multivariate time series methods that account for the amount of energy produced with clean energies, particularly wind and hydro, which are the most relevant renewable energy sources in the Iberian Market. This market is used to illustrate the proposed methodology, as it is one of those markets in which wind power production is more relevant in terms of its percentage of the total demand, but of course our method can be applied to any other liberalised power market. As far as our contribution is concerned, first, the methodology proposed by García-Martos et al(2007 and 2012) is generalised twofold: we allow the incorporation of wind power production and hydro reservoirs, and we do not impose the restriction of using the same model for 24h. A computational experiment and a Design of Experiments (DOE) are performed for this purpose. Then, for those hours in which there are two or more models without statistically significant differences in terms of their forecasting accuracy, a combination of forecasts is proposed by weighting the best models(according to the DOE) and minimising the Mean Absolute Percentage Error (MAPE). The MAPE is the most popular accuracy metric for comparing electricity price forecasting models. We construct the combi nation of forecasts by solving several nonlinear optimisation problems that allow computation of the optimal weights for building the combination of forecasts. The results are obtained by a large computational experiment that entails calculating out-of-sample forecasts for every hour in every day in the period from January 2007 to Decem ber 2009. In addition, to reinforce the value of our methodology, we compare our results with those that appear in recent published works in the field. This comparison shows the superiority of our methodology in terms of forecasting accuracy.