scholarly journals The Use of Official Statistics in Self-Selection Bias Modeling

2016 ◽  
Vol 32 (4) ◽  
pp. 887-905 ◽  
Author(s):  
Luciana Dalla Valle
Keyword(s):  
Selection Bias ◽  
Small Businesses ◽  
Real Data ◽  
Sources Of Information ◽  
Quality Of Data ◽  
Official Statistics ◽  
Step Method ◽  
Development Education ◽  
Self Selection ◽  
Available Information

Abstract Official statistics are a fundamental source of publicly available information that periodically provides a great amount of data on all major areas of citizens’ lives, such as economics, social development, education, and the environment. However, these extraordinary sources of information are often neglected, especially by business and industrial statisticians. In particular, data collected from small businesses, like small and medium-sized enterprizes (SMEs), are rarely integrated with official statistics data. In official statistics data integration, the quality of data is essential to guarantee reliable results. Considering the analysis of surveys on SMEs, one of the most common issues related to data quality is the high proportion of nonresponses that leads to self-selection bias. This work illustrates a flexible methodology to deal with self-selection bias, based on the generalization of Heckman’s two-step method with the introduction of copulas. This approach allows us to assume different distributions for the marginals and to express various dependence structures. The methodology is illustrated through a real data application, where the parameters are estimated according to the Bayesian approach and official statistics data are incorporated into the model via informative priors.

Additional Evidence on Audit Report Lag

2001 ◽  
Vol 20 (1) ◽  
pp. 137-146 ◽  
Author(s):  
W. Robert Knechel ◽  
Jeff L. Payne
Keyword(s):  
Earnings Quality ◽  
Financial Statements ◽  
Financial Statement ◽  
Fiscal Year ◽  
Sources Of Information ◽  
Audit Report ◽  
The Public ◽  
Time Period ◽  
Audit Team ◽  
Available Information

The process for providing accounting information to the public has not changed much in the last century even though the extent of disclosure has increased signifi-cantly. Sundem et al. (1996) suggest that the primary benefit of audited financial statements may not be decision usefulness but the discipline imposed by timely confirmation of previously available information. In general, the value of information from the audited financial statement will decline as the audit report lag (the time period between a company's fiscal year end and the date of the audit report) increases since competitively oriented users may obtain substitute sources of information. Furthermore, the literature on earnings quality and earnings management suggests that unexpected reporting delays may be associated with lower quality information. The purpose of this paper is to extend our understanding about the determinants of audit report lag using a proprietary database containing 226 audit engagements from an international public accounting firm. We examine three previously uninvestigated audit firm factors that potentially influence audit report lag and are controllable by the auditor: (1) incremental audit effort (e.g., hours), (2) the resource allocation of audit team effort measured by rank (partner, manager, or staff), and (3) the provision of nonaudit services (MAS and tax). The results indicate that incremental audit effort, the presence of contentious tax issues, and the use of less experienced audit staff are positively correlated with audit report lag. Further, audit report lag is decreased by the potential synergistic relationship between MAS and audit services.

scholarly journals Benchmarking Unsupervised Outlier Detection with Realistic Synthetic Data

2021 ◽  
Vol 15 (4) ◽  
pp. 1-20
Author(s):  
Georg Steinbuss ◽  
Klemens Böhm
Keyword(s):  
Outlier Detection ◽  
Synthetic Data ◽  
Real Data ◽  
Detection Methods ◽  
Quality Of Data ◽  
Benchmark Data ◽  
Core Idea ◽  
Generic Process ◽  
Unsupervised Outlier Detection

Benchmarking unsupervised outlier detection is difficult. Outliers are rare, and existing benchmark data contains outliers with various and unknown characteristics. Fully synthetic data usually consists of outliers and regular instances with clear characteristics and thus allows for a more meaningful evaluation of detection methods in principle. Nonetheless, there have only been few attempts to include synthetic data in benchmarks for outlier detection. This might be due to the imprecise notion of outliers or to the difficulty to arrive at a good coverage of different domains with synthetic data. In this work, we propose a generic process for the generation of datasets for such benchmarking. The core idea is to reconstruct regular instances from existing real-world benchmark data while generating outliers so that they exhibit insightful characteristics. We propose and describe a generic process for the benchmarking of unsupervised outlier detection, as sketched so far. We then describe three instantiations of this generic process that generate outliers with specific characteristics, like local outliers. To validate our process, we perform a benchmark with state-of-the-art detection methods and carry out experiments to study the quality of data reconstructed in this way. Next to showcasing the workflow, this confirms the usefulness of our proposed process. In particular, our process yields regular instances close to the ones from real data. Summing up, we propose and validate a new and practical process for the benchmarking of unsupervised outlier detection.

Women on the board of directors and corporate tax aggressiveness in Australia

2016 ◽  
Vol 29 (3) ◽  
pp. 313-331 ◽  
Author(s):  
Grant Richardson ◽  
Grantley Taylor ◽  
Roman Lanis
Keyword(s):  
Board Of Directors ◽  
Selection Bias ◽  
Tax Avoidance ◽  
Multivariate Regression Analysis ◽  
Corporate Tax ◽  
Content Type ◽  
Tax Aggressiveness ◽  
Self Selection ◽  
The Board Of Directors ◽  
The Impact

Purpose This paper aims to investigate the impact of women on the board of directors on corporate tax avoidance in Australia. Design/methodology/approach The authors use multivariate regression analysis to test the association between the presence of female directors on the board and tax aggressiveness. They also test for self-selection bias in the regression model by using the two-stage Heckman procedure. Findings This paper finds that relative to there being one female board member, high (i.e. greater than one member) female presence on the board of directors reduces the likelihood of tax aggressiveness. The results are robust after controlling for self-selection bias and using several alternative measures of tax aggressiveness. Research limitations/implications This study extends the extant literature on corporate governance and tax aggressiveness. This study is subject to several caveats. First, the sample is restricted to publicly listed Australian firms. Second, this study only examines the issue of women on the board of directors and tax aggressiveness in the context of Australia. Practical implications This research is timely, as there has been increased pressure by government bodies in Australia and globally to develop policies to increase female representation on the board of directors. Originality/value This study is the first to provide empirical evidence concerning the association between the presence of women on the board of directors and tax aggressiveness.

Reviews and Self-Selection Bias with Operational Implications

2021 ◽  
Author(s):  
Ningyuan Chen ◽  
Anran Li ◽  
Kalyan Talluri
Keyword(s):  
Selection Bias ◽  
Operations Management ◽  
Choice Model ◽  
Theoretical Models ◽  
Empirical Literature ◽  
Service Firms ◽  
Performance Review ◽  
Self Selection ◽  
Ex Post ◽  
Biased Ratings

Reviews for products and services written by previous consumers have become an influential input to the purchase decision of customers. Many service businesses monitor the reviews closely for feedback as well as detecting service flaws, and they have become part of the performance review for service managers with rewards tied to improvement in the aggregate rating. Many empirical papers have documented a bias in the aggregate ratings, arising because of customers’ inherent self-selection in their choices and bounded rationality in evaluating previous reviews. Although there is a vast empirical literature analyzing reviews, theoretical models that try to isolate and explain the bias in ratings are relatively few. Assuming consumers simply substitute the average rating that they see as a proxy for quality, we give a precise characterization of the self-selection bias on ratings of an assortment of products when consumers confound ex ante innate preferences for a product or service with ex post experience and service quality and do not separate the two. We develop a parsimonious choice model for consumer purchase decisions and show that the mechanism leads to an upward bias, which is more pronounced for niche products. Based on our theoretical characterization, we study the effect on pricing and assortment decisions of the firm when potential customers purchase based on the biased ratings. Our results give insights into how quality, prices, and customer feedback are intricately tied together for service firms. This paper was accepted by David Simchi-Levi, operations management.

scholarly journals Alternative sources of data on the level of employment of Russian women in entrepreneurship

POPULATION ◽  
2019 ◽  
Vol 22 (4) ◽  
pp. 90-102
Author(s):  
Aysylu Ilimbetova
Keyword(s):  
Public Relations ◽  
Gender Equality ◽  
Small Businesses ◽  
Sources Of Information ◽  
Men And Women ◽  
Gender Differentiation ◽  
Women In Business ◽  
Structure Of Population ◽  
Alternative Sources ◽  
Social Structuring

Development of the market economy and changes in the principles of social structuring of society lead to the fact that the concept of gender equality goes beyond the labor market and begins to spread to other spheres of public relations, for example, entrepreneurship. However, to obtain empirical data to understand the extent of participation of men and women in business, it is not sufficient to conduct surveys or censuses, because they do not specialize in such information and provide data only on forms of employment (for hire and not for hire). The article deals with the possibilities of using administrative sources of information (the Unified register of small and medium-sized businesses) and the SPARK information base to obtain gender statistics and assess gender equality on the example of women's entrepreneurship in Russia. The main advantage of these sources of information is the possibility of extracting data on the activities of Russian entrepreneurs, for which information is not provided by the statistical collections of Rosstat. Calculations of the author make it possible to establish existence in the Russian business of gender differentiation in entrepreneurship, formation of employment niches assigned to each sex that allows us to speak about the specific features of the Russian business. Thus, women are concentrated in micro- and small businesses; they are mainly engaged in the socially important services—health care and education, other individual services; they are prone to less risky and less innovative spheres, such as trade and services; there are similarities between the structure of entrepreneurship, employment as employees and the professional structure of population.

Sign in / Sign up

Export Citation Format

Share Document