Measuring the effectiveness of bankruptcy institutions: filtering failures in Slovenian financial reorganizations

2019 ◽  
Vol 15 (3) ◽  
pp. 553-567 ◽  
Author(s):  
Jaka Cepec ◽  
Peter Grajzl
Keyword(s):  
Type I ◽  
Type Ii ◽  
Efficient Allocation ◽  
Allocation Of Resources ◽  
Type I Errors ◽  
Ex Post ◽  
Ex Ante ◽  
Different Types ◽  
Type Ii Errors ◽  
Institutional Feature

AbstractWe examine the effectiveness of bankruptcy institutions at promoting socially efficient allocation of resources. Under the Slovenian simplified reorganization procedure, firms with rejected reorganization proposals are not automatically liquidated. This unique institutional feature facilitates an estimation of the extent of different types of filtering failures. Based on an ex-post conceptualization of firm viability, Type I errors (the acceptance of plans by non-viable firms) are more likely than Type II errors (the rejection of plans by viable firms) and the overall incidence of filtering failure is 27%. Based on an ex-ante conceptualization of firm viability, any given reduction in Type II errors would give rise to three times as many Type I errors. We contextualize our findings in the light of prior results in the literature, alternative mechanisms for insolvency resolution, and related bankruptcy reorganization schemes internationally where courts are awarded a comparatively more prominent role.

Rules Rather than Discretion in Audit Standards: Going-Concern Opinions in Belgium

2009 ◽  
Vol 84 (5) ◽  
pp. 1395-1428 ◽  
Author(s):  
Joseph V. Carcello ◽  
Ann Vanstraelen ◽  
Michael Willenborg
Keyword(s):  
Board Of Directors ◽  
Type I ◽  
Type Ii ◽  
Type I Errors ◽  
Going Concern ◽  
Major Revision ◽  
Ex Post ◽  
Type Ii Errors ◽  
Audit Standards ◽  
Ex Post Analysis

ABSTRACT: We study going-concern (GC) reporting in Belgium to examine the effects associated with a shift toward rules-based audit standards. Beginning in 2000, a major revision in Belgian GC audit standards took effect. Among its changes, auditors must ascertain whether their clients are in compliance with two “financial-juridical criteria” for board of directors' GC disclosures. In a study of a sample of private Belgian companies, we report two major findings. First, there is a decrease in auditor Type II errors, particularly by non-Big 6/5 auditors for their clients that fail both criteria. Second, there is an increase in Type I errors, again particularly for companies that fail both criteria. We also conduct an ex post analysis of the decrease in Type II errors and the increase in Type I errors. Our findings suggest the standard engenders both favorable and unfavorable effects, the net of which depends on the priorities assigned to the affected parties (creditors, auditors, companies, and employees).

scholarly journals Statistical Methods for Banking Sectors to Detect the Eligible Customers for Home Loan

2019 ◽  
Vol 8 (4) ◽  
pp. 1849-1853
Keyword(s):  
Sensitivity Analysis ◽  
Statistical Methods ◽  
Sensitivity And Specificity ◽  
Categorical Variables ◽  
Type I ◽  
Type Ii ◽  
Type I Errors ◽  
Fuzzy Analysis ◽  
Type Ii Errors

Nowadays people are interested to avail loans in banks for their needs, but providing loans to all people is not possible to banks, so they are using some measures to identify eligible customers. To measure the performance of categorical variables sensitivity and specificity are widely used in Medical and tangentially in econometrics, after using some measures also if banks provide the loans to the wrong customers whom might not able to repay the loans, and not providing to customers who can repay will lead to the type I errors and type II errors, to minimize these errors, this study explains one, how to know sensitivity is large or small and second to study the bench marks on forecasting the model by Fuzzy analysis based on fuzzy based weights and it is compared with the sensitivity analysis.

scholarly journals Tropical Cyclones and Climate Change Assessment: Part I: Detection and Attribution

2019 ◽  
Vol 100 (10) ◽  
pp. 1987-2007 ◽  
Author(s):  
Thomas Knutson ◽  
Suzana J. Camargo ◽  
Johnny C. L. Chan ◽  
Kerry Emanuel ◽  
Chang-Hoi Ho ◽  
...  
Keyword(s):  
Climate Change ◽  
Historical Data ◽  
False Alarms ◽  
Type I ◽  
Anthropogenic Influence ◽  
Type Ii ◽  
Type I Errors ◽  
Detection And Attribution ◽  
Climate Change Assessment ◽  
Type Ii Errors

AbstractAn assessment was made of whether detectable changes in tropical cyclone (TC) activity are identifiable in observations and whether any changes can be attributed to anthropogenic climate change. Overall, historical data suggest detectable TC activity changes in some regions associated with TC track changes, while data quality and quantity issues create greater challenges for analyses based on TC intensity and frequency. A number of specific published conclusions (case studies) about possible detectable anthropogenic influence on TCs were assessed using the conventional approach of preferentially avoiding type I errors (i.e., overstating anthropogenic influence or detection). We conclude there is at least low to medium confidence that the observed poleward migration of the latitude of maximum intensity in the western North Pacific is detectable, or highly unusual compared to expected natural variability. Opinion on the author team was divided on whether any observed TC changes demonstrate discernible anthropogenic influence, or whether any other observed changes represent detectable changes. The issue was then reframed by assessing evidence for detectable anthropogenic influence while seeking to reduce the chance of type II errors (i.e., missing or understating anthropogenic influence or detection). For this purpose, we used a much weaker “balance of evidence” criterion for assessment. This leads to a number of more speculative TC detection and/or attribution statements, which we recognize have substantial potential for being false alarms (i.e., overstating anthropogenic influence or detection) but which may be useful for risk assessment. Several examples of these alternative statements, derived using this approach, are presented in the report.

Comparing the Variances of Two Dependent Groups

1990 ◽  
Vol 15 (3) ◽  
pp. 237-247 ◽  
Author(s):  
Rand R. Wilcox
Keyword(s):  
Maximum Likelihood ◽  
Low Power ◽  
Maximum Likelihood Estimate ◽  
Type I ◽  
Type Ii ◽  
Type I Errors ◽  
Satisfactory Solution ◽  
Scheffe Test ◽  
Modified Maximum Likelihood ◽  
Type Ii Errors

Let X and Y be dependent random variables with variances σ2x and σ2y. Recently, McCulloch (1987) suggested a modification of the Morgan-Pitman test of Ho: σ2x=σ2y But, as this paper describes, there are situations where McCulloch’s procedure is not robust. A subsample approach, similar to the Box-Scheffe test, is also considered and found to give conservative results, in terms of Type I errors, for all situations considered, but it yields relatively low power. New results on the Sandvik-Olsson procedure are also described, but the procedure is found to be nonrobust in situations not previously considered, and its power can be low relative to the two other techniques considered here. A modification of the Morgan-Pitman test based on the modified maximum likelihood estimate of a correlation is also considered. This last procedure appears to be robust in situations where the Sandvik-Olsson (1982) and McCulloch procedures are robust, and it can have more power than the Sandvik-Olsson. But it too gives unsatisfactory results in certain situations. Thus, in terms of power, McCulloch’s procedure is found to be best, with the advantage of being simple to use. But, it is concluded that, in terms of controlling both Type I and Type II errors, a satisfactory solution does not yet exist.

A Note on Nonindependence and Nonparametric Tests

1993 ◽  
Vol 76 (2) ◽  
pp. 407-412 ◽  
Author(s):  
Donald W. Zimmerman
Keyword(s):  
Random Sampling ◽  
Nonparametric Tests ◽  
Wilcoxon Test ◽  
Type I ◽  
Type Ii ◽  
Random Assignment ◽  
Reverse Effect ◽  
Significance Tests ◽  
Type I Errors ◽  
Type Ii Errors

This study investigated violations of random sampling and random assignment in data analyzed by nonparametric significance tests. A computer program induced correlations within groups, as well as between groups, and performed one-sample and two-sample versions of the Mann-Whitney-Wilcoxon test on the resulting scores. Nonindependence of observations within groups spuriously inflated the probability of Type I errors and depressed the probability of Type II errors, and nonindependence between groups had the reverse effect. This outcome, which parallels the influence of nonindependence on parametric tests, can be explained by the equivalence of the Mann-Whitney-Wilcoxon test and the Student t test performed on ranks replacing the initial scores.

scholarly journals Computer-generated facial areas of interest in eye tracking research: A simulation study

2021 ◽  
Author(s):  
Antonia Vehlen ◽  
William Standard ◽  
Gregor Domes
Keyword(s):  
Eye Tracking ◽  
Voronoi Tessellation ◽  
Data Accuracy ◽  
Type I ◽  
Type Ii ◽  
Eye Tracker ◽  
Type I Errors ◽  
Areas Of Interest ◽  
Type Ii Errors ◽  
The Impact

Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer’s test conditions, validation is essential with regard to data quality and other factors potentially threatening data validity. In this study, we evaluated the impact of data accuracy and areas of interest (AOIs) size on the classification of simulated gaze data. We defined AOIs of different sizes using the Limited-Radius Voronoi-Tessellation (LRVT) method, and simulated gaze data for facial target points with varying data accuracy. As hypothesized, we found that data accuracy and AOI size had strong effects on gaze classification. In addition, these effects were not independent and differed for falsely classified gaze inside AOIs (Type I errors) and falsely classified gaze outside the predefined AOIs (Type II errors). The results indicate that smaller AOIs generally minimize false classifications as long as data accuracy is good enough. For studies with lower data accuracy, Type II errors can still be compensated to some extent by using larger AOIs, but at the cost of an increased probability of Type I errors. Proper estimation of data accuracy is therefore essential for making informed decisions regarding the size of AOIs.

Correction of the Student T Statistic for Nonindependence of Sample Observations

1992 ◽  
Vol 75 (3) ◽  
pp. 1011-1020 ◽  
Author(s):  
Donald W. Zimmerman ◽  
Richard H. Williams ◽  
Bruno D. Zumbo
Keyword(s):  
Unbiased Estimate ◽  
Random Variables ◽  
Type I ◽  
Type Ii ◽  
Population Variance ◽  
Type I Errors ◽  
Computer Simulation Study ◽  
The One ◽  
Type Ii Errors ◽  
Independent Identically Distributed

A computer-simulation study examined the one-sample Student t test under violation of the assumption of independent sample observations. The probability of Type I errors increased, and the probability of Type II errors decreased, spuriously elevating the entire power function. The magnitude of the change depended on the correlation between pairs of sample values as well as the number of sample values that were pairwise correlated. A modified t statistic, derived from an unbiased estimate of the population variance that assumed only exchangeable random variables instead of independent, identically distributed random variables, effectively corrected for nonindependence for all degrees of correlation and restored the probability of Type I and Type II errors to their usual values.

Managerial Ability and the Accuracy of the Going Concern Opinion

2018 ◽  
Vol 18 (1) ◽  
pp. 29-52 ◽  
Author(s):  
Nathan R. Berglund ◽  
Donald R. Herrmann ◽  
Bradley P. Lawson
Keyword(s):  
Type I ◽  
Type Ii ◽  
Managerial Ability ◽  
Type I Errors ◽  
Bankruptcy Risk ◽  
Going Concern ◽  
Information Signal ◽  
Going Concern Opinion ◽  
Prior Literature ◽  
Type Ii Errors

ABSTRACT Current audit guidance directs the auditor to modify their opinion in the presence of significant doubt about their client's ability to continue as a going concern. This paper examines whether managerial ability influences the accuracy of auditors' going concern information signal. Following prior literature, we assess accuracy based on the subsequent viability of the client. We find that, while managerial ability decreases the risk of Type I errors (the auditor issues a going concern opinion for a firm that subsequently remains viable), managerial ability increases the risk of Type II errors (the auditor issues a standard unqualified report for a firm that subsequently files for bankruptcy). Considering prior research indicates that the auditor's opinion provides important information to the market, this finding has important public interest implications regarding the signaling of bankruptcy risk to investors and creditors by auditors' going concern opinion.

Estimation of Discretionary Accruals and the Detection of Earnings Management

2015 ◽  
Author(s):  
Paul Zarowin
Keyword(s):  
Earnings Management ◽  
Discretionary Accruals ◽  
Type I ◽  
Type Ii ◽  
Type I Errors ◽  
New Model ◽  
The Past ◽  
Almost All ◽  
Type Ii Errors

This article reviews recent research on the estimation of discretionary accruals and the detection of earnings management. There has been an explosive growth in research on accrual earnings management over the past twenty years, and almost all has used the Jones (1991) model or one of its close derivatives. Nevertheless, a growing literature has addressed the model’s problems and attempted to improve its estimation of discretionary accruals. The model’s incomplete characterization of how nondiscretionary accruals are determined by the firm’s operations can cause either Type I or Type II errors. This article categorizes recent articles into four groups based on their focus and solution, and while there is no panacea for the problems and no consensus on a new model or method, research offers hope that accrual earnings management is more likely to be detected when it exists and is less likely to be erroneously detected when it is absent (i.e., lower Type II and Type I errors, respectively).

scholarly journals Removing the influence of the serial correlation on the Mann-Kendall test

2014 ◽  
Vol 29 (2) ◽  
pp. 161-170 ◽  
Author(s):  
Gabriel Constantino Blain
Keyword(s):  
Serial Correlation ◽  
Kendall Test ◽  
Temperature Data ◽  
Trend Test ◽  
Type I ◽  
Type Ii ◽  
Weather Station ◽  
Type I Errors ◽  
Serial Correlations ◽  
Type Ii Errors

The Pre-Whitening (PW), the Trend-Free Pre-Whitening (TFPW) and the Modified Trend-Free Pre-Whitening (MTFPW) were developed to remove the influence of serial correlations on the Mann-Kendall trend test. The main purpose of this study was to compare the performance of these algorithms for evaluating trends in auto-correlated series. The PW, TFPW and MTFPW were also applied to the monthly values of the rainfall (Pre), minimum (Tmin) and maximum (Tmax) air temperature data obtained from the weather station of Ribeirão Preto, State of São Paulo, Brazil. Sets of Monte Carlo simulations were carried out to evaluate the occurrence of the type I and the type II errors obtained from these three algorithms. The TFPW has the highest power. However, it also presented the highest occurrence of type I errors. The PW clearly limits the influence of serial correlation on the occurrence of type I errors. Nevertheless, this feature is accomplished at a cost of a great reduction of its ability to detect trends. The MTFPW leads to a better balance between the probabilities of both statistical errors. It was also concluded that the hypothesis of the presence of no climate change in the location of Ribeirão Pareto cannot be accepted.

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