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Financial manipulation means the modification made knowingly and willfully by businesses in accounting records and transactions, in financial statements, through addition and subtraction, for the purpose of misleading financial information users. Financial manipulations are expected to have an effect on the decisions of financial information users. The present study was established on the basis of two main objectives. The first objective is to determine whether banks, which are Public Interest Entities (PIE), manipulate their financial statements. As for the second objective, it is to reveal whether the detected financial manipulations have an effect on investor decisions. The research conducted to achieve the first objective is based on the examination of independent audit reports for the periods between 2009 and 2017, pertaining to 45 banks registered to the Banks Association of Turkey, in terms of presented opinions. Data acquired from examined reports were subjected to content analysis via the Microsoft Excel program. In line with the second objective of the study, investor numbers for the periods between 2010 and 2017, of 13 banks, which are within the scope of BIST BANK, were included in the analysis, according to data acquired from the Central Registry Agency. Financial statements of banks, with audit reports in which a qualified opinion is expressed, were considered to have been manipulated. SPSS 22.0 statistics pack software was used to analyze whether investment demands toward these banks had an effect on decisions of domestic and foreign investors. In the analysis, frequency and One-Way ANOVA tests were used. In consequence of the analyses conducted, it was determined that, around one fifth of financial statements of PIE banks, pertaining to the periods between 2009 and 2017, were manipulated; it was mostly committed by private banks, and majority of the manipulations were committed due to free provisions made. It was also observed that manipulations did not have an effect on decisions of neither domestic nor foreign investors. The reason behind the latter is the fact that while the level of manipulations in financial statements is significant, it is not a widespread occurrence.

Conventional tests of the regression discontinuity design’s identifying restrictions can perform poorly when the running variable is discrete. This paper proposes a test for manipulation of the running variable that is consistent when the running variable is discrete. The test exploits the fact that if the discrete running variable’s probability mass function satisfies a certain smoothness condition, then the observed frequency at the threshold has a known conditional distribution. The proposed test is applied to vote tally distributions in union representation elections and reveals evidence of manipulation in close elections that is in favor of employers when Republicans control the NLRB and in favor of unions otherwise.

The purpose of the financial statements is to present the situations of the enterprises, such as the financial situation, results of operations, etc., in the decision-making processes to the related parties in a suitable, comparable, and realistic manner. In recent years, professional frauds in enterprises have been seriously reflected in financial statements and this has resulted in the manipulation of financial information.

In this study, we aim to determine financial firms, which might manipulate the financial information, by applying the Beneish model and then determine the financial indicators of possible financial statement manipulation, using logistic regression. For this purpose, companies included constantly in Borsa İstanbul-50 (BIST-50) 2015, 2016, and 2017 were examined. After the enterprises which have the possibility of financial manipulation are determined by the Beneish model, it is understood that there is a positive relationship between the probability of manipulating financial information and the Asset Quality Index and Sales, general and administrative expenses index.

This paper introduces a method by which researchers can assess the strength of their status manipulations in experimental research by comparing them against Monte Carlo simulated distributions that use aggregate Status Characteristics Theory (SCT) data.

This paper uses Monte Carlo methods to simulate the m and q parameter distributions and the proportion of stay (P(s)) score distributions for four commonly used status situations. It also presents findings from an experiment that highlight the processes by which researchers can utilize these simulated distributions in their assessment of novel status manipulations.

Findings indicate that implicitly relevant status manipulations have considerably more overlapping P(s) scores in the simulated distributions of high and low states of a status characteristic than explicitly relevant status manipulations. Findings also show that a novel status manipulation, the handedness manipulation, sufficiently creates high- and low-status differences in P(s) scores.

Future researchers can use these simulated distributions to plot the mean P(s) scores of each of their experimental conditions on the overlapping distribution for the corresponding status manipulation. Manipulations that produce scores that fall outside of the range of overlapping values are also likely to create status differences between conditions in other settings or populations.