Investors face a difficult challenge in determining whether news they read is true or fake and, according to psychology theory, an additional challenge of ceasing to rely on news subsequently revealed to be fake. To help address this latter challenge, we examine whether prompting investors to be in a deliberative mindset reduces their reliance on news after they learn that it is fake without affecting their reliance on news later revealed to be true. Consistent with theory, investors adjust their valuation assessments when news is later revealed to be fake, and this adjustment is magnified for investors in a deliberative mindset. Importantly, our results reveal that a deliberative mindset does not cause investors to discount news later revealed to be true. Data Availability: Please contact the authors. JEL Classifications: M41; G11; G4; C91; D83.
{"title":"The Value of Investors Being in a Deliberative Mindset When Reading News Later Revealed to Be Fake","authors":"Stephanie M. Grant, F. Hodge, Samantha C. Seto","doi":"10.2308/jfr-2022-016","DOIUrl":"https://doi.org/10.2308/jfr-2022-016","url":null,"abstract":"\u0000 Investors face a difficult challenge in determining whether news they read is true or fake and, according to psychology theory, an additional challenge of ceasing to rely on news subsequently revealed to be fake. To help address this latter challenge, we examine whether prompting investors to be in a deliberative mindset reduces their reliance on news after they learn that it is fake without affecting their reliance on news later revealed to be true. Consistent with theory, investors adjust their valuation assessments when news is later revealed to be fake, and this adjustment is magnified for investors in a deliberative mindset. Importantly, our results reveal that a deliberative mindset does not cause investors to discount news later revealed to be true.\u0000 Data Availability: Please contact the authors.\u0000 JEL Classifications: M41; G11; G4; C91; D83.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139018641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ABSTRACT Structural equation modeling (SEM), an empirical methodology underutilized in archival research, enables researchers to examine paths linking constructs. SEM consists of two components: a measurement model that generates common factors from observed variables and a path model that links the factors. We discuss SEM’s components, estimation, advantages, best practices, and limitations. We illustrate SEM with an application to disclosure research. Unlike some prior research, we find voluntary disclosure quality is negatively associated with cost of capital, both directly and indirectly through information asymmetry, even after controlling for earnings quality’s direct and indirect associations with cost of capital. We believe SEM offers fruitful avenues for future research because it allows flexibility in modeling relations guided by theory, enables tests of underlying theoretical mechanisms, provides tools to address measurement error and missing data, and estimates simultaneous equations. SEM may be useful in settings that currently use path analysis or principal component analysis. Data Availability: Data used in this study are available from public sources identified in the paper. JEL Classifications: M41; C30.
{"title":"Structural Equation Modeling in Archival Capital Markets Research: An Empirical Application to Disclosure and Cost of Capital","authors":"Lisa A. Hinson, Steven Utke","doi":"10.2308/jfr-2019-0021","DOIUrl":"https://doi.org/10.2308/jfr-2019-0021","url":null,"abstract":"ABSTRACT Structural equation modeling (SEM), an empirical methodology underutilized in archival research, enables researchers to examine paths linking constructs. SEM consists of two components: a measurement model that generates common factors from observed variables and a path model that links the factors. We discuss SEM’s components, estimation, advantages, best practices, and limitations. We illustrate SEM with an application to disclosure research. Unlike some prior research, we find voluntary disclosure quality is negatively associated with cost of capital, both directly and indirectly through information asymmetry, even after controlling for earnings quality’s direct and indirect associations with cost of capital. We believe SEM offers fruitful avenues for future research because it allows flexibility in modeling relations guided by theory, enables tests of underlying theoretical mechanisms, provides tools to address measurement error and missing data, and estimates simultaneous equations. SEM may be useful in settings that currently use path analysis or principal component analysis. Data Availability: Data used in this study are available from public sources identified in the paper. JEL Classifications: M41; C30.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136062613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Covers and Front Matter","authors":"","doi":"10.2308/2380-2154-8-2.i","DOIUrl":"https://doi.org/10.2308/2380-2154-8-2.i","url":null,"abstract":"","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135455261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paul W. Black, Kevin E. Jackson, Stephen P. Rowe, Aaron F. Zimbelman
Technology makes it possible for management to personalize communication with individual investors on a broad scale. Building on information processing research, we predict and find that personalized communication prompts investors to process financial information more systematically and rely less on summary measures, such as earnings. Investors receiving more (as opposed to less) personalized communication respond less to management’s myopic decisions that boost short-term performance in their assessments of investment attractiveness, such that they assess a company that increases R&D (at the expense of net income) as more attractive and a company that decreases R&D as less attractive. Further analysis suggests this result is driven by investors with greater experience evaluating financial statements processing the longer-term implications of R&D expenditures for performance more fully when personalization is present. Our paper speaks to investor earnings fixation and myopic behavior from management and provides insights for implementing investor communication strategies. JEL Classifications: O33; O31; L14; M41; D12; D83.
{"title":"The Effect of Personalized Communication on Investor Earnings Fixation","authors":"Paul W. Black, Kevin E. Jackson, Stephen P. Rowe, Aaron F. Zimbelman","doi":"10.2308/jfr-2022-017","DOIUrl":"https://doi.org/10.2308/jfr-2022-017","url":null,"abstract":"Technology makes it possible for management to personalize communication with individual investors on a broad scale. Building on information processing research, we predict and find that personalized communication prompts investors to process financial information more systematically and rely less on summary measures, such as earnings. Investors receiving more (as opposed to less) personalized communication respond less to management’s myopic decisions that boost short-term performance in their assessments of investment attractiveness, such that they assess a company that increases R&D (at the expense of net income) as more attractive and a company that decreases R&D as less attractive. Further analysis suggests this result is driven by investors with greater experience evaluating financial statements processing the longer-term implications of R&D expenditures for performance more fully when personalization is present. Our paper speaks to investor earnings fixation and myopic behavior from management and provides insights for implementing investor communication strategies. JEL Classifications: O33; O31; L14; M41; D12; D83.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139297668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ABSTRACT To provide a fuller picture of compliance with ASC 350-20, we hand-collect data to track 893 large acquisitions across time. Our model, which links impairments to post-acquisition accounting and market performance declines as well as acquisition-year attributes, identifies 349 acquisitions as likely to impair. We provide evidence that 65 percent of these at-risk acquisitions impair in the next two years. Our study should be useful to future research as it clarifies the role of hand-collection, market to book ratios, segment-level data, and volatility. We also offer descriptive evidence on impairment patterns. Overall, we find high levels of compliance and little opportunism.
{"title":"Goodwill Impairment after M&A: Acquisition-Level Evidence","authors":"James Potepa, Jacob Thomas","doi":"10.2308/jfr-2020-026","DOIUrl":"https://doi.org/10.2308/jfr-2020-026","url":null,"abstract":"ABSTRACT To provide a fuller picture of compliance with ASC 350-20, we hand-collect data to track 893 large acquisitions across time. Our model, which links impairments to post-acquisition accounting and market performance declines as well as acquisition-year attributes, identifies 349 acquisitions as likely to impair. We provide evidence that 65 percent of these at-risk acquisitions impair in the next two years. Our study should be useful to future research as it clarifies the role of hand-collection, market to book ratios, segment-level data, and volatility. We also offer descriptive evidence on impairment patterns. Overall, we find high levels of compliance and little opportunism.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136169047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ABSTRACT As the awareness of environmental, social, and governance (ESG) issues increases, many data vendors have emerged to meet society’s demand for ESG information. Among many roles that CDP plays, an important one is to serve as an information intermediary facilitating the communication between companies and their stakeholders. This study discusses the practices at CDP intended to enhance firm disclosure of ESG information by focusing on its disclosure request policy. It raises the concern that such practice might constitute selective disclosures of material information, thereby violating Regulation Fair Disclosure. JEL Classifications: M14; M41; M48.
{"title":"Do CDP’s Disclosure Requests Constitute Selective Disclosures?","authors":"Xiumin Martin","doi":"10.2308/jfr-2023-023","DOIUrl":"https://doi.org/10.2308/jfr-2023-023","url":null,"abstract":"ABSTRACT As the awareness of environmental, social, and governance (ESG) issues increases, many data vendors have emerged to meet society’s demand for ESG information. Among many roles that CDP plays, an important one is to serve as an information intermediary facilitating the communication between companies and their stakeholders. This study discusses the practices at CDP intended to enhance firm disclosure of ESG information by focusing on its disclosure request policy. It raises the concern that such practice might constitute selective disclosures of material information, thereby violating Regulation Fair Disclosure. JEL Classifications: M14; M41; M48.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136127506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ABSTRACT Motivated by research from the late 1990s and early 2000s, researchers often examine analyst performance as a function of individual analyst characteristics using variables representing analysts’ experience, busyness, and resources. Studies make different choices for variable construction and fixed effects, sometimes with varying results, suggesting there is no standard approach to evaluating the effect of analyst characteristics. We reproduce analyses from two early studies (Clement (1999) and Clement and Tse (2003)) and extend these analyses to a more recent sample period and across different methodological approaches and alternative analyst performance measures. We provide robust evidence that analyst experience is positively associated with earnings forecast accuracy but that associations for analyst resources and busyness are sensitive to variable measurement and fixed effect choices. Our results can inform accounting and finance scholars examining analyst performance as they consider which analyst characteristics to include and how to test the robustness of their findings.
受20世纪90年代末和21世纪初研究的启发，研究人员经常使用代表分析师经验、忙碌程度和资源的变量来检验分析师绩效作为分析师个人特征的函数。研究对变量结构和固定效应做出了不同的选择，有时结果也不尽相同，这表明没有标准的方法来评估分析师特征的影响。我们重现了两个早期研究(Clement(1999)和Clement and Tse(2003))的分析，并将这些分析扩展到最近的样本时期，跨越不同的方法方法和替代的分析师绩效衡量标准。我们提供了强有力的证据，表明分析师经验与盈利预测准确性呈正相关，但分析师资源和忙碌程度的关联对变量测量和固定效应选择敏感。我们的结果可以告知会计和金融学者检查分析师的表现，因为他们考虑哪些分析师特征包括，以及如何测试他们的发现的稳健性。
{"title":"How Do Individual Analyst Characteristics Affect Analyst Performance?","authors":"Brian Bratten, Stephannie Larocque","doi":"10.2308/jfr-2020-024","DOIUrl":"https://doi.org/10.2308/jfr-2020-024","url":null,"abstract":"ABSTRACT Motivated by research from the late 1990s and early 2000s, researchers often examine analyst performance as a function of individual analyst characteristics using variables representing analysts’ experience, busyness, and resources. Studies make different choices for variable construction and fixed effects, sometimes with varying results, suggesting there is no standard approach to evaluating the effect of analyst characteristics. We reproduce analyses from two early studies (Clement (1999) and Clement and Tse (2003)) and extend these analyses to a more recent sample period and across different methodological approaches and alternative analyst performance measures. We provide robust evidence that analyst experience is positively associated with earnings forecast accuracy but that associations for analyst resources and busyness are sensitive to variable measurement and fixed effect choices. Our results can inform accounting and finance scholars examining analyst performance as they consider which analyst characteristics to include and how to test the robustness of their findings.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135248639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maria Nykyforovych Borysoff, Paul J. Mason, Steven Utke
Private equity (PE) funds are increasingly important to the economy and now serve as the primary vehicle for raising new capital. However, a limited understanding of the unique PE fund setting among accounting academics inhibits accounting research in this area. In this paper, we first describe the PE fund setting and explain how fundamental differences between PE and previously studied settings make it difficult to infer PE fund behavior from research performed using other settings. We then discuss how PE funds provide researchers with the ability to explore fundamental questions related to agency costs, governance, compensation, disclosure, and fair value accounting. Finally, we provide guidance on PE data sources available for use in future research. Because of the volume of economic activity currently funneled through PE and the unique aspects of the PE setting, it is important for researchers to explore when, why, and how accounting matters for PE funds. Data Availability: Data used in this study are available from the public sources identified in the text. JEL Classifications: G1; G14; G30; M4; M41.
{"title":"Understanding Private Equity Funds: A Guide to Private Equity Research in Accounting","authors":"Maria Nykyforovych Borysoff, Paul J. Mason, Steven Utke","doi":"10.2308/jfr-2022-012","DOIUrl":"https://doi.org/10.2308/jfr-2022-012","url":null,"abstract":"\u0000 Private equity (PE) funds are increasingly important to the economy and now serve as the primary vehicle for raising new capital. However, a limited understanding of the unique PE fund setting among accounting academics inhibits accounting research in this area. In this paper, we first describe the PE fund setting and explain how fundamental differences between PE and previously studied settings make it difficult to infer PE fund behavior from research performed using other settings. We then discuss how PE funds provide researchers with the ability to explore fundamental questions related to agency costs, governance, compensation, disclosure, and fair value accounting. Finally, we provide guidance on PE data sources available for use in future research. Because of the volume of economic activity currently funneled through PE and the unique aspects of the PE setting, it is important for researchers to explore when, why, and how accounting matters for PE funds.\u0000 Data Availability: Data used in this study are available from the public sources identified in the text.\u0000 JEL Classifications: G1; G14; G30; M4; M41.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72712159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bayesian statistics is a framework for combining new data with existing forms of information to yield more precise inferences than are possible using the data alone. Its greatest practical advantages are the flexibility it offers in incorporating prior information and beliefs, modeling heterogeneity, modeling latent constructs, and combining multiple data sources. There are two goals of this paper: to introduce accounting researchers to Bayesian inference and distinguish it from classical frequentist inference and to showcase when Bayesian modeling can improve inferences in many applications that are of interest to accounting researchers. Data Availability: Data are available from the public sources described in the text. JEL Classifications: C11; C53; G17; M40.
{"title":"What Can Bayesian Inference Do for Accounting Research?","authors":"H. Schütt","doi":"10.2308/jfr-2021-002","DOIUrl":"https://doi.org/10.2308/jfr-2021-002","url":null,"abstract":"\u0000 Bayesian statistics is a framework for combining new data with existing forms of information to yield more precise inferences than are possible using the data alone. Its greatest practical advantages are the flexibility it offers in incorporating prior information and beliefs, modeling heterogeneity, modeling latent constructs, and combining multiple data sources. There are two goals of this paper: to introduce accounting researchers to Bayesian inference and distinguish it from classical frequentist inference and to showcase when Bayesian modeling can improve inferences in many applications that are of interest to accounting researchers.\u0000 Data Availability: Data are available from the public sources described in the text.\u0000 JEL Classifications: C11; C53; G17; M40.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87587637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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