Financial Microeconometrics as Research Methodology in Corporate Finance and Accounting

Gruszczyński, Marek

doi:10.1007/978-3-319-68285-3_6

Cited by 7 publications

(7 citation statements)

References 7 publications

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“…What remains as a major research possibility in examining gender edge vis-à-vis corporate categories is the application of a statistical-econometric methodology. Such research attempts typically use microdata on large numbers of companies and may be placed under the label of "financial microeconometrics" (Gruszczyński 2020).…”

Section: Women On Boards and Financial Results-theoretical Underpinnimentioning

confidence: 99%

“…From the plethora of studies on the topic, we choose a few, one of which specifically represents the "new microeconometrics" methodology. All belong methodologically to financial microeconometrics (Gruszczyński 2020). Ionascu et al (2018) examine Romanian companies listed on the Bucharest Stock Exchange 2012-2016 (343 firm-year observations).…”

Section: Selected Empirical Studiesmentioning

confidence: 99%

“…Specific theories have proved to be unstable over time and space-as shown by empirics-and there is, perhaps, no need to strive for a unified theory of corporate finance. Instead, there is a growing demand for more "operational" results based on statistical data on companies (Gruszczyński 2020). This paper contemplates an area that is in the developmental phase, apparently without solid theory, and, perhaps, that is an advantage.…”

Section: Introduction: Corporate Boards Vis-à-vis Gender Diversitymentioning

confidence: 98%

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Women on Boards and Firm Performance: A Microeconometric Search for a Connection

Gruszczyński

2020

JRFM

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This paper discusses questions of the gender diversity of corporate boards vis-à-vis firm performance. Typically, researchers have asked if a female presence is associated with improved performance and more transparent governance. The paper’s first part reports on several econometric attempts in the quest to prove the existence of such an association. The primary outcome is that the results vary over geographical, cultural, and time settings. The study presented in the second part examines European firms’ annual reports from 2015. Binomial models, multiple regression, and quantile regression are applied resulting in the finding that female presence on a board is not significantly related to firm performance for this sample. Together with the picture that emerged from the paper’s first part, this result leads to the possibility that the search for an association between women on boards and company performance is not fundamental. Nevertheless, modern business societies worldwide may need to boost the female presence on managerial bodies. Current econometric evidence indicates that this is not harmful to corporate results.

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Section: Women On Boards and Financial Results-theoretical Underpinnimentioning

confidence: 99%

Section: Selected Empirical Studiesmentioning

confidence: 99%

Section: Introduction: Corporate Boards Vis-à-vis Gender Diversitymentioning

confidence: 98%

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Women on Boards and Firm Performance: A Microeconometric Search for a Connection

Gruszczyński

2020

JRFM

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“…and more recently, to advanced data analysis. Financial microeconometrics "emerges as a natural consequence of applying statistical and econometric methods to corporate finance, accounting, and other fields of finance; the applied edge of research in accounting and corporate finance is inevitably linked with the use of notions such as statistical sample, population, and the operation on sets of microdata" (Gruszczyński 2018).…”

Section: Bankruptcy Prediction Models and Unbalanced Samplesmentioning

confidence: 99%

On Unbalanced Sampling in Bankruptcy Prediction

Gruszczyński

2019

IJFS

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The paper discusses methodological topics of bankruptcy prediction modelling-unbalanced sampling, sample bias, and unbiased predictions of bankruptcy. Bankruptcy models are typically estimated with the use of non-random samples, which creates sample choice biases. We consider two types of unbalanced samples: (a) when bankrupt and non-bankrupt companies enter the sample in unequal numbers; and (b) when sample composition allows for different ratios of bankrupt and non-bankrupt companies than those in the population. An imbalance of type (b), being more general, is examined in several sections of the paper. We offer an extended view of the relationship between the biased and unbiased estimated probabilities of bankruptcy-probability of default (PD). A common error in applications is neglecting the possibility of calibrating the PD obtained from a bankruptcy model to the unbiased PD that is population adjusted. We show that Skogsviks' formula of 2013 coincides with prior correction known for the logit model. This, together with solutions for other binomial models, serves as practical advice for obtaining the calibration of unbiased PDs from popular bankruptcy models. In the final section, we explore sample bias effects on classification. Zhou, Ligang. 2013. Performance of corporate bankruptcy prediction models on imbalanced data set: The effect of sampling methods. Knowledge-Based Systems 41: 16-25.[CrossRef] Zmijewski, Mark E. 1984. Methodological issues related to the estimation of financial distress prediction models.

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“…The methodology is mainly rooted in microeconomerics. If applied to research problems in corporate finance and accounting it is known as financial microeconometrics (for further discussion see Gruszczyński 2012Gruszczyński , 2018a.…”

Section: Introductionmentioning

confidence: 99%

Good Practices in Empirical Corporate Finance and Accounting Research

Gruszczyński¹

2018

JBFE

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This paper presents the risks of quantitative research pertaining to corporate finance and accounting. These is followed by a survey-like catalogue of good practices in modelling. All considerations are rooted in financial microeconometrics, the field for examining both practical and theoretical questions of applying econometric techniques in corporate finance and accounting research based on the use of microdata (Gruszczyński 2018a). Two major parts of the paper include: (1) discussion of the typical drawbacks in applying regression-type models, like causality vs. correlation, selection of explanatory variables and endogeneity, and (2) list of good practices in microeconometric applications to corporate finance and accounting research, based on Faff (2017), Kennedy (2002), Adams (2017), Hyndman (robjhyndman.com/) and author's own experience. Catalogue of good practices in microeconometric applications to corporate finance and accounting may serve as the checklist for students and researchers.

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Financial Microeconometrics as Research Methodology in Corporate Finance and Accounting

Cited by 7 publications

References 7 publications

Women on Boards and Firm Performance: A Microeconometric Search for a Connection

Women on Boards and Firm Performance: A Microeconometric Search for a Connection

On Unbalanced Sampling in Bankruptcy Prediction

Good Practices in Empirical Corporate Finance and Accounting Research

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