Wei Chen

University of Connecticut - Department of Accounting

School of Business

Storrs, CT 06269-2041

United States

SCHOLARLY PAPERS

7

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Top 25,653

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4,327

TOTAL CITATIONS
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Top 7,476

in Total Papers Citations

65

Scholarly Papers (7)

Incorrect Inferences When Using Residuals as Dependent Variables

Number of pages: 83 Posted: 23 Apr 2015 Last Revised: 29 Sep 2017
Wei Chen, Paul Hribar and Sam Melessa
University of Connecticut - Department of Accounting, University of Iowa - Department of Accounting and University of Iowa - Department of Accounting
Downloads 1,771 (21,142)
Citation 26

Abstract:

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two-stage, residuals, coefficient bias, discretionary accruals, real earnings management

Incorrect Inferences When Using Residuals as Dependent Variables

Journal of Accounting Research, Vol. 56, No. 3, 2018
Posted: 15 Aug 2018
Wei Chen, Paul Hribar and Sam Melessa
University of Connecticut - Department of Accounting, University of Iowa - Department of Accounting and University of Iowa - Department of Accounting

Abstract:

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two-stage; residuals; coefficient bias; discretionary accruals; real earnings management

2.

Standard Error Biases When Using Generated Regressors in Accounting Research

Number of pages: 71 Posted: 12 Nov 2020 Last Revised: 16 Dec 2022
Wei Chen, Paul Hribar and Sam Melessa
University of Connecticut - Department of Accounting, University of Iowa - Department of Accounting and University of Iowa - Department of Accounting
Downloads 1,006 (49,587)
Citation 35

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generated regressor, standard error bias, bootstrapping, predicted values, financial reporting quality, earnings forecasts, investment, litigation risk

3.

The Effect of Conditional Accounting Conservatism on the Predictive Ability of Accruals Components with Respect to Future Cash Flows

Number of pages: 47 Posted: 26 Jun 2017 Last Revised: 05 Jan 2023
University of Connecticut - Department of Accounting, University of Iowa - Department of Accounting and University of Iowa - Department of Accounting
Downloads 587 (101,219)
Citation 2

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conditional conservatism; timely loss recognition; accruals; cash flow predictability.

4.

Estimating the Effects of Factors that Constrain Deviations from Expected or Normal Outcomes

Number of pages: 51 Posted: 10 Oct 2023
Wei Chen, Paul Hribar and Sam Melessa
University of Connecticut - Department of Accounting, University of Iowa - Department of Accounting and University of Iowa - Department of Accounting
Downloads 493 (125,955)
Citation 2

Abstract:

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residuals, absolute value, discretionary accruals, earnings management, financial reporting quality, abnormal investment, investment efficiency, quantile regression

5.

Predictive Ability and Market Pricing of Fair Value Earnings Components for Closed-End Funds

Number of pages: 50 Posted: 03 Feb 2016 Last Revised: 04 Jul 2017
Lancaster University - Department of Accounting and Finance, University of Iowa - Department of Accounting and University of Connecticut - Department of Accounting
Downloads 297 (222,528)

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realized and unrealized gains/losses, closed-end funds, market timing, disposition effect, pricing of fair value earnings components

6.

Decomposition Error in Accruals and Cash Flows: Implications for Inferences about Accrual Quality

Number of pages: 55 Posted: 29 Jan 2025
University of Connecticut - Department of Accounting, University of Iowa - Department of Accounting, University of Iowa - Department of Accounting and Indiana University - Kelley School of Business
Downloads 98 (588,859)

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negatively correlated measurement error, decomposition, backed-into variable, differential persistence, balance sheet accruals, type I error, type II error

7.

The Effect of Conditional Accounting Conservatism on the Predictive Ability of Accrual Components with Respect to Future Cash Flows

Number of pages: 47 Posted: 02 Apr 2024
University of Connecticut - Department of Accounting, University of Iowa - Department of Accounting and affiliation not provided to SSRN
Downloads 75 (692,409)

Abstract:

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conditional conservatism, timely loss recognition, accruals, cash flow predictability.