Earnings Management and Earnings Value Relevance in Indonesia's Property Sector During and Post COVID-19 Pandemic

The COVID-19 pandemic had a significant impact on the property and real estate sector in Indonesia. During the Large-Scale Social Restrictions (PSBB), economic activity declined sharply, resulting in substantial losses for many property companies. This study aims to analyse earnings management and earnings value relevance in real estate companies during and after the COVID-19 pandemic. A descriptive quantitative method was employed using secondary data from the financial statements of 34 companies listed on the Indonesia Stock Exchange. The results of the Kolmogorov–Smirnov (K–S) test indicated that the earnings management variable was normally distributed (significance values during the pandemic = 0.217; post-pandemic = 0.235). Meanwhile, the F-test revealed no significant simultaneous effect of the independent variables (BVPS and EPS) on earnings value relevance in both periods, with a p-value of 1.293 (≥ 0.05). Despite the potentially negative perception of earnings manipulation, such decisions were found to enhance the relevance of earnings and firm value. This study uniquely highlights the pandemic’s impact on accounting practices and the relevance of earnings while also demonstrating corporate strategies to maintain their image and attract investors amid economic uncertainty.

Authors

Institutions

Publication Details

Journal
Journal of Mathematics Instruction Social Research and Opinion
Published
2025-06-22
DOI
https://doi.org/10.58421/misro.v4i2.508
Primary Topic
Corporate Governance and Financial Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Earnings Management and Earnings Value Relevance in Indonesia's Property Sector During and Post COVID-19 Pandemic

Widia Astuti, Wilyan Amri
Journal of Mathematics Instruction Social Research and Opinion
Corporate Governance and Financial Management
article

Earnings Management and Earnings Value Relevance in Indonesia's Property Sector During and Post COVID-19 Pandemic

Widia Astuti, Wilyan Amri
article en

Abstract

The COVID-19 pandemic had a significant impact on the property and real estate sector in Indonesia. During the Large-Scale Social Restrictions (PSBB), economic activity declined sharply, resulting in substantial losses for many property companies. This study aims to analyse earnings management and earnings value relevance in real estate companies during and after the COVID-19 pandemic. A descriptive quantitative method was employed using secondary data from the financial statements of 34 companies listed on the Indonesia Stock Exchange. The results of the Kolmogorov–Smirnov (K–S) test indicated that the earnings management variable was normally distributed (significance values during the pandemic = 0.217; post-pandemic = 0.235). Meanwhile, the F-test revealed no significant simultaneous effect of the independent variables (BVPS and EPS) on earnings value relevance in both periods, with a p-value of 1.293 (≥ 0.05). Despite the potentially negative perception of earnings manipulation, such decisions were found to enhance the relevance of earnings and firm value. This study uniquely highlights the pandemic’s impact on accounting practices and the relevance of earnings while also demonstrating corporate strategies to maintain their image and attract investors amid economic uncertainty.

Journal of Mathematics Instruction Social Research and OpinionVol. 4(2)
University of Mataram (ID)
Openalex Percentile: Top 79%
Corporate Governance and Financial Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.