IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i16p10334-d892618.html
   My bibliography  Save this article

The Quality of Fair Revaluation of Fixed Assets and Additional Calculations Aimed at Facilitating Prospective Investors’ Decisions

Author

Listed:
  • Sarfraz Hussain

    (Putra Business School, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Mohammad Enamul Hoque

    (BRAC Business School, BRAC University, Dhaka 1212, Bangladesh)

  • Perengki Susanto

    (Department of Management, Universitas Negeri Padang, Padang 25131, Indonesia)

  • Waqas Ahmad Watto

    (Commerce Department, Bahauddin Zakariya University, Multan 60000, Pakistan)

  • Samina Haque

    (BRAC Business School, BRAC University, Dhaka 1212, Bangladesh)

  • Pradeep Mishra

    (College of Agriculture, Jawaharlal Nehru Krishi Vishwavidyalaya, Powarkheda, Narmadapuram 461110, India)

Abstract

The main objective of this study is to find out why sugar companies’ revaluation of their fixed assets has no direct financial impact. The purpose of this financial statement analysis of the sugar sector is to help potential investors make better decisions. It can also be used to address information asymmetries and alert investors. Fixed assets form a major part of a company’s value. During 2013–2018, 19 selected enterprises of Pakistan’s sugar sector adopted the International Accounting Standards Board’s international accounting standard 16 for fixed assets. Ordinary least squares, fixed effects, and random effects methods were used as a static panel, a panel-corrected standard errors method was used for the robust standard error and the system generalized method of moments was used as a dynamic panel. The surplus had a negative impact on operative income on revaluation of fixed assets in sugar businesses. As expected, revaluation by fixed asset firms resulted in changes in potential outcomes, as measured by cash in operating income and revenue, both of which were extremely negative. The return on assets was also linked to revaluation balance. The debt over the proportion of assets resulted in a strong correlation between revaluations, which meant that motivation affected how the volatility in asset value reflected the revaluation. Relationships were generally worse and more uncertain for listed companies at a time of strong economic volatility. Investors should not consider such accounting justice. The price-earnings ratio had a beneficial effect on operative income. The statistics support the idea that external concerns help the revaluation of assets.

Suggested Citation

  • Sarfraz Hussain & Mohammad Enamul Hoque & Perengki Susanto & Waqas Ahmad Watto & Samina Haque & Pradeep Mishra, 2022. "The Quality of Fair Revaluation of Fixed Assets and Additional Calculations Aimed at Facilitating Prospective Investors’ Decisions," Sustainability, MDPI, vol. 14(16), pages 1-14, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10334-:d:892618
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/16/10334/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/16/10334/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jaganath Behera & Alok Kumar Mishra, 2020. "Renewable and non-renewable energy consumption and economic growth in G7 countries: evidence from panel autoregressive distributed lag (P-ARDL) model," International Economics and Economic Policy, Springer, vol. 17(1), pages 241-258, February.
    2. Alonso-Borrego, Cesar & Arellano, Manuel, 1999. "Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 36-49, January.
    3. Badi H. Baltagi, 2021. "Econometric Analysis of Panel Data," Springer Texts in Business and Economics, Springer, edition 6, number 978-3-030-53953-5, June.
    4. Yannick Coulon, 2022. "Small Business Valuation Methods," Springer Books, Springer, number 978-3-030-89719-2, December.
    5. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    6. Wenying Fu & Kean Fan Lim, 2022. "The Constitutive Role of State Structures in Strategic Coupling: On the Formation and Evolution of Sino-German Production Networks in Jieyang, China," Economic Geography, Taylor & Francis Journals, vol. 98(1), pages 25-48, January.
    7. Jincheol Bae & Jaehong Lee & Eunsoo Kim, 2019. "Does Fixed Asset Revaluation Build Trust between Management and Investors?," Sustainability, MDPI, vol. 11(13), pages 1-22, July.
    8. Fonkam Mongwa Nkam & Akume Daniel Akume & Molem Christopher Sama, 2020. "Macroeconomic Drivers of Private Equity Penetration in Sub-Saharan African Countries," International Business Research, Canadian Center of Science and Education, vol. 13(1), pages 192-205, January.
    9. Li, Shuangyan & Fu, Huan & Wen, Jun & Chang, Chun-Ping, 2020. "Separation of ownership and control for Chinese listed firms: Effect on the cost of debt and the moderating role of bank competition," Journal of Asian Economics, Elsevier, vol. 67(C).
    10. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    11. Kirsten Andersen & Rebecca Tekula, 2022. "Value, Values, and Valuation: The Marketization of Charitable Foundation Impact Investing," Journal of Business Ethics, Springer, vol. 179(4), pages 1033-1052, September.
    12. Steffen Nestler & Sarah Humberg, 2022. "A Lasso and a Regression Tree Mixed-Effect Model with Random Effects for the Level, the Residual Variance, and the Autocorrelation," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 506-532, June.
    13. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    14. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.
    15. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
    16. Liurui Deng & Yiwen Zhao, 2022. "Investment Lag, Financially Constraints and Company Value—Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(11), pages 3034-3047, September.
    17. Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
    18. Sheikh, Shahbaz, 2022. "CEO power and the likelihood of paying dividends: Effect of profitability and cash flow volatility," Journal of Corporate Finance, Elsevier, vol. 73(C).
    19. Ali Shah Mohd & Danish Ahmed Siddiqui, 2020. "Effect of Macroeconomic Factors on Firms ROA: A Comparative Sectorial Analysis from Pakistan," International Journal of Publication and Social Studies, Asian Economic and Social Society, vol. 5(1), pages 1-17, March.
    20. Yannick Coulon, 2022. "Asset-Based Approach to Valuation," Springer Books, in: Small Business Valuation Methods, chapter 0, pages 21-70, Springer.
    21. Sudip Datta & Mai Iskandar‐Datta & Kartik Raman, 2005. "Managerial Stock Ownership and the Maturity Structure of Corporate Debt," Journal of Finance, American Finance Association, vol. 60(5), pages 2333-2350, October.
    22. Woo, Donghyup & Suresh, Nallan C., 2022. "Voluntary agreements for sustainability, resource efficiency & firm performance under the supply chain cooperation policy in South Korea," International Journal of Production Economics, Elsevier, vol. 252(C).
    23. David A Becher & Thomas P Griffin & Greg Nini, 2022. "Creditor Control of Corporate Acquisitions," The Review of Financial Studies, Society for Financial Studies, vol. 35(4), pages 1897-1932.
    24. N. V. Suvorov & E. A. Rutkovskaya & E. E. Balashova & S. I. Maksimtsova & S. V. Treschina & Yu.V. Beletskii, 2022. "Assessing the Performance of Fixed Assets in the Russian Economy," Studies on Russian Economic Development, Springer, vol. 33(4), pages 367-376, August.
    25. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    26. Ali Shah Mohd & Danish Ahmed Siddiqui, 2020. "Effect of Macroeconomic Factors on Firms ROA: A Comparative Sectorial Analysis from Pakistan," International Journal of Publication and Social Studies, Asian Economic and Social Society, vol. 5(1), pages 1-17.
    27. Olante, Maria Elena & Lassini, Ugo, 2022. "Investment property: Fair value or cost model? Recent evidence from the application of IAS 40 in Europe," Advances in accounting, Elsevier, vol. 56(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yongfu Huang, 2011. "Private investment and financial development in a globalized world," Empirical Economics, Springer, vol. 41(1), pages 43-56, August.
    2. Angelica Gonzalez, 2007. "Angelica Gonzalez," Edinburgh School of Economics Discussion Paper Series 168, Edinburgh School of Economics, University of Edinburgh.
    3. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.
    4. Angelica Gonzalez, 2007. "Empirical Likelihood: Improved Inference within Dynamic Panel Data Models," Edinburgh School of Economics Discussion Paper Series 154, Edinburgh School of Economics, University of Edinburgh.
    5. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 70628, University Library of Munich, Germany.
    6. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    7. Dobbelaere, Sabien & Kiyota, Kozo & Mairesse, Jacques, 2015. "Product and labor market imperfections and scale economies: Micro-evidence on France, Japan and the Netherlands," Journal of Comparative Economics, Elsevier, vol. 43(2), pages 290-322.
    8. Valentín Azofra Palenzuea & Paolo Saona Hoffmann & Eleuterio Vallelado González, 2004. "Estructura De Propiedad Y Oportunidades De Crecimiento Como Determinantes Del Endeudamiento De Las Empresas Chilenas," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 7(2), pages 105-145.
    9. Cheryl Xiaoning Long & Galina Hale & Hirotaka Miura, 2014. "Productivity Spillovers from FDI in the People's Republic of China: A Nuanced View," Asian Development Review, MIT Press, vol. 31(2), pages 77-108, September.
    10. Sarafidis, Vasilis & Yamagata, Takashi & Robertson, Donald, 2009. "A test of cross section dependence for a linear dynamic panel model with regressors," Journal of Econometrics, Elsevier, vol. 148(2), pages 149-161, February.
    11. Sèna Kimm Gnangnon, 2023. "Do unilateral trade preferences help reduce poverty in beneficiary countries?," International Journal of Economic Policy Studies, Springer, vol. 17(1), pages 249-288, February.
    12. Gnangnon, Sèna Kimm, 2021. "Effect of the Utilization of Non-Reciprocal Trade Preferences offered by the QUAD on Economic Growth in Beneficiary Countries," EconStor Preprints 242848, ZBW - Leibniz Information Centre for Economics.
    13. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    14. Keskinsoy, Bilal, 2017. "Lucas Paradox in the Short-Run," MPRA Paper 78783, University Library of Munich, Germany.
    15. Andrew M. Jones & José M. Labeaga, 2003. "Individual heterogeneity and censoring in panel data estimates of tobacco expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(2), pages 157-177.
    16. Osvaldo Lagares, 2016. "Capital, Economic Growth and Relative Income Differences in Latin America," Discussion Papers 16/03, Department of Economics, University of York.
    17. Tun, yin-li & Azman-saini, w.n.w. & Law, siong-hook, 2012. "International evidence on the link between foreign direct investment and institutional quality," MPRA Paper 65644, University Library of Munich, Germany.
    18. Kruiniger, Hugo, 2013. "Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions," Journal of Econometrics, Elsevier, vol. 173(2), pages 175-188.
    19. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute.
    20. Charles Mawusi, 2021. "Economic Uncertainty and Remittances to Developing Economies: A System GMM Approach," Working Papers hal-03147813, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10334-:d:892618. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.