Under ASC 842: COVID-19's Lasting Affect on Lease Accounting: Rent Concessions and Lease Modifications
Keywords:
COVID-19 lease adjustments, ASC 842 compliance, accounting for lease concessionsAbstract
The COVID-19 epidemic generated major financial disturbances that profoundly impacted lease accounting in many different companies. Changes to leases and rental concessions were absolutely vital components of financial strategy as companies dealt with operational changes, income losses, and closures. The Financial Accounting Standards Board (FASB) addressed these particular challenges by adding pragmatic expedients in ASC 842, meant to help lessees and lessors in the more effective lease management.Lease modifications and rent concessions, as stipulated by ASC 842, aim to alleviate the administrative and financial burdens on enterprises during challenging circumstances. This research seeks to examine how these beneficial tools have assisted organizations in adhering to lease accounting regulations and aligning their financial constraints with the pandemic. This paper examines the several problems brought about by COVID-19 lease changes, together with the remedies available to lessees and lessors, their pragmatic relevance, and the long-lasting consequences on lease accounting practices. Additionally, the potential consequences of these modifications are investigated, including their potential impact on future lease agreements, the improvement of precise reporting in the face of fluctuating economic conditions, and the potential impact of these temporary measures on the development of lease accounting standards post-pandemic. Ultimately, FASB's response—which led to the acceptance of ASC 842—equipped businesses with required tools to manage their lease commitments, therefore assuring compliance and saving costs. The talk highlights how fast ASC 842 can be fixed and the basis for future resilience in lease accounting that pragmatic expediency offers, therefore controlling unexpected financial problems.
References
1. Closing, E., Center, E. C., Room, L., MEN, I. M. E. N., Start, M., Safety, P., ... & Fees, N. I. (2017). I. Student Resources.
2. Weidner, D. J. (2017). New FASB rules on accounting for leases: A Sarbanes-Oxley promise delivered. The Business Lawyer, 72(2), 367-404.
3. Freeman, M. S. (2018). ASC 842: Implementing the New Leasing Standard. Management Accounting Quarterly, 20(1).
4. Stancheva-Todorova, E., & Velinova-Sokolova, N. (2019). IFRS 16 leases and its impact on company’s financial reporting, financial ratios and performance metrics. Economic Alternatives, 1(1), 44-62.
5. Paik, D. G. H., van der Laan Smith, J. A., Lee, B. B., & Yoon, S. W. (2015). The relation between accounting information in debt covenants and operating leases. Accounting Horizons, 29(4), 969-996.
6. Comiran, F. H. (2014). Lobbying behavior: Evidence from proposed changes in lease accounting (Doctoral dissertation, UC Berkeley).
7. Glasscock, R., Ainsworth, P., & Shimpa, L. (2016). THE ENERGY INDUSTRY'S RESPONSES TO THE PROMULGATION OF ASC 842: LEASES. Petroleum Accounting and Financial Management Journal, 35(3), 43.
8. Munter, P. (2018). Lessor accounting under ASC 842–Not necessarily business as usual. Journal of Accounting Education, 43, 57-60.
9. Singh, A. (2012). Proposed lease accounting changes: Implications for the restaurant and retail industries. Journal of Hospitality & Tourism Research, 36(3), 335-365.
10. Yamen, S., Silvia, H., & Christiansen, L. (2019). In Defense of the Landlord: A New Understanding of the Property Owner. Urb. Law., 50, 273.
11. McLaren, M. (2019). Covid-19: The Airlines' Battle for Survival. Issues Aviation L. & Pol'y, 19, 173.
12. Wójcik-Czerniawska, A. (2017). Effective Methods of Tax Reduction for Organizations in the Era of COVID-19. In Economic Resilience and Pandemic Response (pp. 211-221). Routledge.
13. Stergiopoulos, V., Mejia-Lancheros, C., Nisenbaum, R., Wang, R., Lachaud, J., O'Campo, P., & Hwang, S. W. (2019). Long-term effects of rent supplements and mental health support services on housing and health outcomes of homeless adults with mental illness: extension study of the At Home/Chez Soi randomised controlled trial. The Lancet Psychiatry, 6(11), 915-925.
14. Nyeko, K. E., Sing, N. K., & Ling, V. M. (2018). The Impact of the Covid-19 Pandemic (Coronavirus) on Small and Medium Enterprises (SMEs) in Kampala Central Division, Uganda.
15. STARNONI, M. (2019). The effects of COVID-19 on the labour market.
16. Komandla, V. Enhancing Security and Fraud Prevention in Fintech: Comprehensive Strategies for Secure Online Account Opening.
17. Komandla, V. Transforming Financial Interactions: Best Practices for Mobile Banking App Design and Functionality to Boost User Engagement and Satisfaction.
18. Gade, K. R. (2017). Integrations: ETL vs. ELT: Comparative analysis and best practices. Innovative Computer Sciences Journal, 3(1).
19. Gade, K. R. (2017). Integrations: ETL/ELT, Data Integration Challenges, Integration Patterns. Innovative Computer Sciences Journal, 3(1).
20. Boda, V. V. R., & Immaneni, J. (2019). Streamlining FinTech Operations: The Power of SysOps and Smart Automation. Innovative Computer Sciences Journal, 5(1).
21. Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2019). End-to-End Encryption in Enterprise Data Systems: Trends and Implementation Challenges. Innovative Computer Sciences Journal, 5(1).
22. Muneer Ahmed Salamkar. Next-Generation Data Warehousing: Innovations in Cloud-Native Data Warehouses and the Rise of Serverless Architectures. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Apr. 2019
23. Muneer Ahmed Salamkar. Real-Time Data Processing: A Deep Dive into Frameworks Like Apache Kafka and Apache Pulsar. Distributed Learning and Broad Applications in Scientific Research, vol. 5, July 2019
24. Muneer Ahmed Salamkar, and Karthik Allam. “Data Lakes Vs. Data Warehouses: Comparative Analysis on When to Use Each, With Case Studies Illustrating Successful Implementations”. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Sept. 2019
25. Muneer Ahmed Salamkar. Data Modeling Best Practices: Techniques for Designing Adaptable Schemas That Enhance Performance and Usability. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Dec. 2019
26. Naresh Dulam. Snowflake: A New Era of Cloud Data Warehousing. Distributed Learning and Broad Applications in Scientific Research, vol. 1, Apr. 2015, pp. 49-72
27. Naresh Dulam. The Shift to Cloud-Native Data Analytics: AWS, Azure, and Google Cloud Discussing the Growing Trend of Cloud-Native Big Data Processing Solutions. Distributed Learning and Broad Applications in Scientific Research, vol. 1, Feb. 2015, pp. 28-48
28. Naresh Dulam. DataOps: Streamlining Data Management for Big Data and Analytics . Distributed Learning and Broad Applications in Scientific Research, vol. 2, Oct. 2016, pp. 28-50
29. Naresh Dulam. Machine Learning on Kubernetes: Scaling AI Workloads . Distributed Learning and Broad Applications in Scientific Research, vol. 2, Sept. 2016, pp. 50-70
30. Sarbaree Mishra, et al. Training Models for the Enterprise - A Privacy Preserving Approach. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Mar. 2019
31. Sarbaree Mishra. Distributed Data Warehouses - An Alternative Approach to Highly Performant Data Warehouses. Distributed Learning and Broad Applications in Scientific Research, vol. 5, May 2019
32. Sarbaree Mishra, et al. Improving the ETL Process through Declarative Transformation Languages. Distributed Learning and Broad Applications in Scientific Research, vol. 5, June 2019
33. Sarbaree Mishra. A Novel Weight Normalization Technique to Improve Generative Adversarial Network Training. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Sept. 2019
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
