Historical Cost Research Articles

The phenomenon of China’s carbon accounting policies and practices

Purpose This study aims to explore China’s carbon accounting policies and practices to enhance its carbon accounting and trading practices and achieve carbon neutrality. Design/methodology/approach This study adopts a phenomenological methodology to explore carbon accounting by setting the scope of the phenomenon, establishing research methods, conducting interviews with 30 participants from 14 emitting entities and four accounting firms and establishing methods for data analysis. Five themes were identified using a five-step coding method. Findings The results show no uniformity in the accounting treatment of carbon trading; however, common characteristics exist, and they have generally adopted simplified and conservative accounting methods under China’s emission trading scheme. Their common characteristics are that the granted allowances are not recognised as assets by most emitting entities, emissions allowance assets are measured using the historical cost method, most emitting entities only conduct accounting when there are actual cash flows or outflows with regard to carbon emissions allowance trading, and only a few emitting entities disclose carbon trading information in their financial statements or corporate social responsibility reports. Originality/value This study highlights accountants’ crucial role in carbon activities by guiding emitting entities’ low-carbon initiatives and culture and transforming managers’ mindsets. It also introduces the China Accounting Standards Committee-based accounting methods for allowances and obligations, aiding carbon disclosure quality and sustainability. These findings also inform the carbon accounting standards that may enhance corporate accountability and address climate change.

Explanatory Model for the Estimation of the Minimum Monoculture Planted Area for Coffee that would allow reaching a Living Income

This study's objective was the construction of an explicative model to determine the minimum area necessary to be planted in coffee, to afford a living income, on monoculture coffee farms. In the sustainable coffee production scenario, the annual net income of families is evaluated in function of the achievement of a decent standard of living for all of its members. The metric which makes this possible is called living income. Unfortunately, among small coffee farmers, there is a large gap between real net income and living income, which is a multidimensional phenomenon, affected by exogenous, difficult-to-control factors, such as area cultivated in coffee and its sale price, in addition to variables derived from productive models employed, such as productivity, costs, and farm food production. Due to it being a multifactorial phenomenon, data mining algorithms were applied (decision tree and random forest), in order to classify those farms that would close the gap between net and living income. Model iterations were performed on a dataset that gathered historical production cost, income, and cultivated area information from farms located in four Colombian departments. It was concluded that the variables which explain the gap in a monoculture coffee system are as follows: Area planted in coffee, productivity, and sale price.

Navigating Reversed Valuation Dilemmas: SME Enterprises Nationalized in 1950s Poland - A Case Study

The publication describes a problem that often arises in court cases regarding the valuation of SME forcibly nationalized in the 1950s. Valuation of compensation to previous SME owners is an ongoing court debate in Poland. The authors proposed an approach that took into account the economic conditions at that time and complied with the principle of paying compensation for the actual losses incurred, and not for the potential losses that could be incurred as a result. At the same time, the publication analysed other similar judgments in cases regarding compensation for nationalized enterprises. The practical and scientific value of the publication lies in the fact that it addresses an existing practical problem and its solution. Research Design & Methods: the paper presents a conceptual proposal of the SME valuation method in unique circumstances, complemented by a detailed case study illustrating the application of this valuation approach. Findings: When calculating the compensation for nationalization or other forms of expropriation courts use various methods of valuing net assets (fair market value, book value, recreation value) plus separately determine the value of intangibles, such as licenses, based on the discounted average profits from such assets for a reasonable period of time. If indexation was employed (for historical cost valuation), it used either average interest rates in the economy, the cost of capital of a company, or the cost of lost opportunities for a particular company. Using discounted cash flow valuation for the entire business was uncommon and even if it was included in the bilateral investment treaties (which were meant to protect investors from expropriation) it was considered by the tribunals as speculative and unreliable. Our approach proposes net asset value approach with the use of inflation or average salaries for indexation (to calculate current values of assets) and a combined approach of historical values if they were known at the moment of nationalization and modern estimates of values of remaining assets (that belonged to the company but their value was not provided in the original documentation). Implications & Recommendations: The analysis of historical compensation decisions and bilateral investment treaties suggests that the most popular approach to valuing a loss from expropriation is the fair market value approach and net assets approach with a separate valuation of significant intangible assets provided that they gave certainty of profits for the investor. Contribution & Value Added: The practical and scientific value of the publication lies in the fact that it presents an existing practical problem of court calculation of compensations to owners of forcibly nationalized SMEs in Poland and its solution together with methodological framework that can be used in the future

Constraint-Guided Behavior Transformer for Centralized Coordination of Connected and Automated Vehicles at Intersections.

The centralized coordination of Connected and Automated Vehicles (CAVs) at unsignalized intersections aims to enhance traffic efficiency, driving safety, and passenger comfort. Autonomous Intersection Management (AIM) systems introduce a novel approach for centralized coordination. However, existing rule-based and optimization methods often face the challenges of poor generalization and low computational efficiency when dealing with complex traffic environments and highly dynamic traffic conditions. Additionally, current Reinforcement Learning (RL)-based methods encounter difficulties around policy inference and safety. To address these issues, this study proposes Constraint-Guided Behavior Transformer for Safe Reinforcement Learning (CoBT-SRL), which uses transformers as the policy network to achieve efficient decision-making for vehicle driving behaviors. This method leverages the ability of transformers to capture long-range dependencies and improve data sample efficiency by using historical states, actions, and reward and cost returns to predict future actions. Furthermore, to enhance policy exploration performance, a sequence-level entropy regularizer is introduced to encourage policy exploration while ensuring the safety of policy updates. Simulation results indicate that CoBT-SRL exhibits stable training progress and converges effectively. CoBT-SRL outperforms other RL methods and vehicle intersection coordination schemes (VICS) based on optimal control in terms of traffic efficiency, driving safety, and passenger comfort.

Methods and data needs to estimate the economic market value of livestock at different spatial scales.

Assessing the economic value of livestock such as cattle, goats, sheep, pigs, chickens and fish can offer information about their financial performance and economic importance at farm, national and global scale. Such information is needed for decision-making surrounding livestock finance, investment and strategic development. The aim of this study was to provide an overview of the key livestock valuation methods and associated data requirements. The study was conducted using a literature review. Five key livestock valuation methods were identified and described: historical costs, net current market value, replacement costs, net present value and cost of production. The findings of this study may be of interest to livestock scientists, veterinarians, policy-makers and other stakeholders who aim to assess the economic value of livestock herds. The Global Burden of Animal Diseases programme relied on the outcomes of this study to identify methods for the estimation of the economic value of livestock at the global scale and for its Ethiopia and Indonesia case studies.

Challenges and Prospects of Establishing Accounting Treatment Standards for Digital Currency

Digital Currency have emerged as a disruptive force in the financial world, challenging traditional accounting practices and regulatory frameworks. This study examines the challenges and prospects for establishing accounting standards for Digital Currency. Initially conceived as a secure medium of exchange, Digital Currency have evolved into assets that can be exchanged for goods or services. However, their dual role as currencies and commodities presents a classification dilemma. Current accounting standards primarily classify Digital Currency as intangible assets, but their rapid appreciation renders historical cost measurement ineffective. Adopting fair value measurement emerges as an optimal solution, but practical hurdles remain. Through insights from existing literature and analysis, this study optimizes accounting approaches for Digital Currency, addressing challenges such as asset valuation, regulatory inconsistencies, diverse investor perspectives, and legal uncertainties. Establishing standardized and transparent accounting practices tailored to Digital Currency is critical to ensuring transparency, consistency, and reliability in financial reporting.

Corporate carbon accounting: balance sheets and flow statements

Current corporate disclosures regarding carbon emissions lack generally accepted accounting rules. The transactional carbon accounting system described here takes the rules of historical cost accounting for operating assets as a template for generating carbon emissions (CE) statements comprising a balance sheet and a flow statement. The asset side of the CE balance sheet reports the carbon emissions embodied in operating assets. The liability side conveys the firm’s cumulative direct emissions into the atmosphere as well as the cumulative emissions embodied in goods acquired from suppliers less those sold to customers. Flow statements report the company’s annual corporate carbon footprint calculated as the cradle-to-gate carbon footprint of goods sold during the current period. Taken together, balance sheets and flow statements generate key performance indicators of a company’s past, current, and future performance in the domain of carbon emissions.

Valuing public land in land policy: The role of accountancy regulations

Land values change in planning processes. Accountancy regulations define the book value of land held by local authorities. This affects the evaluation of alternative lines of action in land development, and in this way, the land policy of local authorities. This paper reflects on the case of the Netherlands, which has a well-established tradition of public land development. Traditionally, valuation has been based on historic costs: the prices for acquisition and costs of infrastructure provision paid in the past, and not the current exchange values. Losses foreseen must be taken immediately; profits can only be booked after they have been made. This paper analyses the changes in these accountancy regulations over time and studies their impact on the economic position of local authorities. It considers both regulations as the outcomes of these as being found in administrative records and the practice in the City of Enschede where there was a difference between the official value as recorded in the books and the value that was the basis for decision-making. The paper discusses the impact on land policy. There is a tension between regulations that more-and-more aim for a direct reflection of property market volatility in the books and the aim of local authorities to present financial stability. This may contribute to less financial involvement in land policies.

Research on Fair Value Application and Financial Impact - Taking Zhongnan Construction Company as an Example

The history of economic and accounting development shows that the more the economy develops, the more important accounting is; the more the economy develops, the stronger the ability of accounting information to promote or hinder economic development. In the long history of accounting, measurement has always been the core of accounting. The choice of accounting methods focuses on the choice of measurement attributes, rather than the choice of measurement units. With the development of market economy and knowledge economy, the accounting information provided by historical cost accounting only involves past costs and ignores future values. It cannot reflect changes in the economic environment in a timely and complete manner, and has no connection with the economic decision-making process. The measurement of fair value can reflect the current and future changes in the economic environment in a timely and complete manner. In the more than ten years since it has been in line with the international accounting community, the issue of fair value has always been an urgent problem to be solved. Corresponding research on related issues, from theoretical review to the practical application of fair value measurement. At present, the control of fair value measurement by Chinese enterprises is still not stable enough, and how to effectively improve is still an in-depth question.

Preperation of Sambhar Premix

Abstract: A sambhar premix is a convenient blend of dry spices and lentils essential for preparing the popular South Indian dish, sambhar. Comprising roasted and ground ingredients like lentils (toor dal, masoor dal), spices (coriander, cumin, fenugreek, mustard seeds), dried red chilies, and aromatics (turmeric, asafetida, curry leaves); this premix offers a quick solution to recreate the flavorsome and aromatic sambhar. When stored in an airtight container, this premix maintains its freshness, making it a time-saving and versatile addition to various culinary creations. masala development process would highlight the key steps and considerations in creating this traditional South Indian spice blend. It would cover aspects suchas ingredient selection, proportioning, grinding techniques, and the preservation methods employed. Additionally, the abstract might touch upon the cultural significance of masala and its role in enhancing the flavor profile of the iconic dish. This abstract delves into the historical evolution of masala, exploring its traditional ingredients and tracing the development of a premix. The document outlines the meticulous method of preparation for the premix, emphasizing key steps such as ingredient selection, proportioning, and grinding techniques. Additionally, it includes a comprehensive cost analysis of the production process. Proximate testing is employed to evaluate the nutritional composition of the masala, shedding light on itsdietary implications. This abstract aims to provide a holistic overview of the masala development process, combining historical context, preparation methodology, cost considerations, and nutritional insights. This detailed abstract explores the rich history, intricate ingredients, and methodical preparation of masala powder, with a focus on developing a premix. The historical analysis delves into the origins and evolution of the spice blend, highlighting the regional variations and cultural significance associated with its use in South Indian cuisine. The document provides a comprehensive overview of the ingredients, emphasizing the selection of authentic spices crucial to achieving the distinctive flavor profile. The method of preparation for the premix is detailed, encompassing precise measurements, grinding techniques, and the blending process to ensure consistency and optimal flavor infusion. A meticulous cost analysis is presented, covering raw materials, processing expenses,and packaging costs, offering insights into the economic feasibility of producing masala on a larger scale. Furthermore, proximate testing is employed to assess the nutritional composition, detailingthe macronutrient and micronutrient content, contributing to a comprehensive understanding of the spice blend's dietary implications. This abstract aims to serve as a comprehensive reference, encapsulating the historical, culinary, economic, and nutritional dimensions of masala powder and its premix variant.

On the Ethics of Fair Value Accounting: Distributive Effects, Distributive Injustice, and Implications for Social Peace

Fair value accounting is at the heart of arguably the world’s most prominent accounting standards, particularly US GAAP and IFRS. Fair value measurement has been the subject of intense debate. Among other things, it has been analyzed from an ethical perspective. However, this discussion has mainly been limited to the judgment involved in fair value measurement and the ethics of fair value in its ability to provide decision-useful information to interested parties. This study pushes the boundaries by adding a new dimension to the discussion of the ethics of fair value accounting by examining its ethics from a more systemic and societal perspective. Drawing on Austrian business cycle theory, it argues that fair value accounting facilitates certain distributive effects in inflationary monetary environments, thereby contributing to distributive injustice and potentially to social discord. In this respect, fair value accounting—in contrast to historical cost accounting—should not be considered fair or just, but unethical instead.

Penerapan Laporan Keuangan Berdasarkan Standar Akuntansi Keuangan Entitas Mikro Kecil dan Menengah (SAK-EMKM) Pada UMKM Pentol Kabul

SAK EMKM is expected to assist entities in transitioning from cash-based financial reporting to accrual-based financial reporting. The issuance of SAK EMKM is expected to serve as one of the drivers of financial literacy for MSMEs in Indonesia, thus widening their access to financing from the banking industry. Financial statements are records of financial information of a company during an accounting period that explain a company's performance. The purpose of financial statements according to PSAK 1 (Revised 2009) is to provide information about the financial position, financial performance, and cash flows of an entity to assist most users of the financial statements in making economic decisions. SAK-EMKM contains simpler accounting regulations than SAK-ETAP because MSMEs conduct transactions with calculations and measurements that purely use historical costs. The type of research method used is descriptive qualitative method. Describing the current financial condition of MSME players. As well as conducting a simple financial statement preparation analysis for MSME players. This study produces financial statements for Pentol Kabul MSMEs that comply with SAK-EMKM standards, including balance sheets, income statements, and notes to the financial statements.

Analisis Pengakuan Beban Kontrak Konstruksi Berdasarkan PSAK NO. 34 pada Perusahaan Jasa Konsultansi Konstruksi: Studi Kasus PT. Ravino Citra Mandiri

This study aims to analyze how the application and recognition of revenue and expenses in construction consulting service companies in accordance with PSAK No. 34 at PT Ravino Citra Mandiri. The data used for this research is secondary data in the form of records of PT Ravino Citra Mandiri's project expenses and revenues for the period July 2021 - December 2021. The method used for data collection is through interviews, observation and documentation. The data analysis technique uses qualitative analysis. The results showed that the application of PSAK No. 34 at PT Ravino Citra Mandiri was still not implemented in its entirety, where the recording was still carried out on a cash basis, but the recording and recognition of expenses was appropriate. The application of the work contract method is not yet appropriate, because the company only records using the cash basis system due to improper management so that the author presents a comparison if the recording is justified using the completed contract method and also the percentage of completion method, the percentage of completion method is used because the billing system carried out for the project uses a term system. The use of this method is considered by the company as a recording with a high accuracy value because it records all historical costs during the work of the work project compared to the completed contract which only records receipts and expenses for the work project.

Institutional practices for charitable medication access for uninsured patients.

To identify the most frequently prescribed medications, the location where prescriptions were filled, and whether a voucher was utilized among patients enrolled in a charitable care program within an academic medicalcenter. This was a retrospective cohort study analyzing electronic health record and pharmacy dispensing information at a medical center's outpatient pharmacies. Patients included in this analysis were enrolled in a charitable care program and had at least 1 ambulatory encounter in a primary care clinic from March 1, 2019, to June 30, 2021. The study identified frequently prescribed medications, prescription payment methods, the overall cost of prescriptions if available, and the percentage of patients who filled their prescription at a medical center's outpatient pharmacies vs external outpatient pharmacies. Descriptive statistics were used to describe the results. This study included 511 patients, 87% of whom were Spanish speaking. A total of 8453 prescriptions were identified, and more than half of the prescriptions were sent to external outpatient pharmacies. The most common medications prescribed were for cardiovascular disease, diabetes, and pain treatment. Forty-seven percent of all prescriptions were sent to the medical center's outpatient pharmacies. The medical center's charitable care program covered the costs of 44% of the prescriptions sent to internal pharmacies, assisting 148 unique patients and incurring a cost of $111,052 for the medical center. Overall, this study was able to characterize patient demographics, historical costs related to charitable care coverage, and the utilization of health care services among this population. This information can be used to support the development and implementation of a charitable medication formulary, with the aims of improving quality of care for this population and reducing medical center costs.

An Empirical Assessment of IAS 40 Investment Property

This study examines the value relevance of the fair value model versus the cost model for evaluating investment properties under IAS 40 Investment Property. Contrary to the popular belief that fair value is the most relevant measurement attribute, we find that the coefficient estimate of investment properties for Chinese companies that adopted IAS 40’s fair value model is significantly smaller than its theoretical value, and is not significantly different from zero, suggesting that reported fair values are not value relevant as perceived by investors for the sample firms. Furthermore, investors tend to adjust the valuation of fair value companies’ non-investment property assets downward. The findings do not support the claim that fair value is superior to historical cost for the investment property valuation. Our findings highlight the need for more implementation guidelines from the IASB to enhance the value relevance of fair value estimates under IAS 40.

Inflation adjustments of financial statements: Implication to price index and performance

This paper examines the critical role of inflation accounting in adjusting financial statements to accurately reflect the impact of inflation on the economy. The primary objectives are twofold: examine the process of restating balance sheets and income statements, emphasizing the limitations inherent in historical cost accounting; and investigate the practical usefulness of price indices in identifying complex changes in the value of monetary and non-monetary assets and liabilities. It uses a systematic analysis of the restatement process, delving into the application of the Constant Purchasing Power Accounting (CPPA) method. The study used Royal Dutch Airlines Company for the years 2018-2019 financial data, including varying different inflation levels. The results of the analysis reveal that indexing revenues under the CPPA method improves liquidity, profitability, and solvency ratios. This improvement is particularly evident in the cash flow statement analysis, where corrections are minimized compared to historical cost accounting. The CPPA method appears to be a powerful solution to the limitations imposed by historical costing in inflationary environments. It is worth noting that the research reveals differences in the practical application of inflation calculations between countries, depending on economic and regulatory factors. This paper calls for continued research efforts to delve deeper into the implications of inflation for different industries, economies and financial reporting frameworks.

The Effect of Fair Value Accounting on Firm Public Debt – Evidence from Business Combinations Under Common Control

We analyze the choice allowed to parent firms under IFRS of how to account for a business combination under common control (BCUCC), and provide evidence on the motivation to select fair values and the economic implications of this choice. A BCUCC is a merger of two firms owned by the same parent. Under IFRS, parent firms can use the acquisition method (fair values) to record the BCUCC or use assets’ historical cost. We show that parents are likely to choose fair values when they desire to increase the transparency of their financial reports and when they likely need to raise capital. Using propensity-score matching, we find that firms that used fair values are more likely to issue new public debt following the transaction. We also find that the cost of issuing new debt for these firms is 55 basis points lower than that of comparable firms that did not do BCUCCs. Our results suggest that using fair values in BCUCCs can increase transparency and lower firms’ cost of debt.

Cost Estimation Proxy Models for Economic Evaluations in Petroleum Projects

Petroleum economic evaluation involves estimating revenues from forecasted production profiles and field costs including capital expenditures (CAPEX), drilling expenses (DRILLEX), and operating expenses (OPEX). The existing cost-estimating tool requires several inputs making it time-intensive and difficult to use with few data during the early stages of projects. Majority of the previously developed time saving cost estimations proxy models rely on unrealistic assumptions that include uniform operational costs for different fields with a different number of wells, casings, and drilled depths. This work focused at developing proxy models that consider the variability of the development costs with different parameters. The developed models benefited from a three-step approach for CAPEX, DRILLEX, and OPEX estimations based on datasets from three wells from a gas field in southern coastal Tanzania. Firstly, cost sensitivity analysis was performed using QUE$TOR v15.1.0.18, a cost estimating commercial software to determine the most influential field parameters of the field costs. Secondly, the field cost models were generated based on historical cost data from the gas field using multivariable regression analysis with the help of Statistical Package for the Social Sciences software (SPSS) v22.0. Lastly, errors analysis was done for checking the predictive reliability of the models. Based on the analysis, the CAPEX and OPEX were found to be strongly linearly dependent on the size of processing facilities, number of producing wells in the gas field and production capacity, respectively. On the other hand, a nonlinearity relation was revealed on of the DRILLEX which was strongly dependent on drilled well depth and number of installed well casing. Results show that the developed models are useful and their reliability becomes robust when more data is used. A stochastic modeling approach was further recommended for the models to incorporate uncertainties associated with the parameters used to quantify the cost estimates.

Trends in and determinants of South African maize exports in the post-deregulation era

Orientation: Agricultural plays a key role in South Africa’s economy, but its exports are constrained by inadequate transport infrastructure, logistical bottlenecks and high production costs. Therefore, most agricultural products are transported to ports by road instead of the more economical rail. Product prices fluctuate with erratic domestic and international supply and demand, which affects competitiveness.Research purpose: The study investigates how transport cost and logistical shortcomings have impacted South African maize exports and competitiveness.Motivation for the study: Little prior research focused on the impact of transport and logistics on the competitiveness of agricultural exports in Africa. Maize, one of South Africa’s leading agricultural products with still-to-be-tapped export potential, was used as an example.Research approach/design and method: Trends in global maize exports and logistics performance are described, as well as South Africa’s share and rankings. Domestic trends in rail and road transport are investigated together with historic costs. Regression analysis investigates determinants of South African maize export volumes.Main findings: South Africa’s logistics-related competitiveness is declining. Rising domestic transport cost has a statistically significant negative effect on maize export volumes while international prices show the expected positive effect. Separate equations for exports through harbours and border posts rendered different results.Practical/managerial implications: Valuable insights are provided into the critical role of logistics efficiency in maize export competitiveness.Contribution/value-add: Empirical findings provide a starting point for more in-depth studies in this area and more informed policy discussions on how the competitiveness of South Africa’s agricultural exports can be enhanced.

Leveraging Remote Sensing Data for Yield Prediction with Deep Transfer Learning

Remote sensing data represent one of the most important sources for automized yield prediction. High temporal and spatial resolution, historical record availability, reliability, and low cost are key factors in predicting yields around the world. Yield prediction as a machine learning task is challenging, as reliable ground truth data are difficult to obtain, especially since new data points can only be acquired once a year during harvest. Factors that influence annual yields are plentiful, and data acquisition can be expensive, as crop-related data often need to be captured by experts or specialized sensors. A solution to both problems can be provided by deep transfer learning based on remote sensing data. Satellite images are free of charge, and transfer learning allows recognition of yield-related patterns within countries where data are plentiful and transfers the knowledge to other domains, thus limiting the number of ground truth observations needed. Within this study, we examine the use of transfer learning for yield prediction, where the data preprocessing towards histograms is unique. We present a deep transfer learning framework for yield prediction and demonstrate its successful application to transfer knowledge gained from US soybean yield prediction to soybean yield prediction within Argentina. We perform a temporal alignment of the two domains and improve transfer learning by applying several transfer learning techniques, such as L2-SP, BSS, and layer freezing, to overcome catastrophic forgetting and negative transfer problems. Lastly, we exploit spatio-temporal patterns within the data by applying a Gaussian process. We are able to improve the performance of soybean yield prediction in Argentina by a total of 19% in terms of RMSE and 39% in terms of R2 compared to predictions without transfer learning and Gaussian processes. This proof of concept for advanced transfer learning techniques for yield prediction and remote sensing data in the form of histograms can enable successful yield prediction, especially in emerging and developing countries, where reliable data are usually limited.