Applied Cost Accounting - I M.Com II Sem - February 2022
This document covers Applied Cost Accounting for the I M.Com II Semester, focusing on Process Costing, including topics such as normal loss, abnormal loss, abnormal gain, joint products, and by-product costing. It details the characteristics of process costing, emphasizing the continuous nature of production, standardization of goods, and cost accumulation across various production stages. It also highlights the types of industries where process costing is applicable, such as textiles, chemicals, and food products.
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PacStat Proposed Topics for Innovative Experiments and Commissioned Works PSMB 13, 22 May 2024 Evelyn Wareham (SPC)
Commissioned Works and Experiments Commissioned Works Innovative Experiments Short-term research projects, such as desk-based literature or methodological reviews, which aim to support NSOs and the PSMB to make decision and recommendation on certain statistical issues. Medium-term research projects that test alternative data collection methods. c. 6 months 1-2 years Up to USD 25K Up to USD 250K Delivered by SPC staff with support from short term consultants Delivered by Pacific countries with PacStat grant and SPC / PacStat technical support
Request for Proposals A request for proposals was circulated for six weeks to Pacific NSO heads and donor and development partners to identify priority areas for research. Five eligible proposals have been received for innovative experiments, and four eligible proposals have been received for commissioned works. Timeline for selection process: Request for proposals circulated 15 March Deadline to submit proposals 26 April Proposals submitted for PSMB13 13 May 2024 Discussion at PSMB 13 22-23 May 2024 Decision by SPC Project Steering Committee 6 June 2024 Noted that the use of administrative and integrated data has been identified as a priority area by PSMB. Should a submission not be successful, SPC will consider it for future research activities.
Recommendations for PSMB It is recommended that the PSMB: 1. Discuss the proposals submitted for the next PSMB commissioned work and innovative experiment funded by PacStat. 2. Provide advice / guidance on which innovative experiment should be taken forward with PacStat funding (noting there is only funding available for one experiment) 3. Provide advice / guidance on which commissioned works SPC should take forward for implementation (noting funding is available for multiple commissioned works) 4. Note that SPC will also work with countries and partners to support progress on the proposals that are not funded under PacStat
Appendix Kiribati National Statistics Office Construct and implement an effective (cost effective and accurate) real time welfare and poverty data monitoring system for Kiribati Government to aid its policy and work programs in response to its National Kiribati Vision KV20 (2016- 2036) and could be used as lesson learned to other NSOs. (IEP-1) Steps Activities Timeline Responsible Cost estimate November to December 2024 1 Use 2023/24 HIES to identify structural inequalities Lead by Consultant assist by Resident Advisor/KNSO 40,000.00 Use small area estimation (SAE)to estimate poor and rank population- HIES 2023/24 HIES and Census 2020 January/February 2025 2 3 February to April 2025 Design and Implement Panel survey 90,000.00 Consultant, Resident Advisor/KNSO Lead by Consultant assist by Resident Advisor/KNSO 30,000.00 4 5 6 Analyse panel survey Identify the effect of context Assess administrative data from line ministries and Linking the factors. Construction and Training on cross validation using HIES data Construct means testing to be used every time a person interacts with a government agency. April to May 2025 June to July 2025 August to September 2025 Lead by Consultant assist by Resident Advisor/KNSO 30,000.00 7 8 Oct-25 Consultant 20,000.00 10 Nov-25 Consultant/RA 20,000.00 Provide traning on SAE and other technical activites provided for this experiment and guidance notes 11 Dec-25 Consultant 20,000.00 250,000.00 Total Cost estimate Initial thoughts: Relevant, useful proposal aligned with PacStat objective. Uses admin data. Very ambitious - would need to adjust scope to ensure it is feasible for completion in 12 months. Could be the first phase of a longer project.
This proposal aims to develop and implement a comprehensive Data Governance Framework (DGF) for Tonga Statistics to ensure the effective management, protection, and utilization of data assets. The proposed DGF will provide guidelines, policies, and procedures for data management, privacy, security, quality assurance, and compliance, enabling Tonga Statistics to maintain data integrity and maximize the value of its data resources. Establishing a Data Governance Framework for Tonga Statistics will enhance data management practices, ensure data integrity and security, and support evidence-based decision- making. Timeline and Budget Needs Assessment and Gap Analysis: 1 months Tonga Statistics Department Strengthening Data Management and Governance for Informed Decision-Making (IEP-2) Framework Design and Development: 1.5 months Capacity Building: 1.5 months Implementation and Integration: 2 months Budget: 30,000 - $50,000 Initial thoughts: Useful work in high value area. Data governance is a priority for HOPS this could be a model for other countries, if treated as a pilot. Less relevant as experiment because not data collection innovation -- could consider this as a PacStat commissioned work.
The SPR is a statistical register of the population of Tuvalu. The register will integrate administrative, census, and survey data to produce high frequency indicators, with the census data as its base. The base will be updated using administrative data from the public health, immigration, and marine department. This will provide the total list of persons in Tuvalu. Tuvalu Central Statistics Department Tuvalu Statistical Population Register (SPR) (IEP-3) Certain sections in the traditional census will not be necessary because it will be retrieved from other sources. Understandably, certain information requires interviews with households and the aim of this project is to minimise the need to visit households, decrease the length of questionnaires, and increase the utilisation of administrative records. The SPR is proposed to be a system that integrates administrative records and other sources and surveys, thus creating a dynamic data source that is updated when the dependent sources are updated. Initial thoughts: Relevant proposal using administrative data to answer a high priority statistical need. Useful example and pilot for the region. Sufficiently different from the previous Tuvalu experiment, which is near complete. Duration: one to one and half years. Budget: c. AUD 150,000
UN Women, ESCAP and SPC Human-friendly time trackers or friendly tracking enumerators? A field experiment to assess innovative technological methods for welfare assessment of income and time poverty (IEP-4) Phase 1 (May-August 2024) - Technological Innovation o This phase spans over four months and aims to lay the foundation for leveraging technology in welfare data collection. This phase is devoted to developing the CAPI tool for a Minimum Harmonized Time-Use Instrument and identifying and purchasing the time-tracker device most suitable for the experiment. Phase 2 (September-October 2024) Field experiment o This phase spans over two months and aims to test the cost-effectiveness of different methods leveraging technology for collecting welfare data on a sample of approximately 400 individuals. This includes training interviewers and assessing their performance during field operations. Phase 3 (November-May 2025) Analysis, validation of results, and report drafting. o This phase conducts data analysis, validates results through a multi-stakeholder online workshop, and drafts reports in view of disseminating lessons learned. Budget: est. USD $250,000 Initial thoughts: Interesting experiment that will deliver value for methods recommendations and an SDG. Less high priority for PICTs and PacStat objective. No use of admin data. Would need to have a lead country to undertake the field work.
Phase 1: Co-creation and Design (0-3 months) Outcomes High Level Stakeholders engaged, and Institutional Buy-In and Strong Partnerships developed. Governance Structure to Coordinate and give Strategic Direction to the Project created. Needs and Priorities of Stakeholders included and Stakeholder Buy-In insured. Budget= $25,000 USDs Vanuatu Bureau of Statistics Empowering Vanuatu: Harnessing Data Science and Technology to Boost Agricultural Productivity and Enhance Livelihoods Phase 2: Development of Innovations (4-14 months) Outcomes Management Information System developed to enhanced agricultural productivity and livelihoods. Machine learning model developed to improve welfare data in real time through mapping farms, identify crop types, and estimate agricultural production. Governance Structure to Coordinate and give Strategic Direction to the Project maintained. Budget= $200,000 USDs Initial thoughts: Well-constructed proposal in a useful and relevant area. Link with 2023 Citizen Generated Data, but in a less sensitive area than GBV. Similar approach to current Vanuatu experiment that is in implementation now. Phase 3: Implementation of Innovations (14-18 months) Outcomes Awareness of CGD system enhanced within community, improving uptake of the Innovation Capacity of the Government of Vanuatu to collect and make accessible quality agricultural, local & global trade, and weather statistics improved Budget= $25,000 USDs Total Budget= $250,000 USDs
From HIES conducted in the Pacific (and other surveys where photos were taken), there is plenty of available information on the following attributes at the household level: Picture of each dwelling. Dwelling characteristics (material used for roof, wall or floor, number of rooms, age of building etc.) With this dataset, we could use machine learning techniques to train a classifier that would predict the dwelling characteristics from a single picture. Once trained and optimised, this model could then infer the characteristics of any dwelling from a single photo. The extended characteristics can then be used in combination with information on the building geographical location (like distance to shore or river, or elevation and slope) extracted via geographical layers and GPS position, to estimate vulnerability to natural disasters. Timeline: est. 3 months SPC Exploration of the use of existing data sources to estimate the vulnerability of dwellings to natural disasters (CWP-1) Initial thoughts: Useful and relevant research testing potential for use of innovative technology to use existing data sources to produce new insights. Focused on an area of high priority for the Pacific region: vulnerability to climate change and natural disasters. Relevant to PACSTAT and PSMB objectives
Codification of occupation is a major challenge. It requires time- consuming manual data entry, and a good comprehension of existing classifications such as ILO s ISCO or ISIC. This codification work could be effectively assisted by an AI-based model. SPC Automatic classification of people occupations with Machine Learning models (Large Language Model, classifier, ...) trained on questionnaire answers We propose to explore 2 options to address this issue: Use of a pre-trained existing Large Language Model (ChatGPT, ...) with effective promptings to predict the best suited occupation code from the answers of the questionnaire (and a list ofcodes) Use of classification model trained on an already existing dataset created out of previous collection and surveys. (CWP-2) Timeline: est. 3 months Initial thoughts: Useful and relevant proposal for research and innovation. Relevant topic for PACSTAT and PSMB. Potential to undertake this jointly with CWP-1 using same consultant
Main activities: SPC (PacStat consultant) Depreciation rate benchmark and core list of durable goods for HIES Carry out literature review on expenditure aggregate, fixed assets and depreciation rate; Conduct analysis of the use value of the durable goods in the expenditure aggregate across Pacific HIES, using different approaches of calculation of depreciation rate; Establish the regional benchmark values of depreciation rates; Analyse the impact of using a limited number of durable goods in order to define the core list of durable goods for HIES. (CWP-4) The proposed research will take around three months, giving time to familiarize with a big number of datasets from different countries and changes in HIES methods over years. Initial thoughts: Strong welfare and methods focus - appropriate for PSMB and PacStat. A benefit is that this would tighten and shorten HIES questionnaire. Has a link to a current Guidance Note (is a separate research project needed?)
This proposal aims to engage a Research Advisor to enhance data collection methods and develop indicators for key socio-economic factors, such as employment, unemployment, poverty, and most crucial indicators also link to National Indicators and SDGs, etc., on a regular basis (monthly and yearly) at Tonga Statistics. By encouraging innovative research techniques and modern technologies, we aim to improve the accuracy, timeliness, and relevance of statistical indicators to support evidence-based decision-making and policy formulation. Tonga Statistics Department Enhancing Data Collection Methods for Improved Statistical Indicators for dissemination (CWP-4) Timeline: c. 8-9 months Estimated budget range: $30,000 - $50,000 Initial thoughts: Review of Tonga methods from collection methods to analysis. Beneficial work for Tonga s National Statistics System, but less fit for aims of PACSTAT regional aims Focus is on strengthening national capacities, rather than supporting overall regional objectives and producing regional guidance.
