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Computers > Data Processing

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Cover Technical Assistance Reports
Ukraine: Technical Assistance Report-Report on Residential Property Price Index (RPPI) Mission (July 15–19, 2024)
International Monetary Fund. Statistics Dept.
A technical assistance (TA) mission was conducted from July 15–19, 2024, to assist the State Statistical Service of Ukraine (SSSU) to develop new processes and methods for the compilation of the House Price Index (HPI). This was the second mission of a project that commenced in April 2024. The mission worked closely with the authorities to (i) develop R scripts to clean the listings data received from an online real estate platform, (ii) implement updated methods for index compilation, and (iii) increase the capacity of the SSSU staff.
Keywords:
House Price Index; Residential Real Estate Price Index; Macroeconomic Statistics; Real Estate; Housing Market; Property Values; Price Appreciation; Inflation; Economic Indicators; Residential Properties; Ukraine.; IMF's statistics department; Property price index; section I.; IMF executive directors; instrumentalities of the CD recipient; OLX data; Export fluctuations; Real estate prices; Land prices; Data processing; Data collection
Cover FinTech Notes
Central Bank Digital Currency Data Use and Privacy Protection
Kieran P Murphy
,
Tao Sun
,
Yong Sarah Zhou
,
Natsuki Tsuda
,
Nicolas Zhang
,
Victor Budau
,
Frankosiligi Solomon
,
Kathleen Kao
,
Morana Vucinic
, and
Kristina Miggiani
This note offers a framework to help countries navigate, as well as tools to help them manage, the trade-offs between CBDC data use and privacy protection. It addresses retail CBDC, as data access and privacy-preserving considerations in a wholesale environment are similar to those of the traditional RTGS systems. It emphasizes the role of institutional arrangements, data collection, access and storage policies, design choices, and technological solutions. At a given level of preference for privacy, central banks can facilitate better use of CBDC data through robust transparency and accountability arrangements, sound policies, and judicious adoption of privacy-by-design approaches including the use of privacy-enhancing technologies.
Keywords:
CBDC; central banks; data use; privacy protection; technology; trust; CBDC data; CBDC design; CBDC stakeholder; IMF Fintech Note 2024/004; Central Bank digital currencies; Data processing; Payment systems; Digital financial services; Anti-money laundering and combating the financing of terrorism (AML/CFT); Global; Europe; data privacy
Cover IMF Working Papers
Has the Transmission of US Monetary Policy Changed Since 2022?
Philip Barrett
and
Josef Platzer
Activity and inflation responded slowly to the Federal Reserve’s rate hikes in 2022. Was this because the transmission of monetary policy had changed? Or did other shocks offset tighter policy? We use pre-pandemic data to estimate a VAR with monetary policy shocks identified from high-frequency data, and use it as a filter to back out the sequence of monetary policy shocks consistent with data since 2022. We compare these implied shocks to the actual shocks and find the difference statistically significant during February-July 2022. These differences imply that monetary transmission was around 25 percent weaker than normal. Our method accounts for other shocks; allowing them to change to match the post-COVID covariance of the data produces similar results but in a shorter period. We decompose changes in the uncertainty of our estimate and find that colinearity of shocks is generally more important than uncertainty over model parameters. We extend our analysis to central bank information shocks and find Federal Reserve communication was less powerful than usual during 2021.
Keywords:
Monetary Policy; Semi-structural Identification; VAR; Filtering; rate hike; monetary policy shock; transmission of monetary policy; pandemic data; Federal Reserve communication; Vector autoregression; Data processing; Inflation; COVID-19; Labor markets; Global
Cover Technical Assistance Reports
Republic of Moldova: Technical Assistance Report-Report on Consumer Price Index Mission (September 11-15, 2023)
International Monetary Fund. Statistics Dept.
New data sources are now available in many countries to supplement direct collection of prices for the consumer price index (CPI). This technical assistance mission supported the National Bureau of Statistics of the Republic of Moldova with incorporating scanner data from the State Tax Service of the Republic of Moldova electronic sales monitoring system into the CPI.
Keywords:
Republic of Moldova; Prices; Inflation; Big Data.; IMF's Statistics department; section I.; instrumentalities of the CD recipient; World Bank staff; CPI software; Consumer price indexes; Price indexes; Housing; Data processing; Global
Cover IMF Working Papers
Predicting IMF-Supported Programs: A Machine Learning Approach
Tsendsuren Batsuuri
,
Shan He
,
Ruofei Hu
,
Jonathan Leslie
, and
Flora Lutz
This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML prediction results relative to traditional econometric approaches, explores non-linear relationships among predictors indicative of IMF-supported programs, and evaluates model robustness with regard to different feature sets and time periods. ML models consistently outperform traditional methods in out-of-sample prediction of new IMF-supported arrangements with key predictors that align well with the literature and show consensus across different algorithms. The analysis underscores the importance of incorporating a variety of external, fiscal, real, and financial features as well as institutional factors like membership in regional financing arrangements. The findings also highlight the varying influence of data processing choices such as feature selection, sampling techniques, and missing data imputation on the performance of different ML models and therefore indicate the usefulness of a flexible, algorithm-tailored approach. Additionally, the results reveal that models that are most effective in near and medium-term predictions may tend to underperform over the long term, thus illustrating the need for regular updates or more stable – albeit potentially near-term suboptimal – models when frequent updates are impractical.
Keywords:
Early warning systems; IMF Lending; Machine Learning; IMF arrangement; ML model; machine learning approach; state-of-the-art machine learning; machine learning model; Emergency assistance; Data processing; Global financial crisis of 2008-2009; Global
Cover IMF Staff Country Reports
Botswana: Technical Assistance Report-National Accounts Mission
International Monetary Fund. Statistics Dept.
This Technical Assistance report on Botswana focuses on details of National Accounts mission. The draft Census of Economic Establishments (CEE) questionnaires finalized during the previous mission in March 2023, have been tested. Some improvements were identified and have been incorporated into the CEE questionnaires. The mission and team commenced development of the data collection and data processing manuals. The deflator issues raised by the IMF country team were discussed. The Statistics Botswana (SB) indicated they had resolved these issues after the Ministry of Finance raised the same concern. SB are planning to use the tax list to identify the sample frame for this rebase. SB need to commence discussions with Botswana Unified Revenue Service to determine the sample frame as soon as possible. The sample design will have an impact on the data processing system. The mission reminded the team that they should be consulting now with the Population and Housing Census data processing team to obtain the data required for the rebase.
Keywords:
Rebasing; Census of Economic Establishments (CEE); data collection; data processing; sample frame.; World Bank staff; processing system; Data Processing manual; topic household survey; draft IT specification; IMF executive directors; Housing census data processing team
Cover IMF Staff Country Reports
Botswana: Technical Assistance Report-National Accounts Statistics Mission
International Monetary Fund. Statistics Dept.
This paper presents technical assistance report on National Accounts Statistics mission in Botswana. The mission reviewed and suggested updates of two strategic documents pertaining to the rebase with the national accounts team. The first document broadly outlined the main objectives of a rebase and the key tasks. The second document concentrated on the more detailed implementation strategy. The timeline for the rebasing exercise was reviewed and agreed upon. The data input and processing system development is expected to be undertaken during 2023/24, commencing in May 2023. Therefore, the strategic documents, questionnaire design and sample frame need to be close to final by the end of April 2023. The national accounts team will need to start developing the information technology (IT) data processing system specifications so that in May 2023 they will have something to provide the IT consultant. It is recommended that Statistics Bostwana ensure that all of the required data is collected only once using the Agriculture Census form. Consequently, the national accounts team need to be involved in the development of the Agriculture Census form.
Keywords:
national accounts; rebase; base year; CEE data input; CEE questionnaire; topic household survey; IT data processing system specification; World Bank staff; instrumentalities of the CD recipient; Data processing
Cover IMF Staff Country Reports
Philippines: Technical Assistance Report-Property Price Index Mission
International Monetary Fund. Statistics Dept.
This technical assistance report on Philippines provides details about the Property Price Index mission. The authorities intend to improve the methods used for the Residential Real Estate Price Index and publish the Commercial Property Price Index (land only) for the first time. Some further improvements to the methods should be implemented, including amending the level at which the weights are applied in the aggregation process. The new methodology was evaluated to ensure that it adheres to international compilation standards and best practices. The authorities are committed to increasing the coverage of the statistics to include both cash purchases and other forms of non-bank lending. The existing data source used for the property price statistics are quarterly reports from the commercial banks. The report recommends to increase the capacity of the team with hedonic regression methods through attendance at a training course and/or planning further technical assistance.
Keywords:
Prices Property; property price index mission; World Bank staff; instrumentalities of the TA recipient; price data distribution; title information; RREPI revision; Land prices; Price indexes; Data processing; Research in revenue administration; Commercial banks
Cover IMF Staff Country Reports
Suriname: Technical Assistance Report on Government Finance Statistics Mission (April 19-May 6, 2022)
International Monetary Fund. Statistics Dept.
This technical assistance (TA) mission on Government Finance Statistics was conducted during April 19– May 6, 2022. The main purpose of the mission was to review the progress made by the authorities in implementing previous TA recommendations and provide further support to improve fiscal data compilation and dissemination in line with international standards set out in the Government Finance Statistics Manual 2014.
Keywords:
IMF's Statistics Department; Suriname debt management office; staff team of the International Monetary Fund; debt data; World Bank staff; Government finance statistics; Stocks; External sector statistics; Data processing; Western Hemisphere
Cover IMF Staff Country Reports
Peru: Technical Assistance Report-Consumer Price Index Mission
International Monetary Fund. Statistics Dept.
This technical assistance mission collaborated with the National Institute of Statistics and Informatics in Peru to incorporate big data methods into compilation of the consumer price index (CPI). This includes both prices ingested from the websites of large retailers and data recorded through in-store checkout scanners.
Keywords:
consumer price index mission; scanner data; staff team of the International Monetary Fund; World Bank staff; data provider; Consumer price indexes; Data collection; Data processing; Big data