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Europe > Ukraine

You are looking at 1 - 4 of 4 items for :

  • Type: Journal Issue x
  • Data Collection and Data Estimation Methodology; Computer Programs: General x
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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 Technical Assistance Reports
Ukraine: Technical Assistance Report-Report on the Residential Property Price Index Mission (April 8–12, 2024)
International Monetary Fund. Statistics Dept.
A technical assistance (TA) mission was conducted from April 8–12, 2024, to assist the State Statistical Service of Ukraine (SSSU) with a methodological review of their House Price Index (HPI). The mission assessed the existing data and methodology used for the compilation of the HPI and made recommendations for improvements as required, in line with international statistical standards. The mission completed the following tasks: (i) undertake a review of the listings data collected by the SSSU and the data preparation being applied, (ii) assess the stratification and hedonic methods used for the HPI, (iii) review the weights and aggregation procedures used to compile the national index, (iv) provide guidance on the dissemination of the HPI, and (v) provide practical training to staff in the SSSU.
Keywords:
RPPI; Residential Property Price Index (RPPI); property prices; real estate prices; macroeconomic statistics; macroprudential policy; financial sector risks.; IMF executive directors; World Bank staff; instrumentalities of the CD recipient; listings data; weight information; Price indexes; Data collection; Land prices; House price indexes; Export fluctuations
Cover Policy Papers
Use of Third-Party Indicators in Fund Reports
International Monetary Fund
Fund staff use indicators developed by other organizations as input into analysis in surveillance and, to a lesser extent, in program work. While the Fund has been able to rely on data and statistics provided by member countries and compiled internally, continued efforts to foster global economic and financial stability require staff to work with indicators drawn from numerous third-party compilers. These indicators of varied qualities are used to measure concepts such as business environment, competitiveness, and quality of governance. It is anticipated that staff will continue to draw on other institutions’ expertise and estimates. This practice is consistent with the Executive Board’s guidance in areas where internal expertise is lacking or limited. It also puts a premium on staff’s understanding of the third-party indicators (TPIs) used to add analytical value, avoid flawed conclusions and presentation, and support traction with the membership. This paper outlines a framework to promote best practice with respect to use of TPIs in Fund reports. The framework will apply to all documents that are subject to the Fund’s Transparency Policy. Staff are encouraged to follow similar guidelines for other Fund documents. It draws on lessons from the current practice in the Fund and other selected international organizations (IOs), and insights from the application of an adapted data quality assessment framework (DQAF) to a subset of TPIs commonly used by Fund staff. Common good practices across IOs include the emphasis on staff judgment, review, and consultation with stakeholders.
Keywords:
PP; third-party indicator; director; fund staff; indicator; staff effort; staff analysis; staff report; Data Quality Assessment Framework (DQAF); Business environment; Corruption; Global
Cover Statistical Capacity Building
Statistical Capacity Building
Case Studies and Lessons Learned
Mr. Thomas K. Morrison

Abstract

IMF technical assistance provided by the Statistics Department--toward assisting IMF member countries in developing the ability to provide reliable and comparable economic and financial data on a timely basis to policymakers and markets--has increased more than fourfold over the past decade. This assistance has proven critical in countries building their statistical capacity so as to come into line with international data standards in an increasingly globalized and electronically interconnected world. Statistical Capacity Building: Case Studies and Lessons Learned presents four case studies drawn from experience in three countries in transition to the market, two of which were also in postconflict situations, in the 1990s and early 2000s: Cambodia, Bosnia and Herzegovina, and Ukraine. Issues of setting, institutional and statistical arrangements, strategies, and implementation are examined, and lessons learned.

Keywords:
M&G; government; BiH Office; donor; country; statistics; NBU staff; State statistics law; developing country government; IMF TA; BiH authorities; Monetary statistics; Commercial banks; Financial statistics; Southeast Asia; Asia and Pacific; Eastern Europe; Global; Central Asia; Real sector statistics; Data collection