Search Results

You are looking at 1 - 10 of 44 items for :

  • "CPI purpose" x
Clear All
International Monetary Fund

and behaviour of the various kinds of index number that are, or might be, used for CPI purposes. In principle, it is necessary to settle what type of index to calculate before going on to consider the best way in which to estimate it in practice, taking account of the resources available. 1.6 The main topics covered in this chapter are as follows: –the origins and uses of CPIs; –basic index number theory, including the axiomatic and economic approaches to CPIs; –elementary price indices and aggregate CPIs; –the transactions, activities and

International Monetary Fund

; –they may produce them themselves for their own consumption; –they may receive them as payments in kind through barter transactions, particularly as remuneration in kind for work done; –they may receive them as free gifts, or transfers, from other economic units. 3.8 The broadest concept of consumption for CPI purposes would be a price index embracing all four categories of consumption goods and services listed above. This set of consumption goods and services may be described as total acquisitions . Total acquisitions are equivalent to the total

International Monetary Fund

data. When such data are being collected, therefore, it is important to recognize that they can be used for PPPs as well as CPIs. PPPs are essentially international deflators which are analogous to the inter-temporal deflators needed for the national accounts of a single country. Thus, while the processing and aggregation of the basic data for CPI purposes should be determined by the needs of the CPI itself, it is appropriate to take account of the requirements of these other kinds of price indices at the data collection stage. There may be important economies of

Statistical Office of the European Communities, International Labour Office, International Monetary Fund, Organization for Economic Co-operation and Development, United Nations, and World Bank

Introduction 8.1 In Chapter 3 it was mentioned that for national accounts and CPI purposes, it will be useful or necessary to have a decomposition of the residential property price index (RPPI) into two components: a quality adjusted price index for structures and a price index for the land on which the house is built. The present chapter outlines how hedonic regression can be utilized to derive such a decomposition. Hedonic regression methods were discussed in Chapter 5 . 8.2 Some economic reasoning will be helpful to derive an appropriate hedonic

Brian Graf

methodology here but simply to note that PPPs create another demand for basic price data. When such data are being collected, it is important to recognize that they can be used for PPPs as well as CPIs. PPPs are essentially international deflators that are analogous to the intertemporal deflators needed for the national accounts of a single country. Thus, while the processing and aggregation of the basic data for CPI purposes should be determined by the needs of the CPI itself, it is appropriate to take into account the requirements of these other kinds of price indices at

Mr. Marshall B Reinsdorf
COVID-19 changed consumers’ spending patterns, making the CPI weights suddenly obsolete. In most regions, adjusting the CPI weights to account for the changes in spending patterns increases the estimate of inflation over the early months of the pandemic. Under-weighting of rising food prices and over-weighting of falling transport prices are the main causes of the underestimation of inflation. Updated CPI weights should be developed as soon as is feasible, but flux in spending patterns during the pandemic complicates the development as quickly as 2021 of weights that represent post-pandemic spending patterns.
International Monetary Fund
This Report on the Observance of Standards and Codes data module provides a review of Senegal’s data dissemination practices against the IMF’s General Data Dissemination System, complemented by an in-depth assessment of the quality of the national accounts, consumer price index, government finance, monetary balance of payments, and income poverty statistics. The assessment reveals that Senegal generally follows the recommendations of this system for the coverage, periodicity, and timeliness of all data categories. Overall, the institutional environment of the data-producing agencies supports statistical quality.
International Monetary Fund
This Report on the Observance of Standards And Codes (ROSC) on data module for Uganda provides an assessment of Uganda’s macroeconomic statistics against the recommendations of the General Data Dissemination System (GDDS) complemented by an assessment of data quality based on the IMF’s Data Quality Assessment Framework. This ROSC data module contains the main observations covering four macroeconomic data sets, namely national accounts, the consumer price index (CPI), government finance statistics (GFS), and balance of payments (BOP). It also provides an overview of the dissemination practices compared with the GDDS.
International Monetary Fund
This report on the Observance of Standards and Codes on Data Module is a summary assessment of Estonia's data practices against the IMF's Special Data Dissemination Standard, complemented by an in-depth assessment of the dimensions of data quality that underlie the national accounts, consumer prices, government finance, monetary, and balance-of-payments statistics. Accuracy and reliability are generally good, but could be improved in a few areas of national accounts and in general government data by strengthening source data and improving statistical techniques.
International Monetary Fund
This data module of the Report on the Observance of Standards and Codes (ROSC) contains a summary assessment of dissemination practices in Ecuador relative to the IMF’s Special Data Dissemination Standard (SDDS). It also presents an assessment of data quality for national accounts, consumer price, producer price, balance of payments, government finance, and monetary statistics, based on the Data Quality Assessment Framework (DQAF). The assessment reveals that Ecuador is in observance of SDDS specifications on coverage, periodicity, timeliness, and dissemination of advance release calendars for data subject to the SDDS.