1-month change in the Adjusted price index based on monthly adjusted consumer expenditure basket weights created by Statistics Canada, in partnership with the Bank of Canada. The Adjusted price index has been updated to incorporate the 2020 basket weights and is now based on a Similarity-linked Fisher price index formula. The expenditure data covers all goods and services in the Consumer Price Index.

United States PPI: Weights: PO: Formula Feeds data was reported at 0.413 % in 2024. This records a decrease from the previous number of 0.432 % for 2023. United States PPI: Weights: PO: Formula Feeds data is updated yearly, averaging 0.381 % from Dec 2007 (Median) to 2024, with 18 observations. The data reached an all-time high of 0.469 % in 2022 and a record low of 0.266 % in 2007. United States PPI: Weights: PO: Formula Feeds data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.I068: Producer Price Index: by Commodities: Weights.

Graph and download economic data for Nominal Broad U.S. Dollar Index (DTWEXBGS) from 2006-01-02 to 2025-07-03 about trade-weighted, broad, exchange rate, currency, goods, services, rate, indexes, and USA.

Singapore Consumer Price Index (CPI): Weights: FFSS: Milk, Cheese & Eggs: Formula Milk Powder data was reported at 0.270 % in Dec 2024. This stayed constant from the previous number of 0.270 % for Nov 2024. Singapore Consumer Price Index (CPI): Weights: FFSS: Milk, Cheese & Eggs: Formula Milk Powder data is updated monthly, averaging 0.270 % from Jan 2014 (Median) to Dec 2024, with 132 observations. The data reached an all-time high of 0.270 % in Dec 2024 and a record low of 0.270 % in Dec 2024. Singapore Consumer Price Index (CPI): Weights: FFSS: Milk, Cheese & Eggs: Formula Milk Powder data remains active status in CEIC and is reported by Singapore Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.I007: Consumer Price Index: 2019=100: Weights.

1-month change in the Adjusted price index based on monthly adjusted consumer expenditure basket weights created by Statistics Canada, in partnership with the Bank of Canada. The Adjusted price index has been updated to incorporate the 2020 basket weights and is now based on a Similarity-linked Fisher price index formula. The expenditure data covers all goods and services in the Consumer Price Index.

Japan Output Price Index: Mfg: GM: MI: Electronic Calculator data was reported at 98.100 1995=100 in Jun 2005. This stayed constant from the previous number of 98.100 1995=100 for May 2005. Japan Output Price Index: Mfg: GM: MI: Electronic Calculator data is updated monthly, averaging 98.100 1995=100 from Jan 1995 (Median) to Jun 2005, with 126 observations. The data reached an all-time high of 102.900 1995=100 in Apr 1998 and a record low of 96.200 1995=100 in Oct 2000. Japan Output Price Index: Mfg: GM: MI: Electronic Calculator data remains active status in CEIC and is reported by Bank of Japan. The data is categorized under Global Database’s Japan – Table JP.I288: Output Price Index: Gross Weighted: 1995=100: Major Commodity.

Dataset includes condensed results from o-DGT contaminant analysis following deployment in urban stormwater ponds, calculation of sampling rates, and calculation of time-weighted average concentrations in water.

Abstract

Transition to free economic structure and, as a consequence, processes of privatization of large agricultural and industrial organizations and birth of numerous new economic entities led to significant changes in quantitative and qualitative characteristics of industrial organizations and peasant farms in RA. During the last decade and especially the last 4-5 years, the structural changes, in their turn, caused also certain complications in the mentioned fields in terms of ensuring collection, comprehensiveness and reliability of statistical data on prices and pricing.

In particular, in case of radical structural changes, international recommendations require the weights upon which price indexes are based to be periodically updated. In order to have a real picture and dynamics of the present situation on creation of indicators for new base year, i.e. collection of information on set of goods-representatives, their weights, average annual prices, prices and price changes, it would be necessary to periodically conduct sample surveys for further improvement of the methodology for price index calculation.

The objectives of the survey were: • to improve the sample, develop a new sample, • to revise the base year and weights, • to receive additional information on prices of sales of industrial, agricultural product and purchase (acquisition of production means) in RA, • to improve methodology for price observation and calculation of price indexes (survey technology, price and other necessary data collection, processing, analyzing), • to revise the base year for producer price indexes, components structure, shares, calculation mechanism, etc., • to derive price indexes that would be in line with the international definitions, standards and classifications, • to complement the NSS RA price indexes database and create preconditions for its regular updating, • to update the information on economic units covered by price indexes calculation, • to ensure use of international standards and classifications in statistics, • to form preconditions for extension of sample observation mechanisms in the state statistics.

Besides the above mentioned, the need of the given survey was also stipulated by the following reasons: - a great mobility of micro-sized, small and medium-sized organizations mainly caused by increased speed of their births, activity and produced commodity changes or deaths that decreases the opportunity to create long-term fixed-base time series of prices and price indexes, - According to the CPA classification coding and recoding activities related to the introduction of Armenian classification of economic activities - NACE (based on the European Communities’ NACE classification).

Geographic coverage

National

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN

Agriculture The sample of the survey was desighned in the conditions of lack of farm register. The number of peasant farms was calculated and derived by database analysis. The number of villages (quotas) selected from each marz was determined taking into account the percent of rural population of marzes. The villages from marz were selected randomly. The peasant farms covered by the survey were selected based on number of privatized plots. The survey was carried out in 200 rural communities selected from 10 marzes, in 5-20 households from each community. Pilot survey was conducted with 1 901 farms in the sample.

Industry The sample frame for the survey was designed as follows: 1. The industrial organizations with share 5 and more percent have been selected by reduction method from fifth level (each subsection) of NACE for whole RA industry. 476 out of 2231 industrial organizations covered by statistical observation were selected for pilot survey.

1. 70 organizations suggested by Industry statistics division of NSS RA and 70 organizations included in state observations on prices conducted previously by the NSS RA (in all 140 organizations), which are considered important and representative for price observation and excluded from the above-mentioned sample, were separated from the general population. These organizations have also been included in sample population of the pilot survey. As it became obvious from further work, the sample covered both the large and medium-sized and the small and micro-sized organizations, which ensured the representativeness of separate branches of industry and organizations by size. As a result, given by the objective of the survey, as well as available financial constraints, the sample population of the pilot survey comprised 616 industrial organizations, the volumes of produced production of whichaccording to the data for January-October of 2006 comprised more than 86% of total volume of RA industrial production. 165 (92.7%) out of 178 classes of NACE were covered by the sample.

Mode of data collection

Face-to-face [f2f]

The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 1999-2001. They are based on the sum of price-weighted quantities of different agricultural commodities produced after deductions of quantities used as seed and feed weighted in a similar manner. The resulting aggregate represents, therefore, disposable production for any use except as seed and feed. The commodities covered in the computation of indices of agricultural production are all crops and livestock products originating in each country. Practically all products are covered, with the main exception of fodder crops.

Net Production Index Number (PIN) base 1999-2001

Presents Net Production (Production - Feed - Seed) indices. All indices are calculated by the Laspeyres formula. Net production quantities of each commodity are weighted by 1999-2001average international commodity prices and summed for each year. To obtain the index, the aggregate for a given year is divided by the average aggregate for the base period 1999-2001. Indices are calculated from net production data presented on a calendar year basis.

In the present data compilation the most important group indices of producer prices of agricultural products in form of long series with different base years will be presented in overviews for selected index positions. The index measures the development of selling prices in agriculture in domestic sales.The reference value of the overall index is the value of sales revenues in agriculture in the base year. In respect of the essential calculating process, the indices can be understood as a weighted average of price changes that are calculated for a representative selection of products and services. The price indices of agricultural products are calculated as the annual averages of the estimated average values on a quarterly basis of the goods with the corresponding quarterly sales in the current base year. The indices are calculated with the so called Laspeyres- formula. This means that the estimated numbers from the base year will be unchanged until the conversion of the indices into a new base year.The indices of the producer prices of agricultural products will not only be published as an overall index, but also for different levels of aggregation (product groups) and for single price representatives. In the present long term overviews only the aggregation concerning product types will be considered. Up to and including 1966/67 the reported indices include the betterment and/or sales tax. Since 1967 the index results appear twice in the publications of the federal statistical office; with and without the generalized betterment tax. In the present data compilation the indices in the tables of producer prices of agricultural products by the year of 1968 will be shown exclusively without betterment or sales tax and without upgrading compensation! Data tables in HISTAT:Index of producer prices of agricultural products: marketing years1950/51 = 100 and original base marketing year 1950/52 base changes to 1938/39=100. Base years 1970, 1976, 1980, 1985, 1991, 1995, 2000 = 100. Register of the tables in HISTAT: A.00a Index of producer prices of agricultural products, original base marketing year 1950/51=100 (1938-1959)A.00b Index of producer prices of agricultural products, original base marketing year 1950/51, base changed to 1938/39 = 100 (1938-1958)A.01 Overview: Index of producer prices of agricultural products, long series, originals base marketing year 1962/63 (1950-1972)A.02 Overview: Index of producer prices of agricultural products, long series, originals base marketing year 1970 (1961-1977)A.03 Overview: Index of producer prices of agricultural products, long series, originals base marketing year 1976 (1961-1981)A.04 Overview: Index of producer prices of agricultural products, long series, originals base marketing year 1980 (1961-1987)A.05 Overview: Index of producer prices of agricultural products, long series, originals base marketing year 1985 (1963-1995)A.06 Overview: Index of producer prices of agricultural products, long series, originals base marketing year 1991 (1970-1999)A.07 Overview: Index of producer prices of agricultural products, long series, originals base marketing year 1995 (1983-2003)A.08 Overview: Index of producer prices of agricultural products, long series, originals base marketing year 2000 (2000-2005)

This table shows the price developments of the stock of existing owner-occupied homes per COROP area. The number of transactions, the average sales price and the total value of the sales prices of the homes sold are also published. The price indices for existing owner-occupied homes are based on an integral registration of sales transactions of homes by the Land Registry and WOZ values ​​of all homes in the Netherlands. Index ranges can fluctuate, for example when the number of transactions in a region is limited. It is then recommended to use the long-term developments of the price indices. The average sales price may show a different development than the price index of existing owner-occupied homes. The development of the average sales price is not an indicator for the price development of existing owner-occupied homes. The method used is the same as that of the Price Index for Existing Owner-occupied Homes (PBK), with the exception of the way in which the housing types are weighted within the region. In the calculation at province level, the housing types are weighted separately and then aggregated to a province figure. In the calculation at COROP level, the housing types are aggregated unweighted. The COROP areas of Utrecht and Flevoland are equal to the provinces of the same name and follow the calculation method of the province. For this reason, the confidence margins in the table are missing for these areas. Data available from: 1st quarter 1995 Status of the figures: The figures in this table are immediately definitive. Changes as of July 24, 2023: Figures for the 2nd quarter of 2023 have been added. When will there be new figures: New figures will be published in October 2023.