Consumer price indexes (CPIs) are index numbers that measure changes in the prices of goods and services purchased or otherwise acquired by households, which households use directly, or indirectly, to satisfy their own needs and wants. In practice, most CPIs are calculated as weighted averages of the percentage price changes for a specified set, or ‘‘basket’’, of consumer products, the weights reflecting their relative importance in household consumption in some period. CPIs are widely used to index pensions and social security benefits. CPIs are also used to index other payments, such as interest payments or rents, or the prices of bonds. CPIs are also commonly used as a proxy for the general rate of inflation, even though they measure only consumer inflation. They are used by some governments or central banks to set inflation targets for purposes of monetary policy. The price data collected for CPI purposes can also be used to compile other indices, such as the price indices used to deflate household consumption expenditures in national accounts, or the purchasing power parities used to compare real levels of consumption in different countries.

In an effort to further coordinate and harmonize the collection of CPI data, the international organizations agreed that the International Monetary Fund (IMF) and the Organisation for Economic Cooperation and Development (OECD) would assume responsibility for the international collection and dissemination of national CPI data. Under this data collection initiative, countries are reporting the aggregate all items index; more detailed indexes and weights for 12 subgroups of consumption expenditure (according to the so-called COICOP-classification), and detailed metadata. These detailed data represent a valuable resource for data users throughout the world and this portal would not be possible without the ongoing cooperation of all reporting countries. In this effort, the OECD collects and validates the data for their member countries, including accession and key partner countries, whereas the IMF takes care of the collection of data for all other countries.

The package includes the weights of the house price index. “Weight” means the percentage or promil of the relative share of household monetary expenditure for the purchase of land-based housing belonging to the basic population of the CCI. The higher the weight, the greater the impact of a change in the price level of a land-based housing classification on the price development of a higher level of land-based housing classification. “Weight reference period” means the period during which the weight of the index is calculated. The following procedures for checking and editing the statistics received are carried out: rejecting transactions in which the purchased dwellings are unfit for life due to a lack of completion (< 80%), analysing the purchase-sale transaction data of the dwellings attributed to each basic whole compared to the previous quarters. The editing and validation of data shall be carried out using a computer program for checking price statistics. The resulting price trends are compared to the trends in house prices recorded by real estate agencies. Information on factors influencing changes in house prices is regularly monitored in the press, surveys and reports published by other companies and institutions. The main source of statistical data for the calculation of the CCI is the data of the Real Property Register of the Centre of Registers of the SE and the databases of transactions. Source data is obtained quarterly. The BKI base period is 2015 (2015: 100). Another change to the CCI base period is foreseen for 2026, the former time line will be converted into a new index base period and published after calculation in QI 2026. CCI

The index relates to costs ruling on the first day of each month. NATIONAL HOUSE CONSTRUCTION COST INDEX; Up until October 2006 it was known as the National House Building Index Oct 2000 data; The index since October, 2000, includes the first phase of an agreement following a review of rates of pay and grading structures for the Construction Industry and the first phase increase under the PPF. April, May and June 2001; Figures revised in July 2001due to 2% PPF Revised Terms. March 2002; The drop in the March 2002 figure is due to a decrease in the rate of PRSI from 12% to 10¾% with effect from 1 March 2002. The index from April 2002 excludes the one-off lump sum payment equal to 1% of basic pay on 1 April 2002 under the PPF. April, May, June 2003; Figures revised in August'03 due to the backdated increase of 3% from 1April 2003 under the National Partnership Agreement 'Sustaining Progress'. The increases in April and October 2006 index are due to Social Partnership Agreement "Towards 2016". March 2011; The drop in the March 2011 figure is due to a 7.5% decrease in labour costs. Methodology in producing the Index Prior to October 2006: The index relates solely to labour and material costs which should normally not exceed 65% of the total price of a house. It does not include items such as overheads, profit, interest charges, land development etc. The House Building Cost Index monitors labour costs in the construction industry and the cost of building materials. It does not include items such as overheads, profit, interest charges or land development. The labour costs include insurance cover and the building material costs include V.A.T. Coverage: The type of construction covered is a typical 3 bed-roomed, 2 level local authority house and the index is applied on a national basis. Data Collection: The labour costs are based on agreed labour rates, allowances etc. The building material prices are collected at the beginning of each month from the same suppliers for the same representative basket. Calculation: Labour and material costs for the construction of a typical 3 bed-roomed house are weighted together to produce the index. Post October 2006: The name change from the House Building Cost Index to the House Construction Cost Index was introduced in October 2006 when the method of assessing the materials sub-index was changed from pricing a basket of materials (representative of a typical 2 storey 3 bedroomed local authority house) to the CSO Table 3 Wholesale Price Index. The new Index does maintains continuity with the old HBCI. The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. Oct 2008 data; Decrease due to a fall in the Oct Wholesale Price Index.

Graph and download economic data for Nominal Broad U.S. Dollar Index (DTWEXBGS) from 2006-01-02 to 2025-03-21 about trade-weighted, broad, exchange rate, currency, goods, services, rate, indexes, and USA.

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)

Price index of consumer goods and services is calculated on the basis of the results of:
- surveys on prices of consumer goods and services on the retail market,
- surveys on household budgets, providing data on average expenditures on consumer goods and services; these data are then used for compilation of a weight system.

Calculating price index of consumer goods and services is done on the basis of the Classification of Individual Consumption by Purpose (COICOP) adapted for the use of Harmonized Indices of Consumer Prices (HICP).

The price index of a representative in the region included in the price survey results from relating its average monthly price to an average annual price from the previous yea The all-Polish price index of a representative included in the survey is calculated as geometric mean of price indices from all regions. Calculating price indices of groups of consumer goods and services at the lowest level of weight system aggregation is done on the basis of price indices of the representatives included in price survey in a given group by using geometric mean. They are then used by applying weight system to calculate indices of higher level of aggregation up to the price index of total consumer goods and services. price index is calculated in line with the Laspeyress’s formula by applying weights from the year preceding the reference year.

This study deals with the price development of import and export goods as a part of transactions carried out in the context of foreign trade. On the basis of the foreign trade price statistics (as part of the official statistics), the trend of prices shall be constantly monitored. For this special purpose foreign trade price indices are calculated. Foreign trade price indices measures the price trends of all goods traded between the Federal Republic of Germany and abroad. The reference parameter of the overall indices of import or export prices is the sum of import values and export values in the base year, as they are detected by the external trade statistics. In regard to the main calculation processes, the indices can be seen as the weigthed average of individual price change figures, which were calculated for a representative selection of import and export goods (the so called price representatives, or ‘Preisrepräsentanten’). The import and export values of those results of the base year’s event, for which a specific price range is considered to be representative, serves as weighting figures or weighting pattern. The index is calculated by using the so called Laspayres-formula.

With the aim to collect import and export prices monthly surveys of import and export enterprises are made. In the framework of these surveys the prices of about 6500 selected products are gathered. Information on the reporting month average prices of all contracts is collected. The reported prices are actual prices charged and not list prices, and they refer to the value ‘free German border / frei deutsche Grenzen” (‘cif’ for import prices, and ‘fob’ for export prices). Public charges (i.e. taxes, customs duties, absorptions, monetary compensatory amounts, import turnover tax ) are not enclosed into this prices . In foreign currency reported prices are converted on the basis of the current exchange rate. About 2980 reporting departments collecting 13000 price series.

Foreign trade indices: Foreign trade indices are not only calculated and published for the entire import and export prices, but also for a large number of commodities of various aggregation levels. The export prices are published according to the following commodity systematics: a) commodity group of food industry and manufacturing sectors b) according to the predominant use of commodities, a classification, which serves primarily to distinguish between capital and consumer goods c) according to one- and two-digit items of the international foreign trade commodity index d) according to selected items of the systematic nomenclature of goods for the production statistics.

The present data collection is on the basis of a) and d).

Data tables in the search and download system HISTAT (topic: foreign trade / Außenhandel): Study description and data description in HISTAT only available in German.

A. Overvies

A.01 Übersicht: Index der Ausfuhrpreise (1954-2005) (index of export prices) A.02 Übersicht: Index der Einfuhrpreise (1950-2005) (index of import prices) A.03 Terms of Trade (1954-2005)

B. Data tables by commodity groups of the foreign trade

B.01 Warengruppen: Index der Ausfuhrpreise (1954 -2005) (Index of export prices) B.02 Warengruppen: Index der Einfuhrpreise (1950-2005) (index of import prices)

C. Data tables according to production management context

C.01a Produktionswirtschaftlicher Zusammenhang: Index der Ausfuhrpreise ausgewählter Gütergruppen, bis Basisjahr 1991=100 (1954-1998) (index of export prices of selected commodity groups, up to base year 1991=100) C.01b Produktionswirtschaftlicher Zusammenhang: Index der Ausfuhrpreise ausgewählter Gütergruppen, veränderte Systematik, Basisjahre 1995/2000=100 (1994-2005) (index of selected commodity groups, changed systematics, base years 1995/2000=100) C.02a Produktionswirtschaftlicher Zusammenhang: Index der Einfuhrpreise ausgewählter Gütergruppen, bis Basisjahr 1991=100 (1950-1998) (Index of import prices of selected commodity groups, up to base year 1991=100) C.02b Produktionswirtschaftlicher Zusammenhang: Index der Einfuhrpreise ausgewählter Gütergruppen, veränderte Systematik, Basisjahre 1995/2000=100 (1994-2005) (Index of import prices of selected commodity groups, changed systematics, base years 1995/2000=100)

This dataset provides quarterly truck rates for select Brazilian soybean-export routes (designated by origin and destination).

This dataset is also used to calculate a weighted-average truck rate, which can be viewed here: https://agtransport.usda.gov/d/i4ty-m7hq. A share associated with each row is used to define the weight of a given route's freight price in the composition of the weighted freight index. This calculation is made based on the quantity of production in the route's mesoregion as that quantity relates to the total produced by all mesoregions considered in the project. In 2020, the selected mesoregions represented about 81 percent of national production, so the shares will not sum to one.

The Chinese economy has undergone a long-term transition reform, but there is still a planned economy characteristic in the financial sector, which is financial repression. Due to the existence of financial repression, China’s actual interest rate level should be lower than the Consumer Price Index (CPI). However, based on official China’s interest rates and CPI, over half of the years China’s actual interest rate remained higher than CPI by our calculation from 1999 to 2022. This is inconsistent with the financial repression that exists in China, and the main reason is the calculation methods of China’s CPI. China’s CPI measurement system originated from the planned economy era, which did not fully consider the rise in housing purchase prices, so the current CPI measurement system can be more realistically presented by taking the rise in housing prices into consider. The core idea of this study is to mining relevant official statistical data and calculate the proportion of Chinese residents’ expenditure on purchasing houses to their total expenditure. By taking the proportion of house purchases as the weight of house price factor, and taking the proportion of other consumption as the weight of official CPI, the Generalized CPI (GCPI) is formulated. The GCPI is then compared with market interest rates to determine the actual interest rate situation in China over the past 20 years. This study has found that if GCPI is used as a measure, China’s real interest rates have been negative for most years since 1999. Chinese residents have suffered the negative effects of financial repression over the past 20 years, and their property income cannot keep up with the actual losses caused by inflation. Therefore, it is believed that China’s CPI calculation method should be adjusted to take into account the rise in housing prices, so China’s actual inflation level could be more accurately reflected. In view of the above, deepening interest rate marketization reform and expand channels for financial investment are the future development goals of China’s financial system.

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.

Abstract

The Montenegro Household Budget Survey (HBS) 2015 collects data about incomes, expenditures and consumption of households, i.e., data about primary elements of personal consumption, as well as data about some important indicators of living standard (dwelling conditions, possession of permanent goods, etc.) and primary data about demographic, economical and sociological characteristics of households.

This survey provides data necessary for producing the balance of personal consumption in the NA system, and data necessary for obtaining the weights used for the calculation of CPI. The data obtained through this survey are also used for producing the poverty line.

The aim of the Household Budget Survey is: - to calculate data for the balance of personal consumption within the National Accounts System; - to create a database for obtaining the weight for the calculation of consumer price index; - to serve as the main source of data for production on poverty lines and analyses (consumption method).

Geographic coverage

National

Analysis unit

The survey unit is a household.

The term household refers to: a) Single person living, spending and feeding individually; b) Community of persons living, feeding and spending received income together.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the survey is two-stage stratified sample, with enumeration areas as primary and household as secondary selection units. On annual level, the sample consists of 1824 households, each month 19 enumeration areas, i.e. 152 households are selected. The 2015 survey examined 1318 households which make the 72.26% response rate.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey uses the questionnaire based interview method, where the reference period for permanent goods is 12 months, for semi-durables 3 months, using the diary (household is running the consumption diary in the reference month).

进口价格指数：W：GM：其他通用机械设备：OM：电子计算机器在05-01-2012达0.900Per 1000，相较于04-01-2012的0.900Per 1000保持不变。进口价格指数：W：GM：其他通用机械设备：OM：电子计算机器数据按月更新，01-01-2005至05-01-2012期间平均值为0.900Per 1000，共89份观测结果。该数据的历史最高值出现于05-01-2012，达0.900Per 1000，而历史最低值则出现于05-01-2012，为0.900Per 1000。CEIC提供的进口价格指数：W：GM：其他通用机械设备：OM：电子计算机器数据处于定期更新的状态，数据来源于日本銀行，数据归类于全球数据库的日本 – Table JP.I365: Import Price Index: 2005=100: Weight。