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.

What are the features of the correlation structure of price indices? To answer this question, 5 types of price indices, including 195 specific price indices from 2003 to 2011, were selected as sample data. To build a weighted network of price indices each price index is represented by a vertex, and a positive correlation between two price indices is represented by an edge. We studied the features of the weighted network structure by applying economic theory to the analysis of complex network parameters. We found that the frequency of the price indices follows a normal distribution by counting the weighted degrees of the nodes, and we identified the price indices which have an important impact on the network's structure. We found out small groups in the weighted network by the methods of k-core and k-plex. We discovered structure holes in the network by calculating the hierarchy of the nodes. Finally, we found that the price indices weighted network has a small-world effect by calculating the shortest path. These results provide a scientific basis for macroeconomic control policies.

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

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.

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.

The Consumer Price Index (CPI) is a measure that examines the weighted average of prices of a basket of consumer goods and services, such as transportation, food, and medical care. It is calculated by taking price changes for each item in the predetermined basket and averaging them. Prices are collected periodically, and the CPI is often used to measure inflation, reflecting the cost of living. The CPI is typically set against a base year. The index is set to 100 in the base year, and changes in the CPI indicate price changes compared to that year. A typical household might purchase a wide range of products and services. Items in the basket are weighted according to their importance or share in total household spending. The Inflation Rate is the percentage increase in the general level of prices for goods and services over a period of time. It indicates how much prices have risen over a specific period, typically a year. Higher inflation decreases the purchasing power of money, meaning consumers can buy less with the same amount of money.It reflects the overall health of an economy. Moderate inflation is expected in a growing economy, but hyperinflation can indicate economic instability. The Inflation Rate is calculated using the following formula: Inflation Rate (%) = ((CPI in Current Year−CPI in Previous Year)/ (CPI in Previous Year))×100

Japan PPI: W: FBTF: Feedstuff: Formula Feeds data was reported at 4.200 Per 1000 in Dec 2016. This stayed constant from the previous number of 4.200 Per 1000 for Nov 2016. Japan PPI: W: FBTF: Feedstuff: Formula Feeds data is updated monthly, averaging 4.200 Per 1000 from Jan 1980 (Median) to Dec 2016, with 444 observations. The data reached an all-time high of 4.200 Per 1000 in Dec 2016 and a record low of 4.200 Per 1000 in Dec 2016. Japan PPI: W: FBTF: Feedstuff: Formula Feeds data remains active status in CEIC and is reported by Bank of Japan. The data is categorized under Global Database’s Japan – Table JP.I097: Producer Price Index: 2010=100: Weight.

Japan IMPI: W: GM: Other GM: OM: Electronic Calculating Machines data was reported at 0.900 Per 1000 in May 2012. This stayed constant from the previous number of 0.900 Per 1000 for Apr 2012. Japan IMPI: W: GM: Other GM: OM: Electronic Calculating Machines data is updated monthly, averaging 0.900 Per 1000 from Jan 2005 (Median) to May 2012, with 89 observations. The data reached an all-time high of 0.900 Per 1000 in May 2012 and a record low of 0.900 Per 1000 in May 2012. Japan IMPI: W: GM: Other GM: OM: Electronic Calculating Machines data remains active status in CEIC and is reported by Bank of Japan. The data is categorized under Global Database’s Japan – Table JP.I365: Import Price Index: 2005=100: Weight.

Graph and download economic data for Nominal Broad U.S. Dollar Index (DTWEXBGS) from 2006-01-02 to 2025-08-15 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 yea.

Data for the 'All-items' index is available below; more data is available in the Knowledge Databases (Retail prices) and News releases (Price indices of consumer goods and services); monthly data (year 1998=100), calculated for analytical purposes with the use of the chain-linking method, is available in the SDDS database (Consumer Prices > Data for earlier periods).

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.

In der vorliegenden Datenkompilation werden die wichtigsten Gruppenindizes der Erzeugerpreise landwirtschaftlicher Produkte in Form von langen Reihen mit unterschiedlichen Basisjahren in Übersichten für ausgewählte Indexpositionen dargestellt. Der Index misst die Entwicklung der Verkaufspreise der Landwirtschaft beim Absatz im Inland. Die Bezugsgröße des Gesamtindex ist der Wert der Verkaufserlöse der Landwirtschaft im Basisjahr. Im Hinblick auf die wesentlichen Rechenvorgänge können die Indizes als gewogene Durchschnitte aus den Preisveränderungszahlen bezeichnet werden, die für eine repräsentative Auswahl von Produkten bzw. Leistungen gebildet werden. Bei den Preisindizes landwirtschaftlicher Produkte werden die Jahresdurchschnittszahlen durch Wägung der Vierteljahresdurchschnittsmesszahlen der einzelnen Waren mit den entsprechenden Vierteljahresumsätzen im jeweiligen Basisjahr gebildet. Die Indizes werden nach der sog. Laspeyres-Formel berechnet. Das bedeutet, dass die aus dem Basisjahr stammenden Wägungszahlen bis zur Umstellung der Indizes auf eine neues Basisjahr unverändert bleiben. Die Indizes der Erzeugerpreise landwirtschaftlicher Produkte werden nicht nur als Gesamtindex, sondern auch für verschiedene Aggregationsstufen (Produktgruppen) bis hin zu einzelnen Preisrepräsentanten veröffentlicht. In den vorliegenden langfristigen Übersichten wird lediglich die Aggregation nach Produktgruppen berücksichtigt. Bis einschließlich dem Wirtschaftsjahr 1966/67 wurden die Indizes einschl. Umsatz-(Mehrwert-) steuer berichtet. Seit dem Wirtschaftsjahr 1967/68 werden die Indexergebnisse in den Publikationen des Statistischen Bundesamtes doppelt dargestellt, d.h. sowohl ohne als auch einschließlich (pauschalierter) Mehrwertsteuer. In der vorliegenden Datenkompilation werden in den Tabellen der Erzeugerpreise landwirtschaftlicher Produkte die Indizes ab dem Jahr 1968 ausschließlich ohne Umsatz-(Mehrwert-)steuer und ohne Aufwertungsausgleich dargestellt! Datentabellen in HISTAT:Index der Erzeugerpreise landwirtschaftlicher Produkte: Wirtschaftsjahre 1950/51 = 100 und Originalbasis Wirtschaftsjahr 1950/51 = 100, umbasiert auf 1938/39 = 100. Wirtschaftsjahr 1962/63 = 100. Basisjahre 1970, 1976, 1980, 1985, 1991, 1995, 2000 = 100. 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)

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 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.

Quarterly estimates of productivity in the total economy and in the industries are derived from a Fisher chained index of gross domestic product (GDP). The approach to measure the GDP in the total economy differs from the one that used in the estimates by industry. For the total economy, GDP is measured using the expenditure approach at market prices published by the Quarterly Income and Expenditure Accounts. For the estimates by industry, GDP is measured using the value added approach at basic prices published by the Industry Accounts Division. This was the Fisher chained index in the case of years for which final input-output tables are available. For the most current years or annual post-benchmarks, the real GDP is based on a fixed-weight Laspeyres chained index formula. GDP estimates in the productivity measures for the businesses producing services and for real estate, and rental and leasing exclude the rental value of owner occupied dwellings. The estimate of the total number of jobs covers four main categories: employee jobs, work owner of an unincorporated business, own account self-employment, and unpaid family jobs. The last category is found mainly in sectors where family firms are important (agriculture and retail trade, in particular). Jobs data are consistent with the System of National Accounts. This is the quarterly average of hours worked for jobs in all categories. The number of hours worked in all jobs is the quarterly average for all jobs times the annual average hours worked in all jobs. Hours worked data are consistent with the System of National Accounts. According to the retained definition, hours worked means the total number of hours that a person spends working, whether paid or not. In general, this includes regular and overtime hours, breaks, travel time, training in the workplace and time lost in brief work stoppages where workers remain at their posts. On the other hand, time lost due to strikes, lockouts, annual vacation, public holidays, sick leave, maternity leave or leave for personal needs are not included in total hours worked. Labour productivity is the ratio between real GDP and hours worked. For the estimates of productivity in the total economy, a Fisher chain index of GDP at market prices is used as measure of the output. On the other hand, in the quarterly productivity estimates for the industries, a Fisher chain index of GDP at basic prices for each industry is used as measure of the output up to the last year benchmark for which final input-output tables are available, after that by a fixed-weight volume Laspeyres chained index formula for the most recent years. The ratio between total compensation for all jobs, and the number of hours worked. The term hourly compensation" is often used to refer to the total compensation per hour worked." This measures the cost of labour input required to produce one unit of output, and equals labour compensation in current dollars divided by the real output. It is often calculated as the ratio of labour compensation per hour worked and labour productivity. Unit labour cost increases when labour compensation per hour worked increases more rapidly than labour productivity. It is widely used to measure inflation pressures arising from wage growth. The measure of real value added used in the labour unit cost estimation is based on a Fisher chain index excluding the rental value of owner occupied dwellings. The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply side or production oriented principles, to ensure that industrial data, classified to NAICS, is suitable for the analysis of production related issues such as industrial performance. Since 1997, the System of National Accounts' (SNA) input-output industry classification system is based on NAICS. In the National Accounts industries, the levels of the different classification systems were chosen so as to provide the most detail possible in order to maximise continuity with the previous classification systems used in Statistics Canada since 1961. Therefore, the greatest level of detail that is available over time occurs at the L level of aggregation, which corresponds, to 105 industries. This L level can also be aggregated to the M level (medium - 56 industries) and to the S level (small - 21 industries). This combines the business establishments of the North American Industry Classification System (NAICS) codes 11, 21, 22, 23, 31-33. This combines the business establishments of the North American Industry Classification System (NAICS) codes 41, 44-45, 48-49, 51, 52, 53, 54, 55, 56, 61, 62, 71, 72, 81. The Gross Domestic Product (GDP) used to measure productivity excludes rent value for owner occupied dwellings from the business service producing industries. This combines the business establishments of the North American Industry Classification System (NAICS) code 53. The gross domestic product (GDP) used to measure productivity excludes rent value for owner occupied dwellings from this industry code. This combines the business establishments of the North American Industry Classification System (NAICS) codes 61, 62, 81. This combines the part of non-business establishments of the North American Industry Classification System (NAICS) codes 11-91, but also including the owner occupied dwellings industry and the private households. Total economic activities that have been realized within the country. That covers both business and non-business sectors. Unit labour cost in United States dollars is the equivalent of the ratio of Canadian unit labour cost to the exchange rate. This latter corresponds to the United States dollar value expressed in Canadian dollars. This combines the business establishments of the North American Industry Classification System (NAICS) codes 52 and 55.

Sources:

Publications of the official statistics, edited by the Federal Statistical Office, Wiesbaden): - Statistisches Jahrbuch für die Bundesrepublik Deutschland; - Fachserie M, Preise, Löhne, Wirtschaftsrechnungen. Reihe 1, Preise und Preisindices für Außenhandelsgüter: Einfuhr- und Ausfuhrpreise; - Fachserie 17, Preise. Reihe 8, Preisindizes für die Ein- und Ausfuhr; Fachserie 17, Preise. Reihe 8.1, Preisindizes für die Einfuhr 2007. (www.destatis.de). Fachserie 17, Preise. Reihe 8.2, Preisindizes für die Ausfuhr 2007. (www.destatis.de).

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)

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.

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).