Question Paper Solutions of chapter Index Numbers of Business Mathematics and Statistics, Semester III , Bachelors of Commerce (Honours)

Index Numbers of the Costs of Labour and Materials used in Public Sector Construction Projects - Table 615-21001 : Index Numbers of the Costs of Labour and Materials Used in Public Sector Construction Projects ( April 2021 = 100 ) - Costs of Labour Index

Iran Consumer Price Index (CPI): Urban: Food and Non-Alcoholic Beverages (FB) data was reported at 220.400 Apr2016-Mar2017=100 in Jul 2019. This records an increase from the previous number of 216.900 Apr2016-Mar2017=100 for Jun 2019. Iran Consumer Price Index (CPI): Urban: Food and Non-Alcoholic Beverages (FB) data is updated monthly, averaging 166.900 Apr2016-Mar2017=100 from Mar 2018 (Median) to Jul 2019, with 17 observations. The data reached an all-time high of 220.400 Apr2016-Mar2017=100 in Jul 2019 and a record low of 115.800 Apr2016-Mar2017=100 in Mar 2018. Iran Consumer Price Index (CPI): Urban: Food and Non-Alcoholic Beverages (FB) data remains active status in CEIC and is reported by Statistical Centre of Iran. The data is categorized under Global Database’s Iran – Table IR.I002: Consumer Price Index: April 16-March 17=100: Statistical Centre of Iran: Urban.

The dataset contains All India Yearly Industrial Production Index Number from Handbook of Statistics on Indian Economy.

Merchandise Trade Index Numbers - Table 410-51003 : Merchandise Trade Index Numbers - Terms of Trade

Abstract

The Consumer price surveys primarily provide the following: Data on CPI in Palestine covering the West Bank, Gaza Strip and Jerusalem J1 for major and sub groups of expenditure. Statistics needed for decision-makers, planners and those who are interested in the national economy. Contribution to the preparation of quarterly and annual national accounts data.

Consumer Prices and indices are used for a wide range of purposes, the most important of which are as follows: Adjustment of wages, government subsidies and social security benefits to compensate in part or in full for the changes in living costs. To provide an index to measure the price inflation of the entire household sector, which is used to eliminate the inflation impact of the components of the final consumption expenditure of households in national accounts and to dispose of the impact of price changes from income and national groups. Price index numbers are widely used to measure inflation rates and economic recession. Price indices are used by the public as a guide for the family with regard to its budget and its constituent items. Price indices are used to monitor changes in the prices of the goods traded in the market and the consequent position of price trends, market conditions and living costs. However, the price index does not reflect other factors affecting the cost of living, e.g. the quality and quantity of purchased goods. Therefore, it is only one of many indicators used to assess living costs. It is used as a direct method to identify the purchasing power of money, where the purchasing power of money is inversely proportional to the price index.

Geographic coverage

Palestine West Bank Gaza Strip Jerusalem

Analysis unit

The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

Universe

The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

Kind of data

Sample survey data [ssd]

Sampling procedure

A non-probability purposive sample of sources from which the prices of different goods and services are collected was updated based on the establishment census 2017, in a manner that achieves full coverage of all goods and services that fall within the Palestinian consumer system. These sources were selected based on the availability of the goods within them. It is worth mentioning that the sample of sources was selected from the main cities inside Palestine: Jenin, Tulkarm, Nablus, Qalqiliya, Ramallah, Al-Bireh, Jericho, Jerusalem, Bethlehem, Hebron, Gaza, Jabalia, Dier Al-Balah, Nusseirat, Khan Yunis and Rafah. The selection of these sources was considered to be representative of the variation that can occur in the prices collected from the various sources. The number of goods and services included in the CPI is approximately 730 commodities, whose prices were collected from 3,200 sources. (COICOP) classification is used for consumer data as recommended by the United Nations System of National Accounts (SNA-2008).

Sampling deviation

Not apply

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

A tablet-supported electronic form was designed for price surveys to be used by the field teams in collecting data from different governorates, with the exception of Jerusalem J1. The electronic form is supported with GIS, and GPS mapping technique that allow the field workers to locate the outlets exactly on the map and the administrative staff to manage the field remotely. The electronic questionnaire is divided into a number of screens, namely: First screen: shows the metadata for the data source, governorate name, governorate code, source code, source name, full source address, and phone number. Second screen: shows the source interview result, which is either completed, temporarily paused or permanently closed. It also shows the change activity as incomplete or rejected with the explanation for the reason of rejection. Third screen: shows the item code, item name, item unit, item price, product availability, and reason for unavailability. Fourth screen: checks the price data of the related source and verifies their validity through the auditing rules, which was designed specifically for the price programs. Fifth screen: saves and sends data through (VPN-Connection) and (WI-FI technology).

In case of the Jerusalem J1 Governorate, a paper form has been designed to collect the price data so that the form in the top part contains the metadata of the data source and in the lower section contains the price data for the source collected. After that, the data are entered into the price program database.

Cleaning operations

The price survey forms were already encoded by the project management depending on the specific international statistical classification of each survey. After the researcher collected the price data and sent them electronically, the data was reviewed and audited by the project management. Achievement reports were reviewed on a daily and weekly basis. Also, the detailed price reports at data source levels were checked and reviewed on a daily basis by the project management. If there were any notes, the researcher was consulted in order to verify the data and call the owner in order to correct or confirm the information.

At the end of the data collection process in all governorates, the data will be edited using the following process: Logical revision of prices by comparing the prices of goods and services with others from different sources and other governorates. Whenever a mistake is detected, it should be returned to the field for correction. Mathematical revision of the average prices for items in governorates and the general average in all governorates. Field revision of prices through selecting a sample of the prices collected from the items.

Response rate

Not apply

Sampling error estimates

The findings of the survey may be affected by sampling errors due to the use of samples in conducting the survey rather than total enumeration of the units of the target population, which increases the chances of variances between the actual values we expect to obtain from the data if we had conducted the survey using total enumeration. The computation of differences between the most important key goods showed that the variation of these goods differs due to the specialty of each survey. For example, for the CPI, the variation between its goods was very low, except in some cases such as banana, tomato, and cucumber goods that had a high coefficient of variation during 2019 due to the high oscillation in their prices. The variance of the key goods in the computed and disseminated CPI survey that was carried out on the Palestine level was for reasons related to sample design and variance calculation of different indicators since there was a difficulty in the dissemination of results by governorates due to lack of weights. Non-sampling errors are probable at all stages of data collection or data entry. Non-sampling errors include: Non-response errors: the selected sources demonstrated a significant cooperation with interviewers; so, there wasn't any case of non-response reported during 2019. Response errors (respondent), interviewing errors (interviewer), and data entry errors: to avoid these types of errors and reduce their effect to a minimum, project managers adopted a number of procedures, including the following: More than one visit was made to every source to explain the objectives of the survey and emphasize the confidentiality of the data. The visits to data sources contributed to empowering relations, cooperation, and the verification of data accuracy. Interviewer errors: a number of procedures were taken to ensure data accuracy throughout the process of field data compilation: Interviewers were selected based on educational qualification, competence, and assessment. Interviewers were trained theoretically and practically on the questionnaire. Meetings were held to remind interviewers of instructions. In addition, explanatory notes were supplied with the surveys. A number of procedures were taken to verify data quality and consistency and ensure data accuracy for the data collected by a questioner throughout processing and data entry (knowing that data collected through paper questionnaires did not exceed 5%): Data entry staff was selected from among specialists in computer programming and were fully trained on the entry programs. Data verification was carried out for 10% of the entered questionnaires to ensure that data entry staff had entered data correctly and in accordance with the provisions of the questionnaire. The result of the verification was consistent with the original data to a degree of 100%. The files of the entered data were received, examined, and reviewed by project managers before findings were extracted. Project managers carried out many checks on data logic and coherence, such as comparing the data of the current month with that of the previous month, and comparing the data of sources and between governorates. Data collected by tablet devices were checked for consistency and accuracy by applying rules at item level to be checked.

Data appraisal

Other technical procedures to improve data quality: Seasonal adjustment processes

This statistic displays the number of road sections that have been included in the Spanish road safety index in 2019, broken down by level of risk. As can bee seen in the graph, *** road sections in Spain were classified as low-risk in 2020. In contrast, ** road sections were classified as high-risk.

The data refers to the Index Numbers of Foreign Trade. It gives the Unit Value Index and Volume Index of Exports and Imports. It also shows the Terms of trade.

Purpose and brief description The consumer price index is an economic indicator whose main task is to objectively reflect the price evolution over time for a basket of goods and services purchased by households and considered representative of their consumer habits. The index does not necessarily measure the price level of this basket for a specific period of time, but rather the fluctuation between two periods, the first one acting as basis for comparison. Moreover, this difference in the price level is not measured in absolute, but in relative terms. The consumer price index can be determined as a hundred times the ratio between the observed prices of a range of goods and services at a given time and the prices of the same goods and services, observed under the same circumstances during the reference period, chosen as basis for comparison. Price observations always take place in the same regions. Since 2014, the consumer price index has been a chain index in which the weighting reference period is regularly shifted and prices and quantities are no longer compared between the current period and a fixed reference period, but the current period is compared with an intermediate period. By multiplying these short-term indices, and so creating a chain, we get a long-term series with a fixed reference period. Population Belgian private households Data collection method and possible sampling Survey technique applied using a computer, based on the use of electronic questionnaires and laptops. Frequency Monthly. Timing of publication The results are available on the penultimate working day of the reference period. Definitions Weight (CPI): The weight represents the importance of the goods and services included in the CPI in the total expenditure patterns of the households. Weights are determined based on the household budget survey. Consumer price index (CPI): The consumer price index is an economic indicator whose main task is to objectively reflect the price evolution over time for a basket of goods and services purchased by households and considered representative of their consumer habits. Health index: The health index is derived from the consumer price index and has been published since January 1994. The current value of this index is determined by removing a number of products from the consumer price index product basket, in particular alcoholic beverages (bought in a shop or consumed in a bar), tobacco products and motor fuels except for LPG. Inflation: Inflation is defined as the ratio between the value of the consumer price index of a given month and the index of the same month the year before. Therefore, inflation measures the rhythm of the evolution of the overall price level. Consumer price index without petroleum products: This index is calculated by removing the following products from the consumer price index: butane, propane, liquid fuels and motor fuels. Consumer price index without energy products: This index is calculated by removing the following products from the consumer price index: electricity, natural gas, butane, propane, liquid fuels, solid fuels and motor fuels. Smoothed index: The smoothed health index, also called smoothed index (the average value of the health indexes of the last 4 months) is used as a basis for the indexation of retirement pensions, social security benefits and some salaries and wages. Public wages and social benefits are indexed as soon as the smoothed index reaches a given value, called the central index. The smoothed index is also called moving average. In order to perform a 2% index jump (laid down in the Law of 23 April 2015 on employment promotion), the smoothed health index has been temporarily blocked at its value of March 2015 (100.66). The smoothed health index was then reduced by 2% from April 2015. When the reduced smoothed health index (also called the reference index) had increased again by 2% or in other words when it had exceeded the value of 100.66, the index was no longer blocked. It occurred in April 2016. Since April 2016 the smoothed health index is calculated in the same manner as the reference index and therefore corresponds to the arithmetical mean of the health indexes of the last 4 months multiplied by a factor of 0.98. The central index is a predetermined threshold value against which the smoothed health index is compared. If the central index is reached or exceeded, there is an indexation of the wages and salaries or benefits. This indexation is proportional to the percentage between the old and the new central index. For the public sector and social benefits, the difference between the central indices always amounts to 2 %. Therefore, a 2 % indexation is applied every time the central index is reached. There are also collective labour agreements according to which the difference between the central indices amounts to 1 % or 1.5 %. The reaching of a central index then leads to an indexation of 1 % or 1,5 %. See also: https://bosa.belgium.

This table shows the price development of existing own homes. Aside from the price indices, Statistics Netherlands also publishes figures on the number of sold dwellings, the average purchase price, and the total sum of the purchase prices of the sold dwellings. The House Price Index of existing own homes is based on a complete registration of sales of dwellings by the Dutch Land Registry Office (Kadaster) and the (WOZ) value of all dwellings in the Netherlands. Indices can fluctuate, for example when a limited number of dwellings of a certain type is sold. In such cases we recommend using the long-term figures. The average purchase price of existing own homes may differ from the price index of existing own homes. The change in the average purchase price, however, is not an indicator for price developments of existing own homes.

Data available from: January 1995 till December 2023

Status of the figures: The figures in this table are immediately definitive. The calculation of these figures is based on the number of notary transactions that are registered every month by the Dutch Land Registry Office (Kadaster). A revision of the figures is exceptional and occurs specifically if an error significantly exceeds the acceptable statistical margins. The numbers of existing owner-occupied sold homes can be recalculated by Kadaster at a later date. These figures are usually the same as the publication on Statline, but in some periods they differ. Kadaster calculates the average purchasing prices based on the most recent data. These may have changed since the first publication. Statistics Netherlands uses figures from the first publication in accordance with the revision policy described above.

From reporting month January 2024, the base year of the House Price Index for Existing Dwellings (PBK) will be adjusted from 2015 to 2020. In February 2024, the first figures of this new series will be released. These figures will be available in a new StatLine table. The old series (base year = 2015) can still be consulted via StatLine, but will no longer be updated

Changes as of 11 March 2024: This table has been discontinued. This table is followed by Existing own homes; purchase prices, price indices 2020=100. See paragraph 3.

Data in table tells us about the year-wise Consumer price index number for industrial workers. Parameters used to classify data in the table are: Clothing,bedding,footwear, Food and General. The specific weightage of these parameters is also calculated as percentage of whole. Data is gathered from 2007-2016 for Indian States and UTs and also for All India.

Note: The total of the respective weights may not tally as the original weight are calculated to six places of decimals whereas the weights given here are rounded to two places of decimals.

This table shows the input price indices of the costs of labour, materials and equipment for civil engineering works (in Dutch: Grond-, weg- en waterbouw (GWW)). There are ten areas within civil engineering. These areas are based on the standard Classification Products to Activity. For each area a series is calculated based on the price developments of various cost components of which the product to be realised -in this case a civil engineering project- is constructed. The price index for the total of civil engineering is a weighted average of the ten areas. The published price indices of civil engineering are based on the average price level of the month in question. Changes in the overall costs and 'profit and risks' are not taken into account. Changes compared with twelve months previously are also published for all indices.

Data available from: The input price indices in this series are available from January 2020 on.

Status of the figures: Index figures up to November 2024 are definite. Other index figures are provisional. The period the price indices remain provisional depends on the moment that the collectively negotiated (Cao) wage rates for the construction industry are definite. This period can vary from 4 to about 16 months after the period under review.

Changes as of May 28th 2025: Following an adjustment in the weights, the figures have been changed from 2020 onwards. The months February to April 2025 have also been added

Changes as of February 3th 2025: The digits after the decimal point were incorrect due to a mistake while building the table. This has now been corrected.

When will new figures be published? Provisional figures for May, June and July 2025 will be published at the end of August 2025.

Explore the Wholesale Price Index dataset featuring manufacturing, mining and quarrying, agriculture, forestry and fishing data for Kuwait. Get insights on Index Number, % M/M Change, Food, Electricity, Energy, and more.

Manufacturing, Mining and quarrying, Agriculture, forestry and fishing, Index Number, % M/M Change, Food, TOTAL LESS FOOD, % Y/Y Change, ALL ITEMS, TOTAL LESS ENERGY, Electricity, gas, steam and water, Energy, TOTAL LESS ENERGY AND FOOD, Index, Period Change

Kuwait Follow data.kapsarc.org for timely data to advance energy economics research..

A business monitor divided into four different tables and containing detailed indices for revaluation of assets and stocks. It is a comprehensive guide to capital replacement costs. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: MM17

The price index for existing own dwellings (in Dutch PBK) aims to reflect the changes in prices of the sold existing own dwellings. The dwelling must be located on Dutch territory and sold to a private person. In addition, figures on the number of transactions, the average selling price, and the total value of the selling prices of the sold homes are also available. The price index figures for existing homes are based on a comprehensive registration of home sales transactions by the Kadaster and the WOZ values of all homes in the Netherlands. Index series can fluctuate. It is advisable to use the long-term trends of the price index figures. The average selling price may show a different trend than the price index for existing homes. The development of the average selling price is not an indicator of the price development of existing homes.

Data available from: January 1995

Status of the figures: The figures in this table are immediately definitive. The calculation of these figures is based on the number of notary transactions that are registered every month by the Dutch Land Registry Office (Kadaster). A revision of the figures is exceptional and occurs specifically if an error significantly exceeds the acceptable statistical margins. The numbers of existing owner-occupied sold homes can be recalculated by Kadaster at a later date. These figures are usually the same as the publication on Statline, but in some periods they differ. Kadaster calculates the average purchasing prices based on the most recent data. These may have changed since the first publication. Statistics Netherlands uses figures from the first publication in accordance with the revision policy described above.

Changes as of 23 June 2025: New figures for May 2025 are added.

When will new figures be published? New figures are published about 22 days after the period under review.

The index number of agricultural production for coffee in fiscal year 2024 across the country was around 136.2, up from about 128.2 in the previous fiscal year. Coffee in India is mainly cultivated in the southern states of Tamil Nadu, Karnataka and Kerala.

This data set shows the Consumer price index (2005 =100), index numbers for main groups, 2000 - 2005, Malaysia, Peninsular Malaysia, Sabah and SarawakFootnote Major Group classification is based on the Classification of Household Goods and Services (CHGS) Source: Department of Statistics Malaysia

Treasury Inflation-Protected Securities, also known as TIPS, are securities whose principal is tied to the Consumer Price Index. With inflation, the principal increases. With deflation, it decreases. When the security matures, the U.S. Treasury pays the original or adjusted principal, whichever is greater.

Residential Property Price Indices (RPPIs) – also named House price indices (HPIs), are index numbers measuring the evolution of residential property prices over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. Among their professional uses, they serve, for example, to monitor macroeconomic imbalances and risk exposure of the financial sector.

“National and Regional House Price Indices” datasets include RPPI compiled by official statistical agencies following international statistical guidelines. It covers all OECD member countries and some non-member countries. Whenever possible, these RPPIs are broken down by region, dwelling type (single- and multi-family dwellings) and vintage (new and existing dwellings).

The dataset called “National and Regional House Price Indices” contains the full list of available RPPIs.

The figures of existing own homes are related to the stock of existing own homes. Besides the price indices, figures are also published about the numbers sold, the average purchase price, and the total sum of the purchase prices of the sold dwellings. The House Price Index of existing own homes is based on a complete registration of sales of dwellings by the Dutch Land Registry Office (Kadaster) and the (WOZ) value of all dwellings in the Netherlands. Indices may fluctuate, for example if a small number of a certain type of dwellings are sold. In such cases we recommended using the long-term figures. The average purchase price of existing own homes may differ from the price index of existing own homes. The change in the average purchase price, however, is not an indicator for price developments of existing own homes.

Data available from: 1st quarter 1995 to 4th quarter 2023

Status of the figures: The figures in this table are immediately definitive. The calculation of these figures is based on the number of notary transactions that are registered every month by the Dutch Land Registry Office (Kadaster). A revision of the figures is exceptional and occurs specifically if an error significantly exceeds the acceptable statistical margins. The numbers of existing owner-occupied sold homes can be recalculated by Kadaster at a later date. These figures are usually the same as the publication on Statline, but in some periods they differ. Kadaster calculates the average purchasing prices based on the most recent data. These may have changed since the first publication. Statistics Netherlands uses figures from the first publication in accordance with the revision policy described above.

Changes as of 6 Juny 2024: This table has been discontinued. This table is followed by Existing own homes; purchase prices, price index 2020=100, type of dwelling. See paragraph 3.

From reporting period 2024 quarter 1, the base year of the House Price Index for Existing Dwellings (PBK) will be adjusted from 2015 to 2020. In April 2024, the first figures of this new series will be released. These figures will be available in a new StatLine table. The old series (base year = 2015) can still be consulted via StatLine, but will no longer be updated.