Byrne, David M., Kovak, Brian K., and Michaels, Ryan, (2017) “Quality-Adjusted Price Measurement: A New Approach With Evidence from Semiconductors.” Review of Economics and Statistics 99:2, 330-342.

Hedonic quality adjustment was first introduced in the Consumer Prices Index (CPI) in 2003 for PCs. Since then the use of hedonics has expanded in UK consumer price statistics to include a further five technology products; digital cameras, laptops, mobile phones, pay as you go phones, smartphones and tablet PCs. This article reviews the use of hedonic quality adjustment in consumer price indices in the UK and internationally. It also details the reasons for changing the method of quality adjustment for pay-as-you-go phones and digital cameras, from hedonic adjustment to class mean imputation, from March 2014 onwards.

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: Review of hedonic quality adjustment

This study investigates whether people consider elements beyond health when valuing Quality-Adjusted Life-Years (QALYs) monetarily and the influence of inclusion on this value. A Willingness to Pay (WTP) experiment was administered among the general public in which people were asked to assign monetary values to QALYs. Our results show that (stated) UoC increases with quality of life but that instructing people to consider UoC does not impact their monetary valuation of the QALY. Furthermore, many respondents consider elements beyond health when valuing QALYs but the impact on the monetary value of a QALY is limited.This dataset includes the documents related to the construction of the (sub-versions of the) questionnaire, the raw data from the (subversions of the) questionnaire collected by and received from the sampling agency, and the data after merging the individual datasets for the subversions into one dataset, and the code to analyze the data.

Israel IL: Consumer Price Index (CPI): Local Source Base Year: Clothing and Footwear data was reported at 90.467 2020=100 in 2022. This records a decrease from the previous number of 95.092 2020=100 for 2021. Israel IL: Consumer Price Index (CPI): Local Source Base Year: Clothing and Footwear data is updated yearly, averaging 119.871 2020=100 from Dec 1985 (Median) to 2022, with 38 observations. The data reached an all-time high of 167.358 2020=100 in 1997 and a record low of 53.850 2020=100 in 1985. Israel IL: Consumer Price Index (CPI): Local Source Base Year: Clothing and Footwear data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Israel – Table IL.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Annual. The CPI measures the change in prices which consumer pay for fixed market basket of consumption goods and services. Price coverage: Prices include applicable taxes (VAT) and fees on the products at the time of sale. Cash payments are the basis for the price survey. Monthly installment payment and credit card interest are excluded. Price collection procedure: The data collection methods are adapted according to the specific characteristics of the CPI classes. The main price surveys are: Computer Assisted Telephone Interviews (CATI), conducted by the CBS staff at the central office; Computer Assisted Personal Interviews (CAPI) by field collectors with handheld personal computers (HPC) and Direct Data Entry (DDE) into the database. Also for some special items Internet is used either in parallel with CAPI or as a part of DDE collection. The CPI includes a measure of rented housing Owner Occupied Housing (OOH) is included in the CPI and is calculated using rental equivalent method. The method for imputation of OOH is based on stratified average prices of contracts that are subject to renewal. In order to reduce variance in the monthly series, two month moving averages are compared each month. However, the method for OOH still leaves room for quality differences to play role in month-to-month average price changes. The method relies on successful stratification of apartments to groups whose relative price changes are as similar as possible. While the stratification is based on apartment location and number of rooms, some quality characteristics may experience month-to-month variation. Treatment of own account production is not included Goods and services sold illegally, second hand goods, goods and services partially or totally subsidized by the government and financial transactions are not included. Insurance: Insurance of personal transport and Health insurance (private and provided by the Government) are included. Treatment of missing items: Price changes for missing observations are imputed based on the price movements of other observations of the same item. Selection of replacement items: Products that become permantely unavailable are replaced in the sample and enumerators select a replacement possessing as many of the same quality characteristics as possible. Prices from previous period are sought for the replacement item for linking purpose. Treatment of quality change: There are two types of replacement approach: comparable and non-comparable. If a new product possesses the previously defined important characteristics of the old product, the new product is defined as comparable and a minor quality change is regarded as price change. Otherwise, if a significant quality change is introduced, the new product is defined as not comparable. The breakage in price series is treated by the linking method. Explicit quality adjustments are usually not performed. Hedonic methods are being considered but not yet implemented. In some cases, where the product cycle is short and new versions with improved quality characteristics are frequently introduced, the overlap method may give biased estimates. Introduction of new products: New items are introduced when the market basket is updated. New products are introduced into the sample as they gain significant market share. Business and professional periodicles are closely followed to gain information on new products that are gaining consumer demand. Seasonal items: Missing prices for seasonal products are imputed. Certain procedures are in place to avoid too early reintroduction of seasonal products back to the index. For price changes a bridge method is used when the items are reintroduced to the collection. Index series are also calculated and released in seasonally adjusted form.; Index series starts in November 1985

Israel IL: Consumer Price Index (CPI): Local Source Base Year: Transport data was reported at 114.000 2020=100 in Dec 2022. This records a decrease from the previous number of 114.600 2020=100 for Sep 2022. Israel IL: Consumer Price Index (CPI): Local Source Base Year: Transport data is updated quarterly, averaging 93.883 2020=100 from Mar 1985 (Median) to Dec 2022, with 152 observations. The data reached an all-time high of 114.600 2020=100 in Sep 2022 and a record low of 6.700 2020=100 in Mar 1985. Israel IL: Consumer Price Index (CPI): Local Source Base Year: Transport data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Israel – Table IL.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Quarterly. The CPI measures the change in prices which consumer pay for fixed market basket of consumption goods and services. Price coverage: Prices include applicable taxes (VAT) and fees on the products at the time of sale. Cash payments are the basis for the price survey. Monthly installment payment and credit card interest are excluded. Price collection procedure: The data collection methods are adapted according to the specific characteristics of the CPI classes. The main price surveys are: Computer Assisted Telephone Interviews (CATI), conducted by the CBS staff at the central office; Computer Assisted Personal Interviews (CAPI) by field collectors with handheld personal computers (HPC) and Direct Data Entry (DDE) into the database. Also for some special items Internet is used either in parallel with CAPI or as a part of DDE collection. The CPI includes a measure of rented housing Owner Occupied Housing (OOH) is included in the CPI and is calculated using rental equivalent method. The method for imputation of OOH is based on stratified average prices of contracts that are subject to renewal. In order to reduce variance in the monthly series, two month moving averages are compared each month. However, the method for OOH still leaves room for quality differences to play role in month-to-month average price changes. The method relies on successful stratification of apartments to groups whose relative price changes are as similar as possible. While the stratification is based on apartment location and number of rooms, some quality characteristics may experience month-to-month variation. Treatment of own account production is not included Goods and services sold illegally, second hand goods, goods and services partially or totally subsidized by the government and financial transactions are not included. Insurance: Insurance of personal transport and Health insurance (private and provided by the Government) are included. Treatment of missing items: Price changes for missing observations are imputed based on the price movements of other observations of the same item. Selection of replacement items: Products that become permantely unavailable are replaced in the sample and enumerators select a replacement possessing as many of the same quality characteristics as possible. Prices from previous period are sought for the replacement item for linking purpose. Treatment of quality change: There are two types of replacement approach: comparable and non-comparable. If a new product possesses the previously defined important characteristics of the old product, the new product is defined as comparable and a minor quality change is regarded as price change. Otherwise, if a significant quality change is introduced, the new product is defined as not comparable. The breakage in price series is treated by the linking method. Explicit quality adjustments are usually not performed. Hedonic methods are being considered but not yet implemented. In some cases, where the product cycle is short and new versions with improved quality characteristics are frequently introduced, the overlap method may give biased estimates. Introduction of new products: New items are introduced when the market basket is updated. New products are introduced into the sample as they gain significant market share. Business and professional periodicles are closely followed to gain information on new products that are gaining consumer demand. Seasonal items: Missing prices for seasonal products are imputed. Certain procedures are in place to avoid too early reintroduction of seasonal products back to the index. For price changes a bridge method is used when the items are reintroduced to the collection. Index series are also calculated and released in seasonally adjusted form.; Index series starts in November 1985

Greece GR: Consumer Price Index (CPI): Local Source Base Year: All Items data was reported at 114.833 2020=100 in 2023. This records an increase from the previous number of 110.987 2020=100 for 2022. Greece GR: Consumer Price Index (CPI): Local Source Base Year: All Items data is updated yearly, averaging 24.581 2020=100 from Dec 1955 (Median) to 2023, with 69 observations. The data reached an all-time high of 114.833 2020=100 in 2023 and a record low of 0.995 2020=100 in 1955. Greece GR: Consumer Price Index (CPI): Local Source Base Year: All Items data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Greece – Table GR.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Annual. The index measures changes in the general level of the prices of goods and services purchased by the average household. Types of prices: The collected prices correspond with the prices actually paid by the consumer and refer to sales 'in cash', including all the taxes (included VAT). Special offers and discounts are not taken into account. Instead, the reduced prices of general offers and general discounts are collected. Price collection methods: Prices are collected by specialised NSSG staff who visits the outlets within a defined period of the month or on the fixed day of the week and register the prices into special price collection prints. The rent prices are collected directly from households. Treatment of Rentals for Housing: included. Treatment of Owner-Occupied Housing: excluded. Treatment of missing prices: The treatment of missing prices depends on the category of items, for which prices are collected. For seasonal items (fresh vegetables, fresh fruit, clothing and footwear items, etc.) is followed the anticipated method. The treatment of missing prices for the other items depends on the duration of absence of the item in the outlet. If the time interval of its absence exceeds 2 months, then the item is replaced. Selection of replacements items: When a specified item is no longer available in the market or has ceased to be important, as regards the consumption, because of the appearance of new varieties, then it is substituted by the item which has taken its place in the market. If the substitute item is comparable to the item it replaces, then it is tried to estimate whether the deviation of prices is due to differences in quality, weight, package, etc. and adjust the price accordingly, so that the adjusted price corresponds to the price of the new item, with quality level equivalent to that of the old item. However, if the substitute item is not comparable to the one it replaces, then the prices of the two items are linked, and a theoretical base price is calculated for the substitute item. Treatment of quality changes: NSSG uses implicit quality adjustment techniques (such as overlap, etc.), each time taking into account different parameters in the quality adjustment decision. Explicit methods are only used in the form of quantity judgment, expert judgment, etc. in certain cases. The demand for explicit quality adjustment techniques, such as option cost, hedonics, etc. should be explored in the long run in the scope of NSSG. Seasonal items: For dealing with the seasonality of fresh vegetables and fruit the method of monthly changing weights of the various species of these goods, by keeping the weights of sub-groups 'Fresh vegetables' and 'Fresh fruit' constant, is applied. For the other items which are not offered, exactly the same, throughout the year (such as clothing and footwear items, heating oil, cinema and theatre tickets, sport equipment, etc.), their last observed regular price is repeated for the months in which these items are not available in the market.; Index series starts in January 1955

Comparator: Do nothing.†(Sensitivity).*(Sensitivity/Specificity).Bold Text: Strategy is cost effective (ICER versus Do Nothing is

*SE: standard error of the mean.†Dis. : diseases.

The latest closing stock price for BlackRock MuniYield Quality Fund II as of July 07, 2025 is 9.65. An investor who bought $1,000 worth of BlackRock MuniYield Quality Fund II stock at the IPO in 1992 would have $4,106 today, roughly 4 times their original investment - a 5.06% compound annual growth rate over 33 years. The all-time high BlackRock MuniYield Quality Fund II stock closing price was 12.38 on July 28, 2021. The BlackRock MuniYield Quality Fund II 52-week high stock price is 11.00, which is 14% above the current share price. The BlackRock MuniYield Quality Fund II 52-week low stock price is 9.05, which is 6.2% below the current share price. The average BlackRock MuniYield Quality Fund II stock price for the last 52 weeks is 10.19. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Background and objectivesThe estimation of a cost- Effectiveness (CE) threshold from the perspective of those who have experienced a life-threatening disease can provide empirical evidence for health policy makers to make the best allocation decisions on limited resources. The aim of the current study was to empirically determine the CE threshold for cancer interventions from the perspective of cancer patients in Iran.MethodsA composite time trade-off (cTTO) task for deriving quality adjusted life-year (QALY) and a double-bounded dichotomous choice (DBDC) approach followed by open-ended question for examining patients’ willingness-to-pay were performed. A nationally representative sample of 580 cancer patients was recruited from the largest governmental cancer centers in Iran between June 2021 and January 2022, and data were gathered using face-to-face interviews. The CE threshold was calculated using the nonparametric Turnbull model and parametric interval-censored Weibull regression model. Furthermore, the factors that affect the CE threshold were determined using the parametric model.ResultsThe estimated CE threshold using the nonparametric Turnbull model and parametric interval-censored Weibull regression model was IRR 440,410,000 (USD 10,485.95) and IRR 595,280,000 (USD 14,173.33) per QALY, respectively. Gender, age, education, income, type of cancer, and current treatment status were significantly associated with the estimated CE threshold.ConclusionsThe value of parametric model-based threshold in this study was 1.98 times the Iranian GDP per capita, which was lower than the CE threshold value recommended by the WHO (i.e., 3 times the GDP per capita) for low-and middle-income countries.

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

Greece GR: Consumer Price Index (CPI): Local Source Base Year: Furnishings, Household Equipment and Routine Household Maintenance data was reported at 114.013 2020=100 in 2023. This records an increase from the previous number of 106.812 2020=100 for 2022. Greece GR: Consumer Price Index (CPI): Local Source Base Year: Furnishings, Household Equipment and Routine Household Maintenance data is updated yearly, averaging 106.812 2020=100 from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 119.128 2020=100 in 2011 and a record low of 95.334 2020=100 in 1999. Greece GR: Consumer Price Index (CPI): Local Source Base Year: Furnishings, Household Equipment and Routine Household Maintenance data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Greece – Table GR.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Annual. The index measures changes in the general level of the prices of goods and services purchased by the average household. Types of prices: The collected prices correspond with the prices actually paid by the consumer and refer to sales 'in cash', including all the taxes (included VAT). Special offers and discounts are not taken into account. Instead, the reduced prices of general offers and general discounts are collected. Price collection methods: Prices are collected by specialised NSSG staff who visits the outlets within a defined period of the month or on the fixed day of the week and register the prices into special price collection prints. The rent prices are collected directly from households. Treatment of Rentals for Housing: included. Treatment of Owner-Occupied Housing: excluded. Treatment of missing prices: The treatment of missing prices depends on the category of items, for which prices are collected. For seasonal items (fresh vegetables, fresh fruit, clothing and footwear items, etc.) is followed the anticipated method. The treatment of missing prices for the other items depends on the duration of absence of the item in the outlet. If the time interval of its absence exceeds 2 months, then the item is replaced. Selection of replacements items: When a specified item is no longer available in the market or has ceased to be important, as regards the consumption, because of the appearance of new varieties, then it is substituted by the item which has taken its place in the market. If the substitute item is comparable to the item it replaces, then it is tried to estimate whether the deviation of prices is due to differences in quality, weight, package, etc. and adjust the price accordingly, so that the adjusted price corresponds to the price of the new item, with quality level equivalent to that of the old item. However, if the substitute item is not comparable to the one it replaces, then the prices of the two items are linked, and a theoretical base price is calculated for the substitute item. Treatment of quality changes: NSSG uses implicit quality adjustment techniques (such as overlap, etc.), each time taking into account different parameters in the quality adjustment decision. Explicit methods are only used in the form of quantity judgment, expert judgment, etc. in certain cases. The demand for explicit quality adjustment techniques, such as option cost, hedonics, etc. should be explored in the long run in the scope of NSSG. Seasonal items: For dealing with the seasonality of fresh vegetables and fruit the method of monthly changing weights of the various species of these goods, by keeping the weights of sub-groups 'Fresh vegetables' and 'Fresh fruit' constant, is applied. For the other items which are not offered, exactly the same, throughout the year (such as clothing and footwear items, heating oil, cinema and theatre tickets, sport equipment, etc.), their last observed regular price is repeated for the months in which these items are not available in the market.; Index series starts in January 1999

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. 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 and estimations of non-available items' prices: Under each category, a number of common items are used in Palestine to calculate the price levels and to represent the commodity within the commodity group. Of course, it is

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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. 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 and estimations of non-available items' prices: Under each category, a number of common items are used in Palestine to calculate the price levels and to represent the commodity within the commodity group. Of course, it is

Graph and download economic data for Producer Price Index by Industry: Saw Blade, Handsaw, and Hand and Edge Tool Manufacturing: Precision Measuring Tools (Inspection, Quality Control, Etc.) (DISCONTINUED) (PCU33221633221629) from Jan 1967 to Dec 2017 about tool, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

In many developing countries, the average firm is small, does not grow and has low productivity. Lack of market integration and limited information on non-local products often leave consumers unaware of the prices and quality of non-local firms. They therefore mostly buy locally, limiting firms' potential market size (and competition). We explore this hypothesis using a natural experiment in the Kerala boat-building industry. As consumers learn more about non-local builders, high quality builders gain market share and grow, while low quality firms exit. Aggregate quality increases, as does labor specialization, and average production costs decrease. Finally, quality-adjusted consumer prices decline.

Greece GR: Consumer Price Index (CPI): Local Source Base Year: Recreation and Culture data was reported at 104.165 2020=100 in 2023. This records an increase from the previous number of 100.913 2020=100 for 2022. Greece GR: Consumer Price Index (CPI): Local Source Base Year: Recreation and Culture data is updated yearly, averaging 105.532 2020=100 from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 116.695 2020=100 in 2010 and a record low of 92.379 2020=100 in 1999. Greece GR: Consumer Price Index (CPI): Local Source Base Year: Recreation and Culture data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Greece – Table GR.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Annual. The index measures changes in the general level of the prices of goods and services purchased by the average household. Types of prices: The collected prices correspond with the prices actually paid by the consumer and refer to sales 'in cash', including all the taxes (included VAT). Special offers and discounts are not taken into account. Instead, the reduced prices of general offers and general discounts are collected. Price collection methods: Prices are collected by specialised NSSG staff who visits the outlets within a defined period of the month or on the fixed day of the week and register the prices into special price collection prints. The rent prices are collected directly from households. Treatment of Rentals for Housing: included. Treatment of Owner-Occupied Housing: excluded. Treatment of missing prices: The treatment of missing prices depends on the category of items, for which prices are collected. For seasonal items (fresh vegetables, fresh fruit, clothing and footwear items, etc.) is followed the anticipated method. The treatment of missing prices for the other items depends on the duration of absence of the item in the outlet. If the time interval of its absence exceeds 2 months, then the item is replaced. Selection of replacements items: When a specified item is no longer available in the market or has ceased to be important, as regards the consumption, because of the appearance of new varieties, then it is substituted by the item which has taken its place in the market. If the substitute item is comparable to the item it replaces, then it is tried to estimate whether the deviation of prices is due to differences in quality, weight, package, etc. and adjust the price accordingly, so that the adjusted price corresponds to the price of the new item, with quality level equivalent to that of the old item. However, if the substitute item is not comparable to the one it replaces, then the prices of the two items are linked, and a theoretical base price is calculated for the substitute item. Treatment of quality changes: NSSG uses implicit quality adjustment techniques (such as overlap, etc.), each time taking into account different parameters in the quality adjustment decision. Explicit methods are only used in the form of quantity judgment, expert judgment, etc. in certain cases. The demand for explicit quality adjustment techniques, such as option cost, hedonics, etc. should be explored in the long run in the scope of NSSG. Seasonal items: For dealing with the seasonality of fresh vegetables and fruit the method of monthly changing weights of the various species of these goods, by keeping the weights of sub-groups 'Fresh vegetables' and 'Fresh fruit' constant, is applied. For the other items which are not offered, exactly the same, throughout the year (such as clothing and footwear items, heating oil, cinema and theatre tickets, sport equipment, etc.), their last observed regular price is repeated for the months in which these items are not available in the market.; Index series starts in January 1999

Information and communication technology (ICT) products are the core of the digital economy, and their classified price index plays an important role in the compilation of CPI index. This paper starts from the characteristics of ICT products that have a fast update rate and do not necessarily meet the unit substitution elasticity between products, and improves the traditional product price index model by considering the mismatch item processing and product substitution elasticity and chain drift factors to construct the Hedonic-SV-RYGEKS price index model in this paper. Using the weekly data of Jingdong mobile phone price on whale staff platform and the monthly data of notebook computer on magic mirror insight platform, after processing, a total of 1586 sets of mobile phone data and 136 sets of notebook computer data are obtained. By writing SPSS macro program and python program, the weekly price index of mobile phone and the monthly price index of notebook computer are calculated, and the ring price index and fixed base price index of mobile phone and notebook computer are compiled respectively. The chain ring price index based on model calculation is compared with the fixed base price index to investigate the rationality of the model. The results show that: Firstly, based on the principle of the quality adjustment model, the characteristic variables that can reflect the characteristics of the product are selected, and a Hedonic quality adjustment model is established between them and the product price. Through the actual data test, the model is suitable for fitting the price of mismatched products. Secondly, from the perspective of reflecting the elasticity of substitution of products, the evaluation criteria of the price index, and the adjustment of product quality, this paper constructs the Hedonic-SV-RYGEKS price index based on the Hedonic model and SV index, which avoids the incomparability of samples caused by the low matching degree of inter-temporal samples, and effectively inhibits the chain drift of chain price index caused by the rapid update of products. Finally, it is hoped that the research content of this paper can provide a reference for improving and innovating the processing method of mismatched projects in the compilation of price index.

Background Low molecular weight heparins hold several advantages over unfractionated heparin including convenience of administration. Enoxaparin is one such heparin licensed in the UK for use in unstable coronary artery disease (unstable stable angina and non-Q wave myocardial infarction). In these patients, two large randomised controlled trials and their meta-analysis showed small benefits for enoxaparin over unfractionated heparin at 30–43 days and potentially at one year. We found no relevant published full economic evaluations, only cost studies, one of which was conducted in the UK. The other studies, from the US, Canada and France, are difficult to interpret since their resource use and costs may not reflect UK practice. Methods We aimed to compare the benefits and costs of short-term treatment (two to eight days) with enoxaparin and unfractionated heparin in unstable coronary artery disease. We used published data sources to estimate the incremental cost per quality adjusted life year (QALY), adopting a NHS perspective and using 1998 prices. Results The base case was a 0.013 QALY gain and net cost saving of £317 per person treated with enoxaparin instead of unfractionated heparin. All but one sensitivity analysis showed net savings and QALY gains, the exception (the worst case) being a cost per QALY of £3,305. Best cases were a £495 saving and 0.013 QALY gain, or a £317 saving and 0.014 QALY gain per person. Conclusions Enoxaparin appears cost saving compared with unfractionated heparin in patients with unstable coronary artery disease. However, cost implications depend on local revascularisation practice.