Philippines Percentage to Total Expenditure (PTE): Food Expenditure (FE) data was reported at 41.900 % in 2015. This records a decrease from the previous number of 42.800 % for 2012. Philippines Percentage to Total Expenditure (PTE): Food Expenditure (FE) data is updated yearly, averaging 42.800 % from Dec 1997 (Median) to 2015, with 7 observations. The data reached an all-time high of 44.200 % in 1997 and a record low of 41.400 % in 2006. Philippines Percentage to Total Expenditure (PTE): Food Expenditure (FE) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Philippines Share to Family Expenditure (SFE): Food & Non-Alcoholic Beve (FN) data was reported at 40.930 % in 2023. This records a decrease from the previous number of 42.620 % for 2021. Philippines Share to Family Expenditure (SFE): Food & Non-Alcoholic Beve (FN) data is updated yearly, averaging 42.550 % from Dec 2018 (Median) to 2023, with 3 observations. The data reached an all-time high of 42.620 % in 2021 and a record low of 40.930 % in 2023. Philippines Share to Family Expenditure (SFE): Food & Non-Alcoholic Beve (FN) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H023: Family Income and Expenditure Survey: 2023 Master Sample: Percentage Distribution of Family Expenditure.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The HIECS 2008/2009 is the tenth Household Income, Expenditure and Consumption Survey that was carried out in 2008/2009, among a long series of similar surveys that started back in 1955.

The survey main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To measure mean household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To define mean household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependant on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income and expenditure for commodities and services. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its sources and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to sources, either from household production or not, in addition to household expenditure for non food commodities and services. - To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ...) in urban and rural areas. - To identify the percentage distribution of income recipients according to some background variables such as housing conditions, size of household and characteristics of head of household.

Compared to previous surveys, the current survey experienced certain peculiarities, among which: 1- Doubling the number of area segments from 1200 in the previous survey to 2526 segments with decreasing the number of households selected from each segment to be (20) households instead of (40) in the previous survey to ensure appropriate representatives in the society. 2- Changing the survey period to 15 days instead of one month in the previous one 200412005, to lighten the respondent burden and encourage more cooperation. 3- Adding some additional questions: a- Participation or the benefits gained from pension and social security system. b- Participation in health insurance system. 4- Increasing quality control Procedures especially for fieldwork to ensure data accuracy and avoid any errors in suitable time.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The sample of HIECS, 2008-2009 is a two-stage stratified cluster sample, approximately self-weighted, of nearly 48000 households. The main elements of the sampling design are described in the following.

1- Sample Size
It has been deemed important to retain the same sample size of the previous two HIECS rounds. Thus, a sample of about 48000 households has been considered. The justification of maintaining the sample size at this level is to have estimates with levels of precision similar to those of the previous two rounds: therefore trend analysis with the previous two surveys will not be distorted by substantial changes in sampling errors from round to another. In addition, this relatively large national sample implies proportional samples of reasonable sizes for smaller governorates. Nonetheless, over-sampling has been introduced to raise the sample size of small governorates to about 1000 households As a result, reasonably precise estimates could be extracted for those governorates. The over-sampling has resulted in a slight increase in the national sample to 48658 households.

2- Cluster size
An important lesson learned from the previous two HIECS rounds is that the cluster size applied in both surveys is found to be too large to yield an accepted design effect estimates. The cluster size was 40 households in the 2004-2005 round, descending from 80 households in the 1999-2000 round. The estimates of the design effect (deft) for most survey measures of the latest round were extraordinary large. As a result, it has been decided to decrease the cluster size to only 19 households (20 households in urban governorates to account for anticipated non-response in those governorates: in view of past experience non-response is almost nil in rural governorates).

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among the documentation materials published in both Arabic and English.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following: 1- Expenditure and consumption questionnaire. 2- Diary questionnaire for expenditure and consumption. 3- Income questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention of Labor Statisticians held in Geneva, 2003. - Using the recent Classification of Individual Consumption according to Purpose (COICOP). - Using more than one approach of expenditure measurement to serve many purposes of the survey.

A brief description of each questionnaire is given next:

1- Expenditure and Consumption Questionnaire

This questionnaire comprises 14 tables in addition to identification and geographic data of household on the cover page. The questionnaire is divided into two main sections.

Section one: Household schedule and other information. It includes: - Demographic characteristics and basic data for all household individuals consisting of 18 questions for every person. - Members of household who are currently working abroad. - The household ration card. - The main outlets that provide food and beverage. - Domestic and foreign tourism. - The housing conditions including 15 questions. - Means of transportation used to go to work or school. - The household possession of appliances and means of transportation. - This section includes some questions which help to define the social and economic level of households which in turn, help interviewers to check the plausibility of expenditure, consumption and income data.

Section two: Expenditure and consumption data It includes 14 tables as follows: - The quantity and value of food and beverages commodities actually consumed. - The quantity and value of the actual consumption of alcoholic beverages, tobacco and narcotics. - The quantity and value of the clothing and footwear. - The household expenditure for housing. - The household expenditure for furnishings, household equipment and routine maintenance of the house. - The household expenditure for health care services. - The household expenditure for transportation. - The household

Philippines PTE: Under PhP 40,000: Food Expenditure (FE) data was reported at 60.800 % in 2015. This records a decrease from the previous number of 62.300 % for 2012. Philippines PTE: Under PhP 40,000: Food Expenditure (FE) data is updated yearly, averaging 61.550 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 62.300 % in 2012 and a record low of 60.800 % in 2015. Philippines PTE: Under PhP 40,000: Food Expenditure (FE) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Geographic coverage

Palestine

Analysis unit

Household

Universe

It consists of all Palestinian households and individuals who are staying normally in the state of Palestine during 2013

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample is two stage stratified cluster (pps) sample: First stage: selection a stratified sample of 300 EA with (pps) method. Second stage: selection a random area sample of 25 responded households from each enumeration area selected in the first stage, the selection starts from a random point in the enumeration area ( building number).

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionnaire Represents the main tool for the data collection, and so it must achieve the technical specifications for all phases of the survey, and the questionnaire consists of several sections: · Cover Page: Contains the identification data for the family, the date of the visit, data on the team work of the field, office and data entry. · The Roaster: Which contains demographic, social and economic data for the family members selected. · Housing Characteristics: It includes data on the type of dwelling, tenure, number of rooms, housing unit connection to public networks (water, electricity), the method of waste disposal, the main source of energy used in the housing unit, durable goods available to the family as well as data on the confiscation / Isolation Lands of the family by the Israeli occupation and land area. · Agriculture: The family ownership of agricultural land and land area, and sources of irrigation of agricultural crops, livestock and their numbers and data on the number of workers in agriculture from family members. · Assistances and Coping Strategy: Contains data about the family receiving of all kinds of assistances (food, cash, employment, school feeding), and source of assistance, and satisfaction for assistance and the reason for the dissatisfaction for assistance. And It contains data on the length of time in which the family can survive financially in the future, and the difficulties faced by the family and the actions carried out by the family to cope with difficulties. · Consumption/Expenditures: This section contains data on household expenditure in terms of increase or decrease, as well as the average household expenditure during the past six months, the rate of household expenditure on food and water during the past six months ... etc.. · Dietary Diversity and Facing Food Shortages: Includes data about how many days the family consume some food during the past week and the origin and source of such food. · Income: This section contains data on the sources of family income and the value of the family's monthly income over the past month and the value of annual income, and the percentage of annual income from agriculture. Freedom of Movement: The data includes all restrictions on the movement of the family during the past six months, and the problems prevent any family member from access to work, land, school or university and health facilities

Cleaning operations

Both data entry and tabulation were performed using the Access and SPSS software programs. Data entry was organized corresponding to the main parts of the questionnaire. A data entry template was designed to reflect an exact image of the questionnaire, and included various electronic checks: logical check, range checks, consisting checks and cross-validation. Complete manual inspection of results after data entry was performed, and questionnaires containing field-related errors were sent back to the field for corrections.

Response rate

Response rate was 83.6%

Sampling error estimates

Data of this survey affected by sampling errors due to use of the sample and not a complete enumeration. Therefore, certain differences are expected in comparison with the real values obtained through censuses. Variance were calculated for the most important indicators, the variance table is attached with the final report. There is no problem to disseminate results at the national level and regional level (west bank , gaza strip).

Data appraisal

Non-sampling errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained in how to carry out the interview, what to discuss and what to avoid, carrying out a pilot survey and practical and theoretical training during the training course.

Also data entry staff was trained on the entry program that was examined before starting the data entry process. Continuous contacts with the fieldwork team were maintained through regular visits to the field and regular meetings during the different field visits. Problems faced by fieldworkers were discussed to clarify issues and provide relevant instructions.

Philippines PTE: PhP 100,000 - 249,999: Food Expenditure (FE) data was reported at 51.600 % in 2015. This records a decrease from the previous number of 51.800 % for 2012. Philippines PTE: PhP 100,000 - 249,999: Food Expenditure (FE) data is updated yearly, averaging 51.700 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 51.800 % in 2012 and a record low of 51.600 % in 2015. Philippines PTE: PhP 100,000 - 249,999: Food Expenditure (FE) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Abstract

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The first survey that covered all the country governorates was carried out in 1958/1959 followed by a long series of similar surveys. The current survey, HIECS 2012/2013, is the eleventh in this long series.

Starting 2008/2009, Household Income, Expenditure and Consumption Surveys were conducted each two years instead of five years. This would enable better tracking of the rapid changes in the level of the living standards of the Egyptian households.

CAPMAS started in 2010/2011 to follow a panel sample of around 40% of the total household sample size. The current survey is the second one to follow a panel sample. This procedure will provide the necessary data to extract accurate indicators on the status of the society. The CAPMAS also is pleased to disseminate the results of this survey to policy makers, researchers and scholarly to help in policy making and conducting development related researches and studies

The survey main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To define average household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services. - To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index. - To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household. - To provide a time series of the most important data related to dominant standard of living from economic and social perspective. This will enable conducting comparisons based on the results of these time series. In addition to, the possibility of performing geographical comparisons.

Compared to previous surveys, the current survey experienced certain peculiarities, among which : 1) The total sample of the current survey (24.9 thousand households) is divided into two sections: a - A new sample of 16.1 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, ....... etc.

b - A panel sample of 2008/2009 survey data of around 8.8 thousand households were selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2) Some additional questions that showed to be important based on previous surveys results, were added to the survey questionnaire, such as: a - The extent of health services provided to monitor the level of services available in the Egyptian society. By collecting information on the in-kind transfers, the household received during the year; in order to monitor the assistance the household received from different sources government, association,..etc. b - Identifying the main outlet of fabrics, clothes and footwear to determine the level of living standards of the household.

3) Quality control procedures especially for fieldwork are increased, to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment.

Geographic coverage

National coverage, covering a sample of urban and rural areas in all the governorates.

Analysis unit

• Household/family
• Individual/person

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of HIECS 2012/2013 is a self-weighted two-stage stratified cluster sample, of around 24.9 households. The main elements of the sampling design are described in the following.

Sample Size The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 24863 households has been considered, and was distributed between urban and rural with the percentages of 45.4 % and 54.6, respectively. This sample is divided into two parts: a) A new sample of 16094 households selected from main enumeration areas. b) A panel sample of 8769 households (selected from HIECS 2010/2011 and the preceding survey in 2008/2009).

Cluster Size The cluster size in the previous survey has been decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, it has been decided to use a cluster size of only 8 households (In HIECS 2011/2012 a cluster size of 16 households was used). While the cluster size for the panel sample was 4 households.

Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2012 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources.

New Households Sample 1000 sample areas were selected across all governorates (urban/rural) using a proportional technique with the sample size. The number required for each governorate (urban/rural) was selected from the enumeration areas of the core sample using a systematic sampling technique.

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following: 1) Expenditure and Consumption Questionnaire. 2) Diary Questionnaire (Assisting questionnaire). 3) Income Questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention of

Survey of Household Spending (SHS), average household spending, Canada, regions and provinces.

In recent years, the total annual spending of households in Italy grew steadily, with a contraction between 2020 and 2021 only, due to the COVID-19 pandemic. In 2023, Italian families spent more than 1.25 trillion euros, with an increase of 73.3 billion euros compared to 2022.

Dog and Cat Food Market Outlook

The global dog and cat food market size was valued at approximately USD 75 billion in 2023 and is anticipated to reach nearly USD 115 billion by 2032, growing at a compound annual growth rate (CAGR) of 5.1% during the forecast period. The growth of this market is primarily driven by the increasing pet ownership rates, rising disposable incomes, and the humanization of pets, which leads to higher spending on premium pet food products.

One of the significant growth factors in the dog and cat food market is the rising trend of pet humanization. Owners increasingly treat their pets like family members, which translates into higher demand for premium and nutritious pet food. The awareness regarding pet health and nutrition is on the rise, as pet owners seek to provide the best possible diet for their pets. This trend has led to a substantial increase in the sales of organic and natural pet food, which often come with higher price points.

Another critical driver of market growth is the increasing disposable income, especially in developing regions. As household incomes rise, pet owners are more willing to spend on high-quality pet food products. This economic factor has a direct correlation with the pet food market, as higher incomes allow consumers to opt for premium brands and specialized diets for their pets. Moreover, the trend towards smaller families and single-person households has further fueled the adoption of pets, subsequently increasing the demand for pet food.

The advent of e-commerce and the proliferation of online retail channels have also significantly contributed to the market's growth. The convenience offered by online shopping platforms has made it easier for pet owners to access a wide range of pet food products, including niche and specialty items that may not be available in traditional brick-and-mortar stores. The online sales channel has witnessed a significant uptick, especially during the COVID-19 pandemic, and this trend is expected to continue in the coming years.

From a regional perspective, North America holds a significant share of the dog and cat food market, driven by high pet ownership rates and a strong preference for premium pet food products. However, the Asia Pacific region is expected to exhibit the highest growth rate during the forecast period, owing to increasing urbanization, rising disposable incomes, and a growing trend of pet adoption in countries like China and India.

Product Type Analysis

The dog and cat food market can be segmented by product type into dry food, wet food, treats and snacks, veterinary diets, and others. Dry food holds the largest market share due to its convenience, affordability, and long shelf life. Pet owners often prefer dry food because it is easier to store and portion out, making it a practical choice for feeding pets on a daily basis. Additionally, dry food is beneficial for pets' dental health as it helps to keep their teeth clean and reduces tartar buildup.

Wet food, although not as dominant as dry food, still commands a significant market share. Wet food is often considered more palatable and easier to digest, making it a preferred choice for older pets or those with dental issues. The high moisture content in wet food helps keep pets hydrated and can be particularly beneficial for cats, who are prone to urinary tract issues. The growing trend towards offering pets a more varied diet has also led to an increase in the demand for wet food.

Treats and snacks have seen substantial growth, driven by the pet humanization trend. Pet owners are increasingly using treats as a way to bond with their pets, reward good behavior, and ensure that their pets are receiving supplemental nutrition. The market for treats and snacks is becoming more diverse, with products ranging from dental chews to gourmet treats made from high-quality ingredients. This segment is expected to continue growing as more innovative products are introduced.

Veterinary diets are specialized food products designed to meet the specific health needs of pets. These diets are often recommended by veterinarians for pets with particular health conditions such as obesity, diabetes, or allergies. The rising awareness about pet health and the increasing prevalence of pet diseases have driven the demand for veterinary diets. Pet owners are becoming more proactive about their pets' health, leading to a higher adoption rate of these specialized products.

Other product types in

The total household expenditure in Italy increased in 2023 compared to the previous year, reaching 1.25 trillion euros. Housing and utilities accounted for the largest expenditure, followed by spending on food, transport, and accommodation.

This layer gives the overview of Food Accessibility in the State of Texas. Food accessLimited access to supermarkets, supercenters, grocery stores, or other sources of healthy and affordable food may make it harder for some people to eat a healthy diet in this country. There are many ways to measure food store access for individuals and for neighborhoods, and many ways to define which areas are low-income and low access—neighborhoods that lack healthy food sources. Most measures and definitions consider at least some of the following indicators of access:Accessibility to sources of healthy food, as measured by distance to a store or by the number of stores in an area;Individual-level resources that may affect accessibility, such as family income or vehicle availability; andNeighborhood-level indicators of resources, such as the average income of the neighborhood and the availability of public transportation.In the Food Access Research Atlas, several indicators are available to measure food access along these dimensions. For example, users can choose alternative distance markers to measure low access in a neighborhood, such as the number and share of people more than one-half mile to a supermarket or 1 mile to a supermarket. Users can also view other census-tract-level characteristics that provide context on food access in neighborhoods, such as whether the tract has a high percentage of households far from supermarkets and without vehicles, individuals with low income, or people residing in group quarters.Specialized Stores - The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is the USDA’s third-largest food assistance program, supporting low-income, nutritionally at-risk women, infants, and children. In 2019, it served 6.4 million participants with Federal spending of $5.2 billion. Participants primarily redeem benefits at WIC-authorized retailers, which range from large supermarkets to smaller stores like convenience stores or specialized “above-50-percent” (A50) stores, where more than 50% of food sales come from WIC transactions. A50 stores can reduce travel distances and improve access to WIC-approved foods, especially in urban areas, but they face stricter pricing regulations to prevent cost inflation. WIC food packages are tailored to participants' nutritional needs and can include fixed quantities of milk, eggs, fruits, vegetables, and infant-specific foods.

Philippines PTE: FE: Food Consumed at Home (FCH) data was reported at 33.700 % in 2015. This records a decrease from the previous number of 35.300 % for 2012. Philippines PTE: FE: Food Consumed at Home (FCH) data is updated yearly, averaging 36.500 % from Dec 1997 (Median) to 2015, with 7 observations. The data reached an all-time high of 39.500 % in 1997 and a record low of 33.700 % in 2015. Philippines PTE: FE: Food Consumed at Home (FCH) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Philippines PTE: PhP 40,000 - 59,999: FE: Food Consumed at Home (FCH) data was reported at 54.800 % in 2015. This records a decrease from the previous number of 58.400 % for 2012. Philippines PTE: PhP 40,000 - 59,999: FE: Food Consumed at Home (FCH) data is updated yearly, averaging 56.600 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 58.400 % in 2012 and a record low of 54.800 % in 2015. Philippines PTE: PhP 40,000 - 59,999: FE: Food Consumed at Home (FCH) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Philippines PTE: PhP 250,000 & over: FE: Food Consumed at Home (FCH) data was reported at 26.700 % in 2015. This records a decrease from the previous number of 26.800 % for 2012. Philippines PTE: PhP 250,000 & over: FE: Food Consumed at Home (FCH) data is updated yearly, averaging 26.750 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 26.800 % in 2012 and a record low of 26.700 % in 2015. Philippines PTE: PhP 250,000 & over: FE: Food Consumed at Home (FCH) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Abstract

The CSES is a household survey with questions to households and the household members. In the household questionnaire there are a number of modules with questions relating to the living conditions, e.g. housing conditions, education, health, expenditure/income and labour force. It is designed to provide information on social and economic conditions of households for policy studies on poverty, household production and final consumption for the National Accounts and weights for the CPI.

The main objective of the survey is to collect statistical information about living standards of the population and the extent of poverty. Essential areas as household production and cash income, household level and structure of consumption including poverty and nutrition, education and access to schooling, health and access to medical care, transport and communication, housing and amenities and family and social relations. For recording expenditure, consumption and income the Diary Method was applied.

Another main objective of the survey is also to collect accurate statistical information about living standards of the population and the extent of poverty as an essential instrument to assist the government in diagnosing the problems and designing effective policies for reducing poverty, and in evaluating the progress of poverty reduction which are the main priorities in the "Rectangular Strategy" of the Royal Government of Cambodia.

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design in the CSES survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two. The sampling designs used in the three stages were: Stage 1: A stratified systematic pps6 sample of villages was selected. Strata were defined by provinces and the urban/rural classification of villages. The size measure used in the systematic pps sampling was the number of households in the village according to the population census 1998. Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1. Stage 3. In each selected EA a sample of households was selected by systematic sampling.

The design described above was used for the CSES 2004 survey.7 In 2007, a subsample of the villages, or EAs, in the 2004 sample was selected by SRS. The villages and EAs surveyed in 2007 were thus included in the sample in both years. In each selected EA a sample of households was selected by systematic sampling. The selected households in 2007 are not necessarily the same as those included in the sample in 2004.

The selection of households in stage three was done in field by first listing the households in the selected EA, and then selecting a systematic sample of households. Selected households were observed during one calendar month. The allocation of the households over the months in 2007 was done so that each village in the 2007 sample was observed in the same calendar month as in 2004. The sample size in 2007 was 360 villages or 3,600 households, compared to the sample for the 2004 survey of 720 villages or 12,000 households.

Some provinces were excluded, due to cost and other reasons, in the sample for 2007. The estimates are however, adjusted for the under coverage error caused by excluding those provinces. Please refer to Technical Documents for details.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four different questionnaires or forms were used in the CSES 2007: 1. Household listing form The listing of households was used for sampling households, see section 4.3.

1. Village questionnaire The village questionnaire was responded by the village leader or a representative of the village leader. The questions are about economy and infrastructure, crop production, health, education, retail prices, rental and sales prices of land etc.

2. Household questionnaire The household questionnaire was responded by the head of the household, spouse of the head of the household or of another adult household member. The household questionnaire includes questions about housing conditions, crop production and other agricultural activities, liabilities, durable goods, construction activities and income from other sources than economic activity. It also includes questions for each household member about education and literacy, migration, current economic activity and employment, health, smoking, HIV/AIDS awareness, and victimization. Some of these questions were responded by the head of household/spouse and some were responded by each household member. The questions in the first part of the household questionnaire are posed during the initial visit to the household. This part includes questions about e.g. the household member's age, sex, marital status, relation to head of household, and questions about household expenditure/consumption of food and non-food items. During a survey month different questions have been asked different weeks according to the following: • Week 1. Questions about education, migration, and housing • Week 2. Questions about economic activity, agricultural and non-agricultural business, household liabilities and other incomes. • Week 3. Questions about construction, durable goods, and child health • Week 4. Questions about current economic activities, health and victimization

3. Diary sheet The diary sheet on daily household expenditure, including value of own production, and income have been filled in during the entire month.

Cleaning operations

A team of data editors, data coders and data entry staff was formed. The data editors were checking the questionnaires before the data entry and also took care of errors to ensure that entered data were consistent with the collected data in the questionnaires or diaries.

Response rate

Not Computed

Sampling error estimates

In order to provide a basis for assessing the reliability or precision of CSES estimates, the estimation of the magnitude of sampling error in the survey data were computed. Since most of the estimates from the survey are in the form of weighted ratios, variances for ratio estimates are presented.

The Coefficients of Variation (CV) on national level estimates are generally below 4 percent. The exception is the CV for total value of assets where there are rather high CVs especially in the urban areas, which should be expected. The CVs are somewhat higher in the urban and rural domains but still generally below 7 percent. For the five zones, the average CVs are in the range 5 to 13 percent with a few exceptions where the CVs are above 20 percent. For provinces the CVs for food consumption are 9 percent on average.

The sample take within Primary Sampling Units (PSU) was set to 10 households per PSU in the CSES 1999. When data on variances became available, it was possible to make crude calculations of the optimal sample take within PSU. Calculations on some of the central estimates in the CSES 1999 show that the design effects in most cases are in the range 1 to 5.

Intra-cluster correlation coefficients have been calculated based on the design effects. These correlation coefficients are somewhat high. The reason is that the characteristics that are measured tend to be concentrated (clustered) within the PSUs. The optimal sample size within PSUs under different assumptions on cost ratios and intra-cluster correlation coefficients was then calculated. The cost ratio is the average cost for adding a village to the sample divided by the average cost of including an extra household in the sample. In the CSES, it was chosen to adopt a fairly low cost ratio due to the fact that the interview time per household is long. Under this assumption the optimal sample size is probably around 10 households per village for many of the CSES indicators.

According to Cognitive Market Research, the global kids food market size is USD 103684.5 million in 2024 and will expand at a compound annual growth rate (CAGR) of 5.00% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 41473.80 million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.2% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 31105.35 million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 23847.44 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.0% from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD 5184.23 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.4% from 2024 to 2031.
Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD 2073.69 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.7% from 2024 to 2031.
The dairy products held the highest kids food market revenue share in 2024.

Market Dynamics of Kids food Market

Key Drivers for Kids food Market

Rising Disposable Income to Increase the Demand Globally

The increase in disposable earnings across the globe is changing how mothers and fathers pick food merchandise for their children. With more economic flexibility, many parents are prioritizing quality over price, looking for top-class alternatives that might be advertised as more healthy or more convenient. This trend is pondered inside the rising call for organic snacks, nutrient-wealthy meals, and clean-to-put-together foods that cater to busy lifestyles, even as making sure dietary fees. Brands have replied by using growing a greater variety of premium products, from natural fruit pouches to fortified cereals. As dads and moms become more conscious about their kids' health, they are willing to invest in top-class meals that align with their values, riding sizeable growth in this market segment.

Working Parents to Propel Market Growth

The upward thrust of twin-profit households has basically shifted their family dynamics, using the demand for convenient meal solutions. With each dad and mom regularly running full-time, there may be less time for conventional meal education, leading families to seek prepared-to-eat or clean-to-prepare meals that shop treasured time. These quick options help reduce strain and streamline each day's routines, permitting mother and father to focus on different priorities. As an end result, the market for handy food has accelerated, with a broader range of products, from microwaveable dinners to meal kits that require minimum cooking. This developing trend displays the modern-day circle of relatives who want performance and convenience without sacrificing quality or nutrition, and meal groups are actively innovating to satisfy those evolving needs.

Restraint Factor for the Kids food Market

Increased Regulations to Limit the Sales

Governments worldwide are intensifying policies on meal merchandise aimed at youngsters to fight the growing fees of weight problems and associated fitness issues in early life. New legal guidelines and suggestions set stricter limits on sugar, salt, and fat content in youngsters' foods, aiming to sell more healthy ingesting behavior from a younger age. These rules impact how manufacturers formulate their products, as they ought to comply with lower thresholds for these probably dangerous components. As a result, companies face the task of reimagining recipes to satisfy these regulatory requirements without compromising taste or enchantment. While this may be seen as a hurdle, it additionally opens possibilities for innovation in growing more healthy meal alternatives. Manufacturers are exploring herbal sweeteners, opportunity flavorings, and innovative element mixtures to fulfil regulatory requirements at the same time as pleasurable kid's palates. Ultimately, these rules inspire a broader shift closer to health-aware meal merchandise for youngsters, fostering a more health-orientated food industry.

Impact of Covid-19 on the Kids food Market

The COVID-19 pandemic substantially impacted the youngsters' grocery stores, reshaping purchaser conduct and delivery chain dynamics. With lockdowns and far-off studying, households spent mor...

In 2024, there were ******* German households with a household net income of under 500 euros per month. ***** households had a monthly income of 5,000 euros and more. Disposable net income While at first glance the aforementioned monthly income may seem manageable, based on general German standards of living, it is worth noting that flexibility and expenditure depends on the number of people living in a household, or rather the number of earners in relation to that number. In the case of employed population members, what remains as disposable net income is influenced by various regular payments made by households after the already taxed salary arrives. These payments include, but are not limited to, rent, different types of insurance, repaying loans, fees for internet and mobile phone services. Food and housing When looking at private household spending in Germany, consistent patterns emerge. Housing, water, electricity, gas and other fuel made up the largest share and will increase even further in the coming months, followed by food, beverages, and tobacco.

Philippines PTE: Under PhP 40,000: FE: Food Consumed Outside Home data was reported at 5.500 % in 2015. This records a decrease from the previous number of 6.400 % for 2012. Philippines PTE: Under PhP 40,000: FE: Food Consumed Outside Home data is updated yearly, averaging 5.950 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 6.400 % in 2012 and a record low of 5.500 % in 2015. Philippines PTE: Under PhP 40,000: FE: Food Consumed Outside Home data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Philippines PTE: PhP 100,000 - 249,999: FE: FFood n.e.c data was reported at 1.300 % in 2015. This records a decrease from the previous number of 1.400 % for 2012. Philippines PTE: PhP 100,000 - 249,999: FE: FFood n.e.c data is updated yearly, averaging 1.350 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 1.400 % in 2012 and a record low of 1.300 % in 2015. Philippines PTE: PhP 100,000 - 249,999: FE: FFood n.e.c data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.