This statistic depicts the largest Guatemalan-American population groups living in different counties across the United States as of 2010. At this time there were 214,939 people of Guatemalan origin living in Los Angeles County in California.

FocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for Guatemala Population.

Guatemala GT: International Migrant Stock: % of Population data was reported at 0.467 % in 2015. This records an increase from the previous number of 0.451 % for 2010. Guatemala GT: International Migrant Stock: % of Population data is updated yearly, averaging 0.459 % from Dec 1990 (Median) to 2015, with 6 observations. The data reached an all-time high of 2.885 % in 1990 and a record low of 0.412 % in 2000. Guatemala GT: International Migrant Stock: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Guatemala – Table GT.World Bank.WDI: Population and Urbanization Statistics. International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.; ; United Nations Population Division, Trends in Total Migrant Stock: 2008 Revision.; Weighted average;

Guatemala GT: International Migrant Stock: Total data was reported at 76,352.000 Person in 2015. This records an increase from the previous number of 66,384.000 Person for 2010. Guatemala GT: International Migrant Stock: Total data is updated yearly, averaging 52,685.500 Person from Dec 1960 (Median) to 2015, with 12 observations. The data reached an all-time high of 264,257.000 Person in 1990 and a record low of 38,201.000 Person in 1975. Guatemala GT: International Migrant Stock: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Guatemala – Table GT.World Bank: Population and Urbanization Statistics. International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.; ; United Nations Population Division, Trends in Total Migrant Stock: 2012 Revision.; Sum;

Guatemala GT: Completeness of Birth Registration: Urban data was reported at 96.800 % in 2015. This records an increase from the previous number of 96.200 % for 2009. Guatemala GT: Completeness of Birth Registration: Urban data is updated yearly, averaging 96.500 % from Dec 2009 (Median) to 2015, with 2 observations. The data reached an all-time high of 96.800 % in 2015 and a record low of 96.200 % in 2009. Guatemala GT: Completeness of Birth Registration: Urban data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Guatemala – Table GT.World Bank.WDI: Population and Urbanization Statistics. Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.; ; UNICEF's State of the World's Children based mostly on household surveys and ministry of health data.; ;

Guatemala immigration statistics for 2015 was 76,352, a 15.02% increase from 2010.

<ul style='margin-top:20px;'>

<li>Guatemala immigration statistics for 2010 was <strong>66,384</strong>, a <strong>15.95% increase</strong> from 2005.</li>
<li>Guatemala immigration statistics for 2005 was <strong>57,252</strong>, a <strong>18.98% increase</strong> from 2000.</li>
<li>Guatemala immigration statistics for 2000 was <strong>48,119</strong>, a <strong>69.19% decline</strong> from 1995.</li>
</ul>International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.

Guatemala GT: Completeness of Birth Registration data was reported at 96.400 % in 2015. This records a decrease from the previous number of 96.700 % for 2009. Guatemala GT: Completeness of Birth Registration data is updated yearly, averaging 96.550 % from Dec 2009 (Median) to 2015, with 2 observations. The data reached an all-time high of 96.700 % in 2009 and a record low of 96.400 % in 2015. Guatemala GT: Completeness of Birth Registration data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Guatemala – Table GT.World Bank.WDI: Population and Urbanization Statistics. Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.; ; UNICEF's State of the World's Children based mostly on household surveys and ministry of health data.; Weighted average;

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

A survey carried out between 2013 and 2018 found out that more than half of the population in Guatemala had a positive view of the United States as a country. In 2018, 58 percent of Guatemalan respondents claimed to have either a good or a very good perception of the U.S., having decreased from 80 percent registered in 2015.

Abstract

Multiple causes for displacement, all too often underpinned by violence and persecution, has led to over 800,000 Central Americans fleeing their homes, beginning in 2013. Year after year, there has been an increase in individuals fleeing. This was marked initially by especially large numbers of unaccompanied children, then joined in around 2018 with dramatic increases in families units fleeing Central America. Families are forced to flee together as violent threats and persecution by criminal groups in communities extend beyond individuals to entire family units.

Given these shifting dynamics in human mobility in these countries, UNHCR and UNICEF, through the Interdisciplinary Development Consultants, CID Gallup, decided to undertake this study with the aim of understanding and giving visibility to the forced displacement of families that flee northern Central America. In addition, the study also seeks to shed light on the current trends, protection risks and factors associated to the forced displacement and migration of unaccompanied and separated children.

For this purpose, Gallup conducted 3,104 surveys, complemented by focus group sessions segmented according to the geography of displacement in the region: country of origin, of transit and of asylum. Additionally, interviews were undertaken with families who were part of large mixed movement "caravans" that left Honduras at the beginning of 2020.

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

A significant sample was taken of each profile interviewed for a total of 3,104 surveys conducted in Honduras, El Salvador, Guatemala and Mexico. The content of each survey was focused on the following profiles:

Families and children and adolescents at risk of displacement in countries of origin: a total of 789 surveys were carried out with families identified from a non-probabilistic sampling. The surveys were taken in areas with the highest criminality and violence rates in countries of origin (El Salvador, Honduras and Guatemala), which were also areas with a prior history of forced displacement identified through previous studies. The survey questions focused on risks faced by families in their places of origin, including those that would compel them to flee, particularly those related to violence and poverty.

Families and children and adolescents in transit: a total of 836 surveys were carried out with families identified from a non-probabilistic sampling. The surveys were taken at locations where persons in transit were typically found in Guatemala and Mexico, such as Casas de Migrantes. For the quantitative component, data of unaccompanied children and adolescents was gatheredin Casa Nuestras Raices in Guatemala City and Quetzaltenango. This segment of the population was surveyed on the risks they faced during transit as well as the causes of displacement from their countries of origin.

Families and children and adolescents in country of destination: through non-probabilistic sampling methods, 453 people were surveyed, the majority of whom were recognized as refugees or asylum seekers in Mexico. Several interviews were facilitated by the UNHCR Office in Mexico in areas with this population profile: Casa del Migrante Monsenor-Oluta Veracruz, Scalabrinianas Mision con Migrantes y Refugiados, State DIF, Municipal DIF, among others. The survey questions for this population focused on the asylum procedure and their living conditions in the country.

Deported families and children and adolescents: non-probability cluster sampling. Interviews were conducted with 1,026 families that had been detained and deported during the 12 months prior to the survey. Locations included the Guatemalan Air Force base, outside of the Center for the Comprehensive Assistance to Migrants (CAIM for its acronym in Spanish) and outside of the following locations in Honduras: Center for the Assistance of Migrant Children and Families in Belen, and Center for the Assistance to the Returned Migrant (CAMR) and CAMR-OMOA.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire contains the following sections: household characteristics, individual characteristics, details on deportation, risks, transit, settled households.

The percentage of population aged over 18 with little trust in political and state institutions in Guatemala was approximately 78 percent in 2023. Between 1996 and 2023, the percentage of population rose by around 20 percentage points, though the increase followed an uneven trajectory rather than a consistent upward trend.

Guatemala GDP per Person Employed: 2021 PPP data was reported at 31,752.188 Intl $ in 2023. This records an increase from the previous number of 31,468.537 Intl $ for 2022. Guatemala GDP per Person Employed: 2021 PPP data is updated yearly, averaging 11,136.069 Intl $ from Dec 1991 (Median) to 2023, with 33 observations. The data reached an all-time high of 15,252.220 Intl $ in 2023 and a record low of 8,261.836 Intl $ in 2003. Guatemala GDP per Person Employed: 2021 PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Guatemala – Table GT.World Bank.WDI: Employment and Unemployment. GDP per person employed is gross domestic product (GDP) divided by total employment in the economy. Purchasing power parity (PPP) GDP is GDP converted to 2021 constant international dollars using PPP rates. An international dollar has the same purchasing power over GDP that a U.S. dollar has in the United States.;World Bank, World Development Indicators database. Estimates are based on employment, population, GDP, and PPP data obtained from International Labour Organization, United Nations Population Division, Eurostat, OECD, and World Bank.;Weighted average;

In 2023, the percentage of population aged over 18, that states their income is insufficient for their needs in Guatemala was estimated at approximately 38 percent. Between 1996 and 2023, the figure dropped by around 10 percentage points, though the decline followed an uneven course rather than a steady trajectory.

Among selected Latin American countries in 2021, Guatemala had the highest share of population that identify themselves as indigenous with over 43.5 percent. Bolivia followed with 41 percent of the total inhabitants. Colombia and Ecuador ranked as the Latin American countries with the highest share of indigenous people living in poverty.

Honduras had over half (54.1 percent) of pre-trial detainees among its prison population in 2022, the highest rate in Central America. Pre-trial detainees are people detained by the state while awaiting for their trial. Guatemala followed second with a share of 48.7 percent. Guatemala was also the Central American nation with the highest prison occupancy rate that year.