The region of present-day China has historically been the most populous region in the world; however, its population development has fluctuated throughout history. In 2022, China was overtaken as the most populous country in the world, and current projections suggest its population is heading for a rapid decline in the coming decades. Transitions of power lead to mortality The source suggests that conflict, and the diseases brought with it, were the major obstacles to population growth throughout most of the Common Era, particularly during transitions of power between various dynasties and rulers. It estimates that the total population fell by approximately 30 million people during the 14th century due to the impact of Mongol invasions, which inflicted heavy losses on the northern population through conflict, enslavement, food instability, and the introduction of bubonic plague. Between 1850 and 1870, the total population fell once more, by more than 50 million people, through further conflict, famine and disease; the most notable of these was the Taiping Rebellion, although the Miao an Panthay Rebellions, and the Dungan Revolt, also had large death tolls. The third plague pandemic also originated in Yunnan in 1855, which killed approximately two million people in China. 20th and 21st centuries There were additional conflicts at the turn of the 20th century, which had significant geopolitical consequences for China, but did not result in the same high levels of mortality seen previously. It was not until the overlapping Chinese Civil War (1927-1949) and Second World War (1937-1945) where the death tolls reached approximately 10 and 20 million respectively. Additionally, as China attempted to industrialize during the Great Leap Forward (1958-1962), economic and agricultural mismanagement resulted in the deaths of tens of millions (possibly as many as 55 million) in less than four years, during the Great Chinese Famine. This mortality is not observable on the given dataset, due to the rapidity of China's demographic transition over the entire period; this saw improvements in healthcare, sanitation, and infrastructure result in sweeping changes across the population. The early 2020s marked some significant milestones in China's demographics, where it was overtaken by India as the world's most populous country, and its population also went into decline. Current projections suggest that China is heading for a "demographic disaster", as its rapidly aging population is placing significant burdens on China's economy, government, and society. In stark contrast to the restrictive "one-child policy" of the past, the government has introduced a series of pro-fertility incentives for couples to have larger families, although the impact of these policies are yet to materialize. If these current projections come true, then China's population may be around half its current size by the end of the century.

This layer shows the Hong Kong Population Distribution aged 5 and over having internally migrated by area by Large Tertiary Planning Unit Group in 2021. It is a subset of the 2021 Population Census made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data is in CSV format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of CSDI Portal at https://portal.csdi.gov.hk.

Abstract

China Living Standards Survey (LSS) consists of one household survey and one community (village) survey, conducted in Hebei and Liaoning Provinces (northern and northeast China) in July 1995 and July 1997 respectively. Five villages from each three sample counties of each province were selected (six were selected in Liaoyang County of Liaoning Province because of administrative area change). About 880 farm households were selected from total thirty-one sample villages for the household survey. The same thirty-one villages formed the samples of community survey. This document provides information on the content of different questionnaires, the survey design and implementation, data processing activities, and the different available data sets.

Geographic coverage

Regional

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The China LSS sample is not a rigorous random sample drawn from a well-defined population. Instead it is only a rough approximation of the rural population in Hebei and Liaoning provinces in North-eastern China. The reason for this is that part of the motivation for the survey was to compare the current conditions with conditions that existed in Hebei and Liaoning in the 1930's. Because of this, three counties in Hebei and three counties in Liaoning were selected as "primary sampling units" because data had been collected from those six counties by the Japanese occupation government in the 1930's. Within each of these six counties (xian) five villages (cun) were selected, for an overall total of 30 villages (in fact, an administrative change in one village led to 31 villages being selected). In each county a "main village" was selected that was in fact a village that had been surveyed in the 1930s. Because of the interest in these villages 50 households were selected from each of these six villages (one for each of the six counties). In addition, four other villages were selected in each county. These other villages were not drawn randomly but were selected so as to "represent" variation within the county. Within each of these villages 20 households were selected for interviews. Thus, the intended sample size was 780 households, 130 from each county. Unlike county and village selection, the selection of households within each village was done according to standard sample selection procedures. In each village, a list of all households in the village was obtained from village leaders. An "interval" was calculated as the number of the households in the village divided by the number of households desired for the sample (50 for main villages and 20 for other villages). For the list of households, a random number was drawn between 1 and the interval number. This was used as a starting point. The interval was then added to this number to get a second number, then the interval was added to this second number to get a third number, and so on. The set of numbers produced were the numbers used to select the households, in terms of their order on the list. In fact, the number of households in the sample is 785, as opposed to 780. Most of this difference is due to a village in which 24 households were interviewed, as opposed to the goal of 20 households

Mode of data collection

Face-to-face [f2f]

Cleaning operations

(a) DATA ENTRY All responses obtained from the household interviews were recorded in the household questionnaires. These were then entered into the computer, in the field, using data entry programs written in BASIC. The data produced by the data entry program were in the form of household files, i.e. one data file for all of the data in one household/community questionnaire. Thus, for the household there were about 880 data files. These data files were processed at the University of Toronto and the World Bank to produce datasets in statistical software formats, each of which contained information for all households for a subset of variables. The subset of variables chosen corresponded to data entry screens, so these files are hereafter referred to as "screen files". For the household survey component 66 data files were created. Members of the survey team checked and corrected data by checking the questionnaires for original recorded information. We would like to emphasize that correction here refers to checking questionnaires, in case of errors in skip patterns, incorrect values, or outlying values, and changing values if and only if data in the computer were different from those in the questionnaires. The personnel in charge of data preparation were given specific instructions not to change data even if values in the questionnaires were clearly incorrect. We have no reason to believe that these instructions were not followed, and every reason to believe that the data resulting from these checks and corrections are accurate and of the highest quality possible.

(b) DATA EDITING The screen files were then brought to World Bank headquarters in Washington, D.C. and uploaded to a mainframe computer, where they were converted to "standard" LSMS formats by merging datasets to produce separate datasets for each section with variable names corresponding to the questionnaires. In some cases, this has meant a single dataset for a section, while in others it has meant retaining "screen" datasets with just the variable names changed. Linking Parts of the Household Survey Each household has a unique identification number which is contained in the variable HID. Values for this variable range from 10101 to 60520. The first number is the code for the six counties in which data were collected, the second and third digits are for the villages within each county. Finally, the last two digits of HID contain the household number within the village. Data for households from different parts of the survey can be merged by using the HID variable which appears in each dataset of the household survey. To link information for an individual use should be made of both the household identification number, HID, and the person identification number, PID. A child in the household can be linked to the parents, if the parents are household members, through the parents' id codes in Section 01B. For parents who are not in the household, information is collected on the parent's schooling, main occupation and whether he/she is currently alive. Household members can be linked with their non-resident children through the parents' id codes in Section 01C. Linking the Household to the Community Data The community data have a somewhat different set of identifying variables than the household data. Each community dataset has four identifying variables: province (code 7 for Hebei and code 8 for Liaoning); county (six two digit codes, of which the first digit represents province and the second digit represents the three counties in each province); township (3 digit code, first digit is county, second digit is county and third digit is township); and village (4 digit code, first digit is county, second digit is county, third digit is township, and third fourth digit is village). Constructed Data Set Researchers at the World Bank and the University of Toronto have created a data set with information on annual household expenditures, region codes, etc. This constructed data set is made available for general use with the understanding that the description below is the only documentation that will be provided. Any manipulation of the data requires assumptions to be made and, as much as possible, those assumptions are explained below. Except where noted, the data set has been created using only the original (raw) data sets. A researcher could construct a somewhat different data set by incorporating different assumptions. Aggregate Expenditure, TOTEXP. The dataset TOTEXP contains variables for total household annual expenditures (for the year 1994) and variables for the different components of total household expenditures: food expenditures, non-food expenditures, use value of consumer durables, etc. These, along with the algorithm used to calculate household expenditures are detailed in Appendix D. The dataset also contains the variable HID, which can be used to match this dataset to the household level data set. Note that all of the expenditure variables are totals for the household. That is, they are not in per capita terms. Researchers will have to divide these variables by household size to get per capita numbers. The household size variable is included in the data set.

Abstract

Gallup Worldwide Research continually surveys residents in more than 150 countries, representing more than 98% of the world's adult population, using randomly selected, nationally representative samples. Gallup typically surveys 1,000 individuals in each country, using a standard set of core questions that has been translated into the major languages of the respective country. In some regions, supplemental questions are asked in addition to core questions. Face-to-face interviews are approximately 1 hour, while telephone interviews are about 30 minutes. In many countries, the survey is conducted once per year, and fieldwork is generally completed in two to four weeks. The Country Dataset Details spreadsheet displays each country's sample size, month/year of the data collection, mode of interviewing, languages employed, design effect, margin of error, and details about sample coverage.

Gallup is entirely responsible for the management, design, and control of Gallup Worldwide Research. For the past 70 years, Gallup has been committed to the principle that accurately collecting and disseminating the opinions and aspirations of people around the globe is vital to understanding our world. Gallup's mission is to provide information in an objective, reliable, and scientifically grounded manner. Gallup is not associated with any political orientation, party, or advocacy group and does not accept partisan entities as clients. Any individual, institution, or governmental agency may access the Gallup Worldwide Research regardless of nationality. The identities of clients and all surveyed respondents will remain confidential.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING AND DATA COLLECTION METHODOLOGY With some exceptions, all samples are probability based and nationally representative of the resident population aged 15 and older. The coverage area is the entire country including rural areas, and the sampling frame represents the entire civilian, non-institutionalized, aged 15 and older population of the entire country. Exceptions include areas where the safety of interviewing staff is threatened, scarcely populated islands in some countries, and areas that interviewers can reach only by foot, animal, or small boat.

Telephone surveys are used in countries where telephone coverage represents at least 80% of the population or is the customary survey methodology (see the Country Dataset Details for detailed information for each country). In Central and Eastern Europe, as well as in the developing world, including much of Latin America, the former Soviet Union countries, nearly all of Asia, the Middle East, and Africa, an area frame design is used for face-to-face interviewing.

The typical Gallup Worldwide Research survey includes at least 1,000 surveys of individuals. In some countries, oversamples are collected in major cities or areas of special interest. Additionally, in some large countries, such as China and Russia, sample sizes of at least 2,000 are collected. Although rare, in some instances the sample size is between 500 and 1,000. See the Country Dataset Details for detailed information for each country.

FACE-TO-FACE SURVEY DESIGN

FIRST STAGE In countries where face-to-face surveys are conducted, the first stage of sampling is the identification of 100 to 135 ultimate clusters (Sampling Units), consisting of clusters of households. Sampling units are stratified by population size and or geography and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size, otherwise simple random sampling is used. Samples are drawn independent of any samples drawn for surveys conducted in previous years.

There are two methods for sample stratification:

METHOD 1: The sample is stratified into 100 to 125 ultimate clusters drawn proportional to the national population, using the following strata: 1) Areas with population of at least 1 million 2) Areas 500,000-999,999 3) Areas 100,000-499,999 4) Areas 50,000-99,999 5) Areas 10,000-49,999 6) Areas with less than 10,000

The strata could include additional stratum to reflect populations that exceed 1 million as well as areas with populations less than 10,000. Worldwide Research Methodology and Codebook Copyright © 2008-2012 Gallup, Inc. All rights reserved. 8

METHOD 2:

A multi-stage design is used. The country is first stratified by large geographic units, and then by smaller units within geography. A minimum of 33 Primary Sampling Units (PSUs), which are first stage sampling units, are selected. The sample design results in 100 to 125 ultimate clusters.

SECOND STAGE

Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day, and where possible, on different days. If an interviewer cannot obtain an interview at the initial sampled household, he or she uses a simple substitution method. Refer to Appendix C for a more in-depth description of random route procedures.

THIRD STAGE

Respondents are randomly selected within the selected households. Interviewers list all eligible household members and their ages or birthdays. The respondent is selected by means of the Kish grid (refer to Appendix C) in countries where face-to-face interviewing is used. The interview does not inform the person who answers the door of the selection criteria until after the respondent has been identified. In a few Middle East and Asian countries where cultural restrictions dictate gender matching, respondents are randomly selected using the Kish grid from among all eligible adults of the matching gender.

TELEPHONE SURVEY DESIGN

In countries where telephone interviewing is employed, random-digit-dial (RDD) or a nationally representative list of phone numbers is used. In select countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day. Appointments for callbacks that fall within the survey data collection period are made.

PANEL SURVEY DESIGN

Prior to 2009, United States data were collected using The Gallup Panel. The Gallup Panel is a probability-based, nationally representative panel, for which all members are recruited via random-digit-dial methodology and is only used in the United States. Participants who elect to join the panel are committing to the completion of two to three surveys per month, with the typical survey lasting 10 to 15 minutes. The Gallup Worldwide Research panel survey is conducted over the telephone and takes approximately 30 minutes. No incentives are given to panel participants. Worldwide Research Methodology and Codebook Copyright © 2008-2012 Gallup, Inc. All rights reserved. 9

Research instrument

QUESTION DESIGN

Many of the Worldwide Research questions are items that Gallup has used for years. When developing additional questions, Gallup employed its worldwide network of research and political scientists1 to better understand key issues with regard to question development and construction and data gathering. Hundreds of items were developed, tested, piloted, and finalized. The best questions were retained for the core questionnaire and organized into indexes. Most items have a simple dichotomous ("yes or no") response set to minimize contamination of data because of cultural differences in response styles and to facilitate cross-cultural comparisons.

The Gallup Worldwide Research measures key indicators such as Law and Order, Food and Shelter, Job Creation, Migration, Financial Wellbeing, Personal Health, Civic Engagement, and Evaluative Wellbeing and demonstrates their correlations with world development indicators such as GDP and Brain Gain. These indicators assist leaders in understanding the broad context of national interests and establishing organization-specific correlations between leading indexes and lagging economic outcomes.

Gallup organizes its core group of indicators into the Gallup World Path. The Path is an organizational conceptualization of the seven indexes and is not to be construed as a causal model. The individual indexes have many properties of a strong theoretical framework. A more in-depth description of the questions and Gallup indexes is included in the indexes section of this document. In addition to World Path indexes, Gallup Worldwide Research questions also measure opinions about national institutions, corruption, youth development, community basics, diversity, optimism, communications, religiosity, and numerous other topics. For many regions of the world, additional questions that are specific to that region or country are included in surveys. Region-specific questions have been developed for predominantly Muslim nations, former Soviet Union countries, the Balkans, sub-Saharan Africa, Latin America, China and India, South Asia, and Israel and the Palestinian Territories.

The questionnaire is translated into the major conversational languages of each country. The translation process starts with an English, French, or Spanish version, depending on the region. One of two translation methods may be used.

METHOD 1: Two independent translations are completed. An independent third party, with some knowledge of survey research methods, adjudicates the differences. A professional translator translates the final version back into the source language.

METHOD 2: A translator

This layer shows the Hong Kong Population Distribution Population Distribution by usual spoken language by Large Tertiary Planning Unit Group in 2021. It is a subset of the 2021 Population Census made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data is in CSV format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of CSDI Portal at https://portal.csdi.gov.hk.

This layer shows the Hong Kong Working Population Distribution by Industry by Large Tertiary Planning Unit Group in 2016. It is a subset of the census data 2016 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in XLSX format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.

This layer shows the Hong Kong Population Distribution by Education Attainment by Large Tertiary Planning Unit Group in 2016. It is a subset of the census data 2016 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in XLSX format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.

The statistic shows the total population of India from 2019 to 2029. In 2023, the estimated total population in India amounted to approximately 1.43 billion people.

Total population in India

India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population.

With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year.

As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

The United States is leading the ranking by number of high networth individuals , recording 26.9 million individuals. Following closely behind is China with 13.9 million individuals, while Lesotho is trailing the ranking with 0 thousand individuals, resulting in a difference of 26.9 million individuals to the ranking leader, the United States. High Net Worth Individuals are here defined as persons with investible assets of at least one million U.S. dollars in current exchange rate terms.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

The statistic shows the unemployment rate in India from 1999 to 2023. In 2023, the unemployment rate in India was estimated to be 4.17 percent. India's economy in comparison to other BRIC states India possesses one of the fastest-growing economies in the world and as a result, India is recognized as one of the G-20 major economies as well as a member of the BRIC countries, an association that is made up of rapidly growing economies. As well as India, three other countries, namely Brazil, Russia and China, are BRIC members. India’s manufacturing industry plays a large part in the development of its economy; however its services industry is the most significant economical factor. The majority of the population of India works in this sector. India’s notable economic boost can be attributed to significant gains over the past decade in regards to the efficiency of the production of goods as well as maintaining relatively low debt, particularly when compared to the total amount earned from goods and services produced throughout the years. When considering individual development as a country, India progressed significantly over the years. However, in comparison to the other emerging countries in the BRIC group, India’s progress was rather minimal. While China experienced the most apparent growth, India’s efficiency and productivity remained somewhat stagnant over the course of 3 or 4 years. India also reported a rather large trade deficit over the past decade, implying that its total imports exceeded its total amount of exports, essentially forcing the country to borrow money in order to finance the nation. Most economists consider trade deficits a negative factor, especially in the long run and for developing or emerging countries.