variables: 959839
Data license: CC-BY
This data as json
| id | name | unit | description | createdAt | updatedAt | code | coverage | timespan | datasetId | sourceId | shortUnit | display | columnOrder | originalMetadata | grapherConfigAdmin | shortName | catalogPath | dimensions | schemaVersion | processingLevel | processingLog | titlePublic | titleVariant | attributionShort | attribution | descriptionShort | descriptionFromProducer | descriptionKey | descriptionProcessing | licenses | license | grapherConfigETL | type | sort | dataChecksum | metadataChecksum |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 959839 | Total population | people | 2024-07-30 12:02:09 | 2024-07-30 12:02:10 | 1816-2016 | 6645 | {
"name": "Total population",
"unit": "people",
"tolerance": 5,
"numDecimalPlaces": 0
} |
0 | tpop | grapher/cow/2024-07-26/national_material_capabilities/national_material_capabilities#tpop | 2 | minor | Total population | Total population is the size of a state’s civilian population in each year for the period 1816-2016. _Data Acquisition and Generation_ While the most reliable total population figures usually appear in national government tallies, modern census-taking was rare before 1850 in Europe and countries of European settlement, and rare before the First World War elsewhere. In all periods, the accuracy and reliability of national census data seem to vary with the level of economic development. As a result, data from the developing world require particular scrutiny. A census may be of the de facto population, comprising all residents within the national boundaries, or of the de jure population, comprising only those who are legal residents. We used the former, where possible, to which totals of military personnel abroad were added. Since the differences between de jure and de facto (between "total" and "total home") population are typically small, we did not analyze this data for sensitivity to these coding distinctions. The United Nations Statistical Office has an estimated yearly total population series, corrected for over- and under-enumeration to the extent possible, for most nations since 1919. We relied on those series where possible. For prior years and nations where we found one or more plausible time series, we took data from the sources presenting the greatest continuity with the U.N. data. We uncovered most of the general censuses taken since 1816 and used alternative sources for the numerous remaining gaps. For example, Japan maintained a system of population registration through a rough running tally. Other countries took sample surveys from which they constructed estimates of the total population. We judged these sources the most reliable. For the occasional nation maintaining reasonably complete registers of vital events (e.g. the United Kingdom), we estimated missing data utilizing Formula TPOP One: Formula TPOP 1: Missing Total Population Data Estimations p(t) = p(to) + b(t) - d(t) + i(t) - e(t), where: p(t) is the known or estimated population at time t, p (to) is the population recorded at time to, and b(t), d(t), i(t), and e(t) are the respective numbers of births, deaths, immigrants, and emigrants recorded since t0. Net migration is usually small enough to be safely disregarded. For nations maintaining registers of births and deaths but not of migration, we estimated i(t) - e(t) to be zero. In lieu of complete demographic records, we resorted to estimation either (1) by interpolation, or (2) by least-squares linear regression with time as the independent variable. The choice between them was based on the availability and quality of information, and on whether the period in question was marked by major wars or territorial boundary changes. First, however, we must note four types of situations in which such change did not take place. The first concerns the many cases for which censuses had been taken regularly. In these cases, the only missing records were for the intervening years. In such instances we interpolated between census records using Formula TPOP Two Below: Formula TPOP Two: Interpolation Between Known Data Points logp(t)= (logp(t2)−logp(tx) (t2 −t1)(t−t1)+logp(t) where: p(t1) and p(t2) are the known population figures at time t1 and t2. This method entailed the assumption of a constant growth rate over the period delineated by t1, t2, and tx from which the formula is derived. In a second type of situation, taking account of the country's demographic history, the manner and quality of its census-taking, the later population trends, and the opinion of demographers, we were able to discern a plausibly reliable population series even though regular censuses were not available. Again, we resorted to interpolation as here it seemed appropriate. A second type of concern arose where data for the final years in a series were missing, either because of loss of national identity (e.g. Estonia, Latvia, and Lithuania in 1940, or Austria- Hungary during World War One). In these cases, we resorted to extrapolation using the above interpolation formula. A third concern was a problem of having no uniform data series at our disposal and what sources were available providing only a patchwork of spotty and conflicting coverage. In this type of situation, we estimated population by regression performed on the logarithms of the known data. A prime consideration in our willingness to use this technique was that data for well-documented nations indicates that growth rates usually change quite slowly. Distortions were thereby introduced but not to as great a degree as would arise from applying interpolation and extrapolation to these highly erratic data. Where necessary, to bring the estimates into agreement with the uniform (typically post-1919 United Nations) series of an adjoining epoch, we raised or lowered the regression line - while maintaining the same slope - such that the line passed through the adjacent values of the series. Finally, in situations of marked discontinuity in population trends associated with wars and exchanges of territory, we applied the above methods as appropriate, but only to the separate intervals on either side of the discontinuity, and only where it could document its demographic magnitude. Interpolation, for example, could be used only if total population before and after the break, or one of them plus the magnitude of the change, was known. We treated all cases in which the nation gained or lost at least 1% of its total home population in this manner. For territorial exchanges, we were able to document many of the gains and losses. We were, however, usually unsuccessful in documenting war losses. Its method was to adjust for the affect of territorial changes and then to extrapolate forward from pre-war and backward from post-war data. Unless otherwise noted, population losses due to war were prorated over its duration. The most pronounced instance was over estimate of Chinese population during and immediately after the Taiping rebellion. | [] |
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