Regional Population Projections for Japan: 2015–2045
Overview of the Method(Released in 2018)

Introduction
We publicized the new population projection by region in March 2018. We projected population byage, sex, and municipalities of Japan, except the municipalities in Fukushima Prefecture. Due to theFukushima Daiichi nuclear disaster triggered by the 3/11 Great East Japan Earthquake in 2011, it
remains troublesome to foresee geographical patterns of future resident mobility and vital statistics inFukushima Prefecture. Therefore, for Fukushima Prefecture, we decided to make use of the total
prefectural population of municipalities as a single projection unit.
Before 2010, the National Institute of Population and Social Security Research had organized
three separate population projection projects corresponding with three levels of geographicalaggregation: all Japan, prefectures, and municipalities. On the release of The Population Census ofJapan, the series of population projections begins with national projection, followed by prefecturaland municipal projections. However, the impacts of the Great East Japan Earthquake on reproduction
and migration behaviors were extensively outspread over municipalities. Hence, following the releaseof the population projection for Japan based on the 2010 Population Census, we conducted population
projections for municipalities first, and we obtained the future prefectural populations by aggregating
the population projections for municipal residents belonging to respective prefectures. In this regional
population projection for municipalities and prefectures as a part of the 2015 round projections, weadopt the approach of the 2010 round. Note that the totals by age and sex of populations in
geographical units reported here are consistent with the medium-variant fertility and medium-variant
mortality projection results of the national projections (published in 2017).
This paper summarizes the projection method and its implementation (i.e., details in assumption
settings). We acknowledge that we utilized statistical tables prepared with the secondary use ofquestionnaire information collected for The Vital Statistics of Japan under Article 32 and Article 33of the Statistics Act No. 53 of May 23, 2007.

An Overview of the Projection Method
1. Projection Horizon and Interval
The projection will be conducted every five years for 30 years, starting with 2015 and ending with 2045.

2. Target Municipalities and Prefectures of the Projection
The geographical units subjected to the projection included 1,798 municipalities (23 Tokyo specialwards, 128 wards in 12 major cities, 766 cities, 713 towns, and 168 villages), within the boundaries asof March 1, 2018, and one prefecture (Fukushima). As noted above, the projection for Fukushima
Prefecture was not conducted by municipalities but only prefectural population was projected; as aconsequence of the Fukushima Daiichi nuclear disaster triggered by the Great East Japan Earthquake,the future municipal patterns of population in Fukushima Prefecture are too uncertain to make aprojection. The 12 major cities, whose wards were taken as the projection unit, were identified by theavailability of data required for the projection. These cities were Sapporo (Hokkaido), Sendai (Miyagi)
Chiba (Chiba), Yokohama (Kanagawa), Kawasaki (Kanagawa), Nagoya (Aichi), Kyoto (Kyoto),Osaka (Osaka), Kobe (Hyogo), Hiroshima (Hiroshima), Kitakyushu (Fukuoka), and Fukuoka(Fukuoka), with the name of the respective prefecture in parentheses.

3. The Method
A variant of the cohort component method was adopted for the projections. The cohort component
method calculates future population by applying future vital rates to an age-specific population in acertain year. In the implementation of this method for the projection of the population of the age group
5 and above, survivorship rates and migration rates are required. For the projection of the populationof age group 0–4, the cohort component method requires future age-specific fertility rates and future
sex ratios at birth, in addition to survivorship and migration rates. However, because municipal-level
annual fertility rates fluctuate, we accommodated a child-woman ratio and a sex ratio of the populationof the age group 0–4. Hence, our projection requires 1) initial populations and making assumptions
for four sets of age- and sex-specific demographic rates, 2) future survivorship rates, 3) future
migration rates, 4) future child-woman ratios, and 5) future sex ratios of the population of the agegroup 0–4.
Note that the initial projection results produced using the future demographic rate assumptions
were adjusted so that the sums of populations by age and sex in geographical units conformed to ageand sex-specific populations in the national projection results (medium fertility and medium mortality).
We report these adjusted municipal populations, whose total is consistent with the national projection
results (medium fertility and medium mortality), as the final results in this paper. Figure 1 (at the endof this document) summarizes this projection procedure in a flowchart.

4. Initial Population
The initial population used as the base for the projection included total population – both Japanesenationals and foreigners – by five-year age group, sex, and municipality as of October 1, 2015,
according to “The Population of Nationality- and/or Age-Unknown Adjusted Population” in the 2015
Population Census of Japan (the Statistics Bureau, Ministry of Internal Affairs and Communications)1.
Note that the projection for Fukushima Prefecture considered prefecture as a single projection unit, so
the prefectural population in the census report was used as the base for Fukushima Prefecture.

5. Setting Future Age-specific Survivorship Rates
In order to reflect the future direction of the national projection’s survivorship-rate assumptions (thecase of medium mortality) (i.e., national tendency of improvements in life expectancy) on regionalmortality, we employ a measure called relative disparity, a ratio of regional survivorship rates to thenational rates. By the relative disparity, we set future survivorship rates for each region as moving thesame direction as the future national levels. Note that, throughout this paper, we refer to the ratio ofregional measures to that of broader area (i.e., the ratio of survivorship rates at the prefectural level tothat of the national level and also the ratio of the survivorship at the municipal level to that of theprefectural level) as a relative disparity or often simply as a disparity2.
For the age groups 55–59→60–64 and below, because regional differentials in mortality among
municipalities are limited, we set future survivorship rates by prefecture and applied them tomunicipalities within each prefecture. Specifically, by using The Prefectural Life Tables 2010 and The
Prefectural Life Tables 2015 (Statistics and Information Department, Minister’s Secretariat, Ministryof Health, Labour and Welfare), the lifetable survivorship ratios by the age group, sex, and prefecture

Somusyo Toukei-kyoku, Heisei-27-Nen Kokusei-chosa no Nenrei･Kokuseki Husyo wo
Anbun-shita Jinko(Sanko-hyo)1( https://www.stat.go.jp/data/kokusei/2015/kekka/anbun.html: access on December 19,2018). This population is the base for The Population Estimates conducted by the Statistics
Bureau. Basically, the population with unknown nationality and/or age was proportionately
distributed to every group of Japanese/foreigners and five-year-olds by living condition andsex within each municipality. By considering living condition, the procedure clarified
whether the population with unknown nationality/age lived alone or not. After theadjustment was made by municipalities, prefectural populations were obtained byaggregating the total populations of respective municipalities. Also, see The Outline of thePopulation Estimates (https://www.stat.go.jp/english/data/jinsui/1.html: accessed on
December 19, 2018).
2 As we adjusted municipal projection results obtained by mechanical calculation using
future vital rates to be consistent with the national projection result (published in 2017), we
utilized the relative disparity in order to set these future vital rates consistent with those of
the national projection. For example, suppose age- and sex-specific survivorship rate of aregion was 20% lower than that of all Japan, say 0.08 and 0.1, respectively, and thenational survivorship rate will improve 10% thus decreasing to 0.09 in future. Then, if weset and keep the relative disparity constant at 0.8, we have the future survivorship rate of
the region at 0.072 calculated by a multiplication of the relative disparity (0.8) and the rateof change for the national survivorship rate (0.9).

for the period 2010–2015 were calculated. Then, the relative disparity of the prefectural survivorshiprates to that of the national level was calculated by the age group and sex for each prefecture. These
relative disparities were assumed to diminish linearly, such that the disparities in the period 2040–
2045 would reach half the corresponding levels of the disparities in the period 2010–2015.
For the age groups 60–64→65–69 and above, since municipal differentials for mortality in eachprefecture are sizeable to the extent of significantly affecting the results of population projections, we
utilized the relative disparities of municipal survivorship rates to the respective prefecture’ssurvivorship rate. Specifically, the life table survivorship ratios by the age group, sex, and municipality
for the period 2000–2010 were calculated by using nLx functions in The Municipal Life Tables 2000,The Municipal Life Tables 2005, and The Municipal Life Tables 2010 (Ministry of Health, Labour andWelfare). Meanwhile, survivorship ratios of prefectures were calculated based on The Prefectural Life
Tables 2000, The Prefectural Life Tables 2005, and The Prefectural Life Tables 2010. Then, therelative disparities between municipal survivorship rates and the rates of respective host prefectures
were computed using these figures. Similar to the method employed in setting survivorship rates forthe age groups 55–59→60–64 and below, we set future municipal survivorship rates with theassumption that the relative disparities remain constant between 2000–2010 and 2040–2045.

6. Setting Future Migration Rates by Age and Sex
Inspired by the migration pool model3, we projected in-migrations and out-migrations by age group,
sex, and region separately for future migration. Specifically, for future emigrants we employed ageand sex-specific out-migration probability for each region, which was irrespective of destinations, andwas calculated by a certain region’s overall out-migrants in a period divided by its residents at thebeginning of that period. For future immigrants, we utilized a region’s share of immigrants in national
totals (“pool”) of immigrants by age and sex. Hereafter, we call these rates as the out-migration
probability and the share of immigrants as migration rates.
Specific patterns and regularities are not easily conceived for a time series of regional migration
rates by age and sex, given that socio-economic conditions of a nation and its regions during eachperiod in time considerably affect the migration behaviors. Hence, in principle, we assumed that thelatest patterns of migration rates in the period 2010‒2015 would last until the end of the projection
horizon.
On the one hand, for the out-migration probability, we use the “Tabulation on Internal

3See, among others, Section 6.5 in Smith, Stanly K., Jeff Tayman, and David A. Swanson,

A practitioner's guide to state and local population projections, Dordrecht: Springer, 2013.

Migration for Population4” from the 2015 Population Census of Japan by the Statistical Bureau, whereage- and sex-specific municipal population based on place of usual residence five years ago by present
residence (at the time of the census) was available for population that survived until the time of thecensus. This table made it possible to identify, for all regions in Japan, the number of out-migrants
who lived in a region in 2010, migrated out of the region, and survived until 2015, and we calculated
municipal out-migration rates by age and sex based on the out-migrants divided by the 2010 census
population. Then, we assumed that the out-migration rates for the period 2010–2015 remained constantuntil the end of the projection horizon.
On the other hand, regarding the in-migration rate, we first calculated the intercensal estimatesof age- and sex-specific in-migrants of all regions using the out-migration rates specified above. For
in-migration, we did not directly calculate in-migration rates from the 2015 Population Census’s
tabulation for migration, because there is a significant population whose residence five years before
the Census was not reported, especially in regions located in metropolitan areas5 6. Once we had thenumber of in-migrants for all regions on hand, calculating a region’s share of in-migrants wasstraightforward. We assumed that this share of the in-migrants in the period 2010‒2015 remained
constant until the end of the projection period7.
As we set the share of immigrants with reference to the migration pool rather than the traditional
net-migration model, we needed to follow the same concept when projecting future population withthese migration rates. We first calculated age- and sex-specific out-migrants for all regions by applying
the out-migration rates set above to population at the beginning of a period. This gave us “pools”(national totals) of migrants by age and sex, and then we were able to assign age- and sex-specific in-https://www.estat.go.jp/en/statsearch/files?page=1&layout=datalist&toukei=00200521&tstat=000001080
615&cycle=0&tclass1=000001093875&tclass2=000001093876&second2=1 accessed on
December 20th, 2018.
5 In the 2015 Population Census’s tabulation, the proportion of population whose residence
five years ago was unknown totaled 8.8% overall for Japan. However, the figure was 23.3%
in Tokyo Prefecture.
6 In-migration rates tend to be higher in urban areas, and we do not have more information
on whether in-migration rates of the population whose residence five years ago was
unknown exceeds those of the population whose residence five years ago was known. We
conjecture that using the census tabulation without addressing this issue is likely to beinappropriate.
7 In order to reflect a regional pattern of migration origin-destination combination observedin the 2015 Population Census in setting the future in-migration share, we incorporate
multiplicative coefficients of (1) future change in age- and sex-specific population
distribution of in-migrant’s origins (weighted total of population shares of in-migrant’s
origins who came to a target municipality by in-migrant distribution of the municipality asa weight) and (2) future change in age- and sex-specific (home) population distribution overregions. The former coefficient becomes greater when population of in-migrant’s origin
increases.
4

migrants to each region according to the in-migration share set above. However, due to internationalmigration, national totals of projected population with these in-migrants did not agree with the national
projection results, especially in the younger population. Hence, for age groups 55‒59→60‒64 andbelow, we projected the age- and sex-specific migrant’s “pools,” estimated by calculating thedifference between the national projection results (including international migrants) and totals ofmunicipal survival populations who had neither died nor migrated.
There are three types of exceptions among regions. First, for municipalities where the migration
patterns were significantly altered after the survey for The Population Census 2015, we set migration
rates reflecting the latest figures. Second, for municipalities where the patterns in the migration rates
had deviated from earlier patterns in the period 2010–2015, we made migration assumptions consistent
with the past patterns observed in the censuses before 2010 with regard to local conditions. Other thanthese, for municipalities with small population sizes where migration rates fluctuated, we aggregated
the number of migrants (both out-migrants and intercensal estimates for in-migrants) during four
periods, from 1995–2000 to 2010–2015, to set the future net migration rates that reflects long-run
average levels in the region.

7. Setting Future Child-Woman Ratios
The child-woman ratio (CWR, hereafter) refers to the average population of the age group 0–4 perwoman in the age group 15–49 in a region. We utilized age- and sex-specific population fromthe national projection results (medium fertility and medium mortality scenario) to set the future
CWRs by the relative disparities between the municipal CWRs and the national CWR.
Specifically, using the 2015 Population Census, we calculated the CWRs of municipalities andof all Japan, and took the national CWR as the basis for normalizing the municipal CWRs in
the form of the relative disparity for an assessment of regional fertility differentials. Next, weset future municipal CWRs with the assumption that relative disparities remained constant from 2015
to 2045 so as regional fertility differentials but future municipal fertility as a whole follows the nationalchange. A similar method was employed for Fukushima Prefecture.
There are a few municipalities where the CWRs deviated in 2015 from the past patterns. For
these municipalities, we calculated average CWRs for the period 2000‒2015, and set the future CWRs,
keeping the average CWRs constant for 2020–2045.

8. Setting Future Sex Ratios for the Age Group 0–4 Population
Sums of male and female populations of the age group 0–4 were projected based on the future CWRs
set in the section 7 above. We needed sex ratios for the age group 0–4 population to divide thepopulation into males and females.

For the sake of simplicity, given limited variation in the sex ratio of the youngest population in
geographical units, we calculated the sex ratios for the age group 0–4 population from the national
projection results (medium fertility and medium mortality scenario) until the end of theprojection horizon. Then, we applied the sex ratios of the national average to all municipalities.

Figure 1. Procedure for Regional Population Projection by the Cohort Component MethodSTAR

Age-sex specific population
k＝1

Assumptions forfrom Population Census

survivorship rates

Assumptions for
migration rates
Age less than 65‒69 in 2015+5k
NoYes
Projected age-sex specificUnadjusted age-sex specificpopulation in 2015+5k

population in 2015+5k

Unadjusted female
population of age 15‒
49 in 2010+5k

Unadjusted
population of age

Assumptions forchild-woman ratios

Assumptions for sex ratiosof 0‒4 population.

0‒4 in 2015+5k
Age-sex specificpopulation in 2015+5k
by Population Projection

for Japan: 2016‒2065(released in 2017)

Yesk≦6k＝k +1

Adjusted age-sex specificpopulation in 2015+5k

NoEND

Adjustments for consistency inage-sex specific population

Output