Special edition · SPECIAL
Mud at rice-planting time and the combine at harvest. A child born on a farm decides, on finishing high school, whether to take over the family fields. A child from a non-farming family can study at an agricultural college or university, join a farming company, or train and start a farm of their own. What to grow (rice, open-field vegetables, greenhouse crops, fruit, dairy or beef), the gentan rice quotas (1970 to 2017) and growing rice after they ended. Heavy rain and snow, price crashes. Take on a neighbor's fields, incorporate, open a farm stand or a farm restaurant, bring in drones. And at the end, who will take over the land? The pixel-art background changes with the seasons and your life: rice planting, green paddies, the harvest, snowy fields, greenhouses, orchards, the barn, the farm stand, the autumn festival and the veranda.
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Sources: Ministry of Agriculture, Forestry and Fisheries (MAFF): 2025 Census of Agriculture and Forestry (as of February 1, 2025), 2025 Survey of New Farmers (published August 2026), the new-farmer support program, the certified new farmer system, the agricultural college overview, the White Paper on Food, Agriculture and Rural Areas (end of production targets from the 2018 crop), and the laws on sixth-sector industrialization (2010) and smart farming technology (2024). Economic Planning Agency, Annual Economic Report 1971 (rice production adjustment in earnest from 1970). The odds of entering farming, crop choice, farm size, income, training and independence timing, the year government funding starts (2012 in this edition), weather, disaster and price events, and how often a successor is found are game assumptions. All people, organizations and producing areas are fictional and unrelated to any real cooperative, company or brand. Sources for "How to become a farmer": MAFF 2025 Census of Agriculture and Forestry, 2025 Survey of New Farmers, new-farmer funding, the certified new farmer system, the agricultural college overview and the White Paper on Food, Agriculture and Rural Areas. · The explainer (real data and assumptions)
Japan's farm ministry (MAFF) counts new farmers in three groups: people who join their family's farm, people hired by farming companies and other employers, and new entrants who start with their own land and money. In 2025 these numbered 29,240, 10,250 and 3,360, for a total of 42,850 (14,410 of them aged 49 or younger).
Prefectural agricultural colleges exist in 41 prefectures. The main course is for people with high-school-level education and is typically two years and at least 2,400 hours, with specialties such as rice, vegetables, fruit, flowers, dairy and beef. About half the time is lectures and half hands-on practice (MAFF).
Under this system, a municipality approves the farming plan a new farmer draws up, and certified new farmers receive focused support. It covers young people generally aged 18 to 44, people under 65 with specific skills, and corporations where such people make up a majority of the officers (MAFF).
People 49 or younger aiming to become the next generation of farmers can receive a training allowance while training at an agricultural college or an advanced farm (¥137,500 a month, up to ¥1.65 million a year, for up to 2 years), and start-up funding until the business is stable (¥1.65 million a year for up to 3 years). Conditions and procedures are handled by local governments (MAFF).
Japan had 836,000 farms in 2025, down 22.3% in five years, while incorporated farms rose 10.1% to 34,000 and average farmland grew to 3.6 ha. 1,036,000 people farm as their main work on individually run farms, and 69.6% of them are 65 or older (2025 Census of Agriculture and Forestry). The government stopped handing out rice production targets from the 2018 crop (MAFF white paper).
These rules and numbers come from official MAFF pages and statistics. Income, farm size, disaster and price events, how many new farms survive and how often a successor is found in the game are game assumptions. All people and organizations in the game are fictional.
Sources: 2025 Census of Agriculture and Forestry summary (MAFF, Japanese) · 2025 Survey of New Farmers (MAFF, Japanese) · New-farmer funding (MAFF, Japanese) · Certified new farmer system (MAFF, Japanese) · Agricultural colleges (MAFF, Japanese) · White Paper on Food, Agriculture and Rural Areas (MAFF, Japanese)
Be born the normal way (no choosing)
The special editions are not meant to mock any job, way of life or family situation. They draw on public statistics and other real data to let you experience, as entertainment, what could happen in that life. Every character is fictional.
Beta 0.9 · updated 2026.10.18
Born in Japan
Somewhere in Japan, in some year, to some family. Born without a choice, you live your one life all the way to the end.
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SPECIAL EDITION
You are born into circumstances that lead toward this life. How far you get still depends on luck and your choices, just as in a regular life.
The special editions are not meant to mock any job, way of life or family situation. They draw on public statistics and other real data to let you experience, as entertainment, what could happen in that life. Every character is fictional.
No matches. Try another word, or tell us which edition you want on the roadmap.
HISTORY SPECIALS
What makes it different from other life simulators
Self-Defense Force members, doctors, comedians, yakuza, monks, politicians... A life born in Japan can take many paths. Start by looking at a few examples.
"Born in Japan" (日本に生まれる) began when I came across a life simulator in which you are born somewhere in the world and live out a whole life.
A world that feels distant when you only read numbers and explanations starts to connect to you when you follow one person's life. That experience was wonderful, and I wished Japan's everyday life and culture could be shared the same way.
We don't get to choose where we're born, when, or into what family.
What if you had been born in a different prefecture? What if your parents had been better or worse off? What if you had been born a little earlier, or later? Who would you have met, what would you have struggled with, and what would you have held dear?
Even within the same Japan, the view changes depending on where and when you grow up. School, work, marriage, life with family. Each of those choices involves not only a person's own feelings but also local customs, the mood of the times, and how society is set up.
On this site, you can live one person's life, guided by Japan's official statistics and mixed with game assumptions. It begins with conditions you can't choose, has moments where you decide for yourself, and brings events you never saw coming. Through it, I hope you can feel how Japanese culture lives on in everyday life and everyday choices.
For people living in Japan, I want to offer a chance to touch lives outside their own idea of "normal." For people abroad, I want to offer a way into the daily life and cultural background of Japan that you can't see from tourist spots or the news alone.
Of course, no single simulation can represent all of Japan. There are circumstances and feelings that statistics can't hold, and every life has meaning only the person living it can know. That's exactly why I hope the life you live here becomes a reason to want to know real people better.
The same birth can lead to a different life.
After you finish playing, maybe you'll look at the road you've walked a little differently, or imagine the life of someone far away. This site hopes that small act of imagination leads to a better understanding of people and cultures.
You can't choose where you're born, your family, or your era. "Born in Japan" is a free life simulator: you are born at random in one of Japan's prefectures, in some year between 1947 and 2010, as the child of some family, and you live a whole life to the end, one year at a time, through decisions about school, dropping out, jobs, changing jobs, marriage, housing, money, and caregiving, along with events like traffic accidents and becoming a victim of crime. No sign-up required.
Read the numbers: The average life in Japan · Oya gacha: the family you are born into · The odds of being born in Japan
The probabilities and amounts for life expectancy, wages, college enrollment, marriage, childbirth, divorce, pensions, savings, and more are based on the following official statistics.
Detailed explainers by area: Birth / School and dropping out / Work and wages / Marriage, children, and divorce / Housing / Savings and investing / Retirement and pensions / Accidents and crime / Life expectancy / Unusual lives (all). There's also a comparison by prefecture.
Parts not covered by statistics (rent, home prices, expected investment returns, how wages change after switching jobs, and so on) are filled in with assumptions that have no source. Which parts are real data and which are assumptions is listed in the notes at the bottom of the results screen.
For analytics, we send information about page views and interactions (how far you've progressed in a life, the decisions shown and chosen, use of the share buttons, and so on, including device and browser information and a cookie-based identifier) to Google Analytics (Google LLC). We use it to improve the service, and we never send the text you type (short notes, your answers during breathers, or names). Amounts are shown in today's money, with inflation removed. This is not a prediction of anyone's future. For visits from the European Economic Area, the UK, and Switzerland, we don't run cookie-based analytics until you allow it.
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Operated by the Born in Japan team (Japan)
Enter your birth year, education, job, and so on, and we'll simulate about 200 lives under the same conditions to show where your income and net worth fall. What you enter is used only on this device and is never sent or saved.
This is an estimate from a simplified model. You're compared with lives simulated from the same birth and conditions, not ranked against real statistics.
Your answers are saved only on this device and sent nowhere. If you stop partway, you can pick up where you left off.
These values come from about 160 lives simulated with the game's model, with the same birth, the same education and work style, and the same family shape. They are not statistics themselves and include assumptions.
Your "My Life card" puts three scenes on one card: your birth, your happiest year, and today. The words you wrote are included too.
These are lives lived to the end here. Stop by and leave some flowers. We show only the names the game assigned automatically, never words written by the people who played.
These are examples made by the simulation, not lives played by real people.
No one has lived a life to the end here yet. You might be the first.
Now it's your turn to be born somewhere in Japan.
Anyone who opens the link can start a life from the same birth as you.
Dates, numbers of people, and the like are publicly reported facts. How likely the experiences in your life were (earthquake damage, places you went, and so on) is an assumption.
This life will appear anonymously in "Everyone's Lives" (no names or notes are shown).
The real data and assumptions for unusual lives (chasing a dream, medical school and retaking entrance exams, elite private elementary schools, growing up in a company president's family, politicians, hairdressers, YouTubers, children raised in a religious group, immigrants and mixed-heritage children, yakuza, crime, alcohol) are listed on the explainer page "Unusual Lives". Births where one parent is a foreign national (Ministry of Health, Labour and Welfare, Vital Statistics) and the number of foreign residents (Immigration Services Agency, Statistics on Foreign Residents) are real data; the chances of making it big, pass rates, election odds, incomes, and so on are assumptions.
Parts that use real data: life expectancy (Ministry of Health, Labour and Welfare, Abridged Life Tables 2024); wages (Ministry of Health, Labour and Welfare, 2025 Basic Survey on Wage Structure, including graduate-school graduates, by sex, age, education, and employment type, and by prefecture); population by prefecture (Statistics Bureau of Japan, Population Estimates as of October 1, 2024); college enrollment rates and gender gaps by prefecture (MEXT, FY2022 School Basic Survey); the share of regular vs. non-regular employment and leaving work due to childbirth or childcare (Statistics Bureau of Japan, 2022 Employment Status Survey); the share of people who leave home for a university in Tokyo (MEXT, School Basic Survey, entrants by prefecture and home region; read from charts, with an error of ±2–3 points); the share of households that own land (Statistics Bureau of Japan, 2023 Housing and Land Survey, land tabulation, site-ownership rate; this is not the homeownership rate itself); the never-married rate at age 50 (Statistics Bureau of Japan, Population Census, as compiled in Ministry of Health, Labour and Welfare materials); the average age at first marriage (husbands 31.1, wives 29.7) and the distribution of divorces by length of cohabitation (Ministry of Health, Labour and Welfare, 2023 Vital Statistics); the distribution of the number of children per couple (National Institute of Population and Social Security Research, 16th Japanese National Fertility Survey); wages by industry, sex, and age (2025 Basic Survey on Wage Structure, Table 5-2; public servants are not covered, so values for compound services and other services are used instead); annual income by company size (National Tax Agency, 2025 Statistical Survey of Actual Status for Salary in the Private Sector, average salary by capital bracket); mortgage rates (3.25%), time-deposit rates (0.45%), inflation (1.8%), and changes in official land prices (residential land: three major metropolitan areas +3.5%, nationwide +2.1%, regional areas +0.9%; Japan Finance Corporation, Economic and Financial Data, September 2026 issue); the breakdown and average amount of savings, and savings by age of household head (Statistics Bureau of Japan, Family Income and Expenditure Survey, Savings and Liabilities, 2025); the share of take-home pay spent by working households (same survey, Income and Expenditure, 2025; average propensity to consume of 65.0% for worker households among households of two or more); the level of living costs by age (Statistics Bureau of Japan, 2024 National Survey of Family Income, Consumption and Wealth); the share of people who changed jobs within five years and the breakdown of reasons for leaving their previous job (Statistics Bureau of Japan, 2022 Employment Status Survey); pension amounts (Ministry of Health, Labour and Welfare, 2017 Survey on Old-age Pension Recipients, average amounts by sex; the full old-age basic pension from the Japan Pension Service); retirement allowances at mandatory retirement and the share of companies with a retirement allowance system (Ministry of Health, Labour and Welfare, 2023 General Survey on Working Conditions, average retirement benefits per mandatory retiree by education and years of service, and the share of companies with a system by company size). The share of people born into households in relative poverty, and the share born into single-parent households and their poverty rate (Ministry of Health, Labour and Welfare, Summary Report of the 2025 Comprehensive Survey of Living Conditions: the child poverty rate, the poverty rate of working-age households with children and only one adult, and the share of households with children that consist only of a single parent and unmarried children; for each generation, we average the values from the survey years that fall in their childhood). The share of students who drop out and the breakdown of reasons (high school: MEXT, FY2024 Survey on Problem Behavior, School Non-attendance, and Other Student Guidance Issues, dropout rate of 1.4%, and the share by reason from the FY2023 edition of the same survey; universities, junior colleges, and graduate schools: MEXT, FY2023 Survey on Students Who Dropped Out or Took Leave, universities 2.04%, junior colleges 3.95%, master's 2.60%, doctoral 3.49%, and the share by reason; in all cases the annual rate is compounded over the years of enrollment). The chance of being injured in a traffic accident (National Police Agency, Trends in Traffic Accidents 1948–2020, White Paper on Crime Victims 2021–2024, and National Police Agency figures for 2025; the number of injured people each year divided by the population); the chance of becoming a crime victim (National Police Agency, Crime Situation in 2025: reported cases of bicycle theft, burglary, fraud, assault, and bodily injury divided by the population, adjusted up or down each year by the trend in reported Penal Code offenses; the trend for 1989–2018 is read from charts); the average loss from fraud (fraud losses ÷ reported cases in the same source = about ¥5.55 million); the chance of being arrested or taken into protective guidance for delinquency as a teenager (Ministry of Justice, White Paper on Crime 2017: juvenile delinquency rates by birth year, rates per population by age group, and the share of girls); the share of people who smoke (Ministry of Health, Labour and Welfare, 2023 National Health and Nutrition Survey, habitual smokers: men 25.6%, women 6.9%); the average life expectancy in the life map and the survival curve (Ministry of Health, Labour and Welfare, Abridged Life Tables 2024); the basis for depicting single parents as mothers (the number of mother-child and father-child households in the Comprehensive Survey of Living Conditions); names for each birth year (Meiji Yasuda Life Insurance, Popular Names by Birth Year, the top 10 for each year); family names (the top 5 family names in your birth prefecture and their shares from Meiji Yasuda Life Insurance's National Surname Survey, 2013; otherwise in proportion to the number of people with each of the top 500 family names nationwide; the numbers are estimates). These real data are calibrated so that the simulation's results come close to the age-specific values in the same statistics. The values used for calibration (bonus and overtime additions, the chance of moving from non-regular to regular employment, the chance of leaving work after childbirth, and so on) are assumptions without a source. All other values are rounded approximations based on official statistics, including: the share of people who work in each industry and company size; the shares choosing humanities vs. sciences; the wage premium for science and engineering (+4%) and the discount for education and the arts (−3%); the rates of going on to graduate school (master's) and doctoral programs; the shares of post-PhD career paths and the chance of a postdoc landing a permanent position (40%); age differences in how easy it is to change jobs, and the additions for non-regular workers and women; the shares of people whose wages go up, stay the same, or go down after changing jobs, and by how much; the chance of moving from non-regular to regular employment (about 40%); expected returns and volatility for stocks (5% nominal, 14% volatility), bonds (1.5%), and real estate investment (4%, 10% volatility); the scenario design limiting job-change decisions to three in a lifetime; returns on life insurance and the like; using the average of managerial, clerical, and technical jobs and manual jobs for the retirement allowance of high school graduates; making retirement allowances for under 20 years of service proportional to years of service; the mapping to company-size categories and the share of small family businesses with a retirement allowance system (50%); the share of the surplus (take-home pay minus spending) that does not remain as savings (15% under age 40, 65% in your 40s, 55% at 50 and over, plus 20 points for unmarried people; this stands for spending and drawdowns that statistics struggle to capture, such as cars, down payments, education costs, and support for children and parents, and was set to match savings by age in the Family Income and Expenditure Survey and the financial assets of single-person households in the Japan Financial Literacy and Education Corporation's Survey of Household Finances, 2024); how a home's value is split between land and building, and the building's depreciation (building share of 50–60% when new, 3% per year); paying off any remaining mortgage at retirement with the retirement allowance and other funds; applying the 65% average propensity to consume to single-person households too; applying 1985–86 values for poverty and single-parent rates to generations whose childhood came before 1985, when no statistics exist; treating the share of single-parent households as the share of children (single parents living in three-generation households are not included); how strongly the national position of non-poor households is tilted by the prefecture's income level; how far the position of non-poor single-parent households is shifted lower; differences in dropout likelihood by family finances; using the junior-college dropout rate for vocational schools; assuming dropout rates don't change across generations; having people who drop out of university because they "want to take a different path" re-enroll in a vocational school; using high school graduate wages for junior high school graduates (junior high graduate wages are not yet included); the amounts, probabilities, share chosen under Auto, and effects on health and mood of this year's focus and small decisions (hobbies, pets, school clubs, cars, helping relatives, the way home from a drinking party, risky invitations, moving to the countryside, a word of thanks, a wavering heart); the size of smoking's effect on health; your spouse's personality and job; the weighting that makes higher-ranked names among the top 10 more likely to be chosen; limiting family names to your prefecture's top 5 and the national top 500, and how they are combined (names outside the top 5 are chosen based on national shares, capped at the share of that prefecture's 5th-ranked name); women taking their husband's family name when they marry; the parents' ages and the type of home in family scenes; assuming the likelihood of traffic injuries doesn't change with age; counting each incident as one victim; assuming the mix of offense types doesn't change by year; treating crime levels before the Heisei era as the same as in 1989; using the juvenile delinquency rate as the chance of being arrested in that year (since re-arrests of the same person aren't distinguished, the share arrested at least once in a lifetime comes out on the high side); applying age-group values to generations without birth-year values; the size of the effects of accidents, victimization, and delinquency on health, mood, and money; the median loss from fraud (¥1 million); the share of people who divorce (about 30%); the division of property at divorce; the survivor's pension added to women's pensions; rent and home prices; and living costs by household size. The net-worth line on the graph is smoothed with a three-year average (including the year before and after) so that yearly swings from investing don't make it hard to read (the net worth shown as a number is the value for each year). Amounts on screen are in today's money, with inflation removed (think of ¥1 million as ¥1 million today, not ¥1 million 100 years from now). This is not a prediction of anyone's future. From 2027 onward, figures are estimates that assume current statistical levels continue. For analytics, we send information about page views and interactions (how far you've progressed in a life, the decisions shown and chosen, use of the share buttons, and so on, including device and browser information and a cookie-based identifier) to Google Analytics (Google LLC). We use it to improve the service, and we never send the text you type (short notes, your answers during breathers, or names). For visits from the European Economic Area, the UK, and Switzerland, we don't run cookie-based analytics until you allow it.
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Example life (made by the simulation)
