In the fiscal year 2022, the gross prefectural domestic product of Tokyo Prefecture amounted to around ***** trillion Japanese yen at current prices. This marked an increase from a GDP of about ***** trillion yen.

Key information about Japan Market Capitalization: % of GDP

• Japan Market Capitalization accounted for 163.9 % of its Nominal GDP in Dec 2024, compared with a percentage of 146.8 % in the previous year
• Japan Market Capitalization: % Nominal GDP is updated yearly, available from Dec 1994 to Dec 2024
• The data reached an all-time high of 163.9 % in Dec 2024 and a record low of 47.3 % in Dec 2002

CEIC calculates annual Market Capitalization as % of Nominal GDP from monthly Market Capitalization and annual Nominal GDP. Japan Exchange Group Inc. provides Market Capitalization in local currency. Economic and Social Research Institute provides Nominal GDP in local currency. Market Capitalization covers Tokyo Stock Exchange only, which is not the only equity market in the country but is highly representative. Before July 2013 Total Market Capitalization of TSE covers TSE 1st Section Shares, 2nd Section Shares and Mothers Shares. Since July 2013, Total Market Capitalization of TSE also covers Market Capitalization of Tokyo Pro Market Shares, JASDAQ Standard Shares and JASDAQ Growth Shares. On April 2022, the stock market was restructured into three new market segments (Prime Market, Standard Market, and Growth Market) replacing previous four market divisions: 1st Section, 2nd Section, Mothers, and JASDAQ (Standard and Growth).


Further information about Japan Market Capitalization: % of GDP

• In the latest reports, Prime Market recorded a monthly P/E ratio of 21.8 in Nov 2025
• Nikkei 225 Stock closed at 50,253.9 points in Nov 2025

This table shows the results from the simulations assuming the shutdown of all non-essential production activities. These results are based on the average of the simulations. (Unit: trillion yen).

Actual value and historical data chart for Japan GDP Per Capita Us Dollar

In 2023, Tokyo Prefecture recorded a 0.99 total fertility rate (TFR). The total fertility rate in the prefecture showed a steady decrease in recent years and fell below one for the first time in 2023.

The Gross Domestic Product per capita in Japan was last recorded at 46097.43 US dollars in 2024, when adjusted by purchasing power parity (PPP). The GDP per Capita, in Japan, when adjusted by Purchasing Power Parity is equivalent to 259 percent of the world's average. This dataset provides - Japan GDP per capita PPP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2023, Tokyo Prefecture registered 1.49 new divorces per 1,000 inhabitants, up from 1.43 divorces in the previous year. The divorce rate in the prefecture had shown a steady decrease until 2023.

In 2023, the male population in Tokyo Prefecture amounted to around 6.6 million. The number of men in the prefecture declined in 2021 for the first time in the past decade.

In the fiscal year 2021, ***** Prefecture recorded the highest GDP growth in real terms in Japan, at *** percent. The real GDP of Tokyo Prefecture grew by *** percent year on year.

In the fiscal year 2021, Tokyo Prefecture recorded the highest GDP at current prices in Japan, at around ***** trillion Japanese yen. The nominal GDP of Osaka Prefecture amounted to **** trillion yen.

Preliminary gridded GDP dataset under SSP2 for 2020–2100 in Tokyo, London, and Bangkok (spatial resolution: 30 arc-seconds)。

In 2023, the female population in Tokyo Prefecture amounted to around 6.85 million. The number of women in the prefecture decreased in 2021 for the first time in years.

In 2023, around 137,240 deaths were recorded in Tokyo, Japan, decreasing slightly compared to the previous year. In 2023, the number of deaths reported in the Japanese metropolis was the highest among all 47 prefectures.

In the fiscal year 2021, the Kanto region recorded the highest GDP at current prices in Japan, at ***** trillion Japanese yen. The GDP of Tokyo Prefecture, which is part of the Kanto region, amounted to ***** trillion yen in the same year.

The statistic shows the gross domestic product (GDP) per capita in Japan from 1987 to 2024, with projections up until 2030. In 2024, the gross domestic product per capita in Japan was around 32,443 U.S. dollars. For further information, see Japan's GDP. Japan's economy Japan is the world’s second largest developed economy and a member of the Group of Eight, also known as G8, which is comprised of the eight leading industrialized countries. Due to a weak financial sector, overregulation and a lack of demand, Japan suffered substantially from the early 1990s until 2000, a time referred to as ‘’The Lost Decade’’. Japan’s economy is still slowly recovering from the country’s asset price bubble collapse; however it continues to struggle to retain economic milestones achieved in the 1980s. Japan’s response to the crash was to stimulate the economy, which in turn resulted in extensive amounts of debt that further increased into the 21st century, most notably after the 2008 financial crisis. Despite maintaining a surprisingly low unemployment rate, demand within the country remains inadequate, primarily because Japanese residents spend a rather small fraction of the money they earned from the workplace. Lower demand often has a direct effect on production, with companies seeing not enough profits to continue production at such a high rate. Based on the consumer confidence index, Japanese households found that their quality of life, income growth, employment and propensity to durable goods was below satisfactory standards, perhaps due to these households still experiencing the effects of the 1990s bubble crash.

In 2023, the gross domestic product (GDP) of the Guangdong - Hong Kong - Macao Greater Bay Area reached around **** trillion U.S. dollars. Although this was not much less than the GDP of the Tokyo Bay and more than the New York Metropolitan Area, per capita GDP in China's Greater Bay Area was considerably lower.

Using all stocks listed in the Tokyo Stock Exchange and macroeconomic data for Japan, the dataset comprises the following series:

1. Monthly returns for 25 size-book-to-market equity portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
2. Monthly returns for 20 momentum portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
3. Monthly returns for 25 price-to-cash flow-dividend yield portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
4. Fama and French three-factors (RM, SMB and HML), following the Fama and French (1993) methodology. (Raw data source: Datastream database)
5. Fama and French five-factors (RM, SMB, HML, RMW, and CMA), following the Fama and French (2015) methodology for all factors, except for RMW, which is determined using the return on assets as sorting variable, as in Hou, Xue and Zhang (2014). (Raw data source: Datastream database)
6. Private final consumption expenditure, in national currency and constant prices, non-seasonally adjusted, for Japan. (Raw data source: OECD)
7. Consumer Confidence Index (CCI) for Japan. (Raw data source: OECD)
8. Three-month interest rate of the Treasury Bill for Japan. (Raw data source: OECD)
9. Gross Domestic Product (GDP) for Japan. (Raw data source: OECD)
10. Consumer Price Index (CPI) growth rate for Japan. (Raw data source: OECD)

We have produced all return series using the following data from Datastream: (i) total return index (RI series), (ii) market value (MV series), (iii) market-to-book equity (PTBV series), (iv) total assets (WC02999 series), (v) return on equity (WC08301 series), (vi) price-to-cash flow ratio (PC series), and (vii) dividend yield (DY series). We have used the generic rules suggested by Griffin, Kelly, & Nardari (2010) for excluding non-common equity securities from Datastream data. We also exclude stocks with less than twelve observations in the period from July 1992 to June 2018. Accordingly, our sample comprises a total number of 5,312 stocks.

REFERENCES:

Fama, E. F. and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56. Fama, E. F. and French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116, 1–22. Griffin, J. M., Kelly, P., and Nardari, F. (2010). Do market efficiency measures yield correct inferences? A comparison of developed and emerging markets. Review of Financial Studies, 23, 3225–3277. Hou K, Xue C, Zhang L. (2014). Digesting anomalies: An investment approach. Review of Financial Studies, 28, 650-705.

SummaryThis metadata record provides details of the data supporting the claims of the related manuscript: “Water scarcity will constrain the formation of a world-class megalopolis in North China”.The data consist of 15 Excel .xlsx format data files.The related study investigated the water challenge the water-scarce Beijing-Tianjin-Hebei (BTH) region faces under China’s goal of developing it into a world-class megalopolis, and the effects of the main water conservation measures in the region towards the goal.Data accessThe data generated and analysed during the related study are publicly available as part of this data record. The 15 Excel files are listed below, along with the names of the figures and supplementary tables from the manuscript that each file supports in square brackets.1-Economic growth &Water; use: This table provides the data of GDP and water use in the BTH region and existing world-class megalopolises (2017). The data sources include United States Geological Survey, The Great Lakes Regional Water Use Database, Statistics of Tokyo, Eurostat, and National Bureau of Statistics of China. [Figure 1]2-The BTH economic and water resource conditions: This table provides the city-level data of the economic and water resource conditions in the BTH region (2017). The data sources include China Statistical Yearbook, Hebei Economic Yearbook, and Water Resources Bulletin of Beijing, Tianjin, and Hebei. [Figure 2 and Supplementary Table 4]3-Water gaps: This table provides the data of water gaps for the BTH region to achieve the two benchmarking goals. The data in the column of ‘Minimum water requirement’ are from model simulation and the data in the column of ‘Average water resources’ are calculated based on official data from China Statistical Yearbook. Water gaps are obtained by subtracting the latter from the former. [Figure 3]4-GDP comparison: This table provides the GDP data of the BTH region and the existing world-class megalopolises. BTH region’s maximum GDP data are from model simulation and the rest of the GDP data are officially released data. The data sources include Bureau of Economic Analysis, Eurostat, Tokyo Statistical Yearbook, and China Statistical Yearbook. [Figure 4]5-Measure effects: This table provides the data of the effects of the applications of water conservation measures. The data in the column of ‘Minimum water requirement’ are from model simulation and the data in the column of ‘The BTH annual average water resources’ are calculated based on official data from China Statistical Yearbook. ‘Water saved by the measures’ are obtained by subtracting the ‘minimum water requirement’ of each measure from the ‘minimum water requirement’ of ‘No conservation measure applied’. [Figure 5]6-Water gaps_four-city-excluded: This table provides the data of the water gaps for the four-city-excluded BTH region to achieve the two benchmarking goals. The data are from model simulation, in which four cities (Handan, Xingtai, Hengshui and Cangzhou) are excluded from the BTH region. [Figure 6]7- Economic size : This table provides the GDP data of the BTH region and the six world-class megalopolises (2017). The data sources include Bureau of Economic Analysis, Eurostat, Statistics of Tokyo, National Bureau of Statistics of China. The exchange rate between USD and CNY is based on the averaged central parity rate of year 2017 released by the People's Bank of China. [Supplementary Table 1]8- Industrial structure : This table provides the data of the industrial structure of the BTH cities (2017). The data are provided by Hebei Provincial Bureau of Statistics and National Bureau of Statistics of China. [Supplementary Table 2]9- Trade data : This table provides the data of the total trade of the BTH cities with their trade partners. The data are calculated based on inter-city input-output table of the BTH region (2012). Total trade value is the summation of the bilateral trade amount between the BTH cities and their trade partners. The exchange rate between USD and CNY is based on the averaged central parity rate of year 2012 released by the People's Bank of China. [Supplementary Table 3]10- Indicators for benchmarks: This table provides the data of representing indicators as criteria for the BTH region's goal of being a world-class megalopolis in model settings. The data are obtained from National Bureau of Statistics of China, Shanghai Bureau of Statistics, Zhejiang provincial Bureau of Statistics, Jiangsu provincial Bureau of Statistics, Bureau of Economic Analysis, and Great Lakes Maritime Research Institute. [Supplementary Table 5]11- Objective of water use efficiency: This table provides the data of water control objective for improving water use efficiency in the BTH region. The Data Sources include: 1) The People’s Government of Beijing Municipality. Beijing Water Development Plan for 'the 13th Five-Year Plan' Period, (2016-7-8). 2) Tianjin Municipal People’s Government. Tianjin Action Plan for Dual Control of Total Water Consumption and Intensity for ‘the 13th Five-Year Plan' Period, (2017-3-30). 3) The People’s Government of Hebei Province. Hebei Implementation Plan for Dual Control of Total Water Consumption and Intensity 2016-2020, (2017-3-7). [Supplementary Table 6]12-SNWTP water use: This table provides the data of the SNWTP water use in the water intake cities of the BTH region (2018). The data are provided by Water Transfer Management Office in Department of Water Resources of Hebei Province. [Supplementary Table 7]13- Macroeconomic parameter comparison_provincial level: This table provides the key macroeconomic parameters at provincial level. The data sources include Beijing Municipal Bureau of Statistics, Tianjin Municipal Bureau of Statistics and Hebei Provincial Bureau of Statistics. [Supplementary Table 8]14- Macroeconomic parameter comparison_city level: This table provides the key macroeconomic parameters at city level. The data are provided by National Bureau of Statistics of China and Hebei Provincial Bureau of Statistics. [Supplementary Table 9]15- Water parameter comparison_city level: This table provides the key water use related parameters at city level. The data are provided by Beijing Water Authority, Tianjin Water Authority, and Department of Water Resources of Hebei Province. [Supplementary Table 10]

This statistic provides a projection of the gross domestic product (GDP) of major megacities worldwide in 2030. As of this time, it is projected that the GDP of Tokyo, Japan, will reach 40 billion U.S. dollars.

Le Produit Intérieur Brut par habitant au Japon a été enregistré à 37144,91 dollars américains en 2024. Le PIB par habitant au Japon équivaut à 294 pour cent de la moyenne mondiale. Cette dataset fournit - Japon PIB par habitant - valeurs actuelles, données historiques, prévisions, graphique, statistiques, calendrier économique et actualités.