Name: World Time Use, Work Hours And GDP
Creator: Kaggle
License: https://opendatacommons.org/licenses/by/1-0/index.html

About this Dataset

World Time Use, Work Hours And GDP

Context

Time use can vary greatly by country and between genders, be it by it's location, cultural differences, or economic situation. The data provided is by no means exhaustive but contains some interesting information on leisure time by gender, as well as historic data (1950-2017) on Avg. work hours and GDP in different countries and continents.

Content

Datasets from two sources are provided:

OECD Time use country statistics: Based on a collection of different questionnaires for different countries, it provides a distribution for time spent on different activities for both men and women in different countries.
Penn World Table (PWT) with information on RGDPO (in mil. 2017US$), work hours and population (in millions) actively working. Covering 183 countries between 1950 and 2019.

*RGDPO: Output-side real GDP at chained PPPs, to compare relative productive capacity across countries and over time.
Example: Productive capacity of China today compared to the US at some point in the past.

If you'd like, you can see an exploration of the data on my notebook: Data exploration

Acknowledgements

These databases provide additional indicators and may be of interest:

Inspiration

It is an interesting, easy to handle dataset which provides a great opportunity for interesting visuals and identifying relationships or trends between indicators.

Some questions to answer:

How to annual working hours relate to GDP per capita.
Is there a specific trend in working hours vs GDP per capita % change? Is it different for any specific region?
Is there any relationship between leisure time use and location, GDP or religion?
Is there a time use discrepancy by gender?

Tables

Avg Hours Worked 1950–2017

@kaggle.felipechapa_time_use_employment_and_gdp_per_country.avg_hours_worked_1950_2017

66.86 kB
3,492 rows
4 columns

CREATE TABLE avg_hours_worked_1950_2017 (
  "year" BIGINT,
  "regioncode" VARCHAR,
  "personsengaged" DOUBLE,
  "avghoursworked" DOUBLE
);

Time Use Oecd

@kaggle.felipechapa_time_use_employment_and_gdp_per_country.time_use_oecd

9.15 kB
329 rows
7 columns

CREATE TABLE time_use_oecd (
  "country_code" VARCHAR,
  "country" VARCHAR,
  "desc" VARCHAR,
  "description" VARCHAR,
  "sex" VARCHAR,
  "age" VARCHAR,
  "minutes_per_day" DOUBLE
);

Yearly Rgdpo 1950–2017

@kaggle.felipechapa_time_use_employment_and_gdp_per_country.yearly_rgdpo_1950_2017

190.5 kB
10,399 rows
4 columns

CREATE TABLE yearly_rgdpo_1950_2017 (
  "yearcode" BIGINT,
  "regioncode" VARCHAR,
  "pop" DOUBLE,
  "rgdpo" DOUBLE
);