EG 10118 Final Project: Time Usage and Macroeconomic Trends

By Daniel Blittschau and Russell Henggeler

1. Introduction

For our project, we set out to find out what implications the time usage of various countries have on their broader productivity and success as a nation. Throughout our research, we considered numerous independent variables and found that many of these variables correlated into strong relationships, while some others lacked a more meaningful relationship. Ultimately, there are many valuable insights that can be gained based on the data we looked at, but in order to make more solidified trends, we would need to expand the scope of our research into other areas.

2. Data Sources

We used several csv based datasets from a diversity of reputable sources to conduct our visualization and analysis. Some of these datasets came from academic papers, while others came from organizations that specialize in data collection.

Here is our complete list of data sources:

3. Data Visualization

Graph 1 (How Nations Spend Time):

All Paid Work Education Other unpaid work & volunteering

In this visualization, we compare how many minutes per day (on average) nations spend on activities related to work or productive activities. We were ultimately able to break the productive time spent down into three categories: paid work, education, and other unpaid work or volunteering. It is evident that there are some stark differences between the lowest and highest countries.

One question that comes to mind is whether some of the most successful countries and largest exports spend the most time in the productive categories. This is largely true as it can be observed that countries such as the United States, Japan, and China (the world's largest exporters) are towards the top.

However, a perhaps less expected observation is that there are also some less economically prosperous countries such as Mexico and Lithuania which are also toward the top in time spent. One possible explanation for this is the type of work that these countries are performing. Although they are spending a significant amount of time per day working, it is largely manual labor that is being done in contrast to the more technologically advanced work being done in the more economically successful countries.

Graph 2 (Population over time graph):

This graph provides a visual color representation of how the world’s countries have changed populations over time. One of the primary expectations that many have when viewing this time lapse is that the countries that we previously stated have the largest economic success and time spent working would have the largest population growth levels. This is largely proven true through this data set as countries such as the US, China, Brazil, and Russia have had some of the most visually stark changes over the years.

A secondary trend which possibly pops out to the viewer is that the populations of many African nations are similarly growing at a faster rate than much of the rest of the world. This could be associated with Africa increasingly coming out of its third world country status as its natural resources are turned to as time goes on.

Graph 3 (Average Annual Working Hours Per Worker versus Year):

This simple, yet extremely insightful line chart demonstrates how working hours have changed over time. Although many people may have expected for working hours to have increased over time as productivity and GDP along with many other factors used for measuring relative success, this is obviously not the case.

For nearly every country we collected data for, it can be seen that there was a stark decrease in working hours around the year 1920. This can be attributed to the technological advancements of companies around the world and the adoption of the assembly line. Additionally, with this increase in technology tasks such as plowing a field, which would have taken a significant amount of time in previous years, could be completed in a day with more advanced tractors and machinery.

One final, possibly most important aspect of this visualization is that the working hours have come to a relative standstill around the world since 1980. As more and more regulations are made around the world regarding the amount of time that can be worked, it is a logical trend that we see a leveling off of the curve.

Graph 4 (GDP versus time):

Various technological innovations over the years have allowed for nations to have a constant increase in GDP while also maintaining a decrease in the hours worked (see Average Annual Working Hours Per Worker versus Time).

The countries that are toward the top, however, are possibly less expected in this graph because of how the GDP is measured, which is in per capita. Although countries such as China, India, and Russia would be expected to have been towards the top of the graph along with the US and Germany, their wealth is largely concentrated in a few large corporations as the structures of their government allow for this. Other than this unexpected trend, this graph largely corresponds with the time that countries spend on work, education, and unpaid work.

Graph 5 (Productivity versus Average Hours Worked Per Year):

As observed previously, as technology continues to advance on a global scale over time, the average hours worked per year has also fallen. As a direct result of this trend, an inverse relationship where productivity has drastically increased as the amount of hours worked decreases can be observed.

As activities that previously would have been performed by humans are now largely automated or speed up with robotics or innovation, people are able to work much less while still maintaining the same amount of money made. Thus, despite differences between countries on how daily time is spent, there is still an overall trend globally in an increase in productivity measures as the average hours continues to decrease overall.

Graph 6 (Productivity versus Vacation Days and Holidays Off per Year):

This visual representation of productivity and vacation days presents a very different type of insight about how developed countries spend their time. The graph relates a scatter plot over four different years of the amount of vacation days and holidays off per year with the corresponding productivity measurements for the same year.

If the trend of developing countries having more time off continued with this dataset, we would see a strong positive correlation for each year, indicating that with higher vacation days you also get more vacation days and holidays off per year. However, we see a flat slope for each year. Thus, the number of vacation days and holidays off per year is more related to the individual country and its respective culture than its productivity.

4. Conclusion

After looking at various data sets relating to population, GDP, productivity, vacation days, work hours, and more, there are a few primary observations that can be discerned.

1. More hours worked by country does not necessarily mean that the country has greater economic success. Technology and cultural values evidently play a large role in determining the overall productivity of a nation.
2. Countries that are widely agreed upon to be the most successful do have the highest GDP per capita, productivity levels, and population growth overtime. Thus these types of measures do appear to be positive indicators for success in the global economy.
3. As a global trend, as time goes on, people are spending less time on work while still maintaining or increasing their economic success.

Ultimately, how any individual country spends its time in relation to the length of the work day, amount of vacation days, or time spent on education or unpaid work does not appear to directly correlate with that nation's success rate measured through economic indicators. There are numerous cultural, technological, and social considerations that are much more difficult to measure that most likely have a large influence on these economic indicators.

In the future, if we were to continue this research, we would look more closely at how technology has increased over time and what impacts it has had on various societies.