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The one dataset to rule em all
Combined dataset is available, by clicking the title above or the image to your right!
Exploring Trends, Outliers, and the Key Drivers Behind Birth Rate Changes Across the World
Understanding global birth rates offers critical insights into the changing dynamics of populations worldwide. While the overall trend points toward declining fertility, certain nations stand out as exceptions, showcasing notable rebounds in birth rates. These outliers raise important questions about the factors driving such recoveries and whether they signal a potential shift in the global demographic landscape.
This analysis dives deep into both trends and anomalies, incorporating statistical and machine learning techniques such as Support Vector Machines (SVM), LightGBM, and Random Forests to evaluate the relative importance of variables. By analyzing demographic factors like migration, mortality, and socioeconomic conditions, we aim to uncover the key drivers most closely associated with birth rates.
From identifying unique springbacks in nations like Uzbekistan and Kazakhstan to uncovering the broader demographic forces shaping population numbers, this page integrates data visualization, feature evaluation, and advanced predictive modeling to provide a comprehensive understanding of the world's evolving population dynamics.
Trend depiction
Birth rates are commonly commented to be decreasing, but how does that decrease look like?
Consider whether following plot accurately depicts the vicissitudes in birth rates of countries like the US?
There will be several options included in plots presented including for the one beside here, where you can hover over the colour map and the timeline. Click the play arrow for a fluid animation of how birth rates have changed over time across the globe.
A race to the bottom
Here is a 'reverse' bar race for the lowest 11 countries in birth rate! Annotations within bars correspond to Birth rate|Deaths per 1000 Net migration that year
Contrary to popular belief, Japan having a low birth rate is not something that was consistently shown in history. In fact, it doesn't even appear to reach the bottom 10 in birth rates in the world as of 2022!
The reason for its relevance of course, is due to Japan's more conservative stance when it comes to immigration, which doesn't allow the country to mask its lack of social cohesion and impact from women's empowerment campaigns and employment like the European countries such as Latvia or Germany, which have had several occasions whereby it was the lowest in birth rates.
Especially in countries like Germany, where sometimes half a million net migrants can come on in, the erasure of the local population is not going to be determinable from cursory statistics that are available, and certainly are not
free from criticism of being belligerently nationalistic.
Potential for hope?
While the global trend in birth rates has largely been one of decline, this is not a universal narrative. A closer look reveals an intriguing counterpoint: in some countries, birth rates have shown signs of recovery. These rebounds, while modest, suggest the possibility of reversing what seems like an inevitable downward trajectory.
Understanding these shifts requires examining the interplay of cultural, economic, and policy-driven factors. In many cases, governments have implemented family-friendly measures such as extended parental leave, subsidized childcare, and financial incentives for larger families. Social dynamics, including changing attitudes towards parenthood and gender roles, also play a significant role.
The graph below highlights these upward trends in select regions, shedding light on countries that challenge the broader global trend. These outliers raise questions about what might drive a more sustained reversal in birth rates—and whether such patterns could become more widespread in the future.
Upticks of at least 0.3 to 1.0 increase over the minimum birth rate for countries that demonstrated an increase in birth rate are available to be filtered accordingly. Hover over the points for more information for each point in time and country such as suicide rate, deaths per 1000 etc.
The one dataset to rule em all
Combined dataset is available, by clicking the title above or the image to your right!
Trend depiction
Focusing solely on birth rates offers valuable insights into global demographic trends, but it only tells part of the story. Birth rates alone are akin to viewing the world’s demographics with just one eye—offering depth but lacking the full perspective. To truly grasp the scope of population dynamics, we must complement this view with data on overall population numbers.Some info is not available in world bank data, such as that of West Sahara etc.
wrt Birth rates and GDP per capita
Isolating the female labour participation variable with respect to birth rates does not appear to show any significant correlation, at least not once the labour participation rate of women exceeds 60%. It is interesting, however sparse the supporting section of the dataset is, that the points whereby birth rates fall significantly are mostly for points whereby the labour participation of women was about above 45%. More variables would definitely come into play to explain diffference in birth rates post that level of labour participation. It is also possible that the spread of female labour force participation is not sufficient to capture the full range of impact, as most countries have reached or exceeded a 50-55% participation rate. Lower values, where women's labor participation is less common, represent a minority of countries, which makes it difficult to visualize the true impact of labor force participation on birth rates.
Historically, the shift of women entering the workforce en masse occurred gradually across different countries. The most significant increase in female labor force participation took place during and after major historical events such as the World Wars and the post-war economic boom:
United States: The entry of women into the workforce increased significantly during World War II, as many women took on roles previously held by men who had gone to war. The trend continued after the war, especially during the 1960s and 1970s, with the rise of the feminist movement and expanded educational opportunities for women. By the 1970s, the female labor force participation rate had notably increased.
United Kingdom: Women's participation in the workforce grew during World War I and II, with women filling roles in manufacturing, healthcare, and other sectors. Post-World War II, the increase continued, with significant rises during the 1960s and 1970s, coinciding with the women's liberation movement and changes in societal expectations.
Germany: In Germany, women entered the workforce en masse during and after World War II, but the trend remained slower in comparison to other industrialized nations due to more traditional gender roles. The post-war period, particularly during the 1960s and 1970s, saw gradual increases in labor force participation.
Japan: Women's workforce participation began to rise significantly during the 1950s and 1960s, spurred by industrialization and economic growth. However, cultural factors, such as the expectation of women to prioritize domestic roles, led to a slower increase compared to Western nations. The 1970s and 1980s saw continued growth as women sought educational and professional opportunities.
France: During and after World War II, there was an increase in female labor force participation, especially in sectors such as healthcare and manufacturing. The 1960s and 1970s also saw growth, partly due to feminist movements and social changes.
Scandinavia: Countries like Sweden, Norway, and Denmark saw early and steady increases in female labor force participation, especially during the 1960s and 1970s, coinciding with strong social welfare policies, progressive gender equality initiatives, and high levels of female educational attainment.
Canada: Similar to the United States, Canada's female labor force participation increased significantly during World War II. Post-war, the trend continued, particularly in the 1960s and 1970s, when women's roles in the workforce expanded significantly.
Australia: Like other Western nations, Australian women entered the workforce in larger numbers during and after World War II. The 1960s and 1970s saw a marked increase, driven by the growth of the service sector and social changes regarding women's rights and education.
In many other countries, the shift toward higher female labor force participation was influenced by economic modernization, urbanization, and educational reforms, with notable changes beginning in the 1960s and accelerating in the 1980s and 1990s. However, the timing of these shifts varied significantly across regions due to different cultural, economic, and political factors.
Which factors explain birth rates the best?
A conversation about birth rates goes down the same list: overpopulation, finances, mortality rates etc. In world bank data, we can look at a number of factors, including suicide aside from those listed previously. Please note that GDP here refers to GDP per capita, as we see no value at all in the statistical value of the measurement, total GDP.
Note that some models such as XGBoost, explicitly cannot handle any missing entries inside the data. As we did not see it appropriate to add in random estimates, XGBoost was not used in this analysis, since filtering out the 14000 entries or so in the original dataset to ones that had no missing entries in any of these fields led to boiling it down to just 200 entries, and that number of entries that remain unaffected would further dwindle if one were to explore even more
explanatory variables.
of most important features
Here is the summed up scaled relative importance of the features in the dataset gathered from world bank. Note that there are plenty of other factors that could be considered that very likely have not been included in our analysis.
Understanding what drives birth rates is a complex challenge, especially when one major factor—time—is already doing much of the heavy lifting. Over the decades, birth rates have shown a clear downward trend across much of the world. But what else contributes to this change? To answer this, a range of machine learning models—LightGBM, Neural Networks, Random Forests, and Support Vector Machines (SVM)—were used to estimate birth rates based on various predictors. The results were combined to give a more holistic picture of which factors matter most.
One key decision was to include Year as a predictor. Why? Because Year captures the general decline in birth rates, providing a baseline for comparison. Any factor ranking higher in importance than Year is likely contributing significantly to birth rate changes, beyond the simple passage of time. Conversely, factors falling below Year may have limited additional explanatory power or may reflect trends already captured by the temporal pattern.
Think of Year as the "dark matter" of this dataset. Just as dark matter represents the unseen but influential mass shaping the universe, Year captures the unseen factors shaping birth rates. It stands in for everything the dataset hasn’t measured—societal changes, technological progress, shifts in cultural norms, and other forces that evolve over time.
In a perfect analysis, all these hidden influences would be explicitly accounted for, with Year becoming far less important. But in this dataset, Year quantifies what we can’t see, providing a broad context against which other factors can be measured. The goal, then, is to identify which variables surpass Year in importance—shedding light on the drivers of change that don’t hide in the shadows.
The results? Factors like Deaths and GDP emerged as the most influential, followed by to a lesser extent, but still arguably significant, the percentage of women's participation in the workforce, followed by that of men, total population and net migration since 1960. Following these factors Year came in as the next most significant factor somewhere in the middle of the pack. This approach helps separate the truly significant drivers of birth rate changes from the less so and thus, it becomes easier to see what’s shaping birth rates—and what isn’t quite so much. Acknowledgement is required for the sporadic record of many of these factors, however, and the admittence that we can never be 100% certain if the currently deemed 'not so significant' factors are indeed not relevant to the prediction of birth rate. With the introduction of more variables for instance, it is possible that some previously determined insignificant factors relative to Year, will come forward as substantially significant compared to 'the times'.
Crude Death rate is the most important
Global Trends in Birth Rates — Birth rates have generally declined worldwide, signaling an ongoing demographic transition. However, some countries, such as
Uzbekistan and Kazakhstan, stand out by showing notable springbacks, with birth rates increasing by about 1 or more over their historical minima.
In contrast, most of the world that mostly continues to decline, while a small few have only managed to slow the decline without reversing it. Mongolia also experienced a smaller rebound,
suggesting regional or policy-driven dynamics worth exploring.
Key Influencing Factors — Machine learning models, including LightGBM, XGBoost, neural networks (NNet), and
random forests, were used to assess the relative importance of variables affecting birth rates. Despite methodological differences, all models identified
Deaths per 1000 population followed by GDP per capita, followed by the variable, Year. Notice how the reasoning behind Year boils down to "birth rates are lower due to the nature of times these days". Analytically, the factor Year
could be interpreted as a conglomerate of other unseen factors that this analysis has not managed to consider.
Population Numbers for Perspective — Shifting focus to population numbers offers a broader view of global demographics. For example, India surpassed China in 2022/23 as the most populous country, marking a historic demographic milestone. While some countries demonstrate resilience or recovery in birth rates, the global trend suggests stabilization of declines rather than reversal, emphasizing the importance of targeted policies and cultural or economic factors to address these shifts.
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