“Why Does It Feel People Are Getting Married So Young and Does Income Affect These Marriages?”

I feel that people are getting married younger and younger these days and I keep seeing people on social media getting married and ask myself “How are they financially stable enough to start a family at such a young age”?? Whether or not they are people I do or do not know the fact that I am seeing marriages, proposals, and fiancés at my age makes me feel old. I wanted to know if there is a correlation between the age at which people are getting married and how income is a factor in that marriage. This means that I am also curious if income ends up being an important factor in marriage down the line and if this income becomes an issue does that mean that inevitably the marriage turns into divorce.?

I started my data collection by using the Census API to gather all sorts of data. This data was all from 2022 and it was on the median age at which people were getting married (both for males and females) on a state level, median household income, and the total amount of divorces in each state for both males and females. I believed that I would find some sort of correlation between one of these four variables with the household income variable. My logic here was that if there were money problems within the household, that the number of divorces would increase and that couples that were more financially independent would be more capable of starting a family.

What I found was that within each of these variables, many of them did not have a large correlation. They all had R-values like 0.201(Men's First Marriage and Median Household Income), 0.236(Womens First Marriage and Median Household), 0.078 (Men's Divorce and Median Household Income), and 0.082 (Women’s Divorce and Median Household Income). This felt somewhat unsatisfactory to me, and I felt there should have been more to this. Here’s what one of the correlation plots looked like.

As we can see even though this is one of the higher correlations that I found and that there may have been somewhat of a weak correlation, it still was not nearly as significant as I believed that it would be. In an attempt to try and either strengthen or weaken these correlations to see if they are really significant, I added all the same data but from the years 2010 all the way to 2019. I thought that this may help clear up if there was a real relationship between any of these variables. Once the data was added I realized some significant changes. While the R-values of Men’s Divorce and Womens Divorce fell off and became very neutral, the two values for Men's First Marriage and Womens First Marriage went up significantly. Men was 0.377 and Women was 0.376. While still relatively weak of a correlation, it is still somewhat significant.

Then if look at this graph you can see that there are a ton of points at the bottom that may be messing up the R-value. I looked at this data and realized that all those points are data that came from Puerto Rico. Knowing this I removed them from the data and the results were very interesting. The R-value went all the way up to 0.536 and had a p-value of 4.08e-43 which is also significant, so we can see that there is somewhat of a correlation. The graph also looks much better, and you can see the trend in front of your eyes. Basically, what all of this means is that the older that men are when they get married, the more money they will be making.

I felt that this was not enough for me. I wanted to see more and make more connections with this data so I decided to make an interactive scatterplot where you could look at all the Median Age of Women at their First Marriage as well as their Median household income in each state. I found a couple of interesting things within the graph. Here is my graph.

The grey dots that are clustered on the top left are all dots of Utah. I put it together eventually that this was because a lot of Mormons live in Utah and in their religion, many people tend to get married earlier. It also shows that many people in Utah have a pretty solid amount of money and are capable of sustaining a marriage. Another finding that I made was that the median age of first marriage tends to be much larger than that of men. This is not very surprising, but it was interesting to see it in data form.

In conclusion, this research journey, uncovered certain correlations between age at marriage and income. While initial findings yielded relatively weak correlations, the further exploration over a broader timeframe revealed significant shifts, particularly emphasizing the correlation between older age at marriage for men and higher income. The interactive scatterplot provided additional insights, which showcased regional variations and cultural influences. This study underscores the intricate interplay between societal norms, economic factors, and marital decisions. Moving forward, deeper examination of the impact of financial stability on marital outcomes remains crucial, offering valuable insights into evolving marriage trends and their societal implications.