What programs and categories of the United States House of Representatives is spending the most and what is being spent on the most frequently?
The United States Government spends trillions of dollars a year on mass programs and sectors to help keep our country in the place it needs to be. So far in 2023 the United States Government has spent 2.5 Trillion dollars in just two and a half months. In 2022 the United States Government spent 6.3 Trillion dollars throughout the whole year. These numbers are absolutely insane and carry a heavy weight on how our society is shaped. The question is, where does this money go? Who is spending this money? Is the money being put into the right places even? In order to investigate these questions I conducted a exploratory data analysis on the 2021 Quarter 3 House disbursement data of the United States House of Representatives. I had many questions to ask about where all the money the government spent was going, and more came forward as the analysis went on.
When taking a look at the dataset I used, a few things caught my eye right off the bat. The dataset contained the columns PROGRAM, CATEGORY and AMOUNT. These pieces of data automatically brought my mind to question how the spending amount and frequency differentiated by programs and category.
I decided to look at category first wondering what category had the highest occurrences of spending. As you can see in the graph below, travel is what had the highest frequency of spending followed by rent communication spending's, and supplies and materials. This chart is really interesting to look at considering that travel of all things has the most amount of expenditures and transportation of things and benefits had nearly, if not zero occurrences.
Even though the amount of expenditures for each category differentiated drastically. These numbers were not enough to tell the whole story of where the money was being spent. The numbers that really mattered were the amounts.
When calculating the actual amounts spent by each category the data looks a lot different. Travel which had a large amount of expenditures had a very not small sum of money spent compared to other categories. It turns out “equipment”, “personnel compensation” and “other services” is where the most amounts of categorical money was spent. The only of those three that had a large amount of expenditures was personnel compensation. This part of my analysis gave me some very interesting insights to look into for the future but I also needed to look at how these numbers differentiated by program.
I was unable to graph the data for the programs due to there being 123 programs compared to only 11 categories. Everything looked messy visualized, but in the numbers alone there was a huge jump from the top spenders to the last 120 programs. The highest spending program of all was…drum roll… “Official Expenses of Members”. The amount spent was 571 million dollars. A crazy amount of money. The crazier thing is the next couple highest spending programs are not nearly that amount. In second place is “Government Contributions” with a total spending of 304 million, and in third place “General Expenditures” with 163 million. The third highest program is nearly one fourth the amount spent as the highest program. The list only gets smaller and smaller as the programs go on. In a future analysis I will likely look at what percentage of spending each program accounted for to better understand the numbers.
In general, looking at the raw data makes it difficult to decipher more specific relevant information other than the basic analysis I conducted. I now know that for quarter 3 of 2021, just one quarter, that the category of travel has the highest amount of expenditures and that the category equipment actually spent the most money. I also know that the program that spent the most was official expenses of members and it spent 571 million dollars. What can I conclude from this? Well, the government likes to spend a lot of money and, without more context into if categories and programs are correlated or subcategories of each other, the data is kind of hard to interpret. What other subcategories are a part of the actual categories and what, in a very specific sense does it go to? In order to answer these questions, there needs to be more data, and a lot more time to look into what these numbers mean. In the meantime, know that the government is spending billions of dollars a quarter on these programs and categories and all we can hope is that it is being spent wisely.
