10:30 AM

Leviathan Always Grows

Anyone who pays even the least bit of attention knows that the U.S. federal government continues to grow, and grow, and grow. This fact cannot be disputed; using the government's own financial data, one can quickly see the magnitude of growth every year. Some may be confused by the unique language spoken near the Potomac, where budget "cuts" are typically not cuts at all, but merely reductions in the rate of growth versus the prior year. In almost all cases, not only does the total budget grow significantly each year, nearly all components of the budget grow as well. Periodically, certain departments or agencies may see a year over year reduction in their budget, although this is the exception to the rule of near continuous growth.

To illustrate this growth and how disproportionate it is to the world you and I live in, I have constructed a budget tracker dashboard in Tableau Public that allows anyone to select individual departments to see just how rapid their growth has been in the 1962-2016 budget period. This is supported by figures showing the growth rate relative to the government's own CPI inflation calculator (admittedly a flawed measure, but a commonly referenced one), as well as budget shares over time, and trend charts displaying annual patterns. It's a fun tool to explore budget growth, and see where things have really gotten out of control.

Read More

20:45 PM

Who Finances the Candidates? Part 1

Revisiting a recurring theme, it's time to examine some more data from the Federal Election Commission (FEC), specifically revolving around the 2016 US presidential campaign cycle. Our goal is to shine a light on which political committees are donating to the campaigns of the various candidates, and to gain a better understanding of the dynamics of campaign finance. Using Gephi and Sigma.js as my platforms, I've built a highly interactive network to facilitate further exploration of the contribution patterns covering a period from January 2015 through February 2016. This type of network is commonly known as bipartite, wherein there are two main categories that connect to each other, but not to their own type. Here we will have committees and candidates connected, but not committee to committee or candidate to candidate.

In this piece, we'll view selected patterns within the network that I find of particular interest, leaving the rest for you the reader to explore further. This article's focus will be on the Democratic contenders, Hillary Clinton and Bernie Sanders.

Let's start with a snapshot of the entire network, with the candidates depicted in blue (Democrat) or red (Republican) shades:

full network

Read More

16:49 PM

Candidate Contribution Patterns

As the 2016 election season trudges inexorably toward a November climax, it might be instructive to learn more about all of the candidates, both those who have withdrawn as well as the remaining hopefuls. An interesting way to do this is to ignore all the debates, talking points, and public pronouncements, and instead focus on the campaign contribution patterns of each candidate. Using data from the Federal Election Commission (FEC) http://www.fec.gov/disclosurep/pnational.do, we can observe and analyze patterns within the contribution filings. This will enable deeper insight into who is funding the campaigns, at least at the visible, public level, if not the somewhat murkier world of political PACs and other organizational entities.

To provide insight into this data, we'll work with a candidate dashboard using Tableau Public. With this approach, not only can I begin to draw some conclusions about the candidates and their supporters, but others can also dive into the data and detect underlying patterns. In this article, I will first provide a link to this dashboard, allowing readers to investigate the data on their own, but we will then look at a variety of excerpts from the dashboard that should call out some of the important patterns in the data.

Read More

14:10 PM

The Unemployment Numbers Game

Recent trends have suggested that unemployment rates in the United States continue to drop to the 5% level, far below peak levels seen in the wake of the 2008-2009 recession. Partisan political supporters are likely to credit the Obama administration for this development, and are quick to criticize those who discount his role in driving these numbers. These figures are routinely quoted by the mainstream media with little investigation or explanation for why the numbers are trending favorably. Even as many other economic indicators suggest an economy stuck in neutral, or perhaps still mired in a long-term depression, low unemployment rates are heralded as indicative of a recovering economy. Yet if unemployment rates are so low, why does the economy seem so sluggish?

In this article, we will use historical data from the Bureau of Labor Statistics (BLS) to track patterns and tell the real story about employment and unemployment patterns in 2015. All datasets focus on adults 16 & over, and are not seasonally adjusted, although some of our charts will use moving averages to smooth the data. To tell this story, we'll focus on several data sets created by the BLS:

  • Labor force participation, expressed as a 0-100 number (a percentage)
  • Employment ratio, also expressed as a 0-100 number (a percentage)
  • Full-time workers, a raw number expressed in thousands (000's)
  • Unemployed workers, expressed in thousands (000's)
  • Labor force, expressed in thousands (000's)
  • Adults not in labor force, expressed in thousands (000's)

We'll navigate through each of these datasets, providing charts for each measure, and offering critical analysis of each trend. Note that all of these charts are interactive; use the small, lower chart to select a range of data to be displayed in the main chart. When the number of data points are sufficiently limited, you will be able to hover over any point to see the time period and corresponding data value.

Read More