Poverty is primarily the result of a failure at the structural level. Nowhere is this more apparent than in the lack of livable wage jobs for all who are in need of such work.

The labor market simulator allows you to analyze the gap between the number of job seekers versus the number of livable wage jobs over the past 20 years, and who succeeds and fails in finding such jobs. To begin, select play.

Musical Chairs of Poverty

As argued throughout this website, poverty is primarily the result of a failure at the structural level. This process can be likened to a game of musical chairs in which there are many more players than there are chairs available. Individuals likely to lose out at this game will have characteristics that put them at a disadvantage in terms of competing in the labor market. These include having less education, and being nonwhite and female. However, these characteristics only help to explain who is more likely to lose out the game, not why the game produces losers in the first place.

Using data from the U.S. Census Bureau and the U. S. Bureau of Labor Statistics, we have constructed a labor market simulation that allows you to observe this dynamic with actual data. In each simulation there are 100 players or job seekers symbolized by 100 dots. The players (or dots) represent individuals between the ages of 25 and 59 who are in the labor market. The chairs (or circles) represent the actual number of jobs available in the labor market for those 100 players.

The Labor Market Simulator

There are three choices to be made before setting the game in motion. First, you can choose the year that you would like to focus on. These include 2020, 2015, 2010, 2005, or 2000. Within any given year we are looking at the labor market in the month of March.

After selecting a year, the next choice is to choose what type of job (or chair) you wish to analyze. The first option is a livable wage job, which is defined as twice the poverty line for a household of two (in 2020, this came out to approximately $16.50 an hour). For comparison purposes, you can also select any job at all, which includes all available jobs in the labor market. When you select your choice, you will see how many chairs there are for our 100 job seekers.

The third selection determines what characteristics will define our 100 job seekers. You may select one, two, or three demographic factors to analyze – education, race, and gender. The 100 individual players are color coded and represent the same percentages found in the national population. For example, if you choose to look at race for 2020, 40 of the players will be nonwhite and 60 will be white (in the overall labor market for 25 to 59 year olds in 2020, 40.2 percent are nonwhite and 59.8 percent are white). If you choose two characteristics to focus on, this results in four different categories of individuals, and the number of players in each category will represent the national population.

Putting the Simulator in Motion

Now that you have made your three choices, you can set the game in motion by clicking “Start.” You will notice that the players circle around the chairs in a somewhat random fashion. This represents the element of chance which is present in any endeavor. Securing and holding on to a job is no different. There is always a role for luck and chance within such a dynamic. When you click the stop button, the players are at various distances from the chairs. Some are closer and some are farther away. This again represents the randomness present in the labor market.

You will then notice that our players move at differing speeds toward the circle of chairs. Their relative speeds have been calculated by using Census data to determine the different probabilities of individuals in each group securing a job. While the position of players when the music stops is important, much more important are their relative speeds. These speeds reflect the advantages and disadvantages that each of the individual players possess.

If you play the game again with the exact same choices, you will notice that the results may be slightly different. This is the result of the element of chance exerting itself in any given game. Nevertheless, the results will be fairly similar across games with the same selections due to the importance of education, race, and gender. What is essential to keep in mind is that no matter who in particular loses, the number of losers remains the same. This represents a failure at the structural level – the economy simply does not produce enough livable wage jobs for all who need them. After looking at your results, you can change the three selection choices to see how this alters the outcomes in further games.

Understanding the Dynamic

What the labor market simulator demonstrates is that poverty can be likened to a large scale version of musical chairs. We can focus on who loses out at the game, or we can focus on why the game produces losers in the first place. Lacking a job that pays a livable wage is perhaps the most important reason for explaining poverty. We can see in the simulation that no matter the year that is chosen, there is a serious shortage of such jobs for all who are competing in the labor market. The result is that someone is bound to lose and will frequently experience poverty. Those who do so tend to have characteristics that place them at a disadvantage in landing such jobs. But we should not confuse who loses out at the game, with why the game produces losers in the first place. Even if all players were suddenly to graduate from college, there would still be a similar number of losers. The only difference would be that now the losers are better educated.

What is unique about our labor market simulation is that like the poverty risk calculator, what you are seeing is based upon actual data. The number of chairs, the characteristics of the players along with their relative speeds, are all based upon extensive analyses that we have conducted using data from the Census Bureau and the Bureau of Labor Statistics.

However, because we are limiting the number of players to 100, there is much more variation across games in the success rates for different groups than there would be if we had 1,000 players instead. This can be likened to the flipping of a coin. Although the probability of a heads or tails is 50 percent, if we flipped a coin 10 times we may very well wind up with 6 or 7 heads or tails. However, if we were to flip a coin 1,000 times, the number of heads and tails would be much closer to 50 percent. Underlying each player in our simulation is a specific probability of success in finding a job based upon data from the Census Bureau. However, due to randomness and the relatively small numbers of players, their success rates will vary somewhat across games. You can see this by playing the game with the same characteristics several times.

The Next Steps

Finally, you can explore the next steps by clicking on the solutions button. Here you will find several different strategies for increasing the number of livable wage jobs within the economy.