An Analysis of Unemployment

Directions: Use the layer list in the bottom right corner of the map extent to select a layer to display. 

Unemployment Rate: Understanding the areas in which there is recession level unemployment can reveal where there are economic downturns in local labor markets, as well as the amount of job opportunities for workers in the area.

Race and Ethnicity Predominance: Race and ethnicity are important factors for understanding employment at the local level because they are closely linked to socioeconomic status and historical patterns of discrimination. These disparities have significant consequences for individuals, families, and the broader community.

Median Home Value: Median home value is important to investigate because it can provide insight into the overall economic well-being of a community. There is often a strong correlation between home values and employment outcomes. Median home values can also provide insight into the availability of affordable housing in a community.

Asthma Prevalence: Asthma prevalence is an important data point because it can provide insight into the physical and mental health and well-being of a community. Like median home value, there is often a strong correlation between asthma prevalence and employment.

Asthma Prevalence Hot Spots: Asthma prevalence hot spots are important to look at because asthma is often linked to exposure to environmental pollutants, such as air pollution and hazardous chemicals, which can be more prevalent in certain areas of the city. Exposure to these pollutants can lead to chronic health conditions such as asthma, which can in turn impact a person's ability to work and their overall employment outcomes.

Diabetes Medication Users (Type 2): The prevalence of Type 2 diabetes medication users in a given area is important to look at, because it can be caused by a range of factors, including genetics, lifestyle factors, and access to healthcare. A lack of employment opportunities may result in unhealthy lifestyle choices as well as less access to healthcare options.

Outliers in the percentage of the population that is white: Finding outliers can reveal the diversity of the local workforce and potential disparities in employment outcomes for different racial and ethnic groups. Outliers in the percentage of the population that is white can indicate the presence of a large minority population or a lack of diversity in the local workforce.

Recession level unemployment (greater than 10%): Areas with recession level unemployment are great causes for concern. This often indicates a severe economic downturn for local labor markets and may indicate the need for targeted job training and retraining programs or other policies aimed at promoting job creation and economic growth in those areas.

1. Describe the relationship between the geography of unemployment and the related indicators. For example, what do you see when you compare each layer?

To an outsider without much local knowledge of Houston, Texas, when it comes to the geography of unemployment, there are clear differences in unemployment rates from tract to tract in the Houston area. Downtown and West Houston have the lowest levels of unemployment, with many tracts in the 0-2.3% range, and some others in the 2.3-6.8% range. On the contrary, Northeast and South Houston both have many tracts where unemployment levels are 6.8-11.3%, as well as above 11.3%, getting up to 16% in some tracts. In terms of comparing layers within the unemployment rate layer group, when looking by state, and even county, there is not nearly as much precision as by zip code, tract, or block group. This shows that there can be some larger areas that may seem like unemployment is low, but in reality there are zip codes within counties, tracts within zip codes, and block groups within tracts, that reveals much more variance in unemployment levels. The smaller the geographic unit, the more fine tuned the results will be. 

In the previously mentioned Northeastern and Southern parts of Houston where unemployment is the highest, there is a direct correlation to Black and African American predominance. Further, virtually all areas experiencing recession level unemployment above 10%, are areas of Black and African American predominance as well. Accordingly, in the Downtown and West Houston area where there is the least observable unemployment by tract, there is a direct correlation to White predominance and the highest median home values. Aside from that, all other tracts within the City of Houston have a much lower median home value. In the northern and southeastern parts of the city where there is Hispanic or Latino predominance, unemployment is generally between 0-6.8%. However, when approaching the outskirts of Houston where there is also Hispanic or Latino predominance, unemployment hits higher levels, in the 6.8-11.3% range.

In regards to health complications, it is important to note that there is a striking correlation between high asthma prevalence and all nonwhite tracts. There is above 10% asthma prevalence in almost all Hispanic, Latino, Black, or African American areas. Meanwhile, there is below 8.5% asthma prevalence in virtually all of the predominantly white areas (Downtown and West Houston). All asthma prevalence hot spots above 90% confidence are found in tracts with low median home value, high unemployment rates, and a high concentration of Black or Latino. Further, the highest potential for Type 2 diabetes medication users is in predominantly Black and African American tracts. There is nothing more than an average potential for type 2 diabetes medication users in any other non-Black or non-African American tract, regardless of race.  

2. How is the influence of or exposure to unemployment different in different places? Why? Use the course readings, discussions, and your map to answer the question.

It is clear from the map and my analysis that exposure to unemployment in the Houston area varies greatly from tract to tract. As Sunley, Martin, and Nativel explain in Chapter 2 of Putting Workfare in Place: Local Labour Markets and The New Deal, which investigates the geographies of worklessness, “There is no such thing as the ‘national labor market’, but rather a complex geographical mosaic of overlapping local and sub-national labor markets defined by a myriad of spaces of labor recruitment by firms and the job search, travel-to-work and migration fields on the part of workers” (Sunley, Martin, and Nativel 2008, 43). Geography separates and segments the labor market, as local labor markets have their own dynamics which establish the kinds of opportunities and challenges that will be faced in a particular location. Visually, this is widely apparent on the interactive map, where unemployment rate, median home value, asthma prevalence, and diabetes medication use, all find themselves fitting almost perfectly within the different tracts characterized by race and ethnicity predominances. All of these imperfect, segmented local labor markets, are influenced by the “historically evolved and locally embedded structures of employment, skills, and workplace relations”, which influence the job opportunities and wage levels of the area (Sunley, Martin, and Nativel 2008, 44). Thus, it would make little sense to compare the conditions and outcomes of local, urban, and regional labor markets, because they operate in “place-specific” ways and will react and adjust differently to economic shocks and changes. This is why geography matters: People live and work in their own specific and distinct places, and the conditions of their experience will differ greatly from place to place.

3. How do the results of your analysis relate to what you have learned so far about the costs of unemployment? For example: public health and unemployment, social group identity-based advantage and disadvantage, and housing.

As we have learned in class, the costs of unemployment go far beyond monetary effects. Aside from being a financial burden, there are significant social and psychological costs associated with unemployment as well. In relation to public health, there is a strong association with unemployment and increased rates of depression, anxiety, and other mental health disorders, as well as substance abuse. The economic strain placed on these individuals may also lead to worsening physical health, that comes with limited access to healthcare and healthy food options. From a social group identity-based perspective, it is clear that individuals of marginalized groups (e.g. POC, disabled), are more likely to experience long-term unemployment. This contributes to the cycle of poverty and social exclusion that perpetuates disparities of income and wealth. Housing issues are another cost of unemployment that is important to mention. Unemployment can lead to housing instability, especially when individuals are unable to make rent or mortgage payments. In some cases this can result in homelessness, which further heightens the physical and mental health effects of unemployment. It can also make securing housing difficult in the first place, as landlords may be less inclined to rent to individuals lacking a stable income. 

From my analysis it is clear that Houston, Texas is representative of all of these previously mentioned phenomena. It is clear that both type 2 diabetes and asthma rates are higher in areas with higher unemployment. On top of that, these areas are most often predominantly Black, African American, Hispanic, or Latino. Location is also important when analyzing unemployment by geography. Houston’s oil refineries and chemical plants surround the Houston Ship Channel in East Houston, making it the second largest petrochemical complex in the world.  The surrounding neighborhoods are all predominantly minorities, who are exposed to higher levels of dangerous air pollutants, and worsening life expectancies the closer you get to the Ship Channel (Bethel 2006). Zip codes become the determinant of health. When looking at median home values by tract, it is apparent that homes in areas with more unemployed are worth much less. This is an easily visible, vicious cycle of unemployment that is very difficult for individuals to break free from. Financial strain from being unemployed can lead to housing insecurity, which has negative effects on physical and mental health. This poor health can make it more difficult for individuals to find and keep employment, further perpetuating the cycle of unemployment and worsening financial strain. From a psychological perspective, social stigma can lead to psychological barriers for those looking to reenter the workforce. Low self esteem, anxiety, and loss of faith in getting a job can make it very difficult for people to get themselves back on track. On a larger scale, high unemployment neighborhoods are plagued with high crime rates and low economic growth, which can perpetuate the unemployment cycle for entire communities. 

References

Bethel, Heidi L. 2006. “A Closer Look at Air Pollution in Houston: Identifying Priority Health Risks.” Environmental Protection Agency. https://www3.epa.gov/ttnchie1/conference/ei16/session6/bethel.pdf.

Sunley, Peter, Ron Martin, and Corinne Nativel. 2008. “The Geographies of Worklessness.” In Putting Workfare in Place: Local Labour Markets and the New Deal, 33. Hoboken, NJ: Wiley-Blackwell. https://doi.org/10.1002/9780470795873.ch2.