The purpose of this report is to provide information on the effect of unemployment rates on consumer spending and relate it to the viability of retail operations. The establishment that operates a retail store already has an idea regarding the impact of unemployment rates on consumer spending, that is, when unemployment rates are high the consumer spending is affected negatively. This is an intuitive assumption since people who do not have jobs or are underemployed will have less money to spend for goods that are not necessities; thus to remain competitive and efficient, retail operations would try to contain their costs. One way of containing costs is the reduction of inventories. Inventories are goods that are in storage, purchased in anticipation of demand. When unemployment rate is high and consumer spending is low, demand is contracted thus the need for goods in storage is lower.
Information on US unemployment rate was acquired from the United States Department of Labor, Bureau of Labor Statistics (2013) for the last ten years (2003 to 2013). The data table is shown below. It is helpful to note that these are percentages for all states in the United States and are acquired from potential employable persons 16 years old and above.
The trend seems to be declining in the last four years. The highest unemployment rate recorded within the 2003 to 2013 period is 10% in October of 2009. To analyse this trend, a regression analysis was conducted on the annual means of the monthly unemployment rates, as shown below.
A linear trend line was derived using the annual data. The independent variable is “year” and the dependent variable is “annual unemployment rate”. The linear regression line’s equation is:
Y = 0.407X - 810.51, with an R-squared value of 0.4954
The linear regression indicates that the average unemployment rate increases by 0.407% every year on the average. Other factors that cause the increase in unemployment contribute to the error term of 810.51. The effect of time on unemployment captures 49.54% of the movement in unemployment rate. Unfortunately, no test of significance was performed due to the limitation in available data.
Predicting Unemployment Rates
Using the regression line shown above, the calculated unemployment rates from 2014 to 2016 are shown in the table below. The calculations presented in this table make the following assumption:
- Data for 2013 is preliminary. However the unemployment rate 7.68 is assumed herein as the annual unemployment rate for 2013. Categorizing 2013 as non-historical data yields different annual results.
Figure 2 Regression Analysis Unemployment Rate
Significance Predicted Unemployment Rates
The forecast indicated that unemployment rates will continue to increase in the next four years. For retailing companies, this indicates a contraction in demand. While it may be true that sales of regular goods will decrease, this type of information also leads to the opening of new and potentially profitable business opportunities. Strategies on offering better value-for-money products could drive revenues, as consumers would be looking for the best deals given their lower purchasing capabilities.
However caution must be used in the interpretation of the data and the forecast presented. The calculations presented herein show unemployment rate changes over time, with time as the only predictor of unemployment rate changes. A historical view of unemployment, from 1950 to March 2013 shows a cyclical movement in unemployment rates. If the regression line were to be used solely for predicting unemployment rates, a cyclical behaviour will not be evident as shown the graph below. The data on unemployment may be accurate but is not the sole determinant for consumer spending and economic performance.
Determinants of Consumer Spending
There is considerable evidence indicating a slowdown of consumer spending in correlation with unemployment rates. Bloomberg (2010) stated that despite unemployment recovering in 2010, the consumer spending rate has not picked up as anticipated. In 2010, when the Bloomberg survey was made, there were still limited consumer spending as evidenced by still depressed home values and limited consumer credit despite capital infusion for job creation (the Obama Administration’s stimulus package). The Bloomberg report states that experts, particularly the chief economist for Moody’s Capital Markets and Barclays Capital in New York saying that there economic stimulus will have a modest effect on the economy and consumer spending.
Lion (2010) states that the change in consumer spending affects unemployment rate, similar to how unemployment rate affects consumer spending, as shown in his report. The two-way movement was explained using Granger’s Causality and Path Analysis. Both types of analysis show that when consumer spending decreases, businesses react by way of controlling costs, and in the case of the data presented by decreasing available employment (limiting hours of work, removing regular work in place for temporary work, etc.).
Other studies indicate that there is no significant correlation between unemployment rates and consumer spending. A study conducted by Saving Pontiac (2010 indicate that the last 25 years of data did not conclude a strong relationship between the two. The analysis states that the US had already infused funds into the US banking system to keep interest rates low and the government’s spending on the economy to pump-prime the economy has failed to jump start the US economy. This is explained by banks holding large amounts of bad debt which is a huge hump before economic recovery could truly begin. With about US$ 500 billion in cash infusion (stimulus) in 2010, the effect is dismal given that the debt banks hold for example, exceed this amount significantly.
In the United States, personal spending account for about 70% of the US Gross Domestic Product. According to Policy Mic (2010), the amount of spending of the US is a significant economic powerhouse of the country’s Gross Domestic Product (GDP). GDP is of course composed of personal consumption, investments, government spending and net exports. The share of consumption is the largest as shown in the graph below and has driven the US economy historically.
The United States accounts US$ 3.6 trillion of consumer spending in 2011. This staggering amount is 25% of the entire GDP of the country. However, despite the very large demand of the US consumers, only 7% of the GDP reflects the production of goods and services that the US economy requires. This great discrepancy is alarming and sadly is not easily resolved. Much of the goods consumed in the US are food and fuel which are both outward in nature (imported from outside resources). In addition, the US generates more services rather than goods (about 46% of GDP). These factors make production to address US personal consumption a non-factor today in reviving the economy.
What is significant to note, is that demand has been addressed by imports. In the US, the growth in consumer spending has been addressed by the growth in importation of consumer goods. According to Emmons (2013), the importation of consumer goods increase every year by a rate of 7.5%, a significant number considering that about 44% of all goods consumed in the United States is imported. The factors here that blatantly combine to deliver poor economic performance are high consumer spending, low domestic production and investments and high importation causes this economic anomaly.
Figure 4 US Consumer Spending as Share of Gross Domestic product
It is presumptuous to think that increasing job opportunities in the US will lead to increasing consumer spending that will improve the economy. As a retail store, it is important to note that while employment does have an effect on demand, it is not the only factor that will influence financial performance, especially on the enterprise level. There are other factors that can be considered and other tactical steps that could be taken.
Steps for managing operations through periods of difficult time include controlling costs (such as inventory controls), improving customer services, maintaining attractive prices, enlarging the customer base, improving product training, improving employee capabilities, building financial reserves (savings), maintaining community involvement, managing accounts receivables, improving product offerings, working with suppliers and continuous assessment of business and value propositions.
My final recommendation is for the business to react critically and to form strategic plans to mute the effect of the US economic slowdown. It is only through active involvement and operations will the retail store survive. Focusing on just one factor, in this case unemployment rates, will not provide a very good understanding of the economy and the consumer markets.
Bloomberg (2010). Unemployment Rate in the US. Web. Retrieved from http://www.bloomberg.com/apps/news?pid=newsarchive&sid=aSqyoDA4ePbg
Bureau of Labor Statistics. (2013). US Unemployment Rate. Department of Labor. Retrieved from http://data.bls.gov/timeseries/LNS14000000
Emmons, W. (2013). Don't Expect Consumer Spending To Be the Engine of Economic Growth It Once Was. Federal Reserve Bank of St. Louis. Retrieved from http://www.stlouisfed.org/publications/re/articles/?id=2201
Google. (2013). US Unemployment Rate. Retrieved from http://www.google.com.ph/publicdata/explore?ds=z1ebjpgk2654c1_&met_y=unemployment_rate&hl=en&dl=en&idim=country:US&fdim_y=seasonality:S
Lion, G. (2010). Change in Consumer Spending Affecting Unemployment Rate? Slide Share. Retrieved from http://www.slideshare.net/gaetanlion/consumer-spending-causing-unemployment-analysis
Washington Blog. (2010.High Unemployment Will Dampen Consumer Spending. Retrieved from http://georgewashington2.blogspot.com/2009/06/high-unemployment-will-dampen-consumer.html