A Two-year Forecast of Unemployment Rate of Georgia Based on Inflation Rates

 

CHRIS ELBERT

College of Business

Western Carolina University

 

Abstract

 

The unemployment rate of Georgia is expected to be between 3.9 and 4.4 percent over the next two years. This short-run forecast is based on the Phillips Curve, the relationship between inflation and unemployment. Expected inflation, unemployment, and U.S. GDP were used as explanatory variables, where inflation was determined by the Michigan inflation survey. (The correlation between unemployment in Georgia and the explanatory variables proved to have some efficiency.) The forecasting regression’s R2 showed that 58% of the variation in unemployment is explained by the variation of the explanatory variables. (Workers and employers should see that current availability in jobs would continue to stay near 4% over the next two years.) (JEL: E24, E31, E66)                                                       

 

Part 1. Introduction

 

This paper forecasts the quarterly unemployment rate for the state of Georgia for the years 2000 and 2001. The sample period for the data was from the first quarter of 1990 through the fourth quarter of 1999. This sample period includes data during the recession of 1990-91, causing the possibility of outliers in the data. The forecast horizon is two years into the future, to make the accuracy of the calculations stronger. The explanatory variables used are the quarterly inflation rate and Gross Domestic Product (GDP) of the U.S. This forecast is based on the Phillips Curve determining the relationship between inflation and unemployment by using the Michigan inflation survey.

 

With an accurate prediction of the unemployment rate for the state of Georgia, state officials will be able to prepare themselves for any shortage in workers or jobs. This will allow the state to determine if any new jobs or positions need to be created for those who are in need of work. This forecast will also help those in the workforce, by allowing them know ahead of time what the future unemployment situation may be. With the amount of data observed, it would be best to predict only two years into the future, because accuracy may be affected with a longer prediction.

 

The rest of this paper is organized as follows: Part 2. presents the data used to forecast the unemployment rate for the state of Georgia; Part 3. presents the theoretical basis for the approach used to forecast the unemployment rate; Part 4. presents the forecasts of unemployment for 2000 and 2001; Part 5. evaluates the importance of this forecast to the economy, and Part 6. explains conclusions for economic policy.

 

Part 2. Data

 

Two of the three variables used in this forecasts came from the Federal Reserve Bank of St. Louis Federal Reserve Economic Data (FRED). The variables GDP and inflation rate came from (FRED), where the expected inflation rate was taking from the Michigan inflation survey. For this forecast the inflation rate was converted from monthly data to quarterly data, by taking the average of each three-month period.

 

The figures for the variable GDP came from (FRED). The data was taken quarterly for the GDP of the U.S. in billions of dollars and is seasonally adjusted.

 

The final variable is the unemployment rate for the state of Georgia. For this forecast, the unemployment rate was converted from monthly data to quarterly data by taking the average of each three-month period. This data was taken from the Economic Time Series Page from the source economagic.com.

 

By converting all data to the same time period such as quarterly data, will better the chance of a more accurate forecast. It is believable that these variables used are good predictors of unemployment. Through the use of the Phillips Curve, it is implied that unemployment and inflation can be used to predict each other. When inflation increases, the unemployment rate tends to decrease.

 

Unemployment rate can also be predicted by glancing back over past unemployment rates. Trend can be pointed out through past data sets to determine if the history of unemployment may repeat itself. The regressions done on these data sets can support the fact and assumption of predicting the future. All data used for this paper can be found at the websites for Federal Reserve Bank of St. Louis Federal Economic Reserve Data and the Economic Time Series Page at EconoMagic.com.

 

Part 3. Economic Theory:

The Phillips Curve and the Michigan Inflation Survey

 

In this forecast, the GDP is already calculated through the data taken from (FRED). The equation used for determining the GDP is taken from the Keynesian Aggregate Expenditures Model and is as follows:

Y = GDP = C+I+G+X

 

Where Y is real GDP, C is consumption spending, I is investment spending, G is government spending, and X is net exports of the U.S.

 

The GDP (Yt) is directly affected by the unemployment rate. GDP will have a smaller value if there is a lack of workers and production. Since GDP is a function of the employment rate, it is also a function of the unemployment rate and the equation is written as follows:

ut = f (Yt-8)

 

Where ut is unemployment rate.

 

The short run Phillips Curve predicts the relationship between unemployment and inflation. According to this theory, unemployment and inflation affect each other inversely. With this information, it can be assumed that the inflation is a function of unemployment:

ut = f (inft-8)

 

Where inft-n is the inflation rate and is determined by the Michigan inflation survey. The expected inflation rate is surveyed up to the quarter of 2000.1.

 

Combining all of the items that are considered a function of unemployment, the hybrid model of unemployment can also be written as follows:

ut = f (ut-8, Yt-8, inft-8)

 

After lagging the right side of the equation by two years equivalent to eight months, the equation can be written as follows:

ut = A0+A1(Yt-8)+A2(inft-8)+A3(ut-8)

 

The equation was lagged eight quarters on the right side to make it possible to forecast unemployment two years into the future.

 

Part 4. Empirical Results:

A Short Term Projection of Georgia’s Unemployment 2000-2001

 

The unemployment forecasting equation came from the quarterly data 1997.4-1999.4, however all data was performed starting from 1990.1. The results from the regression are in Table 1.

 

Table 1

Regression Estimate of Unemployment Rate Forecasting Equation: 1997.4-1999.9

Explanatory Variable

Estimated Coefficient

Intercept

11.61

Yt-8

-0.0007

Inft-8

-.4703

R2 =. 5806

F(zero slopes)=25.61

 

The R2 is equal to .581, which means that 58 percent of the variation in unemployment is explained by the variation of the variables inflation and GDP. The F stat is equal to 25.61, does not give enough significant evidence to reject the null hypothesis of zero slopes.

 

 

Table 2

Forecast of Georgia Unemployment 2000.1-2001.4

Quarter

Forecast

2000.1

4.36%

2000.2

4.45%

2000.3

4.32%

2000.4

4.31%

2001.1

4.21%

2001.2

4.01%

2001.3

3.95%

2001.4

3.81%

 

This forecast projects that the unemployment rate of Georgia will average 4.36 percent in the year 2000 and average 3.995 percent in the year 2001 taken from Table 2. These forecast are very favorable for the economy of the state of Georgia. This forecast shows that there will be a sufficient rise in the economy causing increasing the number of jobs.

 

Part 5. A Rosy Outlook

 

This forecast can benefit all individuals from government officials to lower level employees. As economy rises in the U.S. and Georgia, the unemployment rate lowers, giving a positive outcome. With this forecast it can be seen that there is a positive outlook for the near future in the state of Georgia for income, GSP, and employment. Also, after knowing how good the unemployment rate is, employees and employers can take more risk with working and an economic scale.

 

This forecast is based on the assumption that most of the workforce is changing from producing goods to delivering services. With the widespread use of new technology, many jobs have been created through the Internet giving more opportunities of work. The number of service jobs tends to grow more rapidly than those producing goods.

 

With the assumption of more service jobs than goods jobs, employees who work with producing goods may find themselves losing their jobs. To stay within the workforce, many of these workers are forced to obtain a new trade or working in a service job. With computers and the Internet rapidly growing, those who work in service and are computer literate may find themselves receiving promotions where new jobs may be formed and employment will be needed. Also, through the Internet the rate of self-employment and small business is growing.

 

The way technology is growing it may become necessary for every individual to have some computer skills to have a chance to work. With this assumption, in the long run the unemployment rate may raise again, causing the only jobs available come via the Internet service.

 

Part 6. Policy Conclusion

 

The unemployment rate of the state of Georgia is forecast to remain fairly constant over the next two years, with some decrease in the latter quarters of the year 2001. The rate will remain near 4 percent.

 

Based on this forecast, those who are in the workforce should be able to find excessive amounts of jobs, due to the decrease in unemployment and increase in economy. However, with the use of technology and the need to be computer literate in today’s workforce, which is very heavily represented with service jobs, employers may have difficulty finding employees with the skills necessary to work in its industry. A way to avoid this possible problem is to recommend and encourage employees and future employees to obtain essential skills.

 

This forecast clearly shows that the chances of finding jobs will increase and there is a positive outlook for those who are in the current workforce. Before going on in the workforce, workers should try to obtain necessary skills or trades that can help in advancement.

 

Through reasonable data and thorough test, the data obviously shows that when inflation is up unemployment is down. The U.S. Government and Federal Reserve should observe the predicted data as they decide on what to do about inflation rates, and notice that unemployment rate decreases while the GDP of each state and of the U.S. increases.

 

The goal of the state and federal governments should be to have as many workers in the workforce. The result of more workers increases the amount of consumer spending, which increases the circulation of money.

 

For the Federal Reserve, its goal should be to try to keep inflation rates as constant as possible. The changes in inflation rates affect the interest rates and the spending of households and firms. Also with fluctuation in the inflation rate, the number of people in jobs will begin to vary.

 

References

 

Economic Time Series Page, EconoMagic, http://www.EconoMagic.com/em-cgi/data.exe/fedstl/mich/. 2000.

 

 

Federal Reserve Bank of St. Louis, Federal Reserve Economic Data (FRED), http://www.stls.frb.org/fred/. 2000.