JESSICA N. GROSS and KELI C. BARNHOUSE
This paper forecasts unemployment rates in South Carolina for the years 2001 and 2002.(The variables used are annual averages of monthly data from the years 1991 to the year 2000.This is due to the fact that the data used were not seasonally adjusted).The explanatory variable is the Consumer Price Index.The approach is based on the Phillips Curve Model.The unemployment rate in South Carolina is forecast to rise to 3.71% in the year 2001 and decline to 3.16% in the year 2002.The Fed, the government, and firms should continue to provide ways to maintain the low unemployment level.(JEL:E24).
Part 1. Introduction
This paper forecasts the unemployment rate of South Carolina for the years 2001 and 2002.The explanatory variable used in this forecast is the Consumer Price Index (CPI).This forecast, through utilizing the Phillips Curve approach, estimates the relationship between the unemployment rate and the CPI.
Forecasting unemployment rates is quite important to our economy because it affects consumers.Unemployment rates affect the way they think about the economy, which in turn affects consumer spending. As the unemployment rate begins to rise, there is a decrease in consumer spending.This decrease is reflected in the revenue a company reports.This leads to employee pay cuts and layoffs, which result in a further decrease in consumer spending.This forecast is important in several ways. First, the employed can begin to prepare for the possibility that our jobs may cease to exist (or that it will be much harder to find a new one).Second, consumers can begin to prepare for the downturn in the economy and therefore a decrease in the relative price of goods.Third, business leaders can begin preparing for ways to survive the economic downturn.
The remainder of the paper includes:Part 2., which presents the data used to forecast the South Carolina unemployment rate; Part 3., which explains the theoretical basis for the Phillips Curve approach in forecasting the unemployment rate: Part 4., which presents the forecast of the South Carolina unemployment rate for the two-year period: Part 5., which evaluates the importance of this forecast for the economy, and Part 6., which discusses conclusions for economic policy.
Part 2. Data
The figures required for this forecast were taken from the Bureau of Labor Statistics web site.The Bureau of Labor Statistics variables LAUST45000003 and CUUR0300SAO represent the unemployment rate of South Carolina, and the Consumer Price Index for all urban consumers, respectively.The data are published monthly.However, the provided annual data values were used in this forecast.The forecast is for two years into the future, and the sample period ranges from 1991 to 2000.
Part 3. The Phillips Curve as a Forecasting Instrument
Due to the fact that the forecast horizon is only two years, the relationship being estimated is a short-run Phillips Curve.This curve is quite appropriate for a short-term forecast based upon annual data.
This forecast assumes that unemployment is a function of inflation:
Due to the fact that inflation is extremely volatile, and rarely forecasted more than one year into the future, we are utilizing the Consumer Price Index to illustrate this tradeoff.This results in the following formula:
ut = f ( CPIt )
Due to the fact that we are forecasting the unemployment rate two years into the future, the Consumer Price Index needs to be lagged for that same period:
ut = f ( CPIt-2)
Part 4. South Carolina Unemployment: A Short Term Projection for 2001-2002
The following forecasting equation was estimated for South Carolina by an ordinary least squares regression for the period 1991-2000.The R-squared of the estimate is 0 .7422.This regression also had t-statistics of 6.295 and –4.7995, for the intercept and slope, respecitvely.The estimate of the equation is:
u = -.104(CPIt-2) + 20.57
Table 1 reports the forecast of unemployment rates in South Carolina for the years 2001 and 2002:
Part 5. Forecast Implications: Unemployment to Increase in the Immediate Future
Unemployment forecasting is important to measure the performance of the economy as a whole.Household welfare decreases as unemployment is raises.As the unemployment rate increases, firms hire less workers.These workers no longer earn wages, which were in the past recycled back into the economy, as consumption and investment, aiding in the loss of profits and the competitive advantage for firms.
With a higher unemployment rate, the governments will have lower tax revenues.This will give the government considerably less to spend on social programs.There will also be higher state expenditures on unemployment compensation because less people will be employed.Perhaps the most detrimental aspect though is that, an increase in the unemployment rate decreases an individual’s chance of feeling secure in his job, which in turn decreases the standard of living because money must be saved in preparation for the possible loss of employment.This will also work to increase the deficit.
Part 6. Policy Conclusions
The unemployment rate in South Carolina is projected to increase over the next year, and decrease in the following.For the year 2001, the forecast is expected to rise from the current 3.3% to 3.71% and for the year 2002 the forecast is 3.16%.To prepare for future possible economic hardships as well help prevent them, such as higher unemployment, Alan Greenspan and the Fed have lowered interest rates three consecutive times..
Bureau of Labor Statistics, Bureau of Labor Statistics Data 1991-2000, retrieved from the World Wide Web on February 13, 2001