Executive Summary
Over the
last 15 years,
-
the state of
Wisconsin
had significantly lower unemployment rates than the nation.
-
Portage
and Marathon Counties had similar unemployment rates; however,
Wood
County's
unemployment rate was significantly higher than
Portage
and Marathon Counties' unemployment rates.
-
Portage
and Marathon Counties had similar unemployment rates when compared with
Wisconsin;
however, Wood County had significantly higher unemployment rates than the
State of Wisconsin.
-
Portage,
Marathon and Wood Counties' unemployment rates were drastically lower than
the national unemployment rate.
-
Portage
and Wood Counties' retailers had similar confidence regarding recent changes
in total sales; however; Marathon County retailers were significantly more
confident in total sales than retailers in Portage or Wood County.
-
Portage
and Wood Counties' retailers had similar confidence in recent changes in the
level of store traffic; however,
Marathon
County
retailers were significantly more confident in the level of store traffic
than retailers in Portage or Wood County.
-
Marathon
County retailers were better predictors of future total sales; however,
Portage and Wood Counties' retailers were less accurate predicators of
future total sales.
-
Marathon
County retailers were better predictors of future store traffic; however,
Portage and Wood Counties' retailers were less accurate predicators of
future store traffic.
-
there was an inverse
relationship between the central Wisconsin yearly change in the unemployment
rate and central Wisconsin's retailer confidence in total sales.
-
there was an inverse
relationship between the national half-year change in the unemployment rate
and business confidence in national activity.
-
there was an inverse
relationship between central Wisconsin's retailer confidence in expected
store traffic and the central
Wisconsin
yearly change in the unemployment rate one quarter in the future.
-
there was an inverse
relationship between central Wisconsin's business confidence in expected
local activity and the central
Wisconsin
half-year change in the unemployment rate two quarters in the future.
Introduction
Our main goal is to further
enrich the surrounding community's knowledge of the economic conditions in
central Wisconsin over the past 15 years, from 1990 to 2004. The purpose of
our research was to identify similarities and differences between the central
Wisconsin counties' unemployment rates, and to identify possible relationships
between retailer confidence indices. Additionally, we compared unemployment
rates to business and retailer confidence indices in central Wisconsin to
determine whether or not the confidence of businesses and retailers in the
economy reflects changes in area unemployment rates.
Data
We used data collected by the
Wisconsin Department of Workforce Development (DWD) for the civilian labor
force statistics in
Portage,
Marathon and Wood Counties. These statistics include total workforce, total
employed, total unemployed and the unemployment rate for each quarter over the
last 15 years (1990-2004). This data is made available on a monthly basis;
however, we used the last month of each quarter (i.e. March, June, September,
December) for our analyses. Civilian labor force statistics can be obtained
from the DWD website at
http://worknet.wisconsin.gov/.
The business and retailer
confidence survey data is collected by the Central Wisconsin Economic Research
Bureau on a quarterly basis. Questions on the survey reflect changes in
conditions of the business and retailer sectors in central Wisconsin.
Businesses are asked to rate on a scale of 0 to 100 (in increments of 25) the
following economic changes in their respective business:
-
Change in national activity compared the over the past
six months
-
Change in local activity compared with the over the past
six months
-
Expected change in national activity over the next six
months
-
Expected change in local activity over the next six
months
-
Expected change in industry activity over the next six
months
A rating of 0, 25, 50, 75 or
100 respectively represents a substantially worse, moderately worse, the same,
moderately better or substantially better change in the corresponding economic
condition over the specified time period. Retailers are asked to rate in a
similar fashion the following economic changes their retail outlet
experiences:
-
Change in the level of total sales compared with the
same quarter of the previous year
-
Change in the amount of store traffic compared with the
same quarter of the previous year
-
Expected change in the level of sales in the next
quarter compared with the same time a year ago
-
Expected change in the amount of store traffic in the
next quarter compared with the same time a year ago
Analysis
Our research consists of two
primary sets of statistical analysis. First, we examined unemployment rates
in a comparative manner. These comparisons include:
-
Portage County vs. Marathon
County
-
Portage County
vs. Wood County
-
Marathon County vs. Wood
County
-
Portage County vs. Central
Wisconsin
-
Marathon County vs. Central
Wisconsin
-
Wood County vs. Central
Wisconsin
-
Portage County vs. State of
Wisconsin
-
Marathon County vs. State of
Wisconsin
-
Wood County vs. State of
Wisconsin
-
Portage County vs. The United
States
-
Marathon County vs. The
United States
-
Wood County vs. The United
States
-
State of Wisconsin vs. The
United States
Second, we examined possible
correlations regarding the following:
-
Retailer confidence in the
level of total sales vs. a comparable change in the unemployment rate in
central Wisconsin
-
Retailer confidence in the
amount of store traffic vs. a comparable change in the unemployment rate in
central Wisconsin
-
Business confidence in the
level of national economic activity vs. a comparable change in the national
unemployment rate
-
Business confidence in the
level of local economic activity vs. a comparable change in the unemployment
rate in Central Wisconsin
-
Retailer confidence in the
level of expected sales vs. a comparable change in the unemployment rate in
central Wisconsin
-
Retailer confidence in the
amount of expected store traffic vs. a comparable change in the unemployment
rate in central Wisconsin
-
Business confidence in the
level of expected national economic activity vs. a comparable change in the
national unemployment rate
-
Business confidence in the
level of expected local economic activity vs. a comparable change in the
unemployment rate in central Wisconsin
Methods
Population Mean Rates of Unemployment
The following formulas were
found in the fourth edition of Introduction to Probability and Statistics
by J. Susan Milton and Jesse C. Arnold. When testing for significances in
differences of population mean rates of unemployment from area to area, we
first tested for a difference in population variance. In all tests, the
critical region is based on an alpha level of five percent. Based upon the
result of the test for differences in variances we used the following test
statistics for testing the population mean rate of unemployment:
-
If population variances were equal then we used the
pooled variance given by

in order to
use the pooled T test statistic which equals

-
If population variances were unequal then we used the
Smith-Satterthwaite degrees of freedom given by

in order to
use the unequal variance test statistic which equals
Paired Data between a Retailer Confidence Index and a Retailer Expected
Confidence Index
Data was paired to make a
valid comparison between what retailers thought would happen in the future
quarter against what actually happened in either total sales or store
traffic. In order to analyze this statistically, we used the paired T test
statistic given by,

where D-bar is the average
difference between the confidence index in the current quarter and the
expected confidence index given in the previous quarter, and Sd is
the standard deviation of all the differences.
Correlation between a Confidence Index and a Comparable Change in the
Unemployment Rate
When testing for
significances in linear regressions between two random variables, namely a
confidence index and a change in unemployment rate over a similar time frame,
we used the following test statistic:

We also double checked these
tests, as a demonstration, with the test statistic for the Pearson correlation
coefficient given by
In order to maintain a
consistent comparison of random variables, alterations to the unemployment
rate data were made. The confidence indices for each question have a
reference period. On the retailer confidence survey, questions about changes
in total sales and store traffic are compared either to the current quarter of
the previous year or the next quarter of the previous year. For example, when
a retailer gives a response of greater than 50 (less than 50) in the current
quarter, that means total sales or store traffic have increased (decreased)
compared with the same quarter of the previous year. Thus, a comparable
change in the unemployment rate was determined by using the following formula
*100
When businesses are asked
about recent changes in economic activity the comparison is over the last six
months and future changes in economic activity are compared over the next six
months.
Findings
Average Quarterly
Unemployment Rates Over the Last 15 Years
|
Area |
Unemployment Rate |
|
Portage County |
4.36% |
|
Marathon County |
4.31% |
|
Wood County |
4.87% |
|
Central Wisconsin |
4.47% |
|
Wisconsin |
4.34% |
|
United States |
5.60% |
Table 1
shows the comparison of the average unemployment rate over the last 15 years
between the State of Wisconsin and the nation, which are 4.34% and 5.60%
respectively. The data indicate that the unemployment rate over the last 15
years was significantly lower for Wisconsin compared with the nation. On
average, Wisconsin had a better workforce environment than many of the other
states in the union. Specifically, this difference in the average quarterly
unemployment rate over the last 15 years may be due to Wisconsin's strong work
ethic and public education system compared to the average state.
Table 2
shows each of the central Wisconsin counties compared with a central Wisconsin
aggregate (Portage, Marathon and Wood counties combined) unemployment rate.
The comparison is between the average quarterly unemployment rate over the
last 15 years for Portage, Marathon and Wood counties, which are 4.36%, 4.31%,
and 4.87% respectively, and the central Wisconsin average quarterly
unemployment rate of 4.47%. Clearly, the result that each county's
unemployment rate does not significantly differ from the central Wisconsin
average is expected; however, this shows that none of the counties exhibited
extreme differences in unemployment rates over the last 15 years. From this,
we can conclude that the employment situations in Portage, Marathon and Wood
Counties were relatively stable.
Table 3
shows a pair wise comparison of each of the three central
Wisconsin counties to one another. The two significant results are
the comparisons between
Portage and Wood Counties and
Marathon and Wood Counties. The data indicate that Wood County's average
unemployment rate over the last 15 years of 4.87% was significantly higher
than Portage and Marathon Counties' unemployment rates of 4.36% and 4.31%
respectively. However, the data also indicate that
Portage
and Marathon Counties' unemployment rates were statistically equivalent over
the last 15 years. A possible explanation of this deals with how the
municipalities are structured in Marathon and Portage Counties. In Marathon
there is a large city, Wausau, adjacent to two smaller towns, Rothschild and
Schofield. Similarly, Portage County has a city, Stevens Point, which is
adjacent to two smaller towns, Whiting and Plover. On the contrary,
Wood
County
has two smaller cities, Wisconsin Rapids and Marshfield, which are not
adjacent. It seems likely that the geographic relationship of the municipal
populations in Marathon and Portage Counties are more conducive to a healthy
employment situation. In addition, Wood County's high dependence on paper
manufacturing is likely to have played a role in this outcome.
Furthermore, in
Table 4, the data demonstrate that
Wood
County
is once again the odd one out. According to the data, Portage and Marathon
Counties had similar unemployment rates as Wisconsin whereas Wood County's
unemployment rate of 4.87% was significantly higher than the state's
unemployment rate of 4.34%. In this case, the noted difference in Wood
County's unemployment rate from the State of Wisconsin cannot be attributed
solely to the layout of its municipalities. Education and health care
services typically account for nearly a quarter of Wood County's employment
creating less variety in the labor market. The lack of variety in the labor
market may have lead to poor job opportunities for people who were looking for
work in other sectors. Also, the reliance on a struggling paper manufacturing
industry, along with the less than optimal geographic relationship of its
municipal populations, could possibly be creating the atypical unemployment
rates. In general, Portage and Marathon Counties had more stable employment
situations with respect to
Wisconsin
than that of Wood County's situation.
Table 5
enforces the notion that, on average, central
Wisconsin
had better employment conditions than the nation. In all instances, when the
average unemployment rate over the last 15 years for each of the central
Wisconsin counties were compared with the nation they were significantly
lower. This may be due to the same reasons mentioned above for Table 1.
Table 6
begins our examination of business and retailer confidence regarding the
economy. We first looked at pair wise comparisons of retailers in each county
in central Wisconsin to examine if their confidence in total sales, compared
with the same quarter of the previous year, was significantly different. The
data indicate retailers in
Portage
and Wood Counties experienced similar changes in total sales, on average, over
the last 15 years. On the other hand, when Portage or Wood County were
compared with Marathon County the difference in confidence was significant.
It should be noted that Marathon County experiences a much higher level of
economic activity than either
Portage
or Wood County (evidence of this comes from the Wisconsin Department of
Revenue county sales tax distribution data)-this could be the cause of the
difference in confidence. When data is collected on Marathon County, it is
considered to be a metropolitan statistical area. This means that
Wisconsin
considers this area to be of greater concern than that of Wood or Portage
Counties due to its strong economic influence on the surrounding area.
Table 7
is similar to Table 6 except with regard to store traffic. Retailers in
Portage and Wood Counties had similar confidence over the last 15 years
regarding store traffic compared with the same quarter of the previous year.
However, when Portage or Wood County was compared with Marathon County there
was a significant difference in confidence levels. Once again, this may be
the result of the reason stated above in our findings from Table 6.
Furthermore, the fact that Marathon County is a metropolitan statistical area
may be contributing to the results in Table 7.
Table 8
shows a comparison of the confidence indices between the level of retailer
confidence in total sales and the retailer confidence in expected sales. This
examination should demonstrate whether or not the retailers in the central
Wisconsin counties were good predictors of the future over the last 15 years.
The data indicate that retailers in Portage and Wood Counties were less
accurate in terms of forecasting future changes in total sales than those in
Marathon County. This means that the survey is more useful in predicting what
will occur in the next quarter given the expected confidence in total sales by
retailers in Marathon
County.
The opinions of retailers in Portage and Wood Counties were determined to be
less helpful in predicting what total sales will be like in the future
quarter.
Table 9
shows a similar comparison to that of Table 8 except with regard to store
traffic. Retailers in Marathon County were good predictors of future store
traffic. However, retailers in Portage and Wood Counties were not good
predictors of future store traffic. These results are identical to the
results of Table 8 except that it is with regard to store traffic. In both
Table 8 and Table 9, the fact that Marathon retailers were better predictors
of the future may be due to greater economic stability. That is to say that
growth may have been more constant in
Marathon
County
and more variable (or less predicable) in
Portage
and Wood Counties. Economic stability in Marathon County may be attributable
to the greater amount of economic activity as evidenced by sales tax
distributions and a more robust employment situation.
Table 10
changes our focus to linear regressions between changes in unemployment rates
and confidence indices. The yearly change in the unemployment rate (from
quarter to quarter) was multiplied by 100 to be comparable to the various
confidence indices. The first comparison was between the central
Wisconsin yearly change in the unemployment rate and retailer
confidence in total sales. The linear regression on these two variables was
found to be significant. This means that if the central
Wisconsin unemployment rate
decreases, retailers have a high confidence in total sales. Likewise, if the
central Wisconsin unemployment rate increases, retailers have a low confidence
in total sales. Support of this comes from the fact that a higher
unemployment rate results in a decrease in the average amount of disposable
income per consumer. Thus, one would expect that less disposable income
directly influences the level of sales in an economy.
Table 11
shows the linear regression between the central
Wisconsin yearly change in the unemployment rate and retailer confidence in store
traffic. The regression was determined not to be significant using the
typical standards of statistics. However, if we were to treat this comparison
more leniently then we might find the correlation between unemployment rate
changes and retailer confidence in store traffic to be significant. If that
were the case, then an increase in the central
Wisconsin unemployment rate
results in lower store traffic. The analysis of this relationship is directly
related to what was discussed above about Table 10. A decrease in disposable
income results in consumers frequenting retailer outlets less often in order
to make purchases.
Table 12
shows the linear regression between the national half-year change in the
unemployment rate and business confidence in national activity. The data
indicate that this regression is significant by a large margin. This means
that the business confidence in recent changes in national economic activity
correlates well with similar changes in the national unemployment rate.
Table 13
shows the linear regression between the central
Wisconsin half-year change in the unemployment rate and business confidence in
local activity. The regression was not significant. This means there is no
apparent relationship between the central
Wisconsin half-year change in
the unemployment rate and business confidence in local activity. A possible
explanation of the results in Table 12 and 13 may be due to the fact that it
is easier to predict economic activity on a larger scale than a smaller
scale. For example, a business that provides services to hundreds or
thousands of customers nationally can gauge economic activity much better
compared with the few customers they service on a local level. Another factor
contributing to this correlation may be due to the stability of national
activity in comparison to the variability in local activity.
Table 14
shows the linear regression between central
Wisconsin's
retailer confidence in expected total sales and the central
Wisconsin yearly change in the unemployment rate one quarter in the
future. The regression was not significant. This implies that a change in
the unemployment rate is not necessarily dependent on how confident retailers
are regarding expected total sales. One might expect an inverse relationship
between these two variables where an increase in retailer confidence implies a
lower unemployment rate; however, the lack of a significant relationship may
be due to a lag effect. In other words, increased confidence in any part of
the economy may not be immediately noticed through an indicator such as the
unemployment rate until some period after that increase took place.
Table 15
shows the linear regression between central Wisconsin's retailer confidence in
expected store traffic and the central Wisconsin yearly change in the
unemployment rate one quarter in the future. The regression was significant.
This implies that a change in the level of retailer confidence regarding
expected store traffic corresponds with a change in the unemployment rate.
Although correlation does imply that one variable relates to another, it does
not imply causality. However, it is possible that if entrepreneurs expect to
perform well in the future, more likely than not economic conditions will
improve due their increased activity. This is an illustration of
self-fulfilling prophecy.
Table 16
shows the linear regression between business confidence in expected national
activity and the national half-year change in the unemployment rate two
quarters in the future. The regression was not significant. This means there
is no apparent relationship between business confidence in expected national
activity and the national unemployment rate. This lack of association is most
likely due to the relatively small nature of our survey. Although businesses
in the local area have a large impact on the central Wisconsin economy, their
impact nationally is quite small. Thus, in order to develop a meaningful
correlation between business confidence and the national unemployment rate,
the scope of our survey would need to encompass businesses throughout the
nation. Also, lag times may be contributing to our result in table 15 as
discussed in table 14.
Table 17
shows the linear regression between business confidence in expected local
activity and the central Wisconsin half-year change in the unemployment rate
two quarters in the future. The data indicate that there is a correlation
between these two variables. Clearly, it seems reasonable that an increase in
business confidence in local activity, taken from a survey of central
Wisconsin businesses, would correspond to a lower unemployment rate in central
Wisconsin. This reinforces the notion that as businesses in an area become
more confident in local activity the area experiences a better employment
situation. Lag times may not be contributing to our results as significantly
as in the other tables because confidence in local activity may have a more
direct relationship with the actual level of economic activity in central
Wisconsin than retailer confidence in total sales as examined in table 14 or
business confidence in national activity as examined in table 15. In order
for retailers to increase the number of workers at their outlets, they must
first experience increases in revenue. On the other hand, if a business
expects an increase in activity then they must accommodate for such
expectations. Therefore, we see a more immediate impact on the unemployment
rate and thus lag times are not as significant with regard to confidence in
expected local activity.
Sources
Central Wisconsin Economic
Research Bureau Business and Retailer Confidence data can be found in part on
the web at
http://www.uwsp.edu/business/cwerb/, or by calling 715-346-3774 for
further information.
Department of Workforce
Development Local Area Unemployment Statistics can be located at
http://worknet.wisconsin.gov/, by clicking Data Analyst on the left, Data
Tables in the submenu, and then Query for LAUS.
Department of Workforce
Development Industry Data for
Wisconsin counties can be located at
http://worknet.wisconsin.gov/, by clicking Data Analyst on the left, Data
Tables in the submenu, and then Query for Non-Metro County Industry Employment
Estimates.
Wisconsin Department of
Revenue County Sales Tax Distributions can be located at
http://www.dor.state.wi.us/report/c.html.
TABLE 1

TABLE 2

TABLE 3

TABLE 4

TABLE 5

TABLE 6

TABLE 7

TABLE 8

TABLE 9

TABLE
10

TABLE
11

TABLE
12

TABLE
13

TABLE
14

TABLE
15

TABLE
16

TABLE
17


DATA
CIVILIAN LABOR FORCE 1990-2004







RETAILER AND BUSINESS CONFIDENCE 1990-2004








