ANALYSIS OF WYOMING'S ECONOMY:

by: Gregg Detweiler

Nationally, Federal Reserve Chairman Alan Greenspan is warning that a mild recession could hit this year since recent economic statistics show an abrupt slowing of growth in the economy. If this should happen, will Wyoming's economy experience a similar decline in growth? As an Economist for the state of Wyoming, one of my responsibilities is to produce current monthly estimates on the number of jobs in various industries (see
"Wyoming Nonagricultural Wage and Salary Employment"). These types of data are considered measures of economic well-being and changes in the data are related to the business cycle. However, total nonagricultural employment data are highly seasonal. Therefore, it is very difficult to decide exactly how each industry is faring over time. In the following narrative I will attempt to explain the definition and uses of seasonal data and compare the major industries of Wyoming and the United States through the last two recessions.

Seasonal events are those events that tend to occur at the same time each year. If a time series (frequent measurement over a period of time) like the Current Employment Statistics (CES) is affected by seasonal events, then that series is said to exhibit seasonality. Seasonal adjustment is a statistical tool that attempts to remove or filter out the seasonal fluctuations in a time series. Once the seasonal fluctuations have been removed, the underlying trend or true direction can be more easily observed.

One of the most important uses of CES data is to measure employment trends. These long- and short-term employment trends can be obscured by employment movements caused by seasonality. Seasonal adjustment removes the seasonal fluctuations from a time series, making it easier to see the underlying economic trends. This allows the analyst and users to make month-to-month comparisons of the employment level. The following are major users of seasonally adjusted CES data: Federal Reserve Board, Bureau of Economic Analysis, Congressional Budget Office, Wall Street Analysts and people like yourself.

A time series can be viewed as a sum of individual components that may include: a mathematical expression or term for location (level or statistical mean value), a trend component (long-term movements in the level of a series over time), a seasonal component (repetitive ups/downs over the course of a year caused by recurring annual events), and an irregular component (random fluctuations caused by unexpected or unusual events). Deseasonalizing CES monthly estimates represents an attempt to transform estimates of the number of jobs worked (a measure of labor market demand and economic opportunity) to an economic indicator that can be statistically related to other inputs in the production process.

Reliable and timely economic data that describe emerging business trends are important ingredients in economic analysis. Compared with the wide range of national economic indicators available, regional (multi-county or multi-state) indicators are scarce. There are three types of indicators (leading, lagging, & coincident) used to do economic analysis and Wyoming's Employment Resources Division, Research & Planning, uses leading and coincident indicators of the business cycle. Employees on nonagricultural payrolls (see "Wyoming Nonagricultural Wage and Salary Employment") are classified as a coincident indicator--an economic variable whose movement tends to parallel the general direction of the economy. In other words, the movements of coincident indicators like nonagricultural employment tend to concur with those of the business cycle.

Leading indicators are economic variables whose movements tend to forecast the general direction of the economy. The movements of these variables tend to lead the movements of the business cycles. Average weekly overtime hours for production workers in manufacturing, building permits and average weekly initial claims for unemployment insurance are examples of leading economic indicators for Wyoming. The latter are available at state and county levels and can add important analysis that is helpful in illuminating employment trends when used in association with other data.

Once the raw data has been compiled and the time series seasonally adjusted, we can begin the evaluation of the data and its affects on Wyoming's economy. The two types of analysis used in examining the movements within the economy are external and internal analysis. External analysis is the evaluation of Current Employment Statistics (CES) data against other types of economic data from government agencies and private organizations. Initial claims for unemployment insurance (see Footnote 1 and Figure 1: Wyoming--Initial Claims vs CES Employment), building permits ( Figure 2: Permit Authorized Construction--Building Permits Issued), and unemployment insurance (UI) wage records (see Footnote 2) are three main sources for identifying immediate fluctuations in the number of jobs worked. Figure 1 is a comparison graph of initial unemployment claims (IUC) to CES employment. In theory, we would expect to see an inverse correlation. That is, when CES employment increases, initial claims should decrease and the reverse should hold true as well. A close examination of the graph shows that there is not an inverse correlation. However, this graph is still helpful in gaining insight into Wyoming's economy. By analyzing other related data sources such as UI wage records, we can speculate that the one reason why there is no inverse correlation between initial claims and CES employment is due to the increase of individuals working multiple jobs.

The other type of analysis used to evaluate Wyoming's economy is called internal analysis. Internal analysis is the evaluation of CES data against itself historically using variable time periods, or against trends in the National CES series. The three types of internal analysis used in the CES unit are over-the-month change (level & percent), over-the-year change (level & percent) and comparisons of historical graphs with recessions. The figures presented for the United States and Wyoming (presenting total nonagricultural, goods-producing and service-producing employment) and the "Wyoming Nonagricultural Wage & Salary Employment" table are quality examples of this type of analysis. The figures are seasonally adjusted historical time series comparing the major industry divisions of the United States and Wyoming through the last two recessions. By comparing the graphs of the two series, one can see that the recession from July 1981 thru November 1982 had either a negative effect or no effect on the economies of both the United States and Wyoming. However, looking at the recession ending in March 1991, all but one major industry (Manufacturing) in Wyoming produced a positive gain in employment. In contrast, at the national level all but one major industry (Services) showed a decline throughout the recession period.

If Alan Greenspan's prediction about the possible national recession is correct, based on historical trends and current growth of total nonagricultural employment, Wyoming will continue to contest the outcome of the national economy.

Gregg Detweiler is a Principal Statistican with Research & Planning, specializing in Current Employment Statistics (CES).

1 Refer to the April 1995 issue of Wyoming Labor Force Trends for a discussion of UI data in economic analysis.

2 Refer to the May 1995 issue of Wyoming Labor Force Trends for a description of wage records and their potential uses; also see "Wyoming Unemployment Insurance Wage Record Summary Statistics Update" in this issue.

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