APPENDIX: Methodology for States
Calculating Direct Loss
Total Wages and Salaries by Industry
Total wages by 2 digit SIC industry is calculated using the Bureau of Labor
Statistics’ (BLS) Covered Employment and Wages
program, commonly called the ES202 program. The ES202 program is a cooperative endeavor of
the BLS and the
employment security agencies of the 50 states, and other US territories. Data in the ES202
program arise from information on
employment and wages on covered workers by the State unemployment insurance (UI) laws and
for civilian workers covered
by the program of Unemployment Compensation for Federal Employees (UCFE).
Total wages include gross wages and salaries, bonuses, stock options, tips and other
gratuities, and the value of meals and
lodgings. In some states, employer contributions to certain deferred compensation plans,
such as 401k plans are included. Total
wages do not include employer contributions to Old Age, Survivors, and Disability
Insurance (OASDI); health insurance,
unemployment insurance; workers’ compensation; and private pension and welfare funds.
Wages and Salaries for Employees Paid by the Hour
In the event of a temporary shut down of the majority of industry, the loss of employee
income would be limited to workers
paid by the hour. Salaried workers would still collect their annual wage, and the work
would be made up at a later date.
Unfortunately, payroll data in the ES202 survey is not disaggregated into salaried and
hourly employees. This disaggregation,
however, is an essential part of measuring the impact of a shut down. The salaried to
hourly worker ratio varies considerably
from industry to industry, making the composition of each state’s economy a critical
element in measuring the impact of a
shutdown.
The Canadian industrial structure closely resembles economic activity in the US.
Statistics Canada, the country’s principal
government data collection and compilation agency, gathers detailed information on all
economic activity in Canada. Included in
the data are extensive statistics on average weekly earnings for total employees and those
paid by the hour. The data is
available at the Canadian 2 digit SIC level. The Canadian ratio of wages of employees paid
by the hour to wages and salaries
of total employees was used by DRI to apportion 2 digit US SIC industry level total wages
data by state into salaried and
hourly pay income.
WHEi = WTEi * WHE@CANi
WTE@CANi
Where;
WHEi = Wages of Hourly Employees in industry i
WTEi = Wages and Salaries of Total Employees in industry i
@CAN = postscript indicating Canadian statistics
This calculation provided total wages of employees paid by the hour, by industry, by
state.
Accounting for Seasonal Variation – All statistics used in
these calculations were taken from raw (non-seasonally adjusted)
data. Furthermore, Statistics Canada information is available at a monthly frequency, and
the ratios calculated above were
based on data from October to March. The ES202 program data is available at a quarterly
frequency, and the calculations
above were made using fourth quarter data and the first quarter of the following year.
This methodology ensured a measure of
total wages for hourly employees for the winter months only.
Income Per Day
To assess the possible income loss associated with a total shutdown, it is essential to
produce a measure of total wages per day
of employees paid by the hour. The total wages for hourly employees were converted into an
average daily figure by dividing
the data for October through March by 181 (total number of days).
WHEDi = WHEi
181
Where;
WHEDi = Wages per Day of Hourly Employees in industry i
Essential Services
In the event of a shutdown, it is not reasonable to assume that all essential services
will be closed. To account for the operation
of essential services under a skeleton staff, DRI constructed scaling factors. The
following service industries were classified as
essential services:
SIC Major Group 41: Local and interurban
passenger transit
SIC Major Group 44: Water transportation
SIC Major Group 48: Communication
SIC Major Group 80: Health services
It was assumed that 25 percent of the staff in these industries would be working.
Income Lost Per Day During Shut Down
To calculate the income lost on a per day basis the total wages of hourly employees by
industry was aggregated across all
industries, except essential services. Total wages of hourly employees for essential
services was scaled down using the scaling
factors, and then the aggregate of scaled essential services income was added to the other
industry total.
TWHE = WHEDne +
WHEDe * FACTORe
Where;
TWHE = Total Lost Wages per Day of Hourly Employees
WHEDne = Wages per Day of Hourly Employees in nonessential industries
WHEDe = Wages per Day of Hourly Employees in essential industries
FACTORe = Scaling factor to account for skeleton staff in essential industries
Income Regained
Although hourly employees will lose income during the days in which the area is shutdown,
a portion of this income will be
regained from overtime. Income not regained will be lost due to a permanent decline in
demand and/or production being shifted
to outside the region. Income is not assumed to be regained uniformly across the economy,
but to vary depending on each
industry. Regain factors were constructed for each industry to account for income made-up
due to overtime. In addition, it was
assumed that a portion of this overtime work was paid at time and a half.
Net Income Loss
Although a significant amount of wages would be lost during the shutdown, a sizable
portion will be made-up due to overtime
work, some of which is paid at time and a half. To calculate the Net Income Loss to the
State from the shutdown, DRI took
the income lost during the shutdown and added any income regained after the state returned
to normal.
NETWHED =
TWHE + TWHER
Where;
NETWHED = Net Lost Wages per Day of Hourly Employees
Lost Tax Revenue
DRI’s Regional Information Service uses a system of quarterly models to forecast
approximately 100 concepts for nine regions,
all 50 states, and the District of Columbia. The principal indicator of sectoral economic
activity is employment, which is
forecasted for 20 manufacturing and 8 nonmanufacturing industries. Employment, wage rates
and major components of
personal income are modeled, as well as homebuilding activity, population, labor force and
unemployment rates. Taxes are
calculated using a quarterly time series on personal income to government revenue
coefficients established by DRI’s regional
economists, and exogenous to the regional model.
Loss of tax revenue due to a statewide shut down was calculated using the net income loss
and the state government revenue
coefficients for the fourth and first quarters.
Retail Trade
The shutdown will impact the retail trade sector in two forms. The initial impact will
come through the loss of demand on the
days of the shutdown. Whether or not this lost trade is recouped by purchases made after
the state returns to normal operations
will depend on the nature of the retail trade. Retail trade involving the purchase of
immediately consumable items, such as
restaurant and confectionery items will probably be lost permanently. Although the
purchase of more durable items will be
postponed until after the state has returned to normal operations, these purchases will be
made nonetheless.
To determine the amount of retail trade that would be permanently lost by the shutdown
required data on the components of
retail activity by state. The US Department of Commerce, Bureau of the Census currently
collects monthly retail trade data by
state in its Current Business Report, but this information is limited in its detail. In
earlier years, the Department of Commerce
collected detailed information on state retail trade activity. This information was
unpublished, but included estimates for sales by
retail stores by kind of business. Although this service is now discontinued, information
from earlier years reflects general
purchasing patterns by state.
In calculating lost retail trade data, DRI used the retail trade by kind of business from
1990 to 1995 for the months
November-to-March to construct shares of retail trade attributable to each kind of
business. These shares of retail trade were
then applied to current retail trade statistics to provide an estimate of current retail
trade by kind of business.
Three retail trade sectors were identified as subject to permanent loss of trade due to
state shutdown: general merchandise
stores, eating and drinking places, and gasoline service stations. Scaling factors for
these three retail trade businesses were
established to account for the share of lost trade not recouped after the state returned
to normal operations.
Lost Retail Trade i =
Retail Trade Per Day i
* Scaling Factor i
Where i represents the kind of business.
Calculating Derived Impacts
The loss of income to the state from wages forfeited due to the shutdown has a ripple
effect in the economy. All of the people
who lost income as a result of the shutdown would have spent the majority of that income
in the local economy. Lost sales in
the local economy will amount to a potential loss of income by most retailers and their
employees. The impact ripples further as
retailers and employees curtail their purchasing activity.
To measure this ripple effect, DRI employed its Macroeconomic Model of the US Economy. The
DRI Model incorporates the
best insights of many theoretical approaches to the business cycle: Keynesian,
neoclassical, monetarist, supply-side, and
rational expectations. In addition, the DRI Model embodies the major properties of the
long-term growth models presented by
James Tobin, Robert Solow, Edmund Phelps, and others.
Multipliers were obtained for changes of income on retail trade and income by running an
impact analysis through DRI’s
Model. These multipliers were then applied to the State direct impacts to calculate
indirect impacts on consumption and general
retail trade.
Indirect tax effects were calculated using the indirect income measures and the tax
revenue coefficients from DRI’s state
models.
Other Economic Effect
DRI recognizes that there are additional effects of dangers associated with untreated
snow-covered roads. Such factors as
health, insurance and repair expenses from increased accidents were beyond the scope of
this report.
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