Actual   Predicted

                     Employment Employment

                          1975   1990

Basic employment         200,000 300,000

Local service employment 400,000 6002000

                         600,000 900,000



Ratio of local service

 to basic                       2       2



 Ratio of total to basic

 (multiplier)                    3       3

 

The model is most commonly used, however, as a rule-of-thumb to estimate the effect of specific projects or policies on employment. For example, if a new industrial plant proposes to locate in a region, the impact on employment may be estimated for: (1) a direct impact from the jobs provided by the business itself; (2) an indirect impact if the business buys production materials and services locally; and (3) an induced impact or multiplier effect from the flow of wages spent by new employees, which may provide new jobs in other businesses and in turn the spending of those wages--on and on.

Example: Forecasting Employment by Using an Induced Impact Multiplier

 
Permanent jobs (provided by a

  particular industry)                   780

 Indirect impact on other basic

  employment (from industries

  supplying the above

  industry)                              125



                                          905



Induced impact multiplier                  1.7



 Total employment increase               1,539

 

Assuming that the multiplier also works in the reverse, this process may in turn be used to estimate the total unemployment caused by an industry leaving a city or cutting back employment.

Multipliers take information on employment and income for one part of the economy and use it to extrapolate estimates of employ ment and income in several parts of the economy or all of it. In trying to apply income and employment multipliers, the analyst needs to keep in mind one cardinal fact: the components of the calculations require information that is just not available and the final result is all too often based upon a host of assumptions. Therefore, though convenient to use, multipliers often rely upon poor data and faulty assumptions. When faced with the need to use a multiplier, the best practice is to trust local experience, testing it against as many examples as can be found of multipliers used in comparable jurisdictions. Next, it is always wise to consult with experts who work in this field, for they can provide sound advice and help the novice (and even the experienced) to avoid pitfalls.

Finally, the analyst must choose the components of the multiplier carefully. For example, if the project includes manufacturing and warehousing activities in a new industrial park, applying an exportderived multiplier to employment (e.g. one that includes all base industries) would count the warehouse twice because it moves goods between industries.

Many economists have written about income and employment multipliers. The following examples give empirical values of the multipliers for various regions. Frequently, these studies have computed multipliers for a variety of sectors, but only a respresentative example appears in the tables. The references cited in the tables include some of the more important articles available in the economic journals. Unfortunately, many of the papers which estimate regional multipliers are difficult to acquire because they are the working papers of economic research organizations.

In order to explain the employment multiplier, it is necessary to understand the concept of the income multiplier. The income multiplier measures the change in local income that results from a change in local production stimulated by outside, independent demand:

k_y = [Δlocal income (direct, indirect, and induced)]/ [Δindependent (direct) demand]

where, Δ stands for "change in" a quantity

The use of k as a symbol for the income multiplier may be puzzling to noneconomists. The k probably stands for the British economist John Maynard Keynes; y is often used to symbolize income because i represents other variables.

Example: Changes in Regional Income in Santa Clara County

Assume the increase in demand for electronics products $20,000,000 And the increase in regional production and income = $30,000,000

k_y = $30,000,000/$20,000,000 = 1.5

If the demand for electronics products increases by $32,000,000, then:

Increase in regional income = (1.5) x ($32,000,000) = $48,000,000

The value of k depends upon the increased demand generated per unit by each i4rease in local production. This ratio will be denoted as m (m = 1/3 in the equation below). This ratio measures the extent to which demand feeds back into the local economy. You can use m to derive the value of k_y

k_y = 1/(1-m)

Example: Computation of the Income Multiplier

For the U.S. economy, m is approximately 0.6. Therefore, the income multiplier for the U.S. is:

k_y = 1/(1-0.6) = 1/(0.4) = 2.5

The increase in demand for local production for each increase in local production, (m), can be represented as the product of four factors:

m = (Δdemand for local production)/(Δlocal production) =

(Δlocal incomes)/(Δlocal production)x(Δspending of residents)/(Δlocal income)x

(Δlocal spending of residents)/(Δspending of residents)x (Δdemand for local production)/(Δlocal spending of residents)

The following combines an example drawn from information about San Francisco with an explanation of the ratio m. The first factor measures the change in income of local households that results from a change in local production:

(Δlocal household income)/(Δlocal production

Of the employees working in San Francisco, 60.2% live in the city according to the Journey to Work Survey of the U.S. Census. There is no readily available source of statistics on the proportion of property income in San Francisco that goes to residents. The owernship of property by national corporations would tend to take property income out of San Francisco.

Purchasing power which gets diverted to residents of other regions or to state and federal government does not necessarily induce any spending in the local economy. Payments to local government, however, generally lead to spending in the local economy.

Nationwide, about two-thirds (.67) of any additional production becomes disposable income for households. The share of local income going to households in San Francisco is not very different from the national average - that is, 0.67. About one-fourth (.25) of additional income goes for taxes, while corporations retain one-twelf th (.083) as earnings. Although they are rough, the national ratios give an idea of relative magnitude.

The second factor determining m is the marginal propensity to spend:

(Δspending of residents)/(Δlocal income)

Nationally, this figure stands at 90%. The ratio for San Francisco residents also is probably not much different.

The third factor determining m is the share of spending done in the local economy:

This may involve a sum of terms because of the way income is divided between residents and nonresidents and their spending habits.

For purposes of this example, the distribution of property income between residents and nonresidents is the same as the distrubiton of jobs: 60% to residents and 40% to nonresidents. If 60% of the income from San Francisco's economy goes to San Francisco residents who do 95% of their buying in San Francisco and 40% of the income goes to non-residents who do 30% of their spending in San Francisco, the increase in spending in San Francisco would be:

(0.6)(0.95) + (0.4)(0.3) = 0.69

The final factor determining m is the change in demand for the local economy's products compared to the change in the demand for goods and services in the economy:

Consumers want various goods and services. The extent to which the local economy satisfies their wants depends on the diversity of the local economy. The precise ratio that is involved is the value added to the sales in the local economy. Value added may be created by producing goods locally or by wholesaling or retailing imported goods.

The share of local sales which is locally produced is difficult to establish. It may differ significantly for goods and services. Locally purchased services have to be locally produced. Locally purchased goods are, of course, not necessarily produced locally. According to the 1964 Census of Manufacturers, 42% of the value of sales in San Francisco derived from value added by the local manufacturing sector.

The final factor determining m is a weighted average of 100% local production figure for services and 42% local production figure for goods. The weights represent the share of services and goods in local spending. These shares are not available for San Francisco, but in 1972 f or the U.S. as a whole, 38% of consumer purchases went for services. Using this share, the final factor is:

(.38)(1.00) + (.62)(.42) = 0.64

The value of m for San Francisco based upon the four factors previously computed is:

m = (0.67) X (0.9) X (0.69) X (0.64) = 0.27

The income multiplier is:

k_y = 1/(1.0-0.27) = 1/(0.74) = 1.36

The values of m and k_y for the U.S. economy, where consumers spend virtually all of their money for U.S. goods and services, are:

m (.67) X (.9) X (1.00) X (1.00) = 0.6

k_y = 1/(1-0.6) = 1/(0.4) = 2.5

The difference between the multipliers for the U.S. and San Fran cisco economies is due solely to the dispersion of income out of the San Francisco economy and the lower share of local purchases accounted for by local production.

Economic studies often make use of the concept of the

employment multiplier k_E.

This quantity is defined as:

k_E = (ΔTotal Jobs (Direct, Indirect & Induced))/(ΔJobs Directly Generated)

The employment multipler, k_E may be derived from the income multipler, k_y , through the folrolwing relationship:

k_E = 1 + (_y-1)(a_I/a_D)(W_D/W_I)

where

• a_D = wage income generated per unit of direct local production
• a_I = wage income generated per unit of indirect local production
• W_D = wage rates in jobs related to direct local production
• W_I = wage rates in jobs related to indirect local production

The following tables give a few income and employment multipliers. Some of these come from studies that presented a variety of multipliers. These studies are listed at the end of the table. Example: Computation of Employment Multiplier from income Multiplier

Suppose a region has an income multiplier, k_y , of 1.6, the ratio of the wage shares of industries serving the local market to the industry with directly generated employment (a_Il/a_D) is 1.00 and the ratio of wage rates for direct jobs to induced jobs (W_D/W_I) is equal to 1.3.

The employment multiplier for this region will be:

k_E = 1 + (.6)(1.0)(1.3) = 1.78

Therefore, total employment from 100 new direct employment jobs would be 178, including induced employment of 78.