Minimum Requirements Approach Background

1. Minimum Requirements Approach Background • The Minimum Requirements Approach utilizes a comparison of the local economy with other similar economies to calculate the amount of Basic Employment in the local economy (and by extension the Base Multiplier). • The underlying rationale behind this technique is that the minimum level of employment in an industrial sector that is necessary to meet local demand can be identified by looking at comparable economies. • This approach assumes that local production in the “minimum shares” region is just sufficient to satisfy local demand in areas of that size. (the same as a LQ = 1) • Every other region then has a larger employment share (by definition) and is assumed to export their excess production. Therefore, anything above this “minimum share” is deemed export-based (Basic) employment.

2. Minimum Requirements Approach Basics There are two different ways to apply this approach: 1. The Pure Minimum Requirements Approach Sample other regions of the same size as the study region.Then select region with smallest share of sectoral employment for each sector, use that share as the minimum requirement. 2. Surrogate Minimum Requirements Approach Use surrogate estimators for the "minimum requirements" for each industrial sector as derived from Moore and Jacobsen. 1) First Min Shares (Aggregate and Disaggregate) 2) Second Min Shares (Aggregate and Disaggregate) 3) Productivity Adjustment

3. Pure Minimum Requirements Approach The Procedure1) A set of comparison areas are identified using a single criteria or set of criteria. (often total population)2) The share of the total economy is calculated for each industry.3) The “minimum share” is identified for each industry.4) Using a variation of the LQ formula, the minimum share is used to calculate the amount of Basic employment in each industry. Major Advantage--Compares economy to other similar economies (not the nation) Major Disadvantage--High data requirements and lots of calculations The LQ FormulaB = [(eit/ Eit) - (eTt/ETt)] * Eit The Minimum Shares FormulaB = [(eit/ eTt) - (eimt/emt)] * eTt

4. Surrogate Minimum Requirements Approach • Moore and Jacobsen (1980) gathered historical data for all US counties, MSAs, and a random sample of cities. They ran a regression of median population for each size class against the minimum employment for each industrial sector. • The result is a set of “estimation parameters” (ai and bi coefficients) that can be used for any area, given the population of that area. These can be used as surrogate estimators for the “minimum requirements” for each industrial sector. (See page 150-155, in Klosterman) • These estimation parameters are used in the following equation: sit = ai + bi * log(Popt) where Popt is the population of the area in time t • The calculated si is the minimum employment share (expressed as a percentage) for an area of a given size. • To calculate the amount of Basic Employment in a sector: B = [(eit/ eTt) - (sit/100)] * eTt

6. Surrogate Minimum Requirements Example • For example, Chapin County has a total workforce of 43,340, and an estimated 2000 population of 81,500. • The County has 1,700 jobs in Food Products (SIC 20, NAICS 311), representing 3.923% of the employment in the economy. • Using our the equation: sit = ai + bi * log(Popt) sit = -4.48547 + 1.30744 * log(81,500) sit = -4.48547 + 1.30744 * 4.9116 sit = 1.936 (or 1.936% is estimated as the “minimum share” for Food Products for an area with a population of 81,500 people) • To calculate the amount of Basic Employment in a sector: Basic Emp = [(eit/ eTt) - (sit/100)] * eTtBasic Emp = [(1,700/43,340) - (1.936/100)] * 43,340 Basic Emp = [(.03923)- (.01936)] * 43,340 Basic Emp = 1,133 so Non-Basic = (1,700 - 1,133) = 567

7. Disaggregate Aggregate

8. Disaggregate Aggregate

9. Using Aggregate Minimum Shares • Using the aggregate estimation parameters is very simple: County Total Population: 81,500 County Total Emp: 43,340 Aggregate parameters: a = -30.40331 b = 15.58022 • Basic Employment is estimated as: sit = ai + bi * log(Popt) sit = -30.40331 + 15.58022 * log(81,500) sit = -30.40331 + 15.58022 * 4.9116 sit = 46.114 (or 46.114% of total employment is Non-Basic) • To calculate the amount of Basic Employment in a sector: Basic Emp = [1 - (sit/100)] * eTtBasic Emp = [1 – (46.114/100)] * 43,340 Basic Emp = (.53886) * 43,340 Basic Emp = 23,354 so Non-Basic = (43,340 – 23,354) = 19,986

10. Evaluating the Min Reqs Approach • The Minimum Requirements approach is largely not in use anymore as approaches either less data intensive and easier to implement (Location Quotient) or more data intensive and more complex (Input-Output models) have come to dominate economic base analysis. • However, this approach does illustrate some fundamental lessons for planning analysis: • Planners can and should utilize comparisons between roughly similar units to gain a better understanding of local conditions. The MR approach is useful because it allows the planner to identify and interpret differences between local conditions and other similar geographic units. • The general approach of examining a locality, comparing it to a larger pattern area (state/nation), and then comparing it to similar units, is the basis for much of what is a basic level of analysis in planning.

11. Selecting Appropriate Basic Sector Estimates • Generally speaking, Base Multipliers usually range between 1.0 and 2.0, although they can be between 2.0 and 3.0 for small areas or areas with high resource-based employment. Theoretical Evaluation “Each has its own serious conceptual flaws.” Assumption Approach: Easily eliminated for all but selected sectors LQ Approach: A three-digit NAICS, fully adjusted LQ is considered a good upper bound for a Base Multiplier. Minimum Requirements: Productivity adjusted are better. Disaggregate and Aggregate are equally sound, as are the First and Second Shares. Empirical Evaluation --The best technique: A Complete Local Economic Census (G & W)--The 2nd best: The Minimum Requirements Approach (G & W)--LQ’s generally underestimate basic employment, even at very detailed employment levels (four digit SIC level/five digit NAICS level) .--However, the LQ technique is considered to be the most useful at the county level where we have good data.--Be sure to review pages 160-166 in Klosterman and the G & W article.** **Gibson and Worden (1981). "Estimating the Economic Base Multiplier: A Test of Alternative Procedures," Economic Geography 57, pp. 146-159.