Class Slides CRP 566 Week 3 Firm location, regional trade evaluation - - PDF document

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Class Slides CRP 566 Week 3

Firm location, regional trade evaluation

Community Economics Slides

From Shaffer, Deller, & Marcouiller

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Market for Goods and Services Central Place Dynamics

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Central Place Dynamics Hexagonal Outocome

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Types of Firms Supported by Density of Demand

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CENTRAL PLACE THEORY

Assumes …

• Firms will seek to maximize the trade area served
• Consumers will minimize distances traveled
• Links the central place to its complementary area … how consumer

spending is distributed across space.

Range … the maximum distance consumers will travel to purchase

goods and services at some location (max trade area)

Behavioral Space … consumer perceptions of whether their

demand for a good/service has been satisfied. Includes shopping experience as well as cost of commodity.

Demand Threshold … the minimum market size needed to support

a good/service and yield a profit to the business

Dave Swenson -- Iowa State University

Determinants of Firm Location and Consumer Demand Preferences

Why do firms locate in a particular place?

• Minimize costs:
• Transport costs
• Land and labor (total costs)
• Seek economies of agglomeration
• To maximize demand area to potentially reach as many customers as possible
• To maximize profit – look both at the revenue and the cost side

Dave Swenson -- Iowa State University

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Customers

• Customers – whether households or businesses seek …
• Adequate supply of goods, inputs, or services.
• High attention paid to costs of obtaining them: if costs are too high will seek

substitutes or do without

• Time is money
• Space is tyrannical
• Gravity weighs heavily on decisions

Dave Swenson -- Iowa State University

And the intersection of firms and people?

• A very basic principle:
• People go to where they think they can find work and the goods and services

that they desire

• Firms go, after considering all of the reasons for firm location, where they

either find the workers that they need or the customers that they need

Dave Swenson -- Iowa State University

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About that Gravity Problem

• Yours and my likelihood of doing something in place A decreases the

farther away that I am. The reason is simple: the cost of the transaction goes up as I travel.

• For example,

Dave Swenson -- Iowa State University

Distance and Profit for Hauling Ag Goods

$0 $50 $100 $150 $200 $250 10 16 22 28 34 40 46 52 58 64 70 76 82 88 94 100 106 112 118 124 130 136 142 148 154 160 166 172 178 184 190 196 Total Trip Cost Round Trip Miles Fuel Operating Costs Labor

• Avg. Fixed Costs Per Mile

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Tyranny of Distance

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 5 8 11 14 17 20 23 26 29 32 35 38 41 44 47 50 53 56 59 62 65 68 71 74 77 80 83 86 89 92 95 98 P r

• b

a b i l i t y Miles to Market

Distance – Decay Function

In-commuting to Polk County

2,000 4,000 6,000 8,000 10,000 12,000 14,000 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Miles from City Center Number of Incommuters

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Percent of Labor Force Working in Polk County by Distance

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0% 10 20 30 40 50 60 70 80 Distance from City Center Percent

Percent of neighboring labor force commuting to central city

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 20 40 60 80 100 120 Miles from Des Moines Percent Commuting

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So, we get some rules

• Businesses try to maximize their trade

territories,

And

• Consumers try to minimize the distance that

they travel to obtain goods and services (and work)

Dave Swenson -- Iowa State University

But we have hierarchies

• Lowest level – personal services, retail, convenience goods
• Medium level – specialized retail and services, wholesaling,

different ranges of goods and service availability depending on size

• Highest level – Government, cultural centers, highly specialized

trade and services, finance, etc.

Dave Swenson -- Iowa State University

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Other factors

• Overall density of demand is influenced by
• Population
• Income (purchasing power)
• Economies of scale (agglomerations)
• Transport costs
• Energy costs as they affect travel and housing

Dave Swenson -- Iowa State University

Market Share Analysis

• What is our trade area?
• How are we doing?
• A trade area is the space in which trade is occurring – it can be well

circumscribed or it now can be virtual.

• Is usually a function of the degree of specialization / urbanization in

an area.

Dave Swenson -- Iowa State University

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How do we define a trade area?

• Make one up – assume a fixed territory
• Postal codes (zips) / telephone prefixes
• Newspaper circulation areas
• Surveys – spot , samples,
• License plates
• Check and credit card receipts
• Gravity models

Dave Swenson -- Iowa State University

REI LLY’ S LAW

Reilly’s Law of Retail Gravitation …

• Used to identify market boundaries in geographic space
• Measures shopping areas between two communities
• Is a simple type of Gravity Model
• Most useful for shopping goods (i.e. furniture, health care, autos)

than for convenience goods (i.e. gasoline, food)

Limitations …

• Not useful for urban neighborhoods
• Not good at comparing between wealthy and poor communities
• Not good for different sized communities
• Overestimate shopping population … no market cross-overs

Two Types …

• Reilly’s Gravitation Model
• Reilly’s Break Point Model

Dave Swenson -- Iowa State University

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REI LLY’ S LAW

Reilly’s Gravitation Model …

SAXBi = is how well market A attracts consumers from market X for good i compared to market B P

Ai = is the power of market A for good i

PBi = is the power of market B for good i DBX = is the distance between market B and point X DAX = is the distance between market A and point X P can be population, sales, employment, etc. i is some good or service (NAICS is also commodity) or total trade D can be distance in miles or travel time via road network

2

                

AX BX Bi Ai AXBi

D D P P S

Dave Swenson -- Iowa State University

REI LLY’ S LAW

Reilly’s Break Point Model …

• Adapts the Gravitational model to estimate a “breaking point” or

maximum distance from market A that a customer will travel to shop in market A rather than market B.

• Is useful in delineating the trade area for market A on a map.
• Assumes people will only shop in the market with the greatest

attraction

• Assumes people will not cross market boundaries

Dave Swenson -- Iowa State University

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REI LLY’ S LAW

Reilly’s Break Point Model …

DABi = distance consumers will travel to market A rather than market B for good i DAB = is the distance between markets A and B P

Ai = is the power (gravity) of market A for good i

PBi = is the power (gravity) of market B for good i P can be population, sales, employment, square feet, etc. i is some good or service or total trade D can be distance in miles or travel time via road network

Ai Bi AB ABi

P P D D   1

Dave Swenson -- Iowa State University Dave Swenson -- Iowa State University

Reilly's Law Miles Population All Trade (in Millions) From Storm Lake (City A) 9,706 $144.60 TO: (different City Bs) Cherokee 21.3 4,786 $63.10 Spencer 38.2 10,994 $238.80 Pocahontas 35.0 1,821 $16.40 Sac City 25.3 2,154 $20.40 I da Grove 43.6 2,081 $25.10 Sioux City 79.0 82,684 1235.3 Carroll 56.4 10,000 192

• Ft. Dodge

70.9 25,230 455.5

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Dave Swenson -- Iowa State University Reilly's Law Miles Population All Trade (in Millions) From Storm Lake 9,706 $144.60 Reilly's Law (Miles) TO: Population Trade Cherokee 21.3 4,786 $63.10 12.5 12.8 Spencer 38.2 10,994 $238.80 18.5 16.7 Pocahontas 35.0 1,821 $16.40 24.4 26.2 Sac City 25.3 2,154 $20.40 17.2 18.4 Ida Grove 43.6 2,081 $25.10 29.8 30.8 Sioux City 79.0 82,684 1235.3 20.2 20.1 Carroll 56.4 10,000 192 28.0 26.2

• Ft. Dodge

70.9 25,230 455.5 27.1 25.6

To Cherokee: 21.3/(1+(4786/9706)^(1/2)) = 12.5 and so on …

Dave Swenson -- Iowa State University

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EXAMPLE … Trade Areas

REI LLY’ S LAW

B C D E F G H A

* * * * * * *

Dave Swenson -- Iowa State University

THRESHOLD ANALYSI S

Threshold Analysis …

• Used to identify the minimum market required to support a

good/service and still yield a normal profit to the firm.

• Holds consumer preferences and buying power constant
• Assumes population drives demand (but alternatives exist – can

use income)

• Assumes firm cost structure operates independent of community …

that the market must be of a minimum size regardless of its characteristics.

• If market size for a good/service is under threshold, then market is

not large enough to cover costs and profit … firms will close, eventually, or never open.

Dave Swenson -- Iowa State University

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THRESHOLD ANALYSI S

Limitations …

• Does not account for differences in income/wealth
• Does not account for differences in HH spending patterns
• Does not account for differences in tastes
• Assumes only local population drives demand
• Choosing the proper reference area is essential!
• Local market demand can be measured using establishments per

capita, sales per capita, or employment per capita.

• Good data is needed at high level of geography and NAICS
• Best data sources …

Economic Census from US Census Bureau (estb, jobs, sales) County business patterns for employer firms Taxable sales data from your state Revenue Dept or local govt

Dave Swenson -- Iowa State University

THRESHOLD ANALYSI S

How to conduct a simple Threshold Analysis …

• Choose a representative market that best matches your local market. State

averages are often used (although we have issues with averages!)

• Choose relevant local market sectors to analyze
• Choose threshold variable … usually number of establishments per capita or sales

per capita.

• Calculate the threshold ratio by dividing the threshold variable by the population

for your representative market (ie your state).

• Calculate local demand by multiplying the threshold ratio by your local market

population.

• Find local supply, or the actual amount of local activity.
• Compare local demand and local supply to identify gaps.

Dave Swenson -- Iowa State University

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Dave Swenson -- Iowa State University

Industry Code Description Iowa Firms Demand Per 1,000 Persons Jasper County Demand Jasper County Supply Difference New Car Dealers 436 0.1453 5.32 7 1.68 Used Car Dealers 342 0.1140 4.17 1 (3.17) Recreational Vehicle Dealers 56 0.0187 0.68 1 0.32 Motorcycle, Boat, and Other Motor Vehicle Dealers 192 0.0640 2.34 3 0.66 Automotive Parts and Accessories Stores 584 0.1947 7.12 6 (1.12) Tire Dealers 281 0.0937 3.43 2 (1.43) Furniture Stores 314 0.1047 3.83 3 (0.83) Floor Covering Stores 200 0.0667 2.44 3 0.56 Other Home Furnishings Stores 184 0.0613 2.24 (2.24) Appliance, Television, and Other Electronics Stores 468 0.1560 5.71 3 (2.71) Computer and Software Stores 116 0.0387 1.41 3 1.59 Camera and Photographic Supplies Stores 14 0.0047 0.17 (0.17) Home Centers 89 0.0297 1.09 (1.09) Paint and Wallpaper Stores 95 0.0317 1.16 1 (0.16) Hardware Stores 264 0.0880 3.22 4 0.78 Other Building Material Dealers 599 0.1997 7.30 9 1.70

LOCAL MARKET ANALYSI S

Benefits of using Trade Area statistics …

• Take into account actual sales
• Benchmarked for average consumer spending, can be modified
• Takes into account income/wealth differences
• Estimates the number of people in a trade area
• Estimates the proportion of trade captured in the area
• Estimates the total dollar value of local demand
• Estimates the dollars gained from or lost to other communities
• Gives both relative and absolute trade area performance
• Can be used for specific categories of sales
• When mapped with contiguous geographies, allows one to see

trade flows between areas

Dave Swenson ‐‐ Iowa State University

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LOCAL MARKET ANALYSI S

Limitations of Trade Area statistics …

• Need to identify function economic trade areas that may

not match common political areas (i.e., cities and counties).

• Assumes consumer preferences and tastes are similar to

state averages. Although you can change the reference economy to minimizes errors, you cannot change HH preferences.

• Does not tell you where dollars actually flow. However,

you can infer this through comprehensive mapping.

• You can compile probability of shopping estimates using a

Huff’s procedure.

Dave Swenson ‐‐ Iowa State University

For Example, In Iowa I can calculate how many counties are trade self‐sufficient

Dave Swenson ‐‐ Iowa State University

0.00 0.50 1.00 1.50 2.00 1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97

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Or, I can calculate the number of shopper‐equivalents that they are either gaining or losing

Dave Swenson ‐‐ Iowa State University

‐40000 ‐20000 20000 40000 60000 80000 100000 1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97

Trade Area Calculations

• Potential sales =

Local Pop X State Per Capita Sales X Local PCI / State PCI

• Percentage of retained sales =

Actual local sales / Potential sales X 100

• Trade Area Capture (in persons) =

Actual Sales / (state sales per capita X Local PCI / State PCI)

• Pull Factor =

Trade area capture / local pop

• Surplus or Leakage =

Actual Sales – Potential Sales

Dave Swenson ‐‐ Iowa State University

9/10/2015 21 Po Potential sal sales = Loc Local Po Pop X St State Pe Per Capit Capita Sal Sales X Loc Local PCI PCI / St State PCI PCI

• This tells what our regional expected sales values would be given our

population and our income (our purchasing power).

• It indexes us to the average for the whole state.
• It give us a ready indicator of our regional sales potential.

Dave Swenson ‐‐ Iowa State University

Pe Percenta tage of

• f re

reta tained sales sales = Actual Actual loc local sales sales / Po Potential sales sales X 100 100

• Here we produce a simple percentage:
• If greater than 100 percent then we are

producing for more than our primary region

• If less than 100 percent then we are serving less

than our populations needs – leakage is

• ccurring.

Dave Swenson ‐‐ Iowa State University

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Tr Trade Ar Area Ca Capt ptur ure (in (in per persons) s) = Actu Actual al Sale Sales / (s (state sale sales per per ca capi pita X Lo Local PCI PCI / St State PCI) PCI)

• This is a very good statistic.
• It gives you an estimate of the number of shopper equivalents as persons.
• If you are serving your population or larger you are, statistically, self‐sufficient
• r exporting sales
• If you are not serving your population, then your citizens are obtaining goods

and services elsewhwere.

Dave Swenson ‐‐ Iowa State University

Pu Pull Fa Factor = Tr Trade ar area ea ca capt pture / loc local pop pop

• This is one of the most common trade area values used.
• If greater than 1.0, then you are producing export sales
• If less than 1.0 then you are leaking sales, given your population and income

levels

This ratio is the same as your Percent of Sales Retained value, just arrived at a different way

Dave Swenson ‐‐ Iowa State University

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Surp Surplus lus or

• r Leak

Leakage = Actual Actual Sales Sales – P – Potential Sales Sales

• Here you get a sales value of the surplus or the

leakage.

• If you have calculated these values by particular

type of retail or service activity, you can provide a type of threshold analysis that tells whether you might be able to support a particular type

• f industry.

Dave Swenson ‐‐ Iowa State University

Information needed

• For your State and for your Study

Area get

• Population
• Per capita income
• Total retail sales

Dave Swenson ‐‐ Iowa State University

Trade Area Calculations 2012 Iowa Jasper County Retail trade $ 34,537,967,263 319,585,190 Population 3,062,309 36,547 Per Capita Income $ 41,156 34,457

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Dave Swenson ‐‐ Iowa State University

Trade Area Calculations 2012 Iowa Jasper County Retail trade $ 34,537,967,263 319,585,190 Population 3,062,309 36,547 Per Capita Income $ 41,156 34,457 Retail Trade Per Capita $ 11,278 8,744

Dave Swenson ‐‐ Iowa State University

2012 Iowa Jasper County Retail trade $ 34,537,967,263 319,585,190 Population 3,062,309 36,547 Per Capita Income $ 41,156 34,457 Retail Trade Per Capita $ 11,278 8,744 Potential Sales $ 345,099,079 Percent of Retained Sales 92.6% Trade Area Capture (Persons) 33,845 Pull Factor 0.926 Surplus of Leakage $ (25,513,889) Trade Area Calculations