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Government 90dnMapping the Census
Lecture 8: Spatial Analysis; Economic Data in
the Census
Sumeeta [email protected]
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Spatial AnalysisQueryMeasurementsTransformationDescriptive SummaryOptimizationHypothesis Testing
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Attribute Queries with Crashes
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Attribute Queries with Crashes
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Location Queries with Crashes
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Location Queries with Crashes (and
fatalities)
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Queries with Crashes (and fatalities)
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Crash StatisticsNear high speed roads
Total non-fatality incidents 60 (1 fatal)Average non-fatality incidents: 0.47
On all roadsTotal non-fatality incidents 711 (4 fatal)Average non-fatality incidents: 0.27
On low speed roadsTotal non-fatality incidents 651 (3 fatal)Average non-fatality incidents: 0.26
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Measurement
Distance and lengthShape
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1991 and 2001 Congressional
District Boundaries (San Diego, CA)
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TransformationsBuffersOverlay
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Buffers (Discrete vs Continuous)
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Dissolve Example
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IntersectUse Intersect when you want to overlay a
layer with the polygons in another layer toget only the overlap
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IntersectFlood zones that intersect parking
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Intersect Result
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Descriptive Summaries: Centroids
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Hypotheses Testing
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Moran
Coefficient(from Rick Glazier andPeter Gozdyra, University
of Toronto )
Strong negativeautocorrelationRandomdistribution of values
Strong positiveautocorrelationGeary Ratio
Strong positiveautocorrelation
Randomdistribution of
values
Strong negativeautocorrelation
MoranCoefficient
2.01.00.0-1.0Statistic\Value
Strong negativeautocorrelationRandomdistribution of values
Strong positiveautocorrelationGeary Ratio
Strong positiveautocorrelation
Randomdistribution of
values
Strong negativeautocorrelation
MoranCoefficient
2.01.00.0-1.0Statistic\Value
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Moran?
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Hypotheses testing with Crashes
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Moran of Crashes in CambridgeMoran's Index = -0.131211
Expected Index = -0.001319
Variance = 0.115055
Z Score = -0.382937
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Local Moran of Crashes
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MAUP(Modifiable Areal Unit Problem)
Ecological Fallacy, Robinson, 19501930 census county data, r=.7731930 census individual data, r=.203
(correlation between being black and being illiterate)Iowa Study, Openshawand Taylor, 1979
99 counties in Iowa, r=.35
Regroup into 48 regions many times, -.55 < r < .89Regroup into 12 regions many times, -.94 < r < .99(correlation between % 65+ and % registered
Republican)
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MAUP example
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Economic CensusConducted every five years, in years ending in
2 and 7Data from the 2002 Economic Census are
currently being released
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Economic CensusIndustry Series
Not useful to mapSubject series
SpecializedGeography series
Place and ZIP code levels
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The Base Multiplier Base Multiplier can be expressed as a ratio:
BM = Total EmploymentBasic Employment
Using this approach, analysts can project impactsupon the total economy from expected changes tothe basic sector
Assumed that the ratio of total local employmentactivity to basic employment (the BM) does not varyover time.
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Four steps in EB Analysis1. Area to be Studied (Geography)
2. Unit of Analysis (Measure of theEconomy)
3. Data to be Used (Source for Input Data)4. Technique to be Used (AnalyticalMethods)
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1. Choosing a Study AreaCounty: The most commonly used study area because of excellent data availability
MSA: Best unit for urban analysis; Built on counties, soexcellent data availability as well
Economic Region: A shopping area or media area is useful,but poor data availability makes this a rarely used analysis
area
State: A study area that is too aggregated and likely to
undercount basic sector activity
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2. Selecting the Unit of AnalysisEmployment: The number of jobs by industry
Payroll: Annual payroll for firms by industrySales : Dollar sales by industryValue Added: Like sales, but eliminates
double-counting by subtracting a firmspurchases from their sales
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3. Selecting the Data SetCounty Business Patterns:Pros: Available annually; includes employment, payroll,
salesCons: Derived from a combination of sources; Does notinclude Government employment
Economic CensusPros: Contains employment, payroll, salesCons: Collected only every five years but not available untilseveral years later
ES202 DataPros: Available annually and by quarter; Includesemployment and payrollCons: Not always available for all areas
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4. Economic Base Analysis TechniquesDirect Method: The simplest and moststraightforward, this approach assumes that certainindustries are Basic or Non-basicLocation Quotients: Related to the concentrationconcept, this technique determines the local share of an industry
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The Direct ApproachAssigns activities to the Basic and Non-basic sectorson the basis of assumed sales patterns for differenttypes of industries.Sectors typically assigned to the Basic sector:Manufacturing, State/Federal Government,Agriculture, Forestry, Fishing, Hotels/Lodging,Mining.Sectors typically assigned to the Non-Basic sector:Retail Trade, Local Government, Wholesale Trade,Services, Transportation, Commercial, Utility,Construction.
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The Location Quotient TechniqueLocation quotients compare the local share of a given industryto the share of that industry for a larger area
The formula: LQi = eit/eTtEit/ETt
where: e it = Local employment in sector i at time t
eTt
= Total local employment at time tEit = National employment in sector i at time tEtt = Total national employment at time t
Three values are possible:1) Industries with LQs = 1 ( Self-Sufficiency)2) Industries with LQs < 1 ( Net Importer )3) Industries with LQs > 1 ( Net Exporter )
CalculatingaLocationQuotient
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Calculating a Location Quotientfor Massachusetts Medical related employment
MA's employment in Medical related 404,200MA's total employment 3,323,200US employment in Medical related 6,779,990
US total employment 137,632,000
MA share of employment 404,200 12%
in Medical related 3,323,200
US share of employment 6,779,990 5%in Medical related 137,632,000
MA concentration 12%US concentration 5%
Location quotient 2.40
CalculatingaLocationQuotient
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Calculating a Location Quotientfor Massachusetts Manufacturing Industry
MA's employment in Manufacturing 407900MA's total employment 3,323,200US employment in Manufacturing 17263000
US total employment 137,632,000
MA share of employment 407900 12%
in Manufacturing 3,323,200
US share of employment 17,263,000 13%
in Manufacturing 137,632,000
MA concentration 12%US concentration 13%
Location quotient 0.98
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BLS Location Quotients
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County Business Patterns
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Query to get only County datafor Massachusetts
Query to get only datafor Massachusettswherestate and county dataare available
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Query to get only Middlesex County (17) data for Massachusetts(25) for codes 621-623 Health care services
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Group by counties
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Group by States
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Location Quotients
Middlesex and Suffolk countys share in healthNAIC 621-623 related employment versus stateshare in health related or state overallemployment
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L i Q i b C i MA
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Location Quotients by County in MA(compared to employment in health only)
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