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Correlations > Industry Statistics > Paper manufacturing > Value added

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Showing latest available data.

Correlations between Industry > Paper manufacturing > Value added ...

Variable Strength
...and  Industry > Paper manufacturing > Total value of shipments 98% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Paper manufacturing 95% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Paper manufacturing 95% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Total cost of materials 95% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Paper manufacturing 86% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Total capital expenditures 82% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Annual payroll 77% [plot | correlate | graph]
...and  Labor > Paper manufacturing > Production workers hours 76% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Paper manufacturing 73% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Electrical equipment and appliance manufacturing 70% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Electrical equipment and appliance manufacturing 63% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Electrical equipment and appliance manufacturing 63% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total value of shipments 59% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total cost of materials 58% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Production workers wages 55% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Value added 53% [plot | correlate | graph]
...and  Labor > Paper manufacturing > Number of employees 51% [plot | correlate | graph]
...and  Labor > Paper manufacturing > Production workers (average per year) 50% [plot | correlate | graph]
...and  Labor > Wood product manufacturing > Production workers (average per year) 50% [plot | correlate | graph]
...and  Labor > Wood product manufacturing > Number of employees 50% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Production workers wages 49% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Annual payroll 47% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total capital expenditures 47% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Electrical equipment and appliance manufacturing 46% [plot | correlate | graph]
...and  Industry > Food manufacturing > Annual payroll 46% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Wood product manufacturing 45% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Wood product manufacturing 45% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Wood product manufacturing 45% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Plastics and rubber products manufacturing 45% [plot | correlate | graph]
...and  Labor > Wood product manufacturing > Production workers hours 44% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Value added 44% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Food product manufacturing 43% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Plastics and rubber products manufacturing 43% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Plastics and rubber products manufacturing 43% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Number of employees 42% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Annual payroll 42% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Nonmetallic mineral product manufacturing 41% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Number of employees 41% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total cost of materials 41% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Production workers wages 41% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers hours 40% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Plastics and rubber products manufacturing 39% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Wood product manufacturing 39% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Total value of shipments 38% [plot | correlate | graph]
...and  Labor > Printing & related support activities > Production workers (average per year) 38% [plot | correlate | graph]
...and  Industry > Food manufacturing > Production workers wages 38% [plot | correlate | graph]
...and  Labor > Printing & related support activities > Number of employees 38% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total cost of materials 38% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Total capital expenditures 38% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Production workers wages 38% [plot | correlate | graph]
Average: 53%

About Correlations:

A correlation is a statistical measure of similarity between at least two given sets of data. StateMaster's correlations compare two variables from our database and reveal statistical relationships between them. The percentages you see represent the strength (or likelihood) that a change in the topic variable is matched by a change in the listed variables below it. But remember: These correlations do not imply causation, that is, one does not necessarily cause the other. Also, not all variables contain all states, rather subsets of states matched together.

VIEW FOR THIS VARIABLE:

NOTES:

  • Outliers have been removed only where they are outside 3 standard deviations of the mean.
  • Only variable pairs where at least 15 states match for each have been considered.
  • Strength is given by the correlation coefficient (R squared). It is the fraction of variation in Y that can be attributed to the variation in X. 100% signifies a perfect fit (R squared of 1). The top 50 such stats are displayed


DEFINITION: This measure of manufacturing activity is derived by subtracting the cost of materials, supplies, containers, fuel, purchased electricity, and contract work from the value of shipments (products manufactured plus receipts for services rendered). The result of this calculation is adjusted by the addition of value added by merchandising operations (i.e., the difference between the sales value and the cost of merchandise sold without further manufacture, processing, or assembly) plus the net change in finished goods and work-in-process between the beginning- and end-of-year inventories.

SOURCE: Annual Survey of Manufactures, 2004

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