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GSP chain-type quantity indexes (most recent) by state
 

Economy Statistics > GSP > Chain-type Quantity Indexes > Other transportation and support activities (most recent) by state


Showing latest available data.
Rank   States  Amount 
# 1   District of Columbia: 126.84  
# 2   Wyoming: 118.05  
# 3   Arkansas: 117.49  
# 4   Montana: 116.78  
# 5   Maryland: 114.2  
# 6   West Virginia: 112.87  
# 7   Maine: 112.58  
# 8   Tennessee: 110.61  
# 9   North Dakota: 109.64  
# 10   Vermont: 109.48  
# 11   New Mexico: 109.27  
# 12   Nebraska: 109.26  
# 13   Nevada: 108.65  
# 14   Idaho: 108.17  
# 15   South Dakota: 107.81  
# 16   Kansas: 107.43  
# 17   Kentucky: 106.48  
# 18   Pennsylvania: 106.33  
# 19   Louisiana: 105.89  
# 20   New Hampshire: 105.86  
# 21   Virginia: 105.57  
# 22   Connecticut: 104.71  
# 23   Rhode Island: 104.23  
# 24   Utah: 104.21  
# 25   Oregon: 103.67  
# 26   Indiana: 103.45  
# 27   California: 103.32  
# 28   Texas: 102.79  
# 29   Wisconsin: 102.58  
# 30   Alabama: 102.34  
# 31   Washington: 101.75  
# 32   Iowa: 101.45  
# 33   Mississippi: 101.21  
# 34   Florida: 101.12  
# 35   Colorado: 99.87  
# 36   Alaska: 99.83  
# 37   Minnesota: 99.78  
# 38   New Jersey: 99.3  
# 39   Arizona: 98.91  
# 40   Georgia: 98.84  
# 41   New York: 98.1  
# 42   Illinois: 97.01  
# 43   Michigan: 96.56  
# 44   North Carolina: 96.43  
# 45   Delaware: 95.96  
# 46   South Carolina: 95.69  
# 47   Hawaii: 94.73  
# 48   Oklahoma: 90.47  
# 49   Ohio: 90.38  
# 50   Massachusetts: 89.62  
# 51   Missouri: 86.21  
Weighted average: 103.8   



DEFINITION: Other transportation and support activities, Chain-type Quantity Indexes (2000 = 100) A quantity index is an index number that measures the change in the level of a quantity from a base year, apart from anychanges in relative prices. The value of the quantity index is 100 for the base year.The Bureau of Economic Analysis uses chain-type annual-weighted indexes, also known as Fisher indexes, as its measure of realoutput and prices. These measures allow for the effects of changes in relative prices and in the composition of output overtime, thereby eliminating a major source of bias inherent in fixed-weight indexes.

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