Economic Trends and Forecast Data compiled, analyzed and presented by: Ryan Demien Tyler Jensen Sally Smith Presented 26 April 2006 Sustainable Air Quality.

Economic Trends and Forecast

Data compiled, analyzed and presented by:Ryan DemienTyler JensenSally Smith

Presented 26 April 2006Sustainable Air QualityWashington University

Professor R. Husar

Economy Trend Data &Relevance to Sulfur Emissions

• Sulfur emissions are harmful to humans, animals and the environment

• By analyzing economy sectors and their trends sulfur emissions may be reduced

• The economy may be broken up into three main sectors relating to sulfur emissions:

1. Residential / Commercial 2. Industrial 3. Transportation

• Each of the above sectors may be described by sub-sectors

More information can be found on the website of the Bureau of Economic Analysis or, specifically, in the tables for National Income Without Capital Consumption Adjustment by Industry.

Data Sources

• The economic data for each individual sector allows for the calculation of energy and pollution efficiencies per sector.

• The three subsectors are adjusted to account for inflation.

Spending within relative sectors provides an indicator of:

1. Amounts of energy being consumed

2. Where emissions originate

Residential / Commercial Subsector

Res / Com sectors are combined as they share many subsectors that make their connection to the economy and sulfur emissions similar.

This sector includes:

1. Public Utilities2. Wholesale Trade3. Retail trade and automobile services4. Finance, insurance and real estate5. Government6. Services

Industrial Subsector

This sector includes:

1. Agriculture, forestry and fisheries2. Mining3. Contract construction4. Manufacturing (including durable goods

and nondurable goods)5. Public utilities (including electric, gas and

sanitary services)6. Government

This sector involves the production of goods or services summarized under subsectors within private sectors.

Transportation Subsector

This sector includes:

1. Means for transportation such as airports and runways, pipelines, railways, waterways, port, terminals

2. Vehicles such as cars, motorcycles and buses

3. Government4. Services

The transportation sector involves the movement of physical information, people and products.

Trend Data

A brief overview of the distribution within various economic sectors is represented by the following charts.

Each gives a specific representation of economic data collected from 1929 - 2004.

National Income by Sector

Relative Income by Sector

National Income per Capita by Sector

Res / Com Income by Sector

Industrial per Capita Income

Transportation Income by Sector

Economy Trend Data Analysis

The following graphs depict trend analysis performed for 2005 - 2050 based off of economic data provided by the BEA for 1929 - 2004.

Multiple forecasts were made using a number of different methodologies which will be explained with each graph.

National Income by Sector

Res / Com per Capita Income

Wholesale TradeWholesale Trade Income per Capita

1.0

10.0

100.0

1000.0

10000.0

100000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er

Ca

pit

a

Wholesale Trade Exp. Growth Forecast Projected (Recent)

Retail TradeRetail Trade & Auto Services Income per Capita

1.0

10.0

100.0

1000.0

10000.0

100000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er C

apit

a

Retail Trade & Auto Services Exp. Growth Forecast

Projected (Recent)

Finance, Insurance and Real Estate

FInance, Insurance and Real Estate Income per Capita

1.010.0

100.01000.0

10000.0100000.0

1000000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er

Ca

pit

a

Finance, Insurance and Real EstateExp. Growth ForecastProjected (Recent)

ServicesServices Income per Capita

1.0

10.0

100.0

1000.0

10000.0

100000.0

1000000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er

Ca

pit

a

Services Exp. Growth Forecast

CommunicationsCommunications Income per Capita

1.0

10.0

100.0

1000.0

10000.0

100000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er

Ca

pit

a

Communications Exp. Growth Forecast

Government (RC)Government (RC) Income per Capita

1.0

10.0

100.0

1000.0

10000.0

100000.0

1000000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er

Ca

pit

a

Government (RC) Exp. Growth Forecast Projected (Recent)

Industrial per Capita Income

MiningMining

1.0

10.0

100.0

1000.0

10000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ P

er

Ca

pit

a

Mining Projected Projected (Recent)

ConstructionConstruction

1.0

10.0

100.0

1000.0

10000.0

100000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ P

er

Ca

pit

a

Contract construction Projected Projected (Recent)

Agriculture, Forestry and Fisheries

Agriculture, Forestry, and Fisheries

1.0

10.0

100.0

1000.0

10000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ P

er

Ca

pit

a

Agriculture, forestry, and fisheries

Projected

Projected (Linearly)

ManufacturingManufacturing

1.0

10.0

100.0

1000.0

10000.0

100000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er

Ca

pit

a

Manufacturing Projectedl Projected (Recent)

Electric, Gas and Sanitary Services

Electric, gas, and sanitary services

1.0

10.0

100.0

1000.0

10000.0

100000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er

Ca

pit

a

Electric, gas, and sanitary servicesProjectedProjected Recent

Government (IN)Governement (IN)

1.0

10.0

100.0

1000.0

10000.0

100000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er

Ca

pit

a

Gov't (IN) Projected Projected (Recent)

Transportation per Capita Income

TransportationTransportation

1.0

10.0

100.0

1000.0

10000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er C

apit

a

Transportation TR Projected

Government (TR)Government

1.0

10.0

100.0

1000.0

10000.0

1920 1940 1960 1980 2000 2020 2040 2060

Year

$ p

er C

apit

a

Gov't (TR) TR Projected Projected (Recent)

Future Work

• Extend analysis – look into projection techniques

• Elaborate on BEA data –used per capita approach, but perhaps there are other approaches

• Causalities – look into why the data resulted the way it did

• Further understand sulfur emissions and its connection to the economy and its connection to energy and emissions

Thank you!

Questions or comments?

Contact information:Ryan Demien | [email protected] Jensen | [email protected] Smith | [email protected]