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International Maritime Statistics Forum Annual Conference Gdansk, Poland April 2008.

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Presentation on theme: "International Maritime Statistics Forum Annual Conference Gdansk, Poland April 2008."— Presentation transcript:

1 International Maritime Statistics Forum Annual Conference Gdansk, Poland April 2008

2 Uses/Misuses of Marine Transportation Statistics Introduction (Types of Data) Elastic Expectations (Forecasting) Market by Inference (Forecasting) Supply/Demand Matching Hybrid Approach

3 Types of Data Primary Data: Focused actionable data collected for a specific purpose, usually collected through focus groups, customer surveys/feedback surveys…... Secondary Data: Data that was originally collected for another purpose, usually collected on forms, such as vessel manifests, customs documents, Securities and Exchange filings, vessel registrations.

4 Elastic Expectations Up-turns will continue; down-turns are temporary! Market by Inference Project will succeed because things (GDP, Trade) are growing, but even if things aren’t growing, the project will steal market from others? Project is good from others? Project is good no matter what happens! no matter what happens! Supply/Demand Matching Trade (demand) is growing so we need more transportation assets (supply). Or, transportation assets are wearing out. In either are wearing out. In either case, more assets are required! case, more assets are required! Analytical Sins – Secondary Data (pro-investment bias)

5 Elastic Expectations/Market by Inference and Forecasting In the 1970’s, Data Resources Inc. provided analysts with tools for do-it-yourself forecasts. In the 1970’s, Data Resources Inc. provided analysts with tools for do-it-yourself forecasts. U.S. Domestic Trade = 453.455 + 0.119 x (real GDP) U.S. Domestic Trade = 453.455 + 0.119 x (real GDP) (16.865) (13.653) (16.865) (13.653) Interval: 1950-1975 Interval: 1950-1975 R 2 = 0.886 R 2 = 0.886 Elasticity (% change trade/% change trade) = 0.45 Elasticity (% change trade/% change trade) = 0.45

6 The Forecast

7 The Result

8 Typical Forecasts Fang & Cone

9 Conclusion, Hybrid Approach Secondary Data Analysis Primary Data Collection and Analysis Long Term Customer Commitments Investment Decision

10 Bottom Line Start with secondary data, finish with primary data.

11 QUESTIONS? Russell Byington Chief Economist Maritime Administration U.S. Department of Transportation 202 366 2278 russ.byington@dot.gov Web Site: www.marad.dot.gov/marad_statistics Contact Me


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