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Course Intro

Scott Matthews12-706 / 19-702 / 73-359Lecture 1 - 8/29/2005

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Objectives

Prepare you to construct, assess, and explain models to aid in public decision making

Build a framework on which you can add additional courses and knowledge

Understand issues of estimation, economics, uncertainty, coping with multiple parties and objectives in decision making.

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Scott MatthewsAsst. Prof., CEE/EPPResearch Director and Faculty

Green Design InstituteB.S. ECE/Engineering & Public Policy,

M.S. Economics, PhD. EconomicsResearch

Sustainable infrastructure and green product/system design

Make sure corporations understand all private and social costs of decisions.

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Merged Course – Economists and Engineers

Seemed to work well during the past 8 years.

Courses overlapped in content - need for practical decision making aids.

Engineers need economic perspective; economists need an engineering (practical problem solving) perspective.

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Course History

I’ve taught this course for 10 years1995: Benefit-cost analysis (73-359)1997: Merged with CEE 12-7062005: Merged with EPP 19-702

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Changes Over Time

I’ve gotten old.Some of you weren’t Born when the greatestAlbum of all time cameOut!

I got married and had2 boys.

Now I get no sleep

I have 2 great other helpers

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TAs: Joe and Paulina

Contact info on syllabus

When should office hours be?

Would an (infrequent) Friday review be helpful? When would we schedule it?

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Course Web Page

Course web page: http://www.ce.cmu.edu/~hsm/bca2005/

Lecture notes, problem sets and schedule

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Course Grade Components

5-6 Problem Sets Midterm QuizFinal ExaminationSeveral Group Projects (grad

students)Participation: Borderline cases

(I will learn all names)

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Text and Handouts

Campbell and Brown “BCA with spreadsheets” (aka Campbell)

Clemen and Reilly “Making Hard Decisions” (aka Clemen)

Lecture notes- available on web page.Application cases.Miscellaneous: articles, problems, etc.

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Graduate Course “Rules”

Students do readings in advance I supplement reading with discussion

and examplesI do not re-lecture what you’ve readClass time will be mostly spent on

applications and demosShould reconsider if not comfortable

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Cheating / etc. Guidelines

I will not tolerate itThe whole point of this class is to teach

you how to build your own models and use them

Stealing what others have done, aside from being against policy, undermines the purpose of the course

If you use external sources to help you build models, make sure you cite them

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Application Areas

Methods and techniques are general.Emphasize environmental / civil

systems investment and pricing applications as examples. Ports, roadways, transit systems. Air and water pollution Water and wastewater systems. Public, private and mixed

investment/finance decisions (e.g. Stadium construction).

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Planning Process versus Analysis

Benefit-Cost Analysis and Design support planning processes, often performed by consultants or staff.

Planning processes tend to involve many different parties (current terminology - “stakeholders”), all with their own agendas.

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Example Planning Process: New Plant

Initiated by Owner or DeveloperProjected benefits/costs reviewed by

financiers.Local government and public often

involved in planning for land acquisition.Local government, utilities, regulatory

agencies and public participate in permitting process.

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The Policy WorldNormative vs. Positive theoriesN - based on ‘norms’ - ‘should be done’P - based on ‘reality’ - ‘actually done’This reinforces the idea of perspective

See Guardian vs. Spender mentality in chapter

Guardians bottom-line oriented, see only tolls Tend to underestimate costs

Spenders see everything (inc. costs) as benefits Tend to overestimate benefits

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Preview: Estimation

The first concept we will go over (Wednesday) is on structured estimation problems.

How do we construct an estimate for a number when we do not know the answer?

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Estimation in the Course

We will encounter estimation problems in sections on demand, cost and risks.

We will encounter estimation problems in several case studies.

Projects will likely have estimation problems.

Need to make quick, “back-of-the-envelope” estimates in many cases. Don’t be afraid to do so!

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Problem of Unknown Numbers

If we need a piece of data, we can: Look it up in a reference source Collect number through survey/investigation Guess it ourselves Get experts to help you guess it

Often only ‘ballpark’, ‘back of the envelope’ or ‘order of magnitude needed Situations when actual number is unavailable or where

rough estimates are good enough E.g. 100s, 1000s, … (102, 103, etc.)

Source: Mosteller handout

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Notes on Estimation

Move from abstract to concrete, identifying assumptions

Draw from experience and basic data sources Use statistical techniques/surveys if needed Be creative, BUT Be logical and able to justify Find answer, then learn from it. Apply a reasonableness test ** very important

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How Many TV Sets in the US?

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How many TV sets in the US?

Can this be calculated? Estimation approach #1:

Survey/similarity How many TV sets owned by class? Scale up by number of people in the

US Should we consider the class a

representative sample? Why not?

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TV Sets in US – another way

Estimation approach # 2 (segmenting): Work from # households and # TV’s per

household - may survey for one input Assume x households in US Assume z segments of ownership (i.e.

what % owns 0, owns 1, etc) Then estimated number of television

sets in US = x*(4z5+3z4+2z3+1z2+0z1)

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TV Sets in US – sample

Estimation approach # 2 (segmenting): work from # households and # tvs per

household - may survey for one input Assume 50,000,000 households in US Assume 19% have 4, 30% have 3, 35%

2, 15% 1, 1% 0 television sets Then

50,000,000*(4*.19+3*.3+2*.35+.15) = 125.5 M television sets

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TV Sets in US – still another way

Estimation approach #3 – published data

Source: Statistical Abstract of US Gives many basic statistics such as

population, areas, etc. Done by accountants/economists - hard

to find ‘mass of construction materials’ or ‘tons of lead production’.

How close are we?

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