regression and forecasting models
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Part 0: Introduction0-1/17
Regression and Forecasting Models
Professor William GreeneStern School of Business
IOMS Department Department of Economics
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Regression and Forecasting Models
Part 0 - Introduction
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Professor William Greene; Economics and IOMS Departments
Office: KMEC, 7-90 (Economics Department) Office phone: 212-998-0876 Email: wgreene@stern.nyu.edu URL: http://people.stern.nyu.edu/wgreene
http://people.stern.nyu.edu/wgreene/regression/Outline.htm
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Course Objectives
Basic understanding: The regression model as a framework for the analysis of relationships among variables
Technical know how: How to formulate a regression model, estimate its parameters, and understand the implications of the estimated model.
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We used McDonald’s Per Capita
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Macs and Movies
Countries and Some of the DataCode Pop(mm) per cap # of Language Income McDonalds1 Argentina 37 12090 173 Spanish2 Chile, 15 9110 70 Spanish3 Spain 39 19180 300 Spanish4 Mexico 98 8810 270 Spanish5 Germany 82 25010 1152 German6 Austria 8 26310 159 German7 Australia 19 25370 680 English8 UK 60 23550 1152 UK
Genres (MPAA)1=Drama2=Romance3=Comedy4=Action5=Fantasy6=Adventure7=Family8=Animated9=Thriller10=Mystery11=Science Fiction12=Horror13=Crime
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Movie Genres
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Movie Madness Data (n=2198)
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Case Study Using A Regression Model: A Huge Sports Contract
Alex Rodriguez hired by the Texas Rangers for something like $25 million per year in 2000.
Costs – the salary plus and minus some fine tuning of the numbers
Benefits – more fans in the stands. How to determine if the benefits exceed the
costs? Use a regression model.
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Baseball Data (Panel Data – 31 Teams, 17 Years)
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A Regression Model
team
1
Attendance(team,this year) = α + γ Attendance(team, last year) + β Wins (team,this year) 2
3
+ β Wins(team, last year) + All_Stars(team, this year)
+ (team, this year)
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= .54914
1 = 11093.7
2 = 2201.2
3 = 14593.5
Effect of 1 more win11093.7 2201.2= 32757
1 .59414Effect of adding an All Star
14593.5= 359571 .59414
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Marginal Value of an A Rod 8 games * 32,757 fans + 1 All Star = 35957
= 298,016 new fans 298,016 new fans *
$18 per ticket $2.50 parking etc. $1.80 stuff (hats, bobble head dolls,…)
$6.67 Million per year !!!!! It’s not close.
(Marginal cost is at least $16.5M / year)
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Course Prerequisites Basic algebra. (Especially summation) Geometry (straight lines) Logs and exponents
NOTE: I (you) will use only base e (natural) logs, not base 10 (common) logs in this course.
Previous course in basic statistics – up to testing a hypothesis about a mean
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Course Materials
Notes: Distributed in first class Text: McClave, Benson, Sincich; Statistics for
Business and Economics (2nd Custom NYU edition), Pearson, 2011.
On the course website: Class slide presentations Problem sets Data sets for exercises
http://people.stern.nyu.edu/wgreene/regression/Outline.htm
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Course Software: MinitabThe Current Version: Minitab 16
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