Steve Lawford

 

IENAC20 (PREV) Forecasting

 

LATEST ANNOUNCEMENTS

  • (4 Apr) Welcome to the course, and good luck!

 

Course and content

Contact details and office hours: It is best to contact me by email with questions - since I receive a great deal of spam mail, please mark messages with "IENAC20" and / or "Forecasting", somewhere in the subject line, or send the emails from an enac.fr address, otherwise they may get lost. In case of problems, you can contact me by (internal) phone on 719532. Please contact me in advance for individual meetings.

Language: The lectures, classes, all course material, and the assessments, will be in English. If you find this difficult, then I will be happy to receive and reply to questions, and to give you advice or supervision, in French.

Content: This course develops the material covered in Econometrics 1 and Econometrics 2. The first part of the course introduces autocorrelation and binary choice models (probit and logit) in detail. The second part of the course covers panel data models (fixed effects and random effects) and testing. The third part of the course develops some fundamental concepts of time series: difference equations, convergence, linear filters, stationarity of the ARMA(p,q), and the Box-Jenkins methodology for building ARIMA models for forecasting. If there is sufficient time, we will also cover nonstationarity and unit root testing. The theory is illustrated throughout by detailed empirical examples, using the econometric software EViews 6 / EViews 12.

Textbook: I will use my own lecture notes on the subject, and further course material as appropriate. The slides for each class will be posted below (alongside the schedule), after the class. A printed version of all material will be given to you towards the end of the course, before the exam.

Examination (in the Forecasting module): The final grade is based on a written examination, in week 21 (100% of grade) - this will cover both applied and theoretical topics. You will not have computer access during the written examination.

Prize: The student who has the highest score on the final exam will receive a small prize!

Administration:

Various I.E.s & BdP

 

Teaching

16 hours of lectures and classes. These are interchangeable.

There will also be two 3 hour classes by visiting speakers, that will not be assessed during the exam.

Lectures and classes will be held in weeks 2022 // 14 - 16 (Apr).

Class schedules are sometimes subject to change at short notice.

ENAC Intranet upcoming class schedules.

2022 //

Schedule for week 14

Mon 4 Apr 2022 - Class 1/8 - 13:15-15:15 -- room C15 C06 #89, #90, #91, #92, #93, #94 [E2.Applied Problem Set 3] [data for E2.APS3] #78 #79 #80 #81 #82 #83 #84 #85 (E2.APS3 solutions)

Wed 6 Apr 2022 - Class 2/8 - 15:30-17:30 -- room C15 C06 #95, #96, #97, #98, #99, #100 [Applied Problem Set 1] #89 #90 #91 #92 and homework: #93 #94 #96 (required theory) (optional out-of-class story #95)

Fri 8 Apr 2022 - Class 3/8 - 13:15-15:15 -- room C15 C08 #101, #102, #103, #104, #105, #106, #107 [F.Applied Problem Set 1] [data for F.APS1] #98 (required theory) #100 #101 #102 #103 #104 (F.APS1 solutions Q1-5) (optional out-of-class story #97) (optional advanced theory #99)

Schedule for week 15

Mon 11 Apr 2022 - Class 4/8 - 13:15-15:15 -- room C15 C06 #108, #109, #110, #111, #112, #113, #114, #115 #105 #106 #107 #108 #109 #110 #111 #112 #113 #114 #115 (F.APS1 solutions Q6-Q16; note that only #114 00:00 - 06:00 is required for Q15) (optional advanced theory #114 06:00 - 32:54)

Wed 13 Apr 2022 - Class 5/8 - 15:30-17:30 -- room C15 C04 #116, #117, #118, #119, #120, #121, #122, #123, #124, #125, #126, #127, #128 (please note that the applied panel data example is contained in the videos: #121 and #124 to #128, and you need to work through this example using the airline cost data, which is linked here)

Schedule for week 16

Wed 20 Apr 2022 - Class 6/8 - 15:30-17:30 -- room C15 D204 #129, #130, #131, #132, #133, #134, #135 and homework: #136 (required theory)

Fri 22 Apr 2022 - Class 7/8 & Class 8/8 - 13:15-15:15 & 15:30-17:30 -- room C15 D206 (required theory) #137, #138, #139, #140, #141, #142, #143, (F.APS3 solution Q1) #144, (F.APS3 solution Q2) #145

Schedule for week 17

(Econometrics 1 empirical project presentations - see Econometrics 1 webpage)

Wed 27 Apr 2022 - Visiting Speaker (François-Xavier Le Goff) - 15:15-18:15 (3hr slot) -- room Amphi Bréguet

Fri 29 Apr 2022 - Visiting Speaker (Aurore Archimbaud) - 14:15-17:15 (3hr slot) -- room Amphi Bréguet [reading: Schwabish (2014)]

Schedule for week 18 new

(Econometrics 2 bonus paper presentations - see Econometrics 2 webpage)

Schedule for week 19

no classes this week

Schedule for week 20

no classes this week

Schedule for week 21

Mon 23 May 2022 - FINAL WRITTEN EXAMINATION - 13:15-15:15 - room Bréguet

no classes this week

 

Resources

Applied Problem Sets new

Applied Problem Set 1 (discrete choice models)

Applied Problem Set 2 (discrete choice models) [solutions]

Applied Problem Set 3 (time series modelling)

Data

(1) Spector and Mazzeo (1980) grade data, for binary choice modelling [for Applied Problem Set 1]

(2) U.S. union data from the PSID [for Applied Problem Set 2]

(3) Traffic data for empirical forecasting exercise [for Applied Problem Set 3]

(4) U.S. log GNP data [for Applied Problem Set 3]

(5) Monthly bond yield data [for Applied Problem Set 3]

(6) U.S. 3-month T-bill data (implied annualized yield rates), for unit root testing

(7) Series (T=50), (T=100), (T=1000)

(8) Nerlove cost function data

(9) U.S. cigarette consumption data

(10) U.S. metal production data

(11) U.S. gasoline market data

(12) U.S. income and consumption data

(13) U.S. credit card data

(14) U.S. investment data

(15) U.S. money, output and price data

(16) Dow Jones Industrial Average, S&P500, and T-bill data

(17) Airline cost data [in-class panel data estimation and testing]

Additional reading new

Jarque-Bera paper [for E2.APS3 (autocorrelation)]

In-class Exercises new

Solutions to time series theory problems #136 (Q1) #137 (Q2) #140 (Q4, Q4)

Other

(1) Statistical tables [these will be available to you during the final exam]

Past exams new

IENAC17 Forecasting exam ** please note that the mock exam does not contain any coverage of panel data, since this was not covered in class that year; the format of the final exam this year may include discrete choice, panel data, and time series ** [solutions]

 

Reading list

This course follows directly from Econometrics 2.

Textbooks (for reference only):

Additional material that is of particular use here is Greene, W. H. (2000), Econometric Analysis, 4th edition, New Jersey: Prentice-Hall / Chapter 19 binary choice models (probit and logit).

Also helpful is Cameron, A. C. and Trivedi, P. K. (2006), Microeconometrics, Cambridge: Cambridge University Press / Chapter 14 binary choice models (probit and logit).

See Chapter 17 in Hamilton, J. D. (1994), Time Series Analysis, Princeton: Princeton University Press, for excellent technical material on univariate processes with unit roots (asymptotics).

 

Assessment