Applied Econometrics with Stata

3-6 June 2008

Cass Business School, 106 Bunhill Row, London, EC1Y 8TZ, UK.

Contents

Course Description
Course Programme
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Terms and Conditions
Stata Software

Timberlake Consultants Ltd, the UK distributor of Stata, invite you to attend a four days course in Central London, covering the use of Time Series Analyses with Stata 9, the well known statistical software package software package developed by StataCorp (USA).

The Course - Several major advances in time series, forecasting and panel data estimation and management and software engineering have occurred in the past few years. These advances provide a major breakthrough in the modelling of time series and dynamic panels using easy-to-use Windows based software. The course aims to provide delegates with background on econometric modelling methods and demonstrate, using real-life business and industrial data, how to interpret and report the results. The software package Stata will be used throughout the course.

Who should attend - The course, given in English, is aimed at forecasters and researchers in

  • Economic Research/ Model Building
  • Financial Modelling/ Arbitrage Trading
  • Quantitative Investment Management
  • Sales and Inventory Forecasting
  • Traffic Modellers
  • Energy Load Forecasting
  • University Instruction
  • Academic Researchers
  • and more

Advantages - The course will

  • Review all major econometric modelling methods
  • Provide a practical and systematic approach to the modelling of business and financial time series and dynamic panel data
  • Provide hands-on experience in building econometric models using time series and panels - each delegate will have access to a computer throughout the course
  • Provide an opportunity for you to meet with a panel of experienced modellers to discuss industry-specific applications related to forecasting and time series analysis

The Principal Lecturers -

Dr Sean Holly, Director of the Department of Applied Economics and Fellow of Fitzwilliam College , University of Cambridge .

He was formerly Professor of Economics at the University of Sheffield (1991-1996) and Director of Research at the Centre for Economic Forecasting, London Business School (1983-1991). He has published widely on optimal control theory, forecasting, applied econometrics and macro-modelling.

Dr Arnab Bhattacharjee is a Lecturer at the School of Economics and Finance, University of St-Andrews (2004). He joined the University of Cambridge in 2001, after working for 5 years at the Reserve Bank of India, and in 2002, he took up a joint position, as Research Associate in the Department of Applied Economics and as Fellow, College Lecturer and Director of Studies (Economics) at Robinson College, University of Cambridge. He has varied research interests, including econometrics, industrial economics, corporate finance macroeconomics and labour economics.

Cost

Late Registrations
(30- days before the course starts)
Early Registrations
(30+ days before course starts)
1st Participant
 £1,800+VAT=£2,115.00
 £1,530+VAT=£1,797.75
2nd+ Participant £1,600+VAT=£1,880.75 £1,375+VAT=£1,615.63

The cost includes course materials, lunch, refreshments and the use of computers. Agendas and a registration form are enclosed for your convenience. The number of delegates is restricted. Please register early to guarantee your place. If you need assistance in locating hotel accommodation in the area, contact Timberlake Consultants at the above address.

Payment can be made by cheque, bank transfer or credit/debit card (a surcharge of 2% applies to credit card payments only. There is no charge for debit card payments).

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Agenda
(subject to minor changes)

Session 1: Introduction to Stata

  • Data Entry and Management.
  • Handling large data sets.
  • Seasonal Adjustment of Time Series
  • Differencing and Stationarity
  • Modelling a Time Series – the Box-Jenkins Approach
  • Seasonal Integration

Session 2: Practical Session

  • Tests for Orders of Integration
  • Building a Time Series Model
  • Tests of Seasonal Integration

Session 3: Error Correction Models

  • Using a Time Series Model for Forecasting
  • Dealing with Trends
  • Mixing Variables in Levels and Differences
  • A First Introduction to Cointegration

Session 4: Practical Session

  • Estimation of an Error Correction Model
  • Forecasting Using an Error Correction Model

Session 5: The Classical Linear Regression Model

  • Methods of Estimation – Least Squares, Maximum Likelihood, Method of Moments
  • Approaches to Testing – Wald, Likelihood Ratio and Lagrange Multiplier
  • Diagnostic Testing Using Stata.

Session 6: Practical Session

  • Estimating a Model Using the General to Specific Approach
  • Reparameterising the Model
  • Diagnostic Testing

Session 7: Error Correction Models

  • Dealing with Cointegrated Variables
  • The Engle-Granger Two Stage Procedure
  • Common Stochastic Trends

Session 8: Practical Session

  • Testing for Cointegration

Session 9: Non-parametric density estimation and regression.

Session 10: Working with Panel Datasets.

Session 11: Dynamic Panel Models; applications to exports.

Session 12: Practical Session

Session 13: Duration Data Analysis: applications to exits and acquisitions among US firms. US Strike Duration.

Session 14: Limited Dependent Variable Models: application to UK monetary policy.

Session 15: Practical session.

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Terms and Conditions

Registration closes 5 calendar days prior to the start of the course.

Cancellations:

  • full fee returned for cancellations made over 28 calendar days prior to start of the course
  • half-fee returned for cancellations made 14 calendar days prior to he start of the course
  • no fee returned for cancellations made less than 14 calendar days prior to the start of the course.

    Payment of course fees required prior to the course start date

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Last revised:11/04/2008
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