Time Series Data Analysis and Modelling using Stata Course

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We are proud to offer this course in a variety of training formats to suit your needs. We use the highest quality learning facilities to make sure your experience is as comfortable as possible. Our face to face calendar allows you to choose any classroom course of your choice to be delivered at any venue of your choice - offering you the ultimate in convenience and value for money.

July 2024

Code Date Duration Location Fee Action
TSD08 15 Jul 2024 - 19 Jul 2024 5 days Mombasa, Kenya KES 92,000 | $1,100 Register
TSD08 22 Jul 2024 - 26 Jul 2024 5 days Nairobi, Kenya KES 83,000 | $1,100 Register
TSD08 15 Jul 2024 - 19 Jul 2024 5 days Kampala, Uganda $1,900 Register
TSD08 15 Jul 2024 - 19 Jul 2024 5 days Accra, Ghana $2,400 Register
TSD08 22 Jul 2024 - 26 Jul 2024 5 days Johannesburg, South Africa $2,400 Register
TSD08 22 Jul 2024 - 26 Jul 2024 5 days Cape Town, South Africa $2,400 Register
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July 2024

15 Jul - 19 Jul
5 days
KES 92,000 | $1,100
22 Jul - 26 Jul
5 days
KES 83,000 | $1,100
15 Jul - 19 Jul
5 days
- | $1,900
15 Jul - 19 Jul
5 days
- | $2,400
22 Jul - 26 Jul
5 days
- | $2,400
22 Jul - 26 Jul
5 days
Cape Town
- | $2,400
I Want To See More Dates...
I Want To See More Dates...


The course will show how economic and financial time series can be modeled and analyzed. The aim is to provide understanding and insight into the methods used, as well as explaining the technical details. Statistical modeling will be demonstrated using the Stata Software and participants will be given the opportunity to use Stata in class. Statistical modeling will be demonstrated using the Stata Software.


5 Days


Participants are expected to have attended the previous course on Data Management, Graphics and Statistical analysis using Stata or to be familiar with Stata software.

Course Level:

Course Objectives

  • Understand the definitions, features and objectives of time series modeling.
  • Understand descriptive analysis of time series, plots, aggregation, smoothing and regression techniques.
  • Understand and conduct periodic regression and ARIMA modeling using stationary time series.
  • Using ARIMA modeling (Box & Jenkins), understand and use auto-correlation functions and partial auto-correlation functions to study how much an observation at a given time is related to observation at previous lags.

Course Outline

  • Introduction

  • Stationary time series

  • Unobserved components and signal extraction.

  • Time Series Models

  • ARIMA models

  • Structural time series models

  • Explanatory variables and intervention analysis

  • State space models and the Kalman filter.

  • Signal extraction.

  • Missing observations and other data irregularities

  • Spectral analysis

  • Spectra of ARMA processes; stochastic cycles; linear filters; estimation of spectrum

  • Trends and cycles

  • Analysis of the effects of moving average and differencing operations

  • Hodrick-Prescott and band-pass filters. Seasonality

  • Multivariate time series models

  • Common trends and co-integration; control groups

  • Nonlinear models. Financial econometrics; distributions of returns, stochastic volatility and GARCH

  • Dynamic conditional score models

  • Multivariate volatility models.

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Course Administration Details:


The instructor-led training are delivered using a blended learning approach and comprises presentations, guided sessions of practical exercise, web-based tutorials, and group work. Our facilitators are seasoned industry experts with years of experience, working as professionals and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.


Upon successful completion of this training, participants will be issued with an Indepth Research Institute(IRES) certificate certified by the National Industrial Training Authority (NITA).


The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments, and lunch.

All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.


Accommodation and airport pickup are arranged upon request. For reservations contact the Training Officer.

Email:[email protected] / [email protected]


This training can also be customized to suit the needs of your institution upon request. You can have it delivered at our IRES Training Centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817 0r +250 789 621 067

Mob: +254 792516000+254 792516010   +250 789 621 067 or mail [email protected] / [email protected]


Payment should be transferred to IRES account through the bank before the course start date

Send proof of payment to [email protected] / [email protected]

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