Country dropdown

Time Series Data Analysis and Modelling using Stata Course


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.


  • 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.


  • 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.


Participants should be reasonably proficient in English. Applicants must live up to Indepth Research Services (IRES) admission criteria.


The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional 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 Services (IRES) certificate.


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

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


Accommodation is arranged upon request. For reservations contact the Training Officer.

Email:This email address is being protected from spambots. You need JavaScript enabled to view it..  

Mob: +254 715 077 817

Tel: 020 211 3814


This training can also be customized for your institution upon request to a minimum of 4 participants. You can have it delivered in our training centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817, +254 (020) 211 3814 or mail This email address is being protected from spambots. You need JavaScript enabled to view it.


Payment should be transferred to IRES account through bank on or before C.O.B. 3rd August 2020.

Send proof of payment to This email address is being protected from spambots. You need JavaScript enabled to view it.


Payment for the all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

1.    Participants may cancel attendance 14 days or more prior to the training commencement date.

2.    No refunds will be made 14 days or less to the training commencement date. However, participants who are unable to attend may opt to attend a similar training at a later date, or send a substitute participant provided the participation criteria have been met.

Please Note: The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

Event Properties

Event Duration 5 Days
Event Date 10-08-2020
Event End Date 14-08-2020
Cut off date 03-08-2020
Individual Price(Kenyan) KES 69,000
Individual Price (International) EUR 790
Individual Price(International in Dollars) USD 920
Location Nairobi, Kenya
Share this event: