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Regional workshop: Strengthening the technical capacity of public finance managers in selected Caribbean Small Island Developing States (SIDS)

19 de septiembre de 2016|Evento

The workshop will improve the capacity of public finance managers to manage fiscal outcomes that will enhance economic growth.

This workshop is an introduction to time series forecasting for the conduct of public expenditure reviews. It assumes familiarity with basic regression methods and related mathematics but not the methods of time series forecasting. The course is a fast-paced applied course, designed to show how to do forecasting with Stata 14, so only very modest time will be spent on derivation of related theory. Instead, good references on proofs and derivations are provided.

The course is designed in 5 sections reflecting the forecasting methods presented over 5 days:

  1. Introductory issues and basic skills
    1. Qualitative forecasting and judgement forecasting, which are mainly ad hoc and based on expert-opinion.
    2. Introduction to Stata
    3. Weighted moving average methods. These include exponential smoothing and Holt-Winters methods, which essentially fit a suitable curve to historical time series.
  2. Autoregressive integrated moving average forecasting (ARIMA) methods, which allow a variable to be explained by past values of itself independent of any theory but based on their stochastic properties.
  3. Vector autoregressive forecasting models. These address the case of several endogenous variables explained jointly by each other’s past histories in the light of their stochastic properties. A special case is the vector error correction forecasting model designed for nonstationary variables.
    1. Single equation regression forecasting, which is motivated by economic theory in which some dependent variable is explained by one or more independent variables. Topics are geared specifically to time series forecasting.
    2. Simultaneous equation regression models, such as are used for GDP and related forecasting, in which several interdependent endogenous variables are explained by a set of predetermined variables.
  5. Special topics in budget forecasting, including micro-simulation models.



  1. The Course Manual: Annex 3A – Revenue and Expenditure Forecasting for a PER.
  2. Becketti, Sean (2013). Introduction to Time Series Using Stata. College Station, Texas: Stata Press.
  3. The Stata Time Series Reference Manual [TS] Time Series, Release 14.