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Macro-Econometric Modelling, Forecasting And Policy Analysis

Macro-Econometric Modelling, Forecasting And Policy Analysis

TRAINING DATES: 6th October 2025–10th October2025
COUNTRY: Ghana-Accra

Overview

This is an intensive course which provides policy makers tools required to build macroeconomic frameworks from scratch. This course is most ideal for personnel in the Ministries of Finance, Planning, central banks as well as international organizations. 

Course objective: 

By the end of the course the participants will have acquired detailed knowledge of and extensive hands-on experience in:

  • Macroeconometric modeling: history, types, structure.
  • Data, their type, and characteristics.
  • The use of EViews for data analysis.
  • Econometric estimations and testing with EViews.
  • Nonstationarity and Unit root tests.
  • Cointegration tests and long-run estimations.
  • Error correction models and short-run analysis.
  • Building a macroeconometric model in EViews.
  • The algorithms for solving models.
  • Checking the validity and consistency of models.
  • Calibration and update of models.
  • Simulations and scenario building within Eviews
  • Advanced simulations using IRIS/MATLAB or StateSpaceEcon/Julia

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Course Content

Session/Day Lecture Topic Lab session
Module 1 Overview of time series macro econometric modeling
-Time Series and Stationarity (stationary and non-stationary)
-Time Series and Seasonality, and other properties of TS data.
-Time Series Data and Autocorrelation tests
-Tests for stationarity, Data transformations (logs, Seasonality Adjustment, differencing, detrending, lags)
-Autoregressive (AR) Models, Moving Average (MA) Models
-Nonstationary time series processes Deterministic and stochastic trends

-EViews basics and introduction

-Managing data series using EViews

-Statistical descriptive analysis, plots using EViews

– Data transformations (logs, Seasonality Adjustment,

differencing; detrending, lags), and tests for stationarity: unit root tests.

-Autocorrelation function, Correlogram; estimation and elimination of trend and seasonal components.

-Time series properties and data analysis in EViews.

-AR, MA estimation in EViews
Module 2 ARMA/ARIMA /ARIMAX, and Structural breaks
The Box Jenkins Approach, Random Walks
– Identification
– Estimation
– Diagnostic testing
– Structural breaks
– Consequences of structural breaks;
– Testing for structural breaks: graphs; Chow test (if there are priors); recursive estimation; CUSUM
– Unit root tests (autocorrelation function, ADF, Phillips-Perron, ZPSS) Forecasting using Univariate models: AR, MA, ARMA, ARIMA
– Ex post vs ex ante forecasts ; -static vs dynamic forecasts;
– Forecast Evaluation;

ARMA/ARIMA/ARIMAX Estimation, and Structural Breaks

-Simulate ARMA processes

-check for stationarity

-Manually estimate and check ARMA models on simulated series

Simulate ARIMA Models, Estimate ARMA models using EViews automatic model selection procedure, Estimate ARIMAX models

-Test for structural breaks

Construct dynamic and static forecasts using simulated ARIMA series

-Forecast evaluation statistics: -Evaluate forecasts using graphs

Evaluate forecasts

Module 3 Single Equation Error Correction Models
-Specification
-Estimation
-Diagnostic testing
-Evaluating Regression Models
-Forecasting

Estimating Single Equation Error Correction Models

-Specify and estimate an Error Correction Model

Apply the Engle-Granger approach to test for cointegration between 2 variables (e.g CPI Inflation and Money Supply)

-Manual test: unit root tests on individual series; test for residual stationarity
-Automatic (Augmented Engle-Granger (AEG) test in EViews

– Estimate and interpret ECM regression
Module 4 Building Macroeconometric Models using System Object in Eviews
-Simulation analysis using the developed system object.

Development of System Block

Estimation of private consumption

Estimation of private investments

Estimation of exports and imports

Estimation of revenues

Estimation of money demand functions

Enforcement of key identities for national accounts, fiscal, balance of payments and monetary accounts
Module 5 Advanced Macro econometric Models

Using IRIS in Matlab

Using Statespaceecon in Julia

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