Introduction

Economic models and forecasting are essential tools for understanding and analyzing economic performance and making informed decisions. This course aims to equip participants with the skills to build economic models and develop forecasts to address future challenges, with a focus on using data and trend analysis to estimate future market performance and economic changes.

Objectives

• Understand the fundamentals of economic models, how to build them, and how to apply them.

• Acquire skills in data analysis and developing economic forecasts.

• Apply forecasting models to measure the effects of economic variables.

• Learn about tools and techniques for forecasting and trend analysis.

• Develop the ability to produce forward-looking reports that support economic decision-making.

Target Audience

Economists, financial analysts, strategic planning managers, risk management professionals, and anyone seeking to understand economic tools to build accurate forecasts and analyses.

Outlines

Day 1:

Introduction to Economic Models

• What are economic models? Overview of the types of economic models and their importance.

• Fundamentals of model building: Steps to design economic models and analyze assumptions.

• Using data in models: How to collect and process data for model construction.

Day 2:

Economic Forecasting Techniques

• Quantitative forecasting methods: Forecasting using statistical and mathematical approaches.

• Qualitative forecasting: Relying on expertise and judgment to anticipate trends.

• Time series analysis: Applying time-based methods to predict future performance.

Day 3:

Scenario Analysis and Causal Models

• Scenario building: How to develop future scenarios and estimate their impact.

• Causal models: Using causal relationships between economic variables for forecasting.

• Analysis of influencing factors: Measuring the effects of external changes on economic performance.

Day 4:

Forecasting Tools and Techniques

• Advanced mathematical and statistical models: Applying linear and nonlinear models.

• Regression analysis: How to use regression to analyze relationships between variables.

• Model testing: Methods to evaluate the accuracy and reliability of models.

Day 5:

Practical Applications and Developing Forward-Looking Reports

• Developing practical forecasts: Building forecasting models for markets or economic sectors.

• Producing forward-looking reports: How to present forecasting results in a clear way for decision-makers.

• Analytical workshop: Applying learned concepts through real-world case studies.