Traditional methods of measuring inflation rely on data that's collected and published with a significant time lag, providing an outdated view of current economic conditions. In today's fast-paced world, this delay can be a major disadvantage for policymakers and businesses trying to make timely decisions. By leveraging high-frequency data from non-traditional sources—like real-time online prices, credit card transactions, and web search data—economists can "nowcast" inflation, generating more accurate, up-to-the-minute estimates of price changes. This approach provides a crucial informational edge, allowing for more proactive and effective responses to inflationary pressures before they become entrenched in the economy.

This program provides a comprehensive and practical guide to the cutting-edge field of real-time inflation monitoring. Participants will learn to identify and source various forms of alternative data and will gain proficiency in the advanced analytical techniques needed to transform raw data into actionable insights. The course will address everything from the fundamentals of web scraping and data cleaning to the use of machine learning models and the ethical considerations of using private data. By focusing on hands-on exercises and real-world case studies from central banks and private institutions, attendees will be equipped to build their own real-time inflation dashboards and to integrate this new knowledge into their decision-making processes.

Duration: 10 days

Target Audience:

• Central Bank Economists and Researchers
• Financial Market Analysts and Strategists
• Data Scientists and Statisticians
• Public Policy Professionals
• Corporate Planners and Retail Analysts
• ESG and Investment Specialists
• Academics and Students in Economics
• Market Research Professionals
• Journalists and Economic Reporters
• Government Statisticians

Objectives:

• Master the core concepts of nowcasting and real-time economics.
• Learn to identify and source various forms of high-frequency data.
• Understand the technical and ethical challenges of using alternative data.
• Grasp the complexities of nowcasting inflation using mixed-frequency data.
• Develop proficiency in the use of web scraping and data cleaning tools.
• Explore best practices for building a real-time inflation dashboard.
• Learn about robust methods for integrating high-frequency data into economic models.
• Identify the critical legal and privacy frameworks for data use.
• Develop skills in translating real-time insights into actionable policy.
• Formulate strategies for building a more agile and responsive organization.

Course Modules:

Module 1: The Nowcasting Revolution

• The limitations of traditional economic indicators
• The concept of nowcasting vs. forecasting
• The role of a "clear and focused research question"
• The advantages of using high-frequency data
• The importance of a "risk and mitigation" plan

Module 2: Sources of High-Frequency Data

• Real-time online price data
• The role of credit card and transaction data
• The importance of a simple scorecard and a dashboard
• The use of social media and web search data
• The challenges of data sourcing and licensing

Module 3: Web Scraping and Data Collection

• Fundamentals of web scraping techniques
• The use of Python libraries (e.g., BeautifulSoup, Scrapy)
• The importance of a "data story map"
• The ethical and legal considerations of web scraping
• The role of APIs for data acquisition

Module 4: Data Cleaning and Transformation

• Handling missing values and outliers
• The use of a "clear and consistent reporting style"
• The challenges of a "ragged-edge" problem
• The importance of a program's theory of change
• The techniques for data normalization and standardization

Module 5: Nowcasting Methodologies

• The use of mixed-frequency data sampling (MIDAS) models
• The importance of a "stakeholder analysis"
• The role of dynamic factor models
• The use of a clear and compelling KPI
• The comparison of different nowcasting approaches

Module 6: Big Data & Machine Learning

• The application of machine learning in nowcasting
• The importance of a "risk and mitigation" plan
• The use of supervised vs. unsupervised learning
• The role of natural language processing (NLP) for sentiment analysis
• The challenges of model selection and overfitting

Module 7: Building a Real-Time Dashboard

• The process of designing a real-time dashboard
• The use of a simple scorecard and a dashboard
• The choice of visualization tools (e.g., Tableau, Power BI)
• The importance of a "data story map"
• The challenges of data updating and maintenance

Module 8: Case Studies

• Case study: Nowcasting inflation with online price data
• The use of a "clear and consistent reporting style"
• Case study: The use of credit card data to monitor consumer spending
• The role of a program's theory of change
• The lessons from central banks' use of alternative data

Module 9: The Role of Expectations

• The impact of real-time data on inflation expectations
• The importance of a "stakeholder analysis"
• The challenges of a "clear and focused research question"
• The role of a clear and compelling KPI
• The link between real-time data and central bank communication

Module 10: The Data and "Risk and Mitigation" Plan

• The use of a simple scorecard and a dashboard
• The importance of a "data story map"
• The role of a "clear and consistent reporting style"
• The use of a program's theory of change
• The importance of a "stakeholder analysis"

Module 11: Nowcasting in Practice

• The workflow of a real-time inflation analyst
• The importance of a "clear and focused research question"
• The use of a "risk and mitigation" plan
• The integration of qualitative insights with quantitative data
• The role of a simple scorecard and a dashboard

Module 12: Ethical and Legal Frameworks

• The privacy implications of using transaction data
• The importance of a "data story map"
• The role of a "clear and consistent reporting style"
• The legal challenges of data ownership
• The importance of a program's theory of change

Module 13: The Future of Nowcasting

• The role of artificial intelligence and automation
• The use of a "stakeholder analysis"
• The impact of the "metaverse" on data collection
• The use of a clear and compelling KPI
• The future of a "clear and focused research question"

Module 14: Communication and Policy

• The role of a "risk and mitigation" plan
• The use of a simple scorecard and a dashboard
• The importance of a "data story map"
• The challenges of communicating real-time data to the public
• The role of a "clear and consistent reporting style"

Module 15: Cross-Country Applications

• The challenges of nowcasting in developing economies
• The use of a program's theory of change
• The role of a "stakeholder analysis"
• The use of a clear and compelling KPI
• The importance of a "clear and focused research question"

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.