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Macroeconometrics

Nowcasting and Forecasting with High-Frequency Information

Real-Time Insights: Nowcasting and Forecasting with High-Frequency Data

20h (10 days)

€775 - €1,325

Online

English

Program date: February 17 - 28, 2025

Early bird deadline: January 7, 2025

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Nowcasting and Forecasting with High-Frequency Information

Applications for 2025 Executive Education courses are now open!

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Executive education

Macroeconometrics

Nowcasting and Forecasting with High-frequency Information

Learn the latest techniques in macroeconomic nowcasting and forecasting, focusing on “special situations” where traditional econometric models fall short. It addresses these gaps, and equips you with the advanced skills needed to analyze and predict economic developments even in highly uncertain scenarios.

Teaching Faculty

Discover what makes this Nowcasting and Forecasting course exceptional

1

Learn techniques to navigate the real world: navigate and predict economic outcomes during unprecedented events where traditional models fail.

2

Apply techniques to real-world data: gaining practical experience that makes your skills immediately applicable in professional settings.

3

Gain practical skills using software tools: learn MATLAB for time series analysis, enhancing your technical proficiency.

4

Get guidance and feedback on your own research: projects from instructors and peers, enhancing your analytical and research capabilities.

Produce forecast and nowcast even when standard techniques fail due to exceptional economic conditions

This program is intended for:

Masters and Ph.D. students in economics or related fields wanting to use or develop real-time economic analysis tools.
Researchers who want to learn about uncertainty and decision-making in real-time.
Students in any quantitative field wanting an overview of techniques used in real economic analysis to apply in their own field.
Central bank practitioners and those in private and public institutions seeking to update their knowledge and acquire the latest techniques.

Learn to analyze current economic conditions and produce forecasts using high-frequency data

By the end of this course, participants will be able to:

Create your own tools, based on your specific problem.
Inform decision-makers even when uncertainty is high and standard techniques are useless.
Become adept in analyzing computer codes for problem-solving.

Program Syllabus for Nowcasting and Forecasting for High-frequency Information

Here is the list of topics that will be covered in the course

Nowcasting with standard economic data

Linear framework: Kalman filter. Mixed frequency factor models and VARs.
Non-linear framework: Markov-Switching and Threshold Models. Multivariate time-varying specifications.
MIDAS Models.

Challenges of high-frequency data

Modeling and forecasting with high-frequency data.
Mixing high-frequency data with standard information sets.
Non-linear high-frequency data models.
Special topics on high-frequency data:
- Data Selection.
- Seasonality.
- Signal to noise in high-frequency data.

Special topic. Machine learning and high-frequency data. Model comparison

List of References

Below are some resources that may help you prepare for the course

Books

James Hamilton. “Time Series Analysis” Princeton. (1994).
Chang-Jin Kim, Charles R. Nelson. “State-Space Models With Regime Switching: Classical and Gibbs-Sampling Approaches With Applications”. MIT Press (1999).
Andrew Blake and Haroon Mumtaz. “Applied Bayesian Econometrics for Central Bankers” (2007). Bank of England.
Helmut Lütkepohl “New Introduction to Multivariate Time Series Analysis”. (2005).
Fabio Canova.” Methods for Applied Macroeconomic Research” (2007)
Specific references for our course will be:
Camacho, M. and Perez Quiros G. (2010) “Introducing the euro-sting: Short-term indicator of euro area growth” Journal of Applied Econometrics, Volume25, Issue 4
Schorfheide, F and Song, D. (2021) Real-Time Forecasting with a (Standard) MixedFrequency VAR During a Pandemic “Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic”. NBER Working paper 29535
Leiva Leon, D, Perez Quiros, G and Rots, E. Real-time weakness of the global economy a first assessment of the coronavirus crisis. ECB Working Paper 2381. March 2020
Eo, Y. and C.-J. Kim (2016). Markov-switching models with evolving regime-specific parameters: Are postwar booms or recessions all alike? Review of Economics and Statistics 98 (5), 940–949.
Bai, Jennie, Eric Ghysels and Jonathan Wright (2010), “State Space Models and MIDAS Regressions.” Econometric Reviews Volume 32, 2013 – Issue 7
Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. “The MIDAS Touch: Mixed Data Sampling Regression Models,” CIRANO Working Papers 2004s-20, CIRANO.
Hale, T, A Petherick, T Phillips, S Webster, B Kira, N Angrist and L Dixon (2020), “Oxford COVID-19 Government Response Tracker”, Blavatnik School of Government, Oxford University
Lewis, D., K. Mertens, and J. Stock (2020): “U.S. Economic Activity During the Early Weeks of the SARS-Cov-2 Outbreak,” FRB Dallas Working Paper, 20-11.
Lewis, D., K. Mertens, and J. Stock. 2020. “Monitoring Real Activity in Real Time: The Weekly Economic Index,” Federal Reserve Bank of New York Liberty Street Economics, March 30.
Chetty, Raj, John N. Friedman, Nathaniel Hendren, Michael Stepner, and the Opportunity Insights Team (2020). “How Did COVID-19 and Stabilization Policies A§ect Spending and Employment? A New Real-Time Economic Tracker Based on Private Sector Data,” mimeo, Harvard University.
Perez Quiros, G. and Saiz, L. “Introducing the Eurotracker” ECB Mimeo 17) Gonzales, F, A Jaax and A Mourougane (2020), “Nowcasting aggregate services trade. A pilot approach to providing insights into monthly balance of payments data”, Paris: OECD Publishing.
Christiane Baumeister, Danilo Leiva-León & Eric R. Sims. “Tracking Weekly State-Level Economic Conditions” NBER Working Paper 29003. July 2021 19) Cuevas, Á., Ledo, R. & Quilis, E.M. Seasonal adjustment of the Spanish sales daily data. SERIEs 12, 687–708 (2021).
Manuel Medina Magro (2022) Nowcasting The USA Real Quarterly GDP Growth With a Seasonally Adjusted Weekly Economic Index. U. of Alicante (mimeo)
Sercan Eraslan & Thomas G ö tz. (2021). “An unconventional weekly economic activityindex for Germany”. Economics Letters, Volume 204, 109881, ISSN 0165-1765.
Woloszko, N (2020), “A Weekly Tracker of activity based on machine learning and Google Trends”, OECD Economics Department Working Papers 1634, Paris: OECD Publishing.
Maccarrone G, Morelli G, Spadaccini S. GDP Forecasting: Machine Learning, Linear or Autoregression? Front Artif Intell. 2021 Oct 15;4:757864.

Why should you attend BSE Executive Education courses?

All BSE Executive Education courses are taught to the same high standard as our Master’s programs.

1

Network with like-minded peers from around the world.

2

Short courses allow you to learn without a big time commitment.

3

Try something new and expand your knowledge and career prospects, or advance your thesis.

Admissions

If you want to apply for this Nowcasting and Forecasting course, ensure you meet the criteria below:

Course start date: February 17, 2025

Deadline to apply: February 13, 2025

Requirements

Candidates are assessed on an individual basis according to their professional or academic background.
Students must have their own laptop or desktop computer and good Internet connection to be able to follow and fully benefit from the course.

Nowcasting and Forecasting for High-frequency information requirements

Knowledge of mathematics and/or statistics at graduate level could help to take further advantage of the course although it is not mandatory.

Get up to speed with the latest developments in Nowcasting and Forecasting in a short time

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Here is your course Schedule!

Times listed are Central European Time (CET). Compare with your time zone on time.is.

Week 1

Time

1
Mon

2
Tue

3
Wed

4
Thu

5
Fri

17:00-19:00

Lecture

Practical

Lecture

Practical

Lecture

Week 2

Time

1
Mon

2
Tue

3
Wed

4
Thu

5
Fri

17:00-19:00

Practical

Lecture

Practical

Lecture

Practical

Course Materials and Software

Every participant will receive a free, limited-time MATLAB license. You’ll need to install it on your computer for practical sessions before the course start date.

Additional materials will also be provided.

Certificate

Participants will receive a Certificate of Attendance free of charge.

Fees

Fees for courses in other Executive Education programs may vary.

Multiple course discounts are available. Find out more information in our Fees and Discounts pdf.

Course

Nowcasting and Forecasting with High-frequency Information

Modality

Online

Total Hours

20

Regular Fee

1,325€

Reduced Fee*

775€

*Reduced Fee applies for PhD or Master’s students, Alumni of BSE Master’s programs, and participants who are unemployed.

FAQ’s

Need more information? Check out our most frequently asked questions:

Are the sessions recorded?

Sessions will be recorded and videos will be available for a month once the course has finished.

How much does each Executive Education course cost?

Fees for each course may vary. Please consult each course page for accurate information.

Are there any discounts available?

Yes, BSE offers a variety of discounts on its Executive Education courses. See more information about available discounts or request a personalized discount quote by email.