Researchers develop novel methods to improve macroeconomic forecasting

An international team of researchers, led by economists from Masaryk University, have created new modelling tools that allow for more precise predictions of macroeconomic variables such as GDP growth, inflation or interest rates. Novel economic methods developed within the Dynamic Forecast Averaging of Macroeconomics Models project, supported by GA CR, may contribute significantly to evidence-based economic policymaking. The research team aimed to understand how to combine forecasts from different theoretical models and obtain more reliable estimates of the effects of government expenditure and tax changes on GDP growth.

Improving existing prediction models

Obtaining reliable predictions of future changes in economic variables such as GDP is extremely important for policymakers, investors, and companies. The existing theoretical methods aimed at providing forecasts and policy advice rely on particular assumptions about the behaviour of economic agents and highlight different economic transmission mechanisms. In this project, researchers from Masaryk University, the Vienna University of Economics and Business, Charles University and the University of Salzburg joined forces to improve the existing macroeconometric methods to combine the information from theoretical models that stress different economic linkages into composite predictions.


The heatmaps show the deviation of the prior from the posterior mean within the two different regimes using the change in debt-to-GDP as threshold variable. Light grey cells indicate a good fit of the DSGE prior, blue regions imply positive deviations of the posterior from the prior mean, whereas red coloured regions indicate negative deviations of the coefficients. Figure from the article published in Journal of Economic Dynamics and Control.

One work package of the project addressed how fiscal policy (changes in government expenditure or taxes) affects GDP growth in European economies, that is, how large the so-called fiscal multiplier is. Given the economic importance of the public sector in industrialized countries, obtaining precise estimates of fiscal multipliers is particularly important in order to improve forecasts of economic activity. Better multiplier estimates can be obtained by assessing how the use of different methods affects their size. Such an analysis also allows practitioners to understand the biases in current fiscal multipliers estimates.


The dark density corresponds to the full set of fiscal multiplier estimates for Austria; the light density refers to the top 40% best models in terms of predictive ability. Figure from the article published in Oxford Economic Papers.

In parallel to the effects of public policy, other important markets such as the foreign exchange market and the market for cryptocurrencies were also studied in detail. New statistical techniques were developed to obtain a more realistic picture of their driving factors and future dynamics. Such modelling tools can significantly reduce the prediction error in the exchange rate and cryptocurrency returns.


Log predictive Bayes factors relative to the TVP-VAR over time: (a) Bitcoin; (b) Litecoin; (c) Ethereum; (d) log predictive likelihood. Figure from the article published in Journal of Forecasting.

How to combine information from different models of the economy

As part of the project’s ultimate aim, a group of different theoretical models designed to explain macroeconomic dynamics were combined, using novel methods to improve their predictive power. In particular, the research team created several types of adaptive weights that can be used for different macroeconomic variables and different models, leading to better forecasting ability for GDP growth, inflation, and interest rates. The methods used in this phase of the project are expected to result in an improved toolkit that will inform policymakers about future developments in the macroeconomy, thus leading to better decisions in public policy.


Posterior mean of model weights over the hold-out sample for four-step-ahead predictions. The figure shows three different weighting schemes for the three target variables: output, inflation, and interest rate. Variables entering the DSGE models are detrended with the Hamilton filter.

A follow-up of the project is currently expanding the portfolio of models that can be used to create combined predictions and will thus lead to further improvements of predictive ability beyond those reported in this research endeavour. In particular, forecasts of new data-driven statistical models that do not rely on particular theories will be added to the predictions pool and are expected to improve the predictive quality of the resulting combinations. The follow-up project On the time-varying predictive ability of theoretical and empirical macroeconomic models is also supported by GA CR.


Jesús Crespo Cuaresma, principal investigator


Jan Čapek, team member, coordinator of the international team

US and Czech scientists collaborate to explore gamma-ray production with high power lasers

The U.S. National Science Foundation (NSF) and the Czech Science Foundation (GACR) are funding a new collaborative project of scientists from the University of California San Diego in the U.S. and ELI Beamlines (Institute of Physics of the Czech Academy of Sciences) in the Czech Republic which aims to leverage the capabilities of the ELI Beamlines multi-petawatt laser facility. Researchers hope these experiments can achieve a breakthrough by demonstrating efficient generation of dense gamma-ray beams.

Stellar objects like pulsars can create matter and antimatter directly from light because of their extreme energies. In fact, the magnetic field, or “magnetosphere,” of a pulsar is filled with electrons and positrons that are created by colliding photons.

Reproducing the same phenomena in a laboratory on Earth is extremely challenging. It requires a dense cloud of photons with energies that are millions of times higher than visible light, an achievement that has so far eluded the scientists working in this field. However, theories suggest that high-power lasers ought to be able to produce such a photon cloud.

As the first international laser research infrastructure dedicated to the application of high-power and high-intensity lasers, the Extreme Light Infrastructure (ELI ERIC) facilities will enable such research possibilities. The ELI ERIC is a multi-site research infrastructure based on specialized and complementary facilities ELI Beamlines (Czech Republic) and ELI ALPS (Hungary). The new capabilities at ELI will create the necessary conditions to test the theories in a laboratory.

This project combines theoretical expertise from the University of California San Diego (U.S.), experimental expertise from ELI Beamlines, as well as target fabrication and engineering expertise from General Atomics (U.S.). The roughly $1,000,000 project, jointly funded by NSF and GACR, will be led by Prof. Alexey Arefiev at UC San Diego. Target development for rep-rated deployment will take place at General Atomics, led by Dr. Mario Manuel, while the primary experiments will be conducted at ELI Beamlines by a team led by Dr. Florian Condamine and Dr. Stefan Weber.

nsf_gacr_1Figure 1: Super computer simulation of energetic gamma-ray emission (yellow arrows) by a dense plasma (green) irradiated by a high-intensity laser beam (red and blue). The laser propagates from left to right, with the emitted photons flying in the same direction. The smooth blue and red regions represent a strong magnetic field generated by the plasma, whereas the oscillation region corresponds to the laser magnetic field.

The concept for the project was developed by Arefiev’s research group at UC San Diego, which specializes in supercomputer simulations of intense light-matter interactions. The approach for this project leverages an effect that occurs when electrons in a plasma are accelerated to near light speeds by a high-powered laser. This effect is called “relativistic transparency” because it causes a previously opaque dense plasma to become transparent to laser light.

In this regime, extremely strong magnetic fields are generated as the laser propagates through the plasma. During this process, the relativistic electrons oscillate in the magnetic field, which in turn causes the emission of gamma-rays, predominantly in the direction of the laser.

“It is very exciting that we are in a position to generate the sort of magnetic fields that previously only existed in extreme astrophysical objects, such as neutron stars,” says Arefiev. “The ability of the ELI Beamlines lasers to reach very high on-target intensity is the key to achieving this regime.”

These experiments will provide the first statistically relevant study of gamma-ray generation using high-powered lasers. Researchers hope the work will open the way for secondary high-energy photon sources that can be used not only for fundamental physics studies, but also for a range of important industrial applications such as material science, nuclear waste imaging, nuclear fuel assay, security, high-resolution deep-penetration radiography, etc.  Such “extreme imaging” requires robust, reproducible, and well-controlled gamma-ray sources. The present proposal aims exactly at the development of such unprecedented sources.

The experiments will be greatly assisted by another technological advance. Until recently, high-power laser facilities could execute about one shot every hour, which limited the amount of data that could be collected. However, new facilities like ELI Beamlines are capable of multiple shots per second. These capabilities allow for statistical studies of laser-target interactions in ways that were impossible only a few years ago. That means a shift in the way such experiments are designed and executed is necessary to take full advantage of the possibilities.

“The P3 installation at ELI Beamlines is a unique and versatile experimental infrastructure for sophisticated high-field experiments and perfectly adapted to the planned program,” comments Condamine. Weber notes, “This collaboration between San Diego and ELI Beamlines is expected to be a major step forward to bring together the US community and the ELI-team for joint experiments.”

Thus, a major part of this project is training the next generation of scientists at ELI Beamlines to develop techniques that can fully leverage its rep-rated capabilities. UC San Diego students and postdoctoral researchers will also train on rep-rated target deployment and data acquisition on General Atomics’ new GALADRIEL laser facility to help improve the efficiency of the experiments conducted at ELI Beamlines.

nsf_gacr__2Figure 2: The P3 (Plasma Physics Platform)-installation at ELI Beamlines where the experiments will take place.

“This is the first project funded by the Czech Science Foundation and the US National Science Foundation. I believe that the new collaboration between the agencies will lead to a number of successful projects and collaborating scientific teams from the Czech Republic and the USA will benefit from it,” says GACR president Dr. Petr Baldrian.

“We are thrilled to be working with our counterparts in the Czech Republic to further expand international scientific cooperation in artificial intelligence, nanotechnology, and plasma science research. I am optimistic this will be the first of many collaborative projects between NSF and GACR,” says the Director of NSF, Dr. Sethuraman Panchanathan.