Forecasting Economic Activity Using a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to the
German GDP
Oliver Holtemöller, Boris Kozyrev
IWH Discussion Papers,
Nr. 6,
2024
Abstract
In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an autoregressive benchmark model in many practically relevant cases. Then, we applied GRNN to forecast quarterly German GDP growth by extending univariate GRNN to multivariate and mixed-frequency settings. We could distinguish between “normal” times and situations where the time-series behavior is very different from “normal” times such as during the COVID-19 recession and recovery. GRNN was superior in terms of root mean forecast errors compared to an autoregressive model and to more sophisticated approaches such as dynamic factor models if applied appropriately.
Artikel Lesen
Financial Technologies and the Effectiveness of Monetary Policy Transmission
Iftekhar Hasan, Boreum Kwak, Xiang Li
European Economic Review,
January
2024
Abstract
This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We use an interacted panel vector autoregression model to explore how the effects of monetary policy shocks change with regional-level FinTech adoption. Results indicate that FinTech adoption generally mitigates the transmission of monetary policy to real GDP, consumer prices, bank loans, and housing prices, with the most significant impact observed in the weakened transmission to bank loan growth. The relaxed financial constraints, regulatory arbitrage, and intensified competition are the possible mechanisms underlying the mitigated transmission.
Artikel Lesen
Conditional Macroeconomic Survey Forecasts: Revisions and Errors
Alexander Glas, Katja Heinisch
Journal of International Money and Finance,
November
2023
Abstract
Using data from the European Central Bank's Survey of Professional Forecasters and ECB/Eurosystem staff projections, we analyze the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the updating and ex-post performance of predictions for inflation, real GDP growth and unemployment are related to beliefs about future oil prices, exchange rates, interest rates and wage growth. While oil price and exchange rate predictions are updated more frequently than macroeconomic forecasts, the opposite is true for interest rate and wage growth expectations. Beliefs about future inflation are closely associated with oil price expectations, whereas expected interest rates are related to predictions of output growth and unemployment. Exchange rate predictions also matter for macroeconomic forecasts, albeit less so than the other variables. With regard to forecast errors, wage growth and GDP growth closely comove, but only during the period when interest rates are at the effective zero lower bound.
Artikel Lesen
Evidence-based Support for Adaptation Policies in Emerging Economies
Maximilian Banning, Anett Großmann, Katja Heinisch, Frank Hohmann, Christian Lutz, Christoph Schult
IWH Studies,
Nr. 2,
2023
Abstract
In recent years, the impacts of climate change become increasingly evident, both in magnitude and frequency. The design and implementation of adequate climate adaptation policies play an important role in the macroeconomic policy discourse to assess the impact of climate change on regional and sectoral economic growth. We propose different modelling approaches to quantify the socio-economic impacts of climate change and design specific adaptations in three emerging market economies (Kazakhstan, Georgia and Vietnam) which belong to the areas that are heavily exposed to climate change. A Dynamic General Equilibrium (DGE) model has been used for Vietnam and economy-energy-emission (E3) models for the other two countries. Our modelling results show how different climate hazards impact the economy up to the year 2050. Adaptation measures in particular in the agricultural sector have positive implications for the gross domestic product (GDP). However, some adaptation measures can even increase greenhouse gas emissions. In addition, the focus on GDP as the main indicator to evaluate policy measures can produce welfare-reducing policy decisions.
Artikel Lesen
Reports des European Forecasting Network (EFN)
Reports des European Forecasting Network (EFN) Das European Forecasting Network...
Zur Seite
Das IWH auf der Jahrestagung des Vereins für Socialpolitik 2019 "30 Jahre Mauerfall" - Demokratie und Marktwirtschaft
IWH-BROWN-BAG-PANEL "Ost-West-Produktivitätslücke: Ursachen und Folgen" ...
Zur Seite
Evidence-based Support for Adaptation Policies in Emerging Economies
Maximilian Banning, Anett Großmann, Katja Heinisch, Frank Hohmann, Christian Lutz, Christoph Schult
Low Carbon Economy,
Nr. 1,
2023
Abstract
Climate change is increasingly evident, and the design of effective climate adaptation policies is important for regional and sectoral economic growth. We propose different modelling approaches to quantify the socio-economic impacts of climate change on three vulnerable countries (Kazakhstan, Georgia, and Vietnam) and design specific adaptations. We use a Dynamic General Equilibrium (DGE) model for Vietnam and an economy-energy-emission (E3) model for the other two countries. Our simulations until 2050 show that selected adaptation measures, in particular in the agricultural sector, have positive implications for GDP. However, some adaptation measures can even increase greenhouse gas emissions. Focusing on GDP alone can lead to welfare-reducing policy decisions.
Artikel Lesen
COVID-19 Pandemic and Global Corporate CDS Spreads
Iftekhar Hasan, Miriam Marra, Thomas Y. To, Eliza Wu, Gaiyan Zhang
Journal of Banking and Finance,
February
2023
Abstract
We examine the impact of the COVID-19 pandemic on the credit risk of companies around the world. We find that increased infection rates affect firms more adversely as reflected by the wider increase in their credit default swap (CDS) spreads if they are larger, more leveraged, closer to default, have worse governance and more limited stakeholder engagement, and operate in more highly exposed industries. We observe that country-level determinants such as GDP, political stability, foreign direct investment, and commitment to crisis management (income support, health and lockdown policies) also affect the sensitivity of CDS spreads to COVID-19 infection rates. A negative amplification effect exists for firms with high default probability in countries with fiscal constraints. A direct comparison between global CDS and stock markets reveals that the CDS market prices in a distinct set of corporate traits and government policies in pandemic times.
Artikel Lesen
Financial Linkages and Sectoral Business Cycle Synchronization: Evidence from Europe
Hannes Böhm, Julia Schaumburg, Lena Tonzer
IMF Economic Review,
December
2022
Abstract
We analyze whether financial integration leads to converging or diverging business cycles using a dynamic spatial model. Our model allows for contemporaneous spillovers of shocks to GDP growth between countries that are financially integrated and delivers a scalar measure of the spillover intensity at each point in time. For a financial network of ten European countries from 1996 to 2017, we find that the spillover effects are positive on average and much larger during periods of financial stress, pointing towards stronger business cycle synchronization. Dismantling GDP growth into value added growth of ten major industries, we observe that spillover intensities vary significantly. The findings are robust to a variety of alternative model specifications.
Artikel Lesen