arXiv subjects

Martin Feldkircher

Publications and source records attributed to Martin Feldkircher.

6 recordsLinked to original sources

arXiv2023

Integration or fragmentation? A closer look at euro area financial markets

This paper examines the degree of integration at euro area financial markets. To that end, we estimate overall and country-specific integration indices based on a panel vector-autoregression with factor stochastic volatility. Our results indicate a more heterogeneous bond market compared to the market for lending rates. At both markets, the global financial crisis and the sovereign debt crisis led to a severe decline in financial integration, which fully recovered since then. We furthermore identify countries that deviate from their peers either by responding differently to crisis events or by taking on different roles in the spillover network. The latter analysis reveals two set of countries, namely a main body of countries that receives and transmits spillovers and a second, smaller group of spillover absorbing economies. Finally, we demonstrate by estimating an augmented Taylor rule that euro area short-term interest rates are positively linked to the level of integration on the bond market.

econ.EM↗

arXiv2022

Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs

Panel Vector Autoregressions (PVARs) are a popular tool for analyzing multi-country datasets. However, the number of estimated parameters can be enormous, leading to computational and statistical issues. In this paper, we develop fast Bayesian methods for estimating PVARs using integrated rotated Gaussian approximations. We exploit the fact that domestic information is often more important than international information and group the coefficients accordingly. Fast approximations are used to estimate the latter while the former are estimated with precision using Markov chain Monte Carlo techniques. We illustrate, using a huge model of the world economy, that it produces competitive forecasts quickly.

econ.EM↗

arXiv2020

Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession

The COVID-19 recession that started in March 2020 led to an unprecedented decline in economic activity across the globe. To fight this recession, policy makers in central banks engaged in expansionary monetary policy. This paper asks whether the measures adopted by the US Federal Reserve (Fed) have been effective in boosting real activity and calming financial markets. To measure these effects at high frequencies, we propose a novel mixed frequency vector autoregressive (MF-VAR) model. This model allows us to combine weekly and monthly information within an unified framework. Our model combines a set of macroeconomic aggregates such as industrial production, unemployment rates and inflation with high frequency information from financial markets such as stock prices, interest rate spreads and weekly information on the Feds balance sheet size. The latter set of high frequency time series is used to dynamically interpolate the monthly time series to obtain weekly macroeconomic measures. We use this setup to simulate counterfactuals in absence of monetary stimulus. The results show that the monetary expansion caused higher output growth and stock market returns, more favorable long-term financing conditions and a depreciation of the US dollar compared to a no-policy benchmark scenario.

econ.EM↗

arXiv2018

Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models

This paper proposes a straightforward algorithm to carry out inference in large time-varying parameter vector autoregressions (TVP-VARs) with mixture innovation components for each coefficient in the system. We significantly decrease the computational burden by approximating the latent indicators that drive the time-variation in the coefficients with a latent threshold process that depends on the absolute size of the shocks. The merits of our approach are illustrated with two applications. First, we forecast the US term structure of interest rates and demonstrate forecast gains of the proposed mixture innovation model relative to other benchmark models. Second, we apply our approach to US macroeconomic data and find significant evidence for time-varying effects of a monetary policy tightening.

stat.ME↗

arXiv2018

How does monetary policy affect income inequality in Japan? Evidence from grouped data

We examine the effects of monetary policy on income inequality in Japan using a novel econometric approach that jointly estimates the Gini coefficient based on micro-level grouped data of households and the dynamics of macroeconomic quantities. Our results indicate different effects on income inequality for different types of households: A monetary tightening increases inequality when income data is based on households whose head is employed (workers' households), while the effect reverses over the medium term when considering a broader definition of households. Differences in the relative strength of the transmission channels can account for this finding. Finally we demonstrate that the proposed joint estimation strategy leads to more informative inference while results based on the frequently used two-step estimation approach yields inconclusive results.

econ.EM↗

arXiv2017

Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?

We assess the relationship between model size and complexity in the time-varying parameter VAR framework via thorough predictive exercises for the Euro Area, the United Kingdom and the United States. It turns out that sophisticated dynamics through drifting coefficients are important in small data sets, while simpler models tend to perform better in sizeable data sets. To combine the best of both worlds, novel shrinkage priors help to mitigate the curse of dimensionality, resulting in competitive forecasts for all scenarios considered. Furthermore, we discuss dynamic model selection to improve upon the best performing individual model for each point in time.

stat.ME↗