Michał Rubaszek

The paper provides a Bayesian methodological framework for the estimation of structural vector autoregression (SVAR) models with recursive identification schemes that allows for the inclusion of overidentifying restrictions. The proposed framework enables the researcher (i) to elicit the prior on non-zero contemporaneous relations between economic variables and (ii) to derive an analytical expression for the posterior distribution and marginal data density. We illustrate our methodological framework by estimating a New-Keynesian SVAR model for Poland.

Several recent studies pointed out to strong links among the most liquid core European natural gas markets. However, the evidence on the integration of less liquid, peripheral and core European markets is scarce. We address this topic by investigating the dynamics of daily natural gas prices quoted at six European hubs located in Germany, Poland, Czechia, Austria, Italy and Spain. We explore to what extend prices in these hubs are driven by price changes in the most liquid, benchmark European hub (TTF, Netherlands), other energy commodity prices (oil and coal) and local natural gas market fundamentals (whether conditions and gas inventories). We find that natural gas markets are driven by predominantly by changes in the benchmark hub as well as deviations from the law of one price. We also show that other energy commodity prices as well as idiosyncratic factors are important in the least squares regression, but not in a more elaborated GARCH model. These results adds to the discussion on the integration of European natural gas markets.

We construct currency portfolios based on the premise that exchange rates gradually converge toward their equilibrium levels, yielding three key findings. First, this convergence can be leveraged to build profitable portfolios. Second, the slow rate of convergence over shorter horizons aligns with the sustained profitability of carry trade strategies, where investors borrow in low-yield currencies and invest in high-yield ones. Third, incorporating the predictive insights of equilibrium exchange rates can boost the performance of carry trade strategies.

The Russian invasion of Ukraine triggered severe disruptions in the European energy market, causing also significant shifts in global natural gas flows. We investigate how this European shock has affected the dynamics and altered the estimates of the elasticities on the US natural gas market. We use the Bayesian Structural Vector Autoregression framework proposed by Baumeister and Hamilton (Am Econ Rev 109(5):1873–1910, 2019, BH) for the crude oil market and applied by Rubaszek et al. (Energy Econ 103:105526, 2021, RSU) to analyze the dynamics of the US natural gas market. By extending the RSU model for natural gas exports and imports and deriving model’s posterior using most recent data, we approximate the impact of the European energy crisis on the US natural gas market. We show that the estimates of the US natural gas market elasticities change due to our modification, while simply updating the same prior beliefs with most recent data impacts the posterior estimates to a very limited extent. We also find that a shock even as major as the European energy crisis has only marginally affected the US natural gas market, thus confirming the results from the literature that the EU and US natural gas markets evolve independently.

This article uses the interacted panel VAR method to analyse how institutional factors related to the structure of the housing market explain cross‐country heterogeneity in responses to macroeconomic shocks. While the previous literature focused on the stabilizing role of the mortgage market, we argue that housing tenure structure also plays an important role. In the baseline, we use data for nine OECD members to investigate how the size and regulations of the rental market affect the response of the housing market to interest rate shocks. As a reference, we also conduct a similar analysis with the mortgage market structure as the institutional factor. We find that both the rental market size and maximum loan‐to‐value ratios are important in explaining heterogeneity of housing market responses to macroeconomic shocks.

Argumenta Oeconomica, 2024, Nr 1 (52), s. 145-161