Real Estate Transaction Taxes and Credit Supply
Michael Koetter, Philipp Marek, Antonios Mavropoulos
Deutsche Bundesbank Discussion Paper,
Nr. 4,
2021
Abstract
We exploit staggered real estate transaction tax (RETT) hikes across German states to identify the effect of house price changes on mortgage credit supply. Based on approximately 33 million real estate online listings, we construct a quarterly hedonic house price index (HPI) between 2008:q1 and 2017:q4, which we instrument with state-speci c RETT changes to isolate the effect on mortgage credit supply by all local German banks. First, a RETT hike by one percentage point reduces HPI by 1.2%. This effect is driven by listings in rural regions. Second, a 1% contraction of HPI induced by an increase in the RETT leads to a 1.4% decline in mortgage lending. This transmission of fiscal policy to mortgage credit supply is effective across almost the entire bank capitalization distribution.
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Financial Technologies and the Effectiveness of Monetary Policy Transmission
Iftekhar Hasan, Boreum Kwak, Xiang Li
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.
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Energy Markets and Global Economic Conditions
Christiane Baumeister, Dimitris Korobilis, Thomas K. Lee
Abstract
This paper evaluates alternative indicators of global economic activity and other market fundamentals in terms of their usefulness for forecasting real oil prices and global petroleum consumption. We find that world industrial production is one of the most useful indicators that has been proposed in the literature. However, by combining measures from a number of different sources we can do even better. Our analysis results in a new index of global economic conditions and new measures for assessing future tightness of energy demand and expected oil price pressures.
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Stress Tests and Small Business Lending
Kristle R. Cortés, Yuliya Demyanyk, Lei Li, Elena Loutskina, Philip E. Strahan
Journal of Financial Economics,
Nr. 1,
2020
Abstract
Post-crisis stress tests have altered banks’ credit supply to small business. Banks most affected by stress tests reallocate credit away from riskier markets and toward safer ones. They also raise interest rates on small loans. Quantities fall most in high-risk markets where stress-tested banks own no branches, and prices rise mainly where they do. The results suggest that banks price the stress-test induced increase in capital requirements where they have local knowledge, and exit where they do not. Stress tests do not, however, reduce aggregate credit. Small banks seem to increase their share in geographies formerly reliant on stress-tested lenders.
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Financial Linkages and Sectoral Business Cycle Synchronisation: Evidence from Europe
Hannes Böhm, Julia Schaumburg, Lena Tonzer
Abstract
We analyse whether financial integration between countries 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 1996-2017, we find that the spillover effects are positive on average but much larger during periods of financial stress, pointing towards stronger business cycle synchronisation. Dismantling GDP growth into value added growth of ten major industries, we observe that some sectors are strongly affected by positive spillovers (wholesale & retail trade, industrial production), others only to a weaker degree (agriculture, construction, finance), while more nationally influenced industries show no evidence for significant spillover effects (public administration, arts & entertainment, real estate).
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Total Factor Productivity and the Terms of Trade
Jan Teresinski
IWH-CompNet Discussion Papers,
Nr. 6,
2019
Abstract
In this paper we analyse how the terms of trade (TOT) – the ratio of export prices to import prices – affect total factor productivity (TFP). We provide empirical macroeconomic evidence for the European Union countries based on the times series SVAR analysis and microeconomic evidence based on industry level data from the Competitiveness Research Network (CompNet) database which shows that the terms of trade improvements are associated with a slowdown in the total factor productivity growth. Next, we build a theoretical model which combines open economy framework with the endogenous growth theory. In the model the terms of trade improvements increase demand for labour employed in exportable goods production at the expense of technology production (research and development – R&D) which leads to a shift of resources from knowledge development towards physical exportable goods. This reallocation has a negative impact on the TFP growth. Under a plausible calibration the model is able to replicate the observed empirical pattern.
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Resolving the Missing Deflation Puzzle
Jesper Lindé, Mathias Trabandt
Abstract
We propose a resolution of the missing deflation puzzle. Our resolution stresses the importance of nonlinearities in price- and wage-setting when the economy is exposed to large shocks. We show that a nonlinear macroeconomic model with real rigidities resolves the missing deflation puzzle, while a linearized version of the same underlying nonlinear model fails to do so. In addition, our nonlinear model reproduces the skewness of inflation and other macroeconomic variables observed in post-war U.S. data. All told, our results caution against the common practice of using linearized models to study inflation and output dynamics.
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Should We Use Linearized Models To Calculate Fiscal Multipliers?
Jesper Lindé, Mathias Trabandt
Journal of Applied Econometrics,
Nr. 7,
2018
Abstract
We calculate the magnitude of the government consumption multiplier in linearized and nonlinear solutions of a New Keynesian model at the zero lower bound. Importantly, the model is amended with real rigidities to simultaneously account for the macroeconomic evidence of a low Phillips curve slope and the microeconomic evidence of frequent price changes. We show that the nonlinear solution is associated with a much smaller multiplier than the linearized solution in long‐lived liquidity traps, and pin down the key features in the model which account for the difference. Our results caution against the common practice of using linearized models to calculate fiscal multipliers in long‐lived liquidity traps.
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Information Feedback in Temporal Networks as a Predictor of Market Crashes
Stjepan Begušić, Zvonko Kostanjčar, Dejan Kovač, Boris Podobnik, H. Eugene Stanley
Complexity,
September
2018
Abstract
In complex systems, statistical dependencies between individual components are often considered one of the key mechanisms which drive the system dynamics observed on a macroscopic level. In this paper, we study cross-sectional time-lagged dependencies in financial markets, quantified by nonparametric measures from information theory, and estimate directed temporal dependency networks in financial markets. We examine the emergence of strongly connected feedback components in the estimated networks, and hypothesize that the existence of information feedback in financial networks induces strong spatiotemporal spillover effects and thus indicates systemic risk. We obtain empirical results by applying our methodology on stock market and real estate data, and demonstrate that the estimated networks exhibit strongly connected components around periods of high volatility in the markets. To further study this phenomenon, we construct a systemic risk indicator based on the proposed approach, and show that it can be used to predict future market distress. Results from both the stock market and real estate data suggest that our approach can be useful in obtaining early-warning signals for crashes in financial markets.
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