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Banking and Currency Crises: Differential Diagnostics for Developed Countries
Joy, Mark ; Rusnák, Marek ; Šmídková, Kateřina ; Vašíček, Bořek
We identify a set of “rules of thumb” that characterise economic, financial and structural conditions preceding the onset of banking and currency crises in 36 advanced economies over 1970–2010. We use the Classification and Regression Tree methodology (CART) and its Random Forest (RF) extension, which permits the detection of key variables driving binary crisis outcomes, allows for interactions among key variables and determines critical tipping points. We distinguish between basic country conditions, country structural characteristics and international developments. We find that crises are more varied than they are similar. For banking crises we find that low net interest rate spreads in the banking sector and a shallow or inverted yield curve are their most important forerunners in the short term, whereas in the longer term it is high house price inflation. For currency crises, high domestic short-term rates coupled with overvalued exchange rates are the most powerful short-term predictors. We find that both country structural characteristics and international developments are relevant banking crisis predictors. Currency crises, however, seem to be driven more by country idiosyncratic, short-term developments. We find that some variables, such as the domestic credit gap, provide important unconditional signals, but it is difficult to use them as conditional signals and, more importantly, to find relevant threshold values.
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Forecasting Czech GDP Using Mixed-Frequency Data Models
Franta, Michal ; Havrlant, David ; Rusnák, Marek
In this paper we use a battery of various mixed-frequency data models to forecast Czech GDP. The models employed are mixed-frequency vector autoregressions, mixed-data sampling models, and the dynamic factor model. Using a dataset of historical vintages of unrevised macroeconomic and financial data, we evaluate the performance of these models over the 2005–2012 period and compare them with the Czech National Bank’s macroeconomic forecasts. The results suggest that for shorter forecasting horizons the accuracy of the dynamic factor model is comparable to the CNB forecasts. At longer horizons, mixed-frequency vector autoregressions are able to perform similarly or slightly better than the CNB forecasts. Furthermore, moving away from point forecasts, we also explore the potential of density forecasts from Bayesian mixed-frequency vector autoregressions.
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Cross-Country Heterogeneity in Intertemporal Substitution
Havránek, Tomáš ; Horváth, Roman ; Iršová, Zuzana ; Rusnák, Marek
We collect 2,735 estimates of the elasticity of intertemporal substitution in consumption from 169 published studies that cover 104 countries during different time periods. The estimates vary substantially from country to country, even after controlling for 30 aspects of study design. Our results suggest that income and asset market participation are the most effective factors in explaining the heterogeneity: households in rich countries and countries with high stock market participation substitute a larger fraction of consumption intertemporally in response to changes in expected asset returns. Micro-level studies that focus on sub-samples of rich households or asset holders also find systematically larger values of the elasticity.
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Nowcasting Czech GDP in Real Time
Rusnák, Marek
The prominent measure of the current state of the Czech economy, gross domestic product (GDP), is available only with a significant lag of roughly 70 days. In this paper, we employ a Dynamic Factor Model (DFM) to nowcast Czech GDP in real time. Using multiple vintages of historical data and taking into account the publication lags of various monthly indicators, we evaluate the real-time performance of the DFM over the 2005– 2012 period. The results suggest that the accuracy of model-based nowcasts is comparable to that of the judgmental nowcasts of the Czech National Bank (CNB). Our results also suggest that foreign variables are crucial for the accuracy of the model, while omitting financial and confidence indicators does not worsen the nowcasting performance. Finally, we show how releases of new data can be viewed through the lens of the dynamic factor model.
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Transmission Lags of Monetary Policy: A Meta-Analysis
Havránek, Tomáš ; Rusnák, Marek
The transmission of monetary policy to the economy is generally thought to have long and variable lags. In this paper we quantitatively review the modern literature on monetary transmission to provide stylized facts on the average lag length and the sources of variability. We collect 67 published studies and examine when prices bottom out after a monetary contraction. The average transmission lag is 29 months, and the maximum decrease in prices reaches 0.9% on average after a one-percentage-point hike in the policy rate. Transmission lags are longer in large developed countries (25–50 months) than in new EU member countries (10–20 months). We find that the factor most effective in explaining this heterogeneity is financial development: greater financial development is associated with slower transmission. Moreover, greater trade openness in new EU member countries seems to be associated with faster transmission. Our results also suggest that researchers who use monthly data instead of quarterly data report systematically faster transmission. JEL
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