Advances in Using Vector Autoregressions to Estimate Structural Magnitudes
Christiane Baumeister, James D. Hamilton
Econometric Theory,
No. 3,
2024
Abstract
This paper surveys recent advances in drawing structural conclusions from vector autoregressions (VARs), providing a unified perspective on the role of prior knowledge. We describe the traditional approach to identification as a claim to have exact prior information about the structural model and propose Bayesian inference as a way to acknowledge that prior information is imperfect or subject to error. We raise concerns from both a frequentist and a Bayesian perspective about the way that results are typically reported for VARs that are set-identified using sign and other restrictions. We call attention to a common but previously unrecognized error in estimating structural elasticities and show how to correctly estimate elasticities even in the case when one only knows the effects of a single structural shock.
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Herding Behavior and Systemic Risk in Global Stock Markets
Iftekhar Hasan, Radu Tunaru, Davide Vioto
Journal of Empirical Finance,
September
2023
Abstract
This paper provides new evidence of herding due to non- and fundamental information in global equity markets. Using quantile regressions applied to daily data for 33 countries, we investigate herding during the Eurozone crisis, China’s market crash in 2015–2016, in the aftermath of the Brexit vote and during the Covid-19 Pandemic. We find significant evidence of herding driven by non-fundamental information in case of negative tail market conditions for most countries. This study also investigates the relationship between herding and systemic risk, suggesting that herding due to fundamentals increases when systemic risk increases more than when driven by non-fundamentals. Granger causality tests and Johansen’s vector error-correction model provide solid empirical evidence of a strong interrelationship between herding and systemic risk, entailing that herding behavior may be an ex-ante aspect of systemic risk, with a more relevant role played by herding based on fundamental information in increasing systemic risk.
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Advances in Using Vector Autoregressions to Estimate Structural Magnitudes
Christiane Baumeister, James D. Hamilton
Abstract
This paper discusses drawing structural conclusions from vector autoregressions. We call attention to a common error in estimating structural elasticities and show how to correctly estimate elasticities even in the case when one knows only the effects of a single structural shock and the covariance matrix of the reduced-form residuals. We describe the traditional approach to identification as a claim to have exact prior information about the structural model and propose Bayesian inference as a way to acknowledge that prior information is imperfect or subject to error. We raise concerns about the way that results are typically reported for VARs that are set-identified using sign and other restrictions.
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Cryptocurrency Volatility Markets
Fabian Wöbbeking
Digital Finance,
No. 3,
2021
Abstract
By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.
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Regulation, Innovation and Technology Diffusion - Evidence from Building Energy Efficiency Standards in Germany
Makram El-Shagi, Claus Michelsen, Sebastian Rosenschon
Discussionpapers des DIW Berlin,
No. 1371,
2014
Abstract
The impact of environmental regulation on technology diffusion and innovations is studied using a unique data set of German residential buildings. We analyze how energy efficiency regulations, in terms of minimum standards, affects energy-use in newly constructed buildings and how it induces innovation in the residential-building industry. The data used consists of a large sample of German apartment houses built between 1950 and 2005. Based on this information, we determine their real energy requirements from energy performance certificates and energy billing information. We develop a new measure for regulation intensity and apply a panel-error-correction regression model to energy requirements of low and high quality housing. Our findings suggest that regulation significantly impacts technology adoption in low quality housing. This, in turn, induces improvements in the high quality segment where innovators respond to market signals.
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A Federal Long-run Projection Model for Germany
Oliver Holtemöller, Maike Irrek, Birgit Schultz
IWH Discussion Papers,
No. 11,
2012
Abstract
Many economic decisions implicitly or explicitly rely on a projection of the medium- or long-term economic development of a country or region. In this paper, we provide a federal long-run projection model for Germany and the German states. The model fea-tures a top-down approach and, as major contribution, uses error correction models to estimate the regional economic development dependent on the national projection. For the medium- and long-term projection of economic activity, we apply a production function approach. We provide a detailed robustness analysis by systematically varying assumptions of the model. Additionally, we explore the effects of different demographic trends on economic development.
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An Evolutionary Algorithm for the Estimation of Threshold Vector Error Correction Models
Makram El-Shagi
International Economics and Economic Policy,
No. 4,
2011
Abstract
We develop an evolutionary algorithm to estimate Threshold Vector Error Correction models (TVECM) with more than two cointegrated variables. Since disregarding a threshold in cointegration models renders standard approaches to the estimation of the cointegration vectors inefficient, TVECM necessitate a simultaneous estimation of the cointegration vector(s) and the threshold. As far as two cointegrated variables are considered, this is commonly achieved by a grid search. However, grid search quickly becomes computationally unfeasible if more than two variables are cointegrated. Therefore, the likelihood function has to be maximized using heuristic approaches. Depending on the precise problem structure the evolutionary approach developed in the present paper for this purpose saves 90 to 99 per cent of the computation time of a grid search.
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Where Are Global and U.S. Trade Heading in the Aftermath of the Trade Collapse: Issues and Alternative Scenarios
Filippo di Mauro, Joseph Gruber, Bernd Schnatz, Nico Zorell
FRB International Finance Discussion Paper,
No. 1017,
2011
Abstract
Global and U.S. trade declined dramatically in the wake of the global financial crisis in late 2008 and early 2009. The subsequent recovery in trade, while vigorous at first, gradually lost momentum in 2010. Against this backdrop, this paper explores the prospects for global and U.S. trade in the medium term. We develop a unified empirical framework ? an error correction model ? that exploits the cointegrating relationship between trade and economic activity. The model allows us to juxtapose several scenarios with different assumptions about the strength of GDP growth going forward and the relationship between trade and economic activity. Our analysis suggests that during the crisis both world trade and U.S. exports declined significantly more than would have been expected on the basis of historical relationships with economic activity. Moreover, this gap between actual and equilibrium trade is closing only slowly and could persist for some time to come.
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The Quantity Theory Revisited: A New Structural Approach
Makram El-Shagi, Sebastian Giesen
Abstract
While the long run relation between money and inflation is well established, empirical evidence on the adjustment to the long run equilibrium is very heterogeneous. In this paper we show, that the development of US consumer price inflation between 1960Q1 and 2005Q4 is strongly driven by money overhang. To this end, we use a multivariate state space framework that substantially expands the traditional vector error correction approach. This approach allows us to estimate the persistent components of velocity and GDP. A sign restriction approach is subsequently used to identify the structural shocks to the signal equations of the state space model, that explain money growth, inflation and GDP growth. We also account for the possibility that measurement error exhibited by simple-sum monetary aggregates causes the consequences of monetary shocks to be improperly identified by using a Divisia monetary aggregate. Our findings suggest that when the money is measured using a reputable index number, the quantity theory holds for the United States.
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Money and Inflation: The Role of Persistent Velocity Movements
Makram El-Shagi, Sebastian Giesen
Abstract
While the long run relation between money and inflation is well established, empirical evidence on the adjustment to the long run equilibrium is very heterogeneous. In the present paper we use a multivariate state space framework, that substantially expands the traditional vector error correction approach, to analyze the short run impact of money on prices. We contribute to the literature in three ways: First, we distinguish changes in velocity of money that are due to institutional developments and thus do not induce inflationary pressure, and changes that reflect transitory movements in money demand. This is achieved with a newly developed multivariate unobserved components decomposition. Second, we analyze whether the high volatility of the transmission from monetary pressure to inflation follows some structure, i.e., if the parameter regime can assumed to be constant. Finally, we use our model to illustrate the consequences of the monetary policy of the Fed that has been employed to mitigate the impact of the financial crisis, simulating different exit strategy scenarios.
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