The Analytics of SVARs: A Unified Framework to Measure Fiscal Multipliers

Caldara, Dario; Kamps, Christophe

doi:10.2139/ssrn.2054795

Cited by 80 publications

(147 citation statements)

References 24 publications

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“…12 This identification strategy differs from the pure sign restriction identification approach, in that both of our identification schemes identify a single structural VAR specification, rather than a set of models (Caldara and Kamps, 2012;Arias et al, 2013).…”

Section: Identification and Estimationmentioning

confidence: 99%

The Macroeconomic Impact of Financial and Uncertainty Shocks

Caldara¹,

Fuentes-Albero²,

Gilchrist³

et al. 2016

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We are especially grateful to Johannes Pfeifer and Jim Stock for detailed comments and suggestions. We also thank Nicholas Bloom, Robert Kollman, Eric Leeper, Tommaso Monacelli, Werner Roeger, and participants at numerous seminars and conferences for helpful comments. George Gu, Edward Kim, Shaily Patel, and Rebecca Zhang provided outstanding research assistance at various stages of this project. All errors and omissions are our own responsibility. The views expressed in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Board of Governors of the Federal Reserve System, anyone else associated with the Federal Reserve System, or the National Bureau of Economic Research.NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.© 2016 by Dario Caldara, Cristina Fuentes-Albero, Simon Gilchrist, and Egon Zakrajšek. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. ABSTRACTThe extraordinary events surrounding the Great Recession have cast a considerable doubt on the traditional sources of macroeconomic instability. In their place, economists have singled out financial and uncertainty shocks as potentially important drivers of economic fluctuations. Empirically distinguishing between these two types of shocks, however, is difficult because increases in economic uncertainty are strongly associated with a widening of credit spreads, an indication of a tightening in financial conditions. This paper uses the penalty function approach within the SVAR framework to examine the interaction between financial conditions and economic uncertainty and to trace out the impact of these two types of shocks on the economy. The results indicate that (1) financial shocks have a significant adverse effect on economic outcomes and that such shocks were an important source of cyclical fluctuations since the mid-1980s; (2) uncertainty shocks, especially those implied by uncertainty proxies that do not rely on financial asset prices, are also an important source of macroeconomic disturbances; and (3) uncertainty shocks have an especially negative economic impact in situations where they elicit a concomitant tightening of financial conditions. Evidence suggests that the Great Recession was likely an acute manifestation of the toxic interaction between uncertainty and financial shocks.

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Section: Identification and Estimationmentioning

confidence: 99%

The Macroeconomic Impact of Financial and Uncertainty Shocks

Caldara¹,

Fuentes-Albero²,

Gilchrist³

et al. 2016

Self Cite

View full text Add to dashboard Cite

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“…A similar identification strategy to the one used in this paper is employed by Caldara and Kamps (2012), who identify tax and government spending shocks by putting discipline on the systematic component of fiscal policy. They combine zero restrictions with empirically plausible bounds on the output elasticities of fiscal variables.…”

Section: Introductionmentioning

confidence: 99%

The Systematic Component of Monetary Policy in SVARs: An Agnostic Identification Procedure

Arias

Caldara

Rubio-Ramı́rez

2015

internationalfinance

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“…Social security adds to progressivity, such that the overall net-revenue budget strongly reacts to a change in GDP. Caldara and Kamps (2012) show that within a reasonable range of α τ y , not even the sign of the resulting multiplier can be robustly estimated, such that both negative and large positive multipliers can occur. The very nature of the BP approach for estimating revenue multipliers, however, rests upon the assumption of a certain value of α τ y that is imposed as a scalar without taking into account likely uncertainty around this figure.…”

Section: Model Data and Identificationmentioning

confidence: 94%

Top-Down vs. Bottom-Up? Reconciling the Effects of Tax and Transfer Shocks on Output

2017

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in ABSTRACTUsing the bottom-up approach of Romer and Romer (2010), we construct a rich narrative dataset of net-revenue fiscal shocks for Germany by reconstructing and extending the tax shock series of Hayo and Uhl (2014) and coding a shock series for social security contributions, benefits and transfers. Based on quarterly data for 1974q1 to 2013q4 we estimate the multiplier effects of shocks to net-revenues, taxes, social security contributions and benefits in a proxy SVAR framework (Mertens and Ravn 2013) and compare them with estimates of the top-down identification inspired by Blanchard and Perotti (2002). We find multiplier effects of net-revenue components for Germany between 0 and 1 for both the top-down and bottom-up approaches. These estimates are on the lower end of the scale given in the literature and we discuss the differences. (2010), we construct a rich narrative dataset of net-revenue fiscal shocks for Germany by reconstructing and extending the tax shock series of Hayo and Uhl (2014) and coding a shock series for social security contributions, benefits and transfers. Based on quarterly data for 1974q1 to 2013q4 we estimate the multiplier effects of shocks to net-revenues, taxes, social security contributions and benefits in a proxy SVAR framework (Mertens and Ravn 2013) and compare them with estimates of the top-down identification inspired by Blanchard and Perotti (2002). We find multiplier effects of net-revenue components for Germany between 0 and 1 for both the top-down and bottom-up approaches. These estimates are on the lower end of the scale given in the literature and we discuss the differences.

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The Analytics of SVARs: A Unified Framework to Measure Fiscal Multipliers

Cited by 80 publications

References 24 publications

The Macroeconomic Impact of Financial and Uncertainty Shocks

The Macroeconomic Impact of Financial and Uncertainty Shocks

The Systematic Component of Monetary Policy in SVARs: An Agnostic Identification Procedure

Top-Down vs. Bottom-Up? Reconciling the Effects of Tax and Transfer Shocks on Output

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