IDEAS home Printed from https://ideas.repec.org/a/wly/econjl/vy2015i584p746-776.html
   My bibliography  Save this article

Estimating Fiscal Multipliers: News From A Non‐linear World

Author

Listed:
  • Giovanni Caggiano
  • Efrem Castelnuovo
  • Valentina Colombo
  • Gabriela Nodari

Abstract

We estimate nonlinear VARs to assess to what extent .scal spending multipliers are countercyclical in the United States. We deal with the issue of non-fundamentalness due to .scal foresight by appealing to sums of revisions of expectations of .scal expenditures. This measure of anticipated .scal shocks is shown to carry valuable information about future dynamics of public spending. Results based on generalized impulse responses suggest that .scal spending multipliers in recessions are greater than one, but not statistically larger than those in expansions. However, nonlinearities arise when focusing on "extreme" events, i.e., deep recessions vs. strong expansionary periods.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Giovanni Caggiano & Efrem Castelnuovo & Valentina Colombo & Gabriela Nodari, 2015. "Estimating Fiscal Multipliers: News From A Non‐linear World," Economic Journal, Royal Economic Society, vol. 0(584), pages 746-776, May.
    • Handle: RePEc:wly:econjl:v::y:2015:i:584:p:746-776
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/ecoj.2015.125.issue-584
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Alan J. Auerbach & Yuriy Gorodnichenko, 2012. "Measuring the Output Responses to Fiscal Policy," American Economic Journal: Economic Policy, American Economic Association, vol. 4(2), pages 1-27, May.
    2. Eric R. Sims, 2012. "News, Non-Invertibility, and Structural VARs," Advances in Econometrics, in: DSGE Models in Macroeconomics: Estimation, Evaluation, and New Developments, pages 81-135, Emerald Group Publishing Limited.
    3. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
    4. Domenico Giannone & Lucrezia Reichlin, 2006. "Does information help recovering structural shocks from past observations?," Journal of the European Economic Association, MIT Press, vol. 4(2-3), pages 455-465, 04-05.
    5. Paul Beaudry & Franck Portier, 2014. "News-Driven Business Cycles: Insights and Challenges," Journal of Economic Literature, American Economic Association, vol. 52(4), pages 993-1074, December.
    6. Olivier J. Blanchard & Daniel Leigh, 2013. "Growth Forecast Errors and Fiscal Multipliers," American Economic Review, American Economic Association, vol. 103(3), pages 117-120, May.
    7. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    8. Mario Forni & Luca Gambetti & Marco Lippi & Luca Sala, 2017. "Noisy News in Business Cycles," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(4), pages 122-152, October.
    9. Dario Caldara & Christophe Kamps, 2017. "The Analytics of SVARs: A Unified Framework to Measure Fiscal Multipliers," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(3), pages 1015-1040.
    10. Forni, Mario & Gambetti, Luca, 2010. "Fiscal Foresight and the Effects of Goverment Spending," CEPR Discussion Papers 7840, C.E.P.R. Discussion Papers.
    11. Eric M. Leeper & Todd B. Walker & Shu‐Chun Susan Yang, 2013. "Fiscal Foresight and Information Flows," Econometrica, Econometric Society, vol. 81(3), pages 1115-1145, May.
    12. Fève, Patrick & Matheron, Julien & Sahuc, Jean-Guillaume, 2009. "On the dynamic implications of news shocks," Economics Letters, Elsevier, vol. 102(2), pages 96-98, February.
    13. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    14. Ricco, Giovanni, 2015. "A new identification of fiscal shocks based on the information flow," Working Paper Series 1813, European Central Bank.
    15. Olivier Blanchard & Roberto Perotti, 2002. "An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1329-1368.
    16. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    17. Lippi, Marco & Reichlin, Lucrezia, 1993. "The Dynamic Effects of Aggregate Demand and Supply Disturbances: Comment," American Economic Review, American Economic Association, vol. 83(3), pages 644-652, June.
    18. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    19. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    20. Valerie A. Ramey & Sarah Zubairy, 2018. "Government Spending Multipliers in Good Times and in Bad: Evidence from US Historical Data," Journal of Political Economy, University of Chicago Press, vol. 126(2), pages 850-901.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    2. Forni, Mario & Gambetti, Luca, 2016. "Government spending shocks in open economy VARs," Journal of International Economics, Elsevier, vol. 99(C), pages 68-84.
    3. Andrea Boitani & Salvatore Perdichizzi, 2018. "Public Expenditure Multipliers in recessions. Evidence from the Eurozone," DISCE - Working Papers del Dipartimento di Economia e Finanza def068, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    4. Fotiou, Alexandra & Shen, Wenyi & Yang, Shu-Chun S., 2020. "The fiscal state-dependent effects of capital income tax cuts," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    5. Amendola, Adalgiso & Di Serio, Mario & Fragetta, Matteo & Melina, Giovanni, 2020. "The euro-area government spending multiplier at the effective lower bound," European Economic Review, Elsevier, vol. 127(C).
    6. Soccorsi, Stefano, 2016. "Measuring nonfundamentalness for structural VARs," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 86-101.
    7. Ben Zeev, Nadav, 2018. "What can we learn about news shocks from the late 1990s and early 2000s boom-bust period?," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 94-105.
    8. Nadav Ben Zeev, 2019. "Is There A Single Shock That Drives The Majority Of Business Cycle Fluctuations?," Working Papers 1906, Ben-Gurion University of the Negev, Department of Economics.
    9. Salvatore Perdichizzi, 2017. "Estimating Fiscal multipliers in the Eurozone. A Nonlinear Panel Data Approach," DISCE - Working Papers del Dipartimento di Economia e Finanza def058, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    10. Forni, Mario & Gambetti, Luca, 2014. "Sufficient information in structural VARs," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 124-136.
    11. Di Serio, Mario & Fragetta, Matteo & Melina, Giovanni, 2021. "The impact of r-g on Euro-Area government spending multipliers," Journal of International Money and Finance, Elsevier, vol. 119(C).
    12. Pallara, Kevin, 2016. "The dynamic effects of government spending: a FAVAR approach," MPRA Paper 92283, University Library of Munich, Germany.
    13. Mario Forni & Luca Gambetti & Luca Sala, 2018. "Fundamentalness, Granger Causality and Aggregation," Center for Economic Research (RECent) 139, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    14. Kang, Jihye & Kim, Soyoung, 2022. "Government spending news and surprise shocks: It’s the timing and persistence," Journal of Macroeconomics, Elsevier, vol. 73(C).
    15. Danilo Cascaldi-Garcia, 2022. "Forecast Revisions as Instruments for News Shocks," International Finance Discussion Papers 1341, Board of Governors of the Federal Reserve System (U.S.).
    16. Valerie A. Ramey, 2019. "Ten Years after the Financial Crisis: What Have We Learned from the Renaissance in Fiscal Research?," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 89-114, Spring.
    17. Britta Gehrke & Brigitte Hochmuth, 2021. "Counteracting Unemployment in Crises: Non‐Linear Effects of Short‐Time Work Policy," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(1), pages 144-183, January.
    18. Efrem Castelnuovo & Guay Lim, 2019. "What Do We Know About the Macroeconomic Effects of Fiscal Policy? A Brief Survey of the Literature on Fiscal Multipliers," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 52(1), pages 78-93, March.
    19. Emilio Colombo & Davide Furceri & Pietro Pizzuto & Patrizio Tirelli, 2022. "Fiscal Multipliers and Informality," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis2201, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
    20. Born, Benjamin & Peter, Alexandra & Pfeifer, Johannes, 2013. "Fiscal news and macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2582-2601.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:econjl:v::y:2015:i:584:p:746-776. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/resssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.