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Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy

Author

Listed:
  • Antonello D’Agostino

    (ESM)

  • Jacopo Cimadomo

    (ECB)

Abstract

In this paper, we propose a time-varying parameter vector autoregression (VAR) model with stochastic volatility which allows for estimation on data sampled at different frequencies. Our contribution is two-fold. First, we extend the methodology developed by Cogley and Sargent (2005), and Primiceri (2005), to a mixed-frequency setting. In particular, our approach allows for the inclusion of two different categories of variables (high-frequency and low-frequency) into the same time-varying model. Second, we use this model to study the macroeconomic effects of government spending shocks in Italy over the 1988 Q4-2013 Q3 period. Italy - as well as most other euro area economies - is characterised by short quarterly time series for fiscal variables, whereas annual data are generally available for a longer sample before 1999. Our results show that the proposed time-varying mixed-frequency model improves on the performance of a simple linear interpolation model in generating the true path of the missing observations. Second, our empirical analysis suggests that government spending shocks tend to have positive effects on output in Italy. The fiscal multiplier, which is maximized at the one year horizon, follows a U-shape over the sample considered: it peaks at around 1.5 at the beginning of the sample, it then stabilizes between 0.8 and 0.9 from the mid-1990s to the late 2000s, before rising again to above unity during the recent crisis.

Suggested Citation

  • Antonello D’Agostino & Jacopo Cimadomo, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Papers 7, European Stability Mechanism.
  • Handle: RePEc:stm:wpaper:7
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    References listed on IDEAS

    as
    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    3. Roberto Perotti, 2008. "In Search of the Transmission Mechanism of Fiscal Policy," NBER Chapters,in: NBER Macroeconomics Annual 2007, Volume 22, pages 169-226 National Bureau of Economic Research, Inc.
    4. Karel Mertens & MortenO. Ravn, 2010. "Measuring the Impact of Fiscal Policy in the Face of Anticipation: A Structural VAR Approach," Economic Journal, Royal Economic Society, vol. 120(544), pages 393-413, May.
    5. Marcellino, Massimiliano, 2006. "Some stylized facts on non-systematic fiscal policy in the Euro area," Journal of Macroeconomics, Elsevier, vol. 28(3), pages 461-479, September.
    6. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
    7. D’Agostino, Antonello & Ehrmann, Michael, 2014. "The pricing of G7 sovereign bond spreads – The times, they are a-changin," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 155-176.
    8. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    9. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    10. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    11. Jordi Galí & J. David López-Salido & Javier Vallés, 2007. "Understanding the Effects of Government Spending on Consumption," Journal of the European Economic Association, MIT Press, vol. 5(1), pages 227-270, March.
    12. Pereira Manuel Coutinho & Lopes Artur Silva, 2014. "Time-varying fiscal policy in the US," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(2), pages 1-28, April.
    13. Cimadomo, Jacopo & Bénassy-Quéré, Agnès, 2012. "Changing patterns of fiscal policy multipliers in Germany, the UK and the US," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 845-873.
    14. Roel Beetsma & Massimo Giuliodori, 2011. "The Effects of Government Purchases Shocks: Review and Estimates for the EU," Economic Journal, Royal Economic Society, vol. 121(550), pages 4-32, February.
    15. Jordi Galí & Luca Gambetti, 2015. "The Effects of Monetary Policy on Stock Market Bubbles: Some Evidence," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 233-257, January.
    16. Andrew Mountford & Harald Uhlig, 2009. "What are the effects of fiscal policy shocks?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 960-992.
    17. Lawrence Christiano & Martin Eichenbaum & Sergio Rebelo, 2011. "When Is the Government Spending Multiplier Large?," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 78-121.
    18. Giancarlo Corsetti & André Meier & Gernot J. Müller, 2012. "What determines government spending multipliers?," Economic Policy, CEPR;CES;MSH, vol. 27(72), pages 521-565, October.
    19. Onorante, Luca & Pedregal, Diego J. & Pérez, Javier J. & Signorini, Sara, 2010. "The usefulness of infra-annual government cash budgetary data for fiscal forecasting in the euro area," Journal of Policy Modeling, Elsevier, vol. 32(1), pages 98-119, January.
    20. Antonello D’Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2016. "Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 569-594 Emerald Publishing Ltd.
    21. S. J. Koopman & J. Durbin, 2003. "Filtering and smoothing of state vector for diffuse state-space models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 85-98, January.
    22. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
    23. Massimiliano Marcellino & Mario Porqueddu & Fabrizio Venditti, 2016. "Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 118-127, January.
    24. Éric Jacquier & Nicholas G. Polson & Peter E. Rossi, 1995. "Models and Priors for Multivariate Stochastic Volatility," CIRANO Working Papers 95s-18, CIRANO.
    25. Markus Kirchner & Jacopo Cimadomo & Sebastian Hauptmeier, 2010. "Transmission of Government Spending Shocks in the Euro Area: Time Variation and Driving Forces," Tinbergen Institute Discussion Papers 10-021/2, Tinbergen Institute.
    26. Paredes, Joan & Pedregal, Diego J. & Pérez, Javier J., 2009. "A quarterly fiscal database for the euro area based on intra-annual fiscal information," Working Paper Series 1132, European Central Bank.
    27. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    28. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.
    29. Gonzalo Camba-Mendez & Ana Lamo, 2004. "Short-term monitoring of fiscal policy discipline," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 247-265.
    30. Alan J. Auerbach & Yuriy Gorodnichenko, 2012. "Fiscal Multipliers in Recession and Expansion," NBER Chapters,in: Fiscal Policy after the Financial Crisis, pages 63-98 National Bureau of Economic Research, Inc.
    31. 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, Oxford University Press, vol. 117(4), pages 1329-1368.
    32. Giordano, Raffaela & Momigliano, Sandro & Neri, Stefano & Perotti, Roberto, 2007. "The effects of fiscal policy in Italy: Evidence from a VAR model," European Journal of Political Economy, Elsevier, vol. 23(3), pages 707-733, September.
    33. Günter Coenen & Christopher J. Erceg & Charles Freedman & Davide Furceri & Michael Kumhof & René Lalonde & Douglas Laxton & Jesper Lindé & Annabelle Mourougane & Dirk Muir & Susanna Mursula & Carlos d, 2012. "Effects of Fiscal Stimulus in Structural Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(1), pages 22-68, January.
    34. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
    35. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
    36. Caldara, Dario & Kamps, Christophe, 2008. "What are the effects of fiscal policy shocks? A VAR-based comparative analysis," Working Paper Series 877, European Central Bank.
    37. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
    38. Fatás, Antonio & Mihov, Ilian, 2001. "The Effects of Fiscal Policy on Consumption and Employment: Theory and Evidence," CEPR Discussion Papers 2760, C.E.P.R. Discussion Papers.
    39. Anja Baum & Marcos Poplawski-Ribeiro & Anke Weber, 2012. "Fiscal Multipliers and the State of the Economy," IMF Working Papers 12/286, International Monetary Fund.
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    Citations

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    Cited by:

    1. Lilia Cavallari & Simone Romano, 2016. "Foresight And The Macroeconomic Impact Of Fiscal Policy: Evidence For France, Germany And Italy," Working Papers 0216, CREI Università degli Studi Roma Tre, revised 2016.
    2. repec:bla:jorssa:v:180:y:2017:i:2:p:353-407 is not listed on IDEAS
    3. Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2014. "Signals from the Government: Policy Uncertainty and the Transmission of Fiscal Shocks," MPRA Paper 56136, University Library of Munich, Germany.
    4. Koester, Gerrit B. & Priesmeier, Christoph, 2015. "The Timing and Responsiveness of Fiscal Policy over the Business Cycle in Germany," MPRA Paper 68412, University Library of Munich, Germany.
    5. Piacentini, Paolo & Prezioso, Stefano & Testa, Giuseppina, 2015. "Effects of fiscal policy in the North and South of Italy," MPRA Paper 62372, University Library of Munich, Germany.
    6. Götz, Thomas B. & Hauzenberger, Klemens, 2018. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers 40/2018, Deutsche Bundesbank.
    7. Hecq, Alain & Goetz, Thomas, 2018. "Granger causality testing in mixed-frequency Vars with possibly (co)integrated processes," MPRA Paper 87746, University Library of Munich, Germany.

    More about this item

    Keywords

    Time variation; mixed-frequency data; government spending multiplier;

    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
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy
    • H30 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - General
    • H50 - Public Economics - - National Government Expenditures and Related Policies - - - General

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