Structural Time Series Models for Business Cycle Analysis

Proietti, Tommaso

doi:10.1057/9780230244405_9

Cited by 15 publications

(8 citation statements)

References 79 publications

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“…Notably, these proxies tend to attribute an excessive power to low-frequencies, but the error is clearly heterogeneous across filters, with the BP filter performing (by construction) better than all other filters, the HP filter offering an 'intermediate' performance, and others -among which the CBO filter -overemphazizing the relevance of low-frequency fluctuations for the business cycle. 8 In general, problems of leakage (loss of power at the edges of the business cycle frequency band) and compression (increase of power in the middle of the band) are pervasive, a result already pointed out by, among others, Canova (1998), Canova (2007 chapter 3), Canova (2009a), Proietti (2009) and Canova and Ferroni (2011).…”

Section: Different Business Cycle Proxies: a Comparisonmentioning

confidence: 99%

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What does a Monetary Policy Shock Do? An International Analysis with Multiple Filters*

Castelnuovo¹

2012

Oxf Bull Econ Stat

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What does a monetary policy shock do? We answer this question by estimating a new‐Keynesian monetary policy dynamic stochastic general equilibrium model for a number of economies with a variety of empirical proxies of the business cycle. The effects of two different policy shocks, an unexpected interest rate hike conditional on a constant inflation target and an unpredicted drift in the inflation target, are scrutinized. Filter‐specific Bayesian impulse responses are contrasted with those obtained by combining multiple business cycle indicators. Our results document the substantial uncertainty surrounding the estimated effects of these two policy shocks across a number of countries.

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Section: Different Business Cycle Proxies: a Comparisonmentioning

confidence: 99%

“…7 Of course, the list of filters one may think of is much larger Canova (1998Canova ( , 2007. chapter 3),Cogley (2008) andProietti (2009) consider a set of alternative filters and discuss the pros and cons of different filtering strategies at length. © John Wiley & Sons Ltd and the Department of Economics, University of Oxford 2012…”

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confidence: 99%

What does a Monetary Policy Shock Do? An International Analysis with Multiple Filters*

Castelnuovo¹

2012

Oxf Bull Econ Stat

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“…17 As is well known, at the end of the sample the LHP-filtered components are of questionable reliability (Orphanides and Van Norden 2002). In principle, the LHP estimates could be adapted to the characteristics of the present series using appropriate techniques (Proietti 2009). In fact, the dynamic relationship between filtered time series is least distorted if the same (possibly suboptimal) filter is applied to all the series (Wallis 1974).…”

Section: Appendixmentioning

confidence: 99%

“…18 In practice, this non-parametric concordance statistic requires selecting a kernel m t (Á) and a bandwidth. The recent literature proposes a family of estimators, with varying weights on the observations (Proietti 2009). Here, the kernel is allowed to adapt automatically at the boundaries of the sample space, and the bandwidth is related to the time horizon at which the correlation is computed.…”

Section: Appendixmentioning

confidence: 99%

The effects of unification: markets, policy, and cyclical convergence in Italy, 1861–1913

2009

Self Cite

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This paper uses time-series evidence on construction movements to examine the convergence of regional business cycles in the decades that followed Italy's Unification. The aggregate series point to cyclical convergence, but a sector-level analysis traces this result to the decline in differentiated "regional-policy" shocks. The regional market cycles diverged, as regions specialized in different sectors of production; market-cycle convergence is observed only within the "industrial triangle," the regions of which also developed different specializations. This suggests that the balance between growing interdependence and growing differentiation is not general, as the current literature presumes, but specialization-specific

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“…Furthermore, the HP and BK filters as well as Christiano and Fitzgerald (2003, BP henceforth) Band-Pass approach are special cases of the aforementioned models which can be obtained by imposing specific parameters constraints, see e.g. Proietti (2009) and Azevedo et al (2006). We firstly consider a univariate framework where the quarterly real GDP is decomposed into three orthogonal components: trend, cycle and irregular.…”

Section: Introductionmentioning

confidence: 99%

Extracting the Italian output gap: a Bayesian approach

Bernardi¹,

Ruggiero²

2014

Preprint

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During the last decades particular effort has been directed towards understanding and predicting the relevant state of the business cycle with the objective of decomposing permanent shocks from those having only a transitory impact on real output. This trend-cycle decomposition has a relevant impact on several economic and fiscal variables and constitutes by itself an important indicator for policy purposes. This paper deals with trend-cycle decomposition for the Italian economy having some interesting peculiarities which makes it attractive to analyse from both a statistic and an historical perspective. We propose an univariate model for the quarterly real GDP, subsequently extended to include the price dynamics through a Phillips curve. This study considers a series of the Italian quarterly real GDP recently released by OECD which includes both the 1960s and the recent global financial crisis of 2007-2008. Parameters estimate as well as the signal extraction are performed within the Bayesian paradigm which effectively handles complex models where the parameters enter the log-likelihood function in a strongly nonlinear way. A new Adaptive Independent Metropolis-within-Gibbs sampler is then developed to efficiently simulate the parameters of the unobserved cycle. Our results suggest that inflation influences the Output Gap estimate, making the extracted Italian OG an important indicator of inflation pressures on the real side of the economy, as stated by the Phillips theory. Moreover, our estimate of the sequence of peaks and troughs of the Output Gap is in line with the OECD official dating of the Italian business cycle.

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Structural Time Series Models for Business Cycle Analysis

Cited by 15 publications

References 79 publications

What does a Monetary Policy Shock Do? An International Analysis with Multiple Filters*

What does a Monetary Policy Shock Do? An International Analysis with Multiple Filters*

The effects of unification: markets, policy, and cyclical convergence in Italy, 1861–1913

Extracting the Italian output gap: a Bayesian approach

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