The information content of capacity utilization for detrending total factor productivity

Planas, Christophe; Roeger, Werner; Rossi, Alessandro

doi:10.1016/j.jedc.2012.09.005

Cited by 17 publications

(9 citation statements)

References 24 publications

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“…Moreover, Student mean tests indicate that their mean is zero over the estimation period, confirming the stability in the relationship between the CUR and the TFP gap. Like Planas et al (2013), but in a different framework, we find that including the CUR in our TFP model improves the quasi-real-time reliability 10 of TFP gap estimates. We iteratively estimate the TFP equation over samples going from a fixed start date to a rolling end date.…”

Section: Robustness and Quasi-real-time Reliabilitymentioning

confidence: 63%

“…Statistically, this variable also has a number of features that make it extremely valuable from a practical point of view: (1) the CUR is observable and available for many countries, which facilitates international comparisons (see the EU harmonized Business Tendency Surveys); (2) CUR surveys are rapidly available (generally at the beginning of the following month); and (3) the CUR is not revised. By focusing on capacity utilization, our approach builds heavily on Planas et al (2013) but in a trendstationary framework à la Perron (1999).…”

Section: Introductionmentioning

confidence: 99%

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Assessing the losses in euro area potential productivity due to the financial crisis

et al. 2014

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In this article, we show that the recent financial crisis has significantly affected the potential total factor productivity (TFP) of the four largest euro area economies, as well as that of the rest of the euro area. We used a reduced-form equation of TFP, based on an approach recently developed by Cahn and Saint-Guilhem (2010). Our empirical findings show that the permanent impact on potential TFP varies across countries from -3.9 points to -1.3 points in Q2 2012. When these losses are incorporated, TFP gaps develop closely in line with capacity utilization rates (CUR). Moreover, in the case of France, including CUR in our TFP model improves the quasi-real-time reliability of TFP gap estimates.

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Section: Robustness and Quasi-real-time Reliabilitymentioning

confidence: 63%

Section: Introductionmentioning

confidence: 99%

Assessing the losses in euro area potential productivity due to the financial crisis

et al. 2014

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“…This issue was discussed in Orphanides and Van Norden () or Planas et al . () and is closely related to the problem of revision strategy for seasonally adjusted figures. Many NSIs continuously revise their official releases of seasonally adjusted series, since estimates of seasonal effects can be improved as new information becomes available.…”

Section: Model Selection and Estimation Resultsmentioning

confidence: 99%

Multivariate State Space Approach to Variance Reduction in Series with Level and Variance Breaks Due to Survey Redesigns

Bollineni‐Balabay¹,

Brakel²,

Palm

2015

Journal of the Royal Statistical Society Series A: Statistics in Society

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Statistics Netherlands applies a design-based estimation procedure to produce road transportation figures. Frequent survey redesigns caused discontinuities in these series which obstruct the comparability of figures over time. Reductions in the sample size and changes in the sample design resulted in variance breaks and unacceptably large sampling errors in the recent part of the series. Both problems are addressed and solved simultaneously. Discontinuities and small sample sizes are accounted for by using a multivariate structural time series model that borrows strength over time and space. The paper illustrates an increased precision when we move from univariate models to a multivariate model where the domains are jointly modelled. This increase is especially significant in the most recent period when sample sizes become smaller, with standard errors of the design-based estimator of the target variables being reduced by 40-70% with the model-based approach.

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“…We also do not directly deal with intangible capital(Corrado et al, 2012). However, we do use the latest release of the EU KLEMS dataset, which makes some efforts to deal with this latter issue.5The major difference between their approach and BFK is thatBurnside et al (1995) assume a unit elasticity between changes in hours per worker and capital utilization, while BFK estimate this elasticity.6Planas et al (2013) propose a statistical filtering method to extract trend TFP growth for European countries (also relying on capacity utilization surveys). This approach differs from BFK and from our paper by the fact that it uses a statistical model instead of the economic structure imposed by a cost minimization model.…”

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confidence: 99%

A New Measure of Utilization-adjusted TFP Growth for Europe and the United States

Comín¹,

Gonzalez²,

Schmitz³

et al. 2020

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and seminar participants at Bocconi, Pavia and Konstanz for useful comments. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 72073. The views expressed herein are those of the authors and do not necessarily reflect the views of 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.

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The information content of capacity utilization for detrending total factor productivity

Cited by 17 publications

References 24 publications

Assessing the losses in euro area potential productivity due to the financial crisis

Assessing the losses in euro area potential productivity due to the financial crisis

Multivariate State Space Approach to Variance Reduction in Series with Level and Variance Breaks Due to Survey Redesigns

A New Measure of Utilization-adjusted TFP Growth for Europe and the United States

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