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Record W4251311254 · doi:10.1086/663665

Comment

2012· article· en· W4251311254 on OpenAlexaboutno aff
Francesco Giavazzi

Bibliographic record

VenueNBER International Seminar on Macroeconomics · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsnot available
Fundersnot available
KeywordsDebtEconomicsDebt ratioFiscal policyMonetary economicsInternational economicsMacroeconomics

Abstract

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Previous articleNext article FreeCommentFrancesco GiavazziFrancesco GiavazziBocconi University, MIT, and NBER Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreTable 1 (from Favero, Giavazzi, and Perego 2012) illustrates the extent to which fiscal policy reacts to fluctuations in the (lagged) debt/GDP ratio. The table reports the estimated coefficients on the debt/GDP ratio in the fiscal reaction function of eight OECD countries (the data are annual and extend from 1978 to 2009). Debt stabilization plays a role in all countries, as the difference between the feedback coefficients on taxes and government spending implies a positive feedback of the primary surplus to the debt to GDP ratio, with Japan as the only exception. The style of stabilization is, however, heterogenous across countries: lagged debt impacts more significantly (with a negative sign) on expenditures in Canada, the United Kingdom, and in the United States, while it has instead a borderline significant (positive) coefficient on taxes in France. Italian fiscal policy reacts to fluctuations in the debt/GDP ratio by adjusting both taxes and spending.Table 1 . Coefficients of bt–1 ExpendituresRevenuesCountries gtτtBelgium –.038.030 (–.27)(.35)Canada –.149–.072 (–2.25)(.27)France .036.144 (.57)(1.56)Italy –.110.218 (–2.12)(3.18)Japan .015.180 (.10)(1.52)Sweden –.072581.045513 (–.64)(.38)United Kingdom .183.086 (2.02)(.47)United States –.292.47 (–2.23)1(1.62) 1 Source. Favero et al. (2011).Notes. t-stats in parentheses. Yearly data: 1978–2009.View Table ImageThe authors assume that “the costs of changing the tax rates and their enforcement are high relative to the lower political costs of changing the public debt/GDP and the fiscal deficit/GDP. The tax base depends on structural factors that are harder to modify in the short run than adjusting government expenditure.” They thus contend that “the tax revenue as a share of the GDP provides a more efficient way of normalizing macro public finance data [because] the public debt/GDP normalized by the de facto tax base measures the average tax years that it would take to ‘buy’ the outstanding public debt, and provides a stock measure of public debt overhang.” The results in table 1 show that some countries—Italy, and to some extent France, in our sample—do instead adjust taxes. Others use changes in government spending, a variable that the authors implicitly assume to remain constant.Thus, while the authors address a very interesting issue—the sources of heterogeneity in fiscal policy—by concentrating on one variable, their definition of fiscal space, they overlook a number of other factors that determine a government’s reaction to exogenous shocks and to their effect on the debt/GDP ratio. The extent to which a government will use fiscal policy to cushion the effects of a shock, thus letting the debt ratio rise, depends in the end on the credibility of its commitment to satisfy the intertemporal budget constraint(DY)t=∑i=0∞(Tt−1Yt−1−Gt−1Yt−1)i(1+r1+g)i.This does depend on the ability to adjust tax rates, but also spending, and most importantly, depends on the distance of the cost of debt service from the economy’s growth rate. NotesFor acknowledgments, sources of research support, and disclosure of the author’s material financial relationships, if any, please see http://www.nber.org/chapters/c12500.ack.ReferenceGiavazzi, Francesco, Carlo A. Favero, and Jacopo Perego. 2012. “Country Heterogeneity and the International Evidence on the Effects of Fiscal Policy.” IMF Economic Review, forthcoming.First citation in articleGoogle Scholar Previous articleNext article DetailsFiguresReferencesCited by Volume 8, Number 12012 Article DOIhttps://doi.org/10.1086/663665 Views: 103Total views on this site © 2012 by the National Bureau of Economic ResearchPDF download Crossref reports no articles citing this article.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.011

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.257
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2012
Admission routes1
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