Temporal disaggregation of business dynamics: New evidence for U.S. economy
Lorenza Rossi and
Emilio Zanetti Chini ()
Journal of Macroeconomics, 2021, vol. 69, issue C
We provide new disaggregated data and stylized facts on firm dynamics of the U.S economy at establishment level by using a state-space method to transform Census yearly data of entry and exit from 1977 to 2013 into quarterly frequency. We select the most significant determinants of these variables by matching Census data with a new database by Federal Reserve Bank. These determinants are extrapolated by using an unobserved factor model whose loadings are estimated via Principal Component Analysis. Alternative sources and their data are also investigated and discussed. We find that (i) Entry is pro-cyclical, coincident and symmetric; (ii) Exit is lagging with a maximum positive correlation with RGDP at lag 5 and asymmetric along the business cycle; (iii) the standard macroeconometric models estimated on our disaggregated series support the recent theoretical literature.
Keywords: Bayesian VAR; Entry and Exit; Factor models; Overshooting; Variable selection (search for similar items in EconPapers)
JEL-codes: C13 C32 C40 E30 E32 (search for similar items in EconPapers)
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Working Paper: Temporal Disaggregation of Business Dynamics: New Evidence for U.S. Economy (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmacro:v:69:y:2021:i:c:s0164070421000422
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