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How Important are Sectoral Shocks?
32/32 checkable references clean · checked 2026-08-16
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
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The 32 checked references that resolve
resolves10.3386/w14389
Sectoral vs. Aggregate Shocks: A Structural Factor Analysis of Industrial Production
resolves10.1257/aer.98.1.394
Reallocation, Firm Turnover, and Efficiency: Selection on Productivity or Profitability?
resolves10.1086/ma.19.3585339
Technology Shocks and Aggregate Fluctuations: How Well Does the Real Business Cycle Model Fit Postwar U.S. Data?
resolves10.1006/redy.1998.0028
Cyclicality and Sectoral Linkages: Aggregate Fluctuations from Independent Sectoral Shocks
resolves10.1016/j.red.2006.06.002
How important is the intermediate input channel in explaining sectoral employment comovement over the business cycle?
resolves10.1016/j.red.2011.09.005
The structural transformation between manufacturing and services and the decline in the US GDP volatility
resolves10.1016/j.jmoneco.2012.10.008
Methods versus substance: Measuring the effects of technology shocks
resolves10.2307/2078071
Imperfect Competition and the Effects of Energy Price Increases on Economic Activity
resolves10.1016/0304-3932(88)90037-2
Sectoral and national aggregate disturbances to industrial output in seven European countries
resolves10.1111/j.1468-0297.2009.02280.x
Output, Input and Productivity Measures at the Industry Level: The EU KLEMS Database
The 10 references without a DOI — listed, not checked
no DOI — not checkedref16
no DOI — not checkedSectoral vs. Aggregate Shocks In The Business Cycle
no DOI — not checkedagain lowest for bulk milk and highest for raw cane sugar. 49 The results reported here are slightly di�erent from those in Foster, Haltiwanger, and Syverson (2008): I restrict my sample to those plants for which I can observe materials prices, while Foster, Haltiwanger, and Syverson make no such restriction. Their estimate of D is lower for petroleum (^ D = 1:42) and higher for ready-mix concrete (^ D = 5:93). Again, because the normalized variances of materials shares are so small
no DOI — not checkedref33
no DOI — not checkedFor seven of the ten industries in the sample (with the exceptions being the smallest three subsamples), the data would reject a null hypothesis of " Q = 1. The estimates of " Q that correspond to the instrumental-variables-based estimate of P are even smaller, though again much less precisely estimated. The point estimate for " Q is 0:10 for the ready-mix concrete subsample, and is somewhat higher (between 0:40 and 0:55) for the other three industries. For the pooled sample, and three of the four industry subsamples, the data reject a null hypothesis of " Q = 1. In summation, micro data on plants' materials usage patterns indicate that material inputs are gross complements to other factors of production. For most speci?cations (all except for the I.V. speci?cation for the ready-mix concrete subsample, or the ?xed e�ects speci?cation for the smaller industries), the data indicate that
no DOI — not checkedThe Measurement of Economic Depreciation
no DOI — not checkedMaintenance and Repair: Too Big to Ignore
no DOI — not checkedref39
no DOI — not checkedref41
no DOI — not checkedref42
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