Measuring factor income shares at the sectoral level

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in February 2008 AbstractMany applications in economics use multi-sector versions of the growth model. In this paper, we measure the income shares of capital and labor at the sectoral level for the U.S.economy. We also decompose the capital shares into the income shares of land, structures, and equipment. We find that the capital shares differ across sectors. For example, the capital share of agriculture is more than two times that of construction and more than 50% larger than that of the aggregate economy. Moreover, agriculture has by far the largest land share, which mostly explains why it has the largest capital share. Our numbers can directly be used to calibrate standard multi-sector models. Alternatively, if one wants to abstract from differences in sector capital shares, our numbers can be used to establish that this is not crucial for the results.Keywords: input-output tables; industry-by-commodity total requirement matrix; sector factor shares JEL classification: O41; O47 * We thank the editor Tim Kehoe and two anonymous referees for suggestions that improved the paper considerably. We thank Edward Prescott for many helpful discussions about input-output tables, Randal Konoshita from the BLS for providing us with additional data, and Ben Bridgman, Cara McDaniel, Paul Schreck, and the audiences at ASU and the Federal Reserve Bank of Minneapolis for comments. Számos közgazdasági munka a neoklasszikus növekedési modell több szektoros változatát használja. Ebben a tanulmányban a tőkeés a munka szektor szintű jövedelemrészesedését mérjük az EgyesültÁllamokra. A tőke jövedelem részesedét felbontjuk föld,épületekés gépek részesedésére. Munkánk során azt találtuk, hogy a tőke részesedése jelentősen különbözik szektorok között. Például, a tőke részesedése a mezőgazdaságban több mint kétszer akkora, mint azépítőiparbanés 50%-kal magasabb, mint a gazdaság egészében. Számaink közvetlenül felhasználhatóak a több szektoros modellek paramétereinek kalibrálására. Ha pedig valaki el akar vonatkozatni a tőke jövedelemrészesedésének szektorok közötti különbségétől, akkor számaink felhasználhatók annak megállapítására, hogy ez lényeges-e vagy sem.

Kuznets-Kaldor-Puzzle, Neutral Structural Change and Independent Preferences and Technologies

“…we assume α χ < . This is consistent with the empirical evidence presented and discussed in Valentinyi and Herrendorf (2008) Hence, the space above 1 R is not feasible. When the economy reaches a point on 1 R , no labour is used in sub-sectors i=1,…m.…”

“…Similar results for the USA are obtained by Close and Shulenburger (1971) for the period 1948-1965and by Acemoglu and Guerrieri (2008 for the period [1987][1988][1989][1990][1991][1992][1993][1994][1995][1996][1997][1998][1999][2000][2001][2002][2003][2004]. Some new evidence for the USA (presented by Valentinyi and Herrendorf (2008)) supports these results as well. Gollin (2002) (p. 464) analyzes the data from 41 countries reported in the U.N. National Statistics.…”

Implementation of Technological Breakthroughs at Sector Level and Technology-Bias

“…Hence, the cross technology-bias is sufficiently small and has therefore relatively weak impacts on the aggregate economy. Valentinyi and Herrendorf (2008) show that capital-income shares are relatively similar at low degree of disaggregation (i.e. when comparing manufacturing and services).…”

“…in the USA, capital-goods are produced primarily by the manufacturing sector and output-elasticity of capital differs across consumption-goods and capital-goods; see e.g. Valentinyi and Herrendorf (2008 ence, all these determinants affect the cross-sector-factor allocation and thus relative Last not least, there are several further factors, which are not explicitly modele w breakthrough and/or on the nature sectoral output. Some discussion of the nature of sectors and its implications for the scope of technological progress can be found, e.g.…”

Macroeconomic effects of zero corporate income tax on retained earnings

“…The reason for this higher capital share probably arises from a different institutional set of labour markets (such as low union density) in Estonia, but also from a different economic structure in terms of fields of economic activities. Estonia, as a traditional post-communist catching-up country, has a lower share of services -the capital share is usually much higher in agriculture, somewhat higher in manufacturing and lower in services compared to the average in other economies (see, for example, Valentinyi and Herrendorf, 2008, for their estimations using US data). According to Statistics Estonia, the average labour share in Estonia was 47% between 1995 and 2010, which under constant returns to scale and Cobb-Douglas technology provides an unconventionally high capital share of 0.53.…”