The Deadweight Costs of Capital Taxation in Australia

Diewert, W. Erwin; Lawrence, Denis

doi:10.1007/978-1-4757-3592-5_6

Cited by 10 publications

(6 citation statements)

References 25 publications

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“…1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 Year AIM(2) NQ 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 Year AIM(2) NQ variations, whereas those from the NQ trend over time. This problem of lacking variations in own-price elasticities over time with the NQ model was first noted by Diewert and Lawrence (2002) and referred to by them as 'the problem of trending elasticities.' As can seen below, this problem in the NQ model is also reflected in its cross elasticities and carried over to its Morishima elasticities.…”

Section: Elasticity Estimatesmentioning

confidence: 99%

“…As can seen below, this problem in the NQ model is also reflected in its cross elasticities and carried over to its Morishima elasticities. To cure this problem with the NQ model, Diewert and Lawrence (2002) suggested imposing flexibility at two sample points. As with the own-price elasticities, the cross-price elasticities differ significantly between the two models (see Table 5).…”

Section: Elasticity Estimatesmentioning

confidence: 99%

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Productivity trends in U.S. manufacturing: Evidence from the NQ and AIM cost functions

Feng

Serletis

2008

Journal of Econometrics

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Section: Elasticity Estimatesmentioning

confidence: 99%

Section: Elasticity Estimatesmentioning

confidence: 99%

Productivity trends in U.S. manufacturing: Evidence from the NQ and AIM cost functions

Feng

Serletis

2008

Journal of Econometrics

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“…Diewert and Lawrence (2002) point out that, for the normalized quadratic functional form, the estimated elasticities often have strong trends when there are strong trends in the price and quantity data. They also suggest one way to solve this problem.…”

Section: The Estimation Frameworkmentioning

confidence: 96%

Estimation of R&D depreciation rates: a suggested methodology and preliminary application

Huang

Diewert

2011

Canadian Journal of Economics/Revue Canadienne d'Économique

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The 2008 version of the SNA has recommended capitalization of R&D expenditures. To implement this recommendation, we need to determine the depreciation rate of R&D capital. In this paper, we develop a simple model, based on a production function method that allows for monopolistic competition, to estimate the annual depreciation rate of R&D capital. We treat R&D capital as a technology shifter instead of as an explicit input factor. Both the R&D stock and the time variable are used to capture technological progress. Estimated R&D depreciation rates and markup factors are presented for the U.S. manufacturing sector and four U.S. knowledge-intensive industries. JEL classification: C32, C43, C81, D24, D43, D92 Estimation des taux de dépréciation pour la R-D : une méthodologie suggérée et une application préliminaire. L'édition 2008 du SCN recommande la capitalisation des dépenses en R-D. Pour mettre en oeuvre cette recommandation, il est nécessaire d'estimer un taux de dépréciation pour la R-D. Dans le présent article, nous développons un modèle simple, basé sur la méthode dite de fonction de production caractérisée par la concurrence monopolistique pour estimer le taux de dépréciation annuel de la R-D. Nous traitons la R-D comme un levier de la technologie plutôt qu'un facteur de production explicite. Le stock de R-D et la variable temps sont utilisés pour traduire le progrès technologique. Le taux de dépréciation estimé de la R-D et un coefficient de 'mark-up' sont présentés pour le secteur manufacturier desÉtats-Unis et pour quatre de leurs industries du savoir.The views expressed in this paper are those of the authors and do not reflect those of Statistics Canada. The authors thank the SSHRC for financial support and acknowledge very helpful discussions with Alice Nakamura and Paul Schreyer, and two anonymous referees for their helpful comments. We also thank Marc Prud'homme for translating the abstract into French. All errors are ours.

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“…68. Add error terms to each equation, say e n t for equation n in period t. 40 Subtract the logarithm of the first input demand function from these N equations. Suppose that there are data on inputs, output, and input prices for t periods and the period t data are…”

Section: Problemsmentioning

confidence: 99%

Duality in Production

Diewert¹

2020

Handbook of Production Economics

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The chapter reviews the application of duality theory in production theory. Duality theory turns out to be a useful tool for two reasons: (i) it leads to relatively easy characterizations of the properties of systems of producer derived demand functions for inputs and producer supply functions for outputs and (ii) it facilitates the generation of flexible functional forms for producer demand and supply functions that can be estimated using econometrics. The chapter focuses on describing the properties of five functional forms that have been used in the production literature: (i) the constant elasticity of substitution (CES), (ii) the generalized Leontief, (iii) the translog, (iv) the normalized quadratic, and (v) the Konüs Byushgens Fisher functional forms. The applications of GDP functions and joint cost functions to various areas of applied economics are explained.

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The Deadweight Costs of Capital Taxation in Australia

Cited by 10 publications

References 25 publications

Productivity trends in U.S. manufacturing: Evidence from the NQ and AIM cost functions

Productivity trends in U.S. manufacturing: Evidence from the NQ and AIM cost functions

Estimation of R&D depreciation rates: a suggested methodology and preliminary application

Duality in Production

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