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Essays on capitalizing Research and Development expenditures Huang, Ning


The next international version of the System of National Accounts (SNA) will recommend that Research and Development (R&D) expenditures be treated as capital formation instead of immediate expenses as in the present SNA 1993. This recommendation brings in challenges to many aspects of measuring R&D capital stocks. This dissertation focuses on measurement issues associated with capitalizing R&D expenditures. In the first paper, we develop a simple model on production technology that allows for monopolistic competition. It enables estimation of annual depreciation rates for R&D capital. We treat R&D capital as a technology shifter instead of an explicit input factor. Both the R&D stock and the time trend are used to capture technological progress. The R&D depreciation rates and markup factors are estimated for the U.S. manufacturing sector and four U.S. knowledge intensive industries. The second paper looks at the net benefits of a R&D project in the context of a very simple intertemporal general equilibrium model and suggests that R&D expenditures be amortized using the matching principle that has been developed in the accounting literature. This approach matches fixed costs of a project to a stream of future benefits. Of particular interest is the evaluation of the net benefits of a publicly funded project where the results are made freely available to the public. In the third paper, we propose a new method of treating R&D expenditure in the growth accounting framework and investigate how to construct the associated measures for the stock of the R&D capital. We distinguish general knowledge from the more specific technologies applied in goods and services production, and treat them differently in the growth accounting framework. In addition, we derive a general formula to measure the newly created knowledge increments that depend not only on R&D expenditures but also on the existing general knowledge stock and knowledge productivity. We illustrate our new methodology for the treatment of R&D using U.S. manufacturing data for the last half century.

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