Authors:
Seung-Hoon YooSchool of Business and Economics, Hoseo University 268 Anseo-Dong, Cheonan, Chungnam, 330-713, Republic of Korea 268 Anseo-Dong, Cheonan, Chungnam, 330-713, Republic of Korea

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Hye-Seon MoonKorea Institute of Science and Technology Evaluation and Planning Seoul (Republic of Korea) Seoul (Republic of Korea)

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Summary  

Modeling firms' R&D expenditures often become complicated due to the zero values reported by a significant number of firms. The maximum likelihood (ML) estimation of the Tobit model, which is usually adopted in this case, however, is not robust to heteroscedastic and/or non-normal error structure. Thus, this paper attempts to apply symmetrically trimmed least squares estimation as a semi-parametric estimation of the Tobit model in order to model firms' R&D expenditures with zero values. The result of specification test indicates the semi-parametric estimation outperforms the parametric ML estimation significantly.

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Scientometrics
Language English
Size B5
Year of
Foundation
1978
Volumes
per Year
1
Issues
per Year
12
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0138-9130 (Print)
ISSN 1588-2861 (Online)

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