An empirical knowledge production function of agricultural research and extension: The case of the University of California Cooperative Extension

被引:12
作者
Chatterjee, Diti [1 ]
Dinar, Ariel [2 ]
Gonzalez-Rivera, Gloria [3 ]
机构
[1] Univ Calif Riverside, Dept Environm Sci, Riverside, CA 92521 USA
[2] Univ Calif Riverside, Sch Publ Policy, Riverside, CA 92521 USA
[3] Univ Calif Riverside, Dept Econ, Riverside, CA 92521 USA
关键词
Knowledge production function; Cooperative extension; Agricultural R&D; University of California Cooperative Extension; INNOVATION; COLLABORATION; SPILLOVERS; IMPACT;
D O I
10.1016/j.techfore.2018.06.037
中图分类号
F [经济];
学科分类号
02 ;
摘要
Our study examines empirically the impact of agricultural research inputs on the creation and dissemination of knowledge by the University of California Cooperative Extension (UCCE). We formulate a conceptual framework to understand the relationship between the agricultural research inputs employed by UCCE and the knowledge shared. We develop an index of knowledge based on a weighted average of the various modes through which knowledge is produced by UCCE's agricultural research for all counties in the state of California during 2007-2013. Empirical results indicate significant positive impacts of research inputs on the production of knowledge. We find research input, such as number of research positions measured as full-time equivalent (FTE), level of salary per researcher (including seniority and status), and investment in research infrastructure per FTE, positive and significant. Our models suggest diminishing marginal knowledge returns to research infrastructure, and a linear knowledge production function with respect to the number of 1, is and the salary per FTE in the UCCE system.
引用
收藏
页码:290 / 297
页数:8
相关论文
共 40 条
[31]   Spillovers in the production of knowledge: A meta-regression analysis [J].
Neves, Pedro Cunha ;
Sequeira, Tiago Neves .
RESEARCH POLICY, 2018, 47 (04) :750-767
[32]   CAUSAL RELATIONSHIPS BETWEEN PUBLIC-SECTOR AGRICULTURAL-RESEARCH EXPENDITURES AND OUTPUT [J].
PARDEY, PG ;
CRAIG, B .
AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS, 1989, 71 (01) :9-19
[33]   THE AGRICULTURAL KNOWLEDGE PRODUCTION FUNCTION - AN EMPIRICAL LOOK [J].
PARDEY, PG .
REVIEW OF ECONOMICS AND STATISTICS, 1989, 71 (03) :453-461
[34]   PATENT STATISTICS AS INDICATORS OF INNOVATIVE ACTIVITIES - POSSIBILITIES AND PROBLEMS [J].
PAVITT, K .
SCIENTOMETRICS, 1985, 7 (1-2) :77-99
[35]   Innovation, spillovers and university-industry collaboration: an extended knowledge production function approach [J].
Ponds, Roderik ;
van Oort, Frank ;
Frenken, Koen .
JOURNAL OF ECONOMIC GEOGRAPHY, 2010, 10 (02) :231-255
[36]   On estimating a knowledge production function at the firm and sector level using patent statistics [J].
Ramani, Shyama V. ;
El-Aroui, Mhamed-Ah ;
Carrere, Myriam .
RESEARCH POLICY, 2008, 37 (09) :1568-1578
[37]   Knowledge stocks, knowledge flows and innovation: Evidence from matched patents and innovation panel data [J].
Roper, Stephen ;
Hewitt-Dundas, Nola .
RESEARCH POLICY, 2015, 44 (07) :1327-1340
[38]   Technology spillovers between sectors and over time [J].
Verspagen, B ;
De Loo, I .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 1999, 60 (03) :215-235
[39]   Strong ties and weak ties of the knowledge spillover network in the semiconductor industry [J].
Wang, Chun-Chieh ;
Sung, Hui-Yun ;
Chen, Dar-Zen ;
Huang, Mu-Hsuan .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2017, 118 :114-127
[40]  
Wooldridge JM, 2010, ECONOMETRIC ANALYSIS OF CROSS SECTION AND PANEL DATA, 2ND EDITION, P1