Innovation and productivity in agricultural firms: evidence from a country-wide farm-level innovation survey

ABSTRACT

The literature on the links between innovation and productivity at the firm level in agriculture is almost nonexistent. In this paper, we analyze the factors behind the innovation effort of farms and the impact that innovation effort has on farm’s productivity, exploiting a unique farm-level agricultural innovation survey carried out in Uruguay. The results indicate that farm size, cooperation with other agents to perform R&D, the education of the owner of the farm, the participation of foreign capital and the existence of links with other organizations, in particular scientific, horizontal and vertical ones, are positively correlated with innovation effort. Public and private financial support are not clearly linked with innovation effort. The innovation effort has a positive effect on farm’s productivity. Some heterogeneities across industries in agriculture are found.

KEYWORDS:

• innovation
• productivity
• agriculture
• innovation surveys

JEL Classification:

• O12
• O13
• O31
• O33
• O40

Acknowledgements

We thank comments and suggestions made by participants at WINIR Conference 2015 and Central Bank of Uruguay Conference 2015.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Diego Aboal http://orcid.org/0000-0002-6217-962X

Notes

1 The survey follows the Bogota Manual that follows the Oslo Manual. The Bogota Manual is the base of the manufacturing and services innovation surveys in Latin America.

2 The questions for expenditure on innovation activities are nested: the question only applies to those farms that declare to have introduced the respective innovation activity in 2007–2009. Thus, we do not have information on expenditure for farms that were carrying out the activity before 2007.

3 An alternative could have been to estimate a fractional logit model that will generate predictions in the range [0,1].

4 Detailed methodological aspects and analysis of the results of this survey are published in Spanish in Mondelli et al. (2013).

5 For the innovation stage, we have 87 observations for rice and 168 for dairy. For the productivity equation, we have only 45 observations for rice and 98 for dairy.

6 Or manager of the firm in case of partnerships or corporations where is not possible to identify the farmer.

7 The composition of hectares according to agricultural aptitude is deduced from the land composition of the area surrounding the nearest police station. The three categories of land quality defined are marginally or not suitable; moderately suitable; and highly suitable. The share of marginally or non-suitable hectares is omitted due to collinearity issues.

8 See Appendix Table A1 for variables definitions.

Additional information

Funding

This study was financially supported by the National Research and Innovation Agency (ANII, Uruguay), through the project Uruguay +25 of Fundación Astur and Mercosur Economic Research Network (Red Mercosur).