2017
DOI: 10.1111/1477-8947.12133
|View full text |Cite
|
Sign up to set email alerts
|

Productivity effects and natural resource management: econometric evidence from POSAF‐II in Nicaragua

Abstract: Understanding how natural resource management (NRM) technologies impact agricultural productivity is essential in order to ensure that policies designed to reduce environmental degradation and alleviate poverty are successful. In this paper, we analyze the impact of natural resource technologies delivered by the Socio-environmental and Forestry Development Programme-II (POSAF-II) in Nicaragua. Using cross-sectional data for 1,201 farmers (475 beneficiaries, 726 control farmers), we provide empirical evidence c… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

2
7
0

Year Published

2018
2018
2023
2023

Publication Types

Select...
9
1

Relationship

0
10

Authors

Journals

citations
Cited by 16 publications
(9 citation statements)
references
References 50 publications
(73 reference statements)
2
7
0
Order By: Relevance
“…The reason is it is easy to match treated with control individuals based on the common support assumption (Caliendo and Kopeinig, 2008;Smith and Todd, 2005). More importantly, the matching method has been utilized in the literature (see (Bravo-Ureta et al, 2012;De los Santos-Montero and Bravo-Ureta, 2017;Kassie et al, 2011;Villano et al, 2015). Figure 1 illustrates that the estimated propensity scores fall within the area of common support between the treatment and control group, except for only three treated observations that fall in the off-support region.…”
Section: Data and Descriptive Statisticsmentioning
confidence: 99%
“…The reason is it is easy to match treated with control individuals based on the common support assumption (Caliendo and Kopeinig, 2008;Smith and Todd, 2005). More importantly, the matching method has been utilized in the literature (see (Bravo-Ureta et al, 2012;De los Santos-Montero and Bravo-Ureta, 2017;Kassie et al, 2011;Villano et al, 2015). Figure 1 illustrates that the estimated propensity scores fall within the area of common support between the treatment and control group, except for only three treated observations that fall in the off-support region.…”
Section: Data and Descriptive Statisticsmentioning
confidence: 99%
“…Chen et al (2008) also showed that the primary determinants of technical progress, which was the main source of productivity, were the agricultural tax cut, public investment in research and development, infrastructure, as well as mechanisation while market reform, education and disaster mitigations are associated with efficiency improvement. De los Santos-Montero and Bravo-Ureta (2017) showed that an intervention programme on natural resource management positively impacted the two dimensions of productivity, i.e., technical change and technical efficiency. This finding contributed to the understanding of how an environmental intervention programme can also increase the income of poor farm households through increases in productivity.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In the event that farmers self-select into an extension program or adopt a superior production technology, the direct and indirect effects due to heterogeneity in technology or enhanced farmer capacity will be unaccounted for and the full impact will be miss measured. Other studies following the seminal work of Dinar et al (2007) employed a mixed multi-stage approach to address the issue of selectivity and technology heterogeneity (e.g., Bravo-Ureta et al, 2012, 2020Villano et al, 2015;Abdulai and Abdulai, 2016;De los Santos-Montero and Bravo-Ureta, 2017;Abdul-Rahaman and Abdulai, 2018). Even though the mixed multi-stage approach accounts for selection bias, it fails to account for the direct and indirect impacts that heterogeneous production technologies may have on both the production frontier and the efficiency function.…”
Section: Introductionmentioning
confidence: 99%