ICT-based market information and adoption of agricultural seed technologies: Insights from Uganda

Kiiza, Barnabas; Pederson, Glenn D.

doi:10.1016/j.telpol.2012.01.001

Cited by 84 publications

(70 citation statements)

References 14 publications

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“…However, IV regression typically reduces the precision of causal inference, and the robustness of Heckman's two-step regression is presently under scrutiny in different literature bodies because of assumptions related to its distribution of error terms (Kiiza & Pederson, 2012). In this context, PSM is considered comparatively robust because of the existence of no assumption about the error terms and a lack of requirement for any functional form of a model to conduct an empirical study (Cameron & Trivedi, 2005).…”

Section: For Causal Inference With Observational Data Instrumental Vmentioning

confidence: 99%

Access to broadband Internet and labour force outcomes: A case study of the Western Downs Region, Queensland

Alam

Mamun

2017

Telematics and Informatics

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This paper examines the causal effect of household access to broadband Internet on individuals' labour market outcomes in an Australian rural and regional context. This study uses the survey data of 391 households randomly selected from the Western Downs Region of Queensland, Australia, and employs the propensity score matching technique to make causal inferences. This study also controls selection bias issues -an aspect which has been overlooked in previous studies.This study found that the causal effect of household access to broadband Internet on individuals' labour force outcomes is not statistically significant. This finding can add value to our knowledge of the causal relationship between broadband access and labour force participation. As the rollout of a high-speed broadband network in rural and regional Australia is currently underway, the finding can be considered a benchmark for subsequent assessment of the effects of such infrastructure development on socio-economic outcomes.

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Section: For Causal Inference With Observational Data Instrumental Vmentioning

confidence: 99%

Access to broadband Internet and labour force outcomes: A case study of the Western Downs Region, Queensland

Alam

Mamun

2017

Telematics and Informatics

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“…For example, researchers have examined the use of cell phones in developing countries to assist farmers' marketing decisions (Tadesse and Bahiigwa [6]; Muto and Yamano [7]), mobile banking (Donner and Tellez [8]), and the adoption of agricultural technology (Kiiza and Pederson [9]). Donner [10] provides a comprehensive literature review of 231 studies of cell phone use in the developing world, but none of these studies considered cell phone use in the context of natural disasters.…”

Section: Information and Communication Technologiesmentioning

confidence: 99%

Cellular Telephones and Natural Disaster Vulnerability

Toya

Skidmore

2018

Sustainability

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Abstract:A global revolution in information and communication technologies (ICT) has occurred over the past few decades, emerging first in industrialized countries and then in developing countries. While researchers have examined many facets of the ICT revolution, relatively little work has systematically examined the degree to which ICT has reduced natural disaster vulnerability. In this article we use cross-country data over the 1980-2013 period to estimate the relationship between newly-emerging cell phone access/use and disaster-induced fatalities. Our estimates suggest that a one-standard-deviation increase in cell phone usage reduces disaster fatalities by nearly one half. The estimated effect increases to almost three quarters for geologic events where people are typically afflicted without warning. The largest marginal benefit from cell phones in terms of saving lives come from events where there is typically no warning, thus, many are caught by surprise; cell phones are used to call for help and coordinate assistance.

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“…2 Transport accessibility -regardless of mode -has a crucial role to play to reduce input prices and boost agricultural production (Khandker, Bakht and Koolwal, 2009;Donaldson, 2010). A growing literature also suggests the importance of access to information and communication technology to obtain market information (Kiiza andPederson, 2012, Zanello 2012).…”

Section: Introductionmentioning

confidence: 99%

Agriculture Production and Transport Infrastructure in East Africa: An Application of Spatial Autoregression

Iimi¹,

You²,

Wood‐Sichra³

et al. 2015

Policy Research Working Papers

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Africa is estimated to have great potential for agricultural production, but there are a number of constraints inhibiting the development of that potential. Spatial data are increasingly important in the realization of potential as well as the associated constraints. With crop production data generated at 5-minute spatial resolution, the paper applies the spatial tobit regression model to estimate the possible impacts of improvements in transport accessibility in East Africa. It is found that rural accessibility and access to markets are important to increase agricultural production. In particular for export crops, such as coffee, tea, tobacco, and cotton, access to ports is crucial. The elasticities are estimated at 0.3-4.6. In addition, the estimation results show that spatial autocorrelation matters to the estimation results. While a random shock in a particular locality would likely affect its neighboring places, the spatial autoregressive term can be positive or negative, depending on how fragmented the current production areas are.

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ICT-based market information and adoption of agricultural seed technologies: Insights from Uganda

Cited by 84 publications

References 14 publications

Access to broadband Internet and labour force outcomes: A case study of the Western Downs Region, Queensland

Access to broadband Internet and labour force outcomes: A case study of the Western Downs Region, Queensland

Cellular Telephones and Natural Disaster Vulnerability

Agriculture Production and Transport Infrastructure in East Africa: An Application of Spatial Autoregression

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