# Information and Communication Technologies and Agricultural Production: New Evidence from Africa
## 2 Review of Empirical Literature  
Empirical quantitative research on the effect of information and communication technologies on agricultural production in Africa has been conducted from two main methodological approaches. The first approach involves cross-country analysis, often using cross-country panel data (e.g., [56; 59; 60]), while the other usually involves country-specific or sub-country level studies using micro-level data (e.g., [61; 62]). A strand of the literature using the latter approach has sought to understand or describe the channels by which information and communication technologies affect agricultural production and value chains, characterize the stakeholders or actors driving this effect, as well as the factors shaping the adoption and use of information and communication technologies in agriculture (e.g., [41; 63; 64; 65]). Generally, the quantitative evidence, particularly that using cross-country data, is more scant, especially in Africa. This section presents a brief review of the existing literature to help contextualize the key objectives of this study, as well as its contribution to the scholarly literature. The empirical evidence based on the analysis of cross-country panel data in Africa suggests that information and communication technologies have a significant effect on agricultural production (see, for example, [59; 66]). [PERSON] and [PERSON] [67] assessed the impact of ICTs on agricultural production using qualitative data. They found that ICTs link small-scale producers to the markets. [PERSON] et al. [66] assessed whether specific ICTs have a significant impact on agricultural production. This study showed that ICT had a positive but insignificant effect on net profit per acre [66]. It should be noted that the years after [PERSON] et al. 's study have seen the advent and growing penetration of many mobile-phone-based digital innovations, such as mobile money, 3G/4G internet services, and other mobile phone applications that could positively influence the relationship between the use of mobile phone and agricultural production in many significant ways (see [68; 69]). [PERSON] et al. [66] found additionally that the impact of ICTs, seed, fertilizer and credit significantly increased agricultural productivity in Zambia. Unlike [PERSON] et al. [66], a later study by [PERSON] [59], which also used panel data of African countries, showed that both mobile phones and internet play significant roles in agricultural development in Africa. [PERSON] [59] further showed nonlinear effects where mobile phone penetration has an increasing positive effect on agricultural value added, while internet usage has a U-shape effect on agricultural value added. It is important to note that the study by [PERSON] [59] covered 44 African countries over a period of 15 years, from 2001 to 2015, as well as using system Generalized Method of Moments (GMM) estimator, and these factors could account for different results on mobile phones. A more recent study by [PERSON] et al. [56] focused on the effect of ICT infrastructure on agricultural sector performance in sub-Saharan Africa, using agricultural value added and agriculture products as a percentage of total merchandise export as the measures of performance. While findings by [PERSON] et al. [56] are qualitatively similar to the key findings by [PERSON] [59], their study presents additional important insights, particularly through the use of analytical models that help to delineate the long-run and short-run effects. With data covering 23 years (1995-2017) from 39 countries and employing panel autoregressive distributed lag (ARDL) approach, where mobile cellular telephone subscription and individual using internet were the key independent variables, [PERSON] et al. [56] found that ICT infrastructure has a positive effect on agricultural sector performance in the long run but the same cannot be said of the short run. An equally recent study by [PERSON] et al.