Challenges in measuring the impact of Market Information Systems

Abstract

Evaluation of the impact of investments in agricultural market information systems (MIS) on market performance faces several methodological challenges. These include: (a) defining the dimensions of market performance to measure (which is a function of whom the MIS is designed to serve) and identifying reliable indicators of performance dimensions; (b) identifying the pathways through which improved market information affects these dimensions of performance; (c) establishing a reliable baseline against which to measure improved performance; (d) distinguishing between investments in MIS and general improvements in information availability; (e) assessing the contribution of complementary investments and policy changes that frequently accompany the creation of MIS; (f) establishing a credible counterfactual concerning the market situation that would have prevailed in the absence of the MIS; and (g) interpreting the validity of stakeholders' statements and governments' revealed preferences, regarding the utility of MIS. Many of these challenges arise because improved market information can affect the welfare of market actors through improved market polices and increased competition, even if these actors do not have direct access to that information. This article discusses these challenges and identifies approaches that may be useful in developing a ''convergence of evidence'', concerning whether investment in a given MIS is socially worthwhile.

Factors Limiting and Affecting the Use of Market Information Systems in Sahelian Countries

“…Subervie [28] who showed that the ESOKO MIS representing a second-generation MIS enabled producers to receive higher prices for maize around 10% and higher prices for peanuts reaching around 7%. However, for reasons of methodology and limitations observed, authors such as Staatz et al [31] have reservations about the generalization of the results obtained from these studies for all types of…”

Food Systems for an Urbanizing World

“…Market information systems have been shown to lead to a more equitable distribution of bargaining power within the food system, to improve market efficiency through better private decision-making and to improve the design and implementation of government programmes and technology development. 240 As cities conduct urban food system assessments through the TRANSFORM lens, attention may need to be focused on identifying ways to source more food from smallholder producers and SMEs (inclusiveness), to offer more nutritious/healthy food choices and to diversify food sources for greater resilience (including local procurement). More function-specific assessments (e.g.…”

Agricultural market information systems in developing countries: New models, new impacts

“…MIS are expected to have multiple impacts but major methodological difficulties are encountered in their measurement (Staatz et al, 2014). First, MIS may help improve public policy by helping policymakers better consider the market situation and its dynamics.…”

“…Although they arouse the interest of donors and are the subject of a growing number of studies, microeconometric impact analyzes do not provide a full assessment of MIS. These assessment methods are not applicable for all types of MIS, or for all contexts (Staatz et al, 2014). When they can be implemented, the validity of their results is only conditional: the results are valid only in the context of the study, i.e.…”

“…The last three articles in this issue deal with the impact of MIS. Staatz, Kizito, Weber and Dembélé (2014) list the methodological challenges of assessing the different potential impacts of MIS on the balance of power between farmers and traders, on the ability of market players to seize the best trading opportunities, and on the design and implementation of public policies. They identify four major challenges: selecting appropriate indicators; establishing a baseline; distinguishing between direct impacts of ICT and impacts of MIS based on these technologies; overcoming the problem of causal inference.…”