This paper analyzes the impact of data gap in Millennium Development Goals’ (MDGs) performance indicators on actual performance success of MDGs. Performance success, within the MDG framework, is quantified using six different ways proposed in the existing literature, including both absolute and relative performance and deviation from historical transition paths of MDG indicators. The empirical analysis clearly shows that the data gap in performance measurement is a significant predictor of poor MDG performance in terms of any of the six progress measures. Larger the data gap or weaker the performance measurement system, lesser is the probability of MDG performance success. The empirical methodology used in the paper combines a Heckman correction and instrumental variable estimation strategies to simultaneously account for potential endogeneity of the key data gap variable and bias due to sample selection. This result holds true even after controlling for overall national statistical capacity and a variety of socioeconomic factors. The paper underlines the need to strengthen the performance measurement system attached to the 2030 agenda for sustainable development and the associated Sustainable Development Goals (SDGs). This paper is the first attempt at empirically evaluating the value of data in the context of international development goals and gives empirical evidence for the need to harness the “data revolution” for sustainable development.
World Development, Volume 93, May 2017, Pages 260-278,