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IMF Research Perspective (formerly published as IMF Research Bulletin) is a new, redesigned online newsletter covering updates on IMF research. In the inaugural issue of the newsletter, Hites Ahir interviews Valeria Cerra; and they discuss the economic environment 10 years after the global financial crisis. Research Summaries cover the rise of populism; economic reform; labor and technology; big data; and the relationship between happiness and productivity. Sweta C. Saxena was the guest editor for this inaugural issue.
Mr. Abdoul A Wane and Jing Xie

Abstract This chapter analyzes interactions between digitalization and big data innovations and institutional quality, and how these interactions influence economic outcomes. It discusses the increasingly important role of e-government in the provision of online public services, the importance of expanding the existing telecommunication infrastructure, and the necessity of enhancing the ability of populations to use e-government services (the “human capital” dimension). The empirical analysis uses data from 132 countries and confirms the potential of these

, and methodological accuracy in harnessing the power of big data for better policymaking ,” conclude Cornelia Hammer and Diane Kostroch, both of whom are in the IMF’s Statistics Department. The key to success lies in putting together a dynamic environment of people and processes that can take big data innovations forward and put them to work in a timely fashion without falling prey to bureaucratic inertia. ▪

Cornelia Hammer, Ms. Diane C Kostroch, and Mr. Gabriel Quiros-Romero

, organizational, and budgetary challenges . The success of big data projects lies not in implementing a particular piece of technology, but rather in establishing an environment of people and processes that take big data innovations forward and put them to work. Given the diverse skills needed to deal with big data, it also provides an opportunity for organizations to break their internal silos, including between users and producers of data and statistics . From individual applications of big data to its incorporation into the systematic, regular, and large

Cornelia Hammer, Ms. Diane C Kostroch, and Mr. Gabriel Quiros-Romero
Big data are part of a paradigm shift that is significantly transforming statistical agencies, processes, and data analysis. While administrative and satellite data are already well established, the statistical community is now experimenting with structured and unstructured human-sourced, process-mediated, and machine-generated big data. The proposed SDN sets out a typology of big data for statistics and highlights that opportunities to exploit big data for official statistics will vary across countries and statistical domains. To illustrate the former, examples from a diverse set of countries are presented. To provide a balanced assessment on big data, the proposed SDN also discusses the key challenges that come with proprietary data from the private sector with regard to accessibility, representativeness, and sustainability. It concludes by discussing the implications for the statistical community going forward.
Cornelia Hammer, Ms. Diane C Kostroch, and Mr. Gabriel Quiros-Romero

. Big data have the potential to help address development challenges and meet demands for compiling Sustainable Development Goals (SDG) indicators, such as gender equality. 6 The private company LinkedIn is already using its granular data to publish gender diversity statistics and provide training on gender statistics ( Karani 2017 ). 19. Following the IMF Big Data and Analytics Symposium, the IMF in-house Big Data Innovation Challenge paved the way for innovative ways to leverage big data in future work of the IMF . The top six ideas were approved for proof of

Yasmin Alem and Jacinta Bernadette Shirakawa
Based on internal data, this paper finds that the capacity development program of the IMF’s Statistics Department has prioritized technical assistance and training to fragile and conflict-affected states. These interventions have yielded only slightly weaker results in fragile states than in other states. However, capacity development is constantly needed to make up for the dissipation of progress resulting from insufficient resources that fragile and conflict-affected states allocate to the statistical function, inadequate inter-agency coordination, and the pervasive impact of shocks exogenous to the statistical system. Greater coordination with other capacity development providers and within the IMF can help partially overcome low absorptive capacity in fragile states. Statistical capacity development is more effective when it is tailored to countries’ level of fragility.
Yasmin Alem and Jacinta Bernadette Shirakawa

statistics. Below are a few examples of how STA is using Big Data innovation in FCS. In the Republic of Congo, administrative data has been utilized to develop high frequency indicators (HFIs). STA provided CD in 2019 and 2020 to use sales data from the monthly value added tax database for the compilation of GDP estimates and for the development of HFIs. Tax data offer timely and inexpensive source data for large parts of the formal economy but are often underused because of the absence of sharing agreements with the tax office and difficulties inherent to large datasets