This article reviews research and policy work on nonbank financial intermediation (NBFI),
taking a financial stability perspective. It first documents the growth in NBFI, reviews its …

The present paper reviews the use of big data in Asian central banks, leveraging on a
survey conducted by the Irving Fischer Committee on Central Bank Statistics (IFC) of the …

We study how millions of granular and weekly household scanner data combined with
machine learning can help to improve the real-time nowcast of German inflation. Our …

This paper exploits daily infrared images taken from satellites to track economic activity in
advanced and emerging countries. We first develop a framework to read, clean, and exploit …

Using real-time data and machine-learning methods, we produce monthly aggregates on
gross national income (GNI) for 147 Pakistani districts between 2012 and 2021. We use …

Infra-monthly time series have increasingly appeared on the radar of official statistics in
recent years, mostly as a consequence of a general digital transformation process and the …

A key lesson from central banks' experience during the COVID-19 pandemic, as both users
and producers of economic and financial data, is the need to broaden their ability to face …

The ongoing expansion of granular data sets calls for broadening official statistical
frameworks to benefit from this information in order to assist the assembling of …

ABSTRACT COVID-19 has a devastating impact on the global economy, particularly on
robustness and resilience of emerging and develo** economies'(EMDE's) economic-cum …

Official statisticians managed to quickly adapt to the consequences of the COVID-19
pandemic. Looking forward, an important issue is whether, and how, one should be …