Panel Nowcasting for Countries Whose Quarterly GDPs are Unavailable

By Omer Faruk Akbal, Seung M Choi, Futoshi Narita, Jiaxiong Yao

August 4, 2023

Preview Citation

Format: Chicago

Omer Faruk Akbal, Seung M Choi, Futoshi Narita, and Jiaxiong Yao. Panel Nowcasting for Countries Whose Quarterly GDPs are Unavailable, (USA: International Monetary Fund, 2023) accessed November 21, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

Quarterly GDP statistics facilitate timely economic assessment, but the availability of such data are limited for more than 60 developing economies, including about 20 countries in sub-Saharan Africa as well as more than two-thirds of fragile and conflict-affected states. To address this limited data availablity, this paper proposes a panel approach that utilizes a statistical relationship estimated from countries where data are available, to estimate quarterly GDP statistics for countries that do not publish such statistics by leveraging the indicators readily available for many countries. This framework demonstrates potential, especially when applied for similar country groups, and could provide valuable real-time insights into economic conditions supported by empirical evidence.

Subject: Commodity prices, Data collection, Economic and financial statistics, Economic forecasting, Export fluctuations, Foreign exchange, International trade, Prices, Purchasing power parity

Keywords: Annex II, Commodity prices, Data availability, Data availablity, Data collection, Developing economies, Export fluctuations, Fragile and conflict-affected states, GDP, GDP statistic, Global, Growth data, Low-income countries, Nowcasting, Panel Nowcasting, Purchasing power parity, Sub-Saharan Africa

Publication Details

Pages:

36
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2023/158
Stock No:

WPIEA2023158
ISBN:

9798400245053
ISSN:

1018-5941

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