Data transparency and GDP growth forecast errors

Roberta Gatti, Daniel Lederman, Asif Islam, Ha Nguyen, Rana Lotfi and Mennatallah Emam Mousa

Journal of International Money and Finance, 2024, vol. 140, issue C

Abstract: This paper examines the role of data transparency in explaining gross domestic product (GDP) growth forecast errors - the difference between forecasted and realized growth. On average, a one standard deviation increase in the log of a country’s Statistical Capacity Index, a measure of data capacity and transparency, is associated with a decline in absolute forecast errors by 0.44 and 0.49 percentage points for World Bank and International Monetary Fund (IMF) forecasts, respectively. The role of the overall data ecosystem, not just elements related to growth forecasting, is important for forecast accuracy. The study also establishes that forecast errors are large, the Middle East and North Africa region has the largest forecast errors among the world regions, and World Bank forecasts are more accurate and less optimistic than those from the IMF and the private sector.

Keywords: GDP Growth Forecasts; Forecast Error; Optimism; Economic Outlook; Data Transparency; Statistical Capacity (search for similar items in EconPapers)
JEL-codes: C82 E01 E17 E66 O47 O50 R11 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Working Paper: Data Transparency and GDP Growth Forecast Errors (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jimfin:v:140:y:2024:i:c:s0261560623001924

DOI: 10.1016/j.jimonfin.2023.102991

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