Forecast Accuracy Awards · 2022

Asia Pacific 2022 Forecast Accuracy Award Winners

Recognising professional forecasters whose GDP growth and consumer price inflation predictions proved most accurate over the full forecasting cycle.

13 Economies recognised
24 monthsForecasting cycle
GDP + CPIVariables assessed
MAEAccuracy measure

London, April 25, 2023: Consensus Economics, the world’s leading economic survey organization, has announced the recipients of its 2022 Forecast Accuracy Award (FAA). The FAA program recognises the achievements of a select group of expert country economic forecasters who have most accurately predicted the final outturns of GDP growth and Consumer Price Inflation in their targeted economies for the year 2022.

FAA winners vary from year to year and across variables, due to exogenous shocks, data surprises and cyclical and structural adjustments. However, the winners of the 2022 FAA program are recognised for their high quality research, their commitment to regular forecasts and their ability to identify most accurately the trends and levels of key indicators over the 24 month forecasting cycle.

2022 Forecast Accuracy Award Winners

Country Company Economists
Australia Goldman Sachs Andrew Boak,                           William Nixon,                          Bill Zu
China Nomura Ting Lu,                             Jing Wang,                    Harrington Zhang,           Hannah Liu
Hong Kong Barclays Shreya Sodhani
Indonesia Moody’s Analytics Moody’s Analytics APAC Research Team
Japan NLI Research Institute Taro Saito
Malaysia Oxford Economics Alex Holmes
New Zealand ASB Bank ASB Economics Team
Philippines Barclays Shreya Sodhani
Singapore FERI Axel Angermann,                   Volker Kleff
South Korea Economist Intelligence Unit Fei Xue
Taiwan Oxford Economics Daniel von Ahlen,
Lloyd Chan
Thailand S&P Global Market Intelligence Jola Pasku
Vietnam S&P Global Market Intelligence Jola Pasku
Methodology note

How the Forecast Accuracy Awards are determined.

The awards use a consistent error-based test across the full forecasting cycle. Smaller forecast errors indicate greater accuracy.

Primary measure Mean Absolute Error

MAE compares each forecast with the eventual official outturn and measures the size of the error, regardless of whether the forecast was too high or too low.

01

Forecasts tested

Monthly real GDP growth and consumer price inflation forecasts are assessed over the 24-month forecasting cycle for 2022.

02

Official outturns

The forecasts are compared with the subsequently published official GDP and inflation estimates for each economy.

03

Absolute errors

The difference between each forecast and the outturn is measured in absolute terms, so over- and under-estimation are treated equally.

04

Overall accuracy

GDP and inflation error scores are combined to identify the panellist with the lowest overall error across the testing period.

05

Qualification

Panellists must participate consistently through the forecasting cycle so that the comparison rewards sustained forecasting performance.

Read the full methodology note

The Forecast Accuracy Awards were determined using Mean Absolute Error analysis. The errors measured were the differences between the forecasts and the actual data outturns. The forecaster with the lowest average error rate was deemed to have been the most accurate over the testing period.

The Forecasts Used The forecasts we examined were our panellists’ monthly survey contributions for 2022 Real GDP Growth and 2022 Consumer Price Inflation (CPI) expectations (annual average % change). We began collecting these forecasts in January 2021, and the 24 month forecasting cycle ended in December 2022, providing 24 monthly data points to test for each variable.

The Outturns Used The outturns we used as a comparison to the forecasts were the official estimates of 2022 GDP and CPI, which were released between January and April 2023, depending on the country and variable concerned.

The Calculation When calculating the error (the difference between the forecast and the outturn) we looked at the absolute errors, ignoring sign, as errors resulting from over-estimation and under-estimation are equivalent. We then calculated the mean average absolute error for the forecasts of each panellist for both GDP and CPI over the 24 month forecasting period.

Establishing the Most Accurate Forecaster To determine the most accurate forecaster for a given year, we added the mean absolute error rates for GDP and Inflation to identify the panellist with the lowest overall error rate. Smaller errors are best when considering accuracy, and to win the award requires the panellist to have exhibited a strong forecasting performance across both GDP and Inflation variables over the 24 month forecasting horizon.

Qualification To be considered for the award, a panellist needed to have participated consistently in our monthly surveys over the 24 month forecasting period. This ensured that no panellist gained an advantage through non-participation, or by only providing forecasts nearer the end of the 24 month cycle, when the steady release of official data can assist forecasters in making revisions.