GDP Forecasting Bias due to Aggregation Inaccuracy in a Chain- Linking Framework

When evaluating the economy’s performance, Gross Domestic Product (GDP) is the most often used indicator and it is therefore also one of the most often forecasted. Due to the shortcomings of the traditional fixed-base methods, many countries have adopted chain-linking to avoid price structure obsolescence. This has meant that GDP’s well-known accounting identities hold only approximately raising challenges for those reading the numbers, but also for forecasters that follow approaches that rely on these accounting properties. Oddly enough, the issue of aggregation is hardly mentioned in forecasting. This omission could be the result of everybody adopting the chain-linking methodology with ease and considering it unnecessary to make a point out of it, but it could also originate from ignoring the issue altogether. Whatever the reason for this omission, it could lead practitioners that are unfamiliar with the method to make unnecessary mistakes. This document presents explicitly the role of prices in a bottom-up forecasting framework and, based on it, argues that they should be taken into account when generating aggregate forecasts based on the accounting identities. Also, something that should be taken into consideration by practitioners is that discrepancies due to aggregation inaccuracy are not necessarily negligible.