Article 2KMPD Realtime global GDP growth at 4.4% and not 3.5% shows a far stronger economic boom

Realtime global GDP growth at 4.4% and not 3.5% shows a far stronger economic boom

by
brian wang
from NextBigFuture.com on (#2KMPD)

The relative strength of nowcast projections (global growth at 4.4%) compared with more staid IMF forecasts (global growth 3.5%) are a result of ebullient consumer and business confidence surveys, particularly the US. Nowcasts, like those from Fulcrum and the Federal Reserve Bank of New York, rely heavily on "soft" survey data, as it has proven useful in improving the accuracy of projections (pdf). The IMF's widely followed projections typically rely more on "hard" data, like industrial production or employment statistics, which are backward looking and published with a lag to soft data.

Fulcrum projects that global growth will average out to 4% for 2017 and 4.2% in 2018.

If the new projections are correct the world economy would be over $85 trillion at the end of 2018 instead of $83.8 trillion per current IMF projections.

Some observers believe American consumers and businesses are irrationally exuberant about president Trump's ability to cut taxes, reduce regulation, and boost infrastructure spending. However, if the tax cuts and regulation cuts materialize then it suggests it would be a multi-trillion global boom over the next 4-8 years.

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The hard versus soft data methods are discussed in this paper.

In the paper, they examined the role that soft data (qualitative surveys of economic activity) play in nowcasting US GDP by estimating a dynamic factor model in which a survey-specific activity factor interacts with a hard-data-only activity factor. We find evidence that soft data is important both for nowcasting the contemporaneous observations of hard data yet to be released and to predict their future developments, confirming the results of much of the literature on the topic. They also examine the implications for tracking economic activity of two important issues: the divergence between the income and expenditure measures of output, and the lingering residual seasonality present in GDP estimates. Both problems call for downplaying the role of quarterly GDP numbers in tracking the economy in real time, in favor of measures derived from a wealth of economic indicators, in which soft data play an important role.

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