Page 294 - Special Topic Session (STS) - Volume 3

STS544 Paolo F. et al.

Nowcasting finnish real economic activity: A
machine learning approach
2
1
Paolo Fornaro , Henri Luomaranta
1 Research Institute of the Finnish Economy
2 Statistics Finland and University Of Toulouse 1

Abstract
We develop a nowcasting framework based on micro-level data in order to
provide faster estimates of the Finnish monthly real economic activity
indicator, the Trend Indicator of Output (TIO), and of quarterly GDP. In
particular, we rely on firm-level turnovers, which are available shortly after the
end of the reference month, to form our set of predictors. The nowcasts are
obtained from a range of statistical models and machine learning
methodologies which are able to handle high-dimensional information sets.
The results of our pseudo-real-time analysis indicate that a simple nowcasts'
combination based on these models provides faster estimates of the TIO and
GDP, without increasing substantially the revision error. Finally, we examine
the nowcasting accuracy obtained by relying on traffic data extracted from the
Finnish Transport Agency website and find that using machine learning
techniques in combination with this big-data source provides competitive
predictions of real economic activity.

Keywords
Flash Estimates, Machine Learning, Micro-level Data, Nowcasting

1. Introduction
Statistical agencies, central banks, research institutes and private
businesses have access to (and produce) thousands of economic and financial
indicators. However, this wealth of information has not been directly
translated into a faster and more accurate production of important economic
statistics, such as the GDP. Statistical institutes publish economic indicators
with considerable lag and the initial estimates are revised considerably over
time. The advantages of having a timely picture of the state of the economy
are multiple and concern a range of economic actors such as the central bank,
the government and private investors and businesses. Providing this type of
information in a timely manner would be invaluable, because it would
contribute in reducing the uncertainty of the current state of the economy,
thus leading to better informed decisions. The economic advantages of having
a timely picture of the economy have not been disregarded by the statistical
and academic community.

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