Page 308 - Special Topic Session (STS) - Volume 3

STS544 M. Camachoa et al.
state Markov-switching variable and extended to accounts for leading
indicators. Thus, the DFM produces an index of global business cycle
condition, yields short-term forecasts of world GDP quarterly growth in real
time in a monthly basis, and estimate the real-time probabilities of being in a
recessionary regime. Our results are very consistent to the chronology of
global recessions proposed by Martinez-Garcia, Grossman and Mack (2015):
the probabilities of recession jump quickly around the peaks, remain at high
values during recessions and fall to almost zero after the troughs.

4. Discussion and conclusion
Recognizing in advance the evolution of GDP is crucial for economic
agents’ decisions. In this paper, we have reviewed the experience at BBVA
Research in the use of DFM to nowcast and forecast GDP growth in a large
sample of advanced and emerging countries. Our results show that DFM
forecast GDP growth and recession probabilities at least as well as other
alternative models. DFM forecast in a very parsimonious ways, allowing to
present easily the contribution different indicators to forecasts innovations of
GDP growth. Financial variables (e.g., the slope of the yield curve or financial
tension indexes) contain valuable information about future growth and can be
easily introduced in DFM. Additionally, DFM should be tailored to different
countries and variables, and they can be used to estimate underlying activity
in countries where official GDP statistics are not reliable. Finally, DFM allow the
introduction of useful indicators of economic activity obtained using real-time
big data (e.g., retail sales, credit cards spending, etc.), improving nowcasting
and forecasting very significantly.

References
1. Camacho, M., and R. Doménech (2012): “MICA-BBVA: a factor model of
economic and financial indicators for short-term GDP forecasting,”
SERIEs, 3, 475–497. https://goo.gl/WGa4df
2. Camacho, M., and R. Doménech (2019): “Nowcasting and Forecasting
with DynamicFactors Models: Some Experiences and Lessons,” Mimeo.
BBVA Research. https://bit.ly/2ZOsotc
3. Camacho, M., G. Perez-Quiros and P. Poncela (2013): “Short-term
forecasting for empirical economists: A survey of the recently proposed
algorithms,” Foundations and Trends in Econometrics, 6, 101-161.
4. Camacho, M., and A. García-Serrador (2014): The EURO-STING revisited:
the usefulness of financial indicators to obtain Euro area GDP forecasts,”
Journal of Forecasting 33, 186-197.
5. Camacho, M., and J. Martínez-Martín (2014): “Real-time forecasting US
GDP from small-scale factor models,” Empirical Economics, 47, 347-364.

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