TY - UNPB
T1 - The Importance of Updating: Evidence from a Brazilian Nowcasting Model
AU - Bragoli, Daniela
AU - Metelli, Luca
AU - Modugno, Michele
PY - 2014
Y1 - 2014
N2 - How often should we update predictions for economic activity? Gross domestic
product is a quarterly variable disseminated usually a couple of months after the end of the quarter, but many other macroeconomic indicators are released with a higher frequency, and
financial markets react very strongly to them. However, most of the professional forecasters, including the IMF, the OECD, and most central banks, tend to update their forecasts of economic activity only two to four times a year. The main exception is the Central Bank of Brazil which is responsible for collecting and publishing a daily survey on GDP and other variables.
The aim of this article is to evaluate the forecasting performance of the Central Bank of Brazil Survey and to compare it with the mechanical forecasts based on state-of-the-art nowcasting techniques. Results indicate that institutional forecasts perform as well as model-based forecasts.
The latter finding suggests that, on the one hand, judgmental forecasters do not have computational limitations and are able to incorporate very quickly new information in a way that is as efficient as a machine. On the other hand, it confirms what has been found in other studies, namely that a linear time invariant model does a good job and hence that eventual nonlinearities, time variations and soft information (such as weather conditions or government decisions) that could be incorporated by judgment, do not provide new important information.
AB - How often should we update predictions for economic activity? Gross domestic
product is a quarterly variable disseminated usually a couple of months after the end of the quarter, but many other macroeconomic indicators are released with a higher frequency, and
financial markets react very strongly to them. However, most of the professional forecasters, including the IMF, the OECD, and most central banks, tend to update their forecasts of economic activity only two to four times a year. The main exception is the Central Bank of Brazil which is responsible for collecting and publishing a daily survey on GDP and other variables.
The aim of this article is to evaluate the forecasting performance of the Central Bank of Brazil Survey and to compare it with the mechanical forecasts based on state-of-the-art nowcasting techniques. Results indicate that institutional forecasts perform as well as model-based forecasts.
The latter finding suggests that, on the one hand, judgmental forecasters do not have computational limitations and are able to incorporate very quickly new information in a way that is as efficient as a machine. On the other hand, it confirms what has been found in other studies, namely that a linear time invariant model does a good job and hence that eventual nonlinearities, time variations and soft information (such as weather conditions or government decisions) that could be incorporated by judgment, do not provide new important information.
KW - Nowcasting, Updating, Dynamic Factor Model
KW - Nowcasting, Updating, Dynamic Factor Model
UR - http://hdl.handle.net/10807/63461
M3 - Working paper
BT - The Importance of Updating: Evidence from a Brazilian Nowcasting Model
ER -