Nowcasting Gdp in the Euro Area
نویسندگان
چکیده
This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MFVAR) approaches to model speci cation in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coe¢ cients, whereas MF-VAR does not restrict the dynamics and therefore can su¤er from the curse of dimensionality. But if the restrictions imposed by MIDAS are too stringent, the MF-VAR can perform better. Hence, it is di¢ cult to rank MIDAS and MF-VAR a priori, and their relative ranking is better evaluated empirically. In this paper, we compare their performance in a relevant case for policy making, i.e., nowcasting and forecasting quarterly GDP growth in the euro area, on a monthly basis and using a set of 20 monthly indicators. It turns out that the two approaches are more complementary than substitutes, since MF-VAR tends to perform better for longer horizons, whereas MIDAS for shorter horizons. JEL Classi cation Codes: E37, C53
منابع مشابه
Nowcasting is not just Contemporaneous Forecasting
We consider the reasons for nowcasting, the timing of information and sources thereof, especially contemporaneous data, which introduce different aspects compared to forecasting. We allow for the impact of location shifts inducing nowcast failure and nowcasting during breaks, probably with measurement errors. We also apply a variant of the nowcasting strategy proposed in Castle and Hendry (2009...
متن کاملNowcasting Inflation Using High Frequency Data.dvi
This paper proposes a methodology to nowcast and forecast inflation using data with sampling frequency higher than monthly. The nowcasting literature has been focused on GDP, typically using monthly indicators in order to produce an accurate estimate for the current and next quarter. This paper exploits data with weekly and daily frequency in order to produce more accurate estimates of inflatio...
متن کاملDynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.
Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and...
متن کاملAn experimental sentiment indicator for the euro area – the relevance of broad - based sectoral shifts in economic sentiment
The Economic Sentiment Indicator (ESI), published by the European Commission on a monthly basis, is a powerful tool for tracking year on year GDP growth. However, its performance is weaker when GDP growth is expressed in quarter on quarter changes. This paper investigates whether cross-sector survey data gathered in the framework of the harmonised EU Business and Consumer Survey (EU BCS) can be...
متن کاملEstimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components
The paper estimates a large-scale mixed-frequency dynamic factor model for the euro area, using monthly series along with Gross Domestic Product (GDP) and its main components, obtained from the quarterly national accounts. The latter define broad measures of real economic activity (such as GDP and its decomposition by expenditure type and by branch of activity) that we are willing to include in...
متن کامل