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Spanish GDP short-term point and density forecasting using a mixed-frequency dynamic factor model

Fresoli, Diego - In: SERIEs : Journal of the Spanish Economic Association 15 (2024) 2, pp. 145-177

We have assessed the effect of data releases when constructing short-term point and density forecasts of the Spanish gross domestic product growth. For this purpose, we considered a real-forecasting exercise in which we defined several pseudo-data vintages that had a mixture of monthly and...

Persistent link: https://www.econbiz.de/10015073109

EuroMInd-D : a density estimate of monthly gross domestic product for the euro area

Proietti, Tommaso; Marczak, Martyna; Mazzi, Gian Luigi - 2015

EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom-up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model of...

Persistent link: https://www.econbiz.de/10010502772

GDP Growth Predictions Through the Yield Spread. Time-Variation and Structural Breaks

De Pace, Pierangelo - 2011

We use TVP models and real-time data to describe the evolution of the leading properties of the yield spread for output growth in five European economies and in the US over the last decades and until the third quarter of 2010. We evaluate the predictive performance of benchmark term-structure...

Persistent link: https://www.econbiz.de/10013134715

Nowcasting Spanish GDP Growth in Real Time : 'One and a Half Months Earlier'

de Antonio Liedo, David - 2010

The sharp decline in economic activity registered in Spain over 2008 and 2009 has no precedents in recent history. After ten prosperous years with an average GDP growth of 3.7%, the current recession places non-judgemental forecasting models under stress. This paper evaluates the Spanish GDP...

Persistent link: https://www.econbiz.de/10013135034

Forecasting GDP Growth Rates Using Google Trends in the United States and Brazil

Bantis, Evripidis; Clements, Michael P.; Urquhart, Andrew - 2021

In this paper we consider the value of Google Trends search data for nowcasting (and forecasting) GDP growth for a developed (U.S.) and emerging-market economy (Brazil). Our focus is on the marginal contribution of "Big Data" in the form of Google Trends data over and above that of traditional...

Persistent link: https://www.econbiz.de/10013222547

A dynamic factor model for nowcasting Canadian GDP growth

Chernis, Tony; Sekkel, Rodrigo - 2017

This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data. The model is then used to generate nowcasts, predictions of the recent past and...

Persistent link: https://www.econbiz.de/10011592353

A high-frequency GDP indicator for Switzerland

Kronenberg, Philipp - 2024

This paper presents a weekly GDP indicator for Switzerland, which addresses the limitations of existing economic activity indicators using alternative high-frequency data created in the wake of the COVID-19 pandemic. The indicator is obtained from a Bayesian mixed-frequency dynamic factor model...

Persistent link: https://www.econbiz.de/10014562886

Nowcasting Monthly GDP with Big Data : A Model Averaging Approach

Proietti, Tommaso; Giovannelli, Alessandro - 2020

Gross domestic product (GDP) is the most comprehensive and authoritative measure of economic activity. The macroeconomic literature has focused on nowcasting and forecasting this measure at the monthly frequency, using related high frequency indicators. We address the issue of estimating monthly...

Persistent link: https://www.econbiz.de/10014097790

Step by step - a quarterly evaluation of EU Commission's GDP forecasts

Heinisch, Katja - Leibniz-Institut für Wirtschaftsforschung Halle - 2024

The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a...

Persistent link: https://www.econbiz.de/10015078241

Forecasting inflation in Vietnam with univariate and vector autoregressive models

2017

In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To … properties of inflation in Vietnam. Then, I compute the pseudo out-of-sample root mean square error (RMSE) as a measure of … forecasting models from among the different candidates. I find that VAR_m2 is the best monthly model to forecast inflation in …

Persistent link: https://www.econbiz.de/10011663290