The tests carried out by Blanchard and Leigh (2013; IMF, 2012) and Fátas and Summers (2018) are extended here into a panel framework in order to assess the empirical basis of the so-called IMF "mea culpa" regarding the underestimation of Keynesian multipliers during the euro area crisis. The...

We analyse the performance of financial market variables in nowcasting Finnish quarterly GDP growth. In particular, we assess if prediction accuracy is affected by the sampling frequency of the financial variables. Therefore, we apply MIDAS models that allow us to nowcast quarterly GDP growth...

The paper provides a disaggregated mixed-frequency framework for the estimation of GDP. The GDP is disaggregated into components that can be forecasted based on information available at higher sampling frequency, i.e., monthly, weekly, or daily. The model framework is applied for Greek GDP...

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...

The paper compares two forecasts of Slovak GDP, the first with high-frequency data and the second without them. We utilize the last observation from the economic activity index acting as a short-term GDP forecast. We use data from 2000 to 2024 in weekly frequencies and have 27 variables related...

Objective: The objective of the article is to prove the empirical and predictive value of the aggregate opinions of businesses and households for expanding cyclical macroeconomic data in Russia, especially during the coronavirus shocks. Research Design & Methods: We use qualitative information...

We present in this paper an alternative approach to determining and predicting the fluctuations in the daily prices and stock returns of a first-generation bank in the Nigerian Stock Market (NSM). The approach uses a three-state Markov to estimate the expected duration of the asset returns in...

The out-of-sample R2 is designed to measure forecasting performance without look-ahead bias. However, researchers can hack this performance metric even without multiple tests by constructing a prediction model using the intuition derived from empirical properties that appear only in the test...

I conduct an exploratory study about the feasibility of factor timing in the Chinese stock market, covering 24 representative and well-identified risk factors in 10 categories from the literature. The long-short portfolio of short-term reversal exhibits strong out-of-sample predictability, which...

This study discusses the trading behavior of foreign investors with respect to economic uncertainty in the South Korean stock market from a time-varying perspective. We employ a news-based measure of economic uncertainty along with the model of time-varying parameter vector autoregression with...