Changes in Predictive Ability with Mixed Frequency Data

This paper proposes a new regression model - a smooth transition mixed data sampling (STMIDAS) approach - that captures recurrent changes in the ability of a high frequency variable in predicting a low frequency variable. The STMIDAS regression is employed for testing changes in the ability of financial variables in forecasting US output growth. The estimation of the optimal weights for aggregating weekly data inside the quarter improves the measurement of the predictive ability of the yield curve slope for output growth. Allowing for changes in the impact of the short-rate and the stock returns in future growth is decisive for finding in-sample and out-of-sample evidence of their predictive ability at horizons longer than one year.Smooth transition, MIDAS, Predictive ability, Asset prices, Output growth

Structural Breaks and Non-Linearities for Predicting the Probability of US Recessions using the Spread

This paper proposes a structural break threshold model (SBT) to the dynamic relationship between US output growth and the spread between long- and short-term interest rates. This model is able to account for non-linearities, parameter changes and the reduction of the variability of output growth. The SBT model gives better in-sample predictions of the probability of US recessions during 1955-1999 than models with only non-linearity or structural breaks. The presence of a structural break affects the timing and the size of predictions of the probability of recession for 2001.

The Forward Premium of Euro Interest Rates

We show that euro forward rates are biased predictors of future interest rates. A small part of this bias arises from unexpected changes in interest rates, while a larger part is explained by the forward premia, which are generally not time-varying. We estimate the the 3-month forward premia for different horizons using forecasts of yields obtained with the Diebold and Li (2006) approach, extended by the inclusion of macroeconomic variables. Confidence intervals for the estimates are computed using a novel bootstrap approach. When using German data for the period before 1999, we detect a break in the dynamic correlation between yield factors, implying that estimates of the euro forward premium using pre-euro data are biased. Although the forward premia of horizons up to 36 months are on average positive, their confidence intervals indicate that they are significantly equal to zero in some periods of time. They are also positively correlated with the ECB policy rate and with a measure of the market perception that future interest rates could be higher than expected.

Endogenous Monetary Policy Regimes and the Great Moderation

This paper contributes to the literature on the changing transmission mechanism of monetary policy by introducing a model whose parameter evolution explicitly depends on the conduct of monetary policy. We find that the model fits the data well, in particular when complemented with an estimated break around 1985 that could be associated with the re-gained credibility of the central bank. The responses of output and inflation to policy shocks change not only because of the break in 1985 but also according to the monetary policy stance: policy shocks have stronger negative e¤ects when policy is tight. There is also evidence in favour of large changes in the volatility of the output equation, but not of inflation. A set of counterfactual experiments indicate that good policy and good luck contributed to the great moderation, but neither of them can fully explain it. A more general variation in the model dynamics underlying the shock transmission mechanism is required.

Student interactions in online discussion forums: their perception on learning with business simulation games

Digital technology offers new teaching methods with controversial results over learning. They allow students to develop a more active participation in their learning process although it does not always drive to unequivocal better learning outcomes. This study aims to offer additional evidence on the contribution of business simulation games to students' learning outcomes, considering student interactions in online discussion forums. We conducted a qualitative research with the online discussion forums of 5 different courses at bachelor and master levels, which involves 41 students' teams. The final sample was composed of 3681 messages posted by the students. The results reveal that some generic and specific managerial skills exert a positive influence on learning outcomes. Students mostly highlighted teamwork, decision-making, information processing, reaching agreements, and dealing with uncertainty as the most relevant contributions of the game towards their learning. These results have instructional and pedagogical implications for determining the best way to enhance students' motivation and learning outcomes when using digital technology methods, which involves recommendations that affect their design and monitoring

Macroeconomic Forecasting with Mixed Frequency Data : Forecasting US output growth and inflation.

Although many macroeconomic series such as US real output growth are sampled quarterly, many potentially useful predictors are observed at a higher frequency. We look at whether a recently developed mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth and inflation. We carry out a number of related real-time forecast comparisons using various indicators as explanatory variables. We find that MIDAS model forecasts of output growth are more accurate at horizons less than one quarter using coincident indicators ; that MIDAS models are an effective way of combining information from multiple indicators ; and that the forecast accuracy of the unemployment-rate Phillips curve for inflation is enhanced using the MIDAS approach.Data frequency ; multiple predictors ; combination ; real-time forecasting

Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions

We show how to improve the accuracy of real-time forecasts from models that include au-toregressive terms by estimating the models on ‘lightly-revised’data instead of using data from the latest-available vintage. Forecast accuracy is improved by reorganizing the data vintages employed in the estimation of the model in such a way that the vintages used in estimation are of a similar maturity to the data in the forecast loss function. The size of the expected reductions in mean squared error depend on the characteristics of the data revision process. Empirically, we …nd RMSFE gains of 2-4% when forecasting output growth and in‡ation with AR models, and gains of the order of 8% with ADL models.real-time data ; news and noise revisions ; optimal forecasts ; multi-vintage models. JEL Classification: C53

First Announcements and Real Economic Activity

The recent literature suggests that first announcements of real output growth in the US have predictive power for the future course of the economy. We show that this need not point to a behavioural relationship, whereby agents respond to the announcement, but may instead simply be a by-product of the data revision process. Initial estimates are subsequently subject to a number of rounds of revisions: the nature of these revisions is shown to be key in determining any apparent relationship between first announcements and the future course of the economy.Announcements ; real activity ; data measurement ; revisions