This paper analyzes the effect of planned fiscal consolidation on GDP growth forecast errors from the years 2010–2013 using cross section analyses and fixed effects estimations. Our main findings are that fiscal multipliers have been underestimated in most instances for the year 2011 while we...

This paper analyzes the effect of planned fiscal consolidation on GDP growth forecast errors from the years 2010-2013 using cross section analyses and fixed effects estimations. Our main findings are that fiscal multipliers have been underestimated in most instances for the year 2011 while we...

This paper considers panel growth regressions in the presence of model uncertainty and reverse causality concerns. For this purpose, my econometric framework combines Bayesian Model Averaging with a suitable likelihood function for dynamic panel models with weakly exogenous regressors and fixed...

This tutorial shows how to use the jubilee package in R to forecast the 10-year and 20-year growth trajectory of S&P 500 Index. R programs are provided to run the regressions, make predictions, and plot the charts. Additionally, in order to capture the short-horizon volatility (less than 10...

This paper analyzes the effect of planned fiscal consolidation on GDP growth forecast errors from the years 2010-2013 using cross section analyses and fixed effects estimations. Our main findings are that fiscal multipliers have been underestimated in most instances for the year 2011 while we...

A reason for revising the EU fiscal rules in the early 2010s was to improve member states' forecasts against a background of documented biases in official projections. Using data from Stability and Convergence Programmes and the European Commission's Spring Forecasts, evidence is presented which...

Previous research finds that EPS growth is difficult to predict and reasons that much of the observed variation in valuation multiples is due to mispricing (e.g., Lakonishok, Shleifer, and Vishny, 1994; Chan, Karceski, and Lakonishok, 2003; Israel, Laursen, and Richardson, 2021). We revisit these...

This study introduces the Ensemble Empirical Mode Decomposition (EEMD) technique to forecasting popular vote share. The technique is useful when using polling data, which is pertinent when none of the main candidates is the incumbent. Our main interest in this study is the short- and long-term...