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Instability and non-linearity in the EMU. (). Marcellino, Massimiliano.
In: Working Papers.
RePEc:igi:igierp:211.

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  1. Income and wealth inequality in Malta: evidence from micro data. (2019). Georgakopoulos, Ilias.
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  2. Boosting Non-linear Predictabilityof Macroeconomic Time SeriesComplexity and benefit take-up: Empirical evidence from the Finnish homecare allowance. (2018). Virtanen, Timo ; Kauppi, Heikki.
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  3. Forecasting unemployment rates in Malta: A labour market flows approach. (2018). Ellul, Reuben.
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  4. Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques. (2016). Teräsvirta, Timo ; Kock, Anders ; Terasvirta, Timo.
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  5. A Reconsideration of the Meese-Rogoff Puzzle: An Alternative Approach to Model Estimation and Forecast Evaluation. (2016). Burns, Kelly.
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  6. Directional accuracy, forecasting error and the profitability of currency trading: model-based evidence. (2015). Moosa, Imad ; Vaz, John.
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  7. Was the recent downturn in US real GDP predictable?. (2015). Miller, Stephen ; Majumdar, Anandamayee ; GUPTA, RANGAN ; Balcilar, Mehmet.
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  8. Macroeconomic forecasting during the Great Recession: The return of non-linearity?. (2015). Mogliani, Matteo ; Marcellino, Massimiliano ; Ferrara, Laurent.
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  9. Pretesting for multi-step-ahead exchange rate forecasts with STAR models. (2015). Pascalau, Razvan ; Enders, Walter.
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  10. Enhancing the forecasting power of exchange rate models by introducing nonlinearity: Does it work?. (2015). Burns, Kelly ; Moosa, Imad A.
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  11. The unbeatable random walk in exchange rate forecasting: Reality or myth?. (2014). Moosa, Imad ; Burns, Kelly.
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  12. Was the Recent Downturn in US GDP Predictable?. (2013). Miller, Stephen ; Majumdar, Anandamayee ; GUPTA, RANGAN ; Balcilar, Mehmet.
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  13. Forecasting Nevada gross gaming revenue and taxable sales using coincident and leading employment indexes. (2013). Miller, Stephen ; Majumdar, Anandamayee ; GUPTA, RANGAN ; Balcilar, Mehmet.
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  14. Macroeconomic forecasting during the Great Recession: The return of non-linearity?. (2013). Mogliani, Matteo ; Marcellino, Massimiliano ; Ferrara, Laurent.
    In: CEPR Discussion Papers.
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  15. Was the Recent Downturn in US GDP Predictable?. (2012). Miller, Stephen ; Majumdar, Anandamayee ; GUPTA, RANGAN ; Balcilar, Mehmet.
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  16. Was the Recent Downturn in US GDP Predictable?. (2012). Miller, Stephen ; Majumdar, Anandamayee ; GUPTA, RANGAN ; Balcilar, Mehmet.
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  17. Macroeconomic forecasting during the Great Recession: The return of non-linearity?. (2012). Mogliani, Matteo ; Marcellino, Massimiliano ; Ferrara, Laurent.
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  18. Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques. (2011). Teräsvirta, Timo ; Kock, Anders ; Terasvirta, Timo.
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  19. Perspectives on Evaluating Macroeconomic Forecasts. (2010). Stekler, Herman.
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  20. Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes. (2010). Miller, Stephen ; Majumdar, Anandamayee ; GUPTA, RANGAN ; Balcilar, Mehmet.
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  21. Forecasting with nonlinear time series models. (2010). Teräsvirta, Timo ; Kock, Anders ; Terasvirta, Timo.
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  22. Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts. (2008). Rothman, Philip ; Milas, Costas.
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  23. Out-of-Sample Forecasting of Unemployment Rates with Pooled STVECM Forecasts. (2007). Milas, Costas ; Rothman, Philip .
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  24. Forecasting measures of inflation for the Estonian economy. (2006). Consolo, Agostino.
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  27. Forecasting economic variables with nonlinear models. (2005). Teräsvirta, Timo.
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  28. Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination. (2005). van Dijk, Dick ; Teräsvirta, Timo ; Medeiros, Marcelo ; Terasvirta, Timo.
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  29. The power of tests of predictive ability in the presence of structural breaks. (2005). McCracken, Michael ; Clark, Todd.
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  30. Forecasting inflation with thick models and neural networks. (2005). McAdam, Peter ; McNelis, Paul.
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  31. Modelling and Forecasting Fiscal Variables for the euro Area. (2005). Marcellino, Massimiliano ; Favero, Carlo.
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  32. Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination. (2004). van Dijk, Dick ; Teräsvirta, Timo ; Medeiros, Marcelo ; Terasvirta, Timo.
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  33. Combination forecasts of output growth in a seven-country data set. (2004). Watson, Mark ; Stock, James.
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  34. Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination. (2004). van Dijk, Dick ; Teräsvirta, Timo ; Medeiros, Marcelo.
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  35. Forecasting EMU macroeconomic variables. (2004). Marcellino, Massimiliano.
    In: International Journal of Forecasting.
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  36. The predictive content of the output gap for inflation : resolving in-sample and out-of-sample evidence. (2003). McCracken, Michael ; Clark, Todd.
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  37. Forecast-based model selection in the presence of structural breaks. (2002). McCracken, Michael ; Clark, Todd.
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  38. Forecasting EMU Macroeconomic Variables. (2002). Marcellino, Massimiliano.
    In: CEPR Discussion Papers.
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  39. Forecast Pooling for Short Time Series of Macroeconomic Variables. (2002). Marcellino, Massimiliano.
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  40. Evaluating long-horizon forecasts. (2001). McCracken, Michael ; Clark, Todd.
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  41. Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes. (2001). Gupta, Rangan ; Miller, Stephen ; Majumdar, Anandamayee.
    In: Working Papers.
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  42. Forecasting EMU macroeconomic variables. (). Marcellino, Massimiliano.
    In: Working Papers.
    RePEc:igi:igierp:216.

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  43. Forecast pooling for short time series of macroeconomic variables. (). Marcellino, Massimiliano.
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