We present a first assessment of the predictive ability of machine learning methods for inflation forecasting in Costa Rica. We compute forecasts using two variants of k-nearest neighbors, random forests, extreme gradient boosting and a long short-term memory (LSTM) network. We evaluate their...

Nach der Mittelfristprojektion des IWH dürfte das Bruttoinlandsprodukt in Deutschland von 2015 bis 2020 um durchschnittlich 1 1/2% wachsen; das nominale Bruttoinlandsprodukt wird wohl um durchschnittlich 3% zunehmen. Nach einer Unterauslastung der Kapazitäten in den Jahren 2015 und 2016...

There are many types of econometric models used in predicting the inflation rate, but in this study we used a Bayesian shrinkage combination approach. This methodology is used in order to improve the predictions accuracy by including information that is not captured by the econometric models....

Neural networks are well suited to predict future results of time series for various data types. This paper proposes a hybrid neural network model to describe the results of the database of the New York Stock Exchange (NYSE). This hybrid model brings together a self organizing map (SOM) with a...

Nach der Mittelfristprojektion des IWH dürfte das Bruttoinlandsprodukt in Deutschland in den Jahren von 2016 bis 2021 um durchschnittlich 1,5 % wachsen; das nominale Bruttoinlandsprodukt wird wohl um durchschnittlich 3% zunehmen. Nach einer leichten Überauslastung der Kapazitäten in den...

In this study a comparative analysis of the forecasts accuracy for Spain (developed country) and Romania (developing country) was developed for the crisis period (2009 - 2013). The providers are national forecasters: Bank of Spain and FUNCAS (Spanish Savings Banks Foundation) for Spain and two...

The main objective of this study is to assess the usefulness and rationality of the inflation and unemployment rate forecasts made for Romanian by three experts in forecasting: F1, F2 and F3. All the unemployment rate forecasts over the horizon 2001 - 2013 provided by all experts do not provide...

The hierarchical structure of the Colombian Consumer Price Index (CPI) makes possible to calculate inflation as a linear combination of its subcomponents. We use SARIMA models to forecast each component of CPI and construct an forecast of inflation using a lineal combination of the forecasts of...

This paper provides a full characterization of inflation rate forecasts using the mean values from Consensus Economics for a sample of 14 Latin American countries between 1989 and 2014. It also assesses the performance of inflation rate forecasts around business cycles' turning points. Results...

This paper reports a study on the causal dynamics between spot oil price, exchange rates, and stock prices in Poland, the Czech Republic, Hungary, Romania, and Serbia. The results are compared with a benchmark analysis in which U.S. monthly data are used, and time periods are selected according...