Two different tools to evaluate quantile regression forecasts are proposed: MAD, to summarize forecast errors, and a fluctuation test to evaluate in-sample predictions. The scores of the PISA test to evaluate student proficiency is considered. Growth analysis relates school attainment to economic growth. The analysis is complemented by investigating the estimated regression and predictions not only at the centre but also in the tails. For out-of-sample forecasts the estimates in one wave are employed to forecast the following waves. The reliability of in-sample forecasts is controlled by excluding part of the sample selected by a specific rule: boys to predict girls, public schools to forecast private ones, vocational schools to predict non...
A guide to the implementation and interpretation of Quantile Regression models. This book explores t...
An analytical framework is presented for the evaluation of quantile probability forecasts. It is dem...
An introductory section shows the behavior of quantile regressions in datasets with different charac...
Two different tools to evaluate quantile regression forecasts are proposed: MAD, to summarize foreca...
Two different tools to evaluate quantile regression forecasts are proposed: MAD, to summarize foreca...
In this paper, we tackle the problem of prediction and confidence intervals for time series using a ...
Exponential smoothing methods do not involve a formal procedure for identifying the underlying data ...
The paper proposes a method for forecasting conditional quantiles. In practice, one often does not k...
Whether it is possible to improve point, quantile and density forecasts via quantile forecast combin...
Over the past decades, in educational studies, there is a growing interest in exploring heterogeneou...
Abstract The number of studies addressing issues of inequality in educational outcomes using cogniti...
In the regression framework, prediction intervals are a valuable tool to estimate the value of the r...
Abstract: Recent interest in modern regressionmodelling has focused on extending available (mean) re...
Abstract: Recent interest in modern regressionmodelling has focused on extending available (mean) re...
To get a better picture of the future behavior of different economics-related quantities, we need to...
A guide to the implementation and interpretation of Quantile Regression models. This book explores t...
An analytical framework is presented for the evaluation of quantile probability forecasts. It is dem...
An introductory section shows the behavior of quantile regressions in datasets with different charac...
Two different tools to evaluate quantile regression forecasts are proposed: MAD, to summarize foreca...
Two different tools to evaluate quantile regression forecasts are proposed: MAD, to summarize foreca...
In this paper, we tackle the problem of prediction and confidence intervals for time series using a ...
Exponential smoothing methods do not involve a formal procedure for identifying the underlying data ...
The paper proposes a method for forecasting conditional quantiles. In practice, one often does not k...
Whether it is possible to improve point, quantile and density forecasts via quantile forecast combin...
Over the past decades, in educational studies, there is a growing interest in exploring heterogeneou...
Abstract The number of studies addressing issues of inequality in educational outcomes using cogniti...
In the regression framework, prediction intervals are a valuable tool to estimate the value of the r...
Abstract: Recent interest in modern regressionmodelling has focused on extending available (mean) re...
Abstract: Recent interest in modern regressionmodelling has focused on extending available (mean) re...
To get a better picture of the future behavior of different economics-related quantities, we need to...
A guide to the implementation and interpretation of Quantile Regression models. This book explores t...
An analytical framework is presented for the evaluation of quantile probability forecasts. It is dem...
An introductory section shows the behavior of quantile regressions in datasets with different charac...