Quantile factor models (QFM) represent a new class of factor models for high‐dimensional panel da... more Quantile factor models (QFM) represent a new class of factor models for high‐dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables. We propose a quantile regression approach, labeled Quantile Factor Analysis (QFA), to consistently estimate all the quantile‐dependent factors and loadings. Their asymptotic distributions are established using a kernel‐smoothed version of the QFA estimators. Two consistent model selection criteria, based on information criteria and rank minimization, are developed to determine the number of factors at each quantile. QFA estimation remains valid even when the idiosyncratic errors exhibit heavy‐tailed distributions. An empirical application illustrates the usefulness of QFA by highlighting the role of extra factors in the forecasts of U.S. GDP growth and inflation rates using a large set of predictors.
This paper analyses the evolution in Spain of research output in the field of Economics over the ... more This paper analyses the evolution in Spain of research output in the field of Economics over the last decade. Several bibliographical criteria related to the quality and impact of the scientific journals where economists publish their work are used to elaborate rankings by institutions and individual researchers. The information provided by those rankings can be useful for several potential users. Amongst them, there are the following: (i) the Agencies in charge of evaluating projects in order to allocate research funds among the competing institutions and researchers who apply for them.; (ii) the undergraduate and graduate students who wish to choose the right institution where to follow a B.A. or Ph.D. programme, respectively; and (iii) those researchers holding a Ph.D who wish to find an institution where to undertake further research careers.
In this paper we address the issue of the efficient estimation of the cointegrating vector in lin... more In this paper we address the issue of the efficient estimation of the cointegrating vector in linear regression models with variables that follow general (higher order and fractionally) integrated processes. ... To our knowledge, this item is not available for download. To find whether ...
Quantile factor models (QFM) represent a new class of factor models for high‐dimensional panel da... more Quantile factor models (QFM) represent a new class of factor models for high‐dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables. We propose a quantile regression approach, labeled Quantile Factor Analysis (QFA), to consistently estimate all the quantile‐dependent factors and loadings. Their asymptotic distributions are established using a kernel‐smoothed version of the QFA estimators. Two consistent model selection criteria, based on information criteria and rank minimization, are developed to determine the number of factors at each quantile. QFA estimation remains valid even when the idiosyncratic errors exhibit heavy‐tailed distributions. An empirical application illustrates the usefulness of QFA by highlighting the role of extra factors in the forecasts of U.S. GDP growth and inflation rates using a large set of predictors.
This paper analyses the evolution in Spain of research output in the field of Economics over the ... more This paper analyses the evolution in Spain of research output in the field of Economics over the last decade. Several bibliographical criteria related to the quality and impact of the scientific journals where economists publish their work are used to elaborate rankings by institutions and individual researchers. The information provided by those rankings can be useful for several potential users. Amongst them, there are the following: (i) the Agencies in charge of evaluating projects in order to allocate research funds among the competing institutions and researchers who apply for them.; (ii) the undergraduate and graduate students who wish to choose the right institution where to follow a B.A. or Ph.D. programme, respectively; and (iii) those researchers holding a Ph.D who wish to find an institution where to undertake further research careers.
In this paper we address the issue of the efficient estimation of the cointegrating vector in lin... more In this paper we address the issue of the efficient estimation of the cointegrating vector in linear regression models with variables that follow general (higher order and fractionally) integrated processes. ... To our knowledge, this item is not available for download. To find whether ...
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Papers by Juan J. Dolado