In this paper, we empirically assess the predictive accuracy of a large group of models that are speci…ed using principle components and other shrinkage techniques, including Bayesian model averaging and various bagging, boosting, least angle regression and related methods. Our results suggest that model averaging does not dominate other well designed prediction model speci…cation methods, and that using "hybrid"combination factor/shrinkage methods often yields superior predictions. More speci…cally, when using recursive estimation windows, which dominate other "windowing" approaches, "hybrid" models are mean square forecast error "best" around 1/3 of the time, when used to predict 11 key macroeconomic indicators at various forecast horizons. Baseline linear (factor) models also "win" around 1/3 of the time, as do model averaging methods. Interestingly, these broad …ndings change noticably when considering di¤erent sub-samples. For example, when used to predict only recessionary periods, "hybrid" models "win" in 7 of 11 cases, when condensing …ndings across all "windowing" approaches, estimation methods, and models, while model averaging does not "win" in a single case. However, in expansions, and during the 1990s, model averaging wins almost 1/2 of the time. Overall, combination factor/shrinkage methods "win" approximately 1/2 of the time in 4 of 6 di¤erent sample periods. Ancillary …ndings based on our forecasting experiments underscore the advantages of using recursive estimation strategies, and provide new evidence of the usefulness of yield and yield-spread variables in nonlinear prediction model speci…cation.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. In this paper, we empirically assess the predictive accuracy of a large group of models based on the use of principle components and other shrinkage methods, including Bayesian model averaging and various bagging, boosting, LASSO and related methods Our results suggest that model averaging does not dominate other well designed prediction model speci…cation methods, and that using a combination of factor and other shrinkage methods often yields superior predictions. For example, when using recursive estimation windows, which dominate other "windowing" approaches in our experiments, prediction models constructed using pure principal component type models combined with shrinkage methods yield mean square forecast error "best" models around 70% of the time, when used to predict 11 key macroeconomic indicators at various forecast horizons. Baseline linear models (which "win"around 5% of the time) and model averaging methods (which win around 25% of the time) fare substantially worse than our sophisticated nonlinear models. Ancillary …ndings based on our forecasting experiments underscore the advantages of using recursive estimation strategies, and provide new evidence of the usefulness of yield and yield-spread variables in nonlinear prediction speci…cation. Terms of use: Documents in

No abstract

We utilize mixed‐frequency factor‐MIDAS models for the purpose of carrying out backcasting, nowcasting, and forecasting experiments using real‐time data. We also introduce a new real‐time Korean GDP dataset, which is the focus of our experiments. The methodology that we utilize involves first estimating common latent factors (i.e., diffusion indices) from 190 monthly macroeconomic and financial series using various estimation strategies. These factors are then included, along with standard variables measured at multiple different frequencies, in various factor‐MIDAS prediction models. Our key empirical findings as follows. (i) When using real‐time data, factor‐MIDAS prediction models outperform various linear benchmark models. Interestingly, the “MSFE‐best” MIDAS models contain no autoregressive (AR) lag terms when backcasting and nowcasting. AR terms only begin to play a role in “true” forecasting contexts. (ii) Models that utilize only one or two factors are “MSFE‐best” at all forecasting horizons, but not at any backcasting and nowcasting horizons. In these latter contexts, much more heavily parametrized models with many factors are preferred. (iii) Real‐time data are crucial for forecasting Korean gross domestic product, and the use of “first available” versus “most recent” data “strongly” affects model selection and performance. (iv) Recursively estimated models are almost always “MSFE‐best,” and models estimated using autoregressive interpolation dominate those estimated using other interpolation methods. (v) Factors estimated using recursive principal component estimation methods have more predictive content than those estimated using a variety of other (more sophisticated) approaches. This result is particularly prevalent for our “MSFE‐best” factor‐MIDAS models, across virtually all forecast horizons, estimation schemes, and data vintages that are analyzed.

We report a case of the unusual location of a cutaneous bronchogenic cyst on the abdominal wall. The patient was a 9-month-old boy who had presented with a 1.5 cm-sized polypoid mass, present since birth. Pathological examination of the excised mass revealed multiple small cystic structures surrounded by the fibroadipose tissue. The lining epithelium consisted of either pseudostratified ciliated columnar epithelium with goblet cells or a single layer of ciliated or non-ciliated cuboidal to columnar cells. The cystic walls contained a well-developed smooth muscle bundle, mucous glands and hyaline cartilage plate. This lesion was adherent to the peritoneum, but there was no direct communication with the abdominal cavity. Cutaneous bronchogenic cyst located in the abdominal wall has not been described in the English literature. The present case suggests a possible origin from a downward migration, from the sequestered bud of a tracheobronchial tree primordium along the midline of the body surface, during embryonic development.