Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors

In this paper, we assess the predictive content of latent economic policy uncertainty and data surprise factors for forecasting and nowcasting gross domestic product (GDP) using factor-type econometric models. Our analysis focuses on five emerging market economies: Brazil, Indonesia, Mexico, South Africa, and Turkey; and we carry out a forecasting horse race in which predictions from various different models are compared. These models may (or may not) contain latent uncertainty and surprise factors constructed using both local and global economic datasets. The set of models that we examine in our experiments includes both simple benchmark linear econometric models as well as dynamic factor models that are estimated using a variety of frequentist and Bayesian data shrinkage methods based on the least absolute shrinkage operator (LASSO). We find that the inclusion of our new uncertainty and surprise factors leads to superior predictions of GDP growth, particularly when these latent factors are constructed using Bayesian variants of the LASSO. Overall, our findings point to the importance of spillover effects from global uncertainty and data surprises, when predicting GDP growth in emerging market economies.     

Gemini表面活性剂在气/液界面上的微区形貌随表面压的变化

测定了Gemini表面活性剂在pH值为10．86,NaBr浓度为1．0mol／L的溶液气／液界面上的表面压一分子面积的等温线。用自制的Brewster角显微镜(BAM)观察了由Gemini表面活性剂在界面上所形成单分子膜的微区形貌随表面压的变化。结果表明：当pH值为10．86时,Gemini表面活性剂在1．0mol／L NaBr溶液的气／液界面上生成了凝聚态的单分子膜;当表面压较低时,观察到在界面上形成了同心圆结构;随着表面压的增加,这些同心圆可发生聚并而形成多中心结构。     

Neural network versus econometric models in forecasting inflation

Artificial neural network modelling has recently attracted much attention as a new technique for estimation and forecasting in economics and finance. The chief advantages of this new approach are that such models can usually find a solution for very complex problems, and that they are free from the assumption of linearity that is often adopted to make the traditional methods tractable. In this paper we compare the performance of Back‐Propagation Artificial Neural Network (BPN) models with the traditional econometric approaches to forecasting the inflation rate. Of the traditional econometric models we use a structural reduced‐form model, an ARIMA model, a vector autoregressive model, and a Bayesian vector autoregression model. We compare each econometric model with a hybrid BPN model which uses the same set of variables. Dynamic forecasts are compared for three different horizons: one, three and twelve months ahead. Root mean squared errors and mean absolute errors are used to compare quality of forecasts. The results show the hybrid BPN models are able to forecast as well as all the traditional econometric methods, and to outperform them in some cases. Copyright © 2000 John Wiley & Sons, Ltd.     

Identification of a secretory granule-binding protein as caldesmon

Stimulation of adrenal chromaffin cells results in a rise in the concentration of intracellular free calcium which initiates catecholamine secretion by exocytosis. An understanding of the molecular basis of exocytosis will require knowledge of the sites of action of calcium. A role for calmodulin has been implicated in secretion from chromaffin cells, and isolated granule membranes bind both calmodulin and a series of cytosolic proteins in a calcium-dependent fashion. Here, we demonstrate that one of the cytosolic granule-binding proteins with a relative molecular mass (Mr) of 70,000 (70K) is a form of the calmodulin-regulated actin-binding protein caldesmon, first isolated from smooth muscle. Cytoplasmic gels assembled from an adrenal medullary extract in the absence of Ca2+ contained actin and the 70K protein. The association of both of these proteins with the cytoplasmic gel was inhibited by a micromolar concentration of Ca2+. In addition, we have demonstrated that the 70K protein is localized at the periphery of chromaffin cells. These results are consistent with the notion that 70K protein (caldesmon) has a role in regulating the organization of actin filaments of the cell periphery during the secretory process.