ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic)最新文献_第3页

Medicare Reform: Estimation of the Impacts of Premium Support Systems 医疗保险改革:保费支持系统影响的估计

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2016-09-13 DOI: 10.2139/ssrn.2839093

A. Federgruen, Lijian Lu

引用次数: 0

Disciplinary Differences in Opening Research Data 开放研究数据的学科差异

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2016-03-25 DOI: 10.2139/ssrn.3322652

Danny Lämmerhirt

引用次数: 4

How to Measure the Economic Impact of Vector‐Borne Diseases at Country Level 如何在国家层面衡量病媒传播疾病的经济影响

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2015-12-01 DOI: 10.1111/joes.12075

Marcello Basili, F. Belloc

引用次数: 5

A Primer on Global Games Applied to Macroeconomics and Finance 应用于宏观经济和金融的全球博弈入门

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2015-12-01 DOI: 10.1111/joes.12071

J. Jorge, J. Rocha

引用次数: 9

Impact on Firms of the Use of Knowledge External Sources: A Systematic Review of the Literature 外部知识资源使用对企业的影响:文献系统回顾

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2015-12-01 DOI: 10.1111/joes.12089

Carlos Vivas, A. Barge-Gil

{"title":"Impact on Firms of the Use of Knowledge External Sources: A Systematic Review of the Literature","authors":"Carlos Vivas, A. Barge-Gil","doi":"10.1111/joes.12089","DOIUrl":"https://doi.org/10.1111/joes.12089","url":null,"abstract":"This study summarizes the main conclusions from a systematic review of the empirical literature regarding the impact on firms of the use of knowledge external sources (universities, research institutes and knowledge intensive business services). With the aim to organize the literature, we classify the different works according to the research question addressed: (i) which firms use knowledge external sources?; (ii) Do firms using knowledge external sources achieve better results?; And (iii) which firms benefit the most from using knowledge external sources? Stylized facts are that larger, more R&D intensive and high tech firms are more likely to use knowledge external sources and that use of knowledge external sources is associated to firms higher technical results. Less attention has been paid to the third question and evidence is not conclusive. Several recommendations for future research emerge. First, to take in greater consideration methodological issues so that potential biases in the results caused by sample selection and endogeneity are handled properly. Second, to pay more attention to heterogeneous outcomes. Third, to use continuous indicators of depth and breadth of links allowing for non-linear relationships and fourth, to extend evidence for developing countries and service industries.","PeriodicalId":384078,"journal":{"name":"ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124659204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 46

Relationship Data: The Missing Link of the Current Financial Infrastructure 关系数据:当前金融基础设施缺失的一环

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2014-08-29 DOI: 10.2139/ssrn.2504167

I. Leonova, N. Jenkinson

{"title":"Relationship Data: The Missing Link of the Current Financial Infrastructure","authors":"I. Leonova, N. Jenkinson","doi":"10.2139/ssrn.2504167","DOIUrl":"https://doi.org/10.2139/ssrn.2504167","url":null,"abstract":"Improving understanding of the complex relationships among financial entities is critically important for risk managers and for financial authorities charged with multiple policy objectives. High quality information is lacking at both the intra- and inter-enterprise levels and to support analysis of the financial network. Put simply, the current quality and quantity of relationship data is not sufficient to deliver on the ultimate objectives. For the purpose of this discussion we use a very generic definition of a term relationship somewhat similar to the definition used to describe human relationships. And like in the human relationships case we will not claim that only marriage and blood connection makes your relatives, but also loaning a book, loving, hating and sharing a flat. In the financial context, the relationships may be determined by accounting rules set, for example, by IFRS or US GAAP, as well as regulatory requirements in areas of risk management, market integrity, know-your-client, network analysis and statistical consolidation. The financial industry and regulators have spent countless hours arguing and debating the definition of ownership. The problem lies in the question itself. We suggest that as part of any relationship data system the best approach is to put the question aside and avoid a conceptual and practical quagmire. Rather, we recommend collecting and storing less-subjective granular data on theactual legal and economic relationships between firms, which provides a flexibleframework from which any user can answer the question on corporate relationships he or she determines is appropriate at a given time. Encouragingly, technological solutions are available to accommodate this multiplicity of requirements in a single solution. The paper outlines where the practical challenges are that inhibit the development of high quality relationship data and how they can be overcome.","PeriodicalId":384078,"journal":{"name":"ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115065808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs 包含网络信息的正则化回归:协变量系数和连接符号的同时估计

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2014-06-28 DOI: 10.2139/ssrn.2466289

Matthias Weber, M. Schumacher, H. Binder

{"title":"Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs","authors":"Matthias Weber, M. Schumacher, H. Binder","doi":"10.2139/ssrn.2466289","DOIUrl":"https://doi.org/10.2139/ssrn.2466289","url":null,"abstract":"We develop an algorithm that incorporates network information into regression settings. It simultaneously estimates the covariate coefficients and the signs of the network connections (i.e. whether the connections are of an activating or of a repressing type). For the coefficient estimation steps an additional penalty is set on top of the lasso penalty, similarly to Li and Li (2008). We develop a fast implementation for the new method based on coordinate descent. Furthermore, we show how the new methods can be applied to time-to-event data. The new method yields good results in simulation studies concerning sensitivity and specificity of non-zero covariate coefficients, estimation of network connection signs, and prediction performance. We also apply the new method to two microarray time-to-event data sets from patients with ovarian cancer and diffuse large B-cell lymphoma. The new method performs very well in both cases. The main application of this new method is of biomedical nature, but it may also be useful in other fields where network data is available.","PeriodicalId":384078,"journal":{"name":"ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114886728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Assembling International Equity Datasets -- Review of Studies on the Cross-Section of Common Stocks 汇编国际股权数据集——普通股横截面研究综述

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2014-04-22 DOI: 10.2139/ssrn.2427622

A. Waszczuk

引用次数: 8

A Novel Identification Approach to Bayesian Factor Analysis with Sparse Loadings Matrices 基于稀疏负载矩阵的贝叶斯因子分析识别新方法

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2014-02-14 DOI: 10.2139/ssrn.2399368

M. Pape

{"title":"A Novel Identification Approach to Bayesian Factor Analysis with Sparse Loadings Matrices","authors":"M. Pape","doi":"10.2139/ssrn.2399368","DOIUrl":"https://doi.org/10.2139/ssrn.2399368","url":null,"abstract":"Sparse factor analysis comprises aspects of exploratory and confirmatory factor analysis, seeking to establish a parsimonious structure in the loadings matrix of the model. This task is related to the issue of determining the number of factors required for model representation, the question of which variables are useful and which ones can be excluded from the analysis, and the problem whether some variables are driven by a subset of all factors only. Whereas sparsity analysis focuses mainly on the third of these questions, it can provide helpful hints to tackle the first two questions as well. I use multivariate highest posterior density (HPD) intervals calculated for the posterior densities derived from the weighted orthogonal Procrustes (WOP) ex-post identification approach to find a sparse loadings structure. In a simulation study, this method is used to identify different sparse structures, including those with excess variables, and to determine the number of factors in the model, where all three tasks are well achieved. Eventually, I apply the approach on a data set of intelligence test results to determine the number of factors, the required variables and the sparsity structure, where it yields results not only well-comprehensible, but also very similar to those found in former studies analyzing the data set.","PeriodicalId":384078,"journal":{"name":"ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128279181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Risikofaktoren und Multifaktormodelle für den Deutschen Aktienmarkt (Risk Factors and Multi-Factor Models for the German Stock Market) 德国股票市场的风险因素和多因素模型

ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic) Pub Date : 2013-11-12 DOI: 10.2139/ssrn.1960510

M. Hanauer, C. Kaserer, M. Rapp

{"title":"Risikofaktoren und Multifaktormodelle für den Deutschen Aktienmarkt (Risk Factors and Multi-Factor Models for the German Stock Market)","authors":"M. Hanauer, C. Kaserer, M. Rapp","doi":"10.2139/ssrn.1960510","DOIUrl":"https://doi.org/10.2139/ssrn.1960510","url":null,"abstract":"Der deutsche Aktienmarkt sah sich in den letzten 15 Jahren substantiellen Veranderungen gegenuber, welche unter anderem in eine zunehmende Internationalisierung und deutlich erhohten Streubesitz mundeten. In der vorliegenden Arbeit untersuchen wir, inwieweit dies die aus klassischen Multifaktormodellen bekannten Risikofaktoren beeinflusste. Basierend auf den Renditen derCDAX-Unternehmen von Juli 1996 bis Juni 2011 dokumentieren wir vier wesentliche Ergebnisse. Erstens finden wir eine insignifikant (positive) Marktrisikopramie, eine signifikant negative Grosenpramie (Size Premium), eine signifikant positive Substanzpramie (Value Premium) und eine signifikant positive Momentumpramie (Momentum Premium). Zweitens zeigen sich alle vier Faktoren untereinander nur schwach bzw. negativ korreliert und teilweise mit internationalen Gegenstucken nur schwach korreliert. Drittens zeigt sich, dass Renditen von Aktienportfolios, sortiert nach Marktkapitalisierung und Buch-Marktwert-Verhaltnis, durch ein Dreifaktorenmodell nach Fama French (1993) substantiell besser erklart werden, als durch ein Einfaktormodell in Anlehnung an das klassische Capital Asset Pricing Model. Der zusatzliche Erklarungsbeitrag des Momentumfaktors in Anlehnung an Carhart (1997) ist hingegen marginal. Letztendlich argumentieren wir daher vor dem Hintergrund der bekannten Literatur und unserer Ergebnisse fur eine landerspezifische Erweiterung des Capital Asset Pricing Models.","PeriodicalId":384078,"journal":{"name":"ERN: Other Econometrics: Data Collection & Data Estimation Methodology (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133940375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 29