Technological and Output Complementarities, and Inter-Firm Cooperation in Information Technology Ventures

Firms whose profiles of technologicalcompetence are complementary to one another are morelikely to enter into technology-based cooperativeagreements, and a broad level of technologicalcomplementarity is necessary for these agreements toextend as far as a mutual coordination of learningprocesses (combined research ventures). Using data onagreements between the world's largest firms in thearea of information technology (IT) and the patternsof technological specialization of these firms in theIT fields as revealed by their corporate patenting inthe US, we show that the technologicalco-specialization of firms helps to explain allianceformation, over and above the effects of anyco-specialization in IT products. While firms whosetechnological efforts are less complementary are lesslikely to cooperate for technology purposes, if theydo cooperate it is to exploit the differences in theirfields of expertise, and hence they are likely to usequasi-market organizational forms such as licensing,while the purpose of the alliance is restricted to anexchange of knowledge without any joint coordinationof learning (research). Instead, equity jointventures are likeliest when at a broad level ofaggregation the profiles of technologicalspecialization of partners are complementary, but ata more detailed level of disaggregation there is agreater distance between them, such that thecoordination of learning efforts is feasible, butrequires a stronger organizational commitment.     

Testing for Homogeneity in an Exponential Mixture Model

This paper studies diagnostic procedures to test for homogeneity against unobserved heterogeneity in an exponential mixture model. The procedures include a dispersion score test, a likelihood ratio test, a moment likelihood approach and several goodness-of-fit tests. The paper compares the empirical power of these tests on a broad range of alternatives and proposes a new test that combines the dispersion score test with a properly chosen goodness-of-fit procedure; its empirical power comes close to the power of the best of the other tests.     

Frailty models and copulas: similarities and differences

Copulas and frailty models are important tools to model bivariate survival data. Equivalence between Archimedean copula models and shared frailty models, e.g. between the Clayton-Oakes copula model and the shared gamma frailty model, has often been claimed in the literature. In this note we show that, in both the models, there is indeed a well-known equivalence between the copula functions; the modeling of the marginal survival functions, however, is quite different. The latter fact leads to different joint survival functions.     

Inconsistency of the MLE for the Joint Distribution of Interval-Censored Survival Times and Continuous Marks

Abstract.  This paper considers the non-parametric maximum likelihood estimator (MLE) for the joint distribution function of an interval-censored survival time and a continuous mark variable. We provide a new explicit formula for the MLE in this problem. We use this formula and the mark-specific cumulative hazard function of Huang & Louis (1998) to obtain the almost sure limit of the MLE. This result leads to necessary and sufficient conditions for consistency of the MLE, which imply that the MLE is inconsistent in general. We show that the inconsistency can be repaired by discretizing the marks. Our theoretical results are supported by simulations.     

Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data

We implement a joint model for mixed multivariate longitudinal measurements, applied to the prediction of time until lung transplant or death in idiopathic pulmonary fibrosis. Specifically, we formulate a unified Bayesian joint model for the mixed longitudinal responses and time-to-event outcomes. For the longitudinal model of continuous and binary responses, we investigate multivariate generalized linear mixed models using shared random effects. Longitudinal and time-to-event data are assumed to be independent conditional on available covariates and shared parameters. A Markov chain Monte Carlo algorithm, implemented in OpenBUGS, is used for parameter estimation. To illustrate practical considerations in choosing a final model, we fit 37 different candidate models using all possible combinations of random effects and employ a deviance information criterion to select a best-fitting model. We demonstrate the prediction of future event probabilities within a fixed time interval for patients utilizing baseline data, post-baseline longitudinal responses, and the time-to-event outcome. The performance of our joint model is also evaluated in simulation studies.     

Weighted Logrank Permutation Tests for Randomly Right Censored Life Science Data

In biomedical research, weighted logrank tests are frequently applied to compare two samples of randomly right censored survival times. We address the question how to combine a number of weighted logrank statistics to achieve good power of the corresponding survival test for a whole linear space or cone of alternatives, which are given by hazard rates. This leads to a new class of semiparametric projection tests that are motivated by likelihood ratio tests for an asymptotic model. We show that these tests can be carried out as permutation tests and discuss their asymptotic properties. A simulation study together with the analysis of a classical data set illustrates the advantages.     

组织演化理论视角下的股权结构与子公司生存——环境突变、冗余资源的调节作用

本文运用组织演化理论、公司治理和资源基础观理论,以1932家非国有企业的子公司为样本,研究了股权结构、子公司冗余资源等因素对子公司应对环境变化能力的影响,对环境变化和子公司生存状况的动态演化进行了分析。研究发现,在环境较稳定时,合资子公司的失败危险高于独资子公司;而当环境发生突变时（如经济危机）,合资子公司的失败危险则低于独资子公司。冗余资源、资源使用效率和能力的不同是导致子公司在环境变化中生存状况差异的一个重要因素,子公司的股权结构在一定程度上会影响这种效率和能力。本研究证实了子公司的自治程度有助于培养其应对环境变化的能力,从而提高子公司的生存率。以往研究对股权结构与绩效关系多采用静态分析,本文将环境变化和冗余资源引入到分析框架中进行动态分析,丰富了该领域的研究成果。     

在Kalman-Bucy滤波学习过程下的投资者生存能力分析

本文在投资者非完全理性框架下,基于Kalman-Bucy滤波学习过程给出了投资者理性和自信程度的定义,并基于此分析了不同投资者在市场中的生存和影响能力,并为实际市场中多类投资者共存的现象从学习过程的角度给予解释。研究结果表明,投资者在市场中的生存能力受其在学习过程中的理性和自信程度的双重影响。理性和自信程度都较高的投资者对市场把握较好,较容易在市场中生存,并对市场具有较大的影响。如果理性程度较高的投资者不自信,而理性程度不高的投资者自信度较高,那么在这种情况下没有哪类投资者对市场的把握相对准确,也就是说没有哪类投资者能将其他投资者逐出市场,即多类投资者共存于市场中。     

A Class of Weighted Estimating Equations for Semiparametric Transformation Models with Missing Covariates

In survival analysis, covariate measurements often contain missing observations; ignoring this feature can lead to invalid inference. We propose a class of weighted estimating equations for right‐censored data with missing covariates under semiparametric transformation models. Time‐specific and subject‐specific weights are accommodated in the formulation of the weighted estimating equations. We establish unified results for estimating missingness probabilities that cover both parametric and non‐parametric modelling schemes. To improve estimation efficiency, the weighted estimating equations are augmented by a new set of unbiased estimating equations. The resultant estimator has the so‐called ‘double robustness’ property and is optimal within a class of consistent estimators.