Bayesian estimation of duration models: An application of the multiperiod probit model

The multiperiod probit model is presented and Bayesian estimation using the Gibbs sampler with data augmentation is described. As an empirical illustration, the multiperiod probit model is then used to estimate a duration model using employment duration data for the Canadian province of New Brunswick. Bayesian estimation with unobserved heterogeneity is shown to be a simple extension of estimation of a duration model with no unobserved heterogeneity. More importantly, perhaps, some numerical problems encountered by other authors using Maximum Likelihood are avoided.I would like to thank M. Baker, G. Koop, A. Melino and D. Poirier for helpful comments and discussions. I would also like to thank M. Baker for providing his data.     

Efficiency analysis of organized industrial zones in Eastern Black Sea Region of Turkey

Organized Industrial Zones (OIZs) are the production areas of goods and services that are established to provide planned industrialization and planned urbanization by structuring the industry in suitable areas, to prevent environmental problems, and to provide efficient use of resources. The aim of this study is to propose a decision-making model based on data envelopment analysis (DEA) to evaluate the relative efficiencies of OIZs located in the Eastern Black Sea Region of Turkey. First, the efficiency score of each alternative is determined by employing a DEA formulation with interval data. Second, a common weight DEA-based formulation is applied in order to obtain common set of weights and provide ranking results with an improved discriminating power in imprecise nature. In this study, the best performing OIZ alternative, which performs in Eastern Black Sea region of Turkey, is identified based on the approach proposed by Salahi et al. [1]. The DEA-based model developed by Salahi et al. [1] is improved by modifying a constraint. In order to demonstrate the robustness of the application, two numerical illustrations are given. The first example compares the results obtained by the formulation addressed in Salahi et al. [1] and the improved model; while second numerical illustration provides a case study conducted in Eastern Black Sea region of Turkey.     

Data portability effects on data-driven innovation of online platforms: Analyzing Spotify

The EU General Data Protection Regulation (GDPR) introduces a new right to data portability, which allows users to move their personal data to other platforms, potentially affecting competition between rival platforms offering similar (homogeneous/substitute) products or services within the European Union. However, it is still unclear what effects this new regulation could have on competition and, consequently, on innovation in digital markets. Therefore, this paper analyzes the effect of data portability driven by competition on the data-driven innovation response of online platforms such as Spotify, Google, and Facebook.We conduct an empirical analysis of Spotify, which is an online platform facing competition within the EU, and perform a comparison between data portability to number portability of the telecommunication sector to predict the future impact of the new regulation. Finally, we compare the observations on Spotify with Facebook and Google, which are companies in winner-takes-all markets.We argue that online platforms like Spotify, which face competition within the EU, will invest in two forms of data-driven innovation due to the effect of data portability. These types are ‘exploitation-innovation,’ by improving the existing technology, and ‘exploration-innovation’ by developing new technology. In ‘exploitation-innovation,’ firms, like Spotify, will increase investments in data-driven innovation to enhance users' engagement and retention to avoid churn. In ‘exploration-innovation,’ these firms will invest in data-driven innovation to develop new algorithms to include data from customers acquired from their competitors. On the contrary, online platforms, like Facebook or Google, which do not face real competition, will not have a substantial need to invest in data-driven innovation solely due to data portability.     

Reprint of "Performance evaluation of China's high-tech innovation process :Analysis based on the innovation value chain"

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

经济增长与雾霾污染治理:空间环境库兹涅茨曲线检验

文章在对国内外与经济增长、环境污染及环境库兹涅茨曲线（EKC）相关的文献进行述评的基础上，构建了中国经济增长与雾霾污染治理的理论分析框架，利用ArcGIS软件将NASA提供的2003-2016年全球遥感地图年均PM_2.5浓度栅格数据值解析为中国281个地级及以上城市具体的数值，采用探索性空间数据分析（ESDA）方法与动态空间杜宾面板数据模型（SDDPDM）对中国经济增长与雾霾污染之间是否存在EKC曲线以及引致雾霾污染空间溢出的因素进行了经验识别。结果发现，中国（整体）、东部地区及中西部地区均存在雾霾污染EKC曲线（中西部地区没有通过显著性检验）且处于雾霾污染随着经济增长而加剧的EKC曲线第一阶段（拐点为第二阶段）。这与区域经济发展水平，特别是与区域经济发展水平离雾霾污染EKC曲线拐点的距离有关。区域经济发展水平离雾霾污染EKC曲线拐点越近，该区域雾霾污染EKC曲线越显著；反之，则越不显著。中国（整体）、东部地区及中西部地区经济发展水平离各自雾霾污染EKC曲线拐点的距离分别为中等、较近及较远，故，在上述三种情况下，雾霾污染EKC曲线的显著性会出现差异。交通运输对中国雾霾污染治理起到了消极作用；科技水平、产业结构合理化及教育水平对雾霾污染治理均能起到积极的促进作用。中西部地区FDI对中国雾霾污染治理所起的作用是积极的，而东部地区FDI则相反。     

Methods for Generating Longitudinally Correlated Binary Data

The analysis of longitudinally correlated binary data has attracted considerable attention of late. Since the estimation of parameters in models for such data is based on asymptotic theory, it is necessary to investigate the small‐sample properties of estimators by simulation. In this paper, we review the mechanisms that have been proposed for generating longitudinally correlated binary data. We compare and contrast these models with regard to various features, including computational efficiency, flexibility and the range restrictions that they impose on the longitudinal association parameters. Some extensions to the data generation mechanism originally suggested by Kanter (1975) are proposed.     

基于PC机EPP接口的并行遥测数据采集技术

在遥测系统中 ,解调后并行数据流的采集一般是通过PC机插卡方式 ,该方式实现比较复杂。为此 ,提出了一种基于EPP接口的并行遥测数据采集软硬件方案 ,该方案简化了设计 ,实现比较容易。     

WEB‐BASED AND MAIL SURVEYS: A COMPARISON OF RESPONSE,DATA, AND COST

The mail survey is the most common data collection technique used by logistics researchers today. Many researchers have noted that response rates to mail surveys have been declining. The Internet offers logistics researchers several potential advantages over traditional mail surveys. This research compares these two methods across response rates, speed of response, consistency of results, and cost. The research also provides unique insight regarding the ability of electronic methods to gain interest and subsequent participation among potential respondents thereby helping in theory testing.     

Comments on ‘Forecasting with a real-time data set for macroeconomists’

The effects of data revision as removing measurement error on forecast model building is examined. I show various effects on model building using revised or instead real-time data. These effects include lag length selection and measured persistence. I then argue that in practice that one should include the entire dataset available (real-time and past revised data) in forecast construction.     

An Examination of Budgetary Inefficiency in Education Using Data Envelopment Analysis

The generally weak association between educational spending and performance is a source of ongoing debate. This study examined size, type and source of educational operating expenditures as potential explanators of this weak relationship. Using Data Envelopment Analysis (DEA) and publicly available input-output performance metrics, budgetary efficiency was measured across school districts. Budgetary inefficiency was found to be significantly and positively associated with (1) budget size (2) administrative overhead and (3) local revenue accountability. These findings offer a partial explanation for the weak relationship traditionally found between educational spending inputs and performance outcomes. The results are suggestive of how school districts might improve their budgetary goal setting, performance auditing and resource allocation practices.