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.     

Measuring chronic and transient components of poverty: a Bayesian approach

After the publication of Ravallion’s Econ J 98:1171–1182, 1988 seminal work on chronic and transient poverty, wide attention has been given to the components of poverty. We propose a Bayesian mixture model to measure poverty and divide it into chronic and the transient poverty using the Foster, Greer and Thorbecke (FGT) measure. These two types of poverty are illustrated using the Panel Study of Income Dynamics (PSID) data.      

Nested multiple imputation of NMES via partially incompatible MCMC

The multiple imputation of the National Medical Expenditure Survey (NMES) involved the use of two new techniques, both having potentially broad applicability. The first is to use distributionally incompatible MCMC (Markov Chain Monte Carlo), but to apply it only partially, to impute the missing values that destroy a monotone pattern, thereby limiting the extent of incompatibility. The second technique is to split the missing data into two parts, one that is much more computationally expensive to impute than the other, and create several imputations of the second part for each of the first part, thereby creating nested multiple imputations with their increased inferential efficiency.     

α-optimal sampling plans for lot-by-lot defects inspection

Investigations on acceptance sampling have attached rather few importance to defects inspection. For modern quality control, both the steadily increasing complexity of products and the need for differentiated cost calculation involve a clear demand for economic defects sampling in its practically most relevant form: lot-by-lot single sampling plans, where the OC (lot OC) is considered as a function of lot sizeN, sample sizen, acceptance numberc, number of defects in the lotK. Starting from an appropriate lot OC function, the present paper develops an economic cost and control model and an economic objective function for single defects sampling plans by adapting theα-optimal sampling scheme, introduced by E. von Collani for defectives inspection, to the purposes of defects inspection. A simple and accurate approximation ofα-optimal defects plans is derived by means of a Poisson approximation of the lot OC function.     

The Relative Cost Efficiency of Stock versus Mutual Thrifts: A Bayesian Approach

The relative cost efficiency of the mutual versus stock forms of ownership for thrifts has been a relevant issue in an era of deregulation and competition in the financial services industry. In this study, Bayesian‐based Markov chain Monte Carlo (MCMC) resampling methods are used to solve a stochastic cost frontier model and effectively determine cost efficiencies for the stock and mutual thrift groups. We find a statistically significant difference between both the cost frontiers and the cost efficiencies of the two groups, with the stock group operating at the lower‐cost point. Agency problems explain a significant portion of the cost efficiency difference. Capital structure differences, though not helping to explain differences in cost efficiency, do help to explain differences in cost structure and managerial attitudes toward risk.     

Voss wins the Presidency! A commentary essay on “Predicting elections from biographical information about candidates: A test of the index method”

This comment uses the Democratic Party's nomination race from the 1924 U.S. Presidential election to develop a better understanding of Armstrong and Graefe's (2010) Biographical Index. Well-established causal indicators are necessary before actions are taken to nominate, select, or improve the standing of candidates running for election. Forecasting devices such as a Biographical Index cannot eliminate from consideration unworthy candidates. Nonetheless, the Armstrong and Graefe scale appears to have the smallest error of competing forecasting devices.     

全球通货膨胀率的国际联动效应研究——基于贝叶斯潜在多动态因子模型的分析

本文通过构建基于Gibbs抽样估算的贝叶斯潜在多动态因子模型对全球63个国家通货膨胀率的全球性联动效应和区域性联动效应进行了实证研究。研究结论表明:在整体样本期间上,通货膨胀率的全球性联动效应和区域性联动效应能解释各国通货膨胀率波动的36%和18%,而特定国家通货膨胀率的异质性成分对通货膨胀率波动的解释能力接近50%;通货膨胀率的全球性联动效应对工业化国家的通货膨胀率波动的解释能力达到60%以上;大部分国家通货膨胀率的国际联动效应的强度较稳健,但有些国家的通货膨胀率的国际联动效应强度在不同时间区间上变化较大,并能通过相关的历史事件加以解释。     

Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models

In this paper we describe the use of modern numerical integration methods for making posterior inferences in composed error stochastic frontier models for panel data or individual cross- sections. Two Monte Carlo methods have been used in practical applications. We survey these two methods in some detail and argue that Gibbs sampling methods can greatly reduce the computational difficulties involved in analyzing such models.     

The use of sampling methods in advertising research: a gap between theory and practice

In this research note, we reflect critically on the use of sampling techniques in advertising research. Our review of 1028 studies published between 2008 and 2016 in the four leading advertising journals shows that while current academic literature advocates probability sampling procedures, their actual usage is quite scarce. Most studies either lack information on the sampling method used, or engage in non-probability sampling without making adjustments to compensate for unequal selection probabilities, non-coverage, and sampling fluctuations. Based on our results, we call on researchers to revisit the fundamental aspects of sampling to increase their research results’ rigour and relevance.     

CPI理论框架研究——固定篮子价格指数的缺陷及改进

从国际范围来看,"固定篮子"指数理论仍然是编制CPI的主体框架,但透过我国CPI的编制方法可以得出其不但存在理论假设上的缺陷,且在抽样设计、权数确定以及计算公式方面均存在弊端。对此,尝试给出改进思路,以提高CPI的精度与信度。