Jackknife and Analytical Bias Reduction for Nonlinear Panel Models

Fixed effects estimators of panel models can be severely biased because of the well‐known incidental parameters problem. We show that this bias can be reduced by using a panel jackknife or an analytical bias correction motivated by large T. We give bias corrections for averages over the fixed effects, as well as model parameters. We find large bias reductions from using these approaches in examples. We consider asymptotics where T grows with n, as an approximation to the properties of the estimators in econometric applications. We show that if T grows at the same rate as n, the fixed effects estimator is asymptotically biased, so that asymptotic confidence intervals are incorrect, but that they are correct for the panel jackknife. We show T growing faster than n^1/3 suffices for correctness of the analytic correction, a property we also conjecture for the jackknife.     

Testing stochastic orders in tails of contingency tables

Testing for the difference in the strength of bivariate association in two independent contingency tables is an important issue that finds applications in various disciplines. Currently, many of the commonly used tests are based on single-index measures of association. More specifically, one obtains single-index measurements of association from two tables and compares them based on asymptotic theory. Although they are usually easy to understand and use, often much of the information contained in the data is lost with single-index measures. Accordingly, they fail to fully capture the association in the data. To remedy this shortcoming, we introduce a new summary statistic measuring various types of association in a contingency table. Based on this new summary statistic, we propose a likelihood ratio test comparing the strength of association in two independent contingency tables. The proposed test examines the stochastic order between summary statistics. We derive its asymptotic null distribution and demonstrate that the least favorable distributions are chi-bar distributions. We numerically compare the power of the proposed test to that of the tests based on single-index measures. Finally, we provide two examples illustrating the new summary statistics and the related tests.     

Estimating models based on Markov jump processes given fragmented observation series

We consider the problem of estimating the rate matrix governing a finite-state Markov jump process given a number of fragmented time series. We propose to concatenate the observed series and to employ the emerging non-Markov process for estimation. We describe the bias arising if standard methods for Markov processes are used for the concatenated process, and provide a post-processing method to correct for this bias. This method applies to discrete-time Markov chains and to more general models based on Markov jump processes where the underlying state process is not observed directly. This is demonstrated in detail for a Markov switching model. We provide applications to simulated time series and to financial market data, where estimators resulting from maximum likelihood methods and Markov chain Monte Carlo sampling are improved using the presented correction.     

The Quality of Life in Singapore

The Asia Barometer Survey of 1,038 respondents shows that most Singaporeans are happy and enjoy life, although they do not feel a correspondingly high level of accomplishment. Good health, a comfortable home, a job, time with family and having enough to eat emerged as key priorities in life. While Singaporeans are most satisfied with their marriages, family life, friendship, housing, and public safety, their perceptions of their overall quality of life are mostly influenced by their relationships with significant others and their satisfaction with their homes. Detailed demographic analyses are provided and policy implications are discussed in light of these findings.     

Prevalence of Sexual Dysfunction and Associated Risk Factors in Middle-Aged and Elderly Korean Men in Primary Care

Although several studies have individually investigated the risk factors for erectile dysfunction (ED), premature ejaculation (PE), and late-onset hypogonadism (LOH), few studies have considered ED, PE, and LOH as categories of sexual dysfunction (SD) within the same population. We therefore aimed to investigate the prevalence of SD and its associated risk factors among men in primary care. Study participants were enrolled by 18 family physicians from 15 hospital-based family practices in Korea between August 2010 and May 2011. Participants answered a questionnaire regarding their demographic characteristics and lifestyle factors as well as the Korean versions of the Androgen Deficiency in the Aging Male, the International Index of Erectile Function, and the Premature Ejaculation Diagnostic Tool questionnaires. SD prevalence was 64.9% among study participants who were ≥ 40 years of age. ED prevalence was 43.7%, PE prevalence was 38.6%, and LOH prevalence was 16.8%. SD prevalence was significantly associated with increased age, overweight, hypertension, diabetes, and depression. These findings highlight the importance of screening questions for SD in primary care, especially among older male patients with the identified risk factors.