First-order random coefficient integer-valued autoregressive processes

A first-order random coefficient integer-valued autoregressive (RCINAR(1)) model is introduced. Ergodicity of the process is established. Moments and autocovariance functions are obtained. Conditional least squares and quasi-likelihood estimators of the model parameters are derived and their asymptotic properties are established. The performance of these estimators is compared with the maximum likelihood estimator via simulation.     

Accurate Confidence Interval Estimation of Small Area Parameters Under the Fay–Herriot Model

Small area estimation has long been a popular and important research topic due to its growing demand in public and private sectors. We consider here the basic area level model, popularly known as the Fay–Herriot model. Although much of current research is predominantly focused on second order unbiased estimation of mean squared prediction errors, we concentrate on developing confidence intervals (CIs) for the small area means that are second order correct. The corrected CI can be readily implemented, because it only requires quantities that are already estimated as part of the mean squared error estimation. We extend the approach to a CI for the difference of two small area means. The findings are illustrated with a simulation study.     

Analyzing clustered count data with a cluster-specific random effect zero-inflated Conway–Maxwell–Poisson distribution

Count data analysis techniques have been developed in biological and medical research areas. In particular, zero-inflated versions of parametric count distributions have been used to model excessive zeros that are often present in these assays. The most common count distributions for analyzing such data are Poisson and negative binomial. However, a Poisson distribution can only handle equidispersed data and a negative binomial distribution can only cope with overdispersion. However, a Conway–Maxwell–Poisson (CMP) distribution [4] can handle a wide range of dispersion. We show, with an illustrative data set on next-generation sequencing of maize hybrids, that both underdispersion and overdispersion can be present in genomic data. Furthermore, the maize data set consists of clustered observations and, therefore, we develop inference procedures for a zero-inflated CMP regression that incorporates a cluster-specific random effect term. Unlike the Gaussian models, the underlying likelihood is computationally challenging. We use a numerical approximation via a Gaussian quadrature to circumvent this issue. A test for checking zero-inflation has also been developed in our setting. Finite sample properties of our estimators and test have been investigated by extensive simulations. Finally, the statistical methodology has been applied to analyze the maize data mentioned before.     

Nonlinear Autoregression with Positive Innovations

Use of nonlinear models in analyzing time series data is becoming increasingly popular. This paper considers a broad class of nonlinear autoregressive models where the autoregressive part is additive and the terms are nonlinear functions of the past data. Also, the innovation distribution is supported on the non-negative reals and satisfies a tail regularity condition. The linear parameters of the autoregression are estimated using a linear programming recipe which yields much more accurate estimates than traditional methods such as conditional least squares. Limiting distribution of the linear programming estimators is obtained. Simulation studies validate the asymptotic results and reveal excellent small sample properties of the LPE estimator.     

Comparing waiting times in a multi-stage model: A log-rank approach

A proper log-rank test for comparing two waiting (i.e. sojourn, gap) times under right censored data has been absent in the survival literature. The classical log-rank test provides a biased comparison even under independent right censoring since the censoring induced on the time since state entry depends on the entry time unless the hazards are semi-Markov. We develop test statistics for comparing K waiting time distributions from a multi-stage model in which censoring and waiting times may be dependent upon the transition history in the multi-stage model. To account for such dependent censoring, the proposed test statistics utilize an inverse probability of censoring weighted (IPCW) approach previously employed to define estimators for the cumulative hazard and survival function for waiting times in multi-stage models. We develop the test statistics as analogues to K-sample log-rank statistics for failure time data, and weak convergence to a Gaussian limit is demonstrated. A simulation study demonstrates the appropriateness of the test statistics in designs that violate typical independence assumptions for multi-stage models, under which naive test statistics for failure time data perform poorly, and illustrates the superiority of the test under proportional hazards alternatives to a Mann–Whitney type test. We apply the test statistics to an existing data set of burn patients.     

Generalized confounded row–column designs

Generalized Confounded Row–Column (GCRC) designs for factorial experiments have been introduced and methods of constructing GCRC designs have been discussed. Fractionally replicated GCRC designs have also been constructed. The designs obtained ensure balancing with respect to estimable effects.     

Taking Goldschmidt to the Woods: Timberland Ownership and Quality of Life in Alabama*

We use a database of property tax records for 13.6 million acres representing every parcel of privately owned timberland in 48 rural Alabama counties to test two hypotheses inspired by Walter Goldschmidt relating land ownership and quality of life. Our data show private ownership is highly concentrated and 62 percent is absentee owned. We employed Pearson correlations alongside Poisson and negative binomial regression models to estimate influence of both concentrated private ownership and absentee ownership of timberland. Our findings support Goldschmidt‐inspired hypotheses that concentrated and absentee ownership of timberland exhibit a significant adverse relationship with quality of life as measured by educational attainment, poverty, unemployment, food insecurity, eligibility for free or reduced price lunch at public schools, Supplemental Nutritional Assistance Program participation, and population density. Low property taxes in Alabama limit the ability of local governments to generate revenue to support public education or meet other infrastructural or service needs in rural areas. We call on rural sociologists and kindred spirits to pay more attention to the fundamental importance of land ownership which shapes the foundations of power and inequality affecting rural life in America and beyond.     

PERSPECTIVE ARTICLE: The impact of Nordic countries’ family friendly policies on employment,wages, and children

The Nordic countries at the same time exhibit a remarkably high participation rate of mothers and a more moderate decline in fertility rates compared to other Western countries. This has been attributed to the fact that the welfare state model and, especially, the family friendly policies chosen in the Nordic countries are unique. In this paper we evaluate the impact of Nordic countries’ family friendly policies on employment, wages and children’s well-being. We demonstrate that, although the ‘Nordic model’ has been successful in boosting female employment, it is a costly solution. Furthermore, family-friendly policies mainly directed towards giving mothers the right to be on long paid maternal leave have adverse effects on women’s wages with consequences for gender equality. Indeed, extensive family-friendly schemes may even have created a ‘system-based glass ceiling’ hindering women’s career progression. There is no evidence however of a trade-off between family-friendly policies and family welfare as effects on child development and children’s well-being of publicly provided child-care are found to be modest or even positive.

Corporate Reputation: Do Board Characteristics Matter?

Our study draws on institutional and signalling theories to postulate relationships between board characteristics and corporate reputation. Based on a sample of 324 firms featured in Fortune's list of most admired corporations in the USA, our findings indicate that board characteristics significantly influence the assessment of firm reputation by the business community. Specifically, we found that firms with a greater proportion of outside directors and those with larger boards exhibited better reputation than those with smaller boards and a higher proportion of insiders. In addition, we observed an inverted‐U relationship between the average tenure of outside directors and corporate reputation. However, contrary to expectations, our findings indicate a negative association between independent leadership structure (i.e. absence of duality) and corporate reputation.     

Participatory action research and researcher’s responsibilities: an experience with an Indigenous community

This paper seeks to explore the relational participatory action research (PAR) frameworks that have been developed to allow non-Indigenous researchers, along with Indigenous co-researcher participants, to learn and honour Indigenous stories. Specifically, in the context of PAR research in the Chittagong Hill Tracts of Bangladesh, we outline: (a) potential challenges between Indigenous research paradigms and Western research paradigms, (b) the situation of the non-Indigenous researcher in relation to the Indigenous community, (c) challenges associated with the non-Indigenous researcher’s selection of a research site, (d) collaboration throughout the research process and (e) the processes of developing and maintaining responsibilities. The aim is not to offer simple answers to such challenges, but to highlight the manner in which such processes can be addressed. This research may provide practical insight for future non-Indigenous researchers working with Indigenous communities through a participatory sharing process with Indigenous co-researcher participants, Elders, leaders, knowledge-holders and youths.