Synthetic data method to incorporate external information into a current study

We consider the situation where there is a known regression model that can be used to predict an outcome, Y, from a set of predictor variables X . A new variable B is expected to enhance the prediction of Y. A dataset of size n containing Y, X and B is available, and the challenge is to build an improved model for Y| X ,B that uses both the available individual level data and some summary information obtained from the known model for Y| X . We propose a synthetic data approach, which consists of creating m additional synthetic data observations, and then analyzing the combined dataset of size n + m to estimate the parameters of the Y| X ,B model. This combined dataset of size n + m now has missing values of B for m of the observations, and is analyzed using methods that can handle missing data (e.g., multiple imputation). We present simulation studies and illustrate the method using data from the Prostate Cancer Prevention Trial. Though the synthetic data method is applicable to a general regression context, to provide some justification, we show in two special cases that the asymptotic variances of the parameter estimates in the Y| X ,B model are identical to those from an alternative constrained maximum likelihood estimation approach. This correspondence in special cases and the method's broad applicability makes it appealing for use across diverse scenarios. The Canadian Journal of Statistics 47: 580–603; 2019 © 2019 Statistical Society of Canada     

Corporate Environmental Behaviors in Voluntary Programs: Does Timing Matter?*

Objective. Why do some firms participate in voluntary programs earlier than others? What conditions dictate whether firms participate in voluntary programs earlier rather than later? Current research on voluntary programs has not considered discrete processes in which corporate actors could have different motives and objectives in different time dimensions, that is, early versus late. Methods. We adopt a diffusion theory to disaggregate corporate voluntary participation behavior in the Environmental Protection Agency (EPA) sponsored Green Lights (GL) voluntary program. We focus on the GL participants during two periods—the early joiners in 1993–1994, and the late joiners in 1995–1996. Results. At the early diffusion stage, firms are more likely driven by the market motive that garners a “green” reputation, an important strategic asset to promote market competitiveness; at the late diffusion stage, firms are more driven by the institutional motive to improve their relationships with regulatory agencies and subsequently relieve regulatory pressures from them. Conclusion. We find that firms have different motives for GL participation at different diffusion stages. We suggest that policymakers who want to induce firms to join voluntary programs should pay more attention to program designs and implementation schemes that accommodate different corporate interests and objectives in different time orders of firms' participations in voluntary programs.     

Resilience of Cyber Systems with Over‐ and Underregulation

Recent cyber attacks provide evidence of increased threats to our critical systems and infrastructure. A common reaction to a new threat is to harden the system by adding new rules and regulations. As federal and state governments request new procedures to follow, each of their organizations implements their own cyber defense strategies. This unintentionally increases time and effort that employees spend on training and policy implementation and decreases the time and latitude to perform critical job functions, thus raising overall levels of stress. People's performance under stress, coupled with an overabundance of information, results in even more vulnerabilities for adversaries to exploit. In this article, we embed a simple regulatory model that accounts for cybersecurity human factors and an organization's regulatory environment in a model of a corporate cyber network under attack. The resulting model demonstrates the effect of under‐ and overregulation on an organization's resilience with respect to insider threats. Currently, there is a tendency to use ad‐hoc approaches to account for human factors rather than to incorporate them into cyber resilience modeling. It is clear that using a systematic approach utilizing behavioral science, which already exists in cyber resilience assessment, would provide a more holistic view for decisionmakers.     

Goodness-of-Fit Tests for the Additive Risk Model with (p > 2)-Dimensional Time-Invariant Covariates

This paper presents methods for checking the goodness-of-fit of the additive risk model with p(> 2)-dimensional time-invariant covariates. The procedures are an extension of Kim and Lee (1996) who developed a test to assess the additive risk assumption for two-sample censored data. We apply the proposed tests to survival data from South Wales nikel refinery workers. Simulation studies are carried out to investigate the performance of the proposed tests for practical sample sizes.     

Immigration in the 2008 Virginia presidential election: A cultural issue remains puissant despite an economic crisis

In 2006 and 2007, many analysts expected that immigration would be one of the top domestic issues in the 2008 campaign. However, in the 2008 presidential general election, immigration issues were never a major topic between candidates John McCain and Barack Obama. This was partially because McCain has more moderate views toward immigration reform than the passionate anti-immigration faction of the Republican Party. Prior research suggests that an issue in a presidential campaign can remain influential even when the media and campaigns are not discussing or addressing the issue, even when the candidates or parties do not differ greatly on the issue. In a survey of Virginia residents conducted just before the November election, immigration attitudes were a differential factor between McCain and Obama.     

Nonstationary panel data analysis: an overview of some recent developments

This paper overviews some recent developments in panel data asymptotics, concentrating on the nonstationary panel case and gives a new result for models with individual effects. Underlying recent theory are asymptotics for multi-indexed processes in which both indexes may pass to infinity. We review some of the new limit theory that has been developed, show how it can be applied and give a new interpretation of individual effects in nonstationary panel data. Fundamental to the interpretation of much of the asymptotics is the concept of a panel regression coefficient which measures the long run average relation across a section of the panel. This concept is analogous to the statistical interpretation of the coefficient in a classical regression relation. A variety of nonstationary panel data models are discussed and the paper reviews the asymptotic properties of estimators in these various models. Some recent developments in panel unit root tests and stationary dynamic panel regression models are also reviewed.     

Skin color,sex, and educational attainment in the post-civil rights era

We assess the relationship between skin color and educational attainment for native-born non-Hispanic Black and White men and women, using data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study. CARDIA is a medical cohort study with twenty years of social background data and a continuous measure of skin color, recorded as the percent of light reflected off skin. For Black men and women, we find a one-standard-deviation increase in skin lightness to be associated with a quarter-year increase in educational attainment. For White women, we find an association approximately equal in magnitude to that found for Black respondents, and the pattern of significance across educational transitions suggests that skin color for White women is not simply a proxy for family background. For White men, any relationship between skin color and attainment is not robust and, analyses suggest, might primarily reflect differences in family background. Findings suggest that discrimination on the basis of skin color may be less specific to race than previously thought.