Frequency domain bootstrap for ratio statistics under long-range dependence

A frequency domain bootstrap (FDB) is a common technique to apply Efron’s independent and identically distributed resampling technique (Efron, 1979) to periodogram ordinates – especially normalized periodogram ordinates – by using spectral density estimates. The FDB method is applicable to several classes of statistics, such as estimators of the normalized spectral mean, the autocorrelation (but not autocovariance), the normalized spectral density function, and Whittle parameters. While this FDB method has been extensively studied with respect to short-range dependent time processes, there is a dearth of research on its use with long-range dependent time processes. Therefore, we propose an FDB methodology for ratio statistics under long-range dependence, using semi- and nonparametric spectral density estimates as a normalizing factor. It is shown that the FDB approximation allows for valid distribution estimation for a broad class of stationary, long-range (or short-range) dependent linear processes, without any stringent assumptions on the distribution of the underlying process. The results of a large simulation study show that the FDB approximation using a semi- or nonparametric spectral density estimator is often robust for various values of a long-memory parameter reflecting magnitude of dependence. We apply the proposed procedure to two data examples.     

Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

Minority comparison model: Effects of Whites’ multiracial evaluation on symbolic racism and racialized policy preferences

Most Racial Studies primarily focus on African Americans without paying attention to nonblack minorities, and it fails to capture recent increase in racial diversity. Based on previous theories and empirical findings, we propose a new model, minority comparison model, which accounts for theoretical shortcomings in Racial Studies. This model (1) captures psychological processes that compare blacks and nonblacks, and (2) explores the effects of whites’ multiracial evaluation on racialized policy preferences. Drawing on a 2008 national representative sample, this study finds that whites who have positive stereotype of nonblacks (e.g., Hispanics and/or Asians) but negative stereotype of blacks show substantially higher symbolic racism and stronger opposition to Affirmative Action, whereas whites who have positive stereotype of blacks but negative stereotypes of nonblacks have stronger opposition to expansive immigration policy. Our study offers new ways of understanding and accounting for symbolic racism in modern context, and shows how whites’ preferences in racialized policies are influenced by multiracial evaluation.     

The relationship between open innovation,entrepreneurship, and introduction of new business models in Korean and Indonesian information technology enterprises

This case study sought to identify the relationships that can exist between open innovation, entrepreneurship, and the introduction of new business models at the enterprise level. Eleven Korean enterprises and five Indonesian enterprises were chosen, to obtain minimum research generality. While the number of enterprises is not great, it provides enough samples to determine the concrete relationships among these factors. The article starts by pointing out the general relationship between entrepreneurship, open innovation, and the introduction of a new business model. It examines two different contexts: the difference between the Seoul and Daegu regional innovation systems, and the difference between the Indonesian and Korean national innovation systems.