Survivalist Modernity and the Logic of Its Governmentality

In this article, I analyze the governmental discourses of Chung-Hee Park, drawing on Walter Benjamin's concept of the archeology of dreams. Following Benjamin, I argue that modern Korea has been shaped largely under the prevailing influence of survivalism, viewed as a principle of governmentality as well as a collective mentality. Since the late 19th century the Korean peninsula has been enmeshed in enduring geopolitico-economic threats. The Cold War brought about suffering through the Korean War, which was carried over into an authoritarian and developmental state. Finally, under the hegemony of neoliberalism at the end of the 20th century, Koreans once again underwent a collective crisis of survival. Here, I focus on Cold War survivalism and explore the discourses of Chung-Hee Park as representative texts exemplifying the logic and rationale of survivalist governmentality. Viewed as the most influential figure of 20th-century Korea, Park crystallized and implemented a survivalist governmentality, the fundamental logic of which can be delineated in the following four axioms: (i) the transcendental structure of problems, (ii) kairotic time, (iii) the praxeology of power, and (iv) the sovereign leader. These four constitute the specific narrative of national survival that functioned as a blueprint for building up the developmental Korean state.     

Economies of scale,bulk discounts,and liquidity constraints: comparing unit value and transaction level evidence in a poor country

We examine bulk discounts, which are claimed to explain the Deaton and Paxson puzzle about household size and food demand, and which may matter to household behavior studied in other literatures. Most previous studies use unit values, which are subject to several biases and reflect economizing choices made by households, so may not reliably estimate the bulk discount schedule. Instead, individual transaction records in household expenditure diaries are used, which report expenditure, quantity, brand, unit size and number purchased per transaction. The bulk discount schedule is estimated for four foods (rice, canned meat, canned fish and chicken) that make up one-third of the total food budget in a survey in urban Papua New Guinea. For each food we use the dominant brand(s) so there is no quality variation and the estimated price schedule only reflects discounts due to variations in purchase quantity. All foods have precisely measured but small elasticities of unit price with respect to quantity purchased.     

PARAMETRIC FRACTIONAL IMPUTATION FOR NON‐IGNORABLE CATEGORICAL MISSING DATA WITH FOLLOW‐UP

Incomplete data subject to non‐ignorable non‐response are often encountered in practice and have a non‐identifiability problem. A follow‐up sample is randomly selected from the set of non‐respondents to avoid the non‐identifiability problem and get complete responses. Glynn, Laird, & Rubin analyzed non‐ignorable missing data with a follow‐up sample under a pattern mixture model. In this article, maximum likelihood estimation of parameters of the categorical missing data is considered with a follow‐up sample under a selection model. To estimate the parameters with non‐ignorable missing data, the EM algorithm with weighting, proposed by Ibrahim, is used. That is, in the E‐step, the weighted mean is calculated using the fractional weights for imputed data. Variances are estimated using the approximated jacknife method. Simulation results are presented to compare the proposed method with previously presented methods.     

Diagnostic checks for integer-valued autoregressive models using expected residuals

Integer-valued time series models make use of thinning operators for coherency in the nature of count data. However, the thinning operators make residuals unobservable and are the main difficulty in developing diagnostic tools for autocorrelated count data. In this regard, we introduce a new residual, which takes the form of predictive distribution functions, to assess probabilistic forecasts, and this new residual is supplemented by a modified usual residuals. Under integer-valued autoregressive (INAR) models, the properties of these two residuals are investigated and used to evaluate the predictive performance and model adequacy of the INAR models. We compare our residuals with the existing residuals through simulation studies and apply our method to select an appropriate INAR model for an over-dispersed real data.     

Stages of sexual readiness and six-month stage progression among African American pre-teens

We examined the range of sexual intentions and behaviors preceding sexual initiation among 211 African-American pre-teens assigned to the control arm of a longitudinal community-based intervention trial. Stage of sexual readiness was assessed using the stage of change construct from the Transtheoretical Model, and patterns of stage movement during a 6-month period were examined. Overall, 90% of participants were in precontemplation at baseline, with the proportion of participants in this stage declining with each year of age. There was substantial stability in stage of sexual readiness during the 6-month period (87% stable). While definitive conclusions regarding exact patterns of movement are not yet possible, stage movement does not appear to be linear for all pre-teens, and there is evidence of both stage progression and regression. We present emerging patterns of stage movement, which suggest potential variation by age, gender, and baseline stage, and discuss potential implications.     

Hardness of <Emphasis Type="Italic">k</Emphasis>-Vertex-Connected Subgraph Augmentation Problem

Given a k-connected graph G=(V,E) and V ^′⊂V, k-Vertex-Connected Subgraph Augmentation Problem (k-VCSAP) is to find S⊂V∖V ^′ with minimum cardinality such that the subgraph induced by V ^′∪S is k-connected. In this paper, we study the hardness of k-VCSAP in undirect graphs. We first prove k-VCSAP is APX-hard. Then, we improve the lower bound in two ways by relying on different assumptions. That is, we prove no algorithm for k-VCSAP has a PR better than O(log (log n)) unless P=NP and O(log n) unless NP⊆DTIME(n ^{O(log log n)}), where n is the size of an input graph.     

Parametric estimation of association in bivariate failure-time data subject to competing risks: sensitivity to underlying assumptions

Lifetime Data Analysis - There has arisen a considerable body of research addressing the estimation of association between paired failure times in the presence of competing risks. In a 2002 paper,...     

Is There a Jump in the Transition?

This article develops a statistical test for the presence of a jump in an otherwise smooth transition process. In this testing, the null model is a threshold regression and the alternative model is a smooth transition model. We propose a quasi-Gaussian likelihood ratio statistic and provide its asymptotic distribution, which is defined as the maximum of a two parameter Gaussian process with a nonzero bias term. Asymptotic critical values can be tabulated and depend on the transition function employed. A simulation method to compute empirical critical values is also developed. Finite-sample performance of the test is assessed via Monte Carlo simulations. The test is applied to investigate the dynamics of racial segregation within cities across the United States.     

Robust estimation for zero-inflated poisson autoregressive models based on density power divergence

In this study, we consider a robust estimation for zero-inflated Poisson autoregressive models using the minimum density power divergence estimator designed by Basu et al. [Robust and efficient estimation by minimising a density power divergence. Biometrika. 1998;85:549–559]. We show that under some regularity conditions, the proposed estimator is strongly consistent and asymptotically normal. The performance of the estimator is evaluated through Monte Carlo simulations. A real data analysis using New South Wales crime data is also provided for illustration.