BECOMING HONG KONG,RAZING BAOAN,PRESERVING XIN'AN: AN ETHNOGRAPHIC ACCOUNT OF URBANIZATION IN THE SHENZHEN SPECIAL ECONOMIC ZONE

Located just north of Hong Kong, Shenzhen, the largest and oldest of China's Special Economic Zone (SEZ) has been both a project and symbol of post-Mao modernization. In this paper, I trace how the Shenzhen built environment mediates images and experiences of ‘Hong Kong’, arguing that transnationality in the SEZ is an everyday practice where tradition, colonialism, and the Cold War provide raw materials for the local reworking of the changing relationship between the Chinese state apparatus and finance capital. My story has a double focus: the ideology of urbanization as modernization and historic preservation. On the one hand, the ideology of urbanization-as-modernization legitimates a spatial order in which the rural is always posed to be superseded by the urban. Both the rural and the urban are empty signifiers that are created through comparison and deployed to guide action. In this important sense,‘Hong Kong’ has been urban with respect to rural ‘Shenzhen’ (formerly Baoan County), even as ‘Shenzhen’ has been urban with respect to the Chinese hinterland (neidi). On the other hand, historic preservation domesticates ‘Hong Kong’ as Shenzhen's past through the figure of Xin'an County, the geographic predecessor of both Shenzhen and Hong Kong. These complimentary displacements produce a nostalgia peculiar to the SEZ: a desire for a past that entitles contemporary Shenzhen residents to Hong Kong's prosperity. This nostalgia is structured with reference to a shared origin - Xin'an County - where Hong Kong's postwar history (1950–1979) becomes the past that Shenzhen (rural Baoan) would have had, if not for a cruel twist of socialist fate.     

Causes of accidents and the time of day

Abstract

The relationship between accidents and the time of day is not entirely clear. Although there is considerable evidence that performance is poorest in the early morning hours compared to at all other times, the degree to which this is translated into accidents is not understood. In this study work-related fatal accidents were analysed to determine whether the causes of these accidents vary with time. The analysis used a classification and coding system devised to describe the wider circumstances of the causes of fatalities. In terms of absolute numbers, fatalities were most common in the late morning or early afternoon. When these results were expressed in terms of the estimated number of workers at work, the proportion of fatal accidents occurring at night was more than double that occurring during the day. Behavioural factors were the most common cause of fatalities at all times, but most common in the early hours of the morning. Further analysis of the nature of the behavioural involvement showed that errors in automatic processing (skill-based errors) were the most common types of error and did not vary much with time of day. Rule-based errors were most common during the day whereas knowledge-based errors occurred mainly in the afternoon and night shifts. These results cast some doubt on the assumption that there is a direct relationship between the previously observed variations in performance across time and the ultimate safety outcome.     

中国各地区经济发展水平的实证分析

利用1995-2006年数据,采用时序多指标综合评价法,对中国各地区经济发展水平进行评价研究。结论表明：虽然中国1995-2006年经济增长迅速,但是经济发展水平并未得到显著提高;各地区经济发展不均衡,地域差距较大且有逐年扩大的倾向。     

Small area estimation: the EBLUP estimator based on spatially correlated random area effects

This paper deals with small area indirect estimators under area level random effect models when only area level data are available and the random effects are correlated. The performance of the Spatial Empirical Best Linear Unbiased Predictor (SEBLUP) is explored with a Monte Carlo simulation study on lattice data and it is applied to the results of the sample survey on Life Conditions in Tuscany (Italy). The mean squared error (MSE) problem is discussed illustrating the MSE estimator in comparison with the MSE of the empirical sampling distribution of SEBLUP estimator. A clear tendency in our empirical findings is that the introduction of spatially correlated random area effects reduce both the variance and the bias of the EBLUP estimator. Despite some residual bias, the coverage rate of our confidence intervals comes close to a nominal 95%.     

THE POLITICAL ECONOMY OF TIME IN THE INTERNET ERA: FEMINIST PERSPECTIVES AND CHALLENGES

This paper examines the gender matrix of time, arguing for cross-disciplinary consideration of political economy, globalization and technology to achieve a detailed understanding of gendered hierarchies of time and the ways in which public/private identifications of social space and time have variously constructed and maintained them. It is argued that women are alienated from their own time, which is identified as most legitimately allocated to the service of others both in the home and at work. The inter-relationship of technologies and gendered identities is explored in relation to public/private divisions and the political-economic and scientific-technological knowledge processes that contribute to upholding them. ICTs reflect these historically established gendered patterns, but international projects such as 'Women on the Net' also demonstrate the capacities of these technologies for disrupting the gender matrix of time through their use by women for women.     

A Conditional Variance Model for Daily Deviations of an Exchange Rate

A model for the distribution of daily deviations of an exchange rate is suggested. The distribution is Gaussian with a variance that depends on previous deviations. The model is applied to the exchange rate of the U.S. dollar to special drawing rights.     

Inference on Filtered and Smoothed Probabilities in Markov-Switching Autoregressive Models

ABSTRACT

We derive a statistical theory that provides useful asymptotic approximations to the distributions of the single inferences of filtered and smoothed probabilities, derived from time series characterized by Markov-switching dynamics. We show that the uncertainty in these probabilities diminishes when the states are separated, the variance of the shocks is low, and the time series or the regimes are persistent. As empirical illustrations of our approach, we analyze the U.S. GDP growth rates and the U.S. real interest rates. For both models, we illustrate the usefulness of the confidence intervals when identifying the business cycle phases and the interest rate regimes.     

Japanese Clocks and the History of Punctuality in Modern Japan

Although punctuality is well attained in present Japan, many foreign engineers who arrived in Japan from the mid 19th century observed that Japanese were seemingly indifferent to the clock, which leads us to a question about the origin of punctuality in modern Japan. The present paper first explains the time system and clocks in the Edo period, and then follows the origin and the evolution of punctuality in various sectors of Japanese society. Introducing the historian Sakae Tsunoyama’s two-layer theory to explain the origin of punctuality in modern Japan, the paper explores a question about when punctuality was attained and society accelerated in postwar Japan.

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Japanese Abstract  時間規律は現代の日本社会ではよく確立されている。 しかし、19 世紀末に日本に到来した多くの外国人技術者にとっては日本人が時計には無関心であるように思えた。このことは、近代日本における時間規律の起源という歴史的問題に導かれる。本稿は、最初に江戸時代における時刻制度と和時計について説明し、続いて日本社会の各領域における時間規律の起源と発展について追いかける。近代日本における時間規律の起源に関する歴史家角山榮による 2 層理論を紹介した上で、戦後日本における時間規律の達成、社会の加速化について検討する。

     

Graphical Techniques for Selecting Explanatory Variables for Time Series Data

Bayesian model building techniques are developed for data with a strong time series structure and possibly exogenous explanatory variables that have strong explanatory and predictive power. The emphasis is on finding whether there are any explanatory variables that might be used for modelling if the data have a strong time series structure that should also be included. We use a time series model that is linear in past observations and that can capture both stochastic and deterministic trend, seasonality and serial correlation. We propose the plotting of absolute predictive error against predictive standard deviation. A series of such plots is utilized to determine which of several nested and non-nested models is optimal in terms of minimizing the dispersion of the predictive distribution and restricting predictive outliers. We apply the techniques to modelling monthly counts of fatal road crashes in Australia where economic, consumption and weather variables are available and we find that three such variables should be included in addition to the time series filter. The approach leads to graphical techniques to determine strengths of relationships between the dependent variable and covariates and to detect model inadequacy as well as determining useful numerical summaries.