Chinese Township Village Enterprises as Vaguely Defined Cooperations

This paper concerns the paradoxes and dilemmas that the very successful "Chinese model" presents for transition theory. The "Chinese model" is centered on the development of township-village enterprises. The main purpose of this paper is to make the case that TVE's are not just some form of disguised capitalist institution; they are much better described as "vaguely defined cooperatives" - meaning an essentially communal organization extremely far removed from having well defined ownership structure. That a transition strategy based on vaguely defined cooperatives should be so successful presents a severe challenge for traditional property theory. We speculate that to address this challenge properly, traditional property rights should be extended by including a dimension corresponding to the degree of individualism/cooperation existing in a society. A model of the required extension is described. Implications and application are discussed.

The fundamental problem of command : plan and compliance in a partially centralised economy

When a principal gives an order to an agent and advances resources for its implementation, the temptations for the agent to shirk or steal from the principal rather than comply constitute the fundamental problem of command. Historically, partially centralised command economies enforced compliance in various ways, assisted by nesting the fundamental problem of exchange within that of command. The Soviet economy provides some relevant data. The Soviet command system combined several enforcement mechanisms in an equilibrium that shifted as agents learned and each mechanism's comparative costs and benefits changed. When the conditions for an equilibrium disappeared, the system collapsed.Comparative Economic Studies (2005) 47, 296–314. doi:10.1057/palgrave.ces.810011

Is diversity good?

Prominent ethical and policy issues such as affirmative action and female enrollment in science and engineering revolve around the idea that diversity is good. However, even though diversity is an ambiguous concept, a precise definition is seldom provided. We show that diversity may be construed as a factual description, a craving for symmetry, an intrinsic good, an instrumental good, a symptom, or a side effect. These acceptions differ vastly in their nature and properties. The first one cannot lead to any action and the second one is mistaken. Diversity as intrinsic good is a mere opinion, which cannot be concretely applied; moreover, the most commonly invoked forms of diversity (sexual and racial) are not intrinsically good. On the other hand, diversity as instrumental good can be evaluated empirically and can give rise to policies, but these may be very weak. Finally, symptoms and side effects are not actually about diversity. We consider the example of female enrollment in science and engineering, interpreting the various arguments found in the literature in light of this polysemy. Keywords: ethics, policy, higher education, female students, minority students, affirmative actionComment: 7 page

Divergent mathematical treatments in utility theory

In this paper I study how divergent mathematical treatments affect mathematical modelling, with a special focus on utility theory. In particular I examine recent work on the ranking of information states and the discounting of future utilities, in order to show how, by replacing the standard analytical treatment of the models involved with one based on the framework of Nonstandard Analysis, diametrically opposite results are obtained. In both cases, the choice between the standard and nonstandard treatment amounts to a selection of set-theoretical parameters that cannot be made on purely empirical grounds. The analysis of this phenomenon gives rise to a simple logical account of the relativity of impossibility theorems in economic theory, which concludes the paper

Frontal and Parietal Components of a Cerebral Network Mediating Voluntary Attention to Novel Events

Despite the important role that attending to novel events plays in human behavior, there is limited information about the neuroanatomical underpinnings of this vital activity. This study investigated the relative contributions of the frontal and posterior parietal lobes to the differential processing of novel and target stimuli under an experimental condition in which subjects actively directed attention to novel events. Event-related potentials were recorded from well-matched frontal patients, parietal patients, and non-brain-injured subjects who controlled their viewing duration (by button press) of line drawings that included a frequent, repetitive background stimulus, an infrequent target stimulus, and infrequent, novel visual stimuli. Subjects also responded to target stimuli by pressing a foot pedal. Damage to the frontal cortex resulted in a much greater disruption of response to novel stimuli than to designated targets. Frontal patients exhibited a widely distributed, profound reduction of the novelty P3 response and a marked diminution of the viewing duration of novel events. In contrast, damage to posterior parietal lobes was associated with a substantial reduction of both target P3 and novelty P3 amplitude; however, there was less disruption of the processing of novel than of target stimuli. We conclude that two nodes of the neuroanatomical network for responding to and processing novelty are the prefrontal and posterior parietal regions, which participate in the voluntary allocation of attention to novel events. Injury to this network is indexed by reduced novelty P3 amplitude, which is tightly associated with diminished attention to novel stimuli. The prefrontal cortex may serve as the central node in determining the allocation of attentional resources to novel events, whereas the posterior parietal lobe may provide the neural substrate for the dynamic process of updating one's internal model of the environment to take into account a novel event

Employee Stock Ownership and Financial Performance in European Countries: The Moderating Effects of Uncertainty Avoidance and Social Trust

This study investigates how the effect of employee stock ownership on financial performance may hinge on the diverse cultural and societal contexts of European countries. Based on agency and national culture theories, we hypothesize that the positive relationship between employee stock ownership and return on assets (ROA) is stronger in those nations with lower uncertainty avoidance and higher social trust. Using a multisource, time‐lagged, large‐scale dataset of 1,741 firms from 21 countries in Europe, our multilevel, random coefficient modeling analysis found evidence for these hypotheses, suggesting that uncertainty avoidance and social trust serve as important contextual cues in predicting the linkage between employee stock ownership and financial performance. Our supplemental analysis with distinction between the managerial and nonmanagerial employee stock ownership further indicates managerial employee stock ownership has a direct positive effect on ROA. Although nonmanagerial employee stock ownership had a nonsignificant association with ROA, the relationship was positive and significant when uncertainty avoidance was low and social trust was high. This research contributes to the existing literature by illuminating some of the contextual influences altering the effectiveness of employee stock ownership. Our findings also offer practical suggestions for effectively using employee stock ownership

Allocating the Burdens of Climate Action: Consumption-Based Carbon Accounting and the Polluter-Pays Principle

Action must be taken to combat climate change. Yet, how the costs of climate action should be allocated among states remains a question. One popular answer—the polluter-pays principle (PPP)—stipulates that those responsible for causing the problem should pay to address it. While intuitively plausible, the PPP has been subjected to withering criticism in recent years. It is timely, following the Paris Agreement, to develop a new version: one that does not focus on historical production-based emissions but rather allocates climate burdens in proportion to each state’s annual consumption-based emissions. This change in carbon accounting results in a fairer and more environmentally effective principle for distributing climate duties

Sharing Data for Public Health Research by Members of an International Online Diabetes Social Network

Background: Surveillance and response to diabetes may be accelerated through engaging online diabetes social networks (SNs) in consented research. We tested the willingness of an online diabetes community to share data for public health research by providing members with a privacy-preserving social networking software application for rapid temporal-geographic surveillance of glycemic control. Methods and Findings: SN-mediated collection of cross-sectional, member-reported data from an international online diabetes SN entered into a software applicaction we made available in a “Facebook-like” environment to enable reporting, charting and optional sharing of recent hemoglobin A1c values through a geographic display. Self-enrollment by 17% (n = 1,136) of n = 6,500 active members representing 32 countries and 50 US states. Data were current with 83.1% of most recent A1c values reported obtained within the past 90 days. Sharing was high with 81.4% of users permitting data donation to the community display. 34.1% of users also displayed their A1cs on their SN profile page. Users selecting the most permissive sharing options had a lower average A1c (6.8%) than users not sharing with the community (7.1%, p = .038). 95% of users permitted re-contact. Unadjusted aggregate A1c reported by US users closely resembled aggregate 2007–2008 NHANES estimates (respectively, 6.9% and 6.9%, p = 0.85). Conclusions: Success within an early adopter community demonstrates that online SNs may comprise efficient platforms for bidirectional communication with and data acquisition from disease populations. Advancing this model for cohort and translational science and for use as a complementary surveillance approach will require understanding of inherent selection and publication (sharing) biases in the data and a technology model that supports autonomy, anonymity and privacy.Centers for Disease Control and Prevention (U.S.) (P01HK000088-01)Centers for Disease Control and Prevention (U.S.) (P01HK000016 )National Institute of Alcohol Abuse and Alcoholism (U.S.) (R21 AA016638-01A1)National Center for Research Resources (U.S.) (1U54RR025224-01)Children's Hospital (Boston, Mass.) (Program for Patient Safety and Quality

Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network

The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (i) identifies actual clusters of patents: i.e. technological branches, and (ii) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the {citation vector}, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action

Climate Policy Under Fat-Tailed Risk: An Application of Dice

Uncertainty plays a significant role in evaluating climate policy, and fat-tailed uncertainty may dominate policy advice. Should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty? In order to answer to this question, we propose a new way of investigating the impact of (fat-tailed) uncertainty on optimal climate policy: the curvature of the optimal carbon tax against the uncertainty. We find that the optimal carbon tax increases as the uncertainty about climate sensitivity increases, but it does not accelerate as implied by Weitzman's Dismal Theorem. We find the same result in a wide variety of sensitivity analyses. These results emphasize the importance of balancing the costs of climate change against its benefits, also under deep uncertainty. © 2013 Springer Science+Business Media Dordrecht