Structural equation modeling of political discussion networks

This study conducts structural equation modeling (SEM) of political discussion networks. It examines multiple relationships between political discussion networks—network size and non-kin composition, political efficacy, and neighborhood conversation. Based on a two-step approach, it first analyzes and revises the measurement model and then analyzes and revises the structural model given the revised measurement model. The proposed SEM model includes ordered categorical variables as factor indicators in the confirmatory analysis and outcome variables in the structural regressions. Traditional estimation and regression methods need to be adjusted accordingly. This study uses WLS estimation and adopts a latent variable approach to study the categorical outcome variables in the SEM. The results show that the hypothesized SEM model is fully supported. Neighborhood conversation positively and directly contributes to political discussion network size as well as the non-kin composition of the networks. It also indirectly affects network size through political efficacy. Political efficacy also has a direct effect on network size.Statistic

US Seafood Exports and HACCP Regulatory System

This study investigates how the implementation and standards harmonization of HACCP regulation affects U.S. seafood exporting based on the method of Gravity Model and Spatial Error model. The analysis includes top 32 countries that importing seafood from U.S. The results indicate that HACCP standards benefit U.S. seafood exporting in the long time period but do not have significant impact in the short term period. Moreover, the way of performance standards is better for HACCP implementation and standards harmony.HACCP, U.S. seafood exports, Agricultural and Food Policy, Food Security and Poverty, International Relations/Trade,

The Effects of Food Safety Standards on Trade and Welfare: The Case of EU Shrimp Imports

This research explores the link between a gravity model and welfare frameworks and then applies the quantitative model system to analyze how trade and welfare is affected by the Minimum Required Performance Limits (MRPL) in the shrimp importing market of European Union. The quantitative model system consists of two parts: first, this study uses the “phi-ness” gravity model to investigate the trade effects of MRPL on EU shrimp market. The “phi-ness” gravity model partitions the standard variables to avoid biased estimation caused by the correlation between time and country fixed effects and policy variables. The Poisson Pseudo Maximum Likelihood (PPML) method is incorporated into the estimation in order to control for the zero valued observations. Second, based on the theoretic foundation of the gravity model, this research sets up the specific nested Constant Elasticity of Substitution (CES) model of consumers’ utility and further explores the linkage between these two models. The nested CES model incorporates the effects of MRPL on consumers’ confidence in domestic food as well as foreign food imported from developed and developing countries. The empirical results confirm a consistent fact with previous empirical studies: stricter MRPL has significant and negative effects on trade integration between EU and trading partners with lower level of food safety standards. The welfare analysis shows that the zero tolerance policy of MRPL standard would dramatically enhance consumers’ demand for domestic shrimps and foreign shrimps imported from developed countries but reduce the quantity of shrimp supplied from developing countries. It is also indicated that the increased level of MRPL lead to an increase in welfare of domestic consumers, suppliers in developing countries, and in total international trade, as well as a decrease in the welfare of domestic suppliers and foreign suppliers from developed countries. The empirical results also indicate that the combination of GM and Welfare Approach can also be applied to research on other standards or other industries

Augmenting the Calvin-Benson-Bassham cycle by a synthetic malyl-CoA-glycerate carbon fixation pathway.

The Calvin-Benson-Bassham (CBB) cycle is presumably evolved for optimal synthesis of C3 sugars, but not for the production of C2 metabolite acetyl-CoA. The carbon loss in producing acetyl-CoA from decarboxylation of C3 sugar limits the maximum carbon yield of photosynthesis. Here we design a synthetic malyl-CoA-glycerate (MCG) pathway to augment the CBB cycle for efficient acetyl-CoA synthesis. This pathway converts a C3 metabolite to two acetyl-CoA by fixation of one additional CO2 equivalent, or assimilates glyoxylate, a photorespiration intermediate, to produce acetyl-CoA without net carbon loss. We first functionally demonstrate the design of the MCG pathway in vitro and in Escherichia coli. We then implement the pathway in a photosynthetic organism Synechococcus elongates PCC7942, and show that it increases the intracellular acetyl-CoA pool and enhances bicarbonate assimilation by roughly 2-fold. This work provides a strategy to improve carbon fixation efficiency in photosynthetic organisms

Grid multi-category response logistic models.

BackgroundMulti-category response models are very important complements to binary logistic models in medical decision-making. Decomposing model construction by aggregating computation developed at different sites is necessary when data cannot be moved outside institutions due to privacy or other concerns. Such decomposition makes it possible to conduct grid computing to protect the privacy of individual observations.MethodsThis paper proposes two grid multi-category response models for ordinal and multinomial logistic regressions. Grid computation to test model assumptions is also developed for these two types of models. In addition, we present grid methods for goodness-of-fit assessment and for classification performance evaluation.ResultsSimulation results show that the grid models produce the same results as those obtained from corresponding centralized models, demonstrating that it is possible to build models using multi-center data without losing accuracy or transmitting observation-level data. Two real data sets are used to evaluate the performance of our proposed grid models.ConclusionsThe grid fitting method offers a practical solution for resolving privacy and other issues caused by pooling all data in a central site. The proposed method is applicable for various likelihood estimation problems, including other generalized linear models