POPULATION PRESSURE, MARKET ACCESS AND FOOD SECURITY IN THE UPLANDS OF NORTHERN VIETNAM: A MICRO-ECONOMIC ANALYSIS

Upland areas in Vietnam account for two-thirds of its natural area and one-third of its population. These uplands are characterized by heterogeneous and fragile ecosystems, a high incidence of poverty, severe deforestation and soil degradation. Rice is an important staple which is grown in the upland fields using shifting cultivation and in intensive lowland fields. The predominantly subsistence-oriented agricultural production system of these upland areas is undergoing intensification due to rapidly increasing population pressure. Changes in government policies regarding uplands and improvements in access to markets have led to the evolution of market-oriented production systems in some areas. In addition, rapid improvement in the productivity of lowland rice following decollectivization has also affected the use of upland areas. The paper examines the effect of population pressure and market access on cropping patterns, cropping intensity, the extent of commercialization of production systems, land and labor productivity, household food supply and the overall level of poverty. The analysis is based on a cross-sectional survey of 980 farm households from 33 communes of six provinces during the crop year 1997-98. It is hypothesized that (a) the cropping intensity is positively related to the population density and is negatively related to market access, (b) labor productivity in agriculture is higher in areas with better access to market, (c) upland rice occupies proportionately smaller area of upland as the size of the lowland holding increases, and (d) the extent of food shortage depends on land and labor endowments as well as the access to markets. Reduced-form models were used to investigate these hypotheses. Cropping intensity was found to be higher in communes with a higher population density supporting the Boserupian hypothesis. Market access, which was specified as a dummy variable (low access and high access), affected labor productivity and cash income positively. Despite these positive effects, the agricultural production system was found to be predominantly subsistence-oriented with farmers striving to achieve food self-sufficiency even in areas where a lot of cash crop is grown. The proportionate area under upland rice was found to be related negatively with the size of the lowland holding indicating that an improvement in lowland productivity can help reduce the intensification pressure in the upland. Farmers with better access to market and with larger farms were found to have a lower incidence of food shortage than farmers with limited access to markets and with smaller farms. A simulation model was developed to project the likely effect of continued increase in population pressure on food production, labor absorption in agriculture, calorie consumption per capita and the extent of poverty. A simple life table was used to project the population by sex and age group for the next 20 years. The effect of rising population pressure on food production was simulated assuming that the current agricultural productivity of different land/labor quartiles applies to the households as they move across the quartile groups. The static projection indicated that while the labor force will increase by 75% in 20 years, labor use in crop production will increase by only 9%, thus showing the need to expand labor absorption in the non-crop sector. With the existing technology, crop production will increase by only 5% of its current value leading to a dramatic decline in per capita food supply. The growth in rice yield (both upland and lowland) of at least 2% per annum is needed to maintain the current per capita calorie intake. An improvement in the upland rice yield was found to be an important strategy in reducing the poverty of the low-income quartile group that depends mostly on upland rice. Given the size of the population growth, the overall reduction in poverty will require an expansion of employment in the non-crop and non-farm sectors. The paper concludes with recommendations that include (a) further expansion of market access and development of more effective marketing institutions, (b) a regionally differentiated approach to agricultural diversification that recognizes the environmental diversity, (c) improvements in food production technology, (d) expansion of income-generating activities such as agro-processing and (e) more effective population control programs.Food Security and Poverty,

Carbon assessment for cocoa cropping systems in Lampung, Indonesia

Cocoa (Theobroma cacao L.) production plays a key role in the economics of Indonesia, the world’s fourth largest cocoa bean producing country. With more than 1.6 million hectares of land planted with cocoa, small improvements in emissions efficiencies or carbon sequestration opportunities can have a relatively large mitigating effect on emissions from agroforestry and land use. The carbon assessment in Lampung, Sumatra was done to evaluate environmental impacts of cocoa as a commodity through estimation of carbon stock and carbon footprint, GHG emissions during the cultivation of cocoa in different cropping systems. Segmentation of cropping systems along density of intercropping, inputs use intensity and residue management practices identify opportunities for climate smart practices tailored to each segment

Outward Influence and Cascade Size Estimation in Billion-scale Networks

Estimating cascade size and nodes' influence is a fundamental task in social, technological, and biological networks. Yet this task is extremely challenging due to the sheer size and the structural heterogeneity of networks. We investigate a new influence measure, termed outward influence (OI), defined as the (expected) number of nodes that a subset of nodes $S$ will activate, excluding the nodes in S. Thus, OI equals, the de facto standard measure, influence spread of S minus |S|. OI is not only more informative for nodes with small influence, but also, critical in designing new effective sampling and statistical estimation methods. Based on OI, we propose SIEA/SOIEA, novel methods to estimate influence spread/outward influence at scale and with rigorous theoretical guarantees. The proposed methods are built on two novel components 1) IICP an important sampling method for outward influence, and 2) RSA, a robust mean estimation method that minimize the number of samples through analyzing variance and range of random variables. Compared to the state-of-the art for influence estimation, SIEA is $\Omega(\log^4 n)$ times faster in theory and up to several orders of magnitude faster in practice. For the first time, influence of nodes in the networks of billions of edges can be estimated with high accuracy within a few minutes. Our comprehensive experiments on real-world networks also give evidence against the popular practice of using a fixed number, e.g. 10K or 20K, of samples to compute the "ground truth" for influence spread.Comment: 16 pages, SIGMETRICS 201

Importance Sketching of Influence Dynamics in Billion-scale Networks

The blooming availability of traces for social, biological, and communication networks opens up unprecedented opportunities in analyzing diffusion processes in networks. However, the sheer sizes of the nowadays networks raise serious challenges in computational efficiency and scalability. In this paper, we propose a new hyper-graph sketching framework for inflence dynamics in networks. The central of our sketching framework, called SKIS, is an efficient importance sampling algorithm that returns only non-singular reverse cascades in the network. Comparing to previously developed sketches like RIS and SKIM, our sketch significantly enhances estimation quality while substantially reducing processing time and memory-footprint. Further, we present general strategies of using SKIS to enhance existing algorithms for influence estimation and influence maximization which are motivated by practical applications like viral marketing. Using SKIS, we design high-quality influence oracle for seed sets with average estimation error up to 10x times smaller than those using RIS and 6x times smaller than SKIM. In addition, our influence maximization using SKIS substantially improves the quality of solutions for greedy algorithms. It achieves up to 10x times speed-up and 4x memory reduction for the fastest RIS-based DSSA algorithm, while maintaining the same theoretical guarantees.Comment: 12 pages, to appear in ICDM 2017 as a regular pape

Institutional Changes for Private Sector Development in Vietnam : Experience and Lessons

Vietnam, Centrally Planned Economies, Transition, reform, institutions

Construction of Classroom Community in a Full-Inclusion District: Comparative Case Studies with Elementary School Teachers

This research documented how elementary school teachers build, structure, and maintain classroom community in a full-inclusion district. Specifically, this study applied Invitational Theory to investigate the relationship between a full-inclusion school model and the construction of classroom community. The study focused on the teachers’ behaviors to structure and maintain an environment of inclusion, care, and belonging. This qualitative comparative case study documented teachers’ behaviors over a series of 10 weeks at the start of the school year. Documentation evidence of classroom community- building were collected in two formats: classroom observations and teacher interviews. By the end of the observational period, 11 classroom codes, and 11 context-dependent sub-codes summarized teachers’ actions. The codes were deduced into five groups based on context and behavior. These contexts and behaviors allowed for the synthesizing of trends and patterns to generate central themes, which are also the significant findings of the study. The significant findings of the study indicated that the teacher’s intention impacts the classroom environment, teacher encouragement affects student participation, and each teacher’s design of the classroom environment facilitated conditions of learning. The study shared how teachers in a full-inclusion district built and maintained their classroom community. From the findings, the teachers noted the importance to purposefully personalize the learning experience for their students. The research also noted implications for school leaders to promote and enhance community-building experiences for students. Future research to align the relationship between a classroom community and student engagement can further highlight the importance in classroom community construction