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The purpose of this paper is to examine factors that explain dropout of children from primary schools in Lohit district of Arunachal Pradesh, India.

The field survey was carried out in two phases, one, during January to April of 2010 and two, between August and November of 2011. The entire research work is based on stratified random sampling. The population in Lohit district is a set of tribal and non-tribal (mostly general) people. The district has two major tribes – Mishmi and Khamti.

The authors find that children dropout of school is affected by number of factors such as earning compulsions, household work, access to school, school time not suitable and parental unawareness.

It is imperative to mention here that “earning compulsion” can be described only as a derivative of the major problem of abject poverty.

By highlighting the role of appropriate intervention as well as incapacitation, the authors believe that the findings presented above shed light on some important factors that explain dropouts.

The evidence provided in this paper underscores the importance of social interactions in analysing individual outcomes.

The findings may have significant bearings in reducing dropout rates in India.

The concept of poverty traps based on a critical threshold that distinguishes transitory from chronic poverty gives rise to a crucial policy distinction between cargo nets and safety nets. While safety nets are designed to prevent the non‐poor and transitorily poor from falling into chronic poverty, cargo nets are meant to help those who fall below the critical threshold to help them climb out of chronic poverty. The study attempts to determine the factors that affect a beneficiary artisan's decision to use the toolkits provided, i.e. to climb up using the cargo net of improved toolkits and become more active economically.

The paper is based on primary data collected from the supply of improved toolkits to rural artisans (SITRA) programme in 2001‐2002. It is performed on the dataset consisting of 6,788 observations (beneficiary artisans). Due to some missing data 700 observations could not be used. Thus, only 6,088 observations are considered for the purpose of the ordered logit analysis.

The paper develops the related concepts of conditional and structural rigidities restraining the movement and studies the role of these rigidities in determining the economic mobility of a beneficiary household when a climbing cargo net is provided. The paper finds that there is strong evidence that governments are confused about the concept of poverty reduction and alleviation strategies. The study reveals that narrower targeting on beneficiaries with lower conditional rigidities is better as they are more likely to use the toolkits and hence increase their income from craftsmanship and so promote both economic growth and poverty reduction.

The study focuses on a specific poverty alleviation programme. The findings are restricted to a special economic group at all India level. Nonetheless, the study highlights that a thorough understanding of the conditional and structural rigidities faced by a beneficiary artisan and how these affect his economic behaviour would be very useful in both designing and implementation of poverty reduction programmes.

This paper will be of value to researchers, policy makers seeking to gain better understanding of targeting. The paper observes that appreciation of significant conditional rigidities are useful while designing programmes – particularly while targeting the beneficiaries – structural rigidities are more important while implementing and monitoring these programs.

The purpose of this paper is to highlight the dual effect of demographic changes and emigration of young people on the economic growth of small Caribbean economies and the serious economic challenges arising therefrom.

The paper develops a theoretical model leading to a hypothesis that is later tested on Barbados.

Rising incomes have had very significant demographic changes in Barbados and other small Caribbean economies while proximity to large developed economies have contributed to emigration. Together, these have caused capital outflows from the economies as well as simultaneous shortage of skilled workers and high rates of overall unemployment.

Economic vulnerability of small states needs further detailed study.

One implication for the small Caribbean economies is to restructure their labour market through sustained skill development programmes so as to reduce the skill gap between the demand and supply of specific skills.

Although demographic shifts and their effects are widely studied, this paper highlights the special vulnerability of the small Caribbean economies to lower fertility, ageing and emigration.

The purpose of this research is to demonstrate the primacy of adequate human capital for successful completion of infrastructure projects in developing countries.

A case study approach is used and three Caribbean infrastructure projects analyzed using a common framework to identify links between project success and availability of adequate human capital.

Explains how the scarcity of human capital at executive and managerial levels may have disastrous consequences for successful project completion, particularly in developing countries.

Developing countries like those of the Caribbean that have done well in human development rankings can still suffer from scarcity of human capital.

The funding agencies need to emphasize the estimation, provisioning and development of human capital for funded projects and ensure the continued availability of the same until project completion as much as they do for physical and economic capital.

The paper brings out the critical role of human capital, which is quite often scarce in developing countries but is needed to use the Project Management body of knowledge for successful completion of projects.

The purpose of this paper is to develop a theoretical model to explore the economic consequences of an exogenous skill‐biased technological change.

The paper develops a theoretical model based on assumptions and conditions that replicate those of a government‐sponsored poverty reduction programme in India.

The paper finds that, under certain stated conditions, wage inequality between artisans with improved toolkits and those without is likely to increase, while, under a different set of conditions, this is likely to decrease.

Actual wage inequality implications of specific exogenous skill‐biased technological changes need to be studied to take the theoretical model further.

One major implication is that, when government help is provided by way of an exogenous skill‐biased technological change to a fraction of workers, it may have the unintended consequence of increasing wage inequality between the beneficiary and the non‐beneficiary workers. In extreme cases, it may even lower the equilibrium wages of the non‐beneficiary workers.

The paper brings out the critical role of efficiency units of workers with skill‐biased technology (artisans with improved toolkits) and those without these in determining the wage inequality between these categories of workers (artisans) based on a theoretical model of the trajectory along which the rural economy moves.

The purpose of this paper is to focus on valuation practices applied by analysts to derive target price forecasts in Asian emerging markets. The key objective of this study is to understand valuation model preference of analysts and to compare the predictive utility of target price forecasts derived through heuristics-driven price-to-earnings (PE) model and theoretically sound discounted cash flow (DCF) model.

Each research report in the sample of 502 research reports has been studied in detail to understand the dominant valuation model (PE or DCF) applied by analyst to derive target price forecasts. These research reports have been issued on stocks trading in seven emerging markets including India, Malaysia, Indonesia, Taiwan, Philippines, Korea and Thailand during a six-year period starting 2008. Standard OLS and logit regression analysis has been performed to derive empirical findings.

The study finds that lower regulatory and reporting standards prevailing in emerging markets have no significant bearing on analyst choice of valuation model (PE or DCF). Time-series analysis suggests that emerging market analysts did not rely upon the usage of DCF model and preferred PE model during and immediately after the financial crisis of 2008. Multivariate regression results show weak evidence that PE model produces better results than DCF model after adjusting for the complexities associated with analyzing emerging market equities. The results imply that PE model, to some degree, is better equipped to capture market moods and sentiment in dynamic emerging markets rather than theoretically sound DCF model.

Most past studies on valuation model practices have focused on developed markets and this study provides a fresh perspective on analyst valuation model practices and performance in a new institutional setting of Asian emerging markets. The marginally better predictive utility of PE model as compared to DCF model is possibly a feature limited to Asian emerging markets.