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The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development. [ABSTRACT FROM AUTHOR]

In this paper, we explore the problem of establishing a network among the stocks of a market at high frequency level and give an application to program trading. Our work uses high frequency data from the National Stock Exchange, India, for the year 2014. To begin, we analyse the spectrum of the correlation matrix to establish the presence of linear relations amongst the stock returns. A comparison of correlations with pairwise mutual information shows the further existence of non-linear relations which are not captured by correlation. We also see that the non-linear relations are more pronounced at the high frequency level in comparison to the daily returns used in earlier work. We provide two applications of this approach. First, we construct minimal spanning trees for the stock network based on mutual information and study their topology. The year 2014 saw the conduct of general elections in India and the data allows us to explore their impact on aspects of the network, such as the scale-free property and sectorial clusters. Second, having established the presence of non-linear relations, we would like to be able to exploit them. Previous authors have suggested that peripheral stocks in the network would make good proxies for the Markowitz portfolio but with a much smaller number of stocks. We show that peripheral stocks selected using mutual information perform significantly better than ones selected using correlation. [ABSTRACT FROM AUTHOR]

Commercial surrogacy in emerging countries such as India is often associated with exploitation of vulnerable women, the assumption being that it is performed by poor and uneducated women for rich intended parents. However, the hypothesis that surrogates are poor women has rarely been confronted with field data. The objective was to compare the socioeconomic characteristics of Indian surrogates interviewed in social studies with those of Indian women in the general population in order to provide preliminary data on whether surrogates have a specific profile and are indeed disadvantaged compared with their counterparts. The study analyzes the data from four cross-sectional studies carried out in India among surrogates between 2006 and 2014. Surrogates were recruited through clinics, agencies and agents. Data were collected during face-to-face interviews. The resulting convenience sample included 96 Indian surrogates. Their sociodemographic characteristics were compared with those of the general population extracted from Indian national surveys. The surrogates interviewed had their first child at a younger age than women in the general population, but they tended to have a smaller family. Their social situation tended to be better than that of the general population in terms of education, employment and family income. These results provide first empirical evidence moderating the common assumption that Indian surrogates are the poorest and least educated women. This does not mean, however, that exploitation does not exist. More studies are needed to confirm these results and to explore the issue in new international destinations for surrogacy. [ABSTRACT FROM AUTHOR]

Background and Objective: Understanding medical students’ motivation to select medical studies is particularly salient to inform practice and policymaking in countries—such as India—where shortage of medical personnel poses crucial and chronical challenges to healthcare systems. This study aims to develop and validate a questionnaire to assess the motivation of medical students to select medical studies. Methods: A Motivation for Selection of Medical Study (MSMS) questionnaire was developed using extensive literature review followed by Delphi technique. The scale consisted of 12 items, 5 measuring intrinsic dimensions of motivations and 7 measuring extrinsic dimensions. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), validity, reliability and data quality checks were conducted on a sample of 636 medical students from six medical colleges of three North Indian states. Results: The MSMS questionnaire consisted of 3 factors (subscales) and 8 items. The three principal factors that emerged after EFA were the scientific factor (e.g. research opportunities and the ability to use new cutting edge technologies), the societal factor (e.g. job security) and the humanitarian factor (e.g. desire to help others). The CFA conducted showed goodness-of-fit indices supporting the 3-factor model. Conclusion: The three extracted factors cut across the traditional dichotomy between intrinsic and extrinsic motivation and uncover a novel three-faceted motivation construct based on scientific factors, societal expectations and humanitarian needs. This validated instrument can be used to evaluate the motivational factors of medical students to choose medical study in India and similar settings and constitutes a powerful tool for policymakers to design measures able to increase selection of medical curricula. [ABSTRACT FROM AUTHOR]

We examine the impact of religious identity and village-level religious fragmentation on behavior in Tullock contests. We report on a series of two-player Tullock contest experiments conducted on a sample of 516 Hindu and Muslim participants in rural West Bengal, India. Our treatments are the identity of the two players and the degree of religious fragmentation in the village where subjects reside. Our main finding is that the effect of social identity is small and inconsistent across the two religious groups in our study. While we find small but statistically significant results in line with our hypotheses in the Hindu sample, we find no statistically significant effects in the Muslim sample. This is in contrast to evidence from Chakravarty et al. (2016), who report significant differences in cooperation levels in prisoners’ dilemma and stag hunt games, both in terms of village composition and identity. We attribute this to the fact that social identity may have a more powerful effect on cooperation than on conflict. [ABSTRACT FROM AUTHOR]

Background: Emergency referral services (ERS) are being strengthened in India to improve access for institutional delivery. We evaluated a publicly financed and privately delivered model of ERS in Punjab state, India, to assess its extent and pattern of utilization, impact on institutional delivery, quality and unit cost. Methods: Data for almost 0.4 million calls received from April 2012 to March 2013 was analysed to assess the extent and pattern of utilization. Segmented linear regression was used to analyse month-wise data on number of institutional deliveries in public sector health facilities from 2008 to 2013. We inspected ambulances in 2 districts against the Basic Life Support (BLS) standards. Timeliness of ERS was assessed for determining quality. Finally, we computed economic cost of implementing ERS from a health system perspective. Results: On an average, an ambulance transported 3–4 patients per day. Poor and those farther away from the health facility had a higher likelihood of using the ambulance. Although the ERS had an abrupt positive effect on increasing the institutional deliveries in the unadjusted model, there was no effect on institutional delivery after adjustment for autocorrelation. Cost of operating the ambulance service was INR 1361 (USD 22.7) per patient transported or INR 21 (USD 0.35) per km travelled. Conclusion: Emergency referral services in Punjab did not result in a significant change in public sector institutional deliveries. This could be due to high baseline coverage of institutional delivery and low barriers to physical access. Choice of interventions for reduction in Maternal Mortality Ratio (MMR) should be context-specific to have high value for resources spent. The ERS in Punjab needs improvement in terms of quality and reduction of cost to health system. [ABSTRACT FROM AUTHOR]