Background: The population of elderly people aged ≥60 years is increasing worldwide and is projected to reach 1.5 billion by 2050. In India, the elderly people constitute 8.1% of the total population. Malnutrition is highly prevalent in the elderly population due to various diseases and impairments.Methods: A cross-sectional study was carried out amongst 209 elderly people from February 2018 to April 2018. A questionnaire was used to collect data related to socio-demographic characteristics, Mini Nutritional Assessment (MNA) and regarding medication use, comorbidity, use of a walking aid, smoking and alcohol consumption. The MNA tool was used for the assessment of nutrition status. For an assessment of functional status, the activities of daily living scale and instrumental activities of daily living scale were used. Descriptive analysis and Chi-square test were used to present the data.Results: The average MNA score was 23.5 (SD=4.3, range: 7-30) and that of BMI was 23.8 (SD=3.9, range: 15.6-38.9). Of 209 study participants, 9.1% were malnourished, 32.5% were at risk of malnutrition and remaining 58.4% were having normal nutritional status. The possible predictors of malnutrition were older age, lower education level, staying single, unemployed, low income and less than three meals daily.Conclusions: The overall prevalence of malnutrition was found to be 9.1% but the proportion of elderly people at risk of malnutrition was relatively high. Diagnosis and treatment of elderly people at high risk for malnutrition based on the findings of this study may improve functional status and prognosis of elderly people.

This paper examines hedging effectiveness of futures contract on a financial asset and commodities in Indian markets. In an emerging market context like India, the growth of capital and commodity futures market would depend on effectiveness of derivatives in managing risk. For managing risk, understanding optimal hedge ratio is critical for devising effective hedging strategy. We estimate dynamic and constant hedge ratio for S&P CNX Nifty index futures, Gold futures and Soybean futures. Various models (OLS, VAR, and VECM) are used to estimate constant hedge ratio. To estimate dynamic hedge ratios, we use VAR-MGARCH. We compare in-sample and out-of-sample performance of these models in reducing portfolio risk. It is found that in most of the cases, VAR-MGARCH model estimates of time varying hedge ratio provide highest variance reduction as compared to hedges based on constant hedge ratio. Our results are consistent with findings

<p>The purpose of this paper is to classify the value drivers into broad categories and then identify the major drivers of firm’s value for Indian manufacturing industry and also work out the sectorial sensitivity of value drivers. To achieve the objectives of the study we first derive the value driver’s model next we use panel regression with different model specifications to empirically analyse the major drivers of firm’s value. Our study reveals that sales, net margin, book value, dividend per share, beta and earnings per share are the six major financial drivers of value. All the strategic drivers when included in the model have significant relation with value without disturbing the r-square of the model. Thus, it is clear that apart from generic financial drivers, firms need to put more attention on strategic choices they make, because it is the strategic choice that will give firms an edge over others in developing economies like India. Further, we also observe sector specific priorities of the value drivers. This paper provides academicians and practitioners with an overview of the applicability of value drivers for Indian manufacturing industry. Further, the study will fill the gap in literature by adding value drivers’ evidence from one of the fastest growing economies in the world and will benefit researchers in arriving at common consensus for value drivers in emerging economies. </p>

The present study examines the interrelationship between economic growth, saving rate and inflation for southeast and south Asia in a simultaneous equation framework using two stage least squares with panel data. The relationship between saving rate and growth has been found to be bi-directional and positive. Inflation has a highly significant negative effect on growth but positive effect on saving rate. Inflation is not affected by growth but is largely determined by its past values, and saving rate is not affected by interest rate. These findings for countries in Asia with widely divergent values of aggregates are very relevant for development policies and strategies 4 .

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