Determining dental sex dimorphism in South Indians using discriminant function analysis

Dental forensics forms a vital branch of forensic science which deals with proper handling, examination and evaluation of dental evidences for identification of victims of crime, accidents or calamities. Therefore skull and teeth often provide the identification material. The aim of the study was to investigate the accuracy of odontometric methods in sex determination of permanent teeth and to compute new formula to differentiate male and female teeth using discriminant function analysis for South Indian population. A total of 100 subjects were selected for the study from a parent population of 4800 students by simple random sampling method. Alginate impressions of the upper dental arch were made and casts were poured immediately. A digital vernier calliper was used for the measurement of all upper anteriors. Twelve different tooth measurements were recorded and from those two indexes have been computed. Statistical analysis was performed using the SPSS version 17.0 software. All the predictor variables were subjected to stepwise discriminant function analysis which optimally separates the genders and a best discriminant function was generated. In all the observed mean dimensions, male values exceed the female values. Student's 't' test for the different predictor variables of all teeth selected between male and females were found significant (p < 0.05). Very high significance was found in mean MD of 11, 12 and 13 and |c| of 23. The variables exhibiting best discriminant powers were mesiodistal width of both upper central incisors, DB-ML of 13 and canine crown module of 13. Sexual dimorphism in the size of permanent teeth differs from one population to the other and hence the standards set for one population could not be applied for another population. Hence this technique would be a simple, quick, cost effective, reliable and accurate for sex determination.     

Dynamics of exchange rate and stock price volatility: Evidence from India

The article examines causal relationship between exchange rate and stock price volatility. We use daily data from February 2, 2015 to August 30, 2019 to estimate variables employed in ARCH/GARCH, and cross correlation. It gives a feedback that effect between the conditional mean and variance of exchange rate and stock price volatility. The stock market has brought more capital inflow rupee that appreciate while capital moves out of the monetary system rupee depreciate. The Reserve Bank of India has a policy to encourage and to bring huge inflows instead of outflows.     

Exchange rate (USD/INR) pass‐through and wholesale price index: A flexible least square approach

The paper explores the exchange rate (USD/INR) pass‐through and the wholesale price index in India. Exchange rate pass‐through (ERPT) has a stimulated effect on the wholesale prices over the period of time. We use flexible least square approach to estimate time varying approach of ERPT and wholesale price, monthly data for the period from April 1994 to May 2019, find exchange rate over the period of time as well as change the wholesale price. It implies that the ERPT provides heterogeneity information that change the whole price index, even both export/import goods and services play a vital role in fluctuating on exchange rate and also change whole price in the domestic market.     

Stock prices,inflation, and output in India: An empirical analysis

This study focusses on the negative relationship between inflation and stock returns (the puzzle of fisher hypothesis). Fama hypothesis examined the relationship between macroeconomic variable and stock return and found the strong relationship between the real output and stock prices. This study revisits Fama's hypothesis from the period 1990M1 to 2016M6 for emerging country perspective. The results documented that there is a significant negative relationship between inflation and output whereas positive between stock price and output.     

The Impact of Bt Cotton on Poor Households in Rural India

The impact of genetically modified (GM) crops on the poor in developing countries is still the subject of controversy. While previous studies have examined direct productivity effects of Bacillus thuringiensis (Bt) cotton and other GM crops, little is known about wider socioeconomic outcomes. We use a microeconomic modelling approach and comprehensive survey data from India to analyse welfare and distribution effects in a typical village economy. Bt cotton adoption increases returns to labour, especially for hired female workers. Likewise, aggregate household incomes rise, including for poor and vulnerable farmers. Hence, Bt cotton contributes to poverty reduction and rural development.