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This paper explores the estimation of responsiveness factors of productivity in major crops in Bhopal District. The study is based on primary- data (2021-22). The dependent variable is yield of crop (kg|ha), independent variables are labour use, machine use(whr.|ha), irrigation machine use(whr.|ha), Animal use(whr.|ha), seed use(kg\ha), Fertiliser use(kg\ha), farm yard manure use(Qtl.\ha),tractor dummy use, education of household head (year), age year The result of regression analysis show as the yield of cotton is 584 kg per hectare and standard error is (0.276), So it shows that the addition implementation of labour will not be helpful to increase the yield of cotton crop. Machine use had positive impact upon yield of cotton and is significant at 5 percent level of significance. On the other side there seems negative impact on yield if increase the working hours of irrigation machine use, animal use and seed use. Fertilizer use had positive impact on yield and is significant at 10 percent level of significance. Education of house hold had positive impact on yield but is not significant. The results of regression in gram cultivation shows that yield of gram had negative impact of labour use this means that gram is not labour intensive. While as results of regression shows that yield had positive impact of machine- use, tractor and education of house hold.

Keywords: Farm-Size, Productivity, crops

In order to improve incomes, generating year round employment, conservation of natural resources and stabilizing the income over the seasons, crop diversification is regarded as an important strategy to overcome the challenges in agriculture. This study has been undertaken to examine the status and trend of crop diversification in different states in India. Moreover, the paper maps the spatial distribution of diversification index in India. The results indicate that cereals cover the major share of area in gross cropped area among different crop groups during TE years between 1952-53 and 2021-22. Interestingly, the concentration of crops has increased in majority of agricultural states including Chhattisgarh, Telangana, Tamil Nadu, Madhya Pradesh, Andhra Pradesh, Bihar, Odisha, Maharashtra, Punjab, Karnataka, Gujarat, Uttar Pradesh as well as at All India level. The southern and western regions were the only regions having higher agricultural growth during 1990s due to movement towards non-cereal crops. The northern region has more concentration in favour of wheat and rice crops. The eastern region is most backward with respect to growth in agriculture, income and infrastructure and therefore, has relatively low diversification index as compared to other regions. In order to harness the potential benefits of diversification, the appropriate technologies be introduced and suitable infrastructure be created. Domestic reforms in the markets are necessary which support the agricultural diversification in the districts.

Keywords: Simpson’s Crop diversification index, district wise diversification, agriculture

Rural indebtedness is an issue even today when the state has initiated a large number of measures to financially include all the citizens and also to increase the access to credit especially for the rural masses. Though there are contrarian views regarding the role of credit in agriculture and rural economy, the fact cannot be denied that one of the primary reasons for agricultural distress is the lack of credit. Farmer suicides are a reality in India with the primary reason being indebtedness. The state of Madhya Pradesh has economically grown over the last two decades mainly because of improved agricultural production and productivity. However, the state also features highly when it comes to the distress of farmers and their indebtedness. This paper looks at the agricultural distress from the lenses of rural indebtedness and attempts to find its determinants. The analysis has been carried out on the unit level data of NSSO for a period of ten years, taking ten explanatory variables to explain rural farm credit. The paper concludes that farm inputs, farm size, access to financial instruments are the key determinants of agricultural credit in the state of Madhya Pradesh.

Keyword: Indebtedness, NSSO, Rural Credit, Tobit Model, Madhya Pradesh.

The present study examines the impact of artificial intelligence (AI) on the stock market (SM) along with other factors such as trade (tr), foreign investment (FDI), exchange rate (Ex), and inflation (In) from 2000 to 2022 in BRICS nations. BRICS countries were particularly selected due to the high potential for investment. The results show that AI, FDI, and trade have a positive effect on the stock market, whereas exchange rate and inflation have a negative effect. While in the short run, all factors except trade have a positive impact on stock market in BRICS nations. Furthermore, employing the Dumitrescu-Hurlin causality test, a bidirectional causal relationship was found between the stock market and FDI and the stock market and trade. A unidirectional causality was found between AI and the stock market. The findings suggested that policymakers should concentrate more on investment policies and integrating AI techniques for the growth of the stock market.

Keywords: Artificial intelligence; FDI; Panel ARDL; Stock market; Trade
JEL Classification: C1, F10, G1.

This cross-sectional study investigates the user experience and efficacy of digital health tools for mental health, focusing on the influence of gender and age. With a sample size of 250 respondents, convenience sampling and Likert scales were employed to assess responses. The primary objectives were to evaluate the effectiveness of the tools, analyze the user experience, and identify barriers and facilitators across different genders and age groups. 

The findings reveal notable gender-based differences, with females indicating higher perceived effectiveness. Additionally, age-related disparities were observed in the perceived effectiveness of digital health tools. 

The study recommends incorporating personalization, user-friendly designs, and age-appropriate content to enhance these tools. Noteworthy limitations include potential sampling bias and reliance on self-reported data. Future research is advised to employ diverse sampling techniques, include objective measures, and explore longitudinal designs for a comprehensive understanding. The study’s significance lies in providing insights for developers and policymakers to optimize digital health tools, accommodating diverse user needs and promoting favorable mental health outcomes.

Keywords: Digital Health Tools, Mental Health, User Experience, Effectiveness, MMR
JEL Classification: C83, I1, I10