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Dynamic transformations: unravelling the linkages between shifting MPI patterns and economic growth variables in Himachal Pradesh

Ritesh Singh

International Journal of Happiness and Development2025https://doi.org/10.1504/ijhd.2025.147942article
AJG 1
Weight
0.50

What the paper says

Study recognises poverty as complex phenomenon but it can be measured on the basis of three dimensions; Health, Education and Living Standards. There are various indicators of these dimensions of MPI. A change in MPI rate has been observed between two national reports 2015-2016 and 2019-2020 published by NITI Aayog. MPI in urban areas of Himachal Pradesh has increased over the period of time which is an eye opener to the government and needs to be taken care of. The Cooking Fuel is the most deprived indicator over the time period. Although MPI in rural areas has fallen but still its intensity is very high. Multiple Linear Regression model shows that there is positive statistical significant relationship between MPI, HCR and Intensity. Spearman's Rank Correlation shows that out of various different development indicators of Himachal Pradesh; Total Food Grain and Government Jobs have positive correlation with MPI whereas Agriculture Societies and Secondary Sector have negative correlation with MPI.

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https://doi.org/https://doi.org/10.1504/ijhd.2025.147942

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@article{ritesh2025,
  title        = {{Dynamic transformations: unravelling the linkages between shifting MPI patterns and economic growth variables in Himachal Pradesh}},
  author       = {Ritesh Singh},
  journal      = {International Journal of Happiness and Development},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijhd.2025.147942},
}

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Dynamic transformations: unravelling the linkages between shifting MPI patterns and economic growth variables in Himachal Pradesh

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.