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MoSPI and Thapar Institute Sign MoU for Predictive Analysis of Monthly Consumption Expenditure

The Ministry of Statistics and Programme Implementation (MoSPI) signed a Memorandum of Understanding (MoU) with the Thapar Institute of Engineering & Technology, Patiala, on August 31, 2026. The collaboration aims to develop a predictive and analytical framework for Monthly Per Capita Consumption Expenditure (MPCE) in India using data from the Household Consumption Expenditure Survey and applying artificial intelligence and machine learning technologies to enhance statistical modelling.

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Key Facts

  • MoSPI signed an MoU with Thapar Institute of Engineering & Technology, Patiala, Punjab, on 31 August 2026.
  • The MoU focuses on joint research to develop a predictive and analytical framework for Monthly Per Capita Consumption Expenditure (MPCE) at the national and state levels in India.
  • MPCE is a standard statistical indicator derived from Household Consumption Expenditure Survey data, widely used to assess consumption patterns and poverty levels.
  • The research applies artificial intelligence and machine learning techniques to improve estimation and analysis in official statistics.
  • The MoU was signed by Prof. Padmakumar Nair, Vice Chancellor of Thapar Institute, and Shri R. Rajesh, Additional Director General, MoSPI.

Background & Context

MoSPI is the nodal ministry responsible for collecting and disseminating official statistics in India, including surveys and socio-economic indicators. The Household Consumption Expenditure Survey provides comprehensive data on household spending patterns, essential for macroeconomic analysis and policy formulation.

The Thapar Institute, located in Patiala, Punjab, is a premier engineering and technology institute engaged in research and higher education. The partnership leverages academic expertise and advanced analytical methods to improve the use of consumption data.

AI and machine learning are increasingly utilized in statistical systems globally to enhance data analysis, model estimation, pattern detection, and predictive accuracy in official statistics.

Why This Matters for Exams

This MoU illustrates the Indian government's adoption of modern analytical tools like AI/ML in official statistics, which is a key aspect of contemporary governance and policy planning. MPCE is often a topic in economics, development studies, and social science examinations, reflecting its importance in measuring household welfare and poverty.

Understanding the role of institutions like MoSPI and collaborations with academic institutes can assist candidates in questions related to data governance, statistical reforms, and socio-economic policies.

Points to Remember

  • The MoU between MoSPI and Thapar Institute was signed on 31 August 2026.
  • The project involves developing predictive analytical frameworks for MPCE using the Household Consumption Expenditure Survey data.
  • MPCE is a critical measure of monthly household consumption used in economic and poverty analyses.
  • Artificial intelligence and machine learning are applied for more precise and timely statistical estimations.
  • The collaboration exemplifies the integration of technology with official data systems in India.

Practice MCQs

Question 1

  1. When was the MoU between MoSPI and Thapar Institute signed?
  2. a) 31 August 2024
  3. b) 31 August 2025
  4. c) 31 August 2026
  5. d) 30 August 2026

Answer: c) 31 August 2026

Question 2

  1. What is the focus of the collaborative research under the MoU?
  2. a) Migration trends in India
  3. b) Developing predictive and analytical framework for Monthly Per Capita Consumption Expenditure
  4. c) Agricultural price forecasting
  5. d) Urban infrastructure planning

Answer: b) Developing predictive and analytical framework for Monthly Per Capita Consumption Expenditure

Question 3

  1. Which technologies are emphasized in the research collaboration?
  2. a) Blockchain and Internet of Things
  3. b) Virtual Reality and Augmented Reality
  4. c) Artificial Intelligence and Machine Learning
  5. d) 3D Printing and Robotics

Answer: c) Artificial Intelligence and Machine Learning

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