Understanding India’s Economic Sectors and Growth Drivers

Posted by on Aug 27, 2025 in Business Statistics | 0 comments

Economic Concepts and Growth

Short Notes:

  • Service-Led Growth: Economic expansion driven by the service sector (finance, IT, tourism, healthcare), contributing significantly to GDP.
  • Primary Sector: Extraction and production of raw materials (agriculture, mining, fishing).
  • Secondary Sector: Processing and manufacturing of raw materials into finished goods (manufacturing, construction).
  • Tertiary Sector: Provision of services to individuals and businesses (healthcare, education, finance, tourism).
  • Base Year:
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India’s Constitutional Amendments for Local Governance & Reforms

Posted by on Aug 14, 2025 in Business Statistics | 0 comments

The 73rd Constitutional Amendment Act of 1992 is a historic and transformative legislation that gave constitutional status to Panchayati Raj Institutions (PRIs) in India. It marked a major step towards decentralization and grassroots democracy by making village-level governance more structured, democratic, and accountable.

The Act gave effect to Article 40 of the Directive Principles of State Policy, which directed the State to organize village panchayats and endow them with necessary powers. By

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Panel Data Models: Fixed & Random Effects, Hausman Test

Posted by on Jun 21, 2025 in Business Statistics | 0 comments

Panel Data Models: Key Concepts & Estimators

1. General Panel Data Model

The general panel data model is expressed as:

$y_{it} = \alpha_i + X_{it}’\beta + \epsilon_{it}$

  • $\alpha_i$: Represents the individual-specific, time-invariant effect.

  • Goal: Estimate $\beta$ despite unobserved heterogeneity.

2. Fixed Effects (FE) Estimator

Methods:

  • LSDV (Least Squares Dummy Variables): Not feasible for large $N$.

  • Within Estimator:

$y_{it} – \bar{y}_i = (X_{it} – \bar{X}_i)\beta + (\epsilon_{it} – \bar{\epsilon}_i)

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Statistical Analysis of Production Models and Time Series Forecasting

Posted by on Feb 28, 2025 in Business Statistics | 0 comments

Statistical Analysis of Production Models

a) Significance parameters: Divide the model (CAN, BARRELS) using a dummy variable CAN: assign a value of 1 or 0. Barrel: βo + β2(prodtotal – 100)+ β4(prodtotal-100)2 ; Can: (βo + β1) + (β2 + β3)(prdototal – 100) + (β4 + β5)(prodtotal – 100)2 + U

β0 = Expected barrel production when total production is 100hl, β1 = Expected difference between can production and barrel production when total is 100, β2 = Expected increase of barrel production when

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