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  • Home
  • Knowledge Tank
    • Modules
      • Data envelopment analysis or DEA
      • Analyse with STATA
      • Analysing data with Nvivo
      • Analysing data with SPSS
      • Research Methodology
      • Text data analysis with Hamlet II
      • Supervised learning
      • Mendeley to organise references
      • Comprehensive meta-analysis
    • Insights
      • The two faces of FDI
      • Epidemiology of healthcare
      • The volatility of the real estate industry
    • Expert advice
      • Research selection
      • Writing and reporting
      • Literature review
      • Research analysis
    • Industries
      • Banking and finance
      • Microfinance
      • Power and energy
      • Pharmaceutical
      • AYUSH
  • Services
    • Research analysis
      • Quantitative
      • Qualitative
      • Situation
      • Secondary
    • Historical analytics
      • Segmentation
      • Trend analysis
      • Data mining
      • Data modelling
    • Research paper
      • Literature survey
      • Research methodology
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Establishing a relationship between FDI and air pollution in India

By Rashmi Sajwan and Saptarshi Basu Roy Choudhury on November 4, 2018 No Comments

In India, in the last two decades, the inflow of FDI has grown significantly. Similarly, its environmental pollution has also been rising since 1991 due to an increase in economic activity. This article empirically investigates the impact of FDI on air pollution in India.

 environmental cost of fdi, fdi environment relation, the two faces of fdi

How to test normality in STATA?

By Rashmi Sajwan and Priya Chetty on October 31, 2018 1 Comment

Time series data requires some diagnostic tests in order to check the properties of the independent variables. This is called ‘normality’. This article explains how to perform normality test in STATA.

 STATA for data analysis, time series analysis

How to test time series multicollinearity in STATA?

By Rashmi Sajwan and Saptarshi Basu Roy Choudhury on October 24, 2018 No Comments

The problem of multicollinearity arises when one explanatory variable in a multiple regression model highly correlates with one or more than one of other explanatory variables. It is a problem because it underestimates the statistical significance of an explanatory variable (Allen, 1997).

 STATA for data analysis

How to test time series autocorrelation in STATA?

By Rashmi Sajwan and Priya Chetty on October 22, 2018 1 Comment

This article shows a testing serial correlation of errors or time series autocorrelation in STATA. Autocorrelation problem arises when error terms in a regression model correlate over time or are dependent on each other.

 STATA for data analysis, time series analysis, trend analysis

How to perform Granger causality test in STATA?

By Rashmi Sajwan and Priya Chetty on October 16, 2018 1 Comment

Applying Granger causality test in addition to cointegration test like Vector Autoregression (VAR) helps detect the direction of causality. It also helps to identify which variable acts as a determining factor for another variable. This article shows how to apply Granger causality test in STATA.

 STATA for data analysis, time series analysis

How to perform Heteroscedasticity test in STATA for time series data?

By Rashmi Sajwan and Priya Chetty on October 16, 2018 4 Comments

Heteroskedastic means “differing variance” which comes from the Greek word “hetero” (‘different’) and “skedasis” (‘dispersion’). It refers to the variance of the error terms in a regression model in an independent variable.

 STATA for data analysis, time series analysis

Slacks based measure or SBM analysis in DEA

By Rashmi Sajwan and Avishek Majumder on September 19, 2018 No Comments

Slacks based measure or SBM analsysis is a non-radial model to solve the problem in the “additive model” developed by Charnes, Cooper, & Rhodes in 1978. This model can discriminate between efficient and inefficient Decision-Making Units (DMU).

 DEA module, measuring returns to scale with dea
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