Econometric modeling to predict Tax Revenue

Updated: Feb 27, 2020

Agilytics has created an Econometricic Model to predict Tax revenue. As obvious the governments influence the economy by utilizing fiscal policy. It deals with how the funds are used to meet the needs of the country. As far as the government fund is concerned one of its primary sources of funds are the taxes. Taxes are mandatory payments, ruled by laws. Tax revenue is collected from the whole society with differentiated intensity, inspired by considerations of justice, efficiency and effectiveness. Majority of developing countries are dependent on tax revenue for their economic development and India is one of those.

The Objective of the project was to formulate a mathematical model through regression analysis in order to estimate the Tax Revenue in India given the factors affecting it such as: – [1] GDP (X1) [2] Currency in Circulation (X2) [3] Employment (X3) [4] Personal Disposable Income (X4) [5] Direct Tax (X5) [6] Indirect Tax (X6)

Based upon the OLS regression technique and different correlation tests, we found that Currency in Circulation (CIC) was highly correlated with Personal Disposable Income (PDI), Direct Tax and Indirect Tax. Hence GDP, CIC, Employment were considered for further analysis and PDI, Direct Tax and Indirect Tax were not considered.

We used Auto-Regressive Distributed Lag (ARDL) technique to build the econometric model.

Based on the data analysis through the multiple executions of ardl and associated bound test, we found the co-integration between Tax Revenue, GDP, Employment and CIC. Hence, it can be said that there is a Long-run relationship among these variables.

For more information please feel free to order Jupyter Notebook for this Econometric Model by mailing to

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