The Predictive Grey Forecasting Approach for Measuring Tax Collection

Taxation serves as a vital lifeline for government revenue, directly contributing to national development and the welfare of its citizens. Ensuring the efficiency and effectiveness of the tax collection process is essential for maintaining a sustainable economic framework. This study investigates (a) trends and patterns of direct tax collection, (b) the cost of tax collection, (c) the proportion of direct tax in total tax collection, and (d) the tax-to-GDP ratio in India. By utilizing a novel grey forecasting model (GM (1,1)), this study attempted to predict the future trends of India’s direct tax collections, through which it aims to provide a concurrent and accurate future outlook on tax revenue, ensuring resources are optimally allocated for the country’s growth. Results revealed that direct tax collection has consistently increased in the past two decades, and the proportion of direct tax in total tax has also improved significantly. On the contrary, the cost of tax collection has decreased regularly, indicating the efficiency of tax collection. Forecasting shows that the collection from direct tax is expected to reach INR 30.67 trillion in 2029–30, constituting around 54.41% of the total tax, leaving behind collections from indirect tax at a total of INR 25.70 trillion. Such findings offer insights that could enhance revenue management strategies with policy decisions relevant to economists, government, and other stakeholders to understand trends and the efficiency of direct tax collection in India.

Authors

Institutions

Publication Details

Journal
Journal of risk and financial management
Published
2024-12-13
DOI
https://doi.org/10.3390/jrfm17120558
Citations
4
Primary Topic
Grey System Theory Applications
Type
article
Field-Weighted Citation Impact
1.96
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Predictive Grey Forecasting Approach for Measuring Tax Collection

Pitresh Kaushik, Mohsen Brahmi, Shubham Kakran, Pooja Kansra
4 citations
Journal of risk and financial management
Grey System Theory Applications
1.96
article

The Predictive Grey Forecasting Approach for Measuring Tax Collection

Pitresh Kaushik, Mohsen Brahmi, Shubham Kakran, Pooja Kansra
article en
4 citations

Abstract

Taxation serves as a vital lifeline for government revenue, directly contributing to national development and the welfare of its citizens. Ensuring the efficiency and effectiveness of the tax collection process is essential for maintaining a sustainable economic framework. This study investigates (a) trends and patterns of direct tax collection, (b) the cost of tax collection, (c) the proportion of direct tax in total tax collection, and (d) the tax-to-GDP ratio in India. By utilizing a novel grey forecasting model (GM (1,1)), this study attempted to predict the future trends of India’s direct tax collections, through which it aims to provide a concurrent and accurate future outlook on tax revenue, ensuring resources are optimally allocated for the country’s growth. Results revealed that direct tax collection has consistently increased in the past two decades, and the proportion of direct tax in total tax has also improved significantly. On the contrary, the cost of tax collection has decreased regularly, indicating the efficiency of tax collection. Forecasting shows that the collection from direct tax is expected to reach INR 30.67 trillion in 2029–30, constituting around 54.41% of the total tax, leaving behind collections from indirect tax at a total of INR 25.70 trillion. Such findings offer insights that could enhance revenue management strategies with policy decisions relevant to economists, government, and other stakeholders to understand trends and the efficiency of direct tax collection in India.

Journal of risk and financial managementVol. 17(12)
Lovely Professional University (IN), University of Sfax (TN), Doon University (IN)
Openalex Percentile: Top 12%
Grey System Theory Applications
1.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.