Tools of Fiscal Policy

The government has two primary fiscal tools to influence the economy. They are revenue tools and spending tools. Let’s look at each of these tools.

Revenue tools

Revenue tools refer to the taxes collected by the government in various forms. The taxes can be direct or indirect. Direct taxes are taxes levied on the income or wealth individuals and firms. This includes income tax, wealth tax, estate tax, corporate tax, capital gains tax, social security tax, etc.

Indirect taxes are taxes levied on goods and services. This includes sales tax, value added tax, excise duty, etc.

Spending Tools

Spending tools refer to increasing or decreasing government spending/expenditure to influence the economy. Government spending can be in the form of transfer payments, current spending and capital spending.

Current spending includes expenditure on essential goods and services such as health, education, defense, etc.

Capital spending is the public investment in infrastructure such as roads, hospitals, schools, etc.

The above two also include subsidy or direct provision of merit goods and public goods, which would otherwise be underprovided.

Transfer payments are the redistribution of income from taxpayers to those requiring support, for example, unemployment benefits. It also includes interest payments on government debt.

Fiscal policy tools have several advantages.

Spending tools enable services such as defense to benefit everyone in the country and build infrastructure that propels growth. Spending tools also ensure a minimum standard of living for the residents. Subsidies in research and development also help in future economic growth.

Taxes help government in meeting their fiscal needs. By levying high indirect taxes, the government can also discourage use of items such as tobacco, and alcohol.

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Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
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  • Credit Risk Modelling With R
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  • Machine Learning in Finance using Python

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