Tax Revenue Forecasting Using ARIMA and VAR Models and the Implications for Fiscal Policy
Published: 24 June 2024| Version 1 | DOI: 10.17632/874t6tv3t8.1
Contributor:
Tafirenyika SundeDescription
Data and Data Sources Variable Measurement Data Source Tax revenue (TR) Total tax revenue (% GDP) IMF GFS, WBDI, ZIMRA GDP growth (GDPGROWTH) Proxy for economic development WBDI Private consumption expenditure (PCE) Private consumption expenditure (% GDP) WBDI Share of agriculture in GDP (AGRIC) Agriculture sector (% GDP) WBDI Inflation (INFL) Consumer Price Index (proxy of inflation) UNCTAD Trade openness (OPP) Exports and imports (% GDP) WBI Shadow Economy (SECO) Dynamic general equilibrium model-based (DGE) estimates of informal output (% of official GDP) WB Informal Economy Statistics
Files
Steps to reproduce
Unit root tests ARIMA models and VAR Models Granger Causality tests Model Efficiency
Institutions
Namibia University of Science and Technology
Categories
Economics, Econometrics, Relation of Taxation, Subsidies, and Revenue, Fiscal Policy, Forecasting Model