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 Sunde

Description

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

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