TRAIN or no TRAIN a forecasted scenario examining tax measures - Chan, Kyle Terrence (School of Economics, University of the Philippines Diliman, 2019)
This paper compares the Comprehensive tax reform program, also known as TRAIN law as Republic act No. 10963, to a forecasted scenario, using regression models with ARIMA errors, where the TRAIN law did not occur and continued on with the same tax regime to the years prior to gain an insight on the effectivity of the tax reform in attaining additional revenues. The regression models with ARIMA errors used for forecasting is achieved by comparing target revenues projected ex ante by policy makers to actual revenues earned. The study will also look into the tax buoyancies, a measure of total response of tax revenue to its corresponding tax base, and tax elasticities, which measures total response of tax revenue to the base while holding discretionary changes constant, of the previous regime from 1998_2017 to evaluate its performance. Tax elasticities play an important role in constructing accurate forecasting and policy recommendations. The purpose of the research is to justify a need for a tax reform and to determine whether the tax reform was successful in raising additional revenues. Our findings reveal that the tax reforms introduced in the TRAIN law has increased tax revenue collections in the Philippines.