Forecasting the collection of the state value added tax (ICMS) in Santa Catarina: the general to specific approach in regression analysis
Keywords:
Forecasting, general to specific, value added taxesAbstract
In this paper was verified the possibility of improving the monthly forecasts of the Value Added Tax on Merchandise and Services (ICMS) collected by the State of Santa Catarina, Brazil. Dynamic regression will be used based on the concepts of cointegration and error correction utilizing the general to specific approach suggested by the London School of Economics (LSE). Different data series were selected and analyzed for the final model industry profit, consumption of electric energy and other energy sources, and cement, and business consultations to the Credit Service Protection Agency (SPC). In the process of the choice of the variables, Granger’s tests of causality and the analysis of long-run equations were used. The results obtained were very satisfactory for forecasts both inside and outside the sample period, indicating that the use of this model by the Budget Department of the State of Santa Catarina will provide more suitable values for the decision making process and improvement in budget planning.
Downloads
Downloads
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors must have a written permission from any third-party materials used in the article, such as figures and graphics. The permission must explicitly allow authors to use the materials. The permission should be submitted with the article, as a supplementary file.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after BJO&PM publishes it (See The Effect of Open Access).