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Dealing with Interpretability Issues in Predicting Firm Growth: Factor Analysis Approach

100%

Bilandžić A. , Marina J. , Šarlija N.

tom 7

nr 2

23-34

Background: Alongside the theoretical progress made in understanding the factors that influence firm growth, many methodological challenges are yet to be overcome. Authors point to the notion of interpretability of growth prediction models as an important prerequisite for further advancement of the field as well as enhancement of models’ practical values. Objectives: The objective of this study is to demonstrate the application of factor analysis for the purpose of increasing overall interpretability of the logistic regression model. The comprehensive nature of the growth phenomenon implies propensity of input data to be mutually correlated. In such situations, growth prediction models can demonstrate adequate predictability and accuracy, but still lack the clarity and theoretical soundness in their structure. Methods/Approach: The paper juxtaposes two prediction models: the first one is built using solely the logistic regression procedure, while the second one includes factor analysis prior to development of a logistic regression model. Results: Factor analysis enables researchers to mitigate inconsistencies and misalignments with a theoretical background in growth prediction models. Conclusions: Incorporating factor analysis as a step preceding the building of a regression model allows researchers to lessen model interpretability issues and create a model that is easier to understand, explain and apply in real-life business situations.

Methods of forecasting VAT revenues for the state budget of Ukraine

100%

Okseniuk O. , Ivan Franko National University of Lviv

Ekonomia Międzynarodowa

2015

tom 010

VAT is the main indirect tax in Ukraine, among other countries, providing one of the largest items of state budget revenues. The presence of the VAT refund procedure and the need to cover public spending with the revenues from VAT administration require that an effective method of planning and forecasting VAT revenues for the new fiscal year be used. The purpose of the article was to analyze the effectiveness of two methods of forecasting of VAT revenues, such as the moving average method and the method of correlation and regression. This was done by analysing the effectiveness of forecasts made for previous years and comparing them with actual data to make the forecast of VAT revenues using these methods for 2014–2016 years and identifying the main causes of problems in the forecasting process. The results show that the forecasts based on two methods (correlation and regression analysis and double moving average) are sufficiently accurate. After making certain adjustments, these methods can be used at the national level.