Temporal Disaggregation Methods in Flow Variables of Economic Data: Comparison Study

Abstract

Annual Gross Domestic Product (GDP) for Nigeria using observed annual time-series data for the period 1981-2012 was studied. Five different econometric disaggregation techniques, namely the Denton, Denton-Cholette, Chow-Lin-maxlog, Fernandez, and Litterman-maxlog, are used for quarterisation. We made use of quarterly Export and Import as the indicator variables while disaggregating annual into quarterly data. The time series properties of estimated quarterly series were examined using various methods for measuring the accuracy of prediction such as, Theil's Inequality Coefficient, Root Mean Squared Error (RMSE), Absolute Mean Difference (MAD), and Correlation Coefficients. Results obtained showed that export and import are not good indicators for predicting GDP for Nigeria is concerned for the period covered. Denton method proved to be the worst using Mean Absolute Difference (MAD) and Theil's Inequality Coefficient. However, RSME% and Pearson's correlation coefficient gave robust values for Litterman-maxlog, thereby making it the best method of temporal disaggregation of Nigeria GDP.

Forecasting the Emission of Carbon-di-oxide Equivalent in Key Sectors of India Using ARIMA Model

“…Time-series modelling can be done only when the data is of high frequency and Temporal Disaggregation techniques are employed in case of low-frequency data, to convert the series into required high frequency. Several approaches of disaggregation of time series like Sectoral-disaggregation Nain et al, (2017), Temporal disaggregation Ajao et al (2015), MIDAS regression (Guay and Maurin (2015) and Non-Parametric methods Ayodeji (2012) are available in literature, which have been applied on economic series. A literature review suggests that temporal disaggregation technique is a popular and widely used method for economic data.…”