qurterizing time-series (a case study, government oil revenues, consumer price index and liquidity)

due to the high costs of collecting the quarterize or seasonal statistical information and the need of econometricians for modeleny and short analysis, the national statistical institutes decided to obtain quarterize time series as indirect methods of the short-term dynamics of the annual data. in this article, two alternative approaches based on related indicators and pure mathematics has been introduced and then after temporal disaggregation of government oil revenues, consumer price index and liquidity, the approaches compared to each other. the empirical results indicated that boot, feibes and lisman methods deliverd the better results for two series (government oil revenues and consumer price index), whereas chow and lin approach is more approprate for liquidity, based on mse and r2 criteria. also this paper shows that the best choice approach for temporal disaggregation of economic time series is not always possible.