Journal of Income and Wealth

Macroeconomic time series often exhibits seasonality pattern due to intra-year variations in climatic, social or other behavioral factors. Characteristics of such seasonality behavior varies according to the nature of the series. However, to understand long run trend or cyclic fluctuation in the series, it is imperative to remove the inherent seasonality of the data, if present in that time series. It has been a practice by various countries to publish seasonally adjusted Quarterly National Accounts (QNA) series and trend-cycle estimates in addition to unadjusted QNA estimates. Although, this is not currently followed in case of India, which publishes the unadjusted estimates along with Year-on-Year (Y-o- Y) growth rates. However, Y-o-Y growth rates may not be suitable to portray short term fluctuations in the event of institutional, climatic or behavioral changes in the economy, such as recently observed COVID Pandemic. It is in this backdrop; the article attempts to explore seasonal adjustment procedure in real Gross Domestic Product (GDP) estimates series. Additionally, this paper examines the pattern of seasonality in real Gross Value Added (GVA), Net Taxes as well as GVA of various sectors including Agriculture, Manufacturing, Construction and Services. Quarter-on-Quarter growth rates computed based on seasonally adjusted time series reflect the current or intra-year picture of the economic progress. X-13 ARIMA-SEATS method has been explored for performing seasonal adjustment of the mentioned macroeconomic data series.