I believe this is your homework-assignment, therefore you are the one who should find the answers.

Thanks Pandelis. It is not an homework. I thought the discussion could put forth some research questions.

Regards

Arun

It does seem like such.

Anyway, what about price level and disposable income in the period examined?

Agricultural products are necessity products. That means that people would continue buying them even if their disposable income is decreasing and the prices increasing. However, manufacturing includes luxury products, on which case consumer demand (and therefore GVA) would go down in case of price increase/income decrease.

Also, there could be supply shocks. Maybe raw materials or fuel prices increased, and again the final product (GVA) decreased.

Thirdly, some times exogenous shocks may cause significant overturns. Look for articles in the news describing events that may had affected manufacturing more (e.g. strikes in the related business, or natural or political disasters in the most industrialized regions).

Also examine: wages. worker productivity.

I would argue a big chunk of this slowdown can be explained by the problems in the banking system. It's true that policy rates have come down but the leg down in lending rates were rather limited and there were problems in the non-bank financial corporations (shadow banks) which seems to have led to some sort of liquidity crunch in the system, despite RBIs liquidity injections.

It is important to look at all the variables and parameters together, to rightly quantify the impact and recovery of different business and sectors in a country.

We a group of mathematicians and statisticians have modeled the impact of different macro economic parameter on the consumption pattern and stock market for different businesses in a country. to predict the growth and recovery path and pace for businesses overall.

Macro economic factors like GDP, unemployment rate, repo rate, etc.. and its impact on economic recovery is critical.

We have built multiple ensemble models to analyze the impact of Pandemic (increase in infection rate, mortality rate, spread, peak) on macroeconomic parameters, which in-turn will impact stocks and commodity sales. Hence used simulations then to predict the impact of different businesses and their recovery pattern at national and market levels.

Used techniques like nowcasting and DSGE

Article 3Ps- Path, Pace and Pattern of Recovery from COVID-19 for Di...

Arun -

The reasoning Pandelis used regarding the difference in line 1, Statement 5, page 7, Agriculture, etc., when compared to Manufacturing, line 3, appears sound, but line 4, Utility Services, still seems strange. The drop in growth, using "Percent Change Over Previous Year" for the same quarters from 2018-2019 to 2019-2020 was about the same for Q2 and substantially worse for Q3 for Utility Services as compared to Manufacturing. Now if these Utility Services were for plants, that would help, but I assume a huge part is residential.

I used to work in Official Energy Statistics, and people often tried to over-interpret small changes that were easily dismissed as within the relative standard errors to be expected. They wanted explanations published as to why numbers changed a small amount that was just noise. However, these numbers do show enough change in growth to make it reasonable to question them. Is there any information published with regard to accuracy? Are revisions sometimes published when data quality issues are discovered?

Cheers - Jim