Isha Agarwal (no relation to ME blogger!) a graduate student at Cornell Univ has started this intersting blog and hope we get to read some more posts.
In one of the two posts written so far, the author explains the time-series analysis of Indian macro data.
Macro economic time series are known to display trend growth. For example, if we look at a country’s GDP, it rises over time, i.e. it has a trend growth which can be categorized as a long term feature of GDP, however, in the short term we observe that the GDP fluctuates around the deterministic trend. A substantial literature in macro economics deals with the properties of these business cycles and how the government can come up with policies to counter these business cycles – also know as counter cyclical policies. Whether or not such policies are effective in containing the business cycles is a bigger question and there are different schools of thought (Freshwater and saltwater) which feel differently about this issue.
There is a class of models known as RBC (Real Business Cycle) models which addresses questions such as: what causes business cycles, how persistent is the deviation of any time series from its steady state, what accounts for co-movement between various time series(such as consumption and income). RBC model conjectures that business cycle fluctuations are due to real factors (such as shock to technology) as opposed to monetary factors(such as change in money supply/monetary policy). The macro economic course taught in the spring semester at Cornell revolves around RBC theory which also happens to be my area of interest.
In the first lecture of this course I learnt how to extract the cyclical component from any given time series and some stylized facts about GDP, consumption-income ratios, investment-income ratios, their correlations and persistence. In this post I endeavor to conduct the same analysis for Indian data. I take data on GDP and its components from RBI’s website.The first step is to extract the business cycles from the series of GDP. I use annual data from 1950 to 2012 for this analysis.
Nice stuff. Read the post for details.
Though, the graphs could be better as one can hardly detect the difference between original and cyclically/trend adjusted time-series. And then the author could also explain how does one actually detrend all this. It does share a matlab code but a code is a code.
Overall an interesting effort and looking for more such posts..
ME eventually wants to get into posts like these as econ research via papers is getting boring. Idea is to use simple econometrics (an oxymoron!) to convey basic ideas. There is hardly any dedicated website to doing economic research and helping people do research using basic tools. Especially these time series analysis where we fail to look at basics and keep projecting left, right and centre..
But as ME is still not there yet, so will have to wait. ME hopes to get into this space quickly..Till then hope Isha helps us..
Mostly Economics 
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