Results from Census 2011 Household Listing

The results from the houselisting exercise that was conducted as part of the 2011 census have been online for a while now. Most of us know that India’s population is over a billion (1.2 billion to be precise) but some lesser known facts are that the population lives in 244.6 million houses, spread across 0.6 million villages and 7933 towns.

The listing exercise also has collects data on possession of some household assets for communication and transportation. The top 3 modes of communication were: mobile/telephone (63%), television (47%) and radio/transistor (20%), while the top 3 modes of transportation are: bicycle (45%), scooter/moped/motorcycle (21%) and car/jeep/van (5%).

However, the most interesting data point was that 18% of the households do not possess any of the assets i.e. no mobile/telephone, no TV, no radio, no computer, no bicycle nor any vehicle.

The following spreadsheet summarizes the distribution of various household assets:

Click here to view the spreadsheet in a new window/tab.

Prison Statistics India 2010

The National Crime Records Bureau, Ministry of Home Affairs publishes an annual report that details various prison statistics. The report presents “numbers and available capacity of different types of jails, strength and training of jail officials and prison budget and expenditure.” In addition, it also analyses the demographic profile of inmates, distribution of convict and under trial prisoners by offenses and sentences / periods of detention and deaths in jails.

In this blog post, I focus on the occupancy rate in prisons. The occupancy rate is calculated as <inmate population/total capacity*100> and a number over 100 implies overcrowding in prisons. For example, an occupancy rate of 115% means that if the total capacity of all prisons in India was 100 then there were 115 prisoners occupying them in 2010. The following spreadsheet details the occupancy rate in Indian prisons over a decade (2001-2010):

Click here to view spreadsheet in separate tab. (To download the data click on the link and go to “File”> “Download as”)

It’s easy to discern that prisons in India have consistently been overcrowded and while the occupancy rate has marginally declined over the last few years, it is still over 100%.

If you are wondering where these prisons are located, here are some prison maps (sourced from the same report):

For archived reports, click here

Animal Husbandry Statistics

A couple of months ago, Harish Damodaran wrote an article in the Business Line presenting some interesting results from the livestock census. His main finding: farmers prefer to rear buffaloes over cows for production of milk in India. I couldn’t source the numbers cited in the graph but found something else: the last section of the report on ‘Basic Animal Husbandry Statistics’ uses FAOSTAT data for 2010 to rank the world’s top 10 countries in terms of livestock numbers.

India has the highest number of cattle (210.2 m), buffaloes (111.3 m) and goats (150.4 m) in the world. It ranks second in sheep (74 m), fifth in chickens (866 m) and sixth in ducks (26 m). We only just make it to the top 10 list when it comes to total number of camels, but sadly don’t have enough horses to get us there.

Source: FAOSTAT production data 2010, www.faostat.org cited in Basic Animal Husbandry Statistics 2012, p. 131

Click on the following link to download reports:

Basic Animal Husbandry Statistics 2012

Basic Animal Husbandry Statistics 2010

The business of family politics in India

Acemoglu and Robinson, in their new book Why Nations Fail argue that the main difference between successful nations and those that fail is not luck, not culture, not geography, but institutions. The economic and political institutions that a country builds and how they maintain them determine the fate of countries across the world. [For more read their blog: Why Nations Fail.] I want to take off from their argument and look at political parties in India as institutions and how well they are functioning. (This, btw, is a great research topic, as there is little literature on this subject, except for some stuff here and there in newspapers/magazines.)

In this post, I will focus on a narrow aspect and examine dynastic politics. This is also a theme of a new working paper by Mendoza et al who analyze the social and economic effects of political dynasties in Philippines. [For an overview of the findings, see this VoxEU article. The paper has been also discussed by Rupa Subramanya at WSJ India Real Time and Amol Agrawal at Mostly Economics.] To summarize it in a sentence: the key finding is that districts which have dynastic legislator incumbents also have a higher incidence of poverty, suggesting a link between economic inequality and political structure.

One could replicate this study for India and given that 3 out of 10 MPs in India are hereditary the findings could be very interesting. However, in the absence of a dataset that maps district development indicators to parliamentary constituencies, I unable to test this hypothesis. Nevertheless, by combining Patrick French’s dataset (on the biographies and political background of MPs) and ADR’s dataset (on the financial and criminal records of MPs), we can get a closer look at some of the issues. [Side note: to read about crorepati MPs, MPs with criminal records and analysis of Lok Sabha 2009 elections, please read ADR’s main report (check out the maps – they are very good) and this analysis for only Lok Sabha MPs. To read about nepotism and family politics read this.]

Hereditary MPs are 4.5 times wealthier than MPs with no significant political background

Consider table 1 that presents the mean value of total assets (declared by MPs in the affidavits they file along with their nomination papers before the elections), according to political background. The average Indian MP has declared assets worth Rs. 5 crores (Rs. 2 crore movable and Rs. 3 crore immovable assets). Predictably, MPs who have a business background have are on top of the table with an average of Rs. 15 crore of total assets. They are closely followed by MPs from the royal family, who on an average are worth Rs. 14 crore. Ranking third are, to borrow French’s term, “mummy-daddy” MPs worth Rs. 10 crores and right behind them are MPs who were inducted (Rs. 9 crore).

This has to be more than a coincidence, right? You would expect actor-turned-MPs like Jaya Prada, Satabdi Roy, Shatrughan Sinha and cricketer-turned-politician Azharuddin to be rich because of their successful (?) past career, but if you were to take the case of other MPs who were ‘inducted’, like IIT-IIM graduate and successful banker, Prem Das Rai or Shashi Tharoor (India’s most twitter friendly politician) or Annu Tandon (trustee with Mukhesh Ambani’s Reliance group) or US return Madhu Yaskhi and Janardhana Swamy it is hard to not to miss the crucial role of money in politics: all of the above inducted MPs are crorepatis.

On the other hand, the MPs who entered the political area via student politics or RSS route or just the the regular way have only about Rs. 2 crores of total assets, and lie below the national average. Depending on your level of cynicism with the Indian democracy, reactions after looking at these numbers could possibly range from “hmm, interesting” to “so what? tell me something new”.

Hyper-hereditary MPs are the wealthiest of all

Now, let’s look at table 2. If we divide the “mummy-daddy MPs” into hereditary and hyper-hereditary MPs (hyper-hereditary MPs are those who have multiple family connections – you can, loosely speaking, think of them as a proxy for dynastic politics) and run the same analysis, you will see the “mummy-daddy MPs” were masking a crucial distinction. Couple of points:
1. There is a wide difference in the average assets of hyper-hereditary and hereditary MPs: the former is almost twice richer than the latter.
2. More importantly – and this is the result that surprised me – hyper-hereditary MPs are the richest folks in the Lok Sabha and their average total assets is even more than MPs who have a business background!!
3. Another interesting finding: On an average, inducted MPs are richer than hereditary MPs.

Who are these ultra rich, hyper-hereditary MPs, you ask? In descending order, they are: Naveen Jindal, Gaddam Vivekanand, Harsimrat Kaur Badal, Preneet Kaur, Pinaki Misra, Daggubati Purandeswari, Maneka Gandhi, Shruti Choudhry, Dushyant Singh, Varun Gandhi, Sachin Pilot, Ajay Maken, Bharatsinh Madhavsinh Solanki, Salman Khurshid, Ashok Tanwar, Rahul Gandhi, Sandeep Dikshit, Pratik Prakashbapu Patil, Ravneet Singh, Sonia Gandhi, Vijay Bahuguna. Did you also note a common link among these MPs? A significant majority – 16 out of 21 – are part of the Congress.

Clearly, there are a lot of hereditary MPs in the Congress and this coupled with the lack of inter-party democracy speaks volumes about how the institutions of political parties in India are crippling.

Source: ADR dataset and Patrick French (PF) dataset. (Please refer to respective websites for clarifications on the data.)

Note: You may view/download the merged dataset in google doc here. It is likely that the formatting was disturbed when converting the spreadsheet from excel to google doc format.  You may download the original merged data set in excel format from here. Small clarification: while it is true that an analysis based on the ADR dataset will not represent the true picture, but given these are affidavits we are talking about and that there is no incentive for any candidate to overstate their assets, we can consider the declaration of assets as a lower bound and so the results based on the data are only going to be biased downwards.

Documentation: If you are performing the merging of PF’s and ADR’s dataset, be warned that they don’t  have a strict one-to-one correspondence because name of constituencies are spelled differently. If you are referring to the merged dataset, please refer to ‘Merge (MASTER)’ sheet as it takes care of these issues. Data from PF is highlighted in blue and data sourced from ADR is highlighted in green. Merged (MASTER) contains information for all 545 MPs and information that is missing is highlighted in yellow. During analysis, 3 MPs were dropped because their assets and liabilities information was not available. This new dataset is available under ‘Merge (coded)’ sheet. Please refer to the codelist for questions on the codes. The MPs who were dropped are: Raj Babbar (ADR’s dataset and the ECI website have Akhilesh Yadav’s affidavits in place of Raj Babber’s), Charles Dias and Ingrid Mcleod. (The latter two are nominated Anglo-Indians and again corresponding information was not available in their case). I tried to verify the merged dataset by comparing summary stats from it to this ADR report [link is now broken]. The data for the party matches up perfectly, but there is some discrepancy when comparing average assets of MPs according to states. I verified the list of constituencies in PF’s data with ECI’s data and it matches well. Since ADR’s dataset does not contain states, my guess is there may be a coding issue at their end.