In the first
part of this report, I provided a brief summary of the people's mandate in
the 2018 Telangana assembly elections together with a historical comparison of
the verdict.
The present post is related to the methodology of this
report covering both the data & analytical models. Please note this section
is likely to be of a technical nature and probably boring to those looking for
political content. On the other hand, data enthusiasts with little interest in
politics may find it interesting.
Raw data
As per my usual practice all my data is from the public
domain. Data of the previous elections (1978 onwards) is from the Election Commission of India (ECI) while the
present election data is extracted from the details published by Chief Electoral Officer's (CEO) Telangana.
Subject to certain IPR terms, I can provide details of my
calculations to any reader interested for any reason including verifying my
numbers or further analysis.
Party affiliations
ECI & CEO recognize party affiliations of individual
candidates as per the prescribed formal process including individual's
declaration and party nominations (B-form). The official list shows 1,940
"candidates" contesting on behalf of 94 "parties".
This throws up the following challenges for analysts
including too many database elements distracting from serious analysis. For
example, a group calling themselves "Samaikyandhra Parirakshana Samithi"
put up three candidates who secured a grand total of 1,824 votes between them!
To reduce this clutter, I reclassified the raw party affiliation
data into sixteen primary database elements (TRS, INC, TDP, TJS, CPI, BJP, MIM, CPM, BLP, MBT, TRS-REB,
INC-REB, SFB, IND, OTH
& NOTA) that I am
treating as "recognized parties".
A small group of individuals ran on an interesting concept of
trying to obtain votes through "symbol subterfuge" e.g. on the symbol
of a truck that can be confusing to voters intending to vote for the TRS's
"car symbol". Some of these innovative folks enjoyed a reasonable
success in an interesting quirk! I am grouping these candidates under SFB (for
the hitherto unheard of party called Samajwadi Forward Bloc that most of these
chose to represent).
As explained earlier, I am treating the NOTA button in each
constituency as an individual candidate and the overall NOTA category as a
"party" in my analysis.
These sixteen "parties" are further regrouped to
six formations: TRS, UPA, BJP, MIM (Majlis), BLF & OTH (others). BLF did
not trouble the statisticians beyond the initial cursory glance.
Please also note "OTH" is a residual category that
changes with the context. For example, when analyzing victory margins I group
the lone BJP winner among OTH.
Rebel trouble
Formal accreditation as used by the Election Commission may
actually be misleading in several cases e.g. when a known party rebel candidate
fights on the B-form issued by an entity with no local presence. my solution to
this second problem is to rebrand individual candidates denied tickets with the
"correct rebel status".
As everyone knows by now, two rebels made it to the current
assembly. Korukanti Chander Patel, the # 23 Ramagundam champion, officially ran
as the nominee of All India Forward Bloc (AIFB) while Lavudya Ramulu, triumphant from
# 115 Wyra was labeled an independent. My methodology puts these winners down
respectively as TRS & Congress rebels.
Though I tried to be fair to party rebels, I am forced to
give a pass to two lone rebels (one each from TDP & BJP) as they secured
under 1.5% votes. With due apologies to these worthy individuals, I prefer to
keep my database clean J
The great Indian party hopping game
I tracked the peculiar Indian game of party hopping in the
months leading up to the elections. My pre-poll Aya Ram Gaya Ram tracker shows
72 individuals who jumped ship in season with 26 of these fighting the
elections (22 on behalf of the new party). Readers interested in the fate of
these individuals are requested to be patient for now.
A couple of interesting sidelights (both treated as Congress
rebels as per the methodology followed):
·
Former MLA Vooke Abbaiah who had the honor of
fighting the past elections on three major party tickets (CPI, TDP & TRS)
defected to Congress just before the elections. Failing to win its B-form, he
filed his nomination as an independent
·
Syed Ibrahim, twice unsuccessful on TRS ticket
earlier, ran as a rebel and ended up unlucky when he was denied the party
nomination in 2014. He subsequently "returned home" but defected to
Congress after being refused the ticket again. Undeterred by Congress too ignoring
his claim, he managed to obtain the B-form of Bahujan Samaj Party (BSP) but lost
a fourth time
Geographic classification
Telangana state as originally formed under article 3
consisted of ten districts. Subsequently certain areas of the Khammam district
(often incorrectly called "Polavaram submergence mandals") were
transferred to AP through an ordinance (ratified later). This geographic
transfer affecting two constituencies (# 118 Aswaraopeta and # 119 Bhadrachalam)
is however not of material significance to our analysis. It may be noted in
passing there was a certain amount of litigation arising out of the related
vote transfer due processes but this need not deter the present exercise.
The only Loksabha constituency impacted by this geography
transfer is Mahabubabad. All other Loksabha constituencies remain
intact.
Post Telangana formation, the erstwhile ten districts were
reorganized into 31 districts. All references to the term "district"
in this report pertain to the old
districts unless explicitly stated otherwise. I did track the polling
variations across the "new districts" if anyone is interested.
The regional variations in Telangana are subject to varying
interpretations as per the analyst's choice. The delineation followed in this
report is outlined below:
·
North covering Adilabad, Nizamabad, Karimnagar, Warangal
districts in full apart from Medak district (excluding # 40 Patancheru included
in Hyderabad below) totaling 53 constituencies
·
Hyderabad covering 24 constituencies of GHMC,
please note four of these are partially
outside GHMC limits but are included in the "Hyderabad region"
for the purpose of this analysis
·
South covering Mahabubnagar & Nalgonda
districts in full apart from apart from 6 constituencies of the Ranga Reddy
district (not counted in Hyderabad above) totaling 32 constituencies
·
Khammam covering 10 constituencies of the Khammam
district. Certain analysts include this in "North" but I believe the
uniqueness of this district deserves to be treated separately
The term "old city" used often with historical
and/or political implications is defined even more vaguely. In this report I
will instead refer to the Hyderabad Loksabha constituency. It may be noted that
# 65 Goshamahal falls under this limit but # 63 Nampalli does not do
so.
Population density classification
The 2001 census data lists 173 census towns each rated
against a four class system in the then united AP. I used this as the basis for
classifying each of the 119 Telangana assembly constituencies by population
density.
·
Urban: all constituencies in Hyderabad region
plus three constituencies with two census towns plus constituencies with a
single class-1 census town
·
Semi-urban: all constituencies with a single
class-2 census town
·
Semi-rural: all constituencies with a single
class-3 or class-4 census town
·
Rural: all other constituencies i.e. without any
census town
Other demographic indicators
Demographic information is difficult to come by in India
and, where available, of suspect quality. The most reliable data is available
only to commercial users (e.g. FMCG businesses) and often amenable only to
custom analysis suitable to the sponsor's field of interest.
In the light of this drawback, an analyst has little choice
but to resort to "guesstimates" based on his own knowledge of the
area. I picked up the following four parameters and studied constituencies
influenced by these factors:
·
Coal mining belt accounting for 10.4% of the
2018 votes
·
Acute agrarian distress symbolized by out
migration, farmer/weaver suicides, bidi industry presence and/or fluorosis
contributing 19.5% to the 2018 turnout
·
Areas (excluding the seats contested by Majlis)
with significant Muslim population coming to 19.3% of the 2018 votes
·
Constituencies with significant settler
population working out around 9.4% of the 2018 votes
This classification (and indeed even the choice of
parameters) is purely subjective. In addition, the broad "swing"
pertains to the constituency, not the target demography. The fact that TRS
gained 6.4% votes in the "coal belt" does not show which way the miners
voted.
The word "settler" refers to Andhras who migrated
to the Hyderabad state before 1956 and gave up links to their former homes.
Contrary to the belief of several media observers, the number of settlers in
the Hyderabad region is quite low. More recent Andhra migrants living in the
Hyderabad region are not settlers. I
did not treat them as a separate electoral category as I am anyway reviewing
Hyderabad patterns vis-à-vis 2014 and 2016.
Please also note that the classifications are not mutually
exclusive. For example as # 12 Bodhan is home both to sizable Muslim
and settler population, it has been included in both segments.
There are certain demographic indicators (e.g. tank
irrigated areas & Lambada strongholds) that I could not deconstruct. I
would be thankful to anyone who can provide information on such factors.
Linguistic minorities do contribute a good chunk of votes in
Telangana but do not constitute a coherent voting block. This is also true of
non-Lambada tribals. I did not therefore study the constituencies with
significant populations of these demographic groups.
Vote preference & "swing"
bands
Readers familiar with American politics will probably know
Prof. Andrew S. Tanenbaum as a veteran observer-cum-analyst of the local
political landscape. The Tanenbaum
model uses seven color coded vote preference bands ranging from
"strongly Democratic" through "strongly GOP".
As our present context differs a good deal from the strong
bipolar two party system prevalent system I am using a somewhat different and
simplified system:
·
Vote share of >= 50.0% is deemed to be
unbeatable (green)
·
Vote advantage and/or gain ("swing")
of >= 5.0% is considered excellent (green)
·
Vote share of <= 10.0% is treated as below threshold
(red)
·
Vote disadvantage and/or loss ("negative
swing") of >= 5.0% is deemed to be terrible (red)
My unpublished (but available on request subject to my own
terms) spreadsheet thus shows the TRS vote share (50.4%) and vote advantage (19.7%)
in Mahabubnagar district in green. On the other hand though TRS 2014 vote share
in Khammam district is red at 9.5%, the vote gain (31.1%) is green. I did not
use the color coding ("conditional formatting") in the blog posts to
avoid jarring eyeballs.
