A Data-Driven Baseline for Understanding Indian
Development
Written by Dr. Seshadri Kumar, 11 February, 2016
Copyright ©
Dr. Seshadri Kumar. All Rights Reserved.
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Disclaimer: All the opinions expressed in this article are
the opinions of Dr. Seshadri Kumar alone and should not be construed to mean
the opinions of any other person or organization, unless explicitly stated
otherwise in the article.
Disclaimer 2: Every attempt has been made to ensure the accuracy of the data presented herein. However, it is always possible that some errors may have crept into the work, despite the most diligent efforts of the author. The author accepts the responsibility for any errors found and humbly requests those who may find these errors to inform him via comments and the same shall be rectified if found to be in error.
Update, 18 February 2016: 21 new indicators were added to increase the number of key indicators studied from 38 to 59. The new indicators added were the corruption score and the ease of doing business indices. More indicators will be added later, so this is a living document. I invite people to point me to more data sources to make this an even more valuable citizen resource.
Disclaimer 2: Every attempt has been made to ensure the accuracy of the data presented herein. However, it is always possible that some errors may have crept into the work, despite the most diligent efforts of the author. The author accepts the responsibility for any errors found and humbly requests those who may find these errors to inform him via comments and the same shall be rectified if found to be in error.
Update, 18 February 2016: 21 new indicators were added to increase the number of key indicators studied from 38 to 59. The new indicators added were the corruption score and the ease of doing business indices. More indicators will be added later, so this is a living document. I invite people to point me to more data sources to make this an even more valuable citizen resource.
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Abstract
The word “development”
has been bandied around quite freely in Indian economic and political discourse
recently, without much understanding of what it really entails. This study
attempts to provide a quantitative baseline for development in India by
identifying key development indicators and then studying how these indicators
are changing in India, based on data from three past governments at the centre in
India: the NDA government of 1999-2004 and the UPA governments of 2004-2009 and 2009-2014.
Development is a
complex concept comprising a number of macroeconomic, financial, infrastructural,
health, social, environmental, and innovation dimensions. This study explores 59 key indicators comprising all these dimensions. These are: GDP, GNI per capita
(PPP), exports, FDI, GCF, total reserves, percentage of non-performing loans, corruption score, bank capital-to-assets ratio (CAR), inflation, unemployment rate, electricity consumption, energy consumption, highways, railways, container traffic, internet
penetration, mobile telephony, transport investment with private participation, telecom investment with private participation, energy
investment with private participation, ratio of industry and services to agriculture, population growth rate, sanitation, clean water, life expectancy, under-5 mortality,
measles immunization, DPT immunization, gender parity, secondary school enrolment,
adolescent fertility, total fertility, forest cover, protected area percentage,
trademark applications, patent applications, new businesses registered, hi-technology exports,
The achievements and
shortcomings of the two administrations with respect to these development
indicators should give pause to those who are interested in the future of
Indian development and should help them define more sharply what is meant by
development in a quantitative way and how much can realistically be achieved.
Introduction
For the last 3 years, probably the most overused word in
Indian political and economic discussions has been the word “development” – or its
Hindi equivalent, “vikas.”
This topic took centre stage starting in 2013, when the
election campaign for the 2014 general elections began. The present government,
led by Mr. Narendra Modi,
came to power in a landslide victory in May 2014 mainly on the promise of much
better development than the previous ruling dispensation. Even after that
victory, the topic of development has been the focus of much debate.
But better development relative to what?
The term development has been very loosely defined. Economic
development encompasses many dimensions – macroeconomic, financial, infrastructural,
environmental, social, health, financial, and scientific. Political parties, in
their posturing, have often chosen to constrain the debate in narrow ways so as
to benefit themselves. For example, the BJP
has often talked about its government’s achievements in the road sector,
while the UPA has focused on malnutrition and declines in the Human
Development Index (HDI).
How can one talk of more
development unless one understands what the current state of the nation’s
development is? What are the different facets of development and what is the
country’s current status on each of these aspects? And, finally, what kind of
growth has historically taken place in the country in the sphere of
development? These questions have to be answered if we need to critically
evaluate the performance of an elected government with regard to economic and social
development.
Developing a baseline on the key components of development
and understanding the historical data on development is the focus of this
article. I have focused on what has been achieved in the three governments
preceding the current one – the UPA governments of 2004-2009 and 2009-2014 and the NDA
government of 1999-2004. Once we have a clear idea of what the current and
past development indicators of India are, we will be in a position to engage in
a more meaningful and intelligent debate on what "greater" development to expect from the
present government.
To do this, I have used the most reliable data I could find
– that from the World Bank.
The World Bank has data on an astonishing number of parameters from every
country, which it gleans from various sources, chiefly the countries’ own
statistics offices, such as the Ministry of Statistics, Planning,
and Implementation (MOSPI) in India. Since the website of the World Bank is
much easier to navigate than the website of MOSPI, I have chosen to take data
from the World Bank website.
To this, I have also added the corruption scores from Transparency International, and the Ease of Doing Business Indices available from the World Bank Group Ease of Doing Business website.
I am aware that several important indicators are still missing from this work. They will be added at a later stage. These include important indicators such as balance of trade and current account deficit.
Two caveats need to be mentioned here, and the reader should use caution here. One, many subjects are state subjects, and so improvements in those indicators may be driven more by the actions of a state government rather than the central government. But both governments may have a role. Even if the execution is in the hands of the state government, funding may flow from the centre. It is not easy for me to separate the contributions of the state and centre in these indicators. The reader is advised to excercise due discretion. Two, all governments benefit from the good or bad actions of past governments. The effects of certain policies of an elected government may manifest themselves only when it leaves office. So it may seem unfair to some that the credit for an improvement goes to the government presently in power rather than to the previous government. However, I believe this is a zero-sum game. Succinctly put, you win some, you lose some. For instance, the present government might suffer from the lower growth rates of the last two years of the UPA-2 government, but it is already benefiting from the enormous investments made by the previous government in the transparency infrastructure, specifically the Aadhar program and the Jan Dhan Yojana, both of which were started during UPA-2. Similarly, all governments after the PV Narasimha Rao government have benefited from their liberalization policies. So this is part of political life. You get credit for achievements that happen during your rule.
To this, I have also added the corruption scores from Transparency International, and the Ease of Doing Business Indices available from the World Bank Group Ease of Doing Business website.
I am aware that several important indicators are still missing from this work. They will be added at a later stage. These include important indicators such as balance of trade and current account deficit.
Two caveats need to be mentioned here, and the reader should use caution here. One, many subjects are state subjects, and so improvements in those indicators may be driven more by the actions of a state government rather than the central government. But both governments may have a role. Even if the execution is in the hands of the state government, funding may flow from the centre. It is not easy for me to separate the contributions of the state and centre in these indicators. The reader is advised to excercise due discretion. Two, all governments benefit from the good or bad actions of past governments. The effects of certain policies of an elected government may manifest themselves only when it leaves office. So it may seem unfair to some that the credit for an improvement goes to the government presently in power rather than to the previous government. However, I believe this is a zero-sum game. Succinctly put, you win some, you lose some. For instance, the present government might suffer from the lower growth rates of the last two years of the UPA-2 government, but it is already benefiting from the enormous investments made by the previous government in the transparency infrastructure, specifically the Aadhar program and the Jan Dhan Yojana, both of which were started during UPA-2. Similarly, all governments after the PV Narasimha Rao government have benefited from their liberalization policies. So this is part of political life. You get credit for achievements that happen during your rule.
Metrics/Indicators
I have categorized the various development indicators into
the following buckets:
·
Economic and Financial
o
Gross Domestic
Product (GDP) Growth Rate
o
Gross National
Income (GNI) (Based on Purchasing Power
Parity - PPP) Per Capita
o
Exports
o
Foreign Direct
Investment (FDI)
o
Inflation
o
Unemployment Rate
o Corruption Score
·
Infrastructural
o
Electricity Consumption
o
Energy Consumption
o
Highways
o
Railways
o
Container Traffic
o
Internet Penetration
o
Mobile Telephony
o
Transport Investment with Private Participation
o
Telecom Investment with Private Participation
o
Energy Investment with Private Participation
o
Ratio of Industry and Services, Combined, to
Agriculture
·
Health
o
Population Growth Rate
o
Sanitation
o
Clean Water
o
Life Expectancy
o
Under-5 Mortality
o
Immunization – Measles
o
Immunization – DPT
·
Social
o
Gender Parity
o
Secondary School Enrolment
o
Adolescent
Fertility
o
Total Fertility
·
Environmental
o
Forest Cover
o
Protected Areas
· Innovation and Science
o Trademark Applications
o Patent Applications
o New Businesses Registered
o High-technology Exports
·
Ease of Doing Business Metrics
o
Starting a Business – DTF
o
Paying Taxes – DTF
o
Electricity Availability – DTF
o
Registering Property – DTF
o
Getting Credit – DTF
o
Protecting Minority Investors – DTF
o
Trading Across Borders – DTF
o
Resolving Insolvency – DTF
o
Time Needed to Start a Business
o
Cost of Starting a Business
o
Minimum Paid-In Capital for a Business
o
Cost of Construction Permits
o
Cost of Obtaining Electricity
o
Time Needed to Register Property
o
Cost of Registering Property
o
Strength of Legal Rights
o
Credit Bureau Coverage
o
Number of Tax Payments Per Year
o
Time Spent on Paying Taxes
o
Total Tax Rate
· The World Bank site has many more metrics, but data on several
of them is incomplete and too scarce to make a comparison. Also, data on highway
construction was not available. I had to use data that I had previously
collected (see here)
to get the data – and it is not as fine-grained as the rest of the data, so the
reader may see a difference in the way it is presented.
Methodology
The results shown in the next section are based on data for all
the above metrics from the last three governments: NDA (1999-2004) and UPA (2004-2009 and 2009-2014).
Understanding this data should serve to help understand what may be possible in
the future. Averages
shown are multi-year averages over the period of rule of the NDA (5-year) or
UPA (both 5-year and 10-year), to the extent that data is available (some data was not
available beyond 2012, for example).
Some data are presented only as averages because there is no
logical reason to expect them to increase each year. In other categories, especially health and social indices, it makes
logical sense to compare overall percentage improvement over the duration of the
rule of the party, because those indices are expected to improve with time.
Similarly, growth rates may vary from year to year depending on various
factors, including international market conditions, oil prices, and the like,
so it makes most sense to look at long-term averages. FDI is also something
that can, technically speaking, vary from year to year; however, it is an
accepted national objective to increase the level of FDI in the Indian economy,
and so it makes sense to track its percentage growth rate.
Also, in some cases, increases are shown rather than or in
addition to percentage increases because the starting value may have little to
do with the final value. One example of a case where I have
preferred to use increases rather than percentages is in mobile telephony: here
the starting number for the NDA government was so low that percentage
improvements would lead to drastically high and meaningless percentage
increases – mobile telephony was only starting then.
In any case, the raw numbers are there in case someone
wishes to interpret them differently. I have chosen the method that seemed to me most
appropriate for any given data set.
Some of the data will favour the party which ruled most recently.
For example mobile phone and internet penetration will favour the UPA because
the technology has greatly developed in the last 15 years.
One other thing to keep in mind while interpreting the data
is that the UPA had 10 years of rule whereas the NDA had only 5 years. So in some
categories where a long-term improvement trend is expected, it would be
reasonable to expect that the UPA’s overall improvement rate should be roughly double
that of the NDA. For this reason, the individual statistics for UPA-1 and UPA-2 are also provided.
Another fact worth noting is that improving health and social metrics from a higher base is more difficult than improving them from a lower base. So, for example, the UPA and NDA rates of improvement of access to clean water are comparable; however, the UPA’s achievement is greater owing to starting at a higher base.
Another fact worth noting is that improving health and social metrics from a higher base is more difficult than improving them from a lower base. So, for example, the UPA and NDA rates of improvement of access to clean water are comparable; however, the UPA’s achievement is greater owing to starting at a higher base.
It is notable that on many of the social metrics, despite
starting at a higher base, the UPA’s performance has been impressive. For
example, on Under-5 mortality, the UPA’s improvement is 36% compared to the NDA’s
15%. Similarly, the UPA seems to have shown remarkable effort in last-mile
immunization efforts, as its 28% improvement in DPT immunization relative to
the NDA’s 9% shows.
Some people have wondered if it might be better to show the data as a continuous timeline rather than in 5-year periods. My rationale for showing the data graphically in this format is twofold: One, it clearly highlights the improvement (or decline) in each regime, and two, when you cover a 15-year period, financial data cannot be presented in raw format because of inflation - I would need to convert all my figures into PPP (Purchasing Power Parity) numbers, which was more trouble than I was willing to go through right now.
Some people have wondered if it might be better to show the data as a continuous timeline rather than in 5-year periods. My rationale for showing the data graphically in this format is twofold: One, it clearly highlights the improvement (or decline) in each regime, and two, when you cover a 15-year period, financial data cannot be presented in raw format because of inflation - I would need to convert all my figures into PPP (Purchasing Power Parity) numbers, which was more trouble than I was willing to go through right now.
Summarized Results
Economic and
Financial Metrics
·
GDP:
·
GNI Per-Capita Based on PPP (USD):
The GNI is different from GDP in that it accounts for all income, including income generated abroad. The figures reflect purchasing-power parity (PPP) - essentially, based not on just the exchange rate but on what money can actually buy.
·
Total Exports (Billion USD):
·
FDI (Billion USD):
·
Average Gross Capital Formation (GCF):
The GCF measures how much of a country's income is invested in generating new fixed assets instead of just being saved. This is important for a developing country like India.
·
Total Reserves (Billion USD):
Non-Performing Loans (% of Total Loans):
A Non-Performing Loan is a loan that is given by a bank and not repaid for a variety of reasons, such as the business that borrowed the money failing. Often there is an element of corruption involved, as the bank manager may know in advance that this is a bogus business. A high percentage of non-performing loans means the bank is susceptible to collapse and is bad for a country's economy.
Bank Capital-to-Assets Ratio (CAR):
The CAR is the ratio of a bank's capital to its risk. A high value means that the bank can absorb a certain amount of loss without collapsing. The higher the CAR value, the more stable the economy and the safer consumers are in depositing their money in the bank. This, in turn, enables the bank to lend money to businesses to boost growth. Note that some approximations had to be made in getting the above figures, since data were not available for 1999, 2004, 2005, and 2006.
Inflation Rate:
Inflation clearly rose significantly in UPA-1 after being low for all of the NDA years, and then came down in UPA-2.
Unemployment Rate:
The unemployment rate came down during the UPA years because of the tremendous growth of the economy.
Corruption Score:
Transparency International annually compiles a corruption score based on several aspects, measured by several surveys, for all countries. The score is between 0 and 100, with 100 representing no corruption and 0 representing complete corruption.
·
Per-Capita Electricity Consumption (kWh):
Per-Capita Energy Consumption (kg of Oil Equivalent):
High per-capita electricity usage and energy usage are desirable in a developing country like India because they indicate that the country is getting more industrialized and modernized. Electricity demand is important because of both rural electrification and industrial electricity use, and energy consumption in terms of fuel is also important as an indicator of industrialization. For the energy consumption table, data were not available in the World Bank database for 2013 and 2014, so the actual figures for UPA-2 might be better.
·
Total Length of Highways, Km (data from this
study):
Highways are a crucial part of infrastructure development, as are railways. Highways are extremely important because of their ability to transport containers, and railways are needed for really large-scale freight transport.
·
Total Length of Railway Lines (km):
·
Total Container Port Traffic (Measured in Million 20-Feet Units)
Container port traffic is affected both by the quality and capacity of sea-ports as well as the downstream infrastrucure of highways.
·
Internet Penetration (Number of Connections Per 100 People):
·
Mobile Telephony (Number of Subscriptions Per 100 People):
The telecom revolution happened during the UPA years - both UPA-1 and UPA-2. This was an important part of development, as it allowed the nation to leapfrog over the limitation of conventional phone lines. The internet boom has happened mainly during UPA-2.
·
Transport Investment With Private
Participation (in Billion USD):
·
Telecom Investment with Private
Participation (in Billion USD):
·
Energy Investment with Private
Partnership (in Billion USD):
These three are measures of privatization in key infrastructure areas. The UPA-1 government seems to have done outstanding work, but privatization in infrastructure suffered heavily during UPA-2. Privatization is necessary because it brings funds to infrastructure projects through debt and equity and allows faster growth in infrastructure. This allows the government to develop more infrastructure than it could with tax revenues and cesses alone.
Industry and Services, Combined, as % of GDP:
This is an important metric for a developing country, especially a traditionally agrarian economy like India. There are three main sectors of any economy: agriculture, industry, and services. The conventional wisdom is that the share of agriculture in the nation's economy needs to go down and the share of the industry and services sector should rise for the country to become a developed country. For instance, the USA's share of agriculture in GDP is around 1.4% of GDP; the corresponding figure in the UK is 0.7%; in Russia it is 4.2%; in Italy it is 2.2%; and in France it is 1.7%. The remaining share is that of industry and services. India's combined share of industry and services should aim to be close to 90-95%; we are still far away from that, but it is improving. Clearly, the data show that industrialization was most rapid during the NDA years. While the UPA had a higher base to start with, the gap to close was (and is) still quite large, so they could have done more in this regard.
Health Metrics:
·
Population Growth Rate (%):
The population growth rate in India has been steadily decreasing for a few decades now, and the numbers are near constant across all governments. This is because population control measures such as family planning education that were started decades ago have been continued steadily by successive governments.
· Sanitation (% of Population With Access to Better Sanitation):
As can be seen, improvements in sanitation have been happening at a steady rate over the years, but the absolute numbers are abysmal. Even at the end of UPA-2, only 40% had access to clean sanitation. It remains to be seen how much the present government's "Swacch Bharat" initiative can remedy this situation.
·
Clean Water (% of Population With Access to a Clean Water Source):
Even though the absolute increases seem about the same for all the three governments, the achievement is greater for the latest government, because achieving the same absolute increase at a higher base is more difficult (harder to access deeper rural areas, etc.) This is especially true for the clean water figures as the numbers are approaching 100%.
·
Life Expectancy (Years at Birth):
·
Under-5 Mortality (Per 1000 Children):
·
Measles Immunization (% of Children Aged 12-23
Months):
·
DPT Immunization (% of Children Aged 12-23
Months):
Most of the health-related metrics are constant across governments, because they are the result of long-term public health policies, such as vaccination, that have continued unabated across administrations.
Social Metrics:
·
Gender Parity Index (Ratio of Girls to Boys in
Primary and Secondary School):
Although the NDA government's performance seems much better on the basis of percentage increases, it should be noted that the ratio was already 0.9 by the start of the UPA government and they did not have much room to improve - the ideal of near 1 was reached during the first UPA administration itself. Also note that data were not available for 2004, 2013, and 2014.
·
Secondary School Enrolment (% of Children
Enrolled):
Again, the data were not available for 2013 and 2014, so data from 2012 was used to calculate the % increase and the end value. Hence the figures for UPA-2 and the overall UPA improvements might be understated.
·
Adolescent Fertility Rate (Births Per 1000 Women
Aged 15-19):
·
Total Fertility Rate (Births Per Woman):
The same continuous improvement story continues in these health/social metrics. For total fertility, too, as before, data was not available for 2014, so the numbers for UPA-2 might be below actual values.
Environmental
Metrics:
· Forest Cover (Total Area, sq. km.):
Data were not available for 2013 and 2014.
·
Protected Areas (% of Total Area):
It is difficult to comment on these environmental metrics. Increasing forest cover is not easy in a developing nation with constant demand on land for housing. Creating protected areas is an important part of environmental conservation, and creating new sanctuaries is getting progressively more difficult.
Innovation and Technology Metrics:
· Number of Trademark Applications, Annual:
· Number of Patent Applications, Annual:
· Number of New Businesses Registered:
In both these metrics of innovation, the UPA-1 government has an outstanding record. Data for both these categories were not available for 2014, so 2013 data was used as the final point.
There was no data on this metric for the NDA years. But the pace really seems to have increased in UPA-2.
·
Average Hi-Tech Exports (% of Total Manufactured
Exports):
Clearly, the percentage of high-tech exports has been increasing with time, with the UPA-2 government having the best figures. One key reason is the continuing influx of software companies into India, which now has a momentum of its own.
Ease of Doing Business Metrics
The Ease of Doing Business website ranks countries in their ease of doing business using a number of metrics, many of which will be discussed here. These metrics are only available for the UPA-1 and UPA-2 years; data for the NDA years are not available. Ease of doing business is measured by various aspects, such as time needed to obtain permissions, cost of obtaining permissions, number of taxes filed, time spent on filing taxes, and so on. Broadly, they are grouped into the following heads: Starting a Business, Construction Permits, Obtaining Electricity, Paying Taxes, Registering Property, Getting Credit, Protecting Minority Investors, Trading Across Borders, and Resolving Insolvency.
For each metric, individual sub-metrics are shown, and an overall Distance-To-Frontier (DTF) is also calculated in a weighted manner. The DTF concept is a weighted metric that measures how close a particular economy is to the best in all economies. It is rated on a 0-100 scale, with 100 representing the best performance of that metric in any economy, and 0 the worst (furthest from the frontier). Below, DTF metrics for several ease of business indicators are shown. It should be noted that these figures are specific to the city of Mumbai. The World Bank Group started with Mumbai and later added Delhi to their list of cities, but the most comprehensive data is only available for Mumbai, the financial capital of India.
It should be kept in mind that many of these metrics are affected by both central and state rules and requirements. Permits needed to start a business might need a lot of paperwork at the state and city level as well as central permits. Paying taxes might be more of a central limitation, while trading across borders is clearly a central issue. So these must be kept in mind while analyzing these figures. However ease of doing business has been very much in the news lately as it pertains to India, so these figures are important to understand expectations.
DTF: Starting a Business (0-100)
Impressive gains appear to have been made under both UPA regimes.
DTF: Paying Taxes (0-100)
Clearly, ease of paying taxes improved greatly under UPA-2.
DTF: Electricity Availability (0-100)
DTF: Registering Property (0-100)
The UPA-2 administration seems to have been unable to maintain the pace of ease of registering property. There is a strong state government component here as well.
DTF: Getting Credit (0-100)
DTF: Protecting Minority Investors (0-100)
DTF: Trading Across Borders (0-100)
DTF: Resolving Insolvency (0-100)
Time Needed to Start a Business (Days)
The improvement during the UPA-1 administration period in this area seems to have been very impressive. Again, there are many state permits needed for this, so this is a combined center/state achievement.
Cost of Starting a Business (% of Income Per Capita)
Minimum Paid-In Capital For a Business (% of Income Per Capita)
The gains during both UPA administrations is impressive.
Cost of Construction Permits (% of Warehouse Value)
Again, significant improvements during both UPA administrations.
Cost of Obtaining Electricity (% of Income Per Capita)
Significant improvement during UPA-2. No data available for UPA-1 years.
Time Needed to Register Property (Days)
Cost of Registering Property (% of Property Value)
Strength of Legal Rights Index (0 is Worst, 10 is Best)
Significant improvement during UPA-1, no change during UPA-2.
Credit Bureau Coverage (% of Population)
Note that since the starting value for UPA-1 was zero, the next year was taken for the percentage increase. But it is probably more pertinent to look at the absolute increases in the percentage of the population covered under credit scores. The improvement is very good.
Number of Tax Payments Per Year
The real improvement seems to have happened during UPA-2.
Time Spent on Paying Taxes (Days)
The decreases are modest.
Total Tax Rate (% of Profit)
This took a step backward during UPA-1, but significant progress was made in UPA-2. High tax rates suppress innovation and stop new businesses from starting and growing.
In summary, it can be seen that for most indices, significant increases in ease of doing business, with some exceptions, were seen overall across the two UPA administrations. In some cases, the improvment was in UPA-1 and a decline was seen in UPA-2; in some others it was vice versa. There were some indices which saw improvements in both administrations.
Summary
Development as a concept has been given a quantitative basis
by characterizing India’s development using 59 key indices. The performance of
the past three governments has been analysed using these indices. The 2004-2009 UPA government seems to have done better in most of the indices than the other two governments; but there are areas in which the other two governments have also done better. Together, the high watermarks of these three administrations give us an idea of how much development has been possible in India in the past 15 years of governments at the centre completing their terms.
These results are important in setting expectations of the
current government. It is well-known that this government was elected on the
promise of greater development. Until now, what exactly greater development
meant has remained quite vague. It is hoped that this study will give
much-needed clarity to the concept of development in the Indian context and
that citizens of India will now understand what benchmarks the present
government needs to exceed in order to fulfil its promises and take India on a
higher-growth trajectory.
Acknowledgments
I would like to thank my wife, Sandhya, for her valuable inputs and thoughtful and intense discussions which have greatly helped improve the quality of this article. I would also like to thank her for her patience as I worked single-mindedly on this article while she shouldered all family responsibilities single-handedly without complaining. Additionally, I would also like to thank my friend Nilesh Rathi for reading an early draft of this article and for offering valuable suggestions that have greatly improved the article.
Appendix: Graphical Year-By-Year Results
In the previous sections, the summarized results were presented and discussed. To get a more fine-grained idea of the trends in the development indices, these are graphed on a year-by-year basis. The data for all three administrations (NDA, UPA 1, and UPA 2) are shown as a function of the year of their administration. So, for example, Year 1 would correspond to 2000 for the NDA (their first completed year), 2005 for UPA 1, and 2010 for UPA 2.
