The Rise of Electric Vehicles: Paving the Way for a Sustainable Future

Summary

The automotive industry has changed dramatically with the move to electric vehicles (EVs), which is motivated by the pressing need to cut back on fossil fuels and greenhouse gas emissions. EVs have many benefits over conventional internal combustion engine (ICE) vehicles. They run on energy produced by fuel cells or rechargeable batteries. Notably, they have zero tailpipe emissions and are less expensive to operate, making them a desirable option for legislators and consumers. Furthermore, especially in crowded urban areas, their quieter functioning helps to lower noise and air pollution. This analysis outlines the current growth path of EV industries and existing policies to support this growth. 

History and Technological Progress
The first electric vehicle prototypes were created alongside the development of gasoline engines in the 19th century. However, the prevalence of ICE vehicles and battery technology constraints prevented EVs from becoming widely accepted. The performance and convenience of gasoline-powered cars dominated the electric vehicle market for many of the 20th century.
The late 20th century was a watershed for electric vehicles (EVs) due to developments in lithium-ion battery technology, heightened environmental consciousness, and pro-EV legislation. These advancements made EVs more feasible and consumer-friendly by enabling notable gains in battery efficiency, range, and charging infrastructure.
Businesses such as Tesla have been instrumental in transforming the electric vehicle market. In addition to capturing the premium EV market, Tesla has increased rivalry among established manufacturers by concentrating on high-performance electric vehicles and investing in charging infrastructure. The company's success has disproved the long-held belief that EVs are less capable than their gasoline-powered counterparts by proving that electric vehicles can provide both performance and sustainability.
Global EV Market
As of 2020, over 10 million electric vehicles were on the road worldwide, with battery-electric models propelling the market's growth. The worldwide EV market is dominated by various manufacturers, each helping to advance electric mobility. With distinct business plans and target markets, major competitors include Tesla (USA), BYD (China), Tata Motors (India), and Hyundai (South Korea).

 

Number of Electrical Vehicles Sales Across World (2019-2023)

SOURCE: https://www.statista.com/outlook/mmo/electric-vehicles/worldwide#unit-sales

Growth Rate

For the growth rate of the data from 2019-20 to 2023-24, we will calculate the annual compound growth rate (CAGR) for each category and the total. CAGR is useful for showing a consistent growth rate over a period.
The formula for calculating CAGR:
CAGR = [( Ending Value/Starting Value ) 1/Years]-1.
Starting Value: 2019-20
 Ending Value: 2023-24
 Years: 4
Here are the annual compound growth rates (CAGR) for Electric and Hybrid Vehicles over the 4 years (2019-20 to 2023-24):
Electric Vehicles: 53.60% per year
Hybrid Vehicles: 64.36% per year
Total: 56.57% per year
 This shows that Hybrid Vehicles are growing slightly faster than Electric Vehicles during this period, with both showing significant growth.

The Indian EV Market

India's demographic advantages—a sizable population and a young labour force—offer a unique chance for the development of electric vehicles. The Indian government has taken several steps to encourage the use of EVs after realizing their potential to support sustainable development.
One of the main initiatives is the [1] Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) scheme. It offers financial incentives to promote EV adoption and lessen reliance on fossil fuels. FAME II, the program's second phase, was launched in 2019 and increased funding for electric buses, two-wheelers, and charging infrastructure.
Notwithstanding the encouraging outlook, the Indian EV sector still confronts many obstacles. To ensure widespread acceptance, better battery technology must be[2] developed, a strong charging infrastructure must be established, and supportive laws must be put in place. The market must also address concerns about the source and disposal of battery raw materials, which may impact the environment.

Number of Electrical Vehicles Sales in India (2019-2023)

SOURCE: https://www.smev.in/statistics

Growth Rate

For the growth rate of the data from 2019-20 to 2023-24, we will calculate the annual compound growth rate (CAGR) for each category and the total. CAGR is useful for showing a consistent growth rate over a period.
The formula for calculating CAGR:
CAGR = [( Ending Value/Starting Value ) 1/Years]-1.
For example: Starting Value: 2019-20, Ending Value: 2023-24, Years: 4
The annual compound growth rates (CAGR) for each category over the 4 years (2019-20 to 2023-24):
2 wheelers: 143.55% per year
3 wheelers: 45.01% per year
4 wheelers: 148.36% per year
Buses: 70.79% per year
Total: 76.36% per year
This shows that four-wheelers and two-wheelers experienced the highest growth rates, followed by buses and the overall total.

Policies Supporting India’s Transition to Electric Vehicles (EVs)

The switch to electric vehicles (EVs) is a crucial part of India's aggressive goals to cut pollution and greenhouse gas emissions. To facilitate the EV transition, the Indian government has implemented several measures to encourage the adoption of EVs, boost production, and construct the infrastructure required for a cleaner, more sustainable transportation system.

FAME Scheme
The Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) program is a key component of India's EV policy framework. Introduced in 2015, the program uses subsidies and incentives to promote the use of EVs and lessen dependency on fossil fuels. The second phase, FAME II, was introduced in 2019, and financial incentives were increased to support charging infrastructure and electric buses, two-wheelers, and three-wheelers.

The scheme allocates around ₹10,000 crore over three years and focuses primarily on supporting public and shared transport electrification.

PLI Scheme for Advanced Chemistry Cells (ACC)
The Production-Linked Incentive (PLI) Scheme for Advanced Chemistry Cells aims to increase EV battery production in India to decrease reliance on imported batteries. The program offers financial assistance to businesses that set up battery production plants, promoting cost-cutting and innovation in EV battery manufacturing—two essentials for accessible and reasonably priced EVs.

PLI Scheme for Advanced Chemistry Cells (ACC)
To increase EV accessibility, the Goods and Services Tax (GST) on EVs was lowered from 12% to 5%, while the GST on conventional vehicles remained at 28%. Furthermore, under Section 80EEB of the Income Tax Act, people can deduct up to ₹1.5 lakh from their income taxes for the interest on loans they take out to buy EVs. These incentives increase EV sales and directly reduce customer expenses.

Observations

Two-wheelers' dominance in the EV market highlights their affordability and convenience for urban commuting.
The rapid growth of three-wheelers suggests their potential for commercial applications like deliveries and public transportation.
The increasing popularity of four-wheelers indicates a shift towards electric personal transportation.
The slower growth of buses could be attributed to factors like higher upfront costs and infrastructure requirements.

Reasons for the boom

Government Incentives: The Indian government has implemented various policies and subsidies to promote EV adoption and make it more affordable for consumers.
Environmental Concerns: Growing awareness about air pollution and climate change has driven demand for cleaner transportation options.
Technological Advancements: Battery technology, charging infrastructure, and vehicle design improvements have made EVs more practical and appealing.
Fuel Price Volatility: Rising fuel prices have made EVs a more cost-effective choice in the long run.

CONCLUSION

To sum up, the emergence of electric vehicles is changing the transportation industry by providing a sustainable substitute for conventional automobiles. EVs are positioned to play a significant role in combating climate change and promoting cleaner air thanks to their advantages for the environment, cost reductions, and technological developments. Electric vehicles can completely change the automobile industry if nations like India adopt electric mobility through encouraging laws and programs. We can create a more sustainable and environmentally friendly future for future generations by encouraging creativity and teamwork.

Sources

https://www.bcg.com/publications/2024/how-electric-two-wheelers-are-rapidly-gaining-popularity

https://assets.kpmg.com/content/dam/kpmg/in/pdf/2020/10/electric-vehicle-mobility-ev-adoption.pdf]

By

Shreyanshu Lamba, B.A. Economics (2022-25), SBSS, MRIIRS
&
Dr. Durairaj Kumarasamy, Associate Prof. and Head DoE, SBSS, MRIIRS

  

Predicting My Students' SGPA: From OLS to Machine Learning

Summary: This article highlights the importance of machine learning algorithms and traditional econometrics models. Using a classic classroom example, this article suggests that a student of economics should use both tools in economic modeling.  

While teaching econometrics, the fundamental challenge we face is to choose the perfect example or data to use while explaining econometrics and the importance of being present in class. Most of the time, I ended up using the classic example of grade points (GPA or SGPA) and how it is affected by attendance, IQ, internal marks, and so on. The example and the method to prove to my students that these factors are crucial for getting a good grade remained the same for the past few years. The mighty ordinary linear least square (OLS) regressions always do their tricks and show that the student will get lower grades if they perform poorly in the internal exams or have less attendance. However, I always questioned whether the OLS is the best model. In most cases, students are in their first year. I cannot teach them non-linear equations, time-varying state space, or any fancy model that may fit the data perfectly.

Figure 1: SGPA and Average Internal Marks of the students of the Department of Economics

An OLS model seems perfect for the data presented in Figure 1. However, the data has a higher dispersion at specific ranges, such as 60 to 70 or 87 to 94, which is a classic case of heteroskedasticity. One can remove these data points and label them outliers, but then the students will question my intention. So, removing data points or applying a complex model is not an option.

If a student who has an average internal mark of 65 approaches me and wants to know the predicted SGPA, I will use OLS to show that, based on the regression result of Table 1, the student will get an average SGPA of 4.9 with a mean squared error (MSE) of 0.93 and r²=0.81. However, as I mentioned, students in this cluster have a higher variation, which means my prediction may be misleading.

Table 1: Simple OLS result of SGPA on Average Internal Marks

Figure 2: OLS prediction of SGPA for the student with 65 average internal marks

In the era of data analytics and machine learning, I should use machine learning techniques to predict my students' SGPAs. One of the basic methods is the K-Nearest Neighbourhood algorithm. The idea is that we can predict the behavior of data by looking at its nearest neighbors. I used 20% of the data for testing and K=8 nearest neighbors to predict the SGPA of the student with 65 average internal marks. The prediction has changed to 5.23 with a mean squared error of 2.0 and r²=0.49, as depicted in Figure 3. I changed the value of K many times, and it remained above the predicted value of OLS.

Figure 3: K- Nearest Neighborhood prediction of SGPA for a student with 65 Average Internal Marks

The data's clustering behavior may still lead to wrong predictions. So, I used the decision tree algorithm, which is more appropriate when neighboring clusters display different patterns or the data has a more complex pattern. Using a basic decision tree algorithm, I predicted that the student with an average of 65 internal marks might get an SGPA of 6.28 with a mean squared error of 2.03 and r²=0.41, which is way above the OLS prediction (figure 4).

Figure 4: Decision tree prediction of SGPA for a student with 65 average internal marks

All three models have strengths and weaknesses; no one can claim that one model is better in all situations. As the literature has mentioned, there is always a trade-off between unbiasedness and standard error. So the investigator should be careful while using these models for forecasting or predicting a variable. Although machine learning algorithms are popular, OLS is a powerful and simple technique with a solid theoretical background. The overall relationship between Internal marks and SGPA or attendance and SGPA is positive and significant as predicted by the OLS. And remember, under all the assumptions of classical linear regression, OLS is still BLUE (Best Linear Unbiased Estimate). 

Please Note: Don’t take this post seriously. Econometrics is just for fun. (All Python codes are available in open sources.)

By

Dr. Akash Kumar Baikar

Assistant Professor, Department of Economics, SBSS, MRIIRS

The Ladder of Happiness Through Macroeconomic Fundamentals or Social Expenditure: A BRICS Perspective

 Summary:

In current geopolitics, the BRICS nations can set new standards for future economic development. This article explores how these countries should progress in their future development paths. Keeping happiness as an objective, this article suggests that social expenditures are much more critical than macroeconomic fundamentals.  

Figure 1: The Ladder of Happiness of BRICS nations from 2014 to 2023

Source: World Bank Open Data, The size of the bubble represents the level of the Cantril Ladder Index of that country in that year

Introduction

The Cantril Ladder, a simple yet effective tool for gauging subjective well-being, poses a straightforward question: "Imagine a ladder with the best possible life at the top step (10) and the worst possible life at the bottom step (0). On which step do you feel you personally stand at this time?"[1] By quantifying subjective experiences, this scale offers valuable insights into individual life satisfaction. While individual well-being is a complex interplay of personal circumstances and psychological factors, macro-level variables can significantly influence happiness. This study delves into the relationship between these broader economic factors and Cantril Ladder scores, focusing specifically on the BRICS nations as they represent a significant portion of the global economy. Understanding the factors that influence the happiness of their citizens is crucial for policymakers and researchers alike.

Our panel data analysis indicates that three key variables—GDP per capita, expenditure on health and education, and the unemployment rate—significantly influence Cantril Ladder scores within the BRICS nations. The following sections delve into the specific impact of each variable. 

Panel data analysis of BRICS countries

Table 1: Random effect regression result of the Cantril Ladder index on macroeconomic and social expenditure variables

	Model-1	Model-2
CPI	-.002 (0.003)	0.0032 (.002)
Log of GDP Per Capita	0.471** (0.189)	1.262*** (0.09)
Unemployment	-0.058*** (0.01)	-0.058*** (0.006)
Health Expenditure (% of GDP)	0.332*** (0.05)
Expenditure on Education (% of GDP)		0.629*** (0.057)
Intercept	-0.083 (1.79)	-8.61*** 0.996

***,**,* represent 1%, 5%, and 10% L.S. respectively, S.E. in the parentheses

As an indicator of wealth distribution, GDP per capita directly and significantly impacts citizens' happiness. As a country's average income rises, so does the general well-being of its people. Our analysis reveals that a 1% boost in GDP per capita leads to a statistically significant increase in the Cantril Ladder score. This suggests that income distribution is important to a country's happiness level.
However, the relationship between income and happiness is not always linear. Studies have shown that while increased income can boost happiness to a certain point, additional wealth may not significantly increase well-being beyond a certain threshold.
Unemployment, a scourge of modern economies, can cast a long shadow over individual well-being. Job loss can lead to a host of negative consequences, including financial insecurity, increased stress, and a diminished sense of purpose. These factors can significantly impact people's perceptions of their lives and, consequently, their Cantril Ladder scores. Our analysis reveals that a 1% increase in the unemployment rate is associated with a statistically significant 0.058 decrease in the Cantril Ladder score. This finding underscores the detrimental impact of unemployment on subjective well-being. Moreover, high unemployment rates can have broader societal implications, such as increased social unrest and political instability, further eroding people's sense of security and overall well-being.
Government investment in education and healthcare is a cornerstone of societal progress. By prioritizing these sectors, nations can foster long-term economic growth, enhance social development, and improve the overall well-being of their citizens. Our research shows that investing in education and healthcare can significantly boost people's happiness. A 1% increase in health expenditure is linked to a 0.33 increase in the happiness index, while a 1% increase in education expenditure is associated with a 0.629 boost in happiness.

The BRICS: A comparative analysis-  China's sustained economic growth and significant investments in education have contributed to a relatively stable Cantril Ladder score (Figure-1). In contrast, Brazil and Russia have experienced fluctuations in their scores, influenced by economic volatility and political uncertainty. India, despite rapid economic growth, faces challenges related to unemployment and inequality, which can impact its citizens' well-being.
In conclusion, while macroeconomic variables play a significant role in shaping individuals' perceptions of their lives, a holistic approach is necessary to understand the complex interplay between economic conditions and subjective well-being. Policymakers should consider not only economic growth but also social and environmental factors to promote sustainable and equitable development.

R code for the plot: Packages used- dplyr, ggplot2, gganimate

p <- ggplot(data, aes(x = GDPPerCapita, y = HappinessIndex, size = HappinessIndex, color = Country)) +

  geom_point(alpha = 0.7) +

  geom_text(aes(label = Country), vjust = 1.5, hjust = 1.5, size = 3) +

  scale_size(range = c(2, 12)) +

  theme_minimal() +

  labs(

    title = 'BRICS Countries: Happiness Index vs GDP Per Capita',

    x = 'GDP Per Capita',

    y = 'Happiness Index',

    size = 'Happiness Index'

  ) +

  theme(

    plot.title = element_text(hjust = 0.5)

  )

animated_plot <- p + transition_time(Year) +

  labs(subtitle = 'Year: {frame_time}')

References:

[1] OECD Guidelines on Measuring Subjective Well-being

By

Tisha Virmani

M.A. Economics (2024-26), Department of Economics, SBSS, MRIIRS, Faridabad

External Shocks and India's WPI Inflation

Summary: This article outlines the effects of external shocks and their impact on India's Wholesale Price Index (WPI) inflation. It analyzes the factors and channels contributing to inflation's volatile nature in recent years.

Memes and Their Impacts

Summary: This article emphasises the spread of internet memes in modern times and outlines some of the positive and negative effects of this spread on society.

The Google trend data is used to highlight the speed of the spread of Internet memes.
According to Fobes India, "Bhupendra Jogi meme is one of the most viral memes in India (1)"
Timeline: 10 October 2023 to 10 November 2023

Introduction:

In the 21st century, people are getting addicted to memes. Moreover, GEN-Z use this meme more frequently in their daily lives. Additionally, comparing their current life situation with those trending memes on social media creates chaos. Memes are comical images with bold text illustrating ideas, concepts, relatable incidents, etc. These funny pictorial concepts are getting most of the social attention. The hype of memes is spreading worldwide; according to research, a person spends approximately 108 minutes scrolling memes only. These memes are eye-catching, with amazing pictures of famous personalities, cartoon characters, politicians, etc.

Attention Period for Meme:

Individuals suffered under strict government guidelines, such as lockdowns during the pandemic. At that time, memes played a crucial role in digital communication; it was also noticed that most coronavirus memes went viral because people could relate to them. Those who saw memes of COVID-19 are most likely to suffer less as it affects them psychologically. It was noticed that using memes to cope with worry is common.

Meme As a Modern Culture:

Many research studies show that excessive use of memes in daily life indicates social media addiction. For these reasons, people start procrastinating, becoming lazy, and cutting themselves off from the real world. Even in colleges or corporate sectors, most individuals seem to be scrolling memes on social media during break time. Memes are indirectly dominating modern culture and influencing it badly. They are a powerful tool that can drastically affect a country's youth.

Impacts Of Meme:

Positive Side: Many people earn just by editing macro pictures (MEME) for social media pages. To relieve themselves from their busy schedules, people scroll through memes on social media. Many memes hold very powerful information. It encourages people to seek assistance as well.

Negative Side: Many memes negatively impact the image of a particular person whose memes go viral. A Meme spoils someone’s personality on social media and has a lasting effect. It brings negativity. There is inappropriate exposure of content, and so on.

Conclusion:

In today’s world, people readily accept whatever they see online. Similarly, the vital form of memes is actively loved by people on social media despite their accuracy, which transfers the misinformation to the masses. Excess of anything is too bad; we should rely on anything only after getting the information from the absolute source. To conclude, memes have evolved the nation, and one should be aware of their consequences.

(1) Top 10 Most Searched Memes In 2023 In India, According To Google Trends - Forbes India

(2) The surprising power of internet memes (bbc.com)

By 

Kritika, B.A. Economics (2023-26), Department of Economics, SBSS, MRIIRS, Faridabad.

Palette of Change: Artistic Visions for Viksit Bharat

 

Tanvi and Group

Reet and Group

Manasvi and Group

Kritika and Group

Devanshi and Group

Aastha Gautam and Group

Rise of Real Estate in Gurugram

Summary: The main objective of this study is to analyze the current situation of the real estate market in Gurugram. In this process, This article identifies the strengths and weaknesses of Gurugram’s real estate market. 

Rental price of apartments in and out of the city of Gurugram

Source: Historical Prices in Gurgaon (numbeo.com)

Gurugram, located in the state of Haryana, has emerged as a booming real estate hub in recent years. The real estate industry is the most important sector in the world. In terms of immigration as well as other variables are taken into place. Individuals from all over India migrate to urban centers, large cities, IT industries, etc. One cannot overlook Gurugram when discussing migration. It is a major commercial hub of our economy and it is known as a technological center.

Trends Of Gurugram Property Rates:

When we look into Gurugram property trends there is fast growth and transformation seen in the property market of Gurugram in previous years. Gurugram offers many opportunities for buyers and investors its strategic location, excellent connectivity, and rapid urbanization have contributed to the city’s popularity among homebuyers and investors. Regarding property price trends in Gurugram, several factors influence the market like its corporate sector, multinational companies, business parks, etc. It attracted many professionals searching for their business and housing options. This demand has led to a rise in property prices over time.

Configuration	Approx cost in rs
1 bhk	40 lakh
2 bhk	90 lakh
3 bhk	1.8 crore
4 bhk	3.5 crore

Factors Shaping The Gurugram Property Market:-

1. Infrastructural Development

The rapid infrastructure development in Gurugram is a factor that contributes to the high property rates. This city has all of the major need factors like metro connectivity, roadways & transport, boom IT sector, etc. Also, The city is well-connected to major highways, including the Delhi-Mumbai Expressway, Delhi-Jaipur Expressway, Sohna Road, Dwarka Expressway, etc.

2. Supportive Government Policies

The Haryana government’s pro-development policies and initiatives like RERA have built confidence among homebuyers and investors, resulting in heightened activity in the real estate sector. Also, like tax advantages, relaxed rules have been provided by the government.

3. Business Environment

Gurugram has gained popularity as a business location over the past few years. Many big companies operate and look forward to expansion in the rapidly developing business hub, hence it provides a perfect business environment.

4. Luxury Living

Gurugram’s real estate market is filled with many modern amenities and well-designed properties. Developers are meeting this demand with smart homes and community-centric living spaces and it has fully luxury living, premium projects with world-class amenities, and opulent villas. High-net-worth individuals and NRIs are showing their interest in these exclusive properties.

Categories of properties in Gurugram:
·      Residential property
·      Commercial property
·      Mixed use property
·      Industrial property
·      Specialised property
·      Agricultural property

 Land usage distribution of Gurugram :

Land use	Area ( in hectares )
Residential	16021
Commercial	1616
Industrial	4613
Transport & communication	4428
Public Utilities	608
Public & semi-public	2027
Open spaces	2928
Special zone	114
Defense land	633
Existing town	406
Village	478
Total	33872

Some Popular Real Estate Companies Of Gurugram:-
·      DLF Group
·      Ansals
·      Emaar India
·      Unitech Group
·      Godrej Group
·      Tata Group
·      Ireo Group
·      M3M India
·      Vatika Group
·      ATS Infrastructure Limited
 
Reasons for the Massive Property Rates in Gurugram:

1. Affluent Customer Base

A quarter of India’s billionaires in Gurugram act as their primary or secondary abode. Many MNC employees are also prepared to spend more money on a luxury home in a gated neighborhood. As a result, several developers are developing opulent residential structures with the most modern amenities.

2. Rising Business Hub

Gurugram has its own unique identity as a North Indian IT cluster due to the several MNCs that call this area home. Gurugram is a center for business growth in addition to being a great place to live. However, it is very expensive to purchase or rent a commercial property in gurugram. The cost of commercial property in Gurugram is among the highest in India.

3. Infrastructure Development

Infrastructural development plays a main role in shaping the real estate market of gurugram as it has great connectivity with commercial and residential properties. Also, it has facilities like school, hospital ,mall, transportation, huge lane roads etc.

4. Lifestyle Amenities

Gurugram is known for its luxurious lifestyle amenities, which includes shopping malls, restaurants, entertainment centres etc. The presence of such amenities adds to the quality of life in Gurugram and makes it a great location for homebuyers. Developers are also focusing on providing lifestyle amenities within their residential projects, such as swimming pools, clubhouses, fitness centres etc which increase their profit and property rates in the city.

5. Limited Land Availability

Major reason of high property rates in Gurugram is the limited availability of land for new developments. Gurugram is a fully populated city and there is very little vacant land left for new residential or commercial projects. If developers want to buy land in low rates they has only one option lefts that to shift their project location near gurugram like in dwarka, sohna , noida etc. This will affects the property rates. The limited land availability also leads to an increase in demand for properties in prime locations, which further contributes to the high property rates in the city.

 
Why do People prefer Gurugram property at high rates also?

The rising property demand in Gurugram is boosted by business-class people and working professionals migrating to the city. Many working professionals are readily investing in luxury homes in various gated communities. Hence, several high-end real estate developers are launching luxury commercial and residential projects offering the best amenities and features.

Most Expensive Office Spaces

There are many MNCs based in this area, and it has a distinct identity as the IT Hub. Gurugram plays a major role in several business projects and is one of the most popular places to live and run a business.

Top-Tier Infrastructure

Gurugram has gained popularity among real estate investors since the country’s IT hubs were established in Gurugram after that the region has gained popularity among those wishing to invest in real estate, especially in the residential sector.

Standard of living

As people earn more their expectations are also high. They prefer luxury living according to their status. That’s why they shifted their interest toward Gurugram.

Fact About The Gurugram Housing Market

Housing in Gurugram can often be surprising, with home buyers investing an exorbitant amount for small-sized apartments while spending crores for huge spacious homes. As everyone wants to live in a good place.

Gurugram Contribution In Economy:
·      Cyber City
·      Biotechnology Hub
·      Sporting Complex
·      Melting Pot Of Cultures
·      Educational Hub
·      Shopping Paradise
·      Rapid Urbanisation
·      Food Haven
·      Connectivity
·      Festival Galore
·      Iconic Landmarks
·      Sustainability Initiatives
·      Historical Significance
·      Luxury Living
·      Green Spaces
All the above things contribute to the economy in terms of taxation, money supply, investments, etc. All this leads to an increase in overall GDP.

Gurugram as investment:

Except for building sites in Gurugram, the city's business sector is rising faster. Gurugram's evolving structure, constructing unorthodox office spaces is a certainty, as is their increased demand. Gurugram is a beautiful city to live in, with world-class amenities. The expectation of Gurugram Property Investment will only rise with the city's expanding employment possibilities and expansion. Also, The upcoming Delhi-Mumbai Industrial Corridor and the proposed high-speed railway network are expected to further enhance Gurugram’s connectivity and make it a preferred destination for real estate investment. Gurugram continues to dominate the market for real estate in terms of residential and commercial development. Gurugram is one of the fastest-growing cities in the world, and it attracts the richest of the rich.

Conclusion:

Gurugram’s property market remains in a leading position for real estate investments. The strategic location, great infrastructure, luxuriousness, etc contributed to Gurugram’s real estate market. It has flourished in recent years attracting some of the top real estate companies in India. Each of the companies mentioned above has contributed to this city by offering high-quality projects that meet the aspirations of homebuyers and investors. From an investment perspective, Gurugram is highly attractive. 

R code for the plot: Packages used: library(tidyverse) and library(plotly)

colors <- c('#4AC6B7', '#1972A4', '#965F8A', '#FF7070')

P <- plot_ly(

  price_ani, x = ~Year, y = ~Price,

  frame=~Year,

  color = ~Apartment_type, type = "scatter",

  mode="markers", colors=~colors, size=~`Price`,

  marker = list(symbol = 'circle', sizemode = 'diameter',

                      line = list(width = 2, color = '#FFFFFF'), opacity=0.4)

)

By

Kunal

B.A. (H) Economics  (2023-26), School of Behavioural and Social Science (SBSS), Manav Rachna International Institute of Research and Studies (MRIIRS), Faridabad, Haryana.

  Configuration

Approx cost in rs

1 bhk

 40 lakh

2 bhk

 90 lakh

3 bhk

 1.8 crore

4 bhk

 3.5 crore

Land use

Area ( in hectares )

Residential

16021

Commercial

1616

Industrial

4613

Transport & communication

4428

Public Utilities

608

Public & semi-public

2027

Open spaces

2928

Special zone

114

Defense land

633

Existing town

406

Village 

478

Total

33872