Prices of 5 marla plots in some of the societies near Islamabad, Pakistan

 

In the case of real estate, it has to be noted that it is going well at this time. During the year 2024, prices have already started moving towards betterment, as the country’s condition is improving. Nevertheless, considering the investment for short-term, it can be considered that you may invest in any housing society available to you. In the case of long-term investment, in which you may need to invest through installments, you may have to go outside of city.

Near Airport (in Islamabad), there can be different areas (societies) in which 5 marla plots can be purchased (considering long term investment). Blue World City is considered as the last society from Rawalpindi and Islamabad. In this area, 5 marla plots are available in the price range of 15 lacs to 18 lacs. In the Overseas block, 7 marla plots are available in the price range of 18 lacs to 20 lacs. After this Capital Smart city comes, in which Overseas East lies, where the prices of 5 marla plots may range from 28 lacs to 32 lacs. In the Faisal Town Phase 2, developed by Chaudhary Abdul Majeed sb, 5 marla plots are available in the price range of 22 lacs to 26 lacs. It has already completed balloting. In the Silver City Housing Society, 5 marla plots are available in the price range of 18 lacs to 25 lacs. Silver City is one of the most recommended areas to purchase plots. In the I-16 sector, 5 marla plots are available in the price range of 25 to 30 lacs.

Otherwise, Airport Green Garden, 5 marla plots are available in the price range of 50 lacs to 70 lacs. In the Top City, 5 marla plots are available in the price range of 70 lacs to 85 lacs. In the Faisal Town Phase 1, 5 marla plots are available in the price range of 80 lacs to 90 lacs.

Source:

Gondal Group of Marketing Islamabad - Top 10 Housing Projects Near Islamabad Airport, Price Comparison, LowCost Plot For Sale in Islamabad - https://www.youtube.com/watch?v=3J_5p4aw1e4

What to do or check while purchasing a plot?

(Source: Pixabay)

It seems good, if you would purchase a shop in a mall or somewhere, rather than purchasing a plot, as it would start giving you rent immediately. Or a house to give you rent or a land, which is on “theka.”

Nevertheless, one of the buying strategies to purchase plots is to purchase several smaller plots rather than purchasing a large land. In this way, your investment will be diversified and risk would be reduced.

It is also important to consult at least three people, three experts.

Do not rush, take your time. For instance, if you would be in hurry, you may purchase a dipped land or a hill, and these are useless in terms of building houses.

Think and work on location. For instance, people may look for the future developments regarding the location, and may purchase a plot. For instance, in Jinnah avenue, Islamabad, one kanal can be sold at about 100 crores.

Reverse commission can be used in terms of purchasing plots. For instance, you may go to the commission agent, and say that I want to purchase a plot at lower prices, and the lower the price of the plot, the more commission I will give to you.

It is also important to check the maintenance charges of the plot. In some cases, maintenance charges can be more than the price. In this case, you may give some amount of your rent (from houses or shops) in maintenance charges.

It is also important to check whether gas, water, and electricity are available.

Also check that the plot is not land locked, which is related to the point that the land is locked and streets or ways in the surrounding are locking the land to reach inside. If there is road with the plot, its resale value increases.

Do research, before purchasing a plot. In this case, you may go to zameen.com or olx, or offices of property agents. You may also ask neighbours. Eventually, do not go with rumours.

Source:

How To Buy A Plot | 10 Tips to buy Property in Pakistan - Azad Chaiwala - https://www.youtube.com/watch?v=Jdg9u0H47lA

A reason behind the decline in prices of plots

(Source: Pixabay.com)

In the real estate market, prices are down for the past several months. In this case, government policies obviously have some effect, the lack of commitment of most of the people involved in new housing projects is also an important factor behind the decline in prices. For instance, developers may say that this is our land; this is the time in which we would complete our work, etc. but they are not fulfilling their commitment. In this case, it seems imperative talk about them. In most of the cases, our marketing companies, for their own profits, don’t talk about them. It would also be important to note that most of the developers talk their money, which they have gotten from clients, in some other projects that result in the decline in the progress of the clients’ work.

Source:

MASS Global Marketing-MGM - Real Estate Fraud Alert | Real Estate Business in Pakistan #Pakistan #RealEstateBusiness - https://www.youtube.com/watch?v=PXlPktPNcjs

Prices in Block E, Phase 8, Bahria Town, Rawalpindi/Islamabad, Pakistan

 

(Source: https://bahriatown.com/)

Bahria Town, Phase 8, has Block E containing different parts, including E1, E2, and E3. E block has mostly the sizes of plots in the range of 10 marlas, though some plots are also available in the size of 1 kanal. The middle ring road side of this area is not only heighted but also has higher prices, such as in the range of 1.25 crores, while the other side from middle ring road has plots in the size range of 90 lacs. During the last 1.5 to 2 years, prices have gone down about 20 lac rupees. Nevertheless, all E1, E2, and E3 areas are possessionable. In the E1, the prices are in the range of 90 lacs to 1 crore. E1 is also a heighted area. In E1, some plots of 6 marlas are also available, the prices of which are in the range of 75 lacs. E2 and E3 have 5 marla plots. In E3, 5 marla plots are available in the price range of 60 lacs.

Source:

Bahria Town Rawalpindi Phase 8 E Block | Price Latest Updates | Advice Associates - Advice Associates - https://www.youtube.com/watch?v=y7f0xpBmp6c

Day 12: A challenge to learn basics of Structural Equation Modeling (SEM) using lavaan and semPlot packages in R

 

During the next 12 days, I will learn and repeat the basics of structural equation modeling (SEM) using lavaan and semPlot packages in R.

You can search my lavaan posts by typing: #UsmanZafarParacha_lavaan , and semPlot posts by typing: #UsmanZafarParacha_semPlot

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During this day, I learned and studied about Confirmatory Factor Analysis (CFA) while implementing a polychoric matrix and use the robust diagonally weighted least squares (RDWLS) method to evaluate the model fit using several fit indices such as RMSEA, CFI, TLI, SRMR, and chi-square/DF. This same thing can also be found in one of the research papers, such as that conducted Almeida et al. (2024).

Initially, I loaded the essential libraries and created supposed data using the following lines of codes:

 

library(lavaan)

library(semPlot)

library(psych)

 

set.seed(123)  # For reproducibility

n <- 200  # Number of participants

 

# Simulate ordinal data (Likert scale: 1 to 5)

item1 <- sample(1:5, n, replace = TRUE)

item2 <- sample(1:5, n, replace = TRUE)

item3 <- sample(1:5, n, replace = TRUE)

item4 <- sample(1:5, n, replace = TRUE)

item5 <- sample(1:5, n, replace = TRUE)

 

# Create a data frame

data <- data.frame(item1, item2, item3, item4, item5)

 

Then, using the psych package, the polychoric correlation matrix was determined:

 

polychoric_matrix <- polychoric(data)$rho

 

The CFA model was specified:

 

cfa_model <- '

  Factor1 =~ item1 + item2 + item3

  Factor2 =~ item4 + item5

'

 

fit <- cfa(cfa_model, sample.cov = polychoric_matrix, sample.nobs = n, estimator = "ML")

 

and the model fit was checked:

 

summary(fit, fit.measures = TRUE, standardized = TRUE)

 

Eventually, the CFA model was visualized:

 

semPaths(fit, what = "std", edge.label.cex = 1.2, layout = "tree", style = "lisrel", rotation = 2)

 

 

Sources:

Almeida, D. M., Santos-de-Araújo, A. D., Júnior, J. M. C. B., Cacere, M., Pontes-Silva, A., Costa, C. P., ... & Bassi-Dibai, D. (2024). The best internal structure of the Diabetes Quality of Life Measure (DQOL) in Brazilian patients. BMC Public Health, 24(1), 580.

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Some of the most important sectors in DHA, Islamabad/Rawalpindi, Pakistan

(Source: https://www.dhai-r.com.pk/)

Considering the popular sectors of DHA Islamabad/Rawalpindi, Sector A, Sector B, Sector C, and Sector K, are among the most popular sectors. People living in these areas can have access to basic facilities, including banking, saloons, parks, schools, etc. Sector K is also near Golf Course. Considering the prices of most of the plots in Sectors A, B, and C, prices may range from 2.5 crores to 4.5 crores. Plots near main boulevard could be somewhat higher, such as near 3.25 crores. On the other hand, plots away from main boulevard and plots in low-lying areas can also be obtained at lower prices. On the other hand, plots in Sector K can be in the range from 3.5 crores to 4.5 crores.

Source:

Property Gupshup - 💥MOST WANTED sectors in DHA Islamabad Rawalpindi | Property Gupshup - https://www.youtube.com/watch?v=tFVtnk-XpWM

Day 11: A challenge to learn basics of Structural Equation Modeling (SEM) using lavaan and semPlot packages in R

 During the next 12 days, I will learn and repeat the basics of structural equation modeling (SEM) using lavaan and semPlot packages in R.

You can search my lavaan posts by typing: #UsmanZafarParacha_lavaan , and semPlot posts by typing: #UsmanZafarParacha_semPlot

=============

During this day, I loaded lavaan and semPlot, and defined the SEM model, as follows:

# Load the packages

library(lavaan)

library(semPlot)

 

# Define the SEM model

model <- '

  # Direct effect

  productivity ~ management + job_satisfaction + workplace

 

  # Indirect effect

  job_satisfaction ~ management

'

 

Then, a supposed data was developed, as follows:

# Simulate a dataset with the relevant variables

set.seed(123)  # For reproducibility

 

n <- 200  # Number of observations

 

# Simulate random variables for the model

management <- rnorm(n, mean = 5, sd = 2)  # Management style

job_satisfaction <- 0.5 * management + rnorm(n, mean = 0, sd = 1)  # Job satisfaction

workplace <- rnorm(n, mean = 4, sd = 1.5)  # Workplace environment

productivity <- 0.3 * management + 0.4 * job_satisfaction + 0.5 * workplace + rnorm(n, mean = 0, sd = 1)  # Productivity

 

# Combine into a data frame

data <- data.frame(management, job_satisfaction, workplace, productivity)

 

# Inspect the data

head(data)

 

Then, lavaan was used to fit the SEM model, as follows:

 

# Fit the model

fit <- sem(model, data = data)

 

# Display the summary of the SEM results

summary(fit, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE)

 

Eventually, the model is visualized using the semPlot package, as follows:

# Visualize the SEM model

semPaths(fit, what = "std", layout = "tree", edge.label.cex = 1.2,

         style = "ram", nCharNodes = 0, curvePivot = TRUE)

 

Source:

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