According to “A Better Real Estate Philippines” (Abrep) led by ABREP President Anthony Leuterio, the Chamber of Real Estate Builders Associations, the National Real Estate Association, the Real Estate Brokers Association of the Philippines, the Organization of Socialized and Economic Housing Developers of the Philippines and the Subdivision and Housing Developers Association have their own specific positions on proposed amendments to Resa and have united in the push for legislative change.
Abrep is a movement that seeks to promote inclusivity and the use of technology in the industry, the petition aims to formally identify what ABREP calls the “anti-poor, anti-Pinoy, and anti-technology” provisions of RESA.
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The Russian government has implemented the first phase of a new information (IT) system portal that promises to improve the efficiency and productivity of their decision-making processes that leads to business regulations.
This new IT portal comprises functionalities that allows for: (1) internal groups to have face-to-face meetings over the internet, (2) some aspects of planning, (3) tracking progress of the development of business regulation, (4) tracking project approvals, (5) find and analysing documents – parsing for duplicative work and (6) voting during project meetings.
The system is built on algorithms that relies a lot of on advanced data analytics and machine-learning and this is to help to speed up the entire regulation-making process. It was reported that this IT portal allowed for such work to continue even during the pandemic.
Although the system was to designed to improve internal processes, the future phases would comprise modules that includes the private sector business entities too.
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The Indonesia government recently announced a joint initiative with the United Nations Development Programme (UNDP) to adopt the circular economy model for their country. This initiative is expected to bridge the gap between the public and private sector in policy matters and should create new businesses and job opportunities within their economy.
“A Circular economy model is key to achieving zero pollution and a toxic free environment as Indonesia embarks on an industrial and service-based economy in the next decade. The Indonesian Government is pleased to welcome this much-needed initiative which will ease the country’s transition away from a resource-based economy,”
– Mr. Monoarfa, Minister of National Development Planning
The industry sector comprised the largest share in the Indonesia’s GDP, followed by services. Just the industry sector alone made up about 45.7% of their GDP. This workforce is primarily trained to extract raw materials from the primary sector and convert these materials into end-user products. As highlighted by their Minister, Indonesia is currently trying to transit away from a resource-based economy with the circular economy model. Implementing the circular economy will affect this sizeable workforce and they’ll definitely require a smooth transition to even out the ruffles. The transition phases should ideally be designed such that it fits well with their elections periods too.
First of all, the circular economy should be able to bring ecological benefits to their eco-system through preservation of resource, reusing and recycling waste, and converting them into useful products once again. This would reduce the negative ecological impacts to their environment. Secondly, the implementation would be able to create new jobs that might be more sustainable than those involved in raw materials extraction.
An early transition should be beneficial. In the extreme case that Indonesia runs out of natural resources, a part of their workforce would already be trained in the reusing and recycling of waste materials. When it happens, they would be well-positioned to find employment for their young and growing population. Those who are already equipped with the required skills, could serve as anchor points to train and transform the remaining workforce. Job creations should be in the areas of eco-activities, repairs, leasing and used goods.
A successful transition would require close cooperation between the public and the private sector. The key natural resources of Indonesia include silver, coal, fertile soil, natural gas, petroleum, gold, bauxite, tin, copper, timber, and nickel. Plus, it is important to note that the Indonesia is a one of the leading exporters of tin and thermal coal in the world. In addition, we also observe that the mining industry in the country makes up 11.9% of its GDP. This means that the private sector is very entrenched in the industry sector therefore a well-balanced policy must be in place to help its private sector in ironing out the risk. That is a very huge challenge.
I think we could expect the government to work through the banks to incentivise this transition, which might come in the forms of facilitating, lending or subsidising loans to businesses that are seeking to transform their business models, or to those that are creating or incubating startups in the circular and/or social economy.
Source: Statistics Indonesia
If you observe the above chart, you would observe that the Indonesia government was able to grow their labour force participation rate slightly every year prior to the Covid19 pandemic. It was largely around the same rate and there weren’t much breakthrough. The circular economy model might be able to help the government to achieve new breakthroughs. In the meantime, it is expected that the region would need a lot of assistance in the area of data analytics, engineering, consulting, training, capacity building and technology transfer, in order to move towards their sustainability and economic transformation goals.
Already, the UNDP facilitated a workshop that focused on five areas of circular economy in Indonesia, namely food & beverage, textiles, construction, wholesale and retail trade (plastics) and electronics.
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The partnership between the award-winning property developer Blue Horizon Developments and SolidBlock, a portfolio company of BuiltUp Ventures, the leading PropTech venture capital firm investing in some of Israel’s most innovative startups, marks the first real estate securities token offering (STO) and the first real estate project to raise money on the blockchain in Thailand…
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The Philippine real estate industry is poised for a soft recovery this year, buoyed primarily by the continued expansion of the industrial and logistics sectors.
Amid the COVID-19 pandemic last year, these two sectors were found to be the most stable asset classes given the increased e-commerce penetration and demand for warehouses, distribution centers and cold storage facilities…
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The Indonesia government announced that they would be raising financing through their State Sharia Securities (SBSN) to finance the development of their country. The initiative was announced by Bappenas J. Rizal Primana, Deputy for Facilities and Infrastructure of the Ministry of PPN at the Infrastructure Project Financing Policy Forum through SBSN Year 2021.
A total of Rp27.58 trillion has been allocated for financing infrastructure projects, a reduced target of about -15% compared to what was committed in 2020. The reduced target was indicative of their cautious approach to the persisting effects from the Covid19 pandemic
It is expected that the government would be able to hit their targets for 2021 despite the Covid19 pandemic. Based on their performance in 2020, their Ministry of Finance claimed that they were able to achieve 90.96% of the project financing target thereby reaching their initial target value of Rp32.48 Trillion, However, due to the Covid19 pandemic, allocation for the 2020 SBSN projects were shaved down to Rp18.16 Trillion which is about 44% of the initial figure.
The breakdown of the allocation for the projects is as follow:
Achieving 90.96% of the project financing initial target through the SBSN, is a strong vote to the confidence in the SBSN instruments. In 2020, the Indonesia central bank lowered the borrowing cost five times, cutting the main rate by a cumulative 125bps, in an attempt to support the economy after Covid19 hit, as such it is estimated that the interest rates of the SBSN instruments could be priced the same or lower as compared to previous years.
Apart from this, the government has also confirmed that they are in the final stage of the plan to relocate the capital city to Penajam Paser Utara Regency and Kutai Kartanegara Regency in East Kalimantan.
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As part of the Indonesia’s strategy to improve the competitiveness of their Micro, Small and Medium Enterprises (MSME), the government developing a National Strategy for the Digital Economy with the Indonesian FinTech Association (AFTECH). The AFTECH is an association for FinTech industry players in Indonesia.
We would expect to see the collaboration to focus on creating and expanding the education curriculum related to the digital financial services industry and technology, with the main aim to restore the Indonesia economy, increase financial inclusion, increase the and improve people’s welfare.
It is estimated that Indonesia has great digital economic potential due to a large population (270.20 million people), high number of smartphone ownership (estimated to reach 81.87 million users in 2020) and sufficiently high internet penetration (53.7%). With this, AFTECH would work with the Indonesia government to support the digitalisation of their MSMEs through innovations in digital payments, online loans, aggregators, credit scoring, financial planning, insurance technology, online KYC and project financing.
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A lot of functions are already available with the base installation of R and they are usually used for numeric calculations, statistical analyses, plotting and visualisations. These functions can be used immediately and do not require you to load any libraries. However, there are times that you might need to use more specialised techniques in your assessment and the tool sets are contained within packages (also referred to as libraries). There are a number of packages that are included with the base distribution of R and you will need to load them before you can begin to use them. In order to know what is available in your R, you would have to use the following function.
#In this example, I will try to call up a page detailing the installed packages within the R.
R> installed.packages(priority="base")
Package LibPath Version Priority
base "base" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
compiler "compiler" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
datasets "datasets" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
graphics "graphics" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
grDevices "grDevices" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
grid "grid" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
methods "methods" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
parallel "parallel" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
splines "splines" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
stats "stats" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
stats4 "stats4" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
tcltk "tcltk" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
tools "tools" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
utils "utils" "C:/Program Files/R/R-4.0.3/library" "4.0.3" "base"
Depends Imports LinkingTo
base NA NA NA
compiler NA NA NA
datasets NA NA NA
graphics NA "grDevices" NA
grDevices NA NA NA
grid NA "grDevices, utils" NA
methods NA "utils, stats" NA
parallel NA "tools, compiler" NA
splines NA "graphics, stats" NA
stats NA "utils, grDevices, graphics" NA
stats4 NA "graphics, methods, stats" NA
tcltk NA "utils" NA
tools NA NA NA
utils NA NA NA
Suggests Enhances
base "methods" NA
compiler NA NA
datasets NA NA
graphics NA NA
grDevices "KernSmooth" NA
grid "lattice" NA
methods "codetools" NA
parallel "methods" "snow, nws, Rmpi"
splines "Matrix, methods" NA
stats "MASS, Matrix, SuppDists, methods, stats4" NA
stats4 NA NA
tcltk NA NA
tools "codetools, methods, xml2, curl, commonmark" NA
utils "methods, xml2, commonmark" NA
License License_is_FOSS License_restricts_use OS_type
base "Part of R 4.0.3" NA NA NA
compiler "Part of R 4.0.3" NA NA NA
datasets "Part of R 4.0.3" NA NA NA
graphics "Part of R 4.0.3" NA NA NA
grDevices "Part of R 4.0.3" NA NA NA
grid "Part of R 4.0.3" NA NA NA
methods "Part of R 4.0.3" NA NA NA
parallel "Part of R 4.0.3" NA NA NA
splines "Part of R 4.0.3" NA NA NA
stats "Part of R 4.0.3" NA NA NA
stats4 "Part of R 4.0.3" NA NA NA
tcltk "Part of R 4.0.3" NA NA NA
tools "Part of R 4.0.3" NA NA NA
utils "Part of R 4.0.3" NA NA NA
MD5sum NeedsCompilation Built
base NA NA "4.0.3"
compiler NA NA "4.0.3"
datasets NA NA "4.0.3"
graphics NA "yes" "4.0.3"
grDevices NA "yes" "4.0.3"
grid NA "yes" "4.0.3"
methods NA "yes" "4.0.3"
parallel NA "yes" "4.0.3"
splines NA "yes" "4.0.3"
stats NA "yes" "4.0.3"
stats4 NA NA "4.0.3"
tcltk NA "yes" "4.0.3"
tools NA "yes" "4.0.3"
utils NA "yes" "4.0.3"
The page will show you a list of all the installed packages within the R and it is up to you to load one package before you can start using it.
#Use this function to load the library of your choice and I have chosen the library "graphics" for this example.
R> library("graphics")
R>
#If you entered the command properly and command prompt will show as normal. In this example, I purposely spelt wrongly and we will encounter the following error message.
R> library("graphic")
R>Error in library("graphic") : there is no package called ‘graphic’
There are a lot of useful libraries that are contributed by other users and programmers and you would have to install these packages in order to make use of them.
#Use the following function in order to install a package that is not found within your base installation of R. In this example, I decided to perform mathematical calculations using univariate and multivariate spatio-temporal random effects models for point-referenced data using Markov chain Monte Carlo, so I will go for "spBayes" that is the package to do just that.
R>install.packages("spBayes")
#If the command is run successfully, the console will start to show you the running output as the procedure complete.
Every so often, you also might want to check for updates to your packages therefore, you could use the following function to check.
R>update.packages()
#If the command is run successfully, the console will start to show you the running output as the procedure complete.
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Terra Link Research 