Page 68 - Contributed Paper Session (CPS) - Volume 3

CPS1946 Jittima D. et al.
mirror broad base economic activities in general. In addition, such data can be
utilized for economic research in various ways, for example, the U.S. Energy
Information Administration (2014) has tracked electricity consumption data to
indicate economic growth relative to the GDP.
In Thailand, main entities supplying electricity for households consisting of
the Electricity Generating Authority of Thailand (EGAT), the Metropolitan
Electricity Authority (MEA) and the Provincial Electricity Authority (PEA). Data
used by those authorities are for strategic planning and power management,
yet for the Bank of Thailand (BOT), the approach of data usage is an alternative.
Household electricity consumption data, in tradition, is part of components in
Private Consumption Index (PCI) as well as industrial electricity consumption,
one kind of manufacturing indicator, however, data adoption for the above is
in aggregate format.
The MEA and the BOT has entered into a Memorandum of Understanding
(MOU ) for data collaboration. Electricity data obtained from the MEA is
1
micro–level data which is a new and unconventional approach. The data
acquired cover wide range of economic units including households,
businesses and authorities. Major advantages of such data are it has short time
lag (around 2 - 3 weeks) and a long time series which is well sufficient for study
and analytics. In the trial, some key strategic objectives are achieved involving
utilizing micro-data along with the aggregate data to assess state of economy
in a comprehensive and timely manner.
In the crucible, focus is placed on calibrating some indicators for property
sector, particularly, for measuring demand for units in residential buildings –
quite often this is referred to condominiums that share greater weights in real
estate sector in the present. On methodology, an approach developed by
Ecotagious (2016) is adopted. Basically, by applying daily electricity data from
households in Vancouver, Canada to estimate Non-Occupancy Rate (NOR),
also there is a study by the MEA and the Thai National Housing Authority
(2009) aimed to project number of unoccupied dwellings in 3 provinces of
Thailand by using monthly electricity data. In short, the purpose of the study
is to investigate electricity usage data to measure occupancy rate (OR) for
articulating real demand for units in condominiums located in 3 territories
comprising Bangkok, Nonthaburi and Samut Prakan. Final attempt from
findings will serve as downstream indicators for real estate market analysis.
Prior to the use of micro-data, the BOT detected just only up- and midstream
indicators, for instance, number of new unit launched and units sold. With
regards to this, it enhances monitoring capability to be more comprehensive
starting from up-, mid- and downstream level.

1 The MOU was signed on 21 June 2016.
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