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DATA FOR DEVELOPMENT
June 13, 2017
• Recent economic developments and outlook
• Data for development
• Malaysia’s development and its data ecosystem
o Data and the public sector- public service delivery
o Data and academia- the case for homegrown research
o Data and the private sector- productivity and efficiency
• Role of data providers and their key collaborators in Malaysia
• Collecting data
• Disseminating data
• Sharing and collaborating on data
• Feedback from data users
• The way forward for Malaysia- from microsystems to an ecosystem
1
2
3
4
3Source: CEIC, DOSM, World Bank staff calculations
4.0
4.3
4.5
5.6
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0q/q, saar Annual
GDP q/q saar, and annual growth, y/y, %
4Source: CEIC, DOSM, World Bank staff calculations
Contribution to GDP, y/y, %
4.63.3
2.2 2.5 2.8 3.2 3.4 3.1 3.6
4.0 4.34.5
5.6
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
12.0
2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1
Private consumption Fixed investment Change in inventory
Government Net exports Real GDP growth
5
Source: DOSM
Unemployment rate, %
67.3
67.4
67.5
67.6
67.7
67.8
67.9
68.0
68.1
68.2
2.7
2.8
2.9
3.0
3.1
3.2
3.3
3.4
3.5
3.6
Jan-1
5
Fe
b-1
5
Mar-
15
Apr-
15
May-1
5
Jun-1
5
Jul-15
Aug-1
5
Sep-1
5
Oct-
15
No
v-1
5
De
c-1
5
Ja
n-1
6
Fe
b-1
6
Mar-
16
Apr-
16
May-1
6
Jun-1
6
Jul-16
Aug-1
6
Sep-1
6
Oct-
16
No
v-1
6
De
c-1
6
Jan-1
7
Fe
b-1
7
Ma
r-17
Labour force participation Unemployment rate
Labor force participation rate, %
6Source: DOSM
Annual median growth rate, %
6.5 6.2
3
7.58.7
4.6
0
1
2
3
4
5
6
7
8
9
10
2015 2016 2015 2016 2015 2016
Total Urban Rural
7Source: CEIC, DOSM, BNM
Balances, % of GDP, last four quarters
2.3
3.8
1.6
-15.0
-10.0
-5.0
0.0
5.0
10.0
15.0
2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1
Current Transfers Primary and Secondary Income
Services Balance Goods Balance
Current Account
8Source: BNM
Change in import component, y/y,
%
-20
-10
0
10
20
30
40
50
2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1
Intermediate Capital Consumption
9
Source: CEIC, BNM, World Bank staff calculations
Note: A decrease indicates appreciation
Currency/ US$, Rebase = Jan 2017
96
97
98
99
100
101
102
3/1
/2017
5/1
/2017
9/1
/2017
11
/1/2
01
7
13/1
/2017
17/1
/2017
19
/1/2
01
7
23/1
/2017
25/1
/2017
27/1
/2017
2/2
/2017
6/2
/2017
8/2
/2017
13/2
/2017
15/2
/2017
17/2
/2017
21/2
/2017
23
/2/2
01
7
27/2
/2017
1/3
/2017
3/3
/2017
7/3
/2017
9/3
/2017
13/3
/2017
15/3
/2017
17/3
/2017
21/3
/2017
23/3
/2017
27
/3/2
01
7
29/3
/2017
31/3
/2017
Thailand Philippines Indonesia Malaysia
10
Source: BNM, World Bank staff calculations
30-day rolling standard deviation,
MYR/US$
0
0.02
0.04
0.06
0.08
0.1
0.12
30/9
/2016
7/1
0/2
01
6
13/1
0/2
016
19/1
0/2
016
25/1
0/2
016
31/1
0/2
016
4/1
1/2
01
6
10/1
1/2
016
16/1
1/2
016
22/1
1/2
016
28/1
1/2
016
2/1
2/2
016
8/1
2/2
016
15/1
2/2
016
21/1
2/2
016
28/1
2/2
016
4/1
/2017
10
/1/2
01
7
16/1
/2017
20/1
/2017
26/1
/2017
3/2
/2017
10
/2/2
01
7
16/2
/2017
22/2
/2017
28/2
/2017
6/3
/2017
10
/3/2
01
7
16/3
/2017
22/3
/2017
28/3
/2017
11 Source: BNM
Outstanding loans, y/y, %
0
2
4
6
8
10
12
2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1
Total Businesses Household
12
Source: World Bank staff calculations
Annual growth, %
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
2016 2017f 2018f 2019f 2016 2017f 2018f 2019f 2016 2017f 2018f 2019f
World Advanced Economies Emerging Market andDeveloping Economies
Current estimate (June 2017) Previous estimate (January 2017)
-2
0
2
4
6
8
16Q
1
16Q
2
16Q
3
16
Q4
17Q
1
16Q
1
16Q
2
16Q
3
16Q
4
17Q
1
Industrial production Trade
2012-16 average
13Source: World Bank June 2017 Global Economic Prospects
q/q, annualized, %
Global industrial production and goods
trade volume growth
-50
-40
-30
-20
-10
0
10
20
30
201
4
201
5
201
6
20
17
f
201
8f
201
9f
Crude oil Soybeans
Wheat Copper
Annual change, y/y, %
Global commodity prices
14
Source: CEIC, DOSM, World Bank staff calculations
Annual growth, %
4.7
6.0
5.0
4.2
4.9 4.9 5.0
0
1
2
3
4
5
6
7
2013 2014 2015 2016 2017f 2018f 2019f
15
Source: CEIC, DOSM, World Bank staff calculations
Balance of GDP, %
5.2
3.5
4.4
3.0
2.4
1.6
0
1
2
3
4
5
6
2012 2013 2014 2015 2016 2017f
16
GDP Growth is expected to accelerate to 4.9 percent in 2017, supported by
• Strong labor market and ongoing income-support measures
• Stabilization of global commodity prices, higher trade growth
Risks to GDP growth in the short-term stem mainly from external developments
• Threats of protectionism to global trade
• Sudden reversal in oil prices, financial conditions
Continue to Maintain solid macroeconomic framework
Higher GDP growth opens up room to accelerate fiscal consolidation
Accelerate structural reforms to improve productivity
18
1.0E+16
1.0E+17
1.0E+18
1.0E+19
1.0E+20
1.0E+21
1.0E+22
19
86
19
89
19
92
19
95
19
98
20
01
20
04
20
07
20
10
20
13
Analog Digital Total
0
2000
4000
6000
8000
10000
12000
14000
200
3
200
4
20
05
200
6
200
7
20
08
200
9
201
0
201
1
201
2
201
3
High income Rest of the world
Digital data overtook analog around 1998 and
in 2013 amounted to 46 billion trillion bytes
Power of telecommunications capacity
has also grown exponentially over the
last decade
In optimally compressed bytes In optimally compressed kbps
Source: World Development Report 2016
19
Data openness varies across countries
and regions
More openness and data accessibility is
positively correlated with higher GDP per
capita
Component scale GDP per capita, USD thousands
Source: Open Data Barometer, World Development Indicators, World
Bank staff calculations
0
10
20
30
40
50
60
70
80
90
100 ODB-Score-ScaledReadiness-ScaledImplementation-ScaledImpact-Scaled
0
20
40
60
80
100
120
140
160
0 50 100Open Data Barometer-Score-Scaled
21Source: World Bank
How more openness and data availability can impact service delivery
Informing citizens
Feedback on service delivery
Improving management
Accountability
More targeted policies and measures
1
2
34
5
22
High-income countries with higher open data
scores produces more research per capita……as well as producing higher quality research.
Log publication per capita Citation ratio
Source: Open Knowledge Institute, IDEAS, World Bank staff calculations
TWNAUS
KOR
SGP
JPN
HKG
INDIDN
THA
PHL
PAK
NPLCHN
MYS
-1.0
0.0
1.0
2.0
3.0
4.0
0 20 40 60 80 100Open Data Score
TWN
AUS
KOR
SGP
JPN
HKGIND
IDN
THA
PHLPAK
NPLCHN
MYS
0.0
20.0
40.0
60.0
80.0
100.0
120.0
0 20 40 60 80 100Open Data Score
23
The private sector is both producer and users of data
Enhanced data is both an input and a result of digital economy
Governments have recognized the value of big data for the private sector
Opportunity for a data exchange market for the private sector exists
1
2
3
4
25 Source: World Bank
Role of data producers
Collect
Inform
Create, compile information to
be inserted into an information
processing system.
Provide data in easy to
use, machine readable
formats and research-
friendly formatsWork with governments and
service providers to reduce the
financial and procedural burden
for data users to access data
Regularly inform actual
and potential data users
about what is available
and get feedback about
what is needed
Collaborate
Disseminate
26
Source: DOSM
Collect
Scope of DOSM has expanded with development
DOSM’s process is in line with international standards (GSBPM)
DOSM and MAMPU has also looked into ways of adopting big data analytics (BDA) in the public sector
DOSM’s statisticians are deployed to various agencies
DOSM has outlined Transformation Plan 2015–2020 to upgrading its systems and performance
27
Source: DOSM, World Bank
Note: High income countries is the average of Singapore, Spain and
Netherlands
13.4
67.5
86.6
32.5
0
10
20
30
40
50
60
70
80
90
100
Malaysia Advanced economies
Managerial Support
Number of employees, percent of total, 2015
Collect
The statistical workforce should reflect current and future demands, and technology needs
28 Source: Open Data Barometer, 2015
100 050
Most
open
Least
open
Dissem.
29
Malaysia’s internet usage surpasses most
regional comparators…
Internet user (per 100 people), 2015
Source: World Development Indicators, 2016
0102030405060708090
100
0
20
40
60
80
100
120
…as well as secure internet servers
Secure internet servers, per 1million people, 2015
Dissem.
30
Malaysia’s open data score lags many
high-income and regional countriesMalaysia sub-categories scores are also
lower against the region’s average
ODB aggregated scores, 2016ODB score of sub-categories, 2016
Source: Open Data Barometer (ODB)
Note: The ODB scores are calculated based on three categories; readiness,
implementation and impact. Each of the sub-categories contributes to these three
broad categories.
Dissem.
0
10
20
30
40
50
60
70
80
90
100
UK
Ca
nad
aF
ran
ce
US
Ko
rea
Au
str
alia
Ne
w Z
eala
nd
Jap
an
Ne
the
rla
nd
sM
exic
oS
wed
en
Bra
zil
Ph
ilip
pin
es
Sin
ga
pore
Ind
iaK
enya
Ind
on
esia
Tu
rke
yS
ou
th A
fric
aP
eru
Tu
nis
iaM
ala
ysia
Th
aila
nd
Ch
ina
Vie
tna
m
0
25
50
75
Government policies
Government action
Citizens &civil rights
Entrepreneurs &
businessesDatasets:Innovation
Datasets:Socialpolicy
Datasets:Accountabili
ty
Politicalimpact
Socialimpact
Economicimpact
Malaysia East Asia and Pacific
31Source: World Bank
Aspiration by the government to be among the top 30
countries in the Open Data Barometer by 2020Clear government
support
Available
building blocks
Malaysia has the necessary building blocks to improve its
data accessibility and openness e.g. funding, infrastructure
Legal and
regulatory
framework
Existing legal and regulatory framework could benefit from
refinement
More access to
granular data
Malaysia is a data-rich environment, but more high quality,
granular data should be released
Dissem.
32 Source: World Bank
Databases that are maintained by various ministries are
sometimes not fully integrated at the national level or disclosed
Collab.
Collaboration
“Federated system” – no formal central control mechanism,
although DOSM is the largest statistical agency in the country
Inform
Inform
Civil society, business community and academia in Malaysia are
avid users of various types of data – How further collaborate?
Initial steps to manage occasional feedback from the public on
data accuracy, perception and misinterpretation have been done
34 Source: World Bank
Current data ecosystem Potential data ecosystem in the future
35
Role of data producers
Collect
Inform
The workforce and work process
of data collection should move in line
with the country’s economic progress
and growing demand for data
Efforts should focus on
improving access to more
micro data and refining the
current legal framework
Collaborations among
government agencies and other
producers should focus on
addressing data fragmentation
Engagement should
meet the growing
appetite for more
opportunities to interact
and work with
government data
Collaborate
Disseminate
1
2
3
4
3
6