DATA FOR DEVELOPMENT June 13, 2017
1 Recent economic developments and outlook 2 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 3 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 4
GDP q/q saar, and annual growth, y/y, % 8.0 q/q, saar 7.0 Annual 6.0 5.0 4.0 3.0 2.0 1.0 0.0 4.0 4.3 4.5 5.6 3 Source: CEIC, DOSM, World Bank staff calculations
Contribution to GDP, y/y, % 12.0 10.0 Private consumption Fixed investment Change in inventory Government Net exports Real GDP growth 8.0 6.0 4.0 4.0 4.3 4.5 5.6 2.0 0.0 4.6 3.3 2.2 2.5 2.8 3.2 3.4 3.1 3.6-2.0-4.0 2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1 4 Source: CEIC, DOSM, World Bank staff calculations
Jan-15 Feb-15 Mar-15 Apr-15 May-15 Jun-15 Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 Jul-16 Aug-16 Sep-16 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Unemployment rate, % Labor force participation rate, % 3.6 Labour force participation Unemployment rate 3.5 3.4 3.3 3.2 3.1 3.0 2.9 2.8 2.7 68.2 68.1 68.0 67.9 67.8 67.7 67.6 67.5 67.4 67.3 5 Source: DOSM
Annual median growth rate, % 10 9 8 7 6 5 8.7 4 7.5 3 6.5 6.2 2 4.6 3 1 0 2015 2016 2015 2016 2015 2016 Total Urban Rural 6 Source: DOSM
Balances, % of GDP, last four quarters 15.0 Current Transfers Services Balance 10.0 Current Account Primary and Secondary Income Goods Balance 5.0 0.0 2.3 3.8 1.6-5.0-10.0-15.0 2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1 7 Source: CEIC, DOSM, BNM
Change in import component, y/y, % 50 Intermediate Capital Consumption 40 30 20 10 0-10 -20 2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1 8 Source: BNM
3/1/2017 5/1/2017 9/1/2017 11/1/2017 13/1/2017 17/1/2017 19/1/2017 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 23/2/2017 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 27/3/2017 29/3/2017 31/3/2017 Currency/ US$, Rebase = Jan 2017 102 Thailand Philippines Indonesia Malaysia 101 100 99 98 97 96 9 Source: CEIC, BNM, World Bank staff calculations Note: A decrease indicates appreciation
30/9/2016 7/10/2016 13/10/2016 19/10/2016 25/10/2016 31/10/2016 4/11/2016 10/11/2016 16/11/2016 22/11/2016 28/11/2016 2/12/2016 8/12/2016 15/12/2016 21/12/2016 28/12/2016 4/1/2017 10/1/2017 16/1/2017 20/1/2017 26/1/2017 3/2/2017 10/2/2017 16/2/2017 22/2/2017 28/2/2017 6/3/2017 10/3/2017 16/3/2017 22/3/2017 28/3/2017 30-day rolling standard deviation, MYR/US$ 0.12 0.1 0.08 0.06 0.04 0.02 0 10 Source: BNM, World Bank staff calculations
Outstanding loans, y/y, % 12 Total Businesses Household 10 8 6 4 2 0 2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1 11 Source: BNM
Annual growth, % 5.0 Current estimate (June 2017) Previous estimate (January 2017) 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 2016 2017f 2018f 2019f 2016 2017f 2018f 2019f 2016 2017f 2018f 2019f World Advanced Economies Emerging Market and Developing Economies Source: World Bank staff calculations 12
2014 2015 2016 2017f 2018f 2019f 16Q1 16Q2 16Q3 16Q4 17Q1 16Q1 16Q2 16Q3 16Q4 17Q1 8 6 4 Global industrial production and goods trade volume growth q/q, annualized, % 2012-16 average Global commodity prices Annual change, y/y, % 30 Crude oil Wheat 20 10 0 Soybeans Copper 2 0-2 -10-20 -30-40 -50 Industrial production Trade Source: World Bank June 2017 Global Economic Prospects 13
Annual growth, % 7 6 6.0 5 4 4.7 5.0 4.2 4.9 4.9 5.0 3 2 1 0 2013 2014 2015 2016 2017f 2018f 2019f Source: CEIC, DOSM, World Bank staff calculations 14
Balance of GDP, % 6 5 5.2 4.4 4 3 3.5 3.0 2.4 2 1.6 1 0 2012 2013 2014 2015 2016 2017f Source: CEIC, DOSM, World Bank staff calculations 15
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 16
1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Digital data overtook analog around 1998 and in 2013 amounted to 46 billion trillion bytes In optimally compressed bytes 1.0E+22 1.0E+21 In optimally compressed kbps 14000 High income Rest of the world 12000 Power of telecommunications capacity has also grown exponentially over the last decade 1.0E+20 1.0E+19 1.0E+18 1.0E+17 Analog Digital Total 1.0E+16 10000 8000 6000 4000 2000 0 18 Source: World Development Report 2016
Data openness varies across countries and regions Component scale 100 ODB-Score-Scaled 90 Readiness-Scaled Implementation-Scaled 80 Impact-Scaled 70 60 50 40 30 20 10 0 More openness and data accessibility is positively correlated with higher GDP per capita GDP per capita, USD thousands 160 140 120 100 80 60 40 20 0 Open Data Barometer-Score-Scaled 0 50 100 19 Source: Open Data Barometer, World Development Indicators, World Bank staff calculations
How more openness and data availability can impact service delivery 1 Informing citizens 5 More targeted policies and measures 2 Feedback on service delivery 4 Accountability 3 Improving management 21 Source: World Bank
High-income countries with higher open data scores produces more research per capita Log publication per capita 4.0 3.0 2.0 1.0 0.0-1.0 22 HKG THA MYS PHL NPL CHN IDN PAK SGP JPN KOR IND AUS TWN 0 20 40 60 80 100 Open Data Score as well as producing higher quality research. 120.0 100.0 80.0 60.0 40.0 20.0 Citation ratio Source: Open Knowledge Institute, IDEAS, World Bank staff calculations 0.0 MYS IDN SGP KOR JPN IND PHL PAK HKG CHN THA NPL AUS TWN 0 20 40 60 80 100 Open Data Score
1 The private sector is both producer and users of data 2 Enhanced data is both an input and a result of digital economy 3 Governments have recognized the value of big data for the private sector 4 Opportunity for a data exchange market for the private sector exists 23
Regularly inform actual and potential data users about what is available and get feedback about what is needed Inform Collect Role of data producers Create, compile information to be inserted into an information processing system. Disseminate 25 Work with governments and service providers to reduce the financial and procedural burden for data users to access data Source: World Bank Collaborate Provide data in easy to use, machine readable formats and researchfriendly formats
Collect DOSM s process is in line with international standards (GSBPM) Scope of DOSM has expanded with development DOSM s statisticians are deployed to various agencies DOSM and MAMPU has also looked into ways of adopting big data analytics (BDA) in the public sector DOSM has outlined Transformation Plan 2015 2020 to upgrading its systems and performance Source: DOSM 26
Collect The statistical workforce should reflect current and future demands, and technology needs 27 Number of employees, percent of total, 2015 100 90 80 70 60 50 40 30 20 10 0 86.6 13.4 Malaysia Managerial Support Source: DOSM, World Bank Note: High income countries is the average of Singapore, Spain and Netherlands 32.5 67.5 Advanced economies
Dissem. Most open Least open 100 50 0 28 Source: Open Data Barometer, 2015
Dissem. Malaysia s internet usage surpasses most regional comparators as well as secure internet servers Internet user (per 100 people), 2015 100 90 80 70 60 50 40 30 20 10 0 Secure internet servers, per 1million people, 2015 120 100 80 60 40 20 0 29 Source: World Development Indicators, 2016
UK Canada France US Korea Australia New Zealand Japan Netherlands Mexico Sweden Brazil Philippines Singapore India Kenya Indonesia Turkey South Africa Peru Tunisia Malaysia Thailand China Vietnam Dissem. Malaysia s open data score lags many high-income and regional countries ODB aggregated scores, 2016 100 90 80 70 60 50 40 30 20 10 0 Malaysia sub-categories scores are also lower against the region s average ODB score of sub-categories, 2016 Malaysia Economic impact Social impact Political impact Datasets: Accountabili ty Governmen t policies 75 50 25 0 East Asia and Pacific Datasets: Social policy Governmen t action Citizens & civil rights Entreprene urs & businesses Datasets: Innovation 30 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. Clear government support Aspiration by the government to be among the top 30 countries in the Open Data Barometer by 2020 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 31 Source: World Bank
Collab. Inform Collaboration Federated system no formal central control mechanism, although DOSM is the largest statistical agency in the country Databases that are maintained by various ministries are sometimes not fully integrated at the national level or disclosed 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 32 Source: World Bank
Current data ecosystem Potential data ecosystem in the future 34 Source: World Bank
4 Engagement should meet the growing appetite for more opportunities to interact and work with government data Collect 1 The workforce and work process of data collection should move in line with the country s economic progress and growing demand for data Inform Role of data producers Disseminate 2 Efforts should focus on improving access to more micro data and refining the current legal framework 3 35 Collaborations among Collaborate government agencies and other producers should focus on addressing data fragmentation
3 6