1. Capacity for producing economic statistics in Asia and the Pacific
3rd ASIA-PACIFIC ECONOMIC STATISTICS WEEK
Closing the Gaps in Economic Statistics for Sustainable Development
Capacity for producing economic statistics in Asia and the Pacific
Ms. Suzanne Wong
Chair, Task Force on the Capacity Screening Exercise 2017
Seventh meeting of the Steering Group for the Regional Programme on Economic Statistics (SGRPES)
10 May 2018

2. Purpose
Review progress made by countries in Asia and the Pacific in the production and dissemination of the Core Set of Economic Statistics
Identify capacity constraints to producing and disseminating the Core Set of Economic Statistics to inform further Programme implementation at the national and regional level.

3. Background
A survey of NSO’s, from Asia and the Pacific, was conducted in 2013 & 2017
51 responded in 2013, 50 in 2017
46 responded in both periods
Questions were focused on;
The core set of Economic Statistics
Statistical Capacity (Statistics Law, NSDS, Training, advocacy & collections)

4. Core Set of Economic Statistics (2017)
Sub Region
Count of countries
Average Number of Core set items
% of Total Core set
East and North-East Asia 6
27.5
89%
North and Central Asia 7
27.9
90%
Pacific 16
14.6
47%
South and South West-Asia 10
19.4
63%
South -East Asia 11
24.3
78%
Total 50
21.1
68%
Income Groupings
Count of countries
Average Number of Core set items
% of Total Core set
ESCAP low income 15
20.7
67%
ESCAP lower middle income
20.8
ESCAP upper middle income 11
18.2
59%
ESCAP high income 9
25.9
84%
Total 50
21.1
68%
Substantial variation between the regions noted – with Pacific and South and South West-Asia lower than the other regions.
Very interesting result when we consider income groupings - - Countries in the low and lower middle income groupings produced more of the core set on average than the upper middle income countries. We found this result quite interesting and considered other issues.

5. Relevant Groupings Ran regressions count of core set by;
Sub-regions
Income groupings
Population
GDP
Model of best fit was;
Log Population (Explained 67%)
Log GDP Per Capita (Explained 33%)
With the income grouping results, giving us a surprising results we ran some regressions to try to better understand what factors were important for the production of the core set. It was found that:
In the model of best fit only Log GDP and Log Population were statistically significant.
When the coefficients are used to predict the count of core set - Log population is the most important factor accounting for 67% of the predicted value.
It is easy to understand why wealthier country’s would produce more – they have a greater ability to allocate resources to statistics. However that population size of the country appears to be more important was a surprising results.
One possible consideration / advantage is that there are returns to scale for economic statistics. For example; when you quadruple the population you only need to double the sample size to maintain the same RSE (given certain assumptions of course).
𝐶𝑜𝑢𝑛𝑡 𝑜𝑓 𝐶𝑜𝑟𝑒 𝑆𝑒𝑡=𝐶+𝛽1∗𝑙𝑛 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 +𝛽2 𝐿𝑛(𝐺𝐷𝑃 𝑝𝑒𝑟 𝑐𝑎𝑝𝑖𝑡𝑎)
Regression Statistics Multiple R R Square Adjusteds
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept Ln - Pop E Ln -GDP d R Square Standard Error Observations 46
Regression showed;
Ln Population Size of country explained 67% of count of core set
GDP per capita of country only explained 33% of count of core set

6. Population Groupings Grouping Population Range
Count of Countries (2017)
Count of Countries (2013 & 2017)
Combined Population (2017)
Population share (%)
Micro
Less than 100,000 7
227,000
0.0%
Small
100,000 to 1 million 10
4,168,000
0.1%
Medium
1 to 30 million 17 15
177,740,000
4.0%
Large
30 million + 16 14
4,248,763,000
95.9%
Total 50 46
4,430,898,000
100.0%
Countries who responded in by Population Size
Micro
American Samoa, Northern Mariana Islands, Marshall Islands, Cook Islands, Nauru, Tuvalu & Niue
Small
Fiji, Bhutan, Macao (China), Maldives, Brunei Darussalam, Vanuatu, Samoa, Guam, Kiribati, Federated States of Micronesia
Medium
Nepal, Australia, Sri Lanka, Kazakhstan, Cambodia, Azerbaijan, Tajikistan, Papua New Guinea, Hong Kong (China), Lao PDR, Kyrgyzstan, Singapore, New Zealand, Georgia, Mongolia, Armenia & Timor Leste.
Large
China, India, Indonesia, Pakistan, Bangladesh, Russian Federation, Japan, Philippines, Viet Nam, Iran (Islamic Republic of), Turkey, Thailand, Myanmar, Republic of Korea, Afghanistan & Malaysia
Chose population groupings based on natural break points in the data and to give us similar sized population groupings.
Countries in bold didn’t respond in 2013.
For Micro the largest population was 56,000 .

7. Core Set Items (2013-17) Groupings show clear trend
Population size
Range of Country
Count of Countries
Average Number of Core set items
Published in 2017
Average change in the number of core set published since 2013
Micro 7
8.6
0.9
Small 10
17.6
2.3
Medium 15
25.8
0.6
Large 14
27.1
1.2
Total 46
21.8
Groupings show clear trend
Clear improvement on core set
Strong improvement in small countries being led by Samoa and Brunei
The average number of core set by population groupings.

8. Core Set of Economic Statistics
The Core Set Items
Core Set of Economic Statistics
Micro
Small
Medium
Large
Average
Consumer Price Index
100%
Producer Price Index 0%
30%
82%
88%
62%
Commodity Price Index
41%
75%
38%
External merchandise trade price indices
59%
81%
52%
Wages/earnings data
57%
70%
78%
Labour costs/Wage index
10%
65%
63%
44%
GDP (production) nominal and real
94%
98%
GDP (expenditure) nominal and real
29%
80%
External trade - merchandise
86%
96%
External trade - services
14%
Short-term indicator (STI) - industry output
40%
66%
STI - services output
71%
58%
STI - consumer demand
53%
48%
STI - fixed investment
60%
STI - inventories
69%
For the 50 countries, by the size ranges, this is the proportion of the countries that produce these elements of the core set.
The groupings in yellow identify areas with lower than 53% average. .

9. Core Set of Economic Statistics
The Core Set Items- 2017
Core Set of Economic Statistics
Micro
Small
Medium
Large
Average
Economy structure statistics
14%
50%
82%
81%
66%
Productivity 0%
20%
71%
54%
Integrated national accounts for the total economy
29%
40%
77%
88%
Institutional sector accounts
10%
47%
75%
44%
Balance of payments (BOP)
90%
100%
International investment position (IIP)
60%
70%
External debt
80%
76%
Income distribution
64%
Assets / liabilities of depository corporations
43%
Broad money and credit aggregates
72%
Interest rate statistics
General government operations
86%
General government debt
94%
Labour supply and demand
65%
Hours worked
Natural resources and environment
30%
35%
34%

10. Coordination: Statistical Legislation - 2017
Statistics law is a key enabler for the production of economic statistics.
Of the 50 countries to respond 49 stated that they had a statistical Act;
Out of those 49 countries;
All 49 indicated that the Statistical Act protects the confidentiality of respondent's information
47 responded that the Statistical Act has provisions on transparency
46 responded that the Statistical Act protects the independence of official statistics from political influence;
36 said the Statistical Act allows agencies in the national statistical system to acquire administrative data
29 countries indicated that they planned to change their Statistical Act.
Considering that the act in place do seem to meet a lot of the best practice we must consider why we have such a high number of countries that plan to change their statistical law. But from experience we know that there are issues with collecting admin data even if the law / act enables you to do so – as such more changes might be needed.

11. Coordination: NSDS 2013 & 2017
NSDS Status
2013
2017
Change
Developed and implemented 32 28 -4
Developed but not implemented yet 8 6 -2
Being Developed 2 7 5
Not planned 4 1
Count of non-response
Total 46
All 5 countries not planed NSDS in 2017 were Micro & small countries.
NSDS refers to any statistical master plan
All 5 Not Planned in 2017, are from Small & Micro countries

12. Countries with NSDS developed and implemented
Coordination: NSDS 2017
Micro
Small
Medium
Large
Average
Countries with NSDS developed and implemented 1 3 12 13 29
Is available on public website
100%
67%
83%
92%
86%
Coordination across the NSS
Statistical legislation
93%
Government support and advocacy
97%
Detailed action plan
75%
90%
Monitoring and review process
Again we can see the difference in countries of different sizes has the prevalence of NSDS and other statistical infrastructure.
Looking at the countries who have an NSDS that is developed and implemented we do see that they are covering many of the key best practices of an NSDS or national strategy. Should comment on the “detailed action plan”.

13. Skills: Training 2017 Micro Small Medium Large Average Countries 7 10
Micro
Small
Medium
Large
Average
Countries 7 10 17 16 50
Dedicated training unit
29%
60%
71%
88%
68%
Induction programmes on economic statistics in the NSO
50%
77%
100%
78%
Induction programmes on economic statistics for other agencies
53%
94%
62%
Training on economic statistics in the NSO
86%
80%
Training on economic statistics for other agencies
75%
58%
Do see evidence that population size of country matters regarding skills programs.

14. Statistical infrastructure: Collections and Register 2013 & 2017
Collections / Infrastructure
2013
2017
Change
Labour Force Survey 39 38 -1
House Income and Expenditure Survey 43 46 3
Enterprise/Establishment Survey 34 37
Population Census 44 45 1
Statistical Business Register 30
Economic Census 25
Agricultural Census 33
Data collections and the infrastructure that enable them are fundamental for quality statistics. Administrative data can’t explain everything. More countries are conducting surveys on Labour Force, HIEs and business surveys. SBRs and EC need to be analysed together – if administrative data is of sufficient quality and economic census is no longer necessary for the creation of economic statistics. As such – as the quality of admin data improves we can expect the number of SBRs to increase and EC’s to decline.

15. Advocacy: Dissemination 2017
Micro
Small
Medium
Large
Average
Countries 7 10 17 16 50
Data dissemination policies available to users
14%
60%
94%
100%
78%
Contact information published
57%
80%
90%
Statistical publications & documents available to users
Data bank/hub for published statistics
71%
88%
84%
Advance release calendar published
29%
40%
77%
81%
64%

16. Advocacy: User Engagement 2017
Out of the 50 participating countries
47 countries have activities to enhance awareness among users
29 countries have users' surveys
31 countries have other user engagement activities
While countries are engaging in activities to enhance awareness more countries should engage in a more structured way with their stakeholders to ensure that they are meeting stakeholder needs.

17. Questions and Answers