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Document of

The World Bank

Report No: ICR00004174

IMPLEMENTATION COMPLETION AND RESULTS REPORT

(IBRD-80230)

ON A

LOAN

IN THE AMOUNT OF US$ 20 MILLION

TO THE

REPUBLIC OF KAZAKHSTAN

FOR A

KAZSTAT: STRENGTHENING THE NATIONAL STATISTICAL SYSTEM OF

KAZAKHSTAN PROJECT

October 26, 2017

Poverty and Equity Global Practice

ECCKZ (Country Department)

Europe and Central Asia Region (ECA)

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CURRENCY EQUIVALENTS

(Exchange Rate Effective October 24, 2017)

Currency Unit = Kazakh Tenge

KZT 334.02 = US$ 1

FISCAL YEAR

January 1 – December 31

ABBREVIATIONS AND ACRONYMS

ADB Asian Development Bank

APL

ARKS

Adaptable Program Loan

Agency of the Republic of Kazakhstan on Statistics

BOP Balance of Payments

BPM5 IMF’s Balance of Payments Manual Number 5

CAPI

CATI

CES

Computer Assisted Personal Interview

Computer Assisted Telephone Interview

Conference of European Statisticians

CIS Commonwealth of Independent States

CN Combined Nomenclature

COFOG

COICOP

Classification on the Functions of the Government

Classification of Individual Consumption by Purpose

CPA Classification of Products by Activity

CPA Certified Public Accountant

CPI Consumer Price Index

CPS

CSMNE

CWG

DB

DECDG

Country Partnership Strategy

Committee on Statistics under the Ministry of National

Economy

(Inter-Office) Coordination Working Group

Database

Development Economics Data Group

ECO Economic Cooperation Organization

ESS European Statistical System

FAO Food and Agriculture Organization of the United Nations

FD

FMS

Finance Department

Financial Management System

FY Fiscal Year

FISIM Financial Intermediation Services Indirectly Measured

GA Global Assessment

GDP Gross Domestic Product

GDDS General Data Dissemination System

GFSM IMF's Government Finance Statistics Manual

GIS Geographical Information System

GRP Gross Regional Product

HIES Household Income and Expenditure Survey

HS Harmonized System

IBRD International Bank for Reconstruction and Development

ICSE International Classification on Status in Employment

ICC Information Calculating Centre

ICR Implementation Completion and Results Report

ICT Information and Communication Technology

IFR

IIS

Interim Financial Report

Integrated Information System e-Statistics

ILO International Labor Organization

IMF International Monetary Fund

ISCO International Standard Classification of Occupations

ISIC International Standard Industrial Classification

ISR Implementation Status & Results Report

IT Information Technology

JERP

KNSS

LFS

Joint Economic Research Program

Kazakh National Statistical System

Labor Force Survey

MAPS

MIC

Marrakech Action Plan for Statistics

Middle Income Countries

MICS Multiple Indicators Cluster Survey

MMFS IMF’s Manual on Monetary and Financial Statistics

MOF Ministry of Finance

MTR Mid-Term Review

NACE The European Union’s Classification of Economic Activities

NBK National Bank of Kazakhstan

NCEA

NGO

National Classification of Economic Activities

Non-Governmental Organization

NOE

NPISH

Non-Observed Economy

Non-Profit Institutions Serving Households

NSDS National Strategy for the Development of Statistics

NSO National Statistical Office

OECD Organization for Economic Cooperation and Development

PAD Project Appraisal Document

PDF Portable Document Format (Adobe Acrobat)

PDO Project Development Objectives

PEFA

PIN

Public Expenditure & Financial Accountability Assessment

Personal Identification Number

PIT Project Implementation Team

PIU Project Implementation Unit

PPD Public Procurement Department

PPI Producer Price Index

POM Project Operations Manual

PRODCOM European Union’s Classification of Products Produced by the

Industrial Sector

RF Results Framework

SDDS Special Data Dissemination Standard

SDG Sustainable Development Goals

SMP Statistical Master Plan

SNA System of National Accounts

SNTVUT Statistical Nomenclature of the Goods by Kinds of Trade

STATCAP Statistical Capacity Building Program (APL)

TACIS Technical Assistance to the Commonwealth of Independent

States

TFSCB Trust Fund for Statistical Capacity Building

TI Transparency International

TP Twinning Partnership

UN United Nations

UNECE United Nations Economic Commission for Europe

UNESCAP United Nations Economic and Social Commission for Asia

and the Pacific

UNFPA United Nations Population Fund

USD United States Dollar

VAW Violence against Women

VPDN Virtual Private Dial-up Network

VPN Virtual Private Network

WHO World Health Organization

Senior Global Practice Director: Carolina Sanchez-Paramo

Sector Manager: Luis-Felipe Lopez-Calva

Project Team Leader: Mustafa Dinc

ICR Team Leader: Olga Shabalina

KAZAKHSTAN

KAZSTAT: Strengthening the National Statistical System of Kazakhstan

TABLE OF CONTENTS

Data Sheet

A. Basic Information ...................................................................................................................... vi

B. Key Dates ................................................................................................................................... vi

C. Ratings Summary ....................................................................................................................... vi

D. Sector and Theme Codes .......................................................................................................... vii

E. Bank Staff ................................................................................................................................. vii

F. Results Framework Analysis ..................................................................................................... vii

G. Ratings of Project Performance in ISRs .................................................................................... xi

H. Restructuring (if any)................................................................................................................ xii

I. Disbursement Profile .................................................................................................................. xii

1. Project Context, Development Objectives and Design ............................................................... 1

2. Key Factors Affecting Implementation and Outcomes ............................................................... 3

3. Assessment of Outcomes ............................................................................................................. 8

4. Assessment of Risk to Development Outcome ......................................................................... 18

5. Assessment of Bank and Borrower Performance ...................................................................... 20

6. Lessons Learned ........................................................................................................................ 21

7. Comments on Issues Raised by Borrower/Implementing Agencies/Partners ........................... 23

Annex 1: KAZSTAT Project– Results framework........................................................................ 25

Annex 2: KAZSTAT Project Original Components ..................................................................... 26

Annex 3: Project Costs and Financing .......................................................................................... 28

Annex 4: Critical risks and possible controversial aspects ............................................................ 29

Annex 5: Mid-Term Review findings and recommendations ....................................................... 32

Annex 6: Outputs by Components and Sub-components .............................................................. 35

Annex 7: Follow up Technical assistance ..................................................................................... 52

Annex 8: Statistical Performance of Kazakhstan - 2016 ............................................................... 54

Annex 9. Economic and Financial Analysis .................................................................................. 64

Annex 10. Bank Lending and Implementation Support/Supervision Processes ........................... 65

Annex 11. Beneficiary Survey Results .......................................................................................... 67

Annex 12. Stakeholder Workshop Report and Results ................................................................. 67

Annex 13. Summary of Borrower's ICR and/or Comments on Draft ICR .................................... 67

Annex 14. Comments of Cofinanciers and Other Partners/Stakeholders ...................................... 67

Annex 15. List of Supporting Documents ..................................................................................... 68

MAP .............................................................................................................................................. 69

vi

KAZAKHSTAN


D A T A S H E E T

A. BASIC INFORMATION

Country: Kazakhstan Project Name:

KAZSTAT: Strengthening

the National Statistical

System of Kazakhstan

Project ID: P120985 L/C/TF Number(s): IBRD-80230

ICR Date: 10/25/2017 ICR Type: Core ICR

Financing Instrument: APL Borrower: KAZAKHSTAN

Original Total

Commitment: USD 20.00M Disbursed Amount: USD 19.95M

Revised Amount: USD 19.95M

Environmental Category: C

Implementing Agencies: The Statistics Committee under the Ministry of National Economy of the Republic of Kazakhstan

Cofinanciers and Other External Partners:

B. KEY DATES

Process Date Process Original Date Revised / Actual Date(s)

Concept Review: 03/18/2010 Effectiveness: 02/24/2012

Appraisal: 05/13/2010 Restructuring(s):

Approval: 03/31/2011 Mid-term Review: 10/20/2014 10/02/2014

Closing: 04/30/2017 04/30/2017

C. RATINGS SUMMARY

C.1 Performance Rating by ICR

Outcomes: Satisfactory

Risk to Development Outcome: Moderate

Bank Performance: Satisfactory

Borrower Performance: Satisfactory

C.2 Detailed Ratings of Bank and Borrower Performance (by ICR)

Bank Ratings Borrower Ratings

Quality at Entry: Satisfactory Government: Satisfactory

vii

Quality of Supervision: Satisfactory Implementing

Agency/Agencies: Satisfactory

Overall Bank

Performance: Satisfactory

Overall Borrower

Performance: Satisfactory

C.3 Quality at Entry and Implementation Performance Indicators

Implementation

Performance Indicators

QAG Assessments (if

any) Rating

Potential Problem Project at any time (Yes/No):

No Quality at Entry (QEA): None

Problem Project at any time (Yes/No):

No Quality of Supervision

(QSA): None

DO rating before Closing/Inactive status:

Satisfactory

D. SECTOR AND THEME CODES

Original Actual

Major Sector/Sector

Public Administration

Other Public Administration 100 100

Major Theme/Theme/Sub Theme

Public Sector Management

Data Development and Capacity Building 100 100

Data production, accessibility and use 100 100

E. BANK STAFF

Positions At ICR At Approval

Regional Vice President: Cyril E Muller Philippe H. Le Houerou

Country Director: Lilia Burunciuc Motoo Konishi

Practice Manager: Luis-Felipe Lopez-Calva Grant James Cameron

Task Team Leader(s): Mustafa Dinc Mustafa Dinc

ICR Team Leader: Olga Vadimovna Shabalina

ICR Primary Author: Olga Vadimovna Shabalina

F. RESULTS FRAMEWORK ANALYSIS Project Development Objectives (from Project Appraisal Document)

The main objective of the project is to improve efficiency and effectiveness of the national statistical system

to provide relevant, timely and reliable data in line with internationally accepted methodology and best

practices.

viii

Revised Project Development Objectives (as approved by original approving authority)

PDO was not revised.

(a) PDO Indicator(s)

Indicator Baseline Value

Original Target

Values (from

approval

documents)

Formally

Revised Target

Values

Actual Value Achieved

at Completion or Target

Years

Indicator 1 : User satisfaction rates have significantly increased by the closing date (Percentage, Custom) Indicator 1 : User satisfaction rates have significantly increased by the closing date (Percentage, Custom)

Value

quantitative or

Qualitative)

45

80

94.4

Value

quantitative or

Qualitative)

Date achieved 03/17/2011 04/30/2017 10/28/2016 Date achieved

Comments

(incl. %

achievement)

Overachieved. Survey is conducting once in two years based on the international

Methodology. 2016 Survey results are available with Center for Studies of Public

Opinions (independent organization which conducted the survey).

Comments

(incl. %

achievement)

Indicator 2 : Statistical products are easily accessible in relevant media with metadata and interpretation

of findings (Number, Custom) Indicator 1 : Statistical products are easily accessible in relevant media with metadata and interpretation

of

findings (Number, Custom)

Value

quantitative or

Qualitative)

40,000.00

400,000.00

4,200,000.00

Value

quantitative or

Qualitative)


Comments

(incl. %

achievement)

Overachieved. As a result of introducing of TALDAU database, implementation of

metadata system on the website, modernization of website of other data producers.

Comments

(incl. %

achievement)

Indicator 3 : Internationally accepted statistical techniques in collection, compilation, and authenticity

verification are applied and regular validations are carried out for data sources and

statistical products (Percentage, Custom)

Indicator 1 : Internationally accepted statistical techniques in collection, compilation, and authenticity

verification are applied and regular validations are carried out for data sources and

statistical products (Percentage, Custom)

Value

quantitative or

Qualitative)

42

100

95

Value

quantitative or

Qualitative)


Comments

(incl. %

achievement)

Achieved partially (95 out of 100). Kazakh statistics is compiling all basic data following

UNSC, IMF, WTO standards and recommendations on methodology and timeliness.

Comments

(incl. %

achievement)

Indicator 4 : Statistical outputs are released within the time limits and with frequency meeting the SDDS

requirements (Percentage, Custom) Indicator 1 : Statistical outputs are released within the time limits and with frequency meeting the SDDS

requirements (Percentage, Custom)

Value

quantitative or

Qualitative)

40

100

100

Value

quantitative or

Qualitative)


Comments

(incl. %

Achieved. Schedules of disseminating and transferring statistical data to national and

International agencies adopted by the Government and are obligatory for the CSMNE and

Comments

(incl. %

ix

achievement) for other producers of official statistical data. Released calendar is on website

(b) Intermediate Outcome Indicator(s)

Indicator Baseline Value

Original Target

Values (from

approval

documents)

Formally Revised

Target Values

Actual Value Achieved at

Completion or Target Years

Indicator 1 : Mechanisms for effective inter-agency coordination are established and operational.

(Text, Custom)

Value

quantitative or

Qualitative)

Committee

coordinates

statistical actions

and collection of

official data. There

is no complex

evaluation about

applicability of

information

generated as a

result of research.

Efficient

intergovernmental

coordination in

place.

Efficient intergovernmental

coordination in place.

Date achieved 03/17/2011 04/30/2017 10/28/2016

Comments

(incl. %

achievement)

Achieved. Amendments to Law submitted. Community of statistical practice developed.

Integral system of 21 ministries operational. MOUs signed.

Indicator 2 : Mechanisms for effective dialogue with the data users and providers are operational (Text,

Custom)

Value

quantitative or

Qualitative)

Has not completed

yet. Users

satisfaction polling

by independent

experts is not

ensured.

Effective

dialogue between

users and

producers of

statistical data is

in place.

Effective dialogue between

users and producers of

statistical data is in place.

Date achieved 03/17/2011 04/30/2017 10/28/2016

Comments

(incl. %

achievement)

Achieved. User satisfaction surveys conducted. Regular monthly press conferences with

media agencies. One-window arrangements for respondents in place. Call-center

established. Pre-lab is functional.

x

Indicator 3 : CSMNE central and local level structure optimized and staff trained including staff from

Relevant ministries and agencies. (Percentage, Custom)

Value

quantitative or

Qualitative)

40

100

98

Date achieved 03/17/2011 04/30/2017 10/28/2016

Comments

(incl. %

achievement)

Partially achieved. Vast training program completed. New conditions for division of

responsibilities between CSMNE, regional statistical offices and local statistical units

created. Optimization of local structure continues considering existing conditions

Indicator 4 : Registers are compiled and being maintained. (Text, Custom)

Value

quantitative or

Qualitative)

Regular work is in

progress. However,

there are

difficulties with

registers updating,

using data for res

All registers are

properly

maintained and

applied to

generate samples.

Business, Population,

Housing stock and

Agricultural registers are

properly setup and getting

ready to generate samples.

Date achieved 03/17/2011 04/30/2017 10/28/2016

Comments

(incl. %

achievement)

Achieved. Business, Population, Housing and agriculture registers complied with

international standards. Comprehensive database and management system for business

register developed. Online database system for population and HH surveys functional.

Indicator 5 : Internationally accepted classifications standards and methodologies are adapted and used

in data production. (Text, Custom)

Value

quantitative or

Qualitative)

Amending of

accepted

classifications

when required.

Statistics data

generated by the

Agency fully

meets the

international

requirements to

classifications

and standards.

The metadata base system of

maintaining and updating

classifications and glossaries

was designed and

implemented. Basic scope of

metadata covering

internationally accepted

standards, classifications

and definitions was

introduced and is updated..

Date achieved 03/17/2011 04/30/2017 10/28/2016

Comments

(incl. %

achievement)

Achieved: 39 new methodology adapted; 41 improved; 128 new indicators developed.

SNA, Structural, Price, Industrial statistics, Construction and investment, Agriculture,

Environmental, Services and ICT statistics in line with international standards.

Indicator 6 : Standard questionnaires for surveys developed and applied. (Text, Custom)

Value

quantitative or

Qualitative)

Have not been

drafted.

Rules for

approval of

statistical forms

for nation-wide

and sector-

specific statistical

surveys,

guidelines for

Rules for approval of

statistical forms for nation-

wide and sector-specific

statistical surveys,

guidelines for completing

them based on international

recommendations are in

practice.

xi

completing them

based on

international

recommendations

are in practice.

Date achieved 03/17/2011 04/30/2017 10/28/2016

Comments

(incl. %

achievement)

Achieved. Questionnaires are developed and applied for Labor and Household surveys

Indicator 7 : ICT Capacity for operations is adequate and well maintained. (Text, Custom)

Value

quantitative or

Qualitative)

Required to be

improved.

Up to date ICT

network and

equipment.

Networking equipment

(high-performance core

switches and security

equipment) is purchased,

delivered and installed and

adopted.

Date achieved 03/17/2011 04/30/2017 10/28/2016

Comments

(incl. %

achievement)

Achieved. All procurement activities for the ICT (hardware and software) needs completed.

Current level of the ICT at center and in regional offices is up-to-date for purposes of

technological capacity and organization of surveys and dissemination of data

Indicator 8 : All relevant staff at CS have workstations with access to databases for analysis and

tabulations. (Text,

Value

quantitative or

Qualitative)

Required to be

improved.

All staff have

workstations and

able to use them

effectively.

CATI system is operational.

The pilot survey was

conducted using CATI

system.

Date achieved 03/17/2011 04/30/2017 10/28/2016

Comments

(incl. %

achievement)

Achieved. All statistical staff equipped with the ICT, has access to internet, and possessed

modern tools and packages (R software, CATI and CAPI) for the purpose of survey design

and data collection.

G. RATINGS OF PROJECT PERFORMANCE IN ISRs

No. Date ISR

Archived DO IP

Actual Disbursements

(USD millions)

1 09/21/2011 Satisfactory Satisfactory 0.00









xii



H. RESTRUCTURING (IF ANY)

Restructuring Date(s)

Board

Approved

PDO

Change

ISR Ratings at

Restructuring Amount Disbursed

at Restructuring in

USD Millions

Reason for

Restructuring & Key

Changes Made DO IP

I. DISBURSEMENT PROFILE

1

1. PROJECT CONTEXT, DEVELOPMENT OBJECTIVES AND DESIGN

1.1 Context at Appraisal

1. After the 2008 crisis recovery, the economic reforms and country’s growth in

Kazakhstan continued. Kazakhstan weathered the 2008 global financial crises well

through a dexterous response combining fiscal relaxation with the bank stabilization

measures. The decisive approach to macroeconomic and financial sector management

contributed to a quick recovery in output. Economy grew by 7.3 percent and 7.5 percent in

2010-11 (compared to the 1.2 percent in 2009). External position was strengthened: the

current account surplus was estimated at 7.3 percent of the gross domestic product (GDP)

and gross international monetary and fiscal reserves stood at the level of 40 percent of GDP

(by end 2011). Inflationary pressure have been contained. The fiscal position has improved

significantly too. In 2011 non-oil deficit was about 8 percent of GDP compared to 10

percent in 2008-09. Poverty incidence was at a level of 6.5 percent. At the same time, the

development of the balanced economy required the state to redefine its role to permit a

vigorous private sector to develop, governance to be strengthened, tough second generation

structural reforms to be embedded, and public investments to be made.

2. Development of the National Statistical System of Kazakhstan (KNSS). The

KNSS has undergone substantial transformation from a service structured to serve the

needs of a planned economy to one addressing the needs of the developing market economy

and new society, and became one of the best national statistical services in the region.

Kazakhstan subscribed to the Special Data Dissemination Standard (SDDS) in March

2003. The first Law on Statistics was adopted in 1997, and the new one currently in force

- in 2010. The KNSS remained centralized, with the Agency of the Republic of Kazakhstan

on Statistics (ARKS) - established in 2004 - in charge of managing official statistics in the

country, including 16 regional and 187 district offices, and coordinating activities in the

sector with about eleven other agencies and ministries producing official statistics. In 2014

because of administrative reform all Government agencies were transferred under the

ministries, including the ARKS which became a Committee on Statistics under Ministry

of National Economy (CSMNE).

3. At project appraisal, the country development strategy focused on

modernization and a shift towards growth from non-oil sources. It was based on

diversification, innovation, investment in human capital, international trade integration,

increased emphasis on strengthening governance, enabling business environment,

improved quality of public services and in skill levels of the workforces, raising standards

in education, renewed emphasis on regional developments. This ambitious agenda was data

and information intensive. To monitor progress in achieving these significant policy

initiatives, comprehensive, high quality, and reliable statistics would be required.

4. The National Strategy for Development of Statistics (NSDS) was developed to

guide the progress in statistics. In Kazakhstan, the NSDS was prepared under the Joint

Economic Research Program (JERP) – at that time co-financed jointly by the Government

(80 percent) and the Bank (20 percent). The NSDS comprised the thorough assessment of

2

the KNSS with the budgeted Statistical Master Plan (SMP) for 2010-2015. The KAZSTAT

project contributed to the implementation of this NSDS.

5. The KAZSTAT project was in line with the Country Partnership Strategy

(CPS) for 2012-2016. The CPS defined strengthening governance and improving

efficiency in public sector delivery as one of the areas of Bank’ engagement within which

a country’s development goal was to improve public financial management and fight

corruption. KAZSTAT project was included into CPS to contribute to achieving this goal

by strengthening budget and accounting institutions through introducing modern methods

and sharpening skills in government statistics.

6. The rationale for Bank support was to consolidate and build upon the progress

made in statistical capacity building, for which the Bank had a comparative advantage. As

noted in the Project Appraisal Document (PAD), the Bank had a mandate to lead the

statistical capacity initiative. The Bank also had substantial experience in assisting

countries in statistical capacity improvement activities, in a strategic and timely fashion,

linked to a broad development agenda. An important advantage was to offer the necessary

means, including financial, to support such projects as evidenced from several Statistical

Capacity Building Program (STATCAP) projects under implementation at the time of

approval.

1.2 Original Project Development Objectives (PDO) and Key Indicators

7. The main objective of the project was to improve efficiency and effectiveness of

the national statistical system to provide relevant, timely and reliable data in line with

internationally accepted methodology and best practices as stated in the Project Appraisal

Document (page 14 paragraph 18; Technical Annex 3) and Loan Agreement (Schedule 1,

page 5).

8. The progress towards the PDO was to be measured through the Results

Framework (RF) outlined in the PAD (pages 39-43, Annex 3). It encompassed the key

indicators presented in Annex 1: Results Framework.

1.3 Revised PDO (as approved by original approving authority) and Key Indicators, and

reasons/ justification

9. The PDO and key indicators were not revised. Two indicators were slightly re-

worded to reflect more accurately the project results. Information is available for all

indicators in the Implementation Status Reports (ISR).

3

1.4 Main Beneficiaries,

10. The main beneficiaries of the project outcomes were the ARKS/ CSMNE, the

Government and the general public as well as international development partners.

1.5 Original Components

11. The PDO was to be achieved through the implementation of seven project

components with a total allocation of US$22.8 million (loan amount - US$ 20 million and

Government co-financing US$ 2.81 million). The components’ description is based on the

Loan Agreement and presented in Annex 2: KAZSTAT Project Original Components.

1.6 Revised Components

12. There was no revision of components during project implementation. Status of

project funds disbursed during implementation compared with the initially planned

disbursement, is reflected in Annex 3: Project costs and Financing. The Implementation

Completion and Results Report (ICR) team noted that there was a Mid-Term Review

(MTR) recommendation to introduce an additional component on development of regional

statistics. After consideration, it was decided not to restructure the project.

1.7 Other significant changes

13. No significant changes took place in terms of scope, implementation

arrangements, schedule, and initial funding allocations.

2. KEY FACTORS AFFECTING IMPLEMENTATION AND OUTCOMES

2.1 Project Preparation, Design and Quality at Entry

14. The preparation, design and quality at entry of KAZSTAT project were shaped

by:

Analytical underpinning. The technical design of the project was based on a solid

analysis of the strengths and weaknesses of the national statistical system (NSS) of the

country undertaken under the Global Assessment (GA) of the statistical system of the

Republic of Kazakhstan by the UNECE and UNESCAP in 2008. This evaluation was

further supplemented by preparation of the NSDS and SMP (2010-15) through the

Government co-financed JERP channel. Implementation of the ARKS Strategic Plan for

Statistics (2009 – 2013) added to the overall big picture of the status and development of

the KNSS. The Bank played the timely role of integrator of these evaluations and

recommendations to support design of the KAZSTAT project.

Government commitment. Government commitment was strong. The ARKS has

elaborated its own Program Document (2011) to substantiate the project, to align it with the

Government strategy and emphasize the gains to be obtained as a result of KAZSTAT

project implementation.

4

On-going Bank dialog with the Government of Kazakhstan. There was a diverse

Bank policy and operational involvement to support the development in the country.

Country Management Unit (CMU) engagement with the client in different areas provided

a very favorable environment for successful preparation of the statistical operation.

Previous collaboration in statistics. The Bank had knowledge of and experience in

supporting the operations of the ARKS through previous TFSCB and JERP projects. These

earlier engagements have helped to address the request of the Kazakh Government for

assistance in statistics in a timely manner.

15. Lessons from similar operations applied in the design of KAZSTAT project

are:

a) Statistical capacity building (SCB) requires integrated and coordinated

support: previous experience from Kazakhstan, Ukraine, Mongolia and other countries

demonstrated that fragmented and uncoordinated capacity building activities do not result

in sustainable improvements in statistical production and dissemination. Thus, KAZSTAT

was based on SMP to ensure that support would be provided to the NSS in a systemic and

coordinated way.

b) Sustainability issues should be embedded into project design: projects are

often not sustainable once external support stops. KAZSTAT was designed to strengthen

close coordination among all KNSS stakeholders, improve institutional framework,

upgrade human resources, and build necessary physical and statistical infrastructure. It was

therefore expected that investments would be provided for the statistical system with an

active involvement of a wide range of users and producers. In turn, this would generate

new demand for high-quality data, stimulated by training, producer-user dialogue, and data

dissemination. All that would provide an additional impetus for sustainability.

c) Considerations of pros and cons for project implementation unit (PIU)

arrangements: experience demonstrated that projects in Kazakhstan could be implemented

without creating a stand-alone PIU because of strong and continuing commitment of ARKS

and its relatively developed implementation capacity. A Project Implementation Team

(PIT) consisting of relevant ARKS staffers was established within the agency. Local

consultants were hired to perform specific procurement and financial management.

d) Focus on institutional reform, going beyond data collection activities, has

greater impact on the statistical system: the project supported a review of the legal

framework, strengthening of the organizational structure and capacity building of statistical

staff in technical and management skills.

f) Twinning arrangement between the National Statistical Office (NSO) and a

well-developed NSO (or a consortium of such offices) to provide technical assistance and

training. It was decided that in case of Kazakhstan twinning arrangement between ARKS

and advanced European statistical offices could be a better approach instead of hiring

several consulting firms or individual consultants. In the long-term this could also allow

for building lasting partnerships that go beyond the project life. Creation of Consortium of

six European NSOs under the KAZSTAT followed this general recommendation.

5

16. Overall, the PDO was clear, and relevant to Kazakh country’s strategy and

conditions, key CPS pillars, the needs of the entire KNSS and the ARKS. The PDO

appeared to be reachable within the planned project life of five years with available funds

fully disbursed.

17. To achieve the project objectives, the following implementation and

governance arrangements were proposed. Institutional arrangements were designed to

integrate project implementation into regular operations of the ARKS, the project

implementing agency (see paragraph 15, c). The PIT coordinated day-to-day project

activities, managed reporting and auditing activities and ensured compliance with the

procurement, disbursement and financial management policies and procedures. Other

technical activities were the responsibilities of ARKS staff who managed them with the

assistance of local and international consultants. The project aimed at improving the whole

national statistical system, thus, the appropriate level of commitment and support was

ensured from various Government ministries and agencies through establishing an inter-

agency Coordination Working Group (CWG) headed by the ARKS Chairman with

responsibility to oversee and strategically monitor the project implementation. Attention

was paid to coordination of activities with other multilateral and bilateral development

agencies to avoid duplication and inefficient use of funds. Development partners

participated in the CWG meetings. Twinning arrangements were put in place.

18. The main risks and mitigation measures were appropriately identified. The

overall risk rating at project design was Moderate. The main risks identified and their

mitigating measures are presented in Annex 4, based on the PAD (page 24, Implementation

section, D).

19. Project preparation process cycle took two years. This average for project

preparation pace in Kazakhstan was maintained due to project team experience in similar

operations and introduction of a set of standard approaches, continued support from CMU,

strong commitment and well-coordinated work of the ARKS and Government authorities.

2.2 Implementation

20. Overall the project was implemented successfully with regard to its objectives,

initial design and agreed implementation arrangements. Despite some operational

environment conditions (see para 24) the project not only met its targets, but also completed

several innovations in Kazakh statistics. As of project closing date (April 30, 2017), almost

all KAZSTAT project funds were disbursed. The amount of US$ 48,781 of loan proceeds

(0.2 percent) was cancelled in due course.

21. The project was implemented according to the original design and did not

undergo any restructuring or major change. It was smoothly implemented and has never

been assigned “at Risk” status. The MTR mission was conducted within the planned dates.

A 2014 MTR report was prepared in a timely manner, presenting positive assessments and

was discussed in due course. Its recommendations were elaborated by the ARKS, however,

there were limitations to the scope of corrective actions. It was considered to address them

6

not necessarily within the project (Annex 4: Mid-Term Review findings and

recommendations).

22. Project implementation faced minor start-up delays that were effectively

addressed by the ARKS and project team. As in many investment operations, the early

stage of KAZSTAT implementation included minor delays. Due to the complexity of work

program and longer inception phase, the actual execution of Consortium contract started

eight months after its signing. However, both Consortium and ARKS teams gained

implementation speed quickly.

23. Strong inputs from the Consortium to project implementation. As it has proved

effective in some other SCB projects, Consortium of twinning partners was invited to

support implementation of the project, to be led by German DESTATIS and to include five

other European Statistical Offices (Statistics Finland, Czech Statistical Office, Statistics

Korea, Federal State Statistical Service of the Russian Federation and State Office of the

Slovak Republic). The Consortium has played a strong and positive role in delivery of

technical assistance (TA), design of surveys and provision of training for capacity building

components. In financial terms, the Consortium was involved in almost 60 percent of

project financed activities. Annex 5, Table b on Outputs by Project Components has a

detailed description of the Consortium’s work.

24. The project operational environment. There were several potential risk factors

that ARKS and the project team were facing: (i) changes in leadership of the national

statistical office – however, the transition process was handled well by both parties,

including closer supervision and intensive CMU dialog with new counterparts, and didn’t

affect the project implementation; (ii) limited prior experience in managing institutional

development projects – this was mitigated by ARKS attention to project implementation,

Consortium’s responsible work, strong PIT and Bank supervision.

25. There was also a favorable condition for smoother project implementation. In all

countries, execution of large complex WB statistical projects couples with regular work

performed by the NSO that includes large country-wide operations such as periodic

censuses or surveys. Unlike in other countries in Kazakhstan there was no additional

workload related to conducting censuses during the project life. Hence, the ARKS/

CSMNE had the luxury of concentrating fully on project implementation during all five

years, with no distraction on large scale nation-wide activities.

26. Operational risk downgraded from Moderate to Low. In the PAD, operational

risk rating, after mitigating measures was identified, was moderate. Hiring a competent

PIT within the ARKS and signing a contract with the Consortium of well-established

statistical offices led to justified downgrading of operational risk to Low. Timely

preparation of relevant procurement materials, completion of quite difficult ICB process,

timely submission of quarterly financial report, and delivering of project results were part

of the evidence for the risk to remain low. After signing a contract with the Consortium of

well-established NSOs and hiring of competent project team under the ARKS the

operational risk was downgraded to low.

7

2.3 Monitoring and Evaluation (M&E) Design, Implementation and Utilization

27. Overall, the Results Framework was adequate for progress monitoring

purposes. The high-level outcome indicators either had target values or were descriptive.

The intermediate indicators covered the whole range of project activities and were adequate

in number. Baseline information was largely ready at the time of appraisal and was either

descriptive, or had a value or, if missing before project launch, was provided shortly after

the project started. The RF included synthetic quantitative indicator to measure project

achievements, i.e. the user satisfaction survey (USS) based on the internationally

recognized methodology. The survey questionnaire includes questions on simplicity of

access to data, its accuracy and reliability that makes the survey results relevant for

assessing the improvements in data production and dissemination. In addition, the

efficiency of statistical system is indirectly measured by the description of achieved

improvement in physical infrastructure that ensures broader use of modern techniques that

made data collection and processing, faster and less subject to error. Use of tablets with

direct access to integrated data systems, new user-friendly cabinet for respondent to fill in

the statistical forms online reduced the time and overall respondent burden, decreased the

workload per unit and, hence, improved efficiency of statistical system performance.

28. Tracking progress towards the desired outputs and outcomes was supported by

monitoring and evaluation activities. These included project progress reports prepared

jointly by the PIT and the Consortium; minutes of meeting of the KAZSTAT CWG; Aide

Memoires of supervision missions, ISRs; the Interim Financial Reports (IFRs), audit

reports, the MTR report. Indicators for monitoring and evaluation of project progress were

updated regularly.

29. Overall, the RF provided sufficient basis for project monitoring and relatively

robust assessment of results. At the same time, for example, PDO level indicator –

statistical products are easily accessible in relevant media with metadata and interpretation

of findings – was reported to be exceeded by 10 times. This assessment is based on the

number of CSMNE website visits. On one hand, the sharp increase in the number of visits

resulted from introduction of on-line statistical reporting and decrease of the hard copy-

publications, availability of TALDAU database. Thus, it can be linked to improvements

introduced into CSMNE work through the project. On the other hand, this increase partly

happened due to a very rapid and broad dissemination of internet in the country,

improvement in connectivity, and possibility for increasing number of enterprises and

citizens to possess and obtain computers and other devices needed. Though the indicator

is still seen as a reflection of the attribution of the achieved results to the project, the ICR

team could suggest using in addition such indicators as (i) a share of those who have found

the sought-for information and (ii) the number of downloads of reports and datasets from

the website.

2.4 Safeguard and Fiduciary Compliance

30. There were no safeguard policy issues with this project, rated as a category C. The

project focused on institutional reforms and capacity building without any civil works and,

thus, no environmental impact.

8

31. Fiduciary compliance. The KAZSTAT project complied with all applicable Bank

policies and was entirely consistent with the relevant Operations Policy Guidelines. Lack

of capacity in procurement and financial management in ARKS was identified during

project preparation with a risk rating Substantial and Moderate respectively. At the project

onset, performance varied, but it improved during project implementation and remained

consistently satisfactory. No mis-procurement was identified. No overdue IFRs.

32. All legal covenants were respected as agreed in the Loan Agreement.

2.5 Post-completion Operation/Next Phase

33. Certain steps have been taken to maintain project benefits. Part of project

results has been institutionalized and could be sustained (see Annex 6, Table 6.b – the

underlined project outputs and activities have been introduced by the CSMNE in its regular

work). The Government has ensured that recurrent and maintenance costs for the

equipment acquired under the project are adequately covered by the budget allocations. A

new SMP for 2017-25 has been prepared and discussed before project completion.

34. As for the next steps, the CSMNE identified areas for consolidating lessons and is

building on project achievements. A new US$ 100,000 project to move to the SNA 2008

and to develop the Sustainable Development Goals (SDGs) roadmap has been recently

approved under the JERP, currently financed fully by the Kazakh Government (Annex 6:

Follow up Technical Assistance). The expertise and experience acquired by the CSMNE

during KAZSTAT implementation will be further strengthened during the implementation

of this new project.

3. ASSESSMENT OF OUTCOMES

3.1 Relevance of Objectives, Design and Implementation

Relevance of Objectives Sub-rating: Substantial

35. The PDO (to improve efficiency and effectiveness of the national statistical

system) remains relevant and consistent with Kazakhstan current development priorities

outlined in the “National Plan – 100 Specific Steps to Implement Institutional Reforms”

and the Bank’s engagement to support them. Requirements to statistics are growing as new

developments and challenges emerge. In particular, new needs emerge as population well-

being is increasing but issues of inequality and shared prosperity become more important,

issues of sustainable development, globalization, increase in international competition and

migration need to be tackled. Increase in requirements to statistics is rarely accompanied

by proportionate increase of resources to solve the tasks. This contradiction can be resolved

only by means of improving efficiency and effectiveness of the statistical system.

36. State programs of the Republic of Kazakhstan associated with further

development of official statistics.

9

• Step 96 of National Plan provides for ensuring on-line availability of statistical

databases of the central Government authorities, seems to be important from the

perspective of state statistics development. All budgetary and consolidated financial

statements, external financial audit results, results of state policy effectiveness evaluation,

results of public evaluation of state services quality, report on republican and local budget

utilization should be published. This increases the opportunity of the CSMNE in using the

administrative data. • “Strategic Plan of Development until the year 2020” provides for calculation of

several social and economic indicators by the state statistics to monitor the goals set by this

plan.

• State program “Information Kazakhstan - 2020” provides for extensive measures

to ensure effectiveness of the public administration system, in particular - ensuring

integration of information system of the CSMNE with information systems of other

Government authorities (it is planned to integrate additional six information systems of

Government entities in the next two years).

37. The recently endorsed Sustainable Development Goals (SDGs) – the 2030 - Agenda

aims to measure 169 targets by 230 indicators spanning across social, economic and

environment pillars. No one country could produce all required data and indicators to

measure the SDGs. Even the advanced economies such as United States, Canada and

Netherlands announced that they could produce 40 percent of the required statistics. The

CSMNE is expected to play an important role in this matter/endeavor.

Relevance of Project Design and Implementation Sub-rating: Substantial

38. Project design was consistent with the PDO and targeted critical areas for

achieving them. The selection of sub-activities was notably relevant insofar as it was based

on the GA, NSDS and SMP diagnostic. KAZSTAT project design was informed and

grounded in the long-term engagement and technical support provided by the Bank and

other development partners. Technical assistance provided during project preparation

addressed the most pressing needs and ensured consistency in the design of the project.

39. The actual implementation of the project was relevant to the achievement of

the PDO. First, the decision to assign project implementation to ARKS contributed to

building overall experience and capacity of the ARKS/ CSMNE, assuring project

ownership, and strengthening the Kazakh statistical office internally, all of which

contributed to the achievement of the PDO. Second, the introduction of the twinning

arrangement with advanced European national statistical services was a positive initiative

in attaining the PDO, in terms of knowledge obtaining/ sharing, direct access to relevant

processes and procedures, and experience exchange.

40. In terms of process:

• Component A (Improvement of the Institutional Framework and Operations of the

Statistical System) was 100 percent complete with 29 out of planned 29 activities

implemented;

10

• Component B (Improvement of Information and Communication Systems and

Physical Infrastructure) was 100 percent complete with 21 out of planned 21 activities

implemented;

• Component C (Improvement of Human Resources) was 100 percent complete:

after revisions of procurement plan 55 activities were implemented compared to initially

44 planned;

• Component D (Improvement of Statistical Infrastructure, Standards and

Methodology) was 100 percent complete: 58 – two tasks were combined- out of planned

59 activities implemented;

• Component E (Improvement of the User Relations Policy) was 100 percent

complete with 21 out of planned 21 activities implemented;

• Component F (Improvement of Individual Subject Matter Programs and

Methodologies) was 100 percent complete: after revisions of procurement plan 260

activities were implemented compared to initially 256 planned.

Overall Relevance Rating: Substantial

3.2 Achievement of Project Development Objectives

Efficacy (achievement of PDO) Rating: Substantial

41. Almost all the targets set out in the RF were met and two overachieved. By the

end of the project, two PDO level outcome indicators exceeded the target, one – was

achieved in full and one was achieved partially. All intermediate results indicators were

achieved except for one indicator which target value was also almost met.

42. To assess the extent to which the KAZSTAT project achieved the PDO level

results, the causal relationship between project inputs, outputs and outcomes were

reviewed, as outlined in Annex 6 Table 1.a, Attribution and Results Measurement. It is

difficult to attribute achieved results with full certainty, especially in small institution

strengthening and capacity building projects. ICR team noted that at the time of project

implementation KAZSTAT was the only focused intervention aimed at statistical capacity

building. There were no other initiatives or significant donor-funded activities in statistical

development in Kazakhstan. In some years, the project inputs constituted up to more than

16 percent of financial resources available to the CSMNE. Based on these considerations,

results assessed can be most likely associated with the project. In assessing results, the ICR

team considered those that can be causally attributed to project activities.

43. The project has achieved its development objective through institutional

changes, technical innovations and ICT expansion. Annex 6 Table 1.b, Outputs by

Components and Sub-components presents key project outputs in a very detailed way and

with an important separation of what has been done by the Consortium and ARKS/CSMNE

on its own. The following is project contribution to increasing KNSS efficiency and

effectiveness:

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(a) Efficiency

• Introduction of an integrated processing system throughout the country coupled

with a starting optimization of the workload between central and regional offices;

• Integration of CSMNE information systems with 21 information systems of other

Government authorities;

• Establishment of the Working Group to design and introduce the personal workload

recording system that leads to optimization/decrease of workload per staffer;

• Adoption of methodology for estimating the costs of statistical surveys and

development of control system over the costs;

• Introduction of new methods of electronic based survey interviews: (i) household

surveys and price registration on CAPI basis, (ii) telephone interviewing on CATI basis,

and (iii) mobile apps in the Integrated Information System (IIS) e-Statistics;

• Modernization of the CSMNE network equipment: high-performance switch hubs

and safety equipment are installed and operated;

• CSMNE shifted the households’ book record maintenance in rural akims (local

Governments) from paper to electronic format that resulted in reducing the burden and

improving the quality of data entry in agricultural statistics;

• Introduction of R-software into practice of sampling design for statistical surveys,

development of program codes and automated sampling design processes – considerable

reduction in time spent on sampling design;

• Introduction of respondent office (on the CSMNE site) based on the one-window

approach.

(b) Effectiveness

• Increase in using the administrative data based on the improved intergovernmental

coordination;

• Positive changes in the organizational structure of the ARKS/CSMNE with a right

division of labor;

• Introduction of quality management approach (quality control program of statistical

activities for 2014-2016, GSBPM model, QMS documentation revised, Generic

Methodology of stat information production by public authorities developed, Quality

guidelines, training on quality assurance tools);

• Expansion of data user: scientific organizations received an official access to the

databases, including the anonymized microdata;

• Introduction of international standards (example): per experts’ assessment

(DESTATIS, Germany) all aspects of sampling surveys are in line with international

standards;

• Adoption of methodology for seasonal adjustment for all major indicators

developed on a monthly and quarterly basis, preparation of regressor calendar to filter time

series from calendar effects, performs procedures of seasonal and calendar adjustments;

• Establishment of pre-test laboratory etc.

43. Project high level achievements and intermediate outcomes can be outlined as

following:

12

• User satisfaction reached a remarkable level of 94.4 percent as documented by the

final round of 2016 USS. The CSMNE planes to conduct the USS once in two years.

Positive results were achieved due to implementation of the new forms of dissemination of

data (TALDAU central database system, extension of dissemination of data via improved

websites of CSMNE and regional statistical offices, and ministries).

• Statistical products with metadata are now easily accessible. According to the

statistics of visits on the central website of the ARKS/CSMNE, the number of visits was

growing exponentially. The indicator value reached 4 million and suppressed the modest

end target of 400,000. Acceleration of the number of the website visits was observed after

the implementation of the TALDAU database, metadata system, modernization of websites,

reduction in paper publications (see paragraph 29). Dissemination of statistical data and

metadata via CSMNE and other data producers’ sites will be a basic channel of accessing

statistics by the users.

• Internationally accepted statistical techniques in collection, compilation, and

authenticity verification are applied and regular validations are carried out for data

sources and statistical products for most statistical areas. The ARKS/CSMNE has

elaborated the programs of systematic implementation of international standards in the

field of basic statistical data, with special reference to national accounts. The introduction

of national accounts standards in practice has taken place. Significant improvements due

to using these standards in CSMNE paratactical work, data collection, verification and

dissemination were confirmed by the experts. It is estimated that 95 percent of

classifications used by CSMNE shall fully comply with the international standards.

Currently Kazakh statistics is compiling all basic data following UNSC, IMF, WTO

standards and recommendations on methodology and timeliness.

• Statistical outputs are released within the time limits and with frequency, meeting

the SDDS requirements. The scope of indicators compiled by the ARKS/CSMNE fully

covers the requirements of the SDDS since 2014. Schedules of compiling, disseminating

and transferring statistical indicators to national and international agencies are the part of

the statistical program adopted by the Government. They are mandatory for CSMNE and

for other producers of official statistical data. Release calendar is available on the website.

Project activities aimed at reducing the respondent burden. The latter has been reduced by

20 percent, thus, the response rate and timeliness of data production improved notably.

• Inter-agency coordination mechanism established and operational. The CSMNE

coordinates statistical actions and collection of official data. Amendments on

intergovernmental coordination to the current Law have been developed and submitted for

ratification; staff from other ministries participated in the vast project training that led to

creation of community of good practice; and MOUs signed. Administrative data

submission rules and other documents for using data for statistical purposes are now

updated on regular basis. All these shaped the favorable conditions for larger use of

administrative data and, hereby, higher effectiveness of the whole KNSS.

• Mechanisms for effective dialogue with the data users and providers are

operational. The establishment of pre-test laboratory was completed, tested and now ready

for operation. This, will allow for further improvements in questionnaire, other statistical

13

forms and ministerial websites design. In its turn, it will lead to reduction in respondent

burden.

• CSMNE central and local level structure was optimized and staff trained including

staff from relevant ministries and agencies. The KNSS has entered the process of deep

modernization of organization and technology of collecting of data, integrated processing

of statistical data and metadata and ICT-based dissemination. Full implementation of e-

questionnaires from legal entities and individual entrepreneurs as well as the e-interviewing

shall create new conditions for division of responsibilities between the CSMNE, regional

and local statistical units. The organizational structure in CSMNE central office was largely

improved. Number of staff trained exceeded initial plans. Share of trained staff in the

regional offices increased.

• Registers are compiled and being maintained. Business, Population, Housing stock

and Agricultural registers are properly setup and getting ready to generate samples. More

specifically, Business, Population and Housing facilities registers have been updated and

complied in line with international standards. Comprehensive business register database

created, business register management system developed. Online database system for

population and household surveys was developed and is functional. Agriculture register

has been also updated with a plan to use new technology in survey. The development of e-

Government has created favorable conditions for regular updating of statistical registers in

electronic form based on relevant administrative registers managed by the Ministry of

Justice, Ministry of Internal Affairs, Ministry of National Economy and Ministry of Labor.

• Internationally accepted classifications standards and methodologies are adapted

and used in data production. Evidence of successful introduction of international standards

into statistical practice: 39 new methodology were developed and adapted; 41 - were

improved to be in line with international standards; 128 new indicators were developed; as

evaluated by the international experts the National accounts, Structural statistics, Price

statistics, Industrial statistics, Construction and investment, Agriculture statistics,

Environmental statistics, Services and ICT statistics are in line with international standards

and classifications.

• Standard questionnaires for surveys developed and applied. The CSMNE has

prepared questionnaires for several industries and piloted them. According to experts’

assessment, the questionnaires are well designed; implementation of construction statistics

is comparable with European practice; revised questionnaire for ICT statistics survey and

indicators provided to the ITU are robust and suitable.

• ICT capacity for operations is adequate and well maintained. Physical

infrastructure was substantially modernized. All procurement activities for the ICT

(hardware and software) needs were completed. The current level of the ICT in the CSMNE

both at the central and in regional offices is up-to-date for the purposes of technological

capacity and organization of surveys and dissemination of data. The CAPI system was

successfully piloted in February 2017 and was put into nationwide operation for universal

application in July, 2017. The CAPI will become the regular method of data collection for

labor force, price and household surveys. Installation and testing of CATI was completed

14

in June 2017 with a view that introduction of primary data collection in agriculture with

CATI system could be conducted already in 2017.

• All relevant staff at CS have workstations with access to databases for analysis and

tabulations, access to Internet and information system of 21 other ministries, and have been

receiving latest tool and package as per KAZSTAT activities such as R-software, program

for survey design and etc. The project purchased 1550 personal computers and

uninterrupted power supplies, 16 servers and 48 network switches, 832 tablets for central

and regional offices. Overall, the quality of hardware and software have been improved.

44. In addition, several specific project achievements could also be mentioned:

• Data User survey are conducted regularly based on the international methodology;

• Increased data access and user-friendliness in dissemination is supported by newly

established CSMNE Department of publications and dissemination of statistical

information and Call-center;

• Upgrading of staff knowledge and skills, building strong professional self-

confidence within the CSMNE staff at central and sub regional levels;

• Training extended to statistical staff in other line ministries;

• Management issues studied and being introduced in ARKS/CSMNE; and

• Improved English-language proficiency of statisticians.

45. The project has raised awareness and interest in statistics through (i) a new

dissemination policy; and (ii) modernization and unification of the CSMNE central and

reginal website, including a powerful data portal with micro datasets etc.

46. KAZSTAT project was initiated as an instrument of accelerating adjustment

of the ARKS/CSMNE and the KNSS to (i) new information needs of users of statistical

information, with special reference to the needs of Governments, businesses, researchers

and the public, (ii) new information environment of the economy, society and statistics,

created by dynamic development and wide use of modern ICT, (iii) progress in

technological and organizational modernization of the information systems of

Governments and businesses, and (iv) impact of globalization processes on the information

infrastructure of the country. KAZSTAT project was playing a catalytic role for

development, speeding up all the processes bringing the CSMNE on a higher level of

performance.

47. As mentioned by the counterparts, KAZSTAT project provided unique

opportunity to implement an intensive, complex and vast training program within

relatively short period, to introduce new methods of electronic based survey interviews,

and establish the pre-test laboratory.

48. Evidence from international sources. International organizations have confirmed

the current high level of Kazakhstan's statistics:

15

(a) After previous the 2008 GA, the Kazakh statistical system underwent a

similar evaluation at the time of project completion. The 2017 Global Assessment was

conducted by three organizations: United Nations Economic Commission for Europe,

Eurostat and Free Trade Association. Their report has recorded significant progress in

Kazakhstan's statistics, giving it a “leading position in the Central Asian region, and

encouraging sharing experience on methodology”. It also acknowledges the positive

impact of KAZSTAT project in several areas and provides in-depth recommendations on

further improvements for the KNSS and the CSMNE.

(b) IMF Article IV Consultation report (April 2017) assesses data adequacy

for surveillance in Kazakhstan as “broadly adequate though data provision has some

shortcomings”.

• On national accounts the CSMNE has made considerable progress in improving

the statistical infrastructure and updating the business register with full coverage of legal

entities and individual entrepreneurs. Annual estimates of oil and gas sector are compiled

and disseminated following international standards, but only in Russian. The CSMNE also

compiles quarterly GDP, but on a cumulative basis—instead of a discrete basis—and using

“comparable prices” instead of fixed base or previous year prices.

• Kazakhstan has a monthly Consumer Price Index (CPI) which is used for many

purposes. It is broadly appropriate, however, there is a window for improving its quality.

• Annex 7 “Statistical Performance of Kazakhstan -2016” presents a new Statistical

Performance Indicator (SPI) developed by the Bank to assess performance of the NSS and

replace the previously used Statistical Capacity Indicator. The SPI can serve as a

benchmark for future assessments of the development of the KNSS and its comparison

with other countries.

Achievements of Objectives Rating: Substantial.

3.3 Efficiency

Efficiency Rating: Substantial

49. As stated in the PAD, the project is not amenable to a cost-benefit or economic rate

of return analysis. National statistical offices are not involved in any cost-recovery

activities, apart from marginal data publications that generate minor amount of revenue.

The financial returns from this project will not be representative of the economic returns.

Precise quantitative rates of return cannot be determined for this type of project. The ICR

team judges overall efficiency to be substantial. As highlighted by the MTR report, the

project achieved its targets through efficient use of resources and investments. All planned

activities were completed with no project extension. Initial minor delays in project

implementation were effectively resolved with the joint effort of the ARKS/CSMNE and

project team, resulting in full project funds disbursement in a timely manner. Broadly, the

economic benefits from the project could be based on the following: (i) improved

efficiency of statistical operations of the CSMNE, resulting in a broader coverage of and

16

higher quality data that contributes to better functioning of multiple sectors of economy

and society; (ii) better quality data will enhance the potential for evidence-based decision

making at policy, program, and project levels; (iii) a significant reduction in the cost of

data collection through improved systems as well as by moving from full count censuses

to sample surveys.

50. During the ICR team meetings and discussions the counterparts from the CSMNE,

MNE, and MOF mentioned that the project funds were being used efficiently on targeted

activities with consideration for “value for money” and strict spending controls.

3.4 Justification of Overall Outcome Rating

Rating: Satisfactory

51. The project has helped to improve efficiency and effectiveness of the national

statistical system of Kazakhstan to provide relevant, timely and reliable data in line

with international standards. The KAZSTAT was a relevant and timely intervention. The

improvement of the efficiency and effectiveness of the statistical system has been achieved

as evidenced by the production and dissemination at lower costs of better quality data in

almost all areas of economic and social statistics. The immense training of statisticians and

the adoption of new techniques and methods, introduction of international standards have

improved data relevance, timeliness and reliability. The statistical system has become

better coordinated and more dynamic. KAZSTAT project triggered the long-term reform

process, led to increasing data production, and sped up several data collection processes on

the ground. It also successfully overcame all minor issues related to implementation. In

terms of PDO relevance (Substantial), achievements of the PDO (Substantial), efficiency

(Substantial) the project performed at a level consistent with a Satisfactory rating.

3.5 Overarching Themes, Other Outcomes and Impacts

(a) Poverty Impacts, Gender Aspects, and Social Development

52. The project prioritized cross-sectoral issues in statistics, including statistical

infrastructure, SNA, structural statistics, price statistics and other. It was not

specifically focused on social objectives, but had an overall positive impact on improving

socio-demographic, labor statistics and statistics of standards of living by strengthening the

capacity of the ARKS/CSMNE and sub-national statistical bodies. The project had only an

indirect impact on poverty reduction by improving the quality of related data through

introducing international standards into survey methodology, strengthening technological

basis for data collection, simplifying means of communication, reducing the response

burden etc. Under KAZSTAT project, the CSMNE developed a national system of gender

indicators based on best international practice. By providing a steady supply of reliable and

timely social and economic statistics, the CSMNE will contribute to policy making and

monitoring processes in the areas of social development and gender issues.

17

(b) Institutional Change/ Strengthening

53. The CSMNE has strengthened its institutional capacity. This could be

supported by the following evidence: (i) harmonization of statistical legislation with

international recommendations (UN Fundamental Principles of Official Statistics, EU

Code of Practices), which provided the basis for the institutional change of the whole

statistical system, including strengthened collaboration between the CSMNE and other

relevant Government agencies; (ii) optimization of organizational structure (by the end of

the project the new departments and units have been created; (iii) improved management

capabilities; and (iv) significant upgrade of staff expertise and skills.

54. New institutional status of national statistical office of Kazakhstan. In 2014 the

ARKS position was changed due to the administrative reform when all Government

agencies in the country have been moved under the ministries. Thus, ARKS lost its status

of an autonomous Government agency and became a part of the Ministry of National

Economy – CSMNE. This arrangement contradicts the UN Fundamental Principles of

Official Statistics that imply autonomous status of the NSO for the purposes of professional

independence. There are multiple examples of national statistical offices in the developed

countries successfully performing their functions as part of one or another ministry.

However, in Kazakhstan insufficient transparency in the government culture, weak checks

and balances system in Government apparatus make the case different and call for closer

attention and monitoring of the implications of this institutional change.

55. It should be also noted that the KNSS has entered the process of deep modernization

of organization and technology of collecting of data, integrated processing of statistical

data and metadata and ICT-based dissemination. Full implementation of e-questionnaires

from legal entities and individual entrepreneurs as well as the e-interviewing shall create

new conditions of division of responsibilities between the CSMNE, regional statistical

offices (oblast) and local statistical units (rayon). The management of the CSMNE is aware

of the consequences of technological changes for optimizing the structures on central and

territorial levels. The KAZSTAT project provides a good basis for future development

of organizational concept for the KNSS in new technological environment resulting

from e-Statistics and e-Government implementation.

(c) Other Unintended Outcomes and Impacts (positive or negative)

56. No negative unintended outcomes were observed.

3.6 Summary of Findings of Beneficiary Survey and/or Stakeholder Workshops

57. Overall client’s views on project implementation and results were highly

positive. The concluding workshop of the KAZSTAT project was organized in November

2016, with the participation of key stakeholders, including Government, consortium

members, development partners, media, academia and other users. During its two mission

to Kazakhstan, the ICR team met the direct beneficiaries of the project in Astana. There

was also a visit to Astana city statistical office and a separate meeting with respondents.

The interviewed beneficiaries of the project considered that the project was timely and

18

important in bringing the KNSS in line with internationally accepted standards; that it

positively influenced their own professional development and skill sets which, in turn, built

their confidence in their own capacity to operate in a more efficient way. The project helped

to significantly reduce the response burden, to increase the reliability, timeliness and

quality of statistics produced in the country, and, hence, to bolstered trust in the statistical

system. Beneficiaries also stated that the capacity of their respective agencies to collect,

process, disseminate data, and respective institutions to use, understand the data had

significantly improved, and they would be able to sustain these gains in coming years.

4. ASSESSMENT OF RISK TO DEVELOPMENT OUTCOME

Rating: Moderate

58. The prospects of maintaining the project’s development outcomes are

relatively strong, especially in the short-term. Some of the project’s achievements have

already been institutionalized at the central level (see paragraph 33). The CSMNE has

shown very strong commitment. The objectives of the project remain relevant. There are

post–operational steps that have already been taken (section 2.5).

59. Factors in favor of greater sustainability:

(i) CSMNE focus on institutional reform, going well beyond factors of better

data collection; it keeps issues of statistical system architecture and overall efficiency on

the radar screen (the project supported a review of the legal framework and capacity

building of statistical staff in technical and management skills);

(ii) Interactive and consultative process with Government, academia, the

private sector and development partners supported by the project (in keeping with this

approach, project implementation aimed at active involvement of a wide range of data users

and producers, their training, the strengthening of user-producer dialogue and data

dissemination to stimulate a stronger demand for high quality data, that in turn, contributes

to sustainability once external support stops);

(iii) Possibility to maintain the high level of professional/business relationship

with several national statistical offices and their experts that participated in the Consortium

twinning arrangement under the project;

(iv) International exposure will stimulate interest to maintain quality of

statistical system. CSMNE is a member of numerous Working Groups under UNESCAP,

UNECE, OECD, WHO etc. Cooperation with Eurasian Economic Commission (EEC) is

one of the CSMNE focal areas of international activity. Such exposure has positive

influence on the statistical office to develop relevant new approaches to measuring, for

example, contribution of natural resource-based activities and their impact on social sectors

and the environment;

(v) Emerging CSMNE engagement in development partnerships will also

stimulate focus on quality. As Kazakhstan is emerging as a source of technical expertise in

the Central Asian region and beyond, there will be additional desire to maintain the quality

of the NSS. The recent example is Kazakhstan involvement in Kyrgyz and Tajikistan

19

statistical projects where the CSMNE colleagues provided the TA to the neighboring

countries

(vi) Several state programs of the Republic of Kazakhstan that will support

further development of official statistics (see paragraph 36).

60. Several risks were identified that could potentially limit the prospects for the

gains to be expanded over the medium term. On the one hand, the Government has

expressed strong interest in developing its NSS, and the budget allocations for the state

statistical service are stable for regular operations. On the other hand, there is still shortage

of funds for development needs. Some additional risks and challenges include:

External/global

(i) The risk that allocation of budget resources for statistical office would not

be sufficient to catch up with on-going increase in requirements for the quality of statistic

information, its speedy development and changing composition of indicators;

(ii) Competition with non-government producers of provision of statistical

information, unconventional approaches to collect the data and new sources of data that

may present a challenge; and

(iii) Inability to respond adequately to new complex tasks from the global

agenda such as Sustainable Development Goals (data intensive initiative, require capacity

to produce statistical data of reliable quantity and quality, and effectively use them for

policy analysis and design on a scale and in a time frame is a challenge to many).

Internal/local

(i) Absence of State Statistical Council headed by the Prime Minister of the

Republic of Kazakhstan which included 21 top leaders of Government authorities

associated with development or active use of statistical data including the Chairperson of

the NBK, ministers of finances, economy, and internal affairs. In 2014 the Council was

abolished, the KNSS has no coordinating authority of that high level;

(ii) Staffing constraints - the small number, age and experience of staff relative

to the scope and complexity of activities being undertaken and planned, and the danger of

losing staff;

(iii) Risk that inflow of newly trained staff may be delayed of insufficient as the

Academy of Public Administration (APA) has only recently opened a master’s program

“Statistics” to train statisticians and the supply of trained staff will be limited for some

time; and

(iv) Reduced access to international expertise and experience after the project

closure.

61. In whole, the risk is judged to be moderate with a potential to expand to high in

the absence of longer-term corrective actions.

20

5. ASSESSMENT OF BANK AND BORROWER PERFORMANCE

5.1 Bank Performance

(a) Bank Performance in Ensuring Quality at Entry


62. Overall the project team had appropriate skill mix, substantial country experience

and strong leadership. Technical aspects of the project were well covered, and strong

business relationship was established with the Government and the ARKS. Attention was

given to engage partners and stakeholders in the preparation of the project. Lessons from

earlier operations and projects, and complementarities with ongoing initiatives were taken

into consideration and mainstreamed in the design of the project. The project activities

were fully in line with overall country needs and development objectives. Risks were

identified and pro-active mitigation measures introduced. A vital decision to go for a

twinning implementation arrangements was made and effectively executed. Maybe – more

attention could have been paid to the country context and conditions such as renewed focus

on the regional development reflected in the Bank CPS.

(b) Quality of Supervision


63. The composition of the Bank team remained stable and adequate throughout project

implementation. The responsible FM specialist, the Procurement Specialist were residents

in the Astana Bank country office. The TTLship remained at HQ having strong PIT on the

ground and strong ARKS/CSMNE ownership. The Bank’s fiduciary and procurement team

provided constant and regular advice to the ARKS/CSMNE team on areas that required

more handholding at the start. This enabled the project team to identify potential errors in

a timely manner, and/or address issues immediately. The ISRs have been prepared with

enough details and on a timely basis. Overall, the Bank’s performance did not have

shortcomings throughout the project implementation.

(c) Justification of Rating for Overall Bank Performance


64. In light of project outcomes, decent project preparation and quality of supervision

carried out, the overall performance is assessed as satisfactory. There was found an

appropriate combination of project size, its duration, correct assessment of ARKS/CSMNE

absorption capacity, and means of delivery of project results, completion of almost all

planned project activities, and disbursement of project’s funds in full with no extension.

CMU was fully on board for both project preparation and its implementation.

5.2 Borrower Performance

(a) Government Performance

21


65. From the very beginning, the borrower’s ownership and commitment were

consistent and strong. Government demonstrated continuing support, timely co-financing

allocations and leadership throughout the implementation. Other line ministries and agency

were closely collaborating with the ARKS and later – the CSMNE.

(b) Implementing Agency or Agencies Performance


66. The ARKS/CSMNE has been actively engaged in preparation and execution of

KAZSTAT project, maintaining the necessary pace of project implementation till its

completion. They nested the PIT inside the agency, engaged a full time competent and

knowledgeable project coordinator, hired reliable procurement and financial management

specialists to successfully execute the implementation. The financial management system

was run by the ARKS/CSMNE and performed well during the implementation. It recorded

all transactions and balances, and supported the preparation of regular financial statements

that were submitted to the Bank on time. All procurement of goods and services have been

conducted in line with the provisions of the Loan Agreement and Project Procurement

Plans that were approved by the Bank. No procurement compliance issues were raised

during the project implementation.

67. Progressively the twinning partnership (TP) was on track, efficiently and stably

ensured transfer of the technical expertise and practical skills to ARKS/CSMNE. The latter

has been able to learn from best international practices and has benefited from a sustained

engagement with experts and partners.

68. The progress made showed that the ARKS/CSMNE was responsive to the advice

received from consultants, e.g. on institutional and organizational issues, and human

resources, as well as in technical areas. This responsiveness is also evident from CSMNE

acceptance of the GA and other evaluations, its intention to implement recommendations

and to continue development of the national statistics through its continues improvement.

(c) Justification of Rating for Overall Borrower Performance


69. Given all achievements and results the overall borrower performance is rated as

satisfactory.

6. LESSONS LEARNED

70. Sensible consideration of lessons learned during projects preparation and

implementation under similar or related conditions and circumstances. Importance

of the lessons distilled by the Bank from implementation of large number of SCB projects.

Full and consistent application of these lessons to design and implementation of SCB

22

projects accelerate implementation, ensures increased development impact and reduce

implementation risks. Lessons learned comprise country- and sector specific experience

that emerged during KAZSTAT implementation.

71. Senior management commitment/ownership and championship. Agency senior

management ownership and leadership are key for smooth implementation of large

complex development projects. Despite the changes in the ARKS/CSMNE senior and

middle management team there was a continued (a) understanding of project objectives

and support for its success, related decision making and management of the project; (b)

clear understanding of how the project is helping in development of the institution; and (c)

deeper knowledge of the broad sector reform process.

72. Effectiveness of explicit phasing of project implementation. KAZSTAT project

was very intense in training and education. Knowledge transfer and capacity building –

“education stage” – prevailed at the beginning of project implementation. Prioritizing

human development and staff skills during initial phase of the project allowed to develop

ownership among broader cadre of statistical system staff and to enhance further project

implementation. At the same time, there should be a follow up phase of actual practical

usage of the knowledge and skills accumulated and their transformation into day-today

practice and improved data quality.

73. Certain degree of flexibility built into a project. This should be designed form

the very beginning, to allow adequate responses to new challenges and opportunities that

more often emerge at the time of swift technological (ICT, digitalization etc.), governance

and international environment changes. In modern life for statistics (especially official

statistics) there are many new challenges rapidly emerging from inside the system as well

as outside with a very strong and not always clear impact on the further development.

74. Importance of regional and local focus in designing statistical projects were

appropriate. Regional and local dimensions in project design and implementation should

be quite explicit for large countries with significant differences across the regions or

complicated territorial structure, and where excessive centralization tradition is particularly

strong. The project has provided many benefits for regional and local statistical offices and

large groups of population and data users. For future operations regional dimension should

be explicitly and clearly articulated and reflected in project design.

75. Importance of early consideration of borrower national conditions that could

potentially influence project implementation. The KAZSTAT PIT was instrumental in

addressing the challenges caused by the budget cycle, related rules and procedures, high

volatility of the exchange rate and necessity of timely payments under the contracts in

foreign currency; and successfully maintained the financial management of the project on

satisfactory level. It could be suggested to negotiate more flexible payment schedule under

the contracts to avoid pressure caused by fluctuations of external fiscal environment.

76. Relevant organizational home and institutional arrangement for project

implementation team. KAZSTAT project was implemented by a PIT within the

23

ARKS/CSMNE with support of a small group of qualified and experienced consultants

which was been the right solution as all project components were centrally implemented,

even in cases where they benefited other agencies. However, this arrangement might need

to be reconsidered for more decentralized implementation of project components under

projects with several participants such as other ministries and committees.

77. Importance of close coordination of relevant ICT programs and entities

engaged in their design and implementation. Coordination and collaboration between

ICT work undertaken within statistical systems and broader national ambitious e-

Government initiatives and ICT/digitalization progress in the private and business sector

throughout project implementation will bring additional value and synergy as well as time

savings. These client Government and business community solutions might offer unique

opportunities for innovation in statistics and efficiencies through application of big data,

utilization of ICT networks and services of ICT providers.

78. Attention is needed to the role of TP as strategic partner, advisor and mentor

to the country implementing agency. The TP should be designed with country specific

context in mind and include both global leaders in statistics that bring cutting edge

international experience and agencies with recent development challenges, experience on

how to address them and conditions similar to the client’s ones. This combination would

permit to strengthen creative work of the consortiums, develop country relevant contextual

solutions and reduce the risk from consortium members to push for mechanistic replicating

(no customization) of their own experience in partner country. The following elements for

TP success under KAZSTAT project were: clear objectives for TP; relevance of

activities/components; use of well elaborated R&M framework; strong ownership of all

parties involved; availability of in-house technical expertise for the twinning

partner/consortium; strong managerial and staff capacity for delivery the

expertise/training/activities; sufficient political support on client side; capacity to handle

the TP arrangements by implementing agency.

79. Additional attention needed for project outcomes/impact to be

achieved/maintained beyond the scope of project implementation and longer term

sustainability of project results. This primarily would depend on the Government and

senior management of the NSO. On the Bank side this can be stressed through continuous

policy dialog, modification of result framework (including the indicators that would

capture the first results from introduction of new products into regular practice), adding to

set of activities a mandatory piloting of the initiatives prepared.

7. COMMENTS ON ISSUES RAISED BY BORROWER/IMPLEMENTING AGENCIES/PARTNERS (a) Borrower/implementing agencies

As of October 26, 2017, no formal comments were received.

(b) Co-financiers

N/A

24

(c) Other partners and stakeholders

N/A

25

KAZAKHSTAN


ANNEX 1: KAZSTAT PROJECT– RESULTS FRAMEWORK

Results Framework – Key Indicators (as outlined in the PAD)

PDO Project Outcome Indicators

The main objective of the project

is to improve efficiency and

effectiveness of the Kazakh

National Statistical System

(KNSS) to provide relevant,

timely and reliable data in line

with the internationally accepted

methodology and best practices.

Access to information/ dissemination

1. User satisfaction rates have significantly increased by the

Closing Date

2. By the Closing Date, targeted statistical products are easily

accessible in relevant media, with metadata and interpretation

of findings.

Coverage/ Accuracy / Reliability:

3. By the Closing Date, internationally accepted statistical

techniques in collection, complication and authenticity

verification are applied by the Recipient, and regular

validations quality control measures are carried out for data

sources and statistical products.

Timeliness:

4. By the Closing Date, statistical outputs are released in a timely

manner in accordance with internationally accepted frequency

and timeframes

Intermediate Outcomes Intermediate Outcome Indicators

1. Adequate policy and

regulatory framework as well as

effective institutional

framework, management and

human resources for statistics are

in place

1.1 Mechanisms for effective inter-agency coordination are

established and operational.

1.2 Mechanisms for effective dialogue with the data users and

providers are operational.

1.3 ASRK central and local level structure optimized and staff

trained including staff from relevant ministries and agencies.

2. Statistical infrastructure

developed and made operational

2.1 Registers are compiled and being maintained.

2.2 Internationally accepted classifications, standards and

methodologies are adapted and used in data production.

2.3 Standard questionnaire for surveys developed and applied.

3. Investment in physical

infrastructure and equipment to

facilitate the production and

dissemination of data by

statistical agencies is undertaken

and adequately maintained.

3.1 IT capacity for physical operations is adequate and well

maintained.

3.2 All relevant staff at CS have workstations with access to

databases for analysis and tabulations.

26

KAZAKHSTAN


ANNEX 2: KAZSTAT PROJECT ORIGINAL COMPONENTS

Project consists of the following components (as per Loan Agreement):

Component 1: Improvement of the institutional framework and operations of the

statistical system

Providing goods, consulting services, training programs for the following purposes: a)

improvement of legislative base coordinating interaction between government agencies

producing statistical data; b) rationalization of institutional structure of Agency of the

Republic of Kazakhstan on Statistics; c) improvement of procedures and methodology of

strategic planning; d) development and introduction of system for measurement of

personnel burden; e) introduction of Quality management program; f) improvement of

equipment.

Component 2: Improvement of information and communication systems and physical

infrastructure


improvement of integrated system of data processing; b) professional development of

personnel staff of the Department of Classifications and Information Technology; c)

maintenance of computer facility and program support of ARKS in order to accelerate

process of data processing; and d) improvement of corporative communication network of

ARKS.

Component 3: Development of human resources


implementation of new methods for management, career development and practice of

appointment in ARKS; b) development and implementation of training strategy in ARKS;

c) development and implementation of program on training of ARKS staff abroad; and d)

revision of current procedures and recruitment policy in ARKS.

Component 4: Improvement of statistical infrastructure, standards and methodology


improvement of Business register; b) improvement of population register; c) improvement

of housing stock register; d) improvement of agriculture register; e) improvement of

classifications and standards; f) development of statistical toolkit; g) improvement of

quality and methods of conducting sample surveys; h) formation of time series and seasonal

adjustment methods implementation; and i) development of the analytical capacity of the

Agency.

Component 5: Improvement of work with users and respondents

Providing goods, consulting services, training programs for the following purposes:

improvement of policy on relations with respondents; b) improvement of dissemination

27

and marketing statistical information; c) improvement of policy work with respondents; d)

improvement of ARKS web-portal.

Component 6: Improvement of methodology and practice in specific areas of statistics


improvement of macroeconomic statistics; b) improvement of macroeconomic statistics

including statistics of industry, energy, construction, investment, foreign and domestic

trade and service statistics; c) improvement of agriculture statistics; d) improvement of

social statistics; e) improvement of labor statistics; and f) development of environmental

statistics.

Component 7: Project management

Providing goods, consulting services, training programs and operational costs of ARKS for

Project management, implementation, monitoring and assessment.

28

KAZAKHSTAN


ANNEX 3: PROJECT COSTS AND FINANCING

(a) Project Cost by Component (in USD Million equivalent, total project cost)*

Components Appraisal Estimate

(USD millions)

Actual/Latest

Estimate (USD

millions)

Percentage of

Appraisal

A. Improvement of the

Institutional Framework and

Operations of the Statistical

System

1.3 1.3 100

B. Improvement of Information

and Communication Systems and

Physical Infrastructure

7.6 11.0 144

C. Improvement of Human

Resources 0.8 0.9 112

D. Improvement of Statistical

Infrastructure, Standards and

Methodology

1.7 1.6 94

E. Improvement of user, provider

and statistical agency relations 1.4 1.3 93

F. Improvement of Individual

Subject Matter Programs and

Methodologies

9.3 5.9 63

G. Project Management 0.5 0.6

Subtotal 22.6 22.6

Contingencies 0.2

Total Project Costs 22.8 22.6 99

Source: IFR as of March, 2017.

(b) Financing

Source of Funds Type of

Cofinancing

Appraisal

Estimate

(USD

millions)

Actual/Latest

Estimate

(USD

millions)

Percentage of

Appraisal

Borrower 2.81 3.2 .00

International Bank for Reconstruction

and Development 20.00 19.95 .00

29

KAZAKHSTAN


ANNEX 4: CRITICAL RISKS AND POSSIBLE CONTROVERSIAL ASPECTS

Risk factors Description of risk Ratinga

of risk Mitigation measures

Ratinga

of

residual

risk

I. Sector Governance, Policies and Institutions

Sector

Specific Risks

(General

public

administration

sector)

Lack of political support and

commitment for a modern

statistical system, by not

providing adequate legal,

administrative or budgetary

conditions.

Substantial The ASRK has

demonstrated its readiness

to improve the capacity of

KNSS by developing the

SMP and endorsement of

the SMP by the

Government is a good

indicator that potential risks

could in fact be mitigated.

The new management of

ASRK has already obtained

approval from Prime

Minister for the proposed

STATCAP project, which

shows the Government

support and ownership.

During the implementation,

new procedures will be

introduced and they are

unlikely to require more

resources than the

procedures they replace. In

fact, they will produce

substantial efficiencies and

release resources that will

be more than sufficient to

support training activities

and the relatively modest

proposals for expansions in

statistical program through

new surveys and survey

modules.

Moderate

II. Operation-specific Risks

Technical

Design

Lack of effective

coordination among relevant

government agencies

Substantial The project will modify

the legal and

organizational structure of

ASRK in order to

improve efficiency and

effectiveness that will in

turn enhance the

coordination of the

activities of the statistical

Low

30

system and outputs will

be better disseminated.

The current Central

Office structure and the

distribution of

responsibilities between

the ASRK and the ICC

will be rationalized to

streamline operations and

to secure core business in

the ASRK.

Further, the project will

improve the dialogue

between data producers

and users as well as

among the main partners

of the statistical system by

establishing specific

advisory groups and more

active engagement of the

Statistical Council.

Implementation

Capacity And

Sustainability

Lack of capacity in the

present statistical system,

due to loss of competent

staff

Substantial During the

implementation, it is

anticipated that there will

be significant efficiency

gains, part of which could

be used to attract and

retain skilled

professionals, and with

the help of a substantial

training program the stock

of skilled professional

staff is expected to

increase.

Moderate

Financial

Management

ASRK does not have any

prior experience in the

Bank-financed projects, and

FM staff not familiar with

Bank’s FM and

Disbursement procedures

Lack of prior experience in

the Bank-financed projects

is one weakness to be

addressed.

Accounting system currently

does not support project

accounting and reporting

requirements and needs to

be modified to meet these

requirements.

Substantial ASRK will sign a contract

with a local qualified FM

consultant to set up

project accounting

system. The WB will

provide training on World

Bank FM and

Disbursement procedures

The 1C accounting

software will be modified

to include a chart of

accounts appropriate for

the project and have

capacity to generate

interim financial reports.

To facilitate smooth

project implementation,

Project Operations

Manual (POM) will be

prepared and adopted.

Moderate

31

The POM will contain

necessary FM and

disbursement

arrangements. This will

be done by effectiveness.

Procurement Potential procurement

delays: Experience with the

past and on-going projects

in country show frequent

procurement delays due to

poor planning, lack of

qualified procurement staff,

complex internal approval

process.

Low level of competition: Past experience indicates the

procurement in country has

not attracted adequate

competition; often only one

bid was received.

High Careful procurement

planning and realistic

scheduling; advanced

preparation of technical

specifications and/or

TORs; further

procurement training

would be provided during

project implementation;

close Bank supervision

and monitoring,

particularly from the

country office. Careful

procurement packaging to

foster competition; wide

and advance advertising;

proactive search and

contact to potential

suppliers, consultants.

Substantial

Social And

Environmental

Safeguards

N/A

III. Overall Risk (including Reputational Risks) Overall

Risk

No reputational risk is anticipated Moderate

Memo items: a Rating of risks on a four-point scale – High, Substantial, Moderate, Low – according to the likelihood

of occurrence and magnitude of potential adverse impact.

32

KAZAKHSTAN


ANNEX 5: MID-TERM REVIEW FINDINGS AND RECOMMENDATIONS

1. MTR reviewed the activities carried out under the project and its implementation

arrangements to assess their contribution to the achievement of the PDO, and

recommended measures to ensure the project remains on the right path to achieve its

development objectives and to maximize project impact and outcome.

2. MTR main conclusions. The assessment of project implementation was based on

the RF. It was concluded that, overall, project was implementing efficiently at fully

satisfactory or satisfactory level. More specifically:

- Users’ satisfaction survey based on the internationally accepted methodology -

fully satisfactory;

- Cooperation with mass media (target-oriented statistical material is easily

accessible in the relevant mass-media sources including metadata and interpretation of

outcomes) – fully satisfactory.

- Scope / accuracy / authenticity (international statistical methodology in terms of

collection, generation and consistency check shall be applied - satisfactory.

- Timeliness – fully satisfactory.

- Effective tools for intergovernmental cooperation (reference indicators - agency

coordinates statistical actions and collection of official data; target oriented indicators -

administrative data submission rules and other documents for using data in statistical

purposes are updated on regular basis) – satisfactory.

- Dialogue tools with data users and respondents function effectively – satisfactory.

- Agency structure has been optimized at central and territorial levels, staff including

involved Ministries and Agencies has been trained -fully satisfactory for existing model of

the KNSS.

- Registers have been made actual – fully satisfactory (could be used as a best

practice).

- Internationally accepted standards, classifications and methodology have been

adapted and being applied – fully satisfactory.

- Implementation of standards for questionnaires drafting – satisfactory.

- Operating IT-potential adequate and properly maintained - satisfactory (although

final evaluation will be possible after finalizing the contracts of modernization of the ICT

infrastructure and implementation of new hardware and software).

- All the employees of the CSMNE possess computers with an access to data base

for analysis and tabulation - satisfactory, work in progress.

3. First phase of the project (2012-2014) was focused on and limited to the

accelerated transfer of know-how and best practices may be effective and called the

educational phase. The types of actions dominating during this phase (2012 – 2014) were

33

typical for education: seminars, workshops with foreign experts presenting know-how and

best practices, trainings, study visits, participating in international conferences. In practice,

almost all domains of statistics were covered by those types of actions. The implementation

of the results of education actions was realized within the frames of regular statistical works

of the ARKS, according to the multi-annual and annual programs of statistical surveys and

methodological works. It was suggested that the first phase of KAZSTAT project focused

on the transfer of knowledge on best practices, know-how and implementation of inter-

national standards was successfully finalized.

4. The second phase of KAZSTAT project (2014-2016/17) should consume and

implement the human and social capital of statistics created during the previous period and

was suggested to be called implementation stage. The priority should be given to practical

implementation of methods, tools, technologies, selected information systems,

organizational structures, laws and procedures. The scope of implementations should be

concentrated on achieving sustainable effects of progress in the domains that are most of

strategic importance for the KNSS. Educational activities that were dominating earlier,

should be – of course – continued also during the second phase, however the actions should

be subordinated to main sustainable implementations of registers, databases, surveys,

methods and technologies. The regional statistical offices should more actively participate

in the project activities.

5. It was recommended to consider the redefining of the priorities of the second

phase and elaborating of new updated version of the work plan through introducing the

new relevant formulations and tasks. It is suggested that the focus of project activities

would be (i) creative adoption of methods, know-how and best practices learned by the

staff of the ARKS to the specificity of KNSS; and (ii) modernization of existing statistical

systems and processes by implementation of new methods and tools in surveys and other

activities realized by statistical services. The following activities were named of strategic

importance for modernization and sustainable effects of the KAZSTAT project:

• Full transition from paper questionnaires to electronic (intelligent) questionnaires

for respondents and interviewers

• Implementation of integrated microdata capturing, storage, processing and

dissemination.

• Finalization of re-designing of statistical registers (business register, population and

housing register, agricultural register) into strong frame for surveys.

• Elaboration and implementation of new organization and division of

responsibilities between central statistical services of the CSMNE and ministries, regional

and local statistical offices.

• Harmonization of interpretation of national laws regulating official information

systems (administrative and statistical), with special reference to e-government and e-

statistics initiatives.

• Development of analytical and research capacity of official statistics in the forms

of (a) research center of statistics, (b) education center of statisticians, (c) central and

34

regional analytical laboratories offering advanced statistical and analytical services to

governments, businesses and research institutes.

• Continuation of adoption and implementation of new methodological approaches

of statistics for all domains of statistics (component F of KAZSTAT work plan); it is

suggested to pay more attention to statistics of demographic processes, impact of open

market-driven economy on social and economic processes in the country, consequences of

integration of the economy of Kazakhstan in the EurazEC single economic space, statistical

observation of trans-border processes, development of human and social capital, non-

registered and non-observable economy, impact of financial processes on real economy,

regional statistics.

• Active information policy of the CSMNE with special reference to the personalized

statistical services for professional users in governments, research institutes and businesses

and active cooperation with mass media.

6. According to the MTR recommendation:

- the actions of study visits, seminars and trainings should be subordinated to the

realization of concrete implementations. Training and re-training of the staff in regional

and local statistical offices and of the staff involved in the statistical activities of ministries

is the issue of special propriety.

- optimization of the workload between the central office and regional units, that

being coupled with the introduction of an integrated processing system, would make the

system more efficient and effective, could have been address directly through adding a

separate component on regional dimension.

7. In ICR team view, the MTR report has presented quite interesting and important

ideas and recommendations which – once implemented – would have enriched the project

outcomes.

8. However, there were limitations in the scope of corrective actions. First, some

of the MTR recommendation have been considered and implemented. From the beginning

KAZSTAT project included several nation-wide interventions and its training program

secured coverage of statisticians from regional offices. Second, there were several

considerations that influenced the final decision not to go for project restructuring:

1. Anticipation of the follow-up operation that could potentially address the MTR

recommendations;

2. Lack of flexibility on the Government side: introduction of new component would

require an amendment to the Loan Agreement and its ratification (in Kazakhstan this is a

very lengthy procedure which would put the timely project implementation at a risk).

3. Though the TP allows for relative flexibility, the complex contract with Consortium

could not be significantly modified.

35

KAZAKHSTAN


ANNEX 6: OUTPUTS BY COMPONENTS AND SUB-COMPONENTS

Table 6.a: Attribution and Results Measurement

PDO Level Improve efficiency and effectiveness of the Kazakh National Statistical

System to provide relevant, timely and reliable data in line with the

internationally accepted methodology and best practices.

Higher

level

outcome

Access to information/dissemination

1. User satisfaction rates increased (In 2016, it was 94.4 percent

exceeding the target value of 80 percent).

2. Targeted statistical products easily accessible in the media, with

metadata and interpretation of findings. There was a significant

increase (8 times) in the number of visits to CS newly improved

website exceeding 4 million visitors in 2016 after the online

service “Taldau” database was introduced. Standardized the

corporate logo and introduced new style standards for all

statistical domains, print and electronic products. CS updates and

keeps regular press releases and media conferences. Added the

date for statistical data compilation calendar to help with the

collection process.

Coverage/Accuracy/Reliability

3. Internationally-accepted statistical techniques in collection,

compilation and authenticity verification applied, and regular

validations carried out for data sources and statistical products.

(CS improved 80 methodological guidelines over the course of

project. Transition to SNA2008 is ongoing and NACE 2.0

applied to industrial statistics, UNSC standard for International

Energy Product Classification and SEEA for environment

statistics; data quality, quality report and code of practice were

developed based EU quality management practices of ISO 9001

standard and follow GSBPM).

Timeliness:

4. Statistical outputs released in a timely manner in accordance with

internationally-accepted frequency and timeliness (i.e. according

to IMF evaluation the CS met all technical requirements to enter

SDDS according to IMF standards and assessment).

Intermediate

outcomes

1. Adequate policy and regulatory frameworks as well as effective

institutional framework, management and human resources for

statistics are in place.

36

2. Statistical infrastructure developed and operational.

3. Investment in physical infrastructure and equipment to facilitate

the production and dissemination of data by statistical agencies

is undertaken and adequately maintained.

Key

outputs

1. Mechanisms for effective interagency coordination established

and operational; Mechanisms for effective dialogue with data

users and providers operational; Information/call center

established and very active; Business and admin data sources

were established and used for aggregate indicators and reduced

respondents burden by 20 percent; the ARKS/CSMNE central

and local level structure optimized through reorganization and

staff trained (more than 2000 people) including staff from

regional offices, relevant ministries and agencies.

2. Registers compiled and maintained; Internationally accepted

classifications, standards and methodologies adapted and used in

data production; Standard questionnaire for survey developed

and applied; sampling technique improved, thematic statistical

data developed (128 new indicators) and results disseminated.

3. Capacity for physical operations adequate and well maintained;

All staff at central office and regional offices have modern

computer, tablets, network hardware and access to databases for

analysis and tabulation.

Inputs Provision of technical services (e.g. consultancies)

Conducting training and workshops

Procurement of ICT equipment and software

37

Table 6.b: Outputs by Components and sub-components

Component Project outputs (under the contract with

Consortium)

Project outputs and activities implemented by the CSMNE

A. Improvement of the Institutional framework and operations of the statistical system

A.1 Interaction between the

state bodies • Review of statistical institutional framework.

• Review of existing legislation and agreements.

• Training on use of administrative sources.

• Study visits to explore and enhance the

knowledge on access to administrative data

and cooperation between government bodies

of foreign countries (Germany and Finland).

• Strengthen the existing right of CS and

increase the use of admin data and provide

international best practice examples.

• Provided advice to CS approving the forms

and the methods used for the collection of

administrative data.

• Estimated the proportion of administrative data used in the production

of statistical information

• Drafted a register for reporting to be published on the website.

• Designed methodology of administrative accounting database creation

and maintenance for further processing and compilation of aggregated

statistical indicators.

• CS functions as State Control and enact orders or conclude bilateral

agreements for the exchange of data and authority to conduct

inspection in case of suspicion of a violation.

• Streamlined the forms and questions used in data collection of various

agencies thus decreased the burden on its respondents significantly.

A.2 Revision of the

organizational and legal

structure of statistical bodies

and improvement of the state of

the territorial bodies of CS

• Functional analysis of the ARKS and its

territorial bodies and provided relevant

recommendations and structural changes.

• Conduct SWOT survey to personal interview

with head of departments to identify the

strengths and weaknesses of subdivisions of

the CS.

• Study visit to share experience on

organizational structure and planning of

statistical activities to Germany.

• Revised the organizational structure, central and regional level based

on the personal interviews and SWOT survey

• Energy statistics was transferred from the production and environment

statistics division to the services and energy statistics division.

• National accounts department was divided into the national accounts

division and the structural statistics division.

• Created new department of Publications and Statistical Information

Dissemination which centralized and combined all data dissemination

services (electronic and printed).

A.3 Strategic planning and the

methodology of preparation of

the plans

• Study and analyze the existing methods on

strategic planning.

• Provide recommendations to improve the

strategic planning via planning and monitoring

module.

• Support the CS design a Statistical Master

Plan for 2017-2025 to raise the potential of the

statistical system of the Republic of

Kazakhstan next statistical framework.

• Drafted proposal to the superior agency regarding the establishment of

the research and training institute in Kazakhstan.

• Division of Statistical Activities Planning has drafted and designed a

Statistical Master Plan for 2017-2025.

• CS has begun to design a Module 'Planning and Monitoring' under the

s-Statistics Integrated Information System, to automate short-term

planning and monitoring of activities.

38

• Training for more than 40 employees on

strategic planning at the central and regional

level.

• Study visits on planning of statistical

activities, STOJ system/staff workload and

Research and Training institute to foreign

countries (Germany, Finland and Korea, Rep)

• Shared best practice and information about

research and training institutes in developed

countries with CS. A.4 Introduction of the

personnel work load recording

system

• Help introduce effective personnel work load

recording system at CS.

• Study visits on workload recording

information system and STOJ system/staff

workload to foreign countries (Slovakia and

Finland).

• Established internal working group to introduce personnel work load

recording system containing cost determination of individual products

and services, management of value-adding activities and elimination

non-value-adding activities, capacity planning for optimal utilization of

human capital in the organization.

A.5 Quality management

program • Development of tools for quality maintenance

(GSBPM) and quality assurance toolkit

(GSBPM and GSIM models) for CS.

• Review of regulations on processes and sub-

processes affecting quality of statistical

activities.

• Implement quality assurance procedures and

introduced quality management tool and

indicators at CS.

• Training on quality indicator, standards,

principles as well as quality monitoring and

improvement methods including self-

assessment.

• Study visit on quality management To

Germany and practical application of the

GSBPM to Sweden, quality assurance toolkit

to Estonia, self-assessment to Italy and quality

guidelines to Slovakia.

• Made progress towards building up knowledge on quality management,

both the general theory and the use of different quality tools and

approaches such as process mapping.

• Increase the knowledge on quality management at the CS

• Quality reporting and quality indicators are being introduced.

• Drafted methodological guidelines to ensure quality of statistical

products as well as action plan to introduce GSBPM model.

• Updated quality guidelines and manuals in accordance with the

GSBPM model and revised process maps.

• Revised all quality assurance documentation and policy was revised in

the process of integrating the GSBPM models. Quality assessment

tools are being introduced. A phased transition to e-statistics is

accompanied by the introduction of quality reporting.

• Progress achieved in quality improvement will be subsequently

measured through self-assessment surveys including processes in the

regional statistical offices.

• Developed and endorsed training program for newly hired staff and

regional staff on quality issues and assurance tools.

B. Improvement of information and communication systems and physical infrastructure

B.1 Development of integrated

data processing system • Develop integrated software for designing

questionnaire, creating survey frames, sample

selection, capturing data by optical

• Integrated the CS information system with other government agencies’

databases.

39

recognition, editing and imputing, aggregating

and disseminating data from common

metadata repository.

• Implement CATI and CAPI systems.

• Reviewed the rules for providing anonymized

databases.

• Introduce SDMX and integrated metadata

system with other agencies.

• Training on information and data security.

• Added a calendar for compiling data in order to improve the control

over data collection process.

• Amended the rules for providing anonymized data and increased the

access to state research communities.

• Piloted CAPI in registering prices as well as household surveys.

• To reduce burden, online reporting system has been setup and service

was established to receive call from users and respondents.

• Shortlisted supplier for CATI system.

B.2 Strengthening the

institutional structure of

information and

communication technologies

• Study visits to learn about IT systems, its

solutions, management and audit in other

countries (Korea Rep.)

• Provided recommendation and solutions based

on the IT subdivision and performance

analysis.

• Developed and approved guidelines for implementation of IT solutions.

• Amended Information security policy.

B.3 Updating hardware and

software • Training for 40 employees on the use of SPSS

and eViews softwares.

• Purchased and installed over 1500 personal computers and 832 tablets

for CAPI interviews at the national and regional divisions. Existing

hardware is modernized.

B.4 Development of

communications network and

telecommunication channels

• Help develop efficient data transfer network

architecture between the central and territorial

divisions.

• Study visit to Korea Rep on inter-regional

telecommunication channels.

• Approved the data transfer network architecture at CS.

• Purchased and installed 16 servers, 48 network switches for regional

divisions.

C. Improvement of human resources

C.1 Human resources

management • Review of HR management and provide

recommendations to improve human

resources, management methods, career

development and recruitment

• Study visit on HR management and

recruitment to Finland.

• Organized workshop on “presentation, facilitation and consultation

skills for statistical trainers” for 18 experts.

• Implemented trainings programs on statistical legislation to local

authorities at the regional training centers.

• Launched mentorship activities pursuant to an order by the Agency of

the Rep. of Kazakhstan for Civil Service Affairs.

C.2 Development and

implementation of training

strategy

• Training “Change management and strategic

leadership” for 15 heads of the divisions.

• Training for 20 staff on Theory of Statistics.

• Organized English language course for more than 100 CS staff.

• Approved the training program for newly hired staff in 2015.

• Modernized the training room with proper equipment and tools.

• Master’s degree program for Statistics was introduced at the Academy

of Public Management.

D. Improvement of statistical infrastructure, standards and methodology

D.1 Statistical business register

(SBR) • Help establish the SBR, improve methodology

and use of admin data for updating.

• Reapproved rules for information exchange between Legal entities state

database. As result, Ministry of Justice submits data on registration,

40

• Develop procedure for exchange of

information between other government

agencies.

• Help reduce respondent burden with practical

recommendations.

• Introduce quality control in business statistics

by targeting local offices and provide logical

and format validations.

• Recommendations on profiling of enterprises.

• Study visit to Turkey on SBR.

reincorporation, liquidation on businesses on daily basis. CS submits

data to Ministry of Justice and tax authorities.

• Approved the methodological recommendations for maintaining and

updating the SBR.

• Started compilation of new indicators on duration, type of activity and

operating region.

• Launched searchable service on the web on legal entities and

entrepreneurs.

D.2 Statistical population

register (SPR) • Provided recommendation to maintain and

update the SPR using the admin sources and

population census.

• Help draft the agreement between line

ministries and relevant agencies.

• Performed analytical work using the SPR and

update the methodology for SPR.

• Organize training on maintenance of

population register

• Conduct study visits to share knowledge and

increase the expertise of CS staff on education

statistics, population census and SPR (Turkey,

Norway, Germany and Bulgaria)

• Signed new agreement on the procedures to exchange information for

SPR with Ministries of Justice, Interior, Education and Science, Health

and Social Development and Committee on National Security.

• Updated the methodology to maintain SPR.

• Monthly basis, CS analyzes the data from admin sources against the

data on received via traditional channels and record and validate.

• Compiled data on social-economic and ethnic groups in Kazakhstan.

D.3 Statistical register of

housing stock (SRHS) • Provided methodological recommendation on

maintaining a housing stock register.

• Introduced new terms and indicator abandoned

housing.

• Approved and launched online information exchange procedure for

“Real estate register” state database.

• Improved and adopted methodology guideline for SRHS including

employment sample survey.

• Updated the data monthly basis by number of inhabitants from

household surveys a the territorial level.

• Compiled handbook on housing stock by detached houses and

residential properties (apartments).

D.4 Agricultural statistical

register • Recommendations to improve methodology

and maintaining ASR.

• Help design the new methodology to update

ASR and provide necessary technical and

methodological support.

• Conducted study visits to Denmark and

Mongolia.

• Daily basis, data on entities that are operating in agricultural sector

received at CS.

• Revised and agreed procedure to exchange information with Ministry

of Agriculture to receive the livestock data by entity/farm.

• Improved and adopted the methodology and added new section to use

individual and business identification numbers.

• Reapproved the procedures to receive land use and agricultural land

data from Committee on Construction, Utilities and Land Resources

Management of the Ministry of National Economy.

41

• CS shifted the household records maintenance to electronic format to

ease the burden on local governments as well as to improve quality of

ASR.

D.5 Development of system of

classifications and standards • Help develop the statistical classifications and

metadata in accordance with the international

standards

• Improve the methodology for maintaining

classifications and standards

• Introduce SDMX and metadata standards

• Help develop new versions and statistical

classifications in area of need.

• Study visits to increase knowledge on SDMX,

classification and standards, metadata and

server to foreign countries.

• Improved classifications on agriculture, forestry, and fishery products;

industrial products; services; and internal trade services.

• Designed and approved domain based new statistical classifications.

• Improved modules of IS Class through visualization, search and

sorting.

• Developed and updated regulatory documents on metadata

maintenance.

• Approved terminologies used in Kazakhstan in statistical terms.

• Designed data communication system aligned with SDMX standard.

• Approved the plan to implement SDMX standard at the national level

2014 – 2017.

D.6 Development of statistical

toolkit system • Design the statistical toolkit and develop the

guidelines.

• Training on CATI guidelines and data

collections.

• Provide recommendations on conducting

national surveys using the CATI system.

• Introduced new design standards for reporting forms in hard and soft

copies.

• Amended rules for approving statistical reporting forms at national,

sector surveys and instructions to fill them.

• Drafted the regulation for conducting CATI and 8 staff were trained.

D.7 Improving the quality and

methods of conducting sample

surveys

• Revise the organization of sample surveys and

forming of household samples.

• Update methodologies and provide

recommendation to improve the quality of

sample household and employment surveys.

• Training on R-software to estimate standard

errors and calculate rotation and conduct

overlaps of samples.

• Piloted survey on living standards and labor force surveys and

conducted quality assessment.

• Automated the agriculture sample survey based on the sample

population to carry out multidimensional and/or one-dimensional

sampling proportion to the size.

• Updated and approved methodology and guidelines for sampling

design in agriculture, enterprise and household surveys.

• CS central office 37 employees and 16 regional staff were trained and

received knowledge in field of conducting surveys using sampling.

D.8 Formation of time series

and implementation of seasonal

adjustment methods

• Help produce seasonally adjusted data for

main economic indicators in line with

international practice.

• Training on theory, advantages and

disadvantages and practical approaches of

seasonal adjustments.

• Provide recommendations to prepare user

manual for TSW Plus program.

• Drafted the methodology to formulate seasonally adjusted indicator sin

monthly and quarterly basis.

• Prepared calendar regressor tor filtering time series data from calendar

effects.

• Total 49 employees of subject matter division were trained and learned

examples of best practices. Prepared press release to include seasonally

adjusted indicators.

42

D.9 Development of analytical

capacity • Provided training on analyzing data and

forecast and shared international best practice

modules and resources.

• Training on measurement of multifactor

productivity (MFP). The experts were

familiarized with the methods used to

construct the constituents of MFP indexes -

output, capital and labor – and how to

combine them together.

• Staff were completed the 10 stages of OECD Handbook on Cyclical

Composite indicators and compiled leading indicator.

• Obtained theoretical knowledge and practical skills to analyze time

series data.

• Prepared Methodology to Build an Aggregated Leading Indicator’ and

‘Methodology to Measure Multifactor Productivity’.

• Many staff (48 subject matter experts and 135 staff from regional

office) were trained to review, select method and approach and apply

infographics and practical knowledge to conduct analysis. And building

forecast model to estimate GDP.

E. Improvement of users and respondents’ relations

E.1 Improving the user

relations policy • Help design the guidelines for official

statistics users including the main user groups

and subgroups to further structure the user

database.

• Provide recommendations for how to respond

to different groups of users, including the

problematic ones, making adjustments and

providing users with clarifications.

• Training on user relations for staff of regional

statistics departments, including the

interaction with the media and general public,

as well as the introduction of a new corporate

style.

• Designed guidelines on user relations, including media and the public.

• Standardized all corporate tools, such as logo, corporate colors, fonts,

pictograms by domain of statistics, standards of electronic and printed

versions of publications and documents.

• Launched the information service to receive calls from respondents and

users.

• Improved the website and user survey from 2016 showed very positive

results. More than 94.4 percent of users were very satisfied with the

support by CS and the services CS offers online, phone or mail.

E.2 Dissemination and

marketing of statistical

information

• Help design communication and design

strategy for CS.

• Review and formulate the dissemination rules.

• Prepared and adopted Methodology to formulate and disseminate

official statistics. It will allow regulating the process of downloading

materials on the web-portal, the procedure for interaction between

participants ensuring the functioning of the web-portal;

• Number of printed publications has been significantly reduced and

replaced by online services like "Taldau" database;

E.3 Respondent relations

policy • Introduce a pre-test room (laboratory) to test

questionnaires.

• Introduce measure of burden on respondents.

• Study visit to see call centers and CATI and

measurement of respondent burden.

• Launched the information service to receive calls from respondents and

users.

• Drafted and implemented respondent relations policy.

• Designed the concept of using the pre-test room (laboratory) which will

help will improve the quality of official statistics, which in turn will

increase the confidence of a wide range of users in official statistics in

Kazakhstan and improve feedback from respondents.

• CS prepared a Plan to Test Statistical Forms.

43

• Prepared design of a new website, taking test the CS website usage,

with the involvement of statistical information users and respondents.

• Made the pre-test Lab operational.

E.4 Improving the web-portal • Provide recommendation to improve the CS

website with interesting facts and easy

navigation and search functions.

• Web-portal improved - in comparison with 2012 the number of visits to

the website of the Committee has increased almost 8 times. In 2016

almost 5 Mio. visitors of CS website were counted. The availability of

statistical information was generally improved.

• Users have the opportunity to use channels on the CS website for their

feedback, to access methodological documents used for surveys and

survey results.

• The website services are available in three languages - Kazakh, Russian

and English.

F. Improvement of the methodologies and practices in specific areas of statistics

F.1 National accounts statistics • Provide methodological framework for the

transition of SNA 1993 to SNA 2008.

• Implement the integration of non-observed

economy, supply-and-use and input-and-

output tables.

• Provide recommendations on implementation

of satellite accounts and help CS pilot tourism

and financial assets etc.

• Non-observed economy (NOE) is fully integrated into to the system of

national accounts at CS. Currently the estimation of NOE in

Kazakhstan is about 27.5 percent of GDP.

• Compilation of full set of sectoral accounts incl. balance sheets,

production and generation of accounts by activity. Comprehensive

system of sectoral accounts for five institutional sectors and the rest of

the world (each separately) were built. Subsequently, an integration of

various sectors into a unified system was made - i.e. all data of

individual sectors and data balances and tables that are compiled

outside the system of sector accounts were integrated into one common

file.

• The procedure to build a satellite account on tourism was improved.

The methods to build a satellite account on health were studied as well.

• CS has appropriate data sources for the calculation of the quarterly

GDP and its components with use of double deflation approach.

• Forming of financial accounts improved. Further improvement of

cooperation with the National Bank of Kazakhstan is still needed.

• Coordination with other departments at CS on primary data for NA

calculations is improved.

• The methods to form supply-use and input-output tables at current

prices were improved. The CS staff examined the approaches to

estimate supply-use tables of the Czech Statistical Office at previous

year prices, the relation between supply-use tables and GDP calculated

by using three methods at current and constant prices.

• The following methodological works were designed and approved:

- Methodology to Assess the Amounts of Illegal Activities;

- Methodology to Assess Shadow Economy by Economic Activity;

44

- Methodology to Assess Residential Rent;

- Methodology to Account the Output of Financial Intermediation

Services;

- Methodology to Account Insurance Services;

- Methodology to Account Financial Services Provided by Second-Tier

Banks;

- Methodology to Account Services Provided by Central Bank;

- Methodology to Account Taxes on Products and Import;

- Methodology to Estimate Gross Regional Product at Current and

Constant Prices;

- Methodology to Measure Multifactor Productivity;

- Methodological Guidelines to Prepare Supply-Use and Input-Output

Tables;

- Methodology to Build a Financial Account;

- Methodology to Build a Satellite Account on Tourism;

- Methodology to Build a Health Account;

- Methodology to Account Research Activities;

- Methodology to Build and Other Changes in the Volume of Assets

Account;

- Methodology to Build a Capital Account;

- Methodology to Build a Revaluation Account;

• Methodology to Form a Balance Sheet.

F.2 Structural statistics • Help improve the system of structural

statistics indicators in accordance with the

SNA requirements.

• Provide applications of the knowledge

obtained to estimate the indicators used for

economic analysis of enterprises’ economic

activities with the use of structural statistics

indicators.

• Share international practice and concept of

labor productivity estimation based on the

number of hours worked introduced. It

corresponds to the

• Recommendations to adjust structural

statistics and detailed estimations of gross

value added (GVA) by enterprises.

• The statistical toolkit on structural and short-term statistics was

modernized, and 14 statistical forms were revised to meet international

standards.

• In the course of the project, structural statistics was separated from NA

department following the recommendations of international experts.

• The methodology to estimate labor productivity was designed.

• Prepared methodological guidelines to edit structural statistics

databases for SNA purposes.

• A new statistical survey on the individual entrepreneurs sector (1- P

'Report on Individual Entrepreneurs' Activities) was introduced.

F.3 Statistics of small and

medium business (SME) • Help to integrate the use of administrative into

national practice to produce SME statistics.

• Introduced use of admin data (State Revenue Committee of the

Ministry of Finance of the Republic of Kazakhstan).

45

• Improve the methods to carry out a sample

survey and analyze the data obtained.

• Help improve the methodology to estimate

small and medium businesses that includes a

section on assessment of SMEs contribution to

country's economy (SMEs share in GDP) was

improved and approved.

• Introduce an automated data processing

system for statistics of small and medium

businesses that allows integrating data from

different sources.

• Help CS conduct a new survey on

entrepreneurs.

• The statistical toolkit on statistics of small enterprises was modernized

and two statistical forms were revised to meet international standards.

• In order to reduce the burden on respondents, 57 indicators were

excluded from current forms.

• Introduction of new indicator "share of SMEs in Gross Regional

Product" geographically.

• Methodology to estimate small and medium businesses that includes a

section on assessment of SMEs contribution to country's economy

(SMEs share in GDP) was improved and approved.

• Automated data processing system for statistics of small and medium

businesses that allows integrating data from different sources was

introduced.

• A new statistical survey on individual entrepreneurs was carried out.

F.4 Price statistics • Help improve and reliability of the system of

data collection for consumer price statistics,

housing price indices, exports and imports

price indices and producer price indices.

• Improve the methodology to build the

consumer price index and housing market to

international standards.

• Help estimate an improve the methodology for

foreign trade price indexes, price and cost

indices for the construction sector, and price

index on agricultural products.

• Introduce new statistical survey of

warehousing service prices to estimate a new

price index.

• Help design new survey for service industries.

• A new electronic form of data entry to register prices on consumer

goods and services and CAPI software was designed.

• The methodology to build a consumer price index and price index in

the housing market was improved. The index is built by using the

administrative source of the State Database 'Register of Real Estate'.

• Approaches to estimate foreign trade price indices were improved.

Price indices on export and import products are built considering the

prices of actual transactions registered directly with the exporting and

importing enterprises.

• The methodology to estimate the price and cost indices for the

construction sector was improved. The procedure to estimate a new

indicator of the construction cost index was designed experimentally.

• The methodology to estimate the price index on agricultural products

was improved. A new procedure to sample the basic enterprises and

form the weighing schemes was introduced.

• Producer price indices comply with international recommendations and

standards.

• New questionnaires were designed and piloted to be used to carry out

surveys in several service industries.

F.5 Industrial statistics • Provide analysis and recommendation to raise

quality of indicators in industrial statistics and

improve the methodology according to

international recommendations.

• Provide recommendations in the area of

estimating production indices and improving

• The methodology for formulating the composition and values of

industrial statistics indicators was improved to determine common

approaches to collecting, recording and formulating industrial statistics

indicators, and ensuring comparability of data in accordance with

international standards.

• In order to determine the approaches necessary to estimate the gross

output of industrial products and to improve the quality of

46

the quality of official statistics on industrial

production indices.

• Introduce estimation IPI by economic activity,

using the Laspeyres index, expand common

list (basket) of representative goods, and

application of the methods for seasonal

adjustments of time series

macroeconomic calculations, the methodology for estimating the gross

output of industrial products (services) was improved as part of the

System of National Accounts in accordance with international

standards.

• The methodology for estimating the industrial production index (IPI)

was improved by using the gross value added (GVA) as a weight based

on national accounts.

• Revised and adopted the Statistical Classification of Industrial

Products.

F.6 Construction and

investment • Assist CS in improving the statistical toolkit

and methodology of formulating construction

and investment activities indicators in order to

increase the quality of indicators in

construction and investment statistics.

• Provide recommendations for experimental

calculations of imputations for non-response.

• The Index volume of construction works was divided into residential,

non-residential buildings and structures, broken down into construction

and installation work, capital repairs, and current repairs and

maintenance.

• Investment statistics: statistical monthly and annual form 1-invest was

revised.

• Evaluation of results of the new survey on quality of data collected and

on the rate of non-respondents enterprises will be carried out.

• Deflation method using asset specific price index where available was

revised.

F.7 Energy statistics • Introduce main indicators and the international

comparability of energy statistics

• Provide recommendations to establish a

working group for improving data quality and

user relations on energy statistics.

• Introduce the UNSC Standard International

Energy Product Classification (SIEC).

• Help extent the cooperation with Energy

statistics related organizations.

• CS is designing a questionnaire for the survey of energy consumption

by households.

• CS designed statistical toolkit for calculation of the production volumes

of electricity from renewable energy sources (questionnaire for

enterprises, with facilities using renewables), such as solar, wind and

hydro energy.

• Extended the cooperation with IEA, ADEME and INSEE.

F.8 Agriculture statistics • Improve the methodology for formulating

indicators, applying new data collection and

processing methods based on the international

experience.

• Update the indicators in use to estimating the

gross output.

• Changed the methodology for carrying out sample surveys in crop and

livestock. The sample design for surveys in agriculture was improved

as well.

• Indicators for the methodology of estimating the gross output of

agricultural products was updated.

• CATI pilot was carried out with technically adapted statistical forms

and new methodology to be used for agricultural surveys. The

introduction of CATI technology serves also the preparation for the

agricultural census which is scheduled for 2021.

F.9 Environmental statistics • Improve the methodology and creation of a

system of environmental accounts to be used

further in the SNA.

• CS conducts nationwide annual statistical surveys on waste,

environmental protection expenditures and on ambient air protection.

47

• Address quality of indicators; help strengthen

access to administrative data and cooperation

with other state bodies.

• Introduced systems of environmental and

economic accounting (SEEA).

• Help design and introduce 'Classification of

Environmental Protection Activities and Cost

and Resources Management'

• Introduce 'Methodology for Formulating

Primary Indicators Necessary to Build an

Environmental Account in the System of

National Accounts (SNA) (No. 238,

12.10.2016).

• The statistical toolkit developed and used is being updated based on

recommendations of the UN, the EU and the OECD.

• Sector-specific classification of environmental activities 'Classification

of Environmental Protection Activities and Cost and Resources

Management' was designed and introduced (No. 149, 22.07.2016).

• In accordance with international experts' recommendations, the

'Methodology for Formulating Environmental Statistics Indicators' (No.

223, 25.12.2015) was improved.

• The quality of environmental statistics was revised and improved in

accordance with international recommendations.

F.10 Trade and commodity

markets statistics • Improve the methodology to measure internal

trade and to form high-quality statistical data

on commodity markets.

• Help introduce guidelines for formulating

indicators of domestic trade statistics

• Provide recommendations to reduce

respondents burden.

•

• Guidelines for formulating indicators of domestic trade statistics were

introduced. The guidelines are in line with the "International

Guidelines for Distributive Trade Statistics" (2008) of the United

Nations Statistics Division.

• Monthly and annual forms for domestic trade statistics were revised

and adopted with the aim to reduce respondents' burden by modifying

periodicity of the survey on separate indicators.

• CS started to apply administrative sources to conduct sample surveys

on the national level when designing samples of individual

entrepreneurs.

• In order to compile recalculations by informal sector, when forming the

trade sector output, CS started to use household survey data.

• According to international practice, CS began to publish dynamic series

of retail turnover without seasonal factor in order to increase the quality

of domestic trade statistical data.

F.11 Services statistics • Improve the quality of indicators in the areas

of culture and transport in accordance with

international standards as well methodological

guidelines in services statistics in general.

• Provide in-depth methodological knowledge

and practical skills to CS staff.

• Pilot a survey together with CS on transport

sector.

• Methodological guidelines for formulating culture statistics indicators

have been designed. The questionnaire has been updated on additional

indicators.

• CS conducted a large-scale pilot survey on road transport in accordance

with the principles of European Guide on Transport Statistics. The pilot

included both passenger and freight transport, in comparison to Europe

where only freight transport is covered. The survey included also

individual entrepreneurs.

• CS will follow the international recommendations and compare MIA

data with information provided by companies that carry out technical

services of vehicles.

48

• In order to obtain more accurate data on road transport CS will

coordinate this issue with MIA regarding options to include additional

specific characteristics on vehicle registration into the current database.

F.12 Statistics of information-

communication

technologies

• Assist CS in characterizing the development

of ICT in Kazakhstan, revise the system of

indicators and include additional ones that are

in line with EUROSTAT, UNCTAD and ITU.

• Help improve the survey methodology

• Good relations exist also with other data providers (operators and

businesses from the communications and postal sectors) who usually

provide the required information in the timeframe according to legal

regulations.

• After the revision of the questionnaire for the survey followed in 2016

the results showed a realistic effect of efforts in Kazakhstan being up-

to-date with technological progress and providing citizens and

households with affordable ICTs.

• New statistical form of the survey on ICT use by enterprises has been

designed and approved.

• Surveys additional indicators were included for example to measure the

results of national State Program 'Information Kazakhstan - 2020' that

targets to raise IT competences among the population and be among the

top 25 countries that use e-Government.

F.13 External trade statistics • Support the methodology applied and practical

work related to external trade statistics

conducted by the CS

• Introduce methodological and technical

aspects of preparation of the Intra-EU trade

data

• Help prepare indicators for external and

mutual trade statistics according to

requirements of international methodologies

was enhanced.

• Help design the guidelines for trade statistics

to be applied by territorial statistical bodies

and respondents.

• State Revenue Committee delegated powers of preparing external trade

statistics to CS. Hence, it is responsible for trade statistics with the

Customs Union and other countries. The standardization of data and

information exchange according to international standards between CS

the customs services and tax bodies is continuing and being improved.

• The statistical toolkit for the survey on mutual trade statistics "Report

on Mutual Trade in Goods with Member States of the Eurasian

Economic Union" has been designed and is being regularly improved.

• A list of indicators formulated for external and mutual trade statistics

based on integration of trade and business registers.

• Designed guidelines on trade statistics to be applied by territorial

statistical bodies and respondents

• Prepared the quality report on mutual trade statistics based on the

experience of EU countries.

F.14 Science and innovations

statistics • Improve the efficiency and effectiveness of

the surveys and system of indicators

• Review and help update the concepts and

definitions, conducting surveys.

• Recommend best practices of data collection,

editing, imputation and estimation,

dissemination and quality issues in R&D

(research and development).

• CS designed guidelines for "Formulating R&D and Innovations

Statistics Indicators".

• CS revised statistical reporting forms in line with international

recommendations of legislation on R&D and innovations. Compilation

of indicators by four types of innovations is implemented: product,

process, marketing and organizational innovations.

• A working group consisted of national ministries and agencies,

scientific organizations, national companies, development institutions

and other stakeholders was launched.

49

• Support compilation of indicators by four

types of innovations is implemented: product,

process, marketing and organizational

innovations.

• Increase efficiency of measures and ensure

monitoring.

• CS is working to improve innovations statistics, as well as to ensure

monitoring of the State Program of "Forced Industrial-Innovative

Development of Kazakhstan".

• Conducted training for regional statistical offices to update their

knowledge on innovations statistics constantly.

F.15 Tourism statistics • Improve tourism statistics in accordance with

the international recommendations and

national requirements.

• Introduce the Tourism Satellite Account as

well as with self-organized tourism.

• Help develop the methodology for formulating

tourism indicators.

• Recommendation to initiate a working group

consistent of representatives from the Border

Service of the National Security Committee,

Department of Tourism Industry and other

relevant ministries and agencies of Kazakhstan

as well as respondents.

• CS developed and adopted methodological guidelines for "Formulating

Tourism Statistics Indicators" in line with provisions of international

guidelines of the UN and Eurostat in tourism statistics. New indicators

for the Tourism Satellite Account have been introduced too. Results

reached so far for all forms of tourism (inbound, domestic and

outbound) showed high quality.

• In order reduce respondents' burden CS cancelled surveying travel

agencies and replaced its annual form for statistical survey. It conducts

the survey quarterly instead. The form includes indicators

characterizing tourism development by resort zones. Data on travel

agencies are taken from structural statistics.

• A register of accommodation places was developed together with

regional statistical offices and the Department of Tourism Industry of

the Ministry of Investment and Development of RK to ensure good

coverage for the survey.

F.16 Socio-demographic

statistics • Improve methodologies for education, health,

social protection, domestic violence, gender

statistics, crime, population and migration.

• Review existing data and rules and regulations

governing gender data.

• Provide recommendation for survey and make

adjustments for efficiency.

• Organize training course to prepare the

supervisors and interviewers for the fieldwork,

to make them familiar with the new

methodology, the questionnaire and the

special approach for interviewing on this

sensitive topic.

• Implement sample survey on disability.

• Provide avenues to disseminate the data and

analysis

• Crime statistics: Introduce measures of trust

the population have for the legal system and

• Gender statistics: New methodological guidelines were prepared and

integrated. Thus, the national system of gender statistics indicators was

approved and introduced; the related data is already available on the CS

website. Experts from regional statistical offices and related

governmental bodies were trained accordingly. Workshops for the

users and producers of gender statistics became a regular practice and

improved interaction with CS.

• A special survey on domestic violence was introduced as part of gender

statistics. A nationwide survey was conducted with reduced sample size

of 0.3 per cent equally distributed Due to the importance of the survey,

an extensive training was carried out with real interviews and role-

plays reflecting many different and unexpected situations that could

have been occurred during the interview. The survey was conducted for

the first time in Central Asia and the results were widely presented to

elected officials, politicians, the media, non-governmental and

international organizations.

• Sampling survey on disabled people was implemented. CS has

therefore provided methodological guidelines for surveys regarding

statistics of disabled people. The results of the survey were presented to

50

its institutions in Kazakhstan and thus to allow

the law enforcement agencies to assess their

effectiveness and take further measures.

• Demographic statistics: help meet the

standards of statistics users by providing them

with statistical information on vital statistics

of RK broken down by sex, age and regions

and to find appropriate methods to be used

nationally to measure migration flows.

• Introduce all relevant methodologies to

estimate fertility and mortality indicators,

methodology to estimate marriage and divorce

indicators, and methodology to make

population forecasts.

• Help prepare the guidelines to use the software

application and form a database for vital

statistics

• Help improve the methodologies of migration

statistics.

• Introduce new indicators on standardized

fertility and mortality in and measurement of

the level of population ageing were introduced

• Recommend a methodology to formulate

statistical education indicators.

• Help design health statistics methodology to

formulate non-monetary indicators on

sanatorium and resort organizations activities

• Recommendations to help establish

cooperation with data providers at the national

level.

• Recommendations on the statistical form of

the nation-wide survey 'Report of the

organization providing special social

services",

• Recommendations on the use of

administrative data for statistical purposes

taking into account the international

experience and on improvement of the current

methodology to formulate social protection

statistics and statistical toolkit indicators.

concerned parties, issued in a form of an ordinary publication and

formats accessible to persons with disabilities, Braille script and

DAISY standard (audio versions, 'talking' books). The final report in a

form of a Braille script publication and audio versions on electronic

media was sent to all organizations involved in the protection of the

interests of disabled persons and specialized libraries as well.

• Crime statistics: The issues of perception of own security were also

included in the questionnaire.

• The size of the survey was 0.3 per cent of the general population that

still ensured the representativeness of the data at regional level.

Training for regional representatives was held to meet necessary

arrangements and set standards to carry out the fieldwork.

• Demographic statistics: The knowledge gained through consultations

and study visits in this complex area of statistics was taken into account

to improve data collection, processing and validation of input and

output data targeted to create a high-quality database of vital statistics.

• During the project implementation period, three methodologies were

designed and introduced in this area: the methodology to estimate

fertility and mortality indicators, methodology to estimate marriage and

divorce indicators, and methodology to make population forecasts.

• Guidelines to use the software application and form a database for vital

statistics were designed and approved.

• The guidelines on how to use of the local software complex and create

a database 'Natural Population Movement' were designed and

approved.

• New indicators on standardized fertility and mortality in the regions of

the Republic of Kazakhstan and measurement of the level of population

ageing were introduced.

• As for migration statistics, the population migration accounting was

improved. The methodology to estimate basic indicators on population

migration statistics was designed. Together with the international

experts, questionnaires and survey methods were revised. The results

will be included into the questionnaire for the pilot of population

census in Kazakhstan in 2018 - the census is scheduled for 2020.

• Education statistics. The statistical forms of the nationwide survey

'Report on Technical and Professional, Post-Secondary Education" and

'Higher Education Institution Report' were revised in accordance with

the International Standard Classification of Education (ISCED 2011).

• Health statistics. As a result of the activities carried out on health

statistics, a methodology to formulate non-monetary indicators on

sanatorium and resort organizations activities was designed, and a new

51

indicator 'average period of stay by persons who underwent treatment

(taken rest)' was included in the statistical form 1-sanatorium 'report on

sanatorium activities' as per the international experts'

recommendations.

• Social security statistics. Experts recommended to introduce an

estimate indicator 'average number of hospital beds taken per year'. In

addition, when reviewing section 4 'information on support staff' in the

statistical form, the personnel was divided into administrative and

support staff and subject-matter medical specialists to assess the need

for subject-matter specialists in the social area.

F.17 Labour statistics • Improve the methodology of the labor force

survey (LFS) in Kazakhstan and the sample

survey.

• Assist the revision of labor market indicators

and improvement of the methodology of

formation of labor remuneration statistics

addressing the international standards of ILO

and Eurostat.

• The methodology to conduct sample survey of structure and

distribution of wages and salaries was improved and is in accordance

with international standards. A pilot survey of the structure and

distribution of wages and salaries has been carried out.

• The interviews are conducted IT-based with electronic forms.

• Report on data quality improved.

• The revised LFS became more open to add modules for data collection

for other surveys too. This way data from LFS can be used for standard

and living surveys for instance.

F.18 Statistics of standard of

living • Introduce a continuous survey with rotating

panel on standard and living statistics in

accordance with international standards

• Decrease the burden on respondents, provide

training for interviewers and change-over to

CAPI based interviews.

• Training for the use of XLSTAT-PLSPM has

been provided, which necessary for the

analysis of the results of the well-being

module.

• CS introduced most of the relevant indicators to make multi-area

analysis of welfare, poverty and well-being based on the report of the

17th International Conference on Labor Statisticians "statistics of

household income and expenditure".

• Introduction of the set of survey indicators. Various modules were

developed such as quality of life, time use, access to education, health

services and social involvement.

• Nationwide trainings for interviewers were provided.

• The sample survey consists of 12.000 households and is conducted

annually. One third of the sample is rotated every year. The survey can

also be used as a vehicle for broader aspects of standard of living

through add-on modules.

• The results of the survey are used for various publications and bulletins

such as the report on "Quality of Life" in Kazakhstan.

• With introduction of CATI the survey reached its full-scale

implementation.

Note: Underlined project’s outputs have been introduced into regular work of the CSMNE and other related government institutions-

data produces through MOUs and CSMNE internal orders and regulations.

52

KAZAKHSTAN


ANNEX 7: FOLLOW UP TECHNICAL ASSISTANCE

The latest Master Plan for Development of the National Statistical System of the Republic

of Kazakhstan (SMP) has been prepared for the years 2017-2025 at the final stage of KAZSTAT

project. SMP determines the priority directions of development of the KNSS among which are (i)

advancement of the macroeconomic statistics to the latest standards by implementing the SNA

2008 and harmonize with the external debt statistics produced by the National Bank; and (ii)

Sustainable Development Goals 2030 agenda (the gap analysis and development of SDG roadmap

action plan).

The transition to the SNA2008 has started and implemented several major requirements

such as setting up the methodological framework, building the sectoral accounts and their

integration into common file. CS has the appropriate data sources to calculate the quarterly GDP

and is able to compile the quarterly national accounts aggregates following SNA2008

methodology.

It was agreed to have a JERP project Kazakhstan - Strengthening the Statistical Capacity

which goal is to support the CSMNE to i) advance the transition to 2008 System of National

Accounts (SNA) and prepare harmonized macroeconomic indicators according to the latest

international standards and ii) help the Government of Kazakhstan to link the National

Development Plan with 2030 Sustainable Development Goals by supporting the SDG roadmap

workshop.

Under this project, the WBG will assist the Statistics Committee (CS) of the Ministry of

National Economy (MNE) to (i) advance the transition to SNA2008 and preparation of consistent

and comparable national accounts data according to the latest international standards; and (ii)

provide support to SDG roadmap for Kazakhstan.

The CSMNE has keen interest to continue the momentum gained from the implementation of

KAZSTAT project until the new SMP is endorsed and aligned with the next 5-year state strategic

development plan.

The JERP project will have two respective components with a focus on supporting:

the SNA compilation in line with the international standards

• Assist in examining and addressing the imbalance of separate indicators (for example,

significant discrepancies between totals by the capital account and the financial

account);

• Provide support in addressing the incomplete structure of the system of accounts (lack

of the balance sheets and the other changes in the assets account);

• Improve the conventionality of methodologies applied (for example, solve the lack of

continuous inventory models to assess the value of the fixed capital and consumption

of the fixed capital; solve the lack of practice in the application of double deflation

53

technique to re-estimate gross added value in constant prices that degrades the quality

of estimates;

• Provide support to estimate the quarterly GDP on a discrete basis;

• Assist in advancing the transition to SNA 2008 to capture the economic growth in a

more accurate way.

and development of the SDG roadmap

• Provide support in organizing national consultation workshop, dedicated to the

Roadmap for achieving the 2030 Sustainable Development Goals, with participation of

the key local and interested international stakeholders including civil society, local

communities, line ministries and private sector groups. The main objective is to assess

the readiness of the national statistical system to produce global indicators for SDGs

monitoring, and identification of additional national indicators that will be relevant for

Kazakhstan.

• Provide support in developing a medium-term Action Plan based on the Roadmap on

SDGs statistics (up to 2020) aimed to facilitate the implementation of an integrated

SDGs monitoring system.

• Support in developing a national platform for SDGs reporting / a web-page on the

website of the CS of the MNE RK, where all SDGs materials will be posted, including

the first set of data for SDGs monitoring. The implementation of the platform/a web-

page will be carried out by the subordinate organization of the CS MNE RK – RSE

ICC.

• Support in preparation of the first national SDGs monitoring report in regard to the

project structure and support in conducting an analysis of current situation in the SDGs

area.

• Support in organizing additional workshop to present the draft of the first national

SDGs monitoring report.

54

KAZAKHSTAN


ANNEX 8: STATISTICAL PERFORMANCE OF KAZAKHSTAN - 2016

Kazakhstan has made significant progress in reforming and improving the national

statistical system due in large extend to KAZSTAT project and the government’s own initiative of

e-statistics program. As a result, based on the Bank’s recently developed Statistical Performance

Index (SPI) Kazakhstan scored 73.6 out of 100 for 2016 (attached matrix and short note).

The first dimension, Methodology, Standards and Classifications (MSC), looks at whether

countries follow internationally recommended methodology and standards in collecting and

producing data. Kazakhstan gained a score of 80.0 in this dimension where Committee on Statistics

under the Ministry of National Economy of the Republic of Kazakhstan(CSMNE) has adopted

more than 70 new and improved methodological guidelines in line with international standards

during implementation of KAZSTAT project. The CSMNE is still using SNA 1993, however

preparation to move to the latest international standard (SNA 2008) is underway and will be

completed soon. By updating the national accounts and CPI base year with annual chain linking,

the country will be able to capture its national economy in advanced and accurate way. Also, the

country could further improve its score by adopting non-cash recording basis for consolidated

central government accounting, and following the latest government finance statistics manual.

The Censuses and Surveys (CS) section checks whether countries have conducted major

censuses and surveys in internationally recommended form and frequency. Kazakhstan received a

high score of 87.5 in this section. The KNSS system does a good job conducting timely population

and housing census, agriculture census and regular Household Budget Surveys and Labor force

surveys.

In terms of Dissemination Practices and Openness (DPO) that assesses the dissemination

capacity of national statistical systems, Kazakhstan scored relatively high at 71.43. The CSMNE

does provide an advance release calendar, reusable and easy access to time series data and metadata,

as well as a comprehensive, well-developed data portal. The user satisfaction survey results for

CSMNE was 94,4 percent and the website received over 3.5 million visits over the Internet in 2015.

By listing of surveys, microdata, and featuring geospatial data, CSMNE can further improve their

score.

The fourth dimension, Availability of Key Indicators (AKI), checks the availability of

selected core indicators in the international organizations and databases. We prepared the country

score using World Development Indicators database as of March 2017. Kazakhstan received sub-

score of 50 with data from 2016. The score shows that Kazakhstan has the latest available data on

poverty, child immunization, adult literacy rate and completion rate, water and sanitation, and

national accounts. More recent data on social indicators such as stunting, maternal mortality rate,

skilled healthcare workers particularly unemployment and up-to-date CRVS data are missing.

There is usually a two-year gap between the calendar year and the data that are incorporated

to the WDI database. In order words, few advanced systems can produce the latest data within first

quarter of the next calendar year. For Kazakhstan and other advancing economies, the relatively

low AKI score likely to improve as long as the process and channels of submitting and reporting

55

of data to the primary international organizations configured since the latest survey and

methodology is already in place.

The total score of 73.6 leaves a room for improvement of the statistical system particularly

in areas of Sustainable Development Goals, External Trade and National accounts statistics to

properly inform evidence-based decision making process as well as monitoring and evaluating the

development progress in coming years. CS has drafted the Statistical Master plan for 2017-2025

to further integrate activities and improve the statistical system and added a proposal to create a

research and training institute in Kazakhstan based on the best practices of the advanced economies

to train the relevant staff and employees.

56

Detailed Scoring Matrix of the SPI for KAZAKHSTAN

Methodology, Standards & Classifications

# Indicator Score 1 Score 0.5 Score 0 Weight Weighted score

1 System of National Accounts in use

SNA2008/ESA 2010 SNA1993/QNA Manual 2001/ ESA 1995

Otherwise 1 0.5

2 National Accounts base year Annual chain linking Within past 10 years Otherwise 1 0.5

3 Classification of national industry

Latest version is adopted (ISIC Rev 4, NACE Rev 2 or a compatible classification)

Previous version is used (ISIC Rev 3, NACE Rev 1 or a compatible classification)

Otherwise 1 1

4 CPI base year Annual chain linking Within past 10 years Otherwise 1 1

5 Classification of household consumption

Follow Classification of Individual Consumption by Purpose (COICOP)

N.A. Otherwise 1 1

6 Classification of status of employment

Follow International Labor Organization, International Classification of Status in Employment (ICSE-93)

N.A. Otherwise 1 1

7 Central government accounting status

Consolidated central government accounting follows noncash recording basis

Consolidated central government accounting follows cash recording basis

Otherwise 1 0.5

8 Compilation of government finance statistics

Follow the latest Government Finance Statistical Manual (2014)

Previous version is used (GFSM 2001)

Otherwise 1 0.5

9 Compilation of monetary and financial statistics

Follow the latest Monetary and Finance Statistics Manual (2000) or Monetary and Finance Statistics: Compilation Guide (2008)

N.A. Otherwise 1 1

10 SDDS/e-GDDS subscription Subscribing to IMF SDDS standards Subscribing to IMF e-GDDS standards

Otherwise 1 1

Maximum category score: 10 10 8

MSC Country Score = Weighted Score / Maximum Category Score X 100 80 Country Score 80

57

Censuses and Surveys Censuses

# Indicator Score 1 Score 0.5 Score 0 Weight Weighted score

1 Population & Housing census

Population census done within last 10 years

Population census done within last 20 years

Otherwise 1 1

2 Agriculture census Agriculture census done within last 10 years

Agriculture census done within last 20 years

Otherwise 1 1

3 Business/establishment census

Business/establishment census done within last 10 years

Business/establishment census done within last 20 years

Otherwise 1

3 2

Surveys

# Indicator Score 1 Score 0.6 Score 0.3 Score 0 Weight Weighted score

4 Household Survey on income/ consumption/expenditure/ budget/Integrated Survey

3 or more household surveys done within past 10 years;

2 household surveys done within past 10 years;

1 household survey done within past 10 years;

None within past 10 years

1 1

5

Agriculture survey

3 or more agriculture surveys done within past 10 years;

2 agriculture surveys done within past 10 years;

1 agriculture survey done within past 10 years;


1 1

6

Labor Force Survey

3 or more labor force surveys done within past 10 years;

2 labor force surveys done within past 10 years;

1 labor force survey done within past 10 years;


1 1

7 Health/Demographic survey

3 or more health surveys done within past 10 years;

2 health surveys done within past 10 years;

1 health survey done within past 10 years;


1 1

8

Business/establishment survey

3 or more business/establishment surveys done within past 10 years;

2 business/establishment surveys done within past 10 years;

1 business/ establishment survey done within past 10 years;


1 1

5 5


CS Country Score = Weighted Score / Maximum Category Score X 100 87.5

Country Score: 87.5

58

Dissemination Practices & Openness

1) Dissemination capacity of NSO

# Indicator Score 1 Score 0 Weight Weighted score

1 NSO has an Advance Release Calendar and it is published

Yes No 1 1

2 NSO has a listing of surveys and microdata sets (or NADA)

Yes No 1 0

3 NSO has a data portal Yes No 1 1

4 Time series indicators are available for download in reusable format for free

Yes No 1 1

5 Metadata is available providing definition, methodology, standards or classifications for existing data series

Yes No 1 1

6 NSO has conducted a user satisfaction survey

Yes No 1 1

7 Geospatial data available on NSO website Yes No 1 0

Maximum score for sub-category: 7 7 5

2) Openness of data

# Indicator Score Weight Weighted

score

8 Open Data Inventory ODIN Score/100

Year:2016; ODIN score: 46.8; Overall World Rank: 51

0 N.A.

Maximum score for sub-category: 0


DPO Country Score = Weighted Score/ Maximum Category Score X 100 71.43

Country Score: 71.43

59

Availability of Key Indicators

# Indicator Score 1 - Data available for

the latest year Score 0 Weight

Weighted score

1 Proportion of population living below the national poverty line Yes No 1 1

2 Prevalence of stunting among children under 5 years of age Yes No 1 0

3 Maternal mortality ratio Yes No 1 0

4 Proportion of births attended by skilled health personnel Yes No 1 0

5 Child immunization (proportion of one-year-old children immunized against measles) Yes No 1 1

6 Primary completion rate, both sexes (percent) Yes No 1 1

7 Adult literacy rate, population 15+ years, both sexes percent) Yes No 1 1

8 Proportion of population using safely managed drinking water services Yes No 1 1

9 Unemployment, total percent of total labor force) Yes No 1 0

10 Manufacturing value added as a proportion of GDP Yes No 1 1

11 Gross capital formation (percent of GDP) Yes No 1 0

12 GDP implicit price deflator (annual percent growth) Yes No 1 1

13 Net trade in goods and services (BoP, current US$) Yes No 1 1

14 Growth rates of household expenditure or income per capita among the bottom 40 per cent of the population

Yes No 1 0

15 Proportion of children under 5 years of age whose births have been registered with a civil authority (completeness of birth registration)

Yes No 1 0

16 Completeness of death registration with cause-of-death information Yes No 1 0


Availability of Key Indicators Country Score = Weighted Country Score/ Maximum Category Score X 100 50

Country Score: 50

Total SCI score 73.58

60

Scope of the SPI

The SPI framework is designed to capture different aspects of national statistical capacity

by employing most relevant and representative variables that are publicly available. In

order to link the SPI with SCI and, to some degree, maintain consistency both tools will be

prepared together for a few years (SPI will start from 2013) and SPI will gradually replace

SCI. Time series comparison could be done with the availability of data from 2013 to 2018

for both indicators.

The SPI is built around four main dimensions: Methodology, Standards and

Classifications; Censuses and Surveys; Dissemination Practices and Openness; and

Availability of Key Indicators.

Methodology, Standards and Classifications (MSC): Internationally accepted and

recommended methodology, classifications and standards provide the basis for national

statistical offices (NSOs) on data integration, facilitating data exchange and providing the

foundation for the preparation of relevant statistical indicators. This dimension aims to

assess whether national statistical systems have the necessary capacity to adopt and comply

with international statistical standards.

To keep the dimension simple and comparable across countries, the selection is based on

the categories under IMF SDDS standards that basically cover the following sectors: real

sector (national accounts, production index, labor market, price indices etc.), fiscal sector

(central government operations), financial sector and external sector (balance of payments,

external debt).1 Standards in the field of social statistics were also examined but not

selected due to lack of verifiable and actionable assessment criteria for all countries.

The 10 indicators cover important standards on macroeconomics and finance. Examples

include system of national accounts in use, classifications of household consumption and

status of employment, as well as central government accounting status. It is assumed that

if national statistical systems have necessary capacity (human, physical and financial), they

will be able to adopt and employ these standards and receive higher scores and rankings.

This section is also considered to be the basis for the following three sections, as the

collection of quality statistics, and the dissemination of them, are to large extent the results

of following well established methods and standards that are in line with international

recommendations.

Censuses and Surveys (CS): Data collection is the key responsibility of national statistical

systems where information on a nation’s population, economy, health and other aspects are

recorded in an accurate and timely manner. Through censuses and surveys, sometimes

together with administrative systems, the NSSs collect data and generate aggregate

indicators based on the results. This dimension aims to check the availability and frequency

of key censuses and inter-census surveys.

1 The Special Data Dissemination Standard, Guide for Subscribers and Users.

61

The required frequencies of censuses and surveys are established based on international

recommendations (Table 1). In some cases, criteria are adjusted to avoid unnecessarily

punishing the least developed countries where there is huge disparities among country

practices. For example, with labor force survey and establishment survey, the SPI loosened

the criteria compared to the international recommendation.

The use of administrative data in producing official statistics, particularly in advanced

statistical systems, has become an integral part of the data production process, however in

order to make this indicator verifiable and comparable administrative systems such as

population and business registers are not included in rating.

This dimension covers eight indicators on population and housing census, agricultural

census, business census, income and expenditure surveys and other surveys on agriculture,

health, labor force and establishments.

Table 1. Recommended frequencies of data collection with sources

Census/Survey SCI recommended frequency of collection

Source of expert

recommendation on frequency2

Population and Housing Census Every 10 years UNSD

Agriculture census Every 10 years UN-FAO

Business/establishment census Every 10 years DESA-UNSD

Household survey on income/consumption

Every 3 years World Bank

Agriculture survey Every 3 years European Union (FSS 2.5 years); UN-FAO (Yield surveys 5 years)

Labor force survey Every 3 years ILO (recommend monthly/quarterly)

Health/demographic survey Every 3 years DHS program/UNICEF/World Bank (Every 2.5/3 years)

Establishment/industry survey Every 3 years UNIDO (recommend annual)

Dissemination Practices and Openness (DPO): Data users are seen as an integral part of

the national statistical system, which is crucial to the improvement of collection, processing

and dissemination of quality data. Therefore, dissemination practices of statistical systems

reflect an important part of the overall statistical capacity. This dimension is built on the

principle that quality statistics should be delivered to the public in a timely, easily

accessible manner for free. It includes eight indicators under two sub-sections:

Dissemination capacity of NSO and Openness of Data. It should be noted that Openness

2 For detailed explanation of sources, please refer to the metadata section.

62

of Data is measured by Open Data Inventory (ODIN) that was developed by a third party3,

therefore, it is not used for overall scoring and rating.

Availability of Key Indicators (AKI): Transforming source data into statistical outputs

(indicators) and releasing them on a timely basis shows that the statistical systems are

utilizing their capacity in data production. Reporting relevant data to specialized

international agencies on time and getting them published in their respective databases

demonstrates that statistical systems meet required quality standards and timeliness.

Therefore, this dimension evaluates national statistical systems by reviewing the

availability of country data for the most recent year in international databases. By looking

at the data availability in international databases, it also makes the assessment cost-

effective.

The selection of the indicators under the AKI dimension is based on the following

principles:

• It should provide some assessment of national statistical performance, i.e. the

indicators should be produced by countries;

• The availability of indicators should be verifiable, with established standards and

methodologies in producing the statistics.

• It should help addressing the development concerns of countries, especially with

SDGs. 12 out of 16 indicators included in this category are from the Tier 1 SDG

list that are conceptually clear, established methodology and standards are available

and data regularly produced by countries;

These selected indicators cover key socio-economic and SDG indicators that have well

established standards and methodology in the area of poverty, health, education, and

economic development. It is assumed that if national statistical systems have capacity in

the first two dimensions they should be able to produce these selected indicators.

These four dimensions are closely linked and capture the production cycle of national

statistical systems in collecting, producing and disseminating quality statistics. By

following internationally recommended standards and classifications, statistical systems

will have the basic foundations for data collection that will make produced data comparable

with other countries. Then, ideally with a combination of administrative sources and timely

censuses and surveys, statistical systems will collect, process and analyze relevant data and

generate necessary indicators as data products covering different aspects of households and

establishments. Finally, statistical systems will disseminate these final data products

through their official websites, regular publications and by submitting them to relevant

international organizations. Through this cycle statistical systems produce statistics that

reflect the socio-economic conditions of the nation and inform decision making.

3 There are several indices that measure the state of openness: ODIN, ODI (Open Data Index) and ODB (Open Data

Barometer). ODIN was selected as the openness indicator due to its broader country coverage and its use of publicly available data sources.

63

Scoring and Ranking Countries with the SPI

The overall SPI score is a composite index made up of 41 sub-indicators under four

dimensions. The indicator selection process is guided by conventions of international

agencies, expert opinions on statistical performance and the principles of SDGs. However,

given the cost and time constraints and the accuracy concerns of assessment, trade-offs

have to be made to build an actionable, cost-effective and internationally comparable index.

One such trade-off is the equal weighting of each dimension and individual indicator, even

though some of them may be more important than others or countries may assign higher

priority to some than others. The equal weighting selection may be, to some extent biased,

partly failing to address the relative importance of the MSC section. This could be checked

by simulations that will show the sensitivity of SCI scores and rankings in relation to

alternative weights.

To aggregate the scores of four dimensions into an overall SPI score and to create the

composite index the quadratic mean approach is used. Linear model or additive model was

not adopted because of its substitutional nature, in which a higher score of one dimension

can offset a low score of another and may result in a decent overall score for the country.

The designed aggregation method, in contrast, will give higher scores to countries that

perform relatively balanced on all three dimensions. Hence:

𝑇𝑜𝑡𝑎𝑙 𝑆𝐶𝐼 𝑠𝑐𝑜𝑟𝑒 = √(𝑀𝑆𝐶2 + 𝐶𝑆2 + 𝐷𝑃𝑂2 + 𝐴𝐾𝐼2)/4

Each of the four dimensions has a scale of 1-100 and are aggregated by using the quadratic

mean approach into a total score which also ranges from 1 to 100.

While the SPI aims to provide assessment for all countries included in the World

Development Indicators (WDI) and provide meaningful rankings of their statistical

performance, heterogeneity exists among countries along various dimensions such as

income level, population size, and security situation. OECD countries, for example, have

not traditionally reported to international organizations their statistics on maternal

mortality or stunting prevalence. These missing data are not necessarily an indication of

poor statistical capacity. And it may not be meaningful to compare small island countries

with countries with a large population size such as China or India. For another example,

fragile and conflict-affected countries may, by choice, give priority to other issues rather

than improving their statistical capacity.

As a result, the SPI will group and rank countries by similar characteristics to increase the

accuracy and accountability of the index. In addition, using well-defined country

classifications (such as high income vs. low income) better connects the SCI with the

Bank’s operations, which typically make extensive use of country classifications.

64

KAZAKHSTAN


ANNEX 9. ECONOMIC AND FINANCIAL ANALYSIS

N/A

65

KAZAKHSTAN


ANNEX 10. BANK LENDING AND IMPLEMENTATION SUPPORT/SUPERVISION PROCESSES

(a) Task Team members

Names Title Unit Responsibility/

Specialty

Lending

Mustafa Dinc Senior Economist/Statistician DECDG TTL

Gulnara Febres Senior Operations Officer L DECDG TTL

Ilyas Sarsenov Economist ECSPE

Yeraly Beksultan Operations Analyst ECCKZ

Grant J. Cameron Manager–Technical Advisor DECDG

Nurbek Kurmanaliev Procurement Specialist ECSC2

John Otieno Ogallo Senior FM Specialist ECSC3

Aliya Kim Finance Assistant ECCKA

Joseph Formoso Senior Finance Officer CTRFC

Ignacio Jauregui Counsel LEGEM

Cevdet A. Denizer Lead Economist CFPIR Peer Reviewer

Yoichiro Ishihara Senior Economist OPCAE Peer Reviewer

Mohammed Omar Hadi Sr. Program Assistant DECDG

Supervision/ICR

Mustafa Dunc Senior Economist/Statistician DECAE TTL

Buyant Erdene Khaltarkhuu Statistician DECAE

Gulmira Akshatyrova Program Assistant ECCKZ

Nurbek Kurmanaliev Procurement Specialist ECCKZ

Ilyas Sarsenov Senior Economist GMF11

Aliya Kim Finance Assistant ECCKZ

Olga Shabalina Senior Economist/Statistician DECAE ICR

Judericas Dias Senior Statistical Assistant DECAE ICR

Christelle Signo Kouame Program Assistant DECAE ICR

Kenneth Zaul Moreno

Sermeno Team Assistant DECDC

66

(b) Staff Time and Cost

Stage of Project Cycle Staff Time and Cost (Bank Budget Only)

No. of staff weeks USD Thousands (including

travel and consultant costs)

Lending 53.4 $164,875

Supervision/ICR 124.7 $513,936

Total: 178 $678,808

67

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ANNEX 11. BENEFICIARY SURVEY RESULTS

N/A

ANNEX 12. STAKEHOLDER WORKSHOP REPORT AND RESULTS

N/A

ANNEX 13. SUMMARY OF BORROWER'S ICR AND/OR COMMENTS ON DRAFT ICR

N/A

ANNEX 14. COMMENTS OF COFINANCIERS AND OTHER PARTNERS/STAKEHOLDERS

N/A

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ANNEX 15. LIST OF SUPPORTING DOCUMENTS

1. World Bank (March 2012). Country Partnership Strategy for the Republic of

Kazakhstan (2012-2017). Report No. 67876-KZ

2. PARIS21, 2010, Advocating for the National Strategy for Development Statistics:

Country Level Toolkit, Organization for Economic Cooperation and Development

3. Global Assessment of Statistical System of Republic of Kazakhstan by UNECE,

UNESCAP. February 2008

4. Project Appraisal Document March, 2011

5. Grant Agreement dated August 26, 2011

6. Aide-Memoires of Implementation Support/Supervision Missions

7. Mid-term review mission report. October 2014

8. Implementation Status and Results Reports

9. Ministry of National Economy, Committee on Statistics. KAZSTAT Twinning

Partnership.2016

10. Master Plan for Development of the National Statistical System of the Republic of

Kazakhstan (2017-2025). January, 2025.

11. Joint Government of Kazakhstan – ADB Knowledge and Experience exchange

program. Measurement of Kazakhstan’s Service Sector: Statistical issue. 2015

12. IMF. Kazakhstan: 2017 Article IV Consultation

13. Global Assessment of Statistical System of Republic of Kazakhstan by UNECE,

EFTA, Eurostat. 2017

14. Bank Guidance and Procedures (OPCS ICRR Guidance, August 2006. Updated July

2014.

OPSPQ Instructions: Investment Project Financing Implementation Support to project

completion, February 2016.

ICR OPCS presentations, materials from IEG ICR trainings.

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MAP

.