JUNE, 2025
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Table of contents
Table of contents ...................................................................................................................... i Definition of terms ................................................................................................................. ii Abbreviation .......................................................................................................................... iv 1. Introduction ..................................................................................................................... 1 2. Objectives ......................................................................................................................... 2 3. Methodology .................................................................................................................... 2 4. Scope ................................................................................................................................. 2 5. Detailed Assessment Results ......................................................................................... 3 6. Conclusion ..................................................................................................................... 29 7. Recommendations ......................................................................................................... 31 8. References ...................................................................................................................... 32
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Definition of terms Dimension highest level of data quality assessment according to IMF where five broad data quality dimensions are commonly Element second level of data quality assessment according to IMF where granular quality dimensions are considered. Indicator third level of data quality assessment where components of quality elements are identified. Focal issue provides more detail for each indicator that is tailored to the dataset in question Key point identifies quality features that may be considered in addressing the focal issues. The key points are meant to be suggestive, not exhaustive Relevance the extent to which the statistics satisfy the needs of the users Accuracy the closeness of estimates to the exact or true values that the statistics were intended to measure. Reliability the closeness of the initially estimated value(s) to the subsequent estimated value(s) if preliminary figures are disseminated. Timeliness the length of time between the end of a reference period (or date) and the dissemination of the statistics. Punctuality the time lag between the release date and the target date by which the data or statistics should have been delivered. Clarity the availability of appropriate documentation relating to the statistics and the additional assistance that producers make available to users. Coherence the ability to reliably combine statistics and data sets in different ways and for various uses. Consistency is often used as a synonym for coherence. Comparability the extent to which differences in statistics from different geographical areas, non-geographical domains, or over time, can be attributed to differences between the true values of the statistics. Full compliance could be defined as meeting at least 80 per cent of the applicable key points (only little room for improvement).
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Partial
compliance
meeting between 30 and 80 per cent of the applicable key points
(some major improvements are needed)
No compliance
meeting at most 30 per cent of the applicable key points (urgent
action is necessary).
Not applicable
an item is not part of the practice in the methodology or process
of the statistical product which is assessed.
Prerequisites of
quality
Although not itself a dimension of quality, this group of “pointers
to quality” includes elements and indicators that have an
overarching role as prerequisites, or institutional preconditions,
for quality of statistics.
Assurances
of
integrity
This dimension relates to the adherence to the principle of
objectivity in the collection, compilation, and dissemination of
statistics.
The
dimension
encompasses
institutional
arrangements that ensure professionalism in statistical policies
and practices, transparency, and ethical standards.
Methodological
soundness
This dimension covers the idea that the methodological basis for
the production of statistics should be sound and that this can be
attained
following
internationally
accepted
standards,
guidelines, or good practices. This dimension is necessarily
dataset-specific, reflecting different methodologies for different
datasets
Accuracy
and
reliability
This dimension covers the idea that statistical outputs sufficiently
portray the reality of the economy This dimension is also data
specific, reflecting the sources used and their processing.
Serviceability
This dimension relates to the need that statistics are disseminated
with an appropriate periodicity in a timely fashion, are consistent
internally and with other major datasets, and follow a regular
revision policy.
Accessibility
This dimension relates to the need for data and metadata to
presented in a clear and understandable manner on an easily
available and impartial basis, that metadata are up-to-date and
pertinent, and that a prompt and knowledgeable support service
is available.
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Abbreviation
CAPI
Computer Assisted Personal Interview
CPC
Central Product Classification
DQA
Data Quality Assessment
DQAF
Data Quality Assessment Framework
GDDS
General Data Dissemination System
IMF
International Monitoring Fund
ITDM
MEFMI
Information, Technology and Data Management
Microeconomic and Financial Management Institute of Eastern
and Southern Africa
MoF
Ministry of Finance
MoU
Memorandum of Understanding
MTEF
Medium-Term Expenditure Framework
NBS
National Bureau of Statistics
NSS
National Statistical System
OCGS
PAS
Office of Chief Government Statistics
Pan African Statistics
PEPMIS
PPI
Performance Management Information System
Producer Price Index
RSM
SADC
Regional Statistics Managers
Southern African Development Community
SDDS
Data Dissemination Standard
SNA
System of National Account
TDQAF
Tanzania Data Quality Assurance Framework
TSMP
UNIDO
Tanzania Statistical Master Plan United Nations Industrial Development Organization
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- Introduction
The National Bureau of Statistics (NBS) has the responsibility of coordinating,
producing, and disseminating official statistics. In addition, the NBS, as the mandated
oversight institutions for producing statistics in Mainland Tanzania acknowledge the
importance of providing relevant and quality statistics to users.
Through Tanzania Statistical Master Plan Phase Two (TSMP II) 2022/23-2026/27 a
development goal has been set to strengthen the National Statistical System (NSS) in
Tanzania to enable it to produce quality statistics for decision makers in an objective
timely, and cost-effective manner. Production of high quality statistics depends on the
assessment of data quality. Lacking of a systematic assessment of data quality, the
Bureau will risk to lose control of the various statistical processes such as data
collection, editing or weighting. Doing without data quality assessment would result
in assuming that the processes cannot be further improved and that problems will
always be detected without systematic analysis.
Given the varied quality of the official statistics and the increased demand for data
use at all levels, the NBS embarked on this data quality assessment (DQA) to
characterize the quality of routine data, and to identify factors associated with the
quality and use of routine data in Mainland Tanzania. Understanding data quality,
processes of data collection and the associated barriers to enhancing quality helps to
formulate tailor-made strategies to improve data quality and use.
This report provides detailed information on indicators of statistical practices in the
areas of the Producer Price Index (PPI) which was gathered from the assessment
conducted by the department of research and standards and publicly available
documents. The information was provided by the experts of the department of
industrial and construction statistics and other supporting departments of the
National Bureau of Statistics. This assessment was conducted in lines of the generic
IMF - Data Quality Assessment Framework (DQAF) for the Producer Price Index and
used to prepare the summary assessment of data quality elements based on a four-
part scale of compliance which is full compliance, partial compliance, no compliance
and not applicable.
The Data Quality Assessment Framework (DQAF) for the Producer Price Index identifies quality-related features of Governance statistical systems, statistical processes, and statistical products. It is rooted in the UN Fundamental Principles of Official Statistics and grew out of the Special Data Dissemination Standard (SDDS) and General Data Dissemination System (GDDS), the IMF’s initiatives on data dissemination.
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- Objectives The main purpose for conducting qualitative assessment for the Producer Price Index was to ensure that NBS is aware of the strengths, weaknesses (risks), and limitations of the PPI data performance as well as the extent to which the data can be trusted to influence management decisions and eventually, the identification of possible improvement actions.
- Methodology The Research and Standards Department in ensuring that data quality assessment for the PPI is undertaken successfully, the key procedures for conducting the assessment was followed including: issuing the roadmap for the assessment; undertaking orientation to the NBS Management and staff who are responsible for the production of PPI and other staff who were important to some of the assessed quality dimensions such as human resource officers, legal officers, planning officers, information and communication technology officers. After orientation the pre-assessment and actual assessment was conducted and the report was prepared and reviewed for finalisation.
- Scope The assessment was based on levels whereby the first level covers the prerequisites of quality and five dimensions of quality including: assurances of integrity; methodological soundness; accuracy and reliability; serviceability; and accessibility. For each of these prerequisites and five dimensions, there are elements (two-digit level) and indicators (three-digit level). At the next level, focal issues that are specific to the compilation of the PPI were addressed.
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Detailed Assessment Results The following are detailed results of the PPI assessment based on the four (4) levels of the assessment checklist which are dimension, element, indicator and focal issue with narration and links to relative supporting documents such as the Statistics Act CAP. 351, 2008 SNA, PPI Manual Theory and Practice 2004, Industrial Statistics Guidelines and Methodology 2010, Advance Release Calendar, NBS staff regulation, Scheme of Service, NBS strategic plan and statistical guidelines.
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Prerequisites of quality
0.1 Legal and institutional environment
0.1.1 The responsibility for collecting, processing, and disseminating the statistics is clearly specified.
• The primary responsibility for collecting, processing, and disseminating the statistics is clearly established.
The statistics Act CAP. 351 give mandate NBS to collect, compile, analyze and disseminate official statistics. The Statistician General delegate the powers to the government institutions/agencies to collect and publish official statistics subject to guidelines issued by the Bureau. The statistics produced by institutions/agencies shall qualify to be official statistics if they meet criteria set by the bureau and approved by the Statistician General. The bureau can also make any agreement with any agency to jointly collect official statistics as the need arises. The Statistics Act can be downloaded from https://www.nbs.go.tz/publications/acts-and-regulations Producer Price Index is produced by NBS only. Other agencies are not producing PPI statistics, but they are providing inputs for the production of PPI. There are no any challenges of duplication of effort and reporting burden. Conflicts or potential conflicts between the legal authority to produce the statistics and other laws or provisions (e.g. access to information law or bank secrecy laws) have been successfully resolved or reconciled with no major impairment to the data production as provided in section 46 of the Statistics Act CAP. 351. Oversight of the NBS is conducted in order to ensure that statistical work accords with the laws or other provisions governing such work. This is stipulated in the section 26, 27 and 28 of the Statistics Act
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whereby NBS have the right to challenge statistical information from other source and every person have the right to challenge official statistics produced by NBS.
0.1.2 Data sharing and coordination among data-producing agencies are adequate.
• Arrangements or procedures exist to facilitate data sharing and coordination between the agency (agencies) with the primary responsibility for compiling the statistics and other data producing agencies.
Section 17 of the Statistics Act gives NBS the responsibility of coordinating the National Statistical System (NSS) with a view of having an integrated statistical system to ensure optimal utilization of available resources. The NSS includes data providers, producers and users of statistics such as NSO, MDAs, CSOs, research and academic institutions.
The Act provides a comprehensive approach to statistical cooperation in Tanzania, including access to data for the purposes of official statistics production. In access to public or other records, the collection of statistics related to any matter may be obtained from any Government institution, agency, or user or producer of statistics. The Statistician General shall grant access to authorized officer or staff of the Bureau for the purpose of getting information.
The Statistics Act empowers the Statistician General of NBS to share data at the request of any person or agency free of charge, provided the data shared is not about individual persons or entities.
The law does not enforce directly on the flow of source data. Mostly Memorandum of Understanding (MoU) are used in data sharing. NBS has MoU with the key data providers and users to facilitate data sharing and ensure access of data in a standardized manner.
0.1.3 Individual reporters’ data are to be kept confidential and used for statistical purposes only
• The confidentiality of individual reporters’ data is guaranteed and that guarantee is widely known.
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Sections 31, 33, 34, 35 and 43 of the Statistics Act CAP. 351 stipulate restrictions to disclosure of identifiable information and NBS cannot publish, or otherwise make available to any individual or organization, information that would enable the identification of any individual person or entity.
During the inquiries of prices from establishments, respondents are informed of their rights and obligations with regard to provision of information and they are informed that the information provided will be used for the purpose of producing PPI. The consent embedded in the questionnaire is used to assure the confidentiality of information provided by respondent from establishment.
• Procedures are in place to prevent disclosure of individual reporters’ data.
Any person other than staff of the Bureau who is employed in the
execution of any duty relating to statistical production under statistics
Act are obliged to sign an oath of secrecy for the confidentiality of the
statistics collected as stipulated in section 14. NBS Penalties for
disclosure of information are also insisted in the Statistics Act CAP.
351 under section 43.
The Bureau also takes all necessary steps to ensure the security and confidentiality of the information provided where access to individual data is restricted to responsible staff and are kept in accordance with the provision of the Act.
Documentation for statistical products is always done in a secure manner. Staff responsible for production of PPI review all data prepared for dissemination for possible indirect disclosure of individual person or entity information and design tables and outputs in a way that prevents disclosure.
Information collected are stored in the NBS server and staff has password to prevent unauthorized access to individual or establishment data. For research purpose, the confidentiality of individuals and entity is protected by anonymization of all records.
Information is only disseminated in an aggregated manner through statistical releases and/or on the NBS website. Statistics Act, CAP. 351 Section 32, 34, and 43 (1) (b)