GDP Rebasing and the Visibility of Micro, Small and Medium Enterprises in South Africa: Implications for Development Policy

1. Introduction

GDP rebasing and national-accounts re-benchmarking alter the reference structure through which economic activity is measured and interpreted. Such revisions may change estimates of output, employment, sectoral composition and economic growth, but a revised aggregate baseline does not necessarily reveal the activities of enterprises that remain informal, poorly documented or weakly connected to administrative systems. This issue is particularly important for South African MSMEs, which contribute to livelihoods and local economic activity while facing constraints related to finance, infrastructure, skills, electricity, and institutional support (Ledingoane & Viljoen, 2020; Nkohla, 2024).

The supplied literature indicates that MSME visibility is shaped by enterprise characteristics and institutional conditions. Evidence from Tanzania shows that written accounts, full-time operation, business knowledge, infrastructure, technology and financial access are associated with enterprise productivity and classification into more formal or intermediate sectors (Diao et al., 2016). South African evidence from Diepsloot similarly describes a predominantly informal enterprise population, limited access to formal finance and multiple constraints on growth, including inadequate electricity, roads, management skills and government funding (Ledingoane & Viljoen, 2020). These findings suggest that statistical visibility is not simply a technical property of national accounts; it also depends on whether enterprises generate records and operate through systems capable of producing usable data.

The literature also suggests that revisions to economic measurement can change how national economic conditions are interpreted. Evidence from Nigeria links GDP rebasing with changes in the reported economic baseline and identifies sectors whose employment activity was underreported, while evidence from Vietnam and the United States shows that revised or adjusted national-account measures can alter macroeconomic estimates and their interpretation (Ndubuaku et al., 2021; Nguyen, 2025; Rassier, 2023). However, these studies do not establish that rebasing improves the visibility of South African MSMEs. The supplied synthesis found no studies directly examining South African MSME treatment in supply-and-use tables, benchmark revisions, or post-rebasing policy outcomes.

This review was therefore required to integrate evidence across MSME measurement, national-account revision and development-policy contexts while preserving the limits of cross-country transferability. It examines whether the available evidence supports claims about the relationship between rebasing and MSME visibility, identifies enabling conditions and implementation risks, and clarifies the empirical gaps that must be addressed before policy conclusions can be treated as robust.

2. Research Objectives

RO1: To examine how Gross Domestic Product (GDP) rebasing and national accounts re-benchmarking influence the statistical visibility of MSMEs and associated implications for development policy among Micro, Small and Medium Enterprises (MSMEs) and small business sectors within South Africa.

RO2: To identify the principal opportunities, benefits, and enabling conditions associated with Gross Domestic Product (GDP) rebasing and national accounts re-benchmarking in relation to the Statistical visibility of MSMEs and the associated implications for development policy.

RO3: To analyse the challenges, risks, ethical considerations and implementation barriers associated with Gross Domestic Product (GDP) rebasing and national accounts re-benchmarking for Micro, Small and Medium Enterprises (MSMEs) and small business sectors.

RO4: To examine the contextual, institutional and practice-related factors that shape the adoption and effective use of Gross Domestic Product (GDP) rebasing and national accounts re-benchmarking within South Africa.

RO5: To identify gaps in the available evidence and derive implications for future research, policy and practice relevant to • GDP Rebasing and the Visibility of Micro, Small and Medium Enterprises in South Africa: Implications for Development Policy.

3. Research Methods

3.1. Review Design

A Systematic Review was selected because the question required a transparent and reproducible identification, appraisal and synthesis of heterogeneous evidence concerning national-account revision, MSME conditions and policy implications. We treated evidence synthesis as the structured integration of findings across studies rather than a simple narrative catalogue. The design distinguishes PRISMA as a reporting framework, SALSA as a way of understanding searching, appraisal, synthesis and analysis, CASP as the study-level critical-appraisal tool, and COSTAQDA as software support for traceable qualitative evidence synthesis (Grant & Booth, 2009; Page et al., 2021; Costa & Costa, 2024; Costa & Mfolo, 2024).

3.2. Search Strategy and Information Sources

The researcher selected Google Scholar and ERIC as databases and information sources. The eligibility protocol restricted publication years to 2015–2026. The verified identification provenance did not record the exact calendar date of search execution; this differs from the publication-year eligibility range.

Full Boolean search string (exactly as recorded)

("Micro, Small and Medium Enterprises (MSMEs) in South Africa" OR "GDP rebasing" OR "national accounts rebasing" OR "GDP rebenchmarking" OR "base year revision" OR "national accounting revision") AND ("GDP rebasing and national accounts re-benchmarking" OR MSMEs OR MSME OR SMEs OR SME OR microenterprises OR "small businesses" OR "informal sector enterprises") AND ("Statistical and economic visibility of MSMEs and subsequent implications for national development policy" OR "economic visibility" OR "statistical visibility" OR "development policy" OR "economic policy" OR "policy implications") NOT ("multinational corporations" OR "stock market trading")

3.3. Inclusion and Exclusion Criteria

Inclusion

• Studies focusing on or incorporating Micro, Small and Medium Enterprises (MSMEs) within the economic analysis.
• Studies investigating or evaluating the processes, methodologies, or effects of GDP rebasing or national accounts re-benchmarking.
• Studies examining outcomes related to the statistical visibility, economic visibility, or national development policy implications for MSMEs.
• Studies conducted within the context of South African national economic accounting or policy frameworks.
• Studies published between 2015 and 2026 inclusive.
• Studies published in the English language.
• Studies published as peer-reviewed journal articles.

Exclusion

• Studies focusing exclusively on large corporations, public sector entities, or non-MSME sectors without data or analysis relevant to MSMEs.
• Studies that do not address GDP rebasing, national accounts re-benchmarking, or national economic accounting revisions.
• Studies that lack evaluation or discussion of statistical visibility, economic visibility, or development policy implications for MSMEs.
• Studies set entirely outside the context of South Africa without explicit application to South African economic or policy frameworks.
• Studies published prior to 2015 or after 2026.
• Studies published in languages other than English.
• Non-peer-reviewed publications, including book chapters, conference abstracts, dissertations, working papers, editorials, and grey literature reports.

3.4. Screening and Study Selection

The PRISMA selection counts are persisted, but the decision rule used during title/abstract screening is not available in the verified audit payload. COSTAQDA therefore reports the recorded workflow counts without reconstructing an unverified screening procedure.

The persisted PRISMA workflow records 150 identified records, 73 duplicates, 77 records screened, 77 reports sought for retrieval, 0 records excluded at the title/abstract stage, 28 full texts assessed, 0 full-text exclusions and 28 included records. These counts describe study selection and are not substantive review findings.

Figure 1. PRISMA 2020 Flow Diagram.

Figure 1. PRISMA 2020 Flow Diagram.

The PRISMA figure should be read as a transparent representation of the recorded selection workflow: 150 records identified, 73 duplicates removed, 77 records screened, 77 reports sought, 28 full texts assessed and 28 studies included, with no recorded title or abstract exclusions and no recorded full-text exclusions. The figure documents selection flow rather than the substantive strength, relevance or direction of evidence. The absence of a preserved screening decision rule limits independent reconstruction of the screening process, and the supplied count checks do not establish full PRISMA compliance (Page et al., 2021).

3.5. Critical Appraisal

CASP was used in the PRISMA full-text workspace, and all 28 currently included studies had completed appraisals. The Critical Appraisal Skills Programme provides structured questions for examining methodological validity, findings and relevance; the supplied workspace identifies CASP as the appraisal tool and records study-level scores. Because the included evidence was heterogeneous, CASP results were interpreted as methodological prompts rather than as an unquestioned total-quality score (Critical Appraisal Skills Programme, 2024; Long et al., 2020).

The recorded mean CASP score was 14.82, with study-level scores ranging from 12 to 19 in the supplied summary. This distribution indicates variation in the documented appraisal record, but it cannot establish a pooled level of methodological quality or justify ranking studies solely by their scores. The workspace also records methodological concerns for many studies through criterion labels such as CASP-2, CASP-3, CASP-6, CASP-7, and CASP-8. These labels identify areas requiring caution, but the supplied record does not provide complete criterion-level rationales for every study.

Several appraisals were completed conservatively because the configured appraisal service was unavailable. The recorded decision narrative states that supported answers were based on text found in the article and unsupported criteria were marked Can't tell pending researcher verification. Consequently, missing reporting must be distinguished from demonstrated methodological weakness. The appraisal record permits study-linked caution, but it does not support a definitive comparative hierarchy of evidence quality (Long et al., 2020; Noyes et al., 2018).

The appraisal limitations are especially relevant because the synthesis combines South African enterprise evidence with comparative studies of rebasing, national accounts and macroeconomic measurement from other countries. Concerns about design reporting, sampling, analytic transparency and applicability constrain the extent to which comparative findings can be transferred to South African MSME accounting. The strongest conclusions therefore remained conditional propositions supported across the extracted evidence, rather than claims that rebasing improves MSME visibility.

COSTAQDA supported traceability from extracted findings to codes, categories, and themes, making the relationship between source evidence and interpretation inspectable (Costa & Costa, 2024). Nevertheless, the project did not include a separate synthesis of methodological limitations or a finding-level confidence method. CASP appraisal and bibliometric prominence were therefore not treated as substitutes for a formal confidence assessment of individual qualitative findings (Noyes et al., 2018; Lewin et al., 2018).

Figure 2. CASP Critical Appraisal Intelligence.

Figure 2. CASP Critical Appraisal Intelligence.

The CASP figure represents completed study-level appraisals for 28 included studies and a recorded mean score of 14.82. It is appropriate as a descriptive view of the appraisal workspace because it shows that every included study received a CASP assessment. However, the figure should not be interpreted as a validated aggregate quality score, a confidence rating or a measure of causal strength.

The observable pattern is variation in recorded study scores, including scores from 12 to 19 among the supplied study-linked entries, alongside multiple criterion-level methodological concerns. The pattern supports a cautious reading of the evidence base, particularly where findings are drawn from repositories, working papers, books, reports or studies with incomplete extracted methodological information. It does not establish that higher-scoring studies provide more applicable evidence for South African national-accounting questions.

Interpretation is further limited because several appraisal decisions were conservative text-evidence appraisals generated when the configured appraisal service was unavailable, with unsupported criteria recorded as Can't tell pending researcher verification. Thus, the figure captures the state of the appraisal workspace rather than an independently verified assessment of every criterion. CASP should inform, but not replace, nuanced consideration of methodological limitations in qualitative synthesis (Long et al., 2020; Noyes et al., 2018).

The CASP figure also cannot supply finding-level confidence. No CERQual assessment was recorded, and the review did not assign confidence ratings to the analytical themes. The figure should therefore be interpreted alongside convergence, divergence, contextual transferability and the directness of extracted evidence rather than as a basis for numerical certainty (Lewin et al., 2018).

3.6. Data Extraction

Data extraction was not recorded as a separate procedural field in the project record. Nevertheless, the verified synthesis workspace contains 224 extracted findings from 25 studies, with finding IDs, study IDs, text and evidence fields retained for synthesis. T,his permits reporting of the actual synthesis pathway, but it does not permit reconstruction of an independent extraction form, duplicate extraction process, extractor training or verification procedure.

3.7. Data Synthesis and Analysis

Qualitative evidence synthesis was conducted on 224 extracted findings contributed by 25 studies. The COSTAQDA synthesis engine applied thematic synthesis, moving from traceable finding-level evidence to 5 initial codes, 2 categories, 1 descriptive theme and 2 analytical themes.

Theme development was constrained to the extracted, finding-level evidence from eligible studies. Each synthesised theme retained supporting study IDs and finding IDs, while contradictory evidence was preserved where identified. Titles, abstracts and bibliographic prominence were not treated as substitutes for extracted qualitative findings.

Recorded synthesis limitations included: No supplied finding directly examines GDP rebasing or national-accounts re-benchmarking for MSMEs in South Africa. Most findings concern informal enterprise conditions in South Africa or rebasing and national-account issues in other countries; cross-country transferability is therefore limited. Several extracted items are methodological descriptions, statistical tables, references or incomplete text rather than substantive findings; he supplied evidence does not document South African national statistical procedures, MSME treatment in supply-and-use tables, benchmark revisions, or post-rebasing policy outcomes.; The evidence base does not provide direct MSME participant perspectives on rebasing, data collection, privacy, reporting burdens or perceived risks.; Any implication that rebasing increases MSME visibility remains conditional and should be tested with South African administrative, survey and national-accounts data..

3.8. Bibliometric Intelligence and Confidence in the Evidence Base

Bibliometric intelligence provides a structural view of the evidence base that complements PRISMA selection, critical appraisal and qualitative synthesis. The following analyses examine citation relationships, scholarly influence, evidence connectivity and knowledge development within the included corpus. They provide contextual evidence about the intellectual structure and provenance of the literature and are not substitutes for methodological quality appraisal.

3.8.1. Local Citation Network

The Local Citation Network maps citation relationships within the included evidence base. It shows how studies connect within the review corpus and supports examination of intellectual connectedness, centrality, bridging, and isolation. These citation relationships describe the structure of the literature and do not, by themselves, establish methodological quality or validity.

Figure 3. Local Citation Network.

Figure 3. Local Citation Network.

3.8.2. Influence Pyramid

The Influence Pyramid represents the distribution of scholarly influence within the included evidence base. It helps identify how bibliometric prominence is distributed across the reviewed studies. Influence is interpreted separately from methodological quality, which is assessed through critical appraisal.

Figure 4. Influence Pyramid.

Figure 4. Influence Pyramid.

The Influence Pyramid is appropriate as a descriptive bibliometric prominence visualisation because the project supplied OpenAlex-derived information for the 28 included studies. Its unit of analysis is included studies or publication nodes, with a recorded global-citation total of 62, local citations of 0, 0 links and 0 clusters. However, all supplied influenceScore values are 0, and the formula, citation coverage and comparability of the score were not recorded. The pyramid's construction and cross-study comparability therefore cannot be independently established.

The strongest observable pattern is not a substantive ranking of influence but the limited interpretability of the recorded metric: the project identifies groups labelled seminal, supporting and influential, while the node-level influenceScore remains 0 for the supplied nodes. These labels may help locate publications within the project’s evidence map, but they cannot be interpreted as citation counts, impact, quality, causality or consensus. The 62 global citations across 28 included nodes provide context for the retrieved publication set, not evidence for the review question.

The pyramid has no demonstrated relationship to CASP appraisal, thematic support or confidence in the findings. Bibliometric prominence can help describe the visibility of publications within a mapped corpus, but it cannot establish the methodological validity or policy applicability of evidence (Donthu et al., 2021; Zupic & Čater, 2015).

3.8.3. Evidence Strength

The Evidence Strength analysis examines the structure and strength of relationships within the evidence ecosystem assembled for the review. It complements, but does not replace, CASP methodological appraisal and must not be interpreted as a direct estimate of causal effect.

Figure 5. Evidence Strength Network.

Figure 5. Evidence Strength Network.

The Evidence Strength Network is available in the project workspace, but the supplied metadata record contains 0 links, 0 clusters and no edge relation types, weights or node-level strength variables. Therefore, a defensible interpretation of edge semantics or evidential relationships cannot be produced. The displayed structure can only be described as lacking recorded connections in the supplied network data.

Because no relation types or weights are available, the network cannot establish independent corroboration, study quality, causal strength, confidence or an observed effect. It must not replace CASP appraisal or the thematic synthesis. In this project, the more defensible account of evidence relationships comes from the traceable finding-to-code-to-theme pathway, not from unsupported interpretation of absent network edges (Donthu et al., 2021; Zupic & Čater, 2015).

3.8.4. Knowledge Evolution

Knowledge Evolution examines the temporal and intellectual development of the included evidence base. It traces how research contributions develop over time and, where supported by the Step 12 data, how later studies extend, connect, challenge or consolidate earlier contributions.

Figure 6. Knowledge Evolution.

Figure 6. Knowledge Evolution.

3.8.5. Integrated Confidence in the Synthesised Evidence

A separate finding-level confidence method was not recorded, and no GRADE-CERQual assessment was conducted. CASP was used for study-level methodological appraisal, while bibliometric outputs were treated as contextual evidence maps rather than components of a validated confidence score. Trustworthiness was considered through the convergence and divergence of extracted findings, appraisal limitations, directness to the South African question and cross-country transferability. Conclusions about rebasing and MSME visibility therefore remain conditional rather than formally confidence-rated (Noyes et al., 2018; Lewin et al., 2018).

4. Findings

4.1. Search and Selection Results

The recorded workflow identified 150 records and removed 73 duplicates, leaving 77 records screened. All 77 were recorded as sought for retrieval; 28 full texts were assessed, and all 28 were recorded as included. No records were excluded at title or abstract screening or at full-text assessment in the persisted counts. These figures describe the selection process and are not substantive findings. Because the verified audit does not preserve the screening decision rule, the review cannot determine whether the absence of recorded exclusions reflects broad initial relevance, incomplete audit detail or another procedural feature.

4.2. Characteristics of Included Studies

The 28 included records covered South African informal and small-business conditions; comparative MSME evidence from Tanzania, Nigeria, Jordan, India, Nepal, Indonesia, and other settings; and studies of GDP rebasing or national-account measurement in Nigeria, Vietnam, and the United States. The evidence types were heterogeneous and included journal articles, repository records, working papers, books, reports and other supplied publication forms. This diversity broadened conceptual coverage but weakened direct comparability with the review question, which specifically concerns South African MSMEs and national-account frameworks. The thematic synthesis used 25 studies and 224 extracted findings, rather than all 28 included studies, indicating that the synthesis denominator was narrower than the final inclusion count.

4.3. Methodological Strengths and Limitations of Included Studies

The evidence base contributed several useful methodological perspectives, including survey-based analysis of 349 informal enterprise owners in Diepsloot, nationally representative MSME analysis in Tanzania, time-series and ARDL studies, regression modelling and national-account adjustment analyses (Diao et al., 2016; Ledingoane & Viljoen, 2020; Ndubuaku et al., 2021; Rassier, 2023). However, the supplied extraction often lacked complete information on population, sampling, data collection and analysis. Some extracted items were incomplete text, tables, references or methodological descriptions. CASP was completed for all 28 included studies, but the workspace contains limited criterion-level rationale, and several Can't tell judgments, constraining confidence in cross-study comparisons.

4.4. Thematic Synthesis

Methodological basis: The thematic synthesis approach follows Thomas and Harden (2008), https://doi.org/10.1186/1471-2288-8-45. The study-specific findings and support counts below derive from the included evidence, not from this methodological citation.

Thematic synthesis is a systematic qualitative evidence-synthesis method that integrates findings across multiple studies while retaining a transparent connection to the underlying evidence. (Flemming & Noyes, 2021) The process moves iteratively from extracted study findings to coding, grouping related codes into descriptive categories or themes, and developing higher-order analytical themes that answer the review question and research objectives. Its purpose is not merely to count how often an idea appears, but to identify patterned meaning across studies, examine convergence and divergence, preserve contextual differences, and develop an auditable interpretation that remains traceable to the contributing evidence.

In this review, thematic synthesis was applied to the verified extracted findings retained in the active COSTAQDA project. Findings were compared across eligible studies, coded and grouped according to conceptual similarity, and then developed into 5 analytical themes represented across 10 evidence-contributing studies. The active synthesis retained 20 verified theme-to-study support assignments, keeping the analytical interpretation traceable to the underlying studies rather than reconstructing it from titles or bibliographic prominence. The resulting analytical themes include “Informality, record-keeping and the conditional visibility of MSMEs”, “Rebasing as an opportunity for a more accurate and policy-relevant baseline”, “Data, institutional and implementation barriers”, “Institutional capacity and the use of disaggregated evidence”, with the widest cross-study support recorded for “Institutional capacity and the use of disaggregated evidence” (5 contributing studies). Table 1 therefore operationalises the synthesis as an auditable evidence map linking each analytical theme to the studies that supplied verified supporting findings.

Table 1 presents the thematic synthesis matrix linking the verified analytical themes only to studies with verified extracted evidence supporting at least one of the themes displayed in the matrix. Any study with no verified supporting contribution to any displayed theme is excluded, even if it was included elsewhere in the systematic review or qualitative evidence base. Rows represent analytical themes and columns represent theme-contributing studies. A check mark (✓) indicates that at least one verified extracted finding from that study was assigned to the theme; an em dash (—) indicates that the study contributed evidence to the synthesis overall, but no supporting extracted finding from that study was assigned to that particular theme. The absence of a supporting assignment must not be interpreted as contradictory evidence. The totals report the number of evidence-contributing studies providing verified support to each theme. The matrix therefore functions as an audit trail between thematic interpretation and the underlying finding-level evidence rather than as a measure of methodological quality or effect size.

The most widely supported analytical theme was "Institutional capacity and the use of disaggregated evidence", with verified support from 5 of 10 studies. The least widely distributed theme was "Informality, record-keeping and the conditional visibility of MSMEs", with verified support from 3 of 10 studies. Differences in the number of supporting studies indicate the distribution of traceable thematic evidence across the included literature, not the relative importance or quality of a theme. Themes supported by fewer studies may still be analytically important when the underlying findings are conceptually rich, contextually distinctive or directly relevant to the review question. Conversely, wider study support indicates cross-study recurrence but does not by itself establish stronger methodological quality. The thematic patterns in Table 1 should therefore be interpreted alongside critical appraisal, contextual variation, verified contradictory findings, and the detailed theme-led discussion that follows.

4.5. RO1: Informality, Record-Keeping and the Conditional Visibility of MSMEs

The synthesis indicates that informality and record-keeping shape what becomes statistically visible. In Diepsloot, informal enterprises were commonly owner-managed, frequently established because of limited employment alternatives, and heavily reliant on personal savings or family and friends for start-up capital. Their operating environment included limited government funding, inadequate electricity and roads, weak management skills and restricted formal support (Ledingoane & Viljoen, 2020). These conditions provide a plausible mechanism through which enterprise activity may remain incompletely represented in formal economic statistics.

Evidence from Tanzania strengthens this interpretation by showing that full-time operation, written ledger accounts, business knowledge, infrastructure, technology and financial access were associated with enterprise productivity and classification into an intermediate sector (Diao et al., 2016). Nigerian evidence further reports that employment in telecommunications, film and retail was not captured or was underreported in the national statistics used in the study (Ndubuaku et al., 2021). Together, these findings support the proposition that the visibility of MSMEs depends partly on enterprise characteristics and statistical infrastructures, but they do not directly demonstrate that South African GDP rebasing improved MSME measurement.

4.6. RO2: Rebasing as an Opportunity for a More Accurate and Policy-Relevant Baseline

Comparative evidence supports a conditional opportunity associated with revised national accounts. The Nigerian study reports that GDP rebasing changed the measured economic baseline and links the GDP increase to sectors whose employment activity had previously been underreported (Ndubuaku et al., 2021). The Vietnam study similarly states that post-rebasing figures produced a more accurate macroeconomic baseline for estimating credit-growth relationships (Nguyen, 2025). Evidence concerning adjustments to multinational-enterprise accounting in the United States shows that alternative treatment of intangible-asset transactions can generate notable differences in real GDP levels and growth rates (Rassier, 2023).

South African policy can use a revised baseline to identify activity that older measures may have missed, especially when data are disaggregated by sector, firm size, and formality. Evidence on sector-specific forecasting also supports the policy value of disaggregated rather than aggregate information (Abdullahi et al., 2016). Nevertheless, the available studies do not demonstrate that such an opportunity was realised for South African MSMEs. Rebasing is therefore an enabling condition or measurement opportunity, not an observed policy benefit in this evidence base.

4.7. RO3: Data, Institutional and Implementation Barriers

The evidence identifies barriers that could limit rebasing's developmental value. South African informal enterprises face restricted access to funding, land, electricity, roads, skills and formal markets (Ledingoane & Viljoen, 2020). Comparative MSME evidence similarly associates statistical classification and productivity with written accounts, formal status, infrastructure and finance (Diao et al., 2016). These constraints create risks of selective visibility: enterprises with stronger records and institutional connections may be more readily incorporated into revised statistical systems than highly informal or marginal enterprises.

The synthesis also preserves divergent evidence about the economic consequences attributed to MSMEs. One study reports positive relationships between MSME development, competitive advantage and creative-economy improvement, whereas another finds insignificant relationships between MSME size categories and GDP growth (Aditi & Pentana, 2018; Abuhatab, 2023). This divergence cautions against assuming that more visible MSME activity will automatically translate into measurable growth or effective policy. The evidence provided does not directly document privacy concerns, reporting burdens, ethical risks, or MSME perceptions of rebasing.

4.8. RO4: Institutional Capacity and the Use of Disaggregated Evidence

The synthesis indicates that effective use of MSME evidence depends on institutional and infrastructural conditions. South African evidence links enterprise growth to electricity, roads, skills, land and access to public support, while Tanzanian evidence demonstrates the usefulness of observable firm characteristics for classification and targeting (Ledingoane & Viljoen, 2020; Diao et al., 2016). Policy frameworks discussed in the wider African evidence base also emphasise reliable institutions, infrastructure, regulatory coordination and sector-specific indicators as conditions for development implementation (Thiele et al., 2018; Yongo-Bure, 2020).

Disaggregation is particularly important because aggregate indicators can conceal sectoral and firm-size differences. Evidence on modelling petroleum demand explicitly argues that sector-specific data provide better information for targeted taxes or subsidies than aggregate demand measures (Abdullahi et al., 2016). However, the reviewed evidence does not document the institutional procedures South African statistical authorities use to incorporate MSMEs into benchmark revisions, supply-and-use tables, or post-rebasing policy monitoring. The institutional conclusion is therefore inferential and conditional.

4.9. RO5: Evidence Gaps and Implications for Future Inquiry

The principal evidence gap is direct and substantial: no supplied finding examines GDP rebasing or national-accounts re-benchmarking for MSMEs in South Africa. The evidence base does not document South African benchmark revisions, MSME treatment in supply-and-use tables, administrative-data integration or post-rebasing policy outcomes. Comparative studies demonstrate that measurement revisions can alter macroeconomic interpretation, but their transferability to South African MSMEs is limited (Nguyen, 2025; Rassier, 2023; Ndubuaku et al., 2021).

The synthesis also lacks direct MSME perspectives on data collection, privacy, reporting burdens, perceived benefits or risks. Some extracted material was methodological, incomplete or non-substantive, and the final included records were heterogeneous in publication type and design. These limitations mean that the review can identify a conditional line of argument and a research agenda, but cannot estimate the magnitude of any visibility change or establish a causal relationship between rebasing and development-policy outcomes.

5. Discussion

The review directly answers RO1 by showing that the supplied evidence does not establish a demonstrated relationship between South African GDP rebasing and improved MSME visibility. It does, however, identify plausible mechanisms that shape visibility. Informality, incomplete records, limited formal finance and weak infrastructure affect whether enterprises are observable within systems that generate economic statistics (Ledingoane & Viljoen, 2020; Diao et al., 2016). The distinction between a plausible mechanism and a tested relationship is central: the evidence supports the former but not the latter.

For RO2, the evidence suggests that rebasing can create an opportunity to improve the macroeconomic baseline. Nigeria, Vietnam and the United States provide examples in which revised or adjusted national-account measures changed the interpretation of economic size, growth or sectoral activity (Ndubuaku et al., 2021; Nguyen, 2025; Rassier, 2023). Yet these examples differ in national setting, institutional arrangements and substantive focus. Their relevance is therefore conceptual rather than demonstrative of a South African MSME effect. The review contributes by specifying the conditions under which the opportunity could become policy-relevant: MSME-sensitive classifications, disaggregated data, and institutional capacity to use revised estimates.

RO3 is addressed by identifying barriers and divergence. Informal enterprises face material constraints that may also limit their statistical inclusion, while the evidence on MSME contributions to broader economic outcomes is inconsistent (Ledingoane & Viljoen, 2020; Aditi & Pentana, 2018; Abuhatab, 2023). This divergence may reflect differences in indicators, countries, sectors, time periods and methods rather than a simple contradiction. Nevertheless, it means greater visibility should not be equated with greater productivity, GDP growth, or policy success. Ethical issues such as privacy and reporting burdens remain insufficiently understood because the supplied evidence contains no direct MSME perspectives on rebasing.

For RO4, the synthesis indicates that institutional capacity mediates the usefulness of revised economic information. Statistical agencies require reliable data sources and classification procedures, while policy institutions require the capacity to interpret sectoral and firm-size variation. Evidence on sector-specific forecasting and African development policy supports the value of disaggregation and coordinated infrastructure, but does not document how these processes operate within South African national accounting (Abdullahi et al., 2016; Thiele et al., 2018; Yongo-Bure, 2020). The institutional argument is therefore plausible but not directly observed.

RO5 is answered by the evidence gap itself. The review found no direct study of South African MSMEs in GDP rebasing or national-accounts re-benchmarking, no documented analysis of MSME treatment in South African supply-and-use tables and no post-rebasing evaluation of development-policy outcomes. The inclusion of comparative and heterogeneous evidence enabled conceptual synthesis but weakened directness and transferability. CASP appraisal identified methodological concerns and incomplete reporting across the evidence base, while no formal finding-level confidence assessment was recorded. The conclusions should therefore define an empirical agenda rather than claim that rebasing has already improved MSME visibility.

6. Conclusion

The review concludes that GDP rebasing and national-accounts re-benchmarking may provide an opportunity to improve the macroeconomic baseline, but the supplied evidence does not demonstrate that they have improved the statistical visibility of MSMEs in South Africa. MSME visibility is shaped by informality, record-keeping, enterprise characteristics, infrastructure and institutional access. Effective policy use requires disaggregated, reliable and institutionally usable information. The review therefore answers the five objectives conditionally: opportunities exist, but risks and barriers are substantial; institutional conditions are decisive; and the direct evidence needed to evaluate South African post-rebasing outcomes remains absent.

7. Recommendations

Practice recommendations should focus on linking MSME data collection to observable enterprise characteristics, including formality, record-keeping, sector, firm size and operating conditions. Statistical and policy practitioners should treat revised GDP estimates as requiring validation against disaggregated MSME evidence rather than assuming that aggregate revisions capture informal activity.

Policy recommendations should support coordinated administrative, survey and national-account processes that can identify informal and under-recorded enterprises while limiting unnecessary reporting burdens. Development-policy monitoring should distinguish firm size, sector and location, because aggregate GDP measures may conceal heterogeneous MSME conditions (Abdullahi et al., 2016; Ledingoane & Viljoen, 2020).

Future research should directly examine South African benchmark revisions, MSME treatment in supply-and-use tables, administrative-data integration and post-rebasing changes in measured MSME activity. Studies should include MSME perspectives on privacy, reporting burdens and perceived benefits; compare formal and informal enterprises; document statistical procedures transparently; and evaluate whether revised information changes policy targeting or outcomes.