OIT - When the Border Closes

X When the Border Closes A Demand-Driven Spatial Model of Mass Return Migration in Cambodia Authors / Xiao Jiang, Chan Mono Oum, Lehua Jin, Xi Kang

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Authorization for publication: Sangheon, Lee, Chief Economist ILO Working Papers can be found at: www.ilo.org/research-and-publications/working-papers Suggested citation: Jiang, X., Mono Oum, C., Jin, L., Kang, X. 2026. When the Border Closes: A Demand-Driven Spatial Model of Mass Return Migration in Cambodia, ILO Working Paper 179 (Geneva, ILO). https://

doi.org/10.54394/0003528201 ILO Working Paper 179 Abstract The abrupt closure of the Cambodia-Thailand border in 2025 triggered the return of an estimated 820,000 to 950,000 Cambodian migrant workers, a major sudden labour supply shock. This paper develops a new quantitative framework for migration-shock policy analysis, combining Harris-Todaro migration dynamics, a Lewis dual-economy structure, a demand-driven macroeconomic closure, and an empirical returnee identity wedge capturing access frictions relative to domestic workers. The model is calibrated to Cambodia’s 2025 Labour Force Survey, 2022 Economic Census, 2022 Input-Output Table, and 2023 Socio-Economic Survey. Two findings emerge: over

nomic closure, and an empirical returnee identity wedge capturing access frictions relative to domestic workers. The model is calibrated to Cambodia’s 2025 Labour Force Survey, 2022 Economic Census, 2022 Input-Output Table, and 2023 Socio-Economic Survey. Two findings emerge: over 90 per cent of the shock is absorbed into informal employment and non-employment, so the formal share falls even as formal employment rises in absolute terms; and identity-specific frictions shift returnees toward informality relative to domestic workers, with no detectable aggregate employment effect. Each policy lever, from credential recognition to demand-side measures, maps to an explicit model parameter, allowing policymakers to simulate mitigation strategies ex ante or evaluate them ex post.

Keywords: return migration, spatial labour market model, informality, demand-driven framework, Cambodia, reintegration policy, dual economy, and recognition of prior learning

JEL codes: J61, J46, O15, O18, R13, F22.

About the authors Xiao Jiang is a Finance and Economic Development Specialist in the Office of the Chief Economist at the International Labour Organization (ILO). He applies quantitative methods to assess the social and economic impacts of policies and to support country-level policy analysis. He also leads the ILO’s engagement with international financial institutions. His research has been published on a wide range of topics, including trade and employment, macroeconomics and development, economic modeling, demographics, and applied political economy. Before joining the ILO, he was an Associate Professor of Economics at Denison University in the United States. Chan Mono Oum is a Cambodian economist, policy advisor, and researcher specializing in labour economics, labour market analysis, skills development, migration, economic modelling, and impact evaluation. He serves as an Advisor to the Ministry of Labour and Vocational Training, CoFounder and Research Director of Analytics and Insights Asia, and university lecturer. Holding a PhD in Economics from the University of Waikato, he has led research for government agencies and international development partners, translating rigorous evidence into policy development.

pact evaluation. He serves as an Advisor to the Ministry of Labour and Vocational Training, CoFounder and Research Director of Analytics and Insights Asia, and university lecturer. Holding a PhD in Economics from the University of Waikato, he has led research for government agencies and international development partners, translating rigorous evidence into policy development. Lehua Jin is a PhD candidate in Economics at the Geneva Graduate Institute (IHEID) and works as an External Collaborator with the International Labour Organization (ILO). Her research examines labour allocation, migration, structural transformation, and inequality in developing economies. Combining microdata with quantitative structural models, she investigates how mobility barriers, labour-market institutions, and sectoral risks affect employment decisions, household welfare, and the distributional consequences of economic change.02 ILO Working Paper 179 Xi Kang is a PhD candidate in Economics at the Geneva Graduate Institute (IHEID) and an External Collaborator with the International Labour Organization (ILO). His research interests include development economics, climate and environmental economics, social protection, and applied microeconomics. His research combines large-scale microdata and geospatial data with causal inference, microsimulation, and computational modelling to study how public policies, infrastructure, and environmental risks shape economic behaviour and welfare.03 ILO Working Paper 179 Abstract 01 About the authors 01 Acronyms 07 Executive Summary 08 X Introduction 09 X 1 Context and Data 11 The 2025 Return Migration Shock 11 Data Sources 12 X 2 The Conceptual Framework 13 X 3 Model Description 15 Geography and Labour Market States 15

Frictions: Entry Costs and Mobility Costs 15

Earnings and Skill Premium 16 Worker Income and Sectoral Choice 17 Employment Aggregation and Consumption Feedback 19 Output and the Output-to-Labor Ratio 20 Equilibrium and Adjustment Mechanism 20 The Returnee Identity Wedge 21 X 4 Calibration 23 Baseline Calibration 23 Baseline Fit 25 Returnee Wedge Estimation 25

Employment Aggregation and Consumption Feedback 19 Output and the Output-to-Labor Ratio 20 Equilibrium and Adjustment Mechanism 20 The Returnee Identity Wedge 21 X 4 Calibration 23 Baseline Calibration 23 Baseline Fit 25 Returnee Wedge Estimation 25 X 5 Simulation Results 27 Absorption of the Returnee Shock 27 Returnee Integration and the Identity Wedge 28 Welfare Incidence 29 Table of contents04 ILO Working Paper 179 X 6 Policy Implications and Research Priorities 31 What the model implies for policy design 31

Research priorities: policy simulation 33

Research priorities: household microsimulation 34

Data priorities 34 X Conclusion 36 Annex 37 References 41 Acknowledgements 4305 ILO Working Paper 179 List of Figures Figure 1. Labour-supply effect: change in employment by region and broad margin (thousand workers). 28 Figure 2. Identity-wedge effect by worker identity and destination state (thousand workers). 29 Figure 3. Per-worker CEV effects by channel and identity (percentage points). 3006 ILO Working Paper 179 List of Tables Table 1. Baseline calibration objects and methods 23 Table 2. Aggregate employment share diagnostics: model vs. LFS 2025 25 Table 3. LFS-calibrated returnee identity wedges ΔRj 26 Table 4. Key notation 37 Table 5. Entry costs Kaj,r by skill, sector, and region (M KHR/year, σ=1.0) 37 Table 6. Formal wage shifter μj,r, output-to-labour elasticity αj, and log skill premium ηS,j 38 Table 7. Outside-option income bar and mobility cost τBC 38 Table 8. Targeted wage fit: model vs. LFS 2025 38 Table 9. Solved baseline employment by region and state 39

Table 7. Outside-option income bar and mobility cost τBC 38 Table 8. Targeted wage fit: model vs. LFS 2025 38 Table 9. Solved baseline employment by region and state 39 Table 10. Skill-disaggregated absorption of returnee shock (thousand workers, labour-supply effect) 39 Table 11. Incumbent-returnee decomposition of the identity-wedge effect (thousand workers) 4007 ILO Working Paper 179 Acronyms ADB Asian Development Bank CDRI Cambodia Development Resource Institute CEV Consumption-Equivalent Variation CI Confidence Interval CSES Cambodia Socio-Economic Survey EC Economic Census ICLS International Conference of Labour Statisticians IHEID Geneva Graduate Institute (Institut de hautes études internationals et du développement) ILO International Labour Organization JEL Journal of Economic Literature KHR Cambodian Riel LFS Labour Force Survey MLVT Ministry of Labour and Vocational Training MSM Household Microsimulation NIS National Institute of Statistics RPL Recognition of Prior Learning SEIA Socio-Economic Impact Assessment TVET Technical and Vocational Education and Training UNDP United Nations Development Programme08 ILO Working Paper 179 Executive Summary In 2025, the abrupt closure of the Cambodia–Thailand border triggered the return of an estimated 820,000 to 950,000 Cambodian migrant workers within a few months, close to ten per cent of the national labour force, arriving almost at once and concentrated in provinces where formal employment capacity is limited. This working paper develops a new quantitative framework for analysing this kind of shock and the policy options available to respond to it. The framework combines Harris-Todaro migration dynamics, in which workers weigh net returns across sectors, locations, and non-employment; a Lewis dual-economy structure, in which the informal sector absorbs surplus labour with no fixed ceiling; and a demand-driven macroeconomic closure, in which formal-sector output and wages respond to demand rather than being constrained by installed capacity. A novel returnee identity wedge captures the additional access

informal sector absorbs surplus labour with no fixed ceiling; and a demand-driven macroeconomic closure, in which formal-sector output and wages respond to demand rather than being constrained by installed capacity. A novel returnee identity wedge captures the additional access frictions, such as credential non-recognition and lost domestic networks, that returnees face relative to comparable domestic workers. The model is calibrated to Cambodia’s 2025 Labour Force Survey, the 2022 Economic Census, the 2022 Input-Output Table, and the 2023 Cambodia Socio-Economic Survey. Two findings stand out. First, over 90 per cent of the shock is absorbed into informal employment and non-employment rather than formal jobs: the formal employment share falls even as formal employment rises in absolute terms. Second, identity-specific access barriers push returnees disproportionately into informality relative to domestic workers with similar skills and location, generating consumption-equivalent welfare losses of four to five per cent, with no noticeable effect on aggregate employment. Aggregate statistics can therefore look largely unchanged while returnees bear a substantial, hidden welfare cost. Because each channel in the model maps to an explicit policy lever, including credential recognition, skills-bridging training, mobility support, social transfers, demand-side measures such as public investment, employment policy and social protection, policymakers can use the framework to simulate alternative interventions before committing resources, or to evaluate programmes already under way. The paper also sets out a concrete agenda for sharpening these estimates, including an expanded returnee sample and a planned household microsimulation module.09 ILO Working Paper 179 X Introduction In 2025, the abrupt closure of the Cambodia–Thailand border triggered the return of between 820,000 and 950,000 migrant workers, according to the Ministry of Labour and Vocational Training (MLVT) and the Cambodia Development Resource Institute (CDRI) (MLVT, 2025; CDRI, 2025). The scale of this inflow, equivalent to roughly ten per cent of the country’s labour force, represents one of the largest sudden labour supply shocks in Cambodia’s recent economic history. The central

(MLVT) and the Cambodia Development Resource Institute (CDRI) (MLVT, 2025; CDRI, 2025). The scale of this inflow, equivalent to roughly ten per cent of the country’s labour force, represents one of the largest sudden labour supply shocks in Cambodia’s recent economic history. The central challenge is not simply its size, but its structure: most returnees are young, low-educated workers with informal sector experience1, and more than seventy per cent arrived in border provinces where formal employment capacity is severely limited (MLVT, 2025; CDRI, 2025).2 Analysing this shock and the demanded policy response requires tools that existing frameworks do not readily provide. While general equilibrium approaches to return migration exist, none combines the three elements essential for the Cambodian case: an informality margin (since most of the shock’s absorption occurs outside formal employment); spatial mismatch between arrival regions and formal employment centres (since returnees are concentrated far from where formal jobs exist); and a demand-driven closure (since many consequential policy levers operate on the demand side). The latter is especially important given the structural features of the Cambodian economy, and the case for which is developed in Section 3. This paper presents a spatial labour market model designed to fill this gap. Drawing on the intellectual traditions of Lewis’s dual economy and Harris and Todaro’s spatial migration dynamics, and embedding these within a demand-driven macroeconomic closure (in plain terms, one in which output responds to spending and demand conditions, rather than being constrained by technology and cleared only through price adjustment) the framework is intended as a practical policy-simulation tool to assess impacts in the labour market: one that allows policymakers to diagnose labour market bottlenecks and simulate ex-ante the employment and welfare impacts of alternative interventions, both for the current shock and for comparable shocks in the future. A novel returnee identity wedge captures the additional barriers returnees face relative to comparable domestic workers, including credential non-recognition and the loss of Thai labour market networks. The model is calibrated using Cambodia’s 2025 Labour Force Survey, the

future. A novel returnee identity wedge captures the additional barriers returnees face relative to comparable domestic workers, including credential non-recognition and the loss of Thai labour market networks. The model is calibrated using Cambodia’s 2025 Labour Force Survey, the 2022 Economic Census, the 2022 Input-Output Table, and the 2023 Cambodia Socio-Economic Survey. The incumbent baseline is calibrated to a pre-shock sample from which recent Thailand returnees have been excluded; the identity wedge estimation remains preliminary because the recent-returnee subsample is thin. Accordingly, this paper is positioned as an operational framework and an initial calibration rather than a definitive quantitative assessment. Section 6 sets out the concrete policy-simulation and data agenda through which the framework will be sharpened in subsequent work. The remainder of the paper is organised as follows. Section 1 describes the context and data. Section 2 presents the conceptual framework. Section 3 develops the model. Section 4 covers 1 Throughout this paper, informal sector follows the 15th ICLS definition: “a group of production units comprised of unincorporated enterprises owned by households, including informal own account enterprises and enterprises of informal employers (typically small and non-registered enterprises)” (International Labour Organization, 1993). This is a sectoral concept, distinct from the broader 17th ICLS notion of informal employment, which also includes informal employment relationships within formally registered enterprises. Because the model allocates workers across sectors, its informality margin corresponds to the 15th ICLS informal sector, and the text refers throughout to informal sector employment rather than informal employment accordingly. 2 We use “capacity” descriptively, following the cited sources, rather than as an independently measured construct: the underlying constraint could reflect demand conditions, supply-side factors (capital, technology), or both, and disentangling them is beyond this paper’s scope.10 ILO Working Paper 179 calibration. Section 5 presents simulation results. Section 6 concludes with policy implications and research priorities.11 ILO Working Paper 179 X 1 Context and Data

The 2025 Return Migration Shock

paper’s scope.10 ILO Working Paper 179 calibration. Section 5 presents simulation results. Section 6 concludes with policy implications and research priorities.11 ILO Working Paper 179 X 1 Context and Data

The 2025 Return Migration Shock Thailand has historically been the dominant destination for Cambodian labour migrants, with an estimated 724,000 Cambodian migrant workers holding legal working status, employed predominantly in construction, agriculture, and manufacturing, according to the International Organization for Migration (IOM) (IOM, 2020). The migration flow has historically been informal: less than a third used regular migration channels, and the majority circulated without formal contracts or recognised credentials, a feature that proves consequential on return. The profile of the 2025 returnee population reflects this pattern. Survey evidence indicates that 42.5 per cent completed only primary school, 33.3 per cent never attended formal schooling, and 89 per cent reported not having acquired any formally recognised skills while in Thailand (MLVT, 2025). Prior to the conflict and border closure, occupations were concentrated in construction (35%), manufacturing (29%), services (19%), and agriculture (16%), sectors where experience accumulates informally in Thailand but without credentials recognised by Cambodian employers

(MLVT, 2025; CDRI, 2025).

The shock arrived in a structurally constrained labour market. MLVT (2026) reports that, in the context of emergency reintegration measures, around 350,000 returnees were linked to formal-sector jobs, approximately 310,000 entered informal sector employment, and nearly 120,000 remained at risk of unemployment.3 The rapid assessment by MLVT (2025) identifies three overlapping barriers4 that constrain returnee absorption: a skills gap between returnee experience and domestic employer requirements; a geographic mismatch, as formal employment is concentrated in Phnom Penh and Kandal while most returnees arrive in border provinces; and limited enterprise capacity, with the majority of SMEs, which account for over 70 per cent of national employment, operating informally and reluctant to expand hiring (MLVT, 2026). Against this backdrop, this paper develops a spatial labour market model to quantify how the unexpected large inflow of migrant workers reshapes labor market and household living standards, with the ultimate goal of simulating targeted policy responses. To place the size of the shock in context, Cambodia’s labour force numbers approximately ten million (MLVT, 2025; CDRI, 2025), so the return of 820,000 to 950,000 workers within a few months represents close to an additional ten per cent of the labour force arriving almost at once, a shock with few parallels in Cambodia’s recent economic history, and one that implies most returnees must, at least temporarily, be absorbed outside formal employment. The shock also carries household-level dimensions the model does not capture directly. Many returnees financed migration through loans, often from microfinance institutions, and returned still owing this debt: Human Rights Watch interviews describe households choosing between 3 This 780,000 total is based on an initial assessment, smaller than the 820,000–950,000 range estimated in later reports (MLVT, 2025; CDRI, 2025). The formal-job figure is treated here as a policy-influenced administrative benchmark, not as a target for the no-policy simulations in Section 5. 4 The model represents these barriers at different levels of detail. Geographic mismatch and demand-side capacity enter explicitly, while skill mismatch is captured only indirectly through education-based skill groups and returnee access wedges, not through occupation-specific humancapital or productivity. The occupational dimension is left to the subsequent MSM stage.12 ILO Working Paper 179 food, loan repayments, and school fees, with some at risk of losing pledged land (Human Rights Watch, 2025). Return also cuts off remittances that had financed household investment and Cambodia’s foreign exchange earnings. Both channels strengthen the case for the demand-side

food, loan repayments, and school fees, with some at risk of losing pledged land (Human Rights Watch, 2025). Return also cuts off remittances that had financed household investment and Cambodia’s foreign exchange earnings. Both channels strengthen the case for the demand-side and social-protection measures discussed in Section 6, which complement the model's core focus on how the labour-supply shock itself is absorbed. Data Sources The model draws on five calibration data sources. The Cambodia Labour Force Survey 2025 (LFS 2025), conducted by the National Institute of Statistics (NIS) and made available through the ILO Microdata Repository, provides the microdata foundation: person-level employment status, sector, wages, education, province of residence, and international migration histories for a weighted sample representing approximately 13.1 million working-age individuals. It is the primary source for employment shares, wage moments, worker type classification, and the returnee migration module used to estimate returnee access wedges. The Economic Census 2022 (EC 2022), also produced by NIS, supplies establishment-level formal employment by sector and province; it is used to allocate formal demand regionally and to estimate wage-productivity elasticities where cell sizes are adequate. The Input-Output Table 2022 produced by the Asian Development Bank (ADB) provides national final-demand components by sector, including external demand, government expenditure, and investment. The Cambodia Socio-Economic Survey 2023 (CSES 2023) provides household consumption shares and outside-option consumption by skill and region. NIS poverty-line inputs are used where relevant for informal earnings floors and lower-bound consumption inputs. The LFS-derived baseline moments are constructed from an incumbent sample: individuals in the LFS 2025 international migration module are excluded from baseline moments if their most recent foreign destination was Thailand and their return date was May 2025 or later. This avoids double counting the returnee cohort both in the pre-shock baseline and in the simulated shock. The returnee wedge sample is drawn from the same international migration module and includes individuals who previously lived abroad, had Thailand as the most recent destination,

double counting the returnee cohort both in the pre-shock baseline and in the simulated shock. The returnee wedge sample is drawn from the same international migration module and includes individuals who previously lived abroad, had Thailand as the most recent destination, and returned in or after May 2025. Because this recent-returnee subsample is thin, the returnee wedge is preliminary and is estimated as a sectoral, skill-blind, and region-blind wedge. The IOM (2020) and MLVT (2025) surveys offer valuable evidence on returnee characteristics, but as they are not yet weighted to the population they inform qualitative dimensions of the returnee profile rather than the structural calibration.13 ILO Working Paper 179 X 2 The Conceptual Framework

Modelling how workers sort across sectors and locations requires some account of individual decision-making under uncertainty. The framework therefore combines three complementary mechanisms. The Harris-Todaro component captures workers’ spatial and sectoral choices under uncertainty, as returnees compare expected net returns across formal employment, informal sector employment, and non-employment in different locations. The Lewis dual-economy component captures the role of the informal sector as a residual absorber of labour when formal employment opportunities are limited. The demand-driven structuralist component captures the fact that formal labour absorption depends not only on the number of workers available, but also on sectoral demand, enterprise capacity, and the level of economic activity. This is developed formally through the Harris-Todaro framework (Harris and Todaro, 1970), in which workers compare expected returns across options, accounting for wages, employment probabilities, and the costs of moving, and allocate accordingly. This expected-utility migration mechanism remains the workhorse for spatial labour market models in developing countries, and it is the micro-level behavioural foundation of the present framework. Specifically, workers compare net returns across formal sectors, informal sector employment, and non-employment in two regions, subject to entry costs and mobility costs. The structure of the Cambodian economy, however, demands additional structure that HarrisTodaro alone does not provide. Cambodia’s labour market is characterised by a large pool of

compare net returns across formal sectors, informal sector employment, and non-employment in two