Research

A forthcoming chapter in the EUROMOD 30th-anniversary volume describing the development and use of tax-benefit microsimulation models in the Global South, drawing on the experience of SAMOD, the SOUTHMOD model family, and EUROMOD-based models for Latin America.

A forthcoming WIDER working paper examining how to account for informal consumption when modelling value-added tax (VAT) in SOUTHMOD tax-benefit microsimulation models, with applications to Rwanda, Peru, Mozambique, and Uganda.

This report documents RWAMOD, the SOUTHMOD model developed for Rwanda. This work was carried out by UNU-WIDER, SASPRI, and the Rwanda Revenue Authority (RRA). The results presented in this report are derived using RWAMOD version 2.0, which is part of the SOUTHMOD bundle (SOUTHMOD_A4.0) and runs on EUROMOD software. The report describes the different tax-benefit policies in place, how the microsimulation model picks up these different provisions, and the database on which the model runs. It concludes with a validation of results against external data sources for Rwanda.

This report documents UGAMOD, the SOUTHMOD model developed for Uganda. This work was carried out by Uganda Revenue Authority (URA) in collaboration with the project partners. The results presented in this report are derived using UGAMOD version 3.0, which is part of the SOUTHMOD bundle (SOUTHMOD_A4.0) and runs on EUROMOD software. The report describes the different tax-benefit policies in place, how the microsimulation model picks up these different provisions, and the database on which the model runs. It concludes with a validation of results against external data sources for Uganda.

Ethiopia initiated a major electricity sector reform in 2024, significantly increasing tariffs and introducing a value-added tax on electricity consumption to improve the financial sustainability of its state-owned utility. This study assesses the short-term distributional, sectoral, and cost-of-living impacts of this reform. The analysis links a tax-benefit microsimulation model (ETMOD) with a price-based social accounting matrix (SAM) multiplier framework to capture both direct, household-level welfare changes and indirect, economy-wide price transmission effects. The results show the reform is regressive, increasing the national poverty rate by 3.5 percentage points in a static, short-run setting. The tariff increase is the primary driver of this effect, while the VAT has a smaller impact. Indirect effects, transmitted through higher prices for essential goods such as food and water, account for two-thirds of the total poverty impact and are larger than the direct effect of higher electricity bills. Rural and informal households are disproportionately affected. These findings demonstrate that without compensatory measures, electricity pricing reforms necessary for fiscal stability can impose substantial social costs. We conclude that pairing such reforms with targeted social protection is essential to shield vulnerable households from adverse outcomes.

This study investigates the feasibility of generating synthetic input data for the Ghanaian tax-benefit microsimulation model (GHAMOD) to address limitations posed by infrequent survey data. Current GHAMOD input datasets are derived from the 2013 and 2017 Ghana Living Standards Surveys. Reliance on such dated household data reduces the accuracy of policy analysis, particularly when failing to account for broader demographic shifts and structural changes that occur between survey rounds. This research explores methodologies ranging from linear interpolation to advanced machine learning techniques, including imputation and predictive modelling, to create synthetic data for intervening years (2014–16) and future years (2018 onwards). By combining existing survey data with complementary external data sources, this study demonstrates that synthetic data generation is a feasible, transformative approach for enhancing the timeliness of fiscal policy analysis. The research establishes a framework for effectively leveraging high-frequency complementary data to bridge temporal gaps, thereby improving the model's predictive capabilities and relevance for analysing the budgetary and distributional impacts of fiscal policies. This report details findings on suitable data and methods, discusses challenges, offers selected case studies, and provides a roadmap for integrating these techniques into national data ecosystems, with potential applications for other tax-benefit microsimulation models in Africa, Asia, and Latin America.

This paper examines the experience of building and using tax-benefit microsimulation models for countries in the Global South within the EUROMOD framework, drawing on SAMOD, the SOUTHMOD model family, and EUROMOD-based models for Latin America. It reviews the research contributions these tools have enabled — spanning distributional analysis, work incentives, informal employment, and automatic stabilization — and discusses the challenges of maintaining and updating them, as well as the opportunities they open for new avenues of research to strengthen social protection and fiscal capacity in developing economies.

We develop a new methodology to nowcast the effects of the COVID-19 crisis on GDP and forecast its evolution in small, export-oriented countries. To this aim, we exploit variation in financial indexes at the industry level in the early stages of the crisis and relate them to the expected duration of the crisis for each industry, under the assumption that the main shocks to financial prices in 2020 came from COVID-19. Starting from the latest official information available at different stages of the crisis on industry-level trend deviations of GDP, often a few months old, we predict the ensuing recovery trajectories using the most recent financial data available at the time of the prediction. The financial data reflect, among other things, how subsequent waves of infections and information about new vaccines have impacted expectations about the future. We apply our method to Vietnam, one of the most open economies in the world, and obtain predictions that are more optimistic than projections by the International Monetary Fund and other international forecasters, and closer to the realised figures. Our claim is that this better-than-expected performance was visible in stock market data early on but was largely missed by conventional forecasting methods.

The RAND Corporation was asked to assess the state and future of education and training in advanced manufacturing (AM) using robotics, with a special focus on the U.S. Midwest region and the state of Pennsylvania — areas that currently are and historically have been hubs of manufacturing and provide important test cases for answering questions about the availability and content of AM training programs. The research team examines the economic context in which education, training, and workforce development programs currently operate and potentially will operate in the near future; reviews available programs and evaluates their curricular content and instructional practices and technologies; and reviews promising educational practices in these areas. The team also offers recommendations for stakeholders to consider as they work to meet the needs of the future AM workforce.

The National Institute for Occupational Safety and Health (NIOSH) helps ensure U.S. workers operate in safe and healthful working conditions by funding related efforts by external researchers; developing and testing engineering controls, personal protective equipment, and other technologies; and providing educational information, guidance, and training, as well as other services. NIOSH must prioritize its investments in workplace safety and health to make the best use of available funding and must also demonstrate the value of that funding. However, there are a number of challenges in understanding the benefits associated with this or any agency's research activities. In an earlier study, RAND researchers developed an approach for estimating these benefits and demonstrated the approach using three case studies. NIOSH then asked RAND to further build upon that work by developing a process for selecting case studies for evaluation, applying that selection process to a list of ten potential case studies, and selecting three case studies from this list for detailed analysis. In this report, the authors define and document a process for selecting case studies of the economic benefits of research and services at NIOSH and evaluate benefits associated with three selected cases. Together, this body of research helps build a foundation for evaluating the broader societal benefits provided by NIOSH, both by providing quantitative estimates of the benefits associated with specific NIOSH activities and by providing NIOSH with methods and examples for consistently evaluating the societal impact of its own work.

Wireless communications — particularly those enabled by WiFi — play an indispensable role in generating economic prosperity and opportunity, yet there are few empirically driven estimates on how WiFi contributes to the economy. This report helps fill this gap by estimating the potential economic value of the 5.9 GHz frequency band — this portion of spectrum was allocated by the Federal Communications Commission for short-range vehicle-to-vehicle communications in 1999, but, as of 2018, reconsidering this band for WiFi use has become a subject of discussion. The authors detail two approaches for estimating the 5.9 GHz band's potential contribution to U.S. gross domestic product. They also estimate the band's contribution to consumer surplus and producer surplus, provide a sensitivity analysis for the estimates, and consider how current trends and potential future policies, such as privacy regulation, trade policy, and fifth-generation (5G) network deployment, could affect the estimates. The goal of these estimates is to help inform the ongoing debate regarding the 5.9 GHz band. This debate is particularly important because decisions made regarding this the allocation of this frequency band could set a precedent for future unlicensed spectrum policymaking.

The National Institute for Occupational Safety and Health (NIOSH) asked the RAND Corporation to develop an approach, reported here, for estimating the economic benefit of NIOSH research, using three case studies. The cases provide concrete illustrations of the ways in which NIOSH research could affect worker health and safety practices and outcomes, as well as some initial estimates of the economic benefit associated with those impacts. The authors selected the case studies to illustrate variation in types of NIOSH research and in intended users. The first case study examines research to develop, test, and support implementation of engineering control measures to limit exposure to silica among road construction workers. This case study offers an example of NIOSH's intervention and surveillance research and provision of technical assistance. The second case study involves two NIOSH studies that strengthened the evidence base about the linkage between firefighting activities and increased risk of certain cancers among firefighters. This case study provides an example of etiological and exposure surveillance research, coupled with an intervention study. The third case study involves a NIOSH evaluation of the effectiveness of Ohio's Safety Intervention Grant Program in reducing the prevalence and costs of workplace injuries. This case study illustrates intervention research targeting government organizations. The first and second case studies led to the development of control technologies, and all three case studies involved dissemination and stakeholder engagement efforts that promoted the adoption of risk-reducing technologies and practices.

The early days of President Donald Trump's administration were characterized by a burst of activity meant to roll back regulation, including Executive orders (EOs) to regulate the U.S. financial system, enforce a regulatory reform agenda, and reduce regulation while controlling regulatory costs. These reforms, particularly EO 13771, can potentially affect every part of the economy touched by federal regulation through the Office of Management and Budget's (OMB's) annual review of regulation. This Perspective considers how well EO 13771 addresses the concerns of those who have long supported regulatory reform and how agencies and OMB might best face the challenges and opportunities associated with implementing regulatory reform.

This report reviews the current and projected status of wearable technologies with potential for use by law enforcement and describes three conceptual integrated vest systems that incorporate these technologies. These three systems are meant to represent what could conceivably be implemented very quickly to enhance existing capabilities, what might be done in the near term to provide additional capabilities, and what might be considered to take advantage of technologies that are still in development and could provide even greater capabilities. Wearable technologies provide an opportunity to address several problems faced by law enforcement officers in an increasingly complex and technologically challenging environment — for example, the size and weight of equipment they must carry, the proliferation of batteries for electronic devices, the need for mounting and docking systems for body-worn cameras, and the need for comfort and flexibility while wearing body armor underneath uniforms. There is no reason for law enforcement to wait for wearable technologies that can provide improvements in the bulk, weight, and flexibility of carried equipment — major incremental improvements are available today using currently available commercial technology. However, law enforcement agencies need to think about how to engage with manufacturers now to specify their needs and provide input on the directions that research, development, and design should take in the near future to best accommodate their unique challenges and opportunities. By the same token, manufacturers should reach out to law enforcement agencies and practitioners as the technologies described in this report continue to develop.

The Ministry of Education and Culture established a process to review the Finnish Higher Education System in order to analyse its strengths and weaknesses and identify proposals to improve the higher education system and strengthen Finland's innovation system.

A forthcoming chapter in the EUROMOD 30th-anniversary volume describing the development and use of tax-benefit microsimulation models in the Global South, drawing on the experience of SAMOD, the SOUTHMOD model family, and EUROMOD-based models for Latin America.

We examine the distributional effects of the COVID-19 pandemic and associated tax-benefit measures in seven Sub-Saharan African countries, focusing on the onset of the crisis. We evaluate impacts on disposable incomes, considering variations across income groups; assess the effectiveness of tax-benefit policies in mitigating income losses; and analyse the influence of these measures on income-based poverty and inequality. We find notable reductions in disposable incomes, concentrated among higher-income households, and moderate increases in headcount poverty rates and poverty gaps. The study highlights the low effectiveness of pre-existing tax-benefit policies, with coverage gaps for the informal sector and a lack of income-dependent means-tested benefits. Discretionary tax-benefit policies in Mozambique and Zambia cushioned the shock for low-income households to a small extent. Conversely, school closures in Ethiopia and Ghana suppressed the provision of school meals, adding strain to households with school-age children.

This paper investigates the impact of the COVID-19 pandemic and related tax-benefit measures in Viet Nam, relying on tax-benefit microsimulation modelling. The focus is on the initial phase of the crisis in 2020. The study delves into how the pandemic affected disposable incomes, examining the differences across the income distribution and impacts on measures of poverty and inequality. The paper also evaluates the effectiveness of tax-benefit policies in alleviating income losses. The findings suggest that disposable incomes decreased by nearly 2.25 per cent on average, with the most pronounced effect experienced by higher-income households. The estimates point to moderate increases in both the headcount poverty rate and the extent of poverty, as measured by the poverty gap. Automatic stabilizers had a limited effect in cushioning the income shock. The discretionary social protection measures adopted in response to the crisis, however, halved the pandemic-induced rise in the national poverty rate.

In the wake of the COVID-19 pandemic, several countries enacted tax and social protection measures to help mitigate the economic hardship faced by individuals and households. This experience underscores the need to better understand the impact of such programmes on incomes and poverty during crises, especially in low- and middle-income countries where they are most needed. This paper reviews existing empirical literature on the subject, conducting a scoping review on quantitative studies published between 2000 and 2022.

This chapter provides the first Finnish-language overview of the types of economic and social policies that low- and middle-income countries implemented to mitigate the negative effects of economic shocks, how successful or effective these policies were, and how policy measures taken during crises affect post-crisis policies. The topic is assessed through both a social policy and an economic lens.

This study investigates the feasibility of generating synthetic input data for the Ghanaian tax-benefit microsimulation model (GHAMOD) to address limitations posed by infrequent survey data. Current GHAMOD input datasets are derived from the 2013 and 2017 Ghana Living Standards Surveys. Reliance on such dated household data reduces the accuracy of policy analysis, particularly when failing to account for broader demographic shifts and structural changes that occur between survey rounds. This research explores methodologies ranging from linear interpolation to advanced machine learning techniques, including imputation and predictive modelling, to create synthetic data for intervening years (2014–16) and future years (2018 onwards). By combining existing survey data with complementary external data sources, this study demonstrates that synthetic data generation is a feasible, transformative approach for enhancing the timeliness of fiscal policy analysis. The research establishes a framework for effectively leveraging high-frequency complementary data to bridge temporal gaps, thereby improving the model's predictive capabilities and relevance for analysing the budgetary and distributional impacts of fiscal policies. This report details findings on suitable data and methods, discusses challenges, offers selected case studies, and provides a roadmap for integrating these techniques into national data ecosystems, with potential applications for other tax-benefit microsimulation models in Africa, Asia, and Latin America.

This technical note documents UGAMOD-TAX, a microsimulation model for personal taxation in Uganda, built using administrative tax records from the Uganda Revenue Authority (URA). It complements the standard survey-based UGAMOD model, developed under UNU-WIDER's SOUTHMOD project, by leveraging detailed PAYE, presumptive tax, and register data. This administrative foundation enables more accurate simulation of specific taxes and their distributional impacts, particularly capturing high-income earners often underrepresented in survey data. This note focuses on the first version of the model, which uses data and tax policy rules from the 2021/2022 financial year. The model enables policymakers to quantitatively evaluate the fiscal and distributional effects of potential tax reforms.

SOUTHMOD tax-benefit microsimulation models may in some cases oversimulate taxes or benefits, generating greater expenditure, a greater number of beneficiaries, or greater amounts of taxes or taxpayers than reported in administrative data. Drawing on an example of a social benefit policy in Rwanda, implemented in the RWAMOD model, this technical note shows why such issues can be important in the analysis of tax-benefit policy reforms. The note also shows how oversimulation can be addressed in SOUTHMOD models by downward adjustment of relevant taxes and benefits.

This note describes methods to derive employment-to-unemployment transition shares across industries during the COVID-19 pandemic and to use these shares in SOUTHMOD tax-benefit microsimulation models to adjust relevant labour market variables. The first method entails the derivation of industry-specific output shocks from sectoral GDP data, which are used as a proxy for the sectoral shares of workers who transition to unemployment with zero earnings. The second method involves creating a new policy (lma_cc) in a given country model. In this policy, the transition shares are used to allocate randomly selected workers within industries into unemployment and to adjust their incomes to account for the crisis. The analysis follows another technical note on the derivation of sectoral GDP shocks and income adjustments. By presenting an approach to adjust labour market variables inside the EUROMOD software, this note offers an alternative to previous research relying on SOUTHMOD models where such adjustments are applied to model input data.

This note sets out two different methods on how to adjust incomes in the microdata underlying the standard SOUTHMOD models to reflect a sudden shock, in this case the COVID-19 shock, as done in the accompanying working paper by Lastunen et al. (2021). The note first describes how industry-specific GDP shocks are calculated. Next, it describes how these shocks are randomly allocated to individuals' incomes in the microdata. Using the World Bank Phone Survey for Uganda, an alternative, regression-based method is described that models labour market transitions in a more detailed manner as it takes into account individuals' characteristics. The method could easily be replicated for other countries provided such alternative microdata eventually become available. We further track and compare variables between the survey data underlying the UGAMOD input data, the 2016/17 Uganda National Household Survey, and the World Bank Phone Survey for Uganda.

This technical note presents a modelling approach used in Lastunen et al. (2021) where tax and benefit policies are scaled to reflect their actual duration during a single calendar year. It can be applied to tax-benefit microsimulation models implemented in the EUROMOD software. The method is particularly useful when evaluating the impact of discretionary policy measures adopted during the COVID-19 pandemic. Tax-benefit microsimulation models typically simulate policies at a specific point in time, which is problematic when considering changes in policies over time, for instance over the course of the coronavirus pandemic. Using the standard point-in-time approach, only those policies that were in place at the specific cut-off date (e.g. July 2020) would be considered and, even if short-lived in reality, assumed to be effective throughout the whole calendar year. The approach presented here applies 'full-year adjustment' to any policies implemented in 2020 that were in force for less than 12 months, ensuring that relevant benefit amounts and tax liabilities are scaled to reflect realistic payments during the year.

This note, which forms part of a series of technical notes that complement Lastunen et al. (2021), reports the approach used to derive shocks to household expenditures from shocks at the individual-level labour incomes. Its structure is composed of six different parts that describe the technique used for the calculations and include the respective mathematical formulas. Through the sequence of formulas, we manage to calculate household expenditures from shocks at the individual-level labour incomes by first distributing the expenditures of a given household among people within the same household. We then calculate the own-account adjusted expenditure. Subsequently, we obtain the final expenditure by deriving the share of labour income vis-a-vis the total original income for each person and multiplying it by the own-account adjusted expenditure. Lastly, we sum up shocked individual expenditures within each household to derive shocked expenditures at the household level.

A forthcoming WIDER working paper examining how to account for informal consumption when modelling value-added tax (VAT) in SOUTHMOD tax-benefit microsimulation models, with applications to Rwanda, Peru, Mozambique, and Uganda.

Ethiopia initiated a major electricity sector reform in 2024, significantly increasing tariffs and introducing a value-added tax on electricity consumption to improve the financial sustainability of its state-owned utility. This study assesses the short-term distributional, sectoral, and cost-of-living impacts of this reform. The analysis links a tax-benefit microsimulation model (ETMOD) with a price-based social accounting matrix (SAM) multiplier framework to capture both direct, household-level welfare changes and indirect, economy-wide price transmission effects. The results show the reform is regressive, increasing the national poverty rate by 3.5 percentage points in a static, short-run setting. The tariff increase is the primary driver of this effect, while the VAT has a smaller impact. Indirect effects, transmitted through higher prices for essential goods such as food and water, account for two-thirds of the total poverty impact and are larger than the direct effect of higher electricity bills. Rural and informal households are disproportionately affected. These findings demonstrate that without compensatory measures, electricity pricing reforms necessary for fiscal stability can impose substantial social costs. We conclude that pairing such reforms with targeted social protection is essential to shield vulnerable households from adverse outcomes.

This paper examines the experience of building and using tax-benefit microsimulation models for countries in the Global South within the EUROMOD framework, drawing on SAMOD, the SOUTHMOD model family, and EUROMOD-based models for Latin America. It reviews the research contributions these tools have enabled — spanning distributional analysis, work incentives, informal employment, and automatic stabilization — and discusses the challenges of maintaining and updating them, as well as the opportunities they open for new avenues of research to strengthen social protection and fiscal capacity in developing economies.

This paper analyses the effectiveness of tax-benefit systems in reducing poverty and inequality across 13 countries in the Global South. Using national survey data and tax-benefit microsimulation models from the SOUTHMOD project, we provide a cross-country perspective on the redistributive impact of fiscal policies. Our analysis involves decomposing the sources of disposable income across the income distribution and estimating the contributions of different policy instruments to poverty and inequality. Additionally, we assess gender disparities in outcomes, quantify the distributional effects of recent policy changes, and simulate two budget-neutral tax-benefit reforms, focusing on their targeting efficiency and effects on work incentives. Studying the variability of these effects across countries illustrates how better policy design can improve welfare outcomes.

We examine the distributional effects of the COVID-19 pandemic and associated tax-benefit measures in seven sub-Saharan African countries, focusing on the onset of the crisis. We evaluate impacts on disposable incomes, considering variations across income groups; assess the effectiveness of tax-benefit policies in mitigating income losses; and analyse the influence of these measures on income-based poverty and inequality. We find notable reductions in disposable incomes, concentrated among higher-income households, and moderate increases in headcount poverty rates and poverty gaps. The study highlights the low effectiveness of pre-existing tax-benefit policies, with coverage gaps for the informal sector and a lack of income-dependent means-tested benefits. Discretionary tax-benefit policies in Mozambique and Zambia cushioned the shock for low-income households to a small extent. Conversely, school closures in Ethiopia and Ghana suppressed the provision of school meals, adding strain to households with school-age children.

This paper investigates the impact of the COVID-19 pandemic and related tax-benefit measures in Viet Nam. The focus is on the initial phase of the crisis in 2020. The study delves into how the pandemic affected disposable incomes, examining the differences across the income distribution and impacts on measures of poverty and inequality. The paper also evaluates the effectiveness of tax-benefit policies in reducing income losses caused by the pandemic, covering both the automatic stabilization of the pre-existing tax-benefit system and discretionary policy measures adopted in response to the crisis. The findings suggest that disposable incomes decreased by nearly 2.25 per cent on average, with the most pronounced effect experienced by higher-income households. Additionally, the estimates point to moderate increases in both the headcount poverty rate and the extent of poverty, as measured by the poverty gap. Automatic stabilizers had a limited effect in cushioning the income shock. The discretionary social protection measures, however, halved the pandemic-induced rise in the national poverty rate and fully reversed income losses for the poorest income quartile.

In the wake of the COVID-19 pandemic, several countries enacted tax and social protection measures to help mitigate the economic hardship faced by individuals and households. This experience underscores the need to better understand the impact of such programmes on incomes and poverty during crises, especially in low- and middle-income countries (LMICs) where they are most needed. This paper reviews existing empirical literature on the subject, conducting a scoping review on quantitative studies published between 2000 and 2022. Following a structured selection approach, we identify 38 studies about the role of social protection and taxation in LMICs during periods of crisis. The results reveal that LMICs often enact both vertical and horizontal expansions of existing unconditional cash transfer schemes during crises, although the applications vary by geography. Our research also suggests a sharp increase in recent studies because of the COVID-19 pandemic, and a large variety of methods used to study the subject. In terms of effects, social protection can help cushion households against crises, but the effect size depends on the policy adopted, country context, and type of crisis. The minimal empirical evidence about tax policy studies do not enable us to draw conclusions.

Establishing an equitable and efficient tax system is essential for reducing poverty, combating inequality, and fostering sustainable economic growth. Rwanda's government has recognized this and implemented significant changes to the personal income tax schedule for 2023 and 2024 as part of broader tax reforms set forth in its Medium-Term Revenue Strategy. This study examines the fiscal and distributional effects of the personal income tax changes, employing a newly-created tax-benefit microsimulation model for Rwanda. Specifically, we compare the reform to a business-as-usual scenario with the previous income tax regime. The analysis shows that the reform enhances the disposable income of many workers, albeit at the expense of reduced government revenue. At the population level, the reform predominantly benefits the highest income deciles, who constitute the majority of income taxpayers in Rwanda. The lowest deciles, for the most part, remain unaffected by the changes.

This paper assesses the feasibility of developing a tax and benefit microsimulation model in Rwanda. Tax-benefit microsimulation can be used to explore ways in which national development goals can be achieved in a cost-effective manner, and to assess the distributional effects of more comprehensive social security arrangements. The paper presents an account of Rwanda's tax and benefit policies as well as a possible underpinning dataset—the Integrated Household Living Conditions Survey—for a tax-benefit microsimulation model, concluding that developing such a model for Rwanda would be feasible.

Developing countries need to raise sufficient tax revenue to finance development. Revenue mobilization is often hampered by limited tax compliance, weak institutions, and technical problems with tax collection. One solution to these challenges is person-to-government (P2G) mobile phone payments, adopted in a number of developing countries since the early 2000s. This study assesses the causal effect of P2G adoption on tax revenue using propensity score matching. According to the matching estimates, countries that adopt P2G services experience a 1.2–1.3 percentage point boost in direct tax revenue as a share of GDP. P2G adoption increases revenue from both corporate and personal income taxes, with larger effects on the latter. The results remain robust to matching quality tests and alternative estimation methods, including function control, two-stage least squares, and system generalized method of moments. The average treatment effects are largest among lower-middle-income countries and countries characterized by limited tax compliance and corruption control, and by low levels of urbanization and domestic credit to the private sector. The findings suggest that developing countries, particularly those with poor institutions and low levels of financial inclusion, should promote the adoption and use of mobile money services for tax transactions.

Presumptive tax, a final tax on business income, was introduced in Uganda in 1997. The latest reform to the regime in July 2020 sought to make the system more progressive, simpler, and fairer to small firms. In this work, we evaluate the reform, focusing on its revenue implications based on simulations using UGAMOD, a tax-benefit microsimulation model for Uganda. Our findings suggest that, assuming full compliance, the reform reduces tax revenue potential by between 48–72 per cent from the previous rules. Interviews with staff at the Uganda Revenue Authority point to further challenges with the new rules, including slow implementation, ineffective enforcement, and enduring complexity. To address these concerns, we modelled a number of hypothetical reform scenarios, including a 1 per cent and 1.5 per cent flat tax regimes for small businesses with turnover between UGX10–150 million. A low flat tax rate would be a major improvement to the existing presumptive tax regime, as it satisfies the calls for further simplification, is estimated to generate more short-term revenue than the current regime based on the modelling, and has realistic potential to attract more presumptive taxpayers over time.

This paper analyses the distributional effects of the COVID-19 pandemic and related tax-benefit measures in 2020 from a cross-country comparative perspective for five African countries: Ghana, Mozambique, Tanzania, Uganda, and Zambia. We first estimate the impact of the crisis on disposable incomes, how effects vary across the income distribution, and in how far tax-benefit policies stabilized earnings losses. We then evaluate the impact on income-based poverty and inequality and the contribution of discretionary tax-benefit policies in alleviating the shock. Our analysis shows modest increases in headcount poverty rates and inequality, and somewhat larger effects on the poverty gap due to lower relative earnings losses of the poor population at the early stage of the pandemic analysed here. We find very limited stabilizing power of tax-benefit policies overall and automatic stabilizers in particular. This illustrates gaps in coverage for the large informal sector and a general lack of income-related means-tested benefits. Except for the Emergency Social Cash Transfer in Zambia, discretionary tax-benefit policies adopted in response to COVID-19 have had limited impact. Pausing a large school feeding programme in Ghana during lockdown has in turn put additional pressure on households with school-age children.

This report documents RWAMOD, the SOUTHMOD model developed for Rwanda. This work was carried out by UNU-WIDER, SASPRI, and the Rwanda Revenue Authority (RRA). The results presented in this report are derived using RWAMOD version 2.0, which is part of the SOUTHMOD bundle (SOUTHMOD_A4.0) and runs on EUROMOD software. The report describes the different tax-benefit policies in place, how the microsimulation model picks up these different provisions, and the database on which the model runs. It concludes with a validation of results against external data sources for Rwanda.

This report documents UGAMOD, the SOUTHMOD model developed for Uganda. This work was carried out by Uganda Revenue Authority (URA) in collaboration with the project partners. The results presented in this report are derived using UGAMOD version 3.0, which is part of the SOUTHMOD bundle (SOUTHMOD_A4.0) and runs on EUROMOD software. The report describes the different tax-benefit policies in place, how the microsimulation model picks up these different provisions, and the database on which the model runs. It concludes with a validation of results against external data sources for Uganda.

This report documents VNMOD, the SOUTHMOD model developed for Viet Nam. This work has been carried out by the Central Institute for Economic Management (CIEM) in collaboration with UNU-WIDER and SASPRI. The results presented in this report are derived using VNMOD version 3.5, which is part of the SOUTHMOD bundle (SOUTHMOD_A3.0) and runs on EUROMOD software. The report describes the different tax-benefit policies in place, how the microsimulation model picks up these different provisions, and the database on which the model runs. It concludes with a validation of results against external data sources for Viet Nam.

Many countries in Africa have designed simplified tax regimes for small businesses, including presumptive tax, a form of income tax charged on turnover. In Uganda, the most recent presumptive tax reform in July 2020 sought to address past challenges of complexity, regressivity and high tax rates. While the new reform simplifies the presumptive tax regime, it also suffers from challenges with enforcement and has low revenue potential. Alternative reforms presented in this brief, including a low-rate flat tax system, offer ways to simplify the presumptive regime further, with potential to support long-run compliance and revenue generation

The coronavirus pandemic has had a significant impact on the Ugandan economy. In 2020, Uganda's GDP growth rate was its lowest since 2000, owing to weak growth in services. With the exception of food relief and tax deferrals, the government did not implement new tax-benefit measures to support vulnerable populations during the crisis. The general tax-benefit system also had a negligible effect on cushioning income losses.

This study examines the impact of autonomous vehicles (AVs) on the employment prospects of professional drivers in the United States by 2040. I estimate both the number of jobs drivers lose to AVs and the number of new jobs that the AV industry generates for unemployed drivers. Since fully autonomous vehicles are expected to reach a market share of no more than 10 to 20 percent by 2030, driver mass unemployment is extremely unlikely before the 2030s. According to my four central estimates, the proportion of drivers that become unemployed (or employed outside the AV industry) will be at most 3% by 2025 and 12% by 2030. The estimates also suggest that the AV industry and related business models can by themselves easily repurpose all jobless drivers by that time. From 2030 onwards, however, all estimates point to substantial labor market impacts. If the effect of AVs on labor demand is not much smaller than projected, the proportion of drivers that become unemployed or employed outside the AV industry will be between 10–29% by 2035 and 19–78% by 2040 (10% and 33% in the central estimates). As job replacement speeds up, AV-supported jobs cover a smaller portion of lost driving jobs (90% in 2030, but only 41% in 2035 and 18% in 2040 in the central scenario).

This paper documents the MOBILE (Modeling Outcomes Based on Inequality in Labor Earnings) modeling framework developed by RAND. Income and wealth disparities within the United States are approaching levels not seen since the roaring 1920s, nine decades ago. While this issue has moved from the political fringes into the mainstream, the policy discussions have not always been grounded on solid evidence and analysis and have become mired in rhetoric. The policy solutions proposed for such disparities are typically the repurposed solutions to the economic maladies of previous cycles. This has created a role RAND is uniquely suited to fill given the broad and diverse skill sets available to study issues related to inequality. RAND has begun the development of the MOBILE model, which can serve as a vehicle for RAND to make a substantive, impactful, and persistent foray into the national discussion around economic disparities and possible policy responses. Fundamentally, the goal of MOBILE is to build a model that integrates childhood investments with labor market participation and outcomes, and can be used to understand the evolution of economic disparities, especially labor earnings, and the impact that various policies can have on such disparities. Such a model will be able to capture many aspects of a suggested policy in an objective way, without having to rely on opinions or ideologies. To that end, the team has developed a modeling framework that incorporates decisions made by key actors (workers, firms, government) and the relationships between these actors. We have developed both a static version of the model as well as a simple dynamic version that incorporates workers' decisions about investment in human capital.

Technological change in the 21st century is predominantly characterized by digitalization, or the use and development of information and communication technologies at companies. While digitalization facilitates economic progress, there is a growing concern about its effects on labor market disparities. In this dissertation, I document recent changes in labor outcomes by education and offer insights into the role of digitalization in shaping these trends. First, I show that the earnings premium for higher education has increased since the 2008 financial crisis. Among those with advanced degrees, technical majors accounted for the entirety of this growth. The gaps between education groups also increased the most in high-technology industries and occupations. In addition to documenting these trends, I examine how premiums have reacted to changes in the labor force composition. I show that the skill premium has increased despite rapid growth in the supply of skilled labor, suggesting that the demand for skill is rising. In subsequent chapters, digital advances are explored as a candidate explanation for this trend. I use variation in technology and labor market outcomes across industries, regions and individuals to study the effects of two complementary proxies of digitalization — investment in information technology and value added from digital goods. The analysis points to a positive impact of both proxies on earnings that increase with education and are concentrated in high-technology sectors. A causal interpretation of the differential effects of digitalization is bolstered by an instrumental variable approach and the limited impact of placebo regressors on the earnings premiums. While the two digitalization proxies amplify skill-based disparities in earnings, no education group is negatively affected by them in absolute terms. Finally, I assess policies that could reduce earnings disparities without slowing down the development of digital technologies or productivity growth more broadly. One effective solution would be to expand the number of skilled workers in the country. In a simple quantitative exercise, I show that relatively modest annual increases in the university-educated workforce could considerably moderate the skill premium. I offer practical recommendations on immigration and education policy to advance this goal in the coming decades.

TRB's National Cooperative Highway Research Program (NCHRP) Research Report 845: Advancing Automated and Connected Vehicles: Policy and Planning Strategies for State and Local Transportation Agencies assesses policy and planning strategies at the state, regional, and local levels that could influence private-sector automated vehicle (AV) and connected vehicle (CV) choices to positively affect societal goals. The report aims to assist agencies with exploring actions that might increase the likelihood that AV and CV technologies will have beneficial impacts on traffic crashes, congestion, pollution, land development, and mobility (particularly for older adults, youths under the age of 16, and individuals with disabilities).

This report discusses the mechanisms through which innovations based on information and communication technologies (ICT) may have effects on social inclusion. The report also assesses the dispersion of innovation performance across regions within countries. A core focus of the report is on exploring how innovation policies can contribute to inclusive growth and how they can be implemented efficiently. Moreover, the report discusses the role policies expanding access to higher education can play in supporting inclusive growth.