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on Informal and Underground Economics |
| By: | Dix-Carneiro, Rafael; Goldberg, Pinelopi Koujianou; Meghir, Costas; Ulyssea, Gabriel |
| Abstract: | We examine the effects of international trade in the presence of a set of domestic distortions giving rise to informality, a prevalent phenomenon in developing countries. In our quantitative model, the informal sector arises from burdensome taxes and regulations that are imperfectly enforced by the government. In equilibrium, smaller, less productive firms face fewer distortions than larger, more productive ones, potentially leading to substantial misallocation. We show that in settings with a large informal sector, the gains from trade are significantly amplified, as reductions in trade barriers imply a reallocation of resources from initially less distorted to more distorted firms. We confirm findings from earlier reduced-form studies that the informal sector mitigates the impact of negative labor demand shocks on unemployment. Nonetheless, the informal sector can exacerbate the adverse real income effects of economic downturns, amplifying misallocation. Last, our research sheds light on the relationship between trade openness and cross-firm wage inequality. |
| Keywords: | Trade; Informality |
| JEL: | F14 F16 J46 O17 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20250 |
| By: | Gabriel Montes-Rojas (IIEP-UBA/CONICET); Fernando Toledo (UNLP); Juan Manuel Rodríguez Repeti (IIEP-UBA) |
| Abstract: | This paper studies what happens when AI gets cheaper, with emphasis on the labor market outcomes, whether it creates formal jobs or whether it pushes workers into informality. We argue that the answer depends on the elasticity of substitution between imported AI capital and formal labor. We build a small open economy DSGE model with a dual labor market, imported AI capital, and country risk, calibrated to an economy where informality is pervasive. The same decline in AI prices produces sharply different labor-market outcomes depending on whether AI substitutes or complements formal workers. Under substitution, cheaper AI weakens formal labor demand and increases the role of the informal sector as an employment buffer. Under complementarity, it expands formal employment and amplifies output, wages, investment, and capital accumulation. The model therefore shows that AI can become either a source of displacement pressure or a driver of formal-sector expansion, depending on how it interacts with human labor. |
| Keywords: | Artificial Intelligence, Informal Economy, Dual Labor Markets, DSGE, Latin America |
| JEL: | E26 F41 O33 J46 C68 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:aoz:wpaper:401 |
| By: | Alessandra Foresta1 Rigissa Megalokonomou2 Michael Vlassopoulos3 |
| Abstract: | This paper investigates whether fiscal crises affect how the judiciary handles tax evasion. We study this question in the context of the Greek debt crisis, in which tax evasion was publicly blamed for the fiscal collapse, and judges themselves experienced substantial salary cuts as part of the resulting austerity programme. Using a novel dataset compiled from Greek Supreme Court rulings between 2006 and 2014, we compare tax evasion appeals with appeals in other serious crimes not directly related to the fiscal crisis, such as homicide and rape, in a difference-in-differences framework. We find that the probability that the Supreme Court rejects tax-evasion appeals increases by about 25 percentage points relative to these control offences after January 2010—about a 43% increase relative to the pre-crisis baseline. Effects are larger in months with greater public attention to tax evasion, as measured by Google Trends, suggesting a role for salience. Our findings suggest that fiscal crisis conditions can alter the judicial treatment of tax offences. |
| Keywords: | fiscal capacity, judicial decision-making, tax evasion, financial crisis, narrative economics |
| JEL: | D91 P16 K40 K42 H20 H26 |
| Date: | 2026–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:mos:moswps:paper_1785128734527_482 |
| By: | Dolado, Juan J; Janez, Alvaro; Wellschmied, Felix |
| Abstract: | Online food delivery platforms typically operate through a controversial business model that relies on subcontracting self-employed workers, known as riders. We quantify the labor-market effects of the Spanish Riders’ Law in 2021 that established the presumption of dependent employment for riders using a search and matching model. Riders with heterogeneous preferences for leisure trade off work flexibility and easier employability as self-employed against enjoying higher wages as employees. Our main finding is that the reform led to a higher share of employees but failed to fully absorb the large flows of workers transiting out of self-employment and decreased riders’ wages leading to welfare losses. However, complementing the reform with a payroll tax cut for platforms hiring employees preserves employment levels and increases riders’ welfare. |
| Keywords: | Employees |
| JEL: | J21 J60 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19974 |
| By: | Jarkko Harju; Ida Kankaanranta; Kaisa Kotakorpi |
| Abstract: | We study the effects of taxi market deregulation in Finland, which removed price controls and lowered barriers to entry. The reform led to a surge in firm entry and a modest increase in exit, indicating substantial changes in market structure. Average taxi prices increased slightly according to price indices, while monthly firm-level reported sales and VAT declined by over 10 percent. Operating costs and mileage remained largely unchanged, suggesting limited demand responses. These findings point to increased tax evasion following deregulation. Consistent with this interpretation, we document a small rise in property crime, with no effects on other criminal offenses. |
| Keywords: | taxi market, deregulation, prices, sales, mileage, exit, entry, tax evasion, crime |
| JEL: | L52 L91 L98 H26 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12819 |
| By: | Jingnan Chen (Department of Economics, University of Exeter); Yixin Chen (Central University of Finance and Economics); Zhixin Dai (School of Finance, Renmin University of China); Tianqi Wei (China University of Political Science and Law); Su Yang (Renmin University of China) |
| Abstract: | Taxpayers rarely observe audit probabilities and must infer changes in enforcement from personal and social experience. We study this process in a laboratory tax-reporting experiment with 568 participants. Each participant faces hidden audit probabilities of 5 percent and 25 percent in randomized order, and we vary peer information across sessions from none to one or two preceding audit outcomes in a sparse network and three in a dense network. Before any peer outcome is transmitted, assignment to either network raises compliance by about 20% relative to no peer information. Once outcomes circulate, compliance in the dense network is approximately twice as responsive to enforcement as without peer information and about 60% more responsive than in the sparse network. This amplification is directional: relative to no peer information, the dense network raises compliance by about 12% after enforcement strengthens but lowers it by about 25% after enforcement weakens. Elicited belief distributions show that broader information reach improves learning about the changed enforcement environment. Higher perceived audit probabilities predict greater subsequent compliance, and the dense network's advantage comes from accumulating more peer signals rather than weighting each signal more heavily. Counterfactual policy exercises show that broader diffusion can reinforce deterrence under strong enforcement but erode it under weak enforcement; a model-based exercise suggests that full disclosure of the audit probability can reduce compliance under both weak and strong enforcement. |
| Keywords: | tax compliance, tax enforcement, social learning, information networks, subjective beliefs |
| JEL: | H26 D83 C91 |
| Date: | 2026–07–31 |
| URL: | https://d.repec.org/n?u=RePEc:exe:wpaper:2610 |
| By: | Andrea Panozzo, Lorenzo Spadavecchia, Adam Mugume, Elizabeth Kasekende, Samuel Namwanja Musoke, Mariss Nakayaga, Deo Sande, Anita Mpagi, Nzima Ghislain |
| Abstract: | In developing economies, output statistics arrive with long lags and omit a large informal sector, while digital payment systems record a growing share of transactions in near real time. We assess whether these records improve GDP nowcasts in Uganda, exploiting two national systems that observe complementary segments of the economy: Mobile Money, covering retail and informal transactions, and real-time gross settlement (RTGS), covering large-value formal payments. Within a pseudo-real-time design respecting each series’ publication lag, we augment a conventional macroeconomic panel with payment data across linear and machinelearning models. Payment data cut forecast errors by up to 16 percent and rank among the most informative predictors, with up to over three times the weight of a typical macroeconomic indicator. The improvement delivered by payment data is robust to macroeconomic disturbances, such as the COVID-19 contraction. Placebo tests attribute these gains to economic content, not added predictors. Already held by central banks, payment data offer a timely, low-cost input for surveillance where conventional statistics are weakest. |
| Keywords: | Nowcasting, Digital payments, Mobile money, RTGS |
| JEL: | C53 E37 G21 O17 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:baf:cbafwp:cbafwp26282 |
| By: | Abbiati, Giovanni; Battistin, Erich; Monti, Paola; Pinotti, Paolo |
| Abstract: | We evaluate a labor market integration program that fast-tracked asylum seekers into the Italian labor market through personalized job mentoring, placement assistance, and on-the-job training. Leveraging randomized assignment across reception centers and individual-level administrative records, we find effects on employment rates of 10 percentage points, or 30% over the baseline, over a 18-month period. The program also improved job quality through increased access to fixed-term and open-ended contracts. Subsidized internships were a critical pathway to transitioning participants into standard employment. Survey data indicate that these effects reflect a net increase in employment, rather than a shift from informal to formal jobs. We also document broader benefits on socioeconomic integration, including language proficiency and social networks with native Italians. |
| JEL: | C93 D04 F22 I38 J15 J61 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20150 |
| By: | Peters, Michael; Torola, Pamela; Uniat, Lindsey; Zilibotti, Fabrizio |
| Abstract: | India’s GDP per capita grew threefold between 1987 and 2019, coinciding with rapid urbanization. During this period, female labor force participation (FLFP) declined significantly. Consistent with this observation, we document a pronounced urban-rural participation gap, where FLFP is higher in poorer, rural labor markets. Using time-use data, we show that this is primarily driven by an extensive margin: in rural districts, women often engage in part-time activities, typically related to agriculture and informal family businesses. These activities are less common in urban areas, where some women take formal jobs, but a larger share withdraws from the labor market to focus on home production. We propose and estimate a model of household labor supply that aligns with these trends. The main drivers of the urban-rural participation gap are higher spousal incomes in cities, which reduce the marginal utility of female labor, and labor market distortions that depress women’s urban wages below their marginal product. Counterfactual simulations show that economic growth is unlikely to provide a sharp reversal of this trend in future decades unless it is accompanied by changes in gender norms and labor market institutions. |
| Keywords: | Informality; Distortions |
| JEL: | J22 O11 O17 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19959 |
| By: | Yeandle, Alex; Doyle, David |
| Abstract: | Mobile money platforms are ubiquitous in many emerging economies. Hailed for raising financial inclusion and economic wellbeing, governments have now turned to mobile payments as a source of tax revenue. Transaction levies are often regressive, unpopular, and can encourage a return to cash. We present experimental evidence that they may also harm tax morale, a core component of the social contract between citizen and state. We present results from a survey experiment in Ghana, in which priming a controversial mobile transaction levy significantly lowers support for the state's right to collect taxes and willingness to comply with tax laws. We combine this with focus group discussions and analyse effect heterogeneity to examine two pre-registered explanations: transaction taxes cost citizens more than they expect to gain (reciprocity) and provoke particular backlash from non-government voters (partisanship). Our findings suggest that taxing mobile money can undermine efforts to expand fiscal capacity, while raising important mechanistic and policy questions for future research. |
| Keywords: | Africa;experiment;mobile money;public opinion;tax morale |
| JEL: | J1 E6 |
| Date: | 2026–06–24 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:140135 |
| By: | Mehrotra, Santosh (Higher School of Economics); sing, Ashutosh (Independent skills specialist with 15 yrs of research, practitioner and consultancy experience) |
| Abstract: | Traditional Technical and Vocational Education and Training (TVET) systems are often misaligned with labour-market needs because they rely on supply-side financing and fragmented labour-market information. This paper addresses these institutional failures by reconstructing the first comprehensive estimate of India's aggregate TVET expenditure, triangulating fragmented data sources to estimate annual spending at US$6.7–9.4 billion. We propose a dual-pillar institutional architecture, integrated with India's Digital Public Infrastructure, comprising the Integrated Labour Contribution Base (ILCB), which links formal, payroll and informal-worker records into a unified labour-market information system, and the Reimbursable Industry Contribution (RIC), a mandatory 2% payroll-linked levy–grant mechanism for formal-sector firms. Macro-fiscal modelling shows that an annual allocation of US$2.2 billion can sustainably co-finance enterprise and apprenticeship training while expanding Recognition of Prior Learning, skill loans and training vouchers. By reducing information failures and employer free-riding, the proposed framework offers a scalable institutional model for financing skills development across India and the Global South. |
| Keywords: | TVET, human capital, Levy–Grant system, digital public infrastructure, informal economy, lifecycle fiscal projection |
| JEL: | H25 I25 J24 O15 O38 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18805 |
| By: | Emek Basker; Lucia Foster; Martha Stinson |
| Abstract: | We study the importance of bunching in the context of tip-income reporting by workers at full-service, single-unit restaurants in the United States. Using tax reports at both the individual and the employer levels, we show that reported tip income varies with minimum-wage laws that provide an incentive for tipped workers to report some, but not necessarily all, of their tips. As a result, reported tips bunch at the minimum required threshold. We quantify missing tips due to bunching at nearly $63 million per year in 2018 dollars, on average over the period 2005-2018. Bunching is stronger for jobs at small employers and in the earlier part of the time series and declined monotonically from 2010 to 2018. Using restaurant-level revenue data, we also estimate the total value of unreported tips assuming an average tip rate of 12%. We find that tips are missing throughout the distribution. All told, missing tips exceed $4 billion per year, implying that bunching explains only 1.5% of all missing tips. |
| Keywords: | Tipping, Restaurants, Tip Reporting, Bunching, Minimum Wage, Tip Credit |
| JEL: | J33 L82 H26 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:cen:wpaper:26-40 |