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on Investment |
| By: | Betcherman, Gordon; Honorati, Maddalena; Moessinger, Martin |
| Abstract: | While the literature on the minimum wage is largely retrospective, analyzing impacts of past policy changes, this paper is uniquely forward-looking, forecasting how a proposed reform in Ukraine would affect future employment, earnings, and social contributions. The analysis simulates these effects by mimicking a proposal that would set a minimum wage floor equal to 40 percent of the previous year’s average wage once martial law is over and increasing the minimum wage by two percentage points annually until reaching 50 percent of the previous year’s average wage. The analysis draws on a 10 percent random sample of 2023 worker-level data from the Pension Fund of Ukraine, covering all jobs with pension contributions in the private sector and nonmilitary public sector. The results indicate that, under the proposal, by the end of the five-year transition period, the minimum wage would be 45 percent above the level it would have reached if adjusted only for wage inflation, which serves as the counterfactual. Projected job losses would be modest (0.51–1.03 percent), while total earnings would increase by up to 3.24 percent. The effect on social contributions and taxes would be the same as the effect on earnings since they are a fixed percentage of earnings in Ukraine. Applied to an administrative data set covering all formal sector workers, the methodology developed in the paper offers a useful tool for policy makers to anticipate the likely effects of the minimum wage reforms that are being considered. The paper concludes by discussing policy implications. |
| Date: | 2026–09–08 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wbrwps:11443 |
| By: | Yanzheng Jin; Pengyang Shao; Yunshan Ma; Haowen Pan; Naixin Zhai; Chen-Hui Song; Fei Shen; Kenji Kawaguchi |
| Abstract: | Formulaic alpha discovery seeks symbolic expressions that predict cross-sectional asset returns. In deployment, multiple formulas are combined into an alpha pool, where each formula is valued through the complementary information it contributes to joint predictive performance. While Reinforcement Learning and Generative Flow Networks have emerged as promising paradigms for generating formulaic alphas, existing frameworks face three related challenges. First, generating formulas individually leaves pool context and inter-formula complementarity outside the generative state. Second, formula-wise generation lacks a unified mechanism for preserving and revising structures at different levels. Third, pool-level rewards jointly reflect predictive performance and redundancy but cannot be differentiated directly through symbolic evaluation to train the generator. To overcome these challenges, we introduce AlphaPADI (Formulaic Alpha Discovery via Pool-Aware Hierarchical Discrete Diffusion), a novel framework built around three components: (1) grammar-constrained buffer initialization that constructs syntactically valid pool candidates, (2) pool-aware hierarchical diffusion that reconstructs complete pools at multiple structural scales under the current pool context, and (3) reward-guided pool refinement that evaluates joint predictive performance and inner diversity, updates the elite buffer, and trains the reverse model through reconstruction and preference learning. Empirical results on the Chinese and U.S. stock markets demonstrate that AlphaPADI outperforms the evaluated baselines in both predictive and portfolio performance, thereby validating pool-aware generation as an effective framework for automated alpha discovery. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.04959 |
| By: | Romero, João Prates |
| Abstract: | Os países da América Latina e do Caribe enfrentam uma crise de desenvolvimento caracterizada por três armadilhas que se reforçam mutuamente: a armadilha da baixa capacidade para crescer; a armadilha da alta desigualdade, baixa mobilidade social e frágil coesão social; e a armadilha da baixa capacidade institucional e governança pouco efetiva. Para romper essas armadilhas e evitar uma nova década perdida na região, é necessário um grande impulso (“big push”) de investimentos transformadores, articulado a políticas de desenvolvimento produtivo que assegurem um futuro mais produtivo, inclusivo e sustentável. No Brasil, desde 2023 vem sendo implementado o programa Nova Indústria Brasil (NIB), a partir de uma abordagem de políticas orientadas por missões, com identificação de cadeias prioritárias. O presente estudo contribui de forma original para os esforços de desconcentração geográfica do desenvolvimento produtivo brasileiro, mapeando a distribuição das cadeias produtivas no território nacional e identificando regiões promissoras para um adensamento tecnológico desconcentrado e inclusivo. |
| Date: | 2026–07–17 |
| URL: | https://d.repec.org/n?u=RePEc:ecr:col127:90193 |
| By: | Atkins, Jon |
| Abstract: | Urban street design plays a critical role in safety, mobility, community and public welfare. Yet, systematic, large analysis of streetscape change remains challenging due to the scale, heterogeneity and unstructured nature of publicly available data. We here introduce StreetTransformer, a unified, open-source, multi-modal visual analytics system and framework for gathering, comparing, retrieving and analyzing urban streetscape state and change over time. We construct a novel spatiotemporally grounded corpus for New York City’s more than 47, 000 intersections by integrating longitudinal aerial imagery, segmentation masks, civic design documents and capital reconstruction project data spanning nearly two decades of New York City history. Innovatively, this corpus includes a large cache of 33, 000 unstructured pdf document pages scraped from the NYC DOT website, which have been parsed, categorized and spatially linked to intersections using OCR and LLM-integrations. Additionally, project metadata, collected from NYC Open Data, is standardized and filtered to safety-focused interventions, grounding the Documents, Images and Masks with the city’s objective records. |
| Keywords: | Social and Behavioral Sciences |
| Date: | 2025–12–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt1bw139gk |
| By: | International Monetary Fund |
| Abstract: | On November 15, 2024, the IMF’s Executive Board concluded the Review of the IMF’s Transparency Policy and Open Archives Policy and approved a number of reforms. As an international institution, making important documents available to the public on timely basis enhances the IMF’s credibility, accountability, and effectiveness and is critical to fulfill its mandate of promoting global economic and financial stability. While transparency at the IMF is achieved through a range of policies and practices, the Transparency Policy and the Open Archives Policy form the core elements of the IMF’s transparency framework. The Fund has come a long way since the inception of these policies in the early nineties. Most Board documents are now published, published more quickly, and under more consistent and evenhanded application of modification rules. The information available in the Fund’s archives has increased and is more easily accessible to the public. While experience suggests that these policies are effective in delivering on their objectives, the landscape in which the Fund operates has evolved since these policies were last reviewed in 2013. In a more interconnected and shock-prone world the pace with which policymakers need to make decisions has accelerated and the expectations of stakeholders on the availability and timeliness of the Fund’s analysis and policy advice has grown. Against this backdrop, the 2024 Review of the IMF’s Transparency Policy and Open Archives Policy focuses on targeted reforms to (i) support faster publication of board documents and communications of Board’s decisions; (ii) strengthen the rules and processes to modify Board documents prior to publication; and (iii) allow faster release of some documents in the Fund’s archives accessible to the public. The reforms further clarify the scope and objectives of these policies, their implementation processes, and how to strengthen knowledge sharing. The review was supported by data analysis as well as surveys and consultations with key stakeholders, including Executive Directors, country authorities, IMF missions chiefs, and civil society organizations as detailed in the three background papers accompanying this 2024 review. |
| Keywords: | Accountability; Archives; Communication; Independence; Lending; Modification Rules; Publication; Surveillance Transparency; transparency Policy; policy debate; TRANSPARANCY Policy; staff candor; IMF Mission Chiefs; staff country report; Civil society organizations; Middle East; Europe |
| Date: | 2024–11–25 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfpps:2024/059 |
| By: | Szymon P. Chudziak |
| Abstract: | A new form of the fiscal multiplier suited to data expressed as gross growth rates is proposed, together with a structural vector autoregression that isolates discretionary fiscal policy from regime and rule-based components. Because cumulating growth-rate responses over a horizon involves a product rather than a sum, the proposed multiplier is multiplicative: both numerator and denominator are polynomials in the size of the fiscal impulse, so the multiplier varies nonlinearly with the scale of the expenditure programme -- a dependence that conventional additive multipliers cannot capture. The multiplier requires no discounting, no ad hoc conversion factor, and no auxiliary estimate of an average expenditure share of output, and it is computed directly from nominal, non-seasonally-adjusted data, matching the terms in which government budgets are actually expressed. A version of the narrative approach to identification is introduced. It allows to decompose the influence of fiscal policy into a regime component, a standard policy rule embedded in the autoregressive structure, and discretionary shocks. Removing the regime component from the residuals yields smaller identified shocks, and correspondingly smaller multipliers, than found in SVARs not controlling for regime changes -- closing much of the gap between SVAR- and DSGE-based estimates. It is found that multipliers vary substantially across countries and across types of government expenditure, that regime volatility itself differs markedly by country, and that several economies display cyclicality in spending and multiplier paths that only becomes visible once responses are cumulated multiplicatively. The resulting multipliers are nominal, derived from unadjusted data, proven to be sensitive to shock size, and purged of regime effects, offering a tool with direct relevance for budget planning and fiscal policy evaluation. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.04982 |
| By: | International Monetary Fund |
| Abstract: | Executive Directors welcomed the report of the Independent Evaluation Office (IEO) on the IMF’s Exceptional Access Policy (EAP), encompassing the policy’s objectives and design, successive reforms, and experience with its implementation. They recognized that the Fund has sought to find a generally good balance between rules and flexibility in applying the EAP, while reinforcing transparency and accountability and adopting adequate safeguards. Directors generally concurred with the thrust of the evaluation that the EAP provided a structured framework for higher scrutiny through the exceptional access criteria (EAC) and enhanced decision making procedures, while maintaining flexibility through room for judgment in assessing the EAC. |
| Keywords: | EAP review; NA program; risk tolerance; Balance of payments need; Credit risk; Debt sustainability; Debt restructuring; Global |
| Date: | 2024–12–12 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfpps:2024/062 |
| By: | Mihaela-Adriana Nistor; Ionel Popescu |
| Abstract: | We study a two-regime summary of a real-valued loss distribution. The two representative levels and the boundary between them are chosen by minimizing a convex residual loss. When the distribution has an atom at the boundary, assigning that atom to the lower or upper regime can give different optimized costs. Taking the better whole-atom assignment yields the lower-semicontinuous cutoff profile. We prove epi-convergence of this profile under a loss-adapted \(\psi\)-weak topology and obtain convergence of minimum values and outer stability of optimal cutoff sets. Under a unique finite atom-free limiting cutoff, positive regime masses, and unique conditional centers, the two fitted levels and a canonical one-jump representation converge as well. We also examine the resulting summary from the viewpoint of monetary risk axioms, establish explicit failures of external monotonicity and subadditivity, and give finite-support algorithms with conditional error control. A four-scenario model illustrates the cutoff geometry and the role of ties and atoms. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.08821 |
| By: | Elisa Giannone; Yuhei Miyauchi; Nuno Paixao; Xinle Pang; Yuta Suzuki |
| Abstract: | How do depopulation and population aging evolve differently across regions within a country, and what are their implications for aggregate economic activity and regional inequality? Using spatially disaggregated data from Japan over the past several decades, we show that rural areas have experienced significantly faster depopulation and aging than urban areas, driven by low fertility and sustained out-migration of young cohorts. Regions undergoing these trends face declining local amenities and rising per-capita public service costs. To study the future evolution and economic consequences of these dynamics, we develop and calibrate a dynamic life-cycle spatial general equilibrium model. The model predicts widening geographic disparities in depopulation, aging, and economic activity in the coming centuries. While subsidies to declining regions can lower regional inequality, they come at the cost of lower aggregate efficiency and higher public service expenditures. |
| JEL: | E62 J11 O18 R12 R13 R23 |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35852 |
| By: | Christophe Barrette; Philippe Goulet Coulombe; Tim Reinicke |
| Abstract: | What should a macroeconomically relevant climate index contain? The composition is inherently ambiguous, and aggregation choices affect structural inference. We introduce the Assemblage VAR, which jointly estimates nonnegative aggregation weights and VAR parameters by maximizing the system likelihood-gain criterion, effectively outsourcing aggregation to observed macroeconomic dynamics. Two variants operate in component-space and rank-space, reweighting named subcomponents or emphasizing regions of the cross-sectional distribution. Applied to disaggregated U.S. climate data from the Actuaries Climate Index and NOAA, VARs using the assembled climate measures yield contractionary impulse responses that are substantially larger than those estimated using fixed-weight benchmarks. Weights emphasize high-wind variables and distributional tails over slow-moving components such as sea level. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.10043 |
| By: | Daniel P. Gross; Dror Shvadron; Hansen Zhang |
| Abstract: | Large language models are diffusing rapidly into science, raising concerns that delegating research writing to AI may undermine the development of expertise that scientific training is supposed to build. We measure AI-generated writing in the dissertations of a near-census of US STEM PhD graduates from 2019 to 2026 and link graduates to their subsequent employment. AI writing is absent before 2023, present in 29% of dissertations filed in 2026, and rapidly growing. Use is more common among students from non-English-speaking countries and at lower-ranked programs. Among graduates in the same program and cohort, those whose dissertations contain AI writing are less likely to enter academic research careers and more likely to enter non-tenure-track roles or industry, with this pattern strongest among US-origin students. At the same time as AI may increase research productivity, it thus appears to also be displacing a potentially important portion of the work through which scientific expertise is developed. |
| JEL: | I23 J24 O31 O33 |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35859 |
| By: | Marco Due\~nas; Antoine Mandel |
| Abstract: | A growing number of countries are adopting policies to reduce greenhouse-gas emissions, a process expected to reshape production systems and labour markets by altering relative prices and changing production and demand patterns across sectors. We develop an agent-based monetary input--output network model to analyse the medium-term effects of climate policies on production networks and sectoral labour allocation. The model features heterogeneous industries and households, incorporates greenhouse-gas emissions accounting, and is calibrated to a multi-regional input--output database covering the world economy. We simulate two alternative climate-policy scenarios over 2026--2035: one based on countries' nationally determined contributions and another targeting larger reductions in global emissions. The results reveal significant economy-wide reallocation: fossil-energy sectors contract, low-carbon energy sectors expand, and their positions within production networks change asymmetrically. Fossil energy loses relevance as a direct supplier and exerts less forward influence, while its remaining production becomes more dependent on intermediate inputs and upstream suppliers; low-carbon energy primarily strengthens its role as a supplier. Carbon pricing also generates sectoral labour gaps that, under mobility frictions, imply greater potential transitional unemployment. Because the model allows only limited technological change and adjustment within existing production links, the simulations provide a counterfactual assessment of how existing production structures respond to a relatively rapid climate transition, revealing the adjustment pressures that emerge when policy ambitions advance faster than the productive system's capacity to adapt. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.04018 |
| By: | Robin Ng; Greg Taylor |
| Abstract: | We study how content moderation facilitates communication on online platforms. A sender transmits information to a receiver, exerting effort to signal their truthfulness. Communication fails without moderation because the effort required is prohibitive. Moderation resolves this problem by making effort a more powerful signal of veracity. However, moderation crowds out sender effort, decreasing engagement value of content on the platform. A socially optimal policy may therefore involve limited moderation, but platforms often have an incentive to allow too much false content. We study the interaction between moderation and other strategic platform choices, including a platform’s decision to share revenue with creators, the decision to be a content-hosting platform, and the enablement of AI features. |
| Keywords: | user-generated content, content moderation, creator economy, media platforms, misinformation |
| JEL: | D83 L82 L86 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_698v4 |
| By: | Stijn Van Nieuwerburgh |
| Abstract: | Artificial intelligence is driving a large expansion in data center capacity, power infrastructure, and specialized computing equipment. We estimate that a 1 GW AI campus costs about $41 billion. A 188 GW U.S. buildout completed by 2032 would require total investment of nearly$9 trillion and amount to annual investment of 3.2 percent of GDP over 2025–2032. As hyperscaler capital expenditures outgrow internal cash flow, financing is shifting toward leases, joint ventures, project debt, private credit, securitization, and special-purpose vehicles. These structures expand funding capacity but also raise asset-level leverage, obscure contingent obligations, and expose investors to tenant concentration, technological obsolescence, execution delays, and uncertain residual values. |
| JEL: | E01 E22 G1 G31 R33 |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35865 |
| By: | Yu, Xuewen |
| Abstract: | Individual-level time series data, such as longitudinal survey data, are increasingly used for policy evaluation. To infer the impact of a policy given such data, we propose a hierarchical Bayesian structural time series (HBSTS) model that extends the existing Bayesian structural time series model. Hierarchical Bayesian structural time series can accommodate multiple observations per time point by adding an extra layer to capture individual-level variation. It also uses a regularized horseshoe prior with a signal-adaptive variable selection algorithm. These extensions provide a more flexible and realistic framework for policy evaluation, and make inference less sensitive to the prior specification of the expected model size (i.e. the expected number of covariates included in the model that are predictive of outcomes). In simulation studies, HBSTS demonstrated greater robustness to misspecification of the expected model size and was more powerful in detecting putative intervention effects compared with BSTS. We apply our model to the UK Household Longitudinal Study to investigate the impact of a UK immigration policy reform. Our findings indicated that the policy led to psychological distress among individuals from Black Caribbean backgrounds, which was also observed in an earlier Bayesian interrupted time series analysis, though derived by comparing them with people from White backgrounds. |
| Keywords: | Bayesian structural time series;causal inference;synthetic control method |
| JEL: | C1 |
| Date: | 2026–10–06 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:141174 |
| By: | Minmin Zeng |
| Abstract: | Financial institutions routinely downsample cross-sectional options panels to meet bandwidth and cost constraints. The industry default---deterministic Top-$k$ selection by open interest---provides no estimate of the aggregation error it introduces, rendering downstream risk metrics unauditable. We make the identification problem precise. For deterministic rules whose selected set depends only on auxiliary variables and not on the outcome (target-blind rules, of which Top-$k$-by-open-interest is one), the target is not identified from the retained outcomes alone unless bounds or modelling assumptions are imposed; under outcome bounds it is partially identified, with a sharp worst-case interval we characterise in closed form. We propose replacing Top-$k$ with probability sampling whose inclusion probabilities are proportional to open interest, paired with the Hajek ratio estimator and a linearised design-based variance estimator, yielding approximate design-based intervals around every aggregate. Experiments on 80 US trading sessions (211 tickers/day) and 83 sessions of Hong Kong options (131 tickers/day) show that for OI-weighted implied volatility the randomized design reduces mean absolute error by 35% (MAE 5.31 vs. 8.15 at 10% retention; paired $t=6.68$, Cohen's $d=0.75$, moving-block-bootstrap 95% CI $[1.82, 3.96]$), and the sharp worst-case interval available to Top-$k$ is 2.7--6.4$\times$ wider than the sampling interval under oracle bounds, and 9--26$\times$ wider under feasible bounds. Empirical coverage is 91.9% against a nominal 95%. We further document that inclusion probabilities must match the target's influence function, motivating a design-aware framework for production pipelines. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.08801 |
| By: | Paul McCloud |
| Abstract: | Entropic risk optimisation is a general framework for pricing and hedging financial derivatives in incomplete markets that can be used to decompose P&L into market and model risk contributions. When the prices are quadratic Gaussian, the coupled equations for price and hedge ratios are solved in closed form. This enables comprehensive analysis of trading P&L, with a decomposition of the model value-at-risk into convexity, dimension and funding contributions that are attributed in the explanation of realised P&L. The equations of the quadratic Gaussian model are directly applicable when the underlying prices follow Gaussian processes, such as fractional Ornstein-Uhlenbeck processes. The model also provides simple parametric expressions for hedge ratios that can be used for regressions in deep hedging. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.06168 |
| By: | Javier Flórez Mendoza; Robert Stehrer |
| Abstract: | Abstract: This policy brief discusses recent macroeconomic developments in the North African economies of Algeria, Egypt, Libya, Morocco, Tunisia, and Sudan as well as recent patterns of trade with the European Union (EU) and Austria, pointing to opportunities as well as challenges. Against a backdrop of supply-chain disruptions, geopolitical fragmentation, and rising vulnerabilities associated with technology dominance, critical raw materials, and energy security, North Africa has acquired renewed strategic relevance for European economic policy. The region combines geographic proximity to the EU along with sizeable markets, a young population, substantial renewable-energy potential, strategic transport corridors, and growing capabilities in sectors linked to the green and digital transitions. For the EU and Austria, deeper economic engagement with North Africa can support the diversification of suppliers, reduce excessive dependencies, and strengthen supply-chain resilience. The potential extends beyond the traditional exchange of fuels and raw materials to environmental technologies and renewable energy. A forward-looking European strategy should therefore combine trade with investment in infrastructure, human capital, renewable-energy systems, and partnerships. Initiatives such as the EU’s Global Gateway, Austria’s Africa Strategy, and the proposed Hydrogen South Corridor can help to connect North African production and energy potential more closely with European markets while supporting regional integration. |
| Keywords: | international trade, Austrian Foreign Trade, exports |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:wsr:pbrief:y:2026:m:10:i:75 |
| By: | Billy Buchanan (SAG Corporation) |
| Abstract: | This talk will describe a new command intended to serve as a near drop-in replacement for twoway to create interactive dashboards in Stata and how the command was developed. This is functionality that several users have requested at previous Stata conferences, and it is now here using syntax that Stata users already know. Just replace twoway with dash and you can be on your way. The inclusion of the Bootstrap CSS framework provides responsive dashboards that will resize themselves automatically based on the device's screen size. |
| Date: | 2026–10–03 |
| URL: | https://d.repec.org/n?u=RePEc:boc:usug26:07 |