This paper examines the impact of Sunday blue law reforms on small-scale wineries in the United States. Using establishment-level data from 2000 to 2020, we employ an event-study framework to analyze the impact of changes in Sunday alcohol sales regulations across states on the performance of small wineries. We find that deregulation is associated with substantial declines in the performance of small wineries. On average, sales fell by 25.5%, employment declined by 7.8%, and survival rates dropped by 5.2% following the repeal of Sunday sales restrictions. These adverse effects are particularly pronounced among the smallest wineries and those located in metropolitan counties. The results suggest that while deregulation increased consumer access to alcohol on Sundays, it also intensified competition from large-scale retail outlets, thereby undermining the direct-to-consumer sales channels that are critical to small wine producers.

This article introduces a blockchain-based insurance scheme that integrates parametric and collaborative elements. A pool of investors, referred to as surplus providers, locks funds in a smart contract, enabling blockchain users to underwrite parametric insurance contracts. These contracts automatically trigger compensation when predefined conditions are met. The collaborative aspect is embodied in the generation of tokens, which are distributed to surplus providers. These tokens represent each participant’s share of the surplus and grant voting rights for management decisions. The smart contract is developed in Solidity, a high-level programming language for the Ethereum blockchain, and deployed on the Sepolia testnet, with data processing and analysis conducted using Python. In addition, open-source code is provided and main research challenges are identified, so that further research can be carried out to overcome limitations of this first proof of concept.

In this study, we provide ex post empirical analysis of the effects of climate policies on carbon emissions at the aggregate national level, using a comprehensive database of 121 countries. Carbon taxes and emissions trading systems (ETS), and the overall stringency of climate policies are considered. We use dynamic panel regressions, controlling for macroeconomic factors (economic development, GDP growth, urbanisation and the energy mix). Higher carbon taxes and ETS prices reduce carbon emissions. An increase in carbon taxes by $10 per ton of CO2 reduces CO2 emissions per capita by 1.3% in the short run and by 4.6% in the long run.

This paper investigates the stability of the demand for money in the United States and provides a comparison among the simple-sum monetary aggregates, the original (non-credit-card-augmented) Divisia monetary aggregates, and the credit-augmented Divisia and credit-augmented Divisia inside aggregates. We use quarterly data from the Center for Financial Stability and the Pesaran et al. (2001) bounds test procedure to investigate the long-run relation between the monetary aggregates and their respective user costs. In doing so, we use three classic money demand functions—the log–log, the semi-log, and the Selden and Latané specifications. With quarterly data over the 1967:q1 through 2025:q1 period, for which the original Divisia monetary aggregates are available, we find evidence of a stable money demand function only with the Sum M4 aggregate under all money demand specifications, but not with any of the Divisia aggregates. With quarterly data over the post-2006 period, for which the credit-augmented Divisia monetary aggregates are also available, our findings show that the demand for money is stable across all money demand specifications with all of the original Divisia aggregates and the credit-augmented Divisia aggregates (but not with all of the credit-augmented Divisia inside aggregates). We also find evidence of cointegration with the Sum M3 and Sum M4 aggregates under all three money demand specifications, but not with the Fed’s Sum M2 aggregate.

Imprecise Bayesianism has been proposed as an alternative to Standard Bayesianism, partly because of its tools for representing ambiguity. Instead of representing credences via precise probabilities, a set of probability distributions is used to model belief states. However, there are criticisms of Imprecise Bayesianism’s update rule. A recent alternative update rule is Alpha Cut, which evades some of the primary criticisms of Imprecise Bayesian updating. We compare Alpha Cut with Imprecise Bayesianism and another alternative update approach called Calibration. We find that Alpha Cut has problems with respect to ambiguity, coherence, and performance qualities, whereas there are more promising alternatives.

Artisanal-and-small-scale gold mining supports millions of livelihoods in the Global South but is the largest anthropogenic source of mercury emissions. Many initiatives promote mercury-free technologies that small miners could employ. Few document mercury impacts. We study an alternative: instead of processing themselves, small miners sell their ore to plants employing larger-scale, mercury-free technologies that also raise gold yields. Some ore-selling occurs without policy intervention, yet impacts on incomes and mercury use remain unclear. We assess ore-selling preferences of female waste-rock collectors (jancheras) in Ecuador, using a discrete-choice experiment. Results demonstrate that jancheras generally are open to ore-selling, yet often reject options similar to a recent pilot intervention. Offers that address formalization hurdles (invoicing), inabilities to meet quantity minima (given limits upon association, storage, and credit), and constraints on trust (including in plants’ ore testing) could increase adoption by tailoring related interventions to the preferences of and challenges for defined populations.

This study examines how WTO members have engaged in Ministerial Conferences from 1996 to 2024 by analyzing over 1,500 formal ministerial statements. Despite being the most public and standardized form of participation in WTO deliberations, these statements have rarely been analyzed systematically. By treating them as indicators of institutional engagement, the study traces long-term patterns in the frequency, intensity, and content of member participation. The analysis confirms some established expectations – such as the tendency of economically larger members to participate more actively – but also uncovers less visible dynamics. Engagement levels shifted significantly around key institutional moments, notably the rise and suspension of the Doha Development Agenda, and evolved unevenly between developed and developing members. Methodologically, the study demonstrates how computational text analysis can extract meaningful patterns from formal international discourse. Using metadata and text-based measures, it shows how member statements can offer insight into negotiation alignments and institutional vitality. These findings complement existing accounts of WTO behavior and suggest new directions for understanding participation and representation in multilateral trade governance.