ABSTRACT The digital economy stimulates economic growth and offers new opportunities for women's flexible employment. Utilizing the “Resources‐Agency‐Achievements” economic empowerment theory and data from the Chinese General Social Survey (2012–2021), alongside provincial digital economy development data, this study estimates a fixed‐effects instrumental‐variable (FE‐IV) model to analyze the digital economy's impact on women's economic empowerment in flexible employment. Digital economic development significantly boosts this empowerment, and the KHB results are consistent with a mediating role for gender role attitudes. Post‐2015, following the “Internet Plus” initiative, the empowerment effect intensified, especially benefiting women with urban registration, higher education, and higher incomes. However, women aged 40 and older experience fewer benefits, and entrepreneurial activity is negatively associated with digital economy development. The study constructs a composite empowerment index and examines gender role attitudes as a mediator, thus expanding the theoretical framework. Policy recommendations include enhancing digital skills training, improving social security for flexible employment, developing women‐friendly digital tools, and promoting female success stories.
Understanding how climate change beliefs are shaped by peer networks is critical for designing effective climate communication strategies, yet the degree of peer influence across spatial and political contexts remains insufficiently understood. This study examines the influence of peer counties on local climate change beliefs using a generalized spatial autoregressive (GSAR) model. We construct geographic, political, and economic peer networks at the county level and quantify the magnitude of peer effects. Results show that a 10% increase in climate change beliefs among peer counties is associated with a 4.2% to 9.4% increase in average beliefs within the focal county, depending on the network type. The geographic peer network exerts the strongest influence, with estimated effects ranging from 6.7% to 9.4%, followed by the political network, with effects between 4.2% and 7.5%, for different climate beliefs. Counterfactual simulations show that targeting interventions to the most connected counties (MCCs)-those occupying central positions in the network-is more effective than focusing on counties with extreme belief levels or on MCCs with below-average beliefs. Targeting low-belief counties yields the largest relative improvements among the most vulnerable groups, whereas targeting top MCCs maximizes aggregate impact without disproportionately disadvantaging low-belief counties in percentage terms. These findings provide actionable insights for policymakers seeking to promote climate belief formation and encourage climate-friendly behaviors through network-informed interventions.
Previous theoretical analysis using classical urban models suggests that planning or topographic restrictions on structure density raise the price of housing in cities. This paper demonstrates that these past results are an artifact of special assumptions about the spatial distribution of planning or topographic restrictions. When alternative and more realistic regulations are examined using either classical or neoclassical models, the average housing price falls compared to laissez faire in the absence of amenity benefits. The standard empirical finding that housing prices rise with regulation implies that planning raises urban amenity. This illustrates the importance of the specific spatial distribution of land use and topographic restrictions and of amenity effects in research on the implications of urban development policies.
ABSTRACT The COVID‐19 pandemic severely hampered human mobility and disrupted a series of economic activities. In this study, I examine the impacts of vaccine coverage on mobility and several other economic indicators in the US. I construct a novel shift‐share instrument that leverages the strong correlation between vaccination rates and demographic composition by sex and age group to address endogeneity concerns. Using high‐frequency data, I find strong evidence that higher vaccine coverage increased mobility, reflected in more trips taken and a lower likelihood of staying at home. I then assess the effects of vaccination on multiple economic indicators. I find modest evidence that higher vaccine coverage increased labor market participation and employment rate, while the effects on new business applications and home mortgage applications are limited.
ABSTRACT This paper evaluates the firm‐level effects of geographical eligibility for the Italian Special Economic Zones (SEZs) policy in the Mezzogiorno over the period 2015–2023. Since administrative records on actual incentive uptake are not available, the empirical analysis should be interpreted as an intention‐to‐treat estimate, capturing the effect of being located in a designated SEZ area rather than the effect of receiving SEZ benefits. Using balance‐sheet data, Coarsened Exact Matching (CEM), and staggered Difference‐in‐Differences estimators, results suggest that SEZ eligibility is associated with a significant increase in investment and, to a lesser extent, profitability, while effects on employment are limited and delayed. Strong regional heterogeneity emerges, with areas such as Campania, Calabria, and Sardinia showing null or negative outcomes. Robustness checks based on alternative staggered‐adoption estimators, matching procedures, and controls for institutional quality confirm the main findings. Overall, the results suggest that place‐based incentives can stimulate firm investment, although their effectiveness varies substantially across territories, providing relevant insights for the design of future regional development strategies.
