This paper examines how individuals engage in retirement planning using unique administrative data from Sweden’s national pension dashboard, minPension. The data provide a detailed proxy for planning behavior by capturing when individuals simulate future pension outcomes. Engagement rises strongly with age: about half of 55-year-olds make a forecast, compared with roughly three-quarters of those aged 65. Usage is unevenly distributed, however. Individuals with higher education and income are more likely to plan, while those with lower socio-economic status engage less, consistent with a digital divide in financial planning. Women are more likely to register on the platform, but men are more active once registered. Major life events such as widowhood, unemployment, or health shocks increase engagement, whereas disruptive events like divorce reduce it. The results highlight the importance of timely, targeted interventions to support retirement planning, especially among groups at risk of under-preparation.

This paper examines the determinants of shadow economy size with a focus on

institutional quality, using data from 165 countries for 2020-2023. We propose two proxies for institutional quality: novel indicator Value Added Tax revenue performance (VAT revenues as a percentage of GDP), and the Government Services Efficiency index (GSE). By using VAT revenue performance, we extend the existing literature beyond its conventional focus on VAT standard rates. We estimate regression models in which the size of the shadow economy is related to VAT revenues as a share of GDP, the VAT standard rate, trade openness, GDP per capita and GSE. Overall, we found that VAT revenue performance is a valid proxy for institutional quality at the cross-country level. We empirically confirm that both VAT revenue performance and GSE serve as reliable proxies for institutional quality.

We study the pass-through and distributional incidence of Value Added Tax (VAT) exemptions on food in a lower-income country with very high informality. Exploiting the unanticipated removal of VAT on selected items, we combine administrative data, a monthly census of supermarket prices, web-scraped online prices, and a nationally representative monthly phone-survey panel. Using difference-in-differences, we estimate pass-through from price changes for exempt versus non-exempt items and measure incidence using household expenditure, quantities, and purchase locations. Pass-through is complete in formal supermarkets in central urban areas, but price reductions are limited elsewhere. This spatial heterogeneity is strongly correlated with local store competition. VAT exemptions are highly regressive: for each dollar of foregone revenue, only five cents reach the poorest quintile, reflecting lower purchases from formal stores in urban areas, greater subsistence, and lower consumption. Compared to forecasts from 237 economists, we show experts misjudge pass-through and overstate benefits for the poor.

Reliable estimates of undeclared work in Germany are scarce, yet they matter for tax and social security policy. Using two large-scale surveys (n=3,988) of the German general population and recipients of transfer benefits specifically, we elicit the prevalence of the supply and demand of undeclared work via direct questions, a crosswise model and a list experiment. We document substantial heterogeneity across sociodemographic groups that are in line with economic theory: Opportunity and incentives shape the decision to work undeclared. The self- and marginally employed as well as transfer recipients who face high effective marginal tax rates are particularly likely to work undeclared. The potential, especially for envelope wages, is substantial. We describe patterns of undeclared work in detail. The crosswise model consistently yields higher prevalence estimates for both supply and demand than direct questioning. We discuss assumptions and challenges when implementing list experiments.