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Mental health is an important component of public health, especially in times of crisis. However, monitoring public mental health is difficult because data are often patchy and low-frequency 1 – 3 . Here we complement established approaches by using data from helplines, which offer a real-time measure of ‘revealed’ distress and mental health concerns across a range of topics 4 – 9 . We collected data on 8 million calls from 19 countries, focusing on the COVID-19 crisis. Call volumes peaked six weeks after the initial outbreak, at 35% above pre-pandemic levels. The increase was driven mainly by fear (including fear of infection), loneliness and, later in the pandemic, concerns about physical health. Relationship issues, economic problems, violence and suicidal ideation, however, were less prevalent than before the pandemic. This pattern was apparent both during the first wave and during subsequent COVID-19 waves. Issues linked directly to the pandemic therefore seem to have replaced rather than exacerbated underlying anxieties. Conditional on infection rates, suicide-related calls increased when containment policies became more stringent and decreased when income support was extended. This implies that financial relief can allay the distress triggered by lockdown measures and illustrates the insights that can be gleaned from the statistical analysis of helpline data. Data collected from crisis helplines during the COVID-19 pandemic show that pandemic-related issues replaced rather than exacerbated underlying anxieties, and demonstrate that helpline data are useful indicators of public mental health.

We document mental and social distress of children, adolescents and adults, using data on 3 million calls to German helplines between January 2019 and May 2022. High-frequency data from crisis helpline logs offer rich information on the evolution of “revealed distress” among the most vulnerable, unaffected by researchers’ study design and framing. Distress of adults, measured by the volume of calls, rose significantly after both the outbreak of the pandemic and the Russian invasion of Ukraine. In contrast, the overall revealed distress of children and adolescents did not increase during those crises. The nature of young people’s concerns, however, changed more strongly than for adults after the COVID-19 outbreak. Consistent with the effects of social distancing, call topics of young people shifted from problems with school and peers to problems with family and mental health. We find the share of severe mental health problems among young people to have increased with a delay, in the second and third year of the pandemic.

We study how declared wealth responds to changes in wealth tax rates. Exploiting rich intranational variation in Switzerland, we find a 1 percentage point drop in a canton’s wealth tax rate raises reported taxable wealth by at least 43 percent after 6 years. Administrative tax records of two cantons with quasi-randomly assigned differential tax reforms suggest that 24 percent of the effect arises from taxpayer mobility and 21 percent from a concurrent rise in housing prices. Savings responses appear unable to explain more than a small fraction of the remainder, suggesting sizable evasion responses in this setting with no third-party reporting of financial wealth. (JEL D91, H24, H26, H31)

Recent theoretical work in economic geography has shown that agglomeration forces can mitigate 'race-to-the-bottom' tax competition, by partly or fully offsetting firms' sensitivity to tax differentials. We test this proposition using data on firm births across Swiss municipalities. We find that corporate taxes deter firm births less in more spatially concentrated sectors. Firms in sectors with an agglomeration intensity in the top quintile are less than half as responsive to differences in corporate tax burdens as firms in sectors with an agglomeration intensity in the bottom quintile. Hence, agglomeration economies do appear to attenuate the impact of tax differentials on firms' location choices.

This paper surveys the literature on the implications of trade liberalisation for intra-national economic geographies. Three results stand out. First, neither urban systems models nor new economic geography models imply a robust prediction for the impact of trade openness on spatial concentration. Whether trade promotes concentration or dispersion depends on subtle modelling choices among which it is impossible to adjudicate a priori. Second, empirical evidence mirrors the theoretical indeterminacy: a majority of cross-country studies find no significant effect of openness on urban concentration or regional inequality. Third, the available models predict that, other things equal, regions with inherently less costly access to foreign markets, such as border or port regions, stand to reap the largest gains from trade liberalisation. This prediction is confirmed by the available evidence. Whether trade liberalisation raises or lowers regional inequality therefore depends on each country's specific geography.

We analyse small businesses' recourse to public support measures during the COVID-19 crisis using a survey of 1011 self-employed workers and small business owners in Switzerland. We find that \"objective\" measures of lockdown affectedness and economic structure explain fairly well how businesses availed of support measures to cover labour costs. Recourse to government-backed corona loans, however, appears to be driven to a larger extent by behavioural idiosyncrasies across firms. Specifically, previously indebted businesses took out corona loans more readily than those who had been debt-free before the pandemic. Since uptake is not well in line with firm fundamentals, we propose making loan repayments contingent on future profits. This will more effectively target and sustain businesses that are in trouble today but would be viable in the absence COVID-19.

We study how industry-level agglomeration economies affect government policy. Using administrative data on firm subsidies in economically lagging regions of Great Britain, we contrast two alternative hypotheses. Economic geography models imply that firms at an industry’s core can sustain higher tax burdens or require lower subsidies than firms in more remote locations. Conversely, political economy models predict firms at the industry’s core to be more successful at lobbying government, particularly at the subnational level, thus obtaining more favourable fiscal treatment. Our evidence suggests that local government agencies structure subsidy offers to favour pre-existing employment in locally agglomerated industries, behaviour more in line with theories of policy capture than with economic geography models. Grants administered by central government agencies, however, conform more strongly with the predictions of economic geography models.

Mental health is an important component of public health, especially in times of crisis. However, monitoring public mental health is difficult, because data are often patchy and low-frequency. As a complement to established approaches, we turn to data from helplines. Helpline calls offer a real-time measure of ‘revealed’ distress and mental health concerns across a range of topics. We have collected data on 7 million calls from 19 countries, focusing on the COVID-19 crisis. We find that call volumes peaked six weeks after the initial outbreak, at 35% above pre-pandemic levels. The increase was mainly driven by fear (including fear of infection), loneliness, and, later in the pandemic, physical-health concerns. Relationship issues, economic problems, violence, and suicidal ideation, however, were less prevalent than before the pandemic. This pattern is apparent both during the first wave and during subsequent COVID-19 waves. Issues directly tied to the pandemic therefore seem to have substituted rather than exacerbated underlying anxieties. Conditional on infection rates, suicide-related calls increased when containment policies became more stringent and decreased when income support was extended. This implies that financial relief can allay the distress triggered by lockdown measures and illustrates the insights that can be gleaned from a statistical analysis of helpline data.

Tax reform proposals in the spirit of the “flat tax” model typically aim to reduce three parameters: the average tax burden, the progressivity of the tax schedule, and the complexity of the tax code. We explore the implications of changes in these parameters for entrepreneurial activity, measured by counts of firm births. The Swiss fiscal system offers sufficient intra-national variation in tax codes to allow us to estimate such effects with considerable precision. We find that high average taxes and complicated tax codes depress firm birth rates, while tax progressivity per se promotes firm births. The latter result supports the existence of an insurance effect from progressive corporate income taxes for risk-averse entrepreneurs. However, implied elasticities with respect to the level and complexity of corporate taxes are an order of magnitude larger than elasticities with respect to the progressivity of tax schedules.