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Access to digital finance
(2024)
Financing entrepreneurship spurs innovation and economic growth. Digital financial platforms that crowdfund equity for entrepreneurs have emerged globally, yet they remain poorly understood. We model equity crowdfunding in terms of the relationship between the number of investors and the amount of money raised per pitch. We examine heterogeneity in the average amount raised per pitch that is associated with differences across three countries and seven platforms. Using a novel dataset of successful fundraising on the most prominent platforms in the UK, Germany, and the USA, we find the underlying relationship between the number of investors and the amount of money raised for entrepreneurs is loglinear, with a coefficient less than one and concave to the origin. We identify significant variation in the average amount invested in each pitch across countries and platforms. Our findings have implications for market actors as well as regulators who set competitive frameworks.
We investigate how the economic consequences of the pandemic, and of the government-mandated measures to contain its spread, affect the self-employed – particularly women – in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. Conversely, we do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, i.e. the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
While a growing body of literature finds positive impacts of Start-Up Subsidies (SUS) on labor market outcomes of participants, little is known about how the design of these programs shapes their effectiveness and hence how to improve policy. As experimental variation in program design is unavailable, we exploit the 2011 reform of the current German SUS program for the unemployed which strengthened case-workers’ discretionary power, increased entry requirements and reduced monetary support. We estimate the impact of the reform on the program’s effectiveness using samples of participants and non-participants from before and after the reform. To control for time-constant unobserved heterogeneity as well as differential selection patterns based on observable characteristics over time, we combine Difference-in-Differences with inverse probability weighting using covariate balancing propensity scores. Holding participants’ observed characteristics as well as macroeconomic conditions constant, the results suggest that the reform was successful in raising employment effects on average. As these findings may be contaminated by changes in selection patterns based on unobserved characteristics, we assess our results using simulation-based sensitivity analyses and find that our estimates are highly robust to changes in unobserved characteristics. Hence, the reform most likely had a positive impact on the effectiveness of the program, suggesting that increasing entry requirements and reducing support in-creased the program’s impacts while reducing the cost per participant.
The self-employed faced strong income losses during the Covid-19 pandemic. Many governments introduced programs to financially support the self-employed during the pandemic, including Germany. The German Ministry for Economic Affairs announced a €50bn emergency-aid program in March 2020, offering one-off lump-sum payments of up to €15,000 to those facing substantial revenue declines. By reassuring the self- employed that the government ‘would not let them down’ during the crisis, the program had also the important aim of motivating the self-employed to get through the crisis. We investigate whether the program affected the confidence of the self-employed to survive the crisis using real-time online-survey data comprising more than 20,000 observations. We employ propensity score matching, making use of a rich set of variables that influence the subjective survival probability as main outcome measure. We observe that this program had significant effects, with the subjective survival probability of the self- employed being moderately increased. We reveal important effect heterogeneities with respect to education, industries, and speed of payment. Notably, positive effects only occur among those self-employed whose application was processed quickly. This suggests stress-induced waiting costs due to the uncertainty associated with the administrative processing and the overall pandemic situation. Our findings have policy implications for the design of support programs, while also contributing to the literature on the instruments and effects of entrepreneurship policy interventions in crisis situations.
We demonstrate how the incentives of firms that partially own their suppliers or customers to foreclose rivals depend on how the partial owner can extract profits from the target (tunneling). Compared to a fully vertically integrated firm, a partial owner may obtain only a share of the target’s profit but influence the target’s strategy significantly. We show that the incentives for customer and input foreclosure can be higher, equal, or even lower with partial ownership than with a vertical merger, depending on how the protection of minority shareholders and transfer price regulations affect the scope for profit extraction.
This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude tacitly. We document that firms are less likely to communicate explicitly about price fixing and more likely to use indirect messages when sanctioning institutions are present. This effect of sanctions on communication reinforces the direct cartel-deterring effect of sanctions as collusion is more difficult to reach and sustain without an explicit agreement. Indirect messages have no, or even a negative, effect on prices.
In light of climate change mitigation efforts, revenues from climate policies are growing, with no consensus yet on how they should be used. Potential efficiency gains from reducing distortionary taxes and the distributional implications of different revenue recycling schemes are currently debated. To account for households heterogeneity and dynamic trade-offs, we study the macroeconomic and welfare performance of different revenue recycling schemes using an Environmental Two-Agent New-Keynesian model, calibrated on the German economy. We find that, in the long run, welfare gains are higher when revenues are used to reduce distortionary taxes on capital, but this comes at the cost of higher inequality: while all households prefer labor income tax reductions to lump-sum transfers, only financially unconstrained households are better off when reducing taxes on capital income. Interestingly, we find that over the transition period relevant to meet short-medium run climate targets, labor income tax cuts are the most efficient and equitable instrument.
We provide the first estimates of the impact of managers’ risk preferences on their training allocation decisions. Our conceptual framework links managers’ risk preferences to firms’ training decisions through the bonuses they expect to receive. Risk-averse managers are expected to select workers with low turnover risk and invest in specific rather than general training. Empirical evidence supporting these predictions is provided using a novel vignette study embedded in a nationally representative survey of firm managers. Risk-tolerant and risk-averse decision makers have significantly different training preferences. Risk aversion results in increased sensitivity to turnover risk. Managers who are risk-averse offer significantly less general training and, in some cases, are more reluctant to train workers with a history of job mobility. All managers, irrespective of their risk preferences, are sensitive to the investment risk associated with training, avoiding training that is more costly or targets those with less occupational expertise or nearing retirement. This suggests the risks of training are primarily due to the risk that trained workers will leave the firm (turnover risk) rather than the risk that the benefits of training do not outweigh the costs (investment risk).
Strategic uncertainty is the uncertainty that players face with respect to the purposeful behavior of other players in an interactive decision situation. Our paper develops a new method for measuring strategic-uncertainty attitudes and distinguishing them from risk and ambiguity attitudes. We vary the source of uncertainty (whether strategic or not) across conditions in a ceteris paribus manner. We elicit certainty equivalents of participating in two strategic 2x2 games (a stag-hunt and a market-entry game) as well as certainty equivalents of related lotteries that yield the same possible payoffs with exogenously given probabilities (risk) and lotteries with unknown probabilities (ambiguity). We provide a structural model of uncertainty attitudes that allows us to measure a preference for or an aversion against the source of uncertainty, as well as optimism or pessimism regarding the desired outcome. We document systematic attitudes towards strategic uncertainty that vary across contexts. Under strategic complementarity [substitutability], the majority of participants tend to be pessimistic [optimistic] regarding the desired outcome. However, preferences for the source of uncertainty are distributed around zero.
On Track to Success?
(2022)
Many countries consider expanding vocational curricula in secondary education to boost skills and labour market outcomes among non-university-bound students. However, critics fear this could divert other students from more profitable academic education. We study labour market returns to vocational education in England, where until recently students chose between a vocational track, an academic track and quitting education at age 16. Identification is challenging because self-selection is strong and because students’ next-best alternatives are unknown. Against this back- drop, we leverage multiple instrumental variables to estimate margin-specific treatment effects, i.e., causal returns to vocational education for students at the margin with academic education and, separately, for students at the margin with quitting education. Identification comes from variation in distance to the nearest vocational provider conditional on distance to the nearest academic provider (and vice-versa), while controlling for granular student, school and neighbourhood characteristics. The analysis is based on population-wide administrative education data linked to tax records. We find that the vast majority of marginal vocational students are indifferent be- tween vocational and academic education. For them, vocational enrolment substantially decreases earnings at age 30. This earnings penalty grows with age and is due to wages, not employment. However, consistent with comparative advantage, the penalty is smaller for students with higher revealed preferences for the vocational track. For the few students at the margin with no further education, we find merely tentative evidence of increased employment and earnings from vocational enrolment.