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We investigate how inviting students to set task-based goals affects usage of an online learning platform and course performance. We design and implement a randomized field experiment in a large mandatory economics course with blended learning elements. The low-cost treatment induces students to use the online learning system more often, more intensively, and to begin earlier with exam preparation. Treated students perform better in the course than the control group: they are 18.8% (0.20 SD) more likely to pass the exam and earn 6.7% (0.19 SD) more points on the exam. There is no evidence that treated students spend significantly more time, rather they tend to shift to more productive learning methods. The heterogeneity analysis suggests that higher treatment effects are associated with higher levels of behavioral bias but also with poor early course behavior.
High growth firms (HGFs) are important for job creation and considered to be precursors of economic growth. We investigate how formal institutions, like product- and labor-market regulations, as well as the quality of regional governments that implement these regulations, affect HGF development across European regions. Using data from Eurostat, OECD, WEF, and Gothenburg University, we show that both regulatory stringency and the quality of the regional government influence the regional shares of HGFs. More importantly, we find that the effect of labor- and product-market regulations ultimately depends on the quality of regional governments: in regions with high quality of government, the share of HGFs is neither affected by the level of product market regulation, nor by more or less flexibility in hiring and firing practices. Our findings contribute to the debate on the effects of regulations by showing that regulations are not, per se, “good, bad, and ugly”, rather their impact depends on the efficiency of regional governments. Our paper offers important building blocks to develop tailored policy measures that may influence the development of HGFs in a region.
In this paper we develop a spatial Cournot trade model with two unequally sized countries, using the geographical interpretation of the Hotelling line. We analyze the trade and welfare effects of international trade between these two countries. The welfare analysis indicates that in this framework the large country benefits from free trade and the small country may be hurt by opening to trade. This finding is contrary to the results of Shachmurove and Spiegel (1995) as well as Tharakan and Thisse (2002), who use related models to analyze size effects in international trade, where the small country usually gains from trade and the large country may lose.
This paper develops the incentives to collude in a model with spatially separated markets and quantity setting firms. We find that increases in transportation costs stabilize the collusive agreement. We also show that, the higher the demand in both markets the less likely will collusion be sustained. Gross and Holahan (2003) use a similar model with price setting firms, we compare their results with ours to analyze the impact of the mode of competition on sustainability of collusion. Further we analyze the impact of collusion on social welfare and find that collusion may be welfare enhancing.
This paper develops a spatial model to analyze the stability of a market sharing agreement between two firms. We find that the stability of the cartel depends on the relative market size of each firm. Collusion is not attractive for firms with a small home market, but the incentive for collusion increases when the firm’s home market is getting larger relative to the home market of the competitor. The highest stability of a cartel and additionally the highest social welfare is found when regions are symmetric. Further we can show that a monetary transfer can stabilize the market sharing agreement.
The present paper proposes a novel approach for equilibrium selection in the infinitely repeated prisoner’s dilemma where players can communicate before choosing their strategies. This approach yields a critical discount factor that makes different predictions for cooperation than the usually considered sub-game perfect or risk dominance critical discount factors. In laboratory experiments, we find that our factor is useful for predicting cooperation. For payoff changes where the usually considered factors and our factor make different predictions, the observed cooperation is consistent with the predictions based on our factor.
While the economic harm of cartels is caused by their price-increasing effect, sanctioning by courts rather targets at the underlying process of firms reaching a price-fixing agreement. This paper provides experimental evidence on the question whether such sanctioning meets the economic target, i.e., whether evidence of a collusive meeting of the firms and of the content of their communication reliably predicts subsequent prices. We find that already the mere mutual agreement to meet predicts a strong increase in prices. Conversely, express distancing from communication completely nullifies its otherwise price-increasing effect. Using machine learning, we show that communication only increases prices if it is very explicit about how the cartel plans to behave.
The experimental literature on antitrust enforcement provides robust evidence that communication plays an important role for the formation and stability of cartels. We extend these studies through a design that distinguishes between innocuous communication and communication about a cartel, sanctioning only the latter. To this aim, we introduce a participant in the role of the competition authority, who is properly incentivized to judge communication content and price setting behavior of the firms. Using this novel design, we revisit the question whether a leniency rule successfully destabilizes cartels. In contrast to existing experimental studies, we find that a leniency rule does not affect cartelization. We discuss potential explanations for this contrasting result.
Numerous studies investigate which sanctioning institutions prevent cartel formation but little is known as to how these sanctions work. We contribute to understanding the inner workings of cartels by studying experimentally the effect of sanctioning institutions on firms’ communication. Using machine learning to organize the chat communication into topics, we find that firms are significantly less likely to communicate explicitly about price fixing when sanctioning institutions are present. At the same time, average prices are lower when communication is less explicit. A mediation analysis suggests that sanctions are effective in hindering cartel formation not only because they introduce a risk of being fined but also by reducing the prevalence of explicit price communication.
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.
A rich literature links knowledge inputs with innovative outputs. However, most of what is known is restricted to manufacturing. This paper analyzes whether the three aspects involving innovative activity - R&D; innovative output; and productivity - hold for knowledge intensive services. Combining the models of Crepon et al. (1998) and of Ackerberg et al. (2015), allows for causal interpretation of the relationship between innovation output and labor productivity. We find that knowledge intensive services benefit from innovation activities in the sense that these activities causally increase their labor productivity. Moreover, the firm size advantage found for manufacturing in previous studies nearly disappears for knowledge intensive services.
The COVID-19 pandemic created the largest experiment in working from home. We study how persistent telework may change energy and transport consumption and costs in Germany to assess the distributional and environmental implications when working from home will stick. Based on data from the German Microcensus and available classifications of working-from-home feasibility for different occupations, we calculate the change in energy consumption and travel to work when 15% of employees work full time from home. Our findings suggest that telework translates into an annual increase in heating energy expenditure of 110 euros per worker and a decrease in transport expenditure of 840 euros per worker. All income groups would gain from telework but high-income workers gain twice as much as low-income workers. The value of time saving is between 1.3 and 6 times greater than the savings from reduced travel costs and almost 9 times higher for high-income workers than low-income workers. The direct effects on CO₂ emissions due to reduced car commuting amount to 4.5 millions tons of CO₂, representing around 3 percent of carbon emissions in the transport sector.
While some pronouncements of expert treaty bodies have been considered ‘key catalysts’ for the development of international human rights law, others are only selectively referred to in legal practice. This article argues that the varying normative impact is due to the informal character of pronouncements. In the absence of treaty provisions specifying their legal effect, practitioners tend to rely on different factors and arguments when either drawing on or rejecting certain pronouncements. Scholars in turn face difficulties when trying to identify explanatory patterns within this diverging practice as the informal character confronts both international lawyers and international relations scholars with their respective methodological ‘blind spots’. In light of these intradisciplinary challenges, this article explores the extent as to which an interdisciplinary approach helps to assess the reasons for the varying impact of pronouncements. After analysing the factors determining their legal significance on the basis of State practice and the academic debate, this article identifies the drafting process as a factor which promises to be particularly insightful when explored from an interdisciplinary perspective and sketches out a framework for future research.
Atwood (2022) analyzes the effects of the 1963 U.S. measles vaccination on longrun labor market outcomes, using a generalized difference-in-differences approach. We reproduce the results of this paper and perform a battery of robustness checks. Overall, we confirm that the measles vaccination had positive labor market effects. While the negative effect on the likelihood of living in poverty and the positive effect on the probability of being employed are very robust across the different specifications, the headline estimate-the effect on earnings-is more sensitive to the exclusion of certain regions and survey years.
Revisiting public investment
(2004)
The consumption equivalence method is the theoretical basis of public cost-benefit analysis. Consumption equivalence public capital prices are explicitly introduces in order to sufficiently care for the opportunity cost of public expenditure. This can solve the dispute about the social rate of discount within public cost-benefit analysis witch was generated on a criterion looking similar to the capital value formula, known as Lind’s approach. The social rate of discount is liberated from opportunity costs considerations and the discounting away of the effects for future welfare vanishes. The corresponding question whether one should accept a positive value of the pure rate of social time preference is an old issue. Its current state between the prescriptive and descriptive view can also be interpreted as a consequence of the oversimplification of standard cost– benefit analysis. But apart from an economic self-process the pure rate of social time preference is also defined as a business-as-usual value of social distance discounting. Hence, a political choice has to be made about this rate which is free in principal.
An exhaustive and disjoint decomposition of social choice situations is derived in a general set theoretical framework using the new tools of the Lifted Pareto relation on the power set of social states representing a pre-choice comparison of choice option sets. The main result is the classification of social choice situations which include three types of social choice problems. First, we usually observe the common incompleteness of the Pareto relation. Second, a kind of non-compactness problem of a choice set of social states can be generated. Finally, both can be combined. The first problem root can be regarded as natural everyday dilemma of social choice theory whereas the second may probably be much more due to modeling technique implications. The distinction is enabled at a very general set theoretical level. Hence, the derived classification of social choice situations is applicable on almost every relevant economic model.
Optimal carbon pricing with fluctuating energy prices — emission targeting vs. price targeting
(2022)
Prices of primary energy commodities display marked fluctuations over time. Market-based climate policy instruments (e.g., emissions pricing) create incentives to reduce energy consumption by increasing the user cost of fossil energy. This raises the question of whether climate policy should respond to fluctuations in fossil energy prices? We study this question within an environmental dynamic stochastic general equilibrium (E-DSGE) model calibrated on the German economy. Our results indicate that the welfare implications of dynamic emissions pricing crucially depend on how the revenues are used. When revenues are fully absorbed, a reduction in emissions prices stabilizes the economy in response to energy price shocks. However, when revenues are at least partially recycled, a stable emissions price improves overall welfare. This result is robust to different modeling assumptions.
The effects of energy price increases are heterogeneous between households and firms. Financially constrained poorer households, who spend a larger relative share of their income on energy, are particularly affected. In this analysis, we examine the macroeconomic and welfare effects of energy price shocks in the presence of credit-constrained households that have subsistence-level energy demand. Within a Dynamic Stochastic General Equilibrium (DSGE) model calibrated for the German economy, we compare the performance of different policy measures (transfers and energy subsidies) and different financing schemes (income tax vs. debt). Our results show that credit-constrained households prefer debt over tax financing regardless of the compensation measure due to their difficulty to smooth consumption. On the contrary, rich households tend to prefer tax-financed measures as they increase the labor supply of poor households. From an aggregate perspective, tax-financed measures targeting firms effectively cushion aggregate output losses.
A casual look at regional unemployment rates reveals that there are vast differences, which cannot be explained by different institutional settings. Our paper attempts to trace these differences in the labor market performance back to the regions' specialization in products that are more or less advanced in their product cycle. The model we develop shows how individual profit and utility maximization endogenously yields higher employment levels in the beginning. In later phases, however, employment decreases in the presence of process innovation. Our model suggests that the only way to escape from this vicious circle is to specialize in products that are at the beginning of their "economic life". The model is based on an interaction of demand and supply side forces.
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.