Hohenheim discussion papers in business, economics and social sciences

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Monetärer Keynesianismus : Versuch einer Rekonstruktion von Hajo Rieses "Theorie der Geldwirtschaft"
(2024) Spahn, Peter
Hajo Riese (FU Berlin) was a pioneer of the "Berlin School of Monetary Keynesianism", particularly in the 1980s and 1990s. His research work was based on the roots of monetary theory in the work of J. M. Keynes, with a particular focus on the theory of capital and interest rates. While in Keynes liquidity preference remained an element of money demand, for Riese it formed the central variable of a theory of credit supply. The credit contract is not based on goods or goods equivalents, but on the nominal category of money, because this is the sole medium for the fulfilment of contracts. In addition to the interest rate, the rate of return on real capital is also determined by the liquidity premium. The central bank has to take into account the regulatory-theoretical significance of monetary stability, which runs counter to the "easy money policy" usually demanded by Keynesians.
Screen for collusive behavior : a machine learning approach
(2024) Bantle, Melissa
The paper uses a machine learning technique to build up a screen for collusive behavior. Such tools can be applied by competition authorities but also by companies to screen the behavior of their suppliers. The method is applied to the German retail gasoline market to detect anomalous behavior in the price setting of the filling stations. Therefore, the algorithm identifies anomalies in the data-generating process. The results show that various anomalies can be detected with this method. These anomalies in the price setting behavior are then discussed with respect to their implications for the competitiveness of the market.
Intermedia agenda-setting from the far right? Three case studies on spillover effects by alternative media inGermany
(2023) Klawier, Tilman
Right-wing alternative media can increase their public impact if they succeed to set their issues on the mainstream media’s agenda. In three qualitative case studies, the present article explores whether and how such intermedia agenda-setting occurs in Germany. Special attention is given to spillover effects between different actors, both at the level of attention and tone towards the issues. Furthermore, the analysis of news articles is supplemented with Twitter data to account for the role of social media. Two of the case studies indicate that right-wing alternative media contributed to push pseudo-scandals into the mainstream. The analyses also reveal alternative news outlets with particular agenda-setting power and point to the crucial role of tabloid media as a bridge to the mainstream. The third study, however, which centered on the Global Compact for Migration, presents a case where intermedia agenda-setting failed. Against this background, the article discusses the conditions under which intermedia agenda-setting by right-wing alternative media is likely to occur and how journalists should deal with such attempts.
Unlocking the power of generative AI models and systems such asGPT-4 and ChatGPT for higher education
(2023) Vandrik, Steffen; Urbach, Nils; Gimpel, Henner; Hall, Kristina; Decker, Stefan; Eymann, Torsten; Lämmermann, Luis; Mädche, Alexander; Röglinger, Maximilian; Ruiner, Caroline; Schoch, Manfred; Schoop, Mareike
Generative AI technologies, such as large language models, have the potential to revolutionize much of our higher education teaching and learning. ChatGPT is an impressive, easy-to-use, publicly accessible system demonstrating the power of large language models such as GPT-4. Other compa- rable generative models are available for text processing, images, audio, video, and other outputs – and we expect a massive further performance increase, integration in larger software systems, and diffusion in the coming years. This technological development triggers substantial uncertainty and change in university-level teaching and learning. Students ask questions like: How can ChatGPT or other artificial intelligence tools support me? Am I allowed to use ChatGPT for a seminar or final paper, or is that cheating? How exactly do I use ChatGPT best? Are there other ways to access models such as GPT-4? Given that such tools are here to stay, what skills should I acquire, and what is obsolete? Lecturers ask similar questions from a different perspective: What skills should I teach? How can I test students’ competencies rather than their ability to prompt generative AI models? How can I use ChatGPT and other systems based on generative AI to increase my efficiency or even improve my students’ learning experience and outcomes? Even if the current discussion revolves around ChatGPT and GPT-4, these are only the forerunners of what we can expect from future generative AI-based models and tools. So even if you think ChatGPT is not yet technically mature, it is worth looking into its impact on higher education. This is where this whitepaper comes in. It looks at ChatGPT as a contemporary example of a conversational user interface that leverages large language models. The whitepaper looks at ChatGPT from the perspective of students and lecturers. It focuses on everyday areas of higher education: teaching courses, learning for an exam, crafting seminar papers and theses, and assessing students’ learning outcomes and performance. For this purpose, we consider the chances and concrete application possibilities, the limits and risks of ChatGPT, and the underlying large language models. This serves two purposes: • First, we aim to provide concrete examples and guidance for individual students and lecturers to find their way of dealing with ChatGPT and similar tools. • Second, this whitepaper shall inform the more extensive organizational sensemaking processes on embracing and enclosing large language models or related tools in higher education. We wrote this whitepaper based on our experience in information systems, computer science, management, and sociology. We have hands-on experience in using generative AI tools. As professors, postdocs, doctoral candidates, and students, we constantly innovate our teaching and learning. Fully embracing the chances and challenges of generative AI requires adding further perspectives from scholars in various other disciplines (focusing on didactics of higher education and legal aspects), university administrations, and broader student groups. Overall, we have a positive picture of generative AI models and tools such as GPT-4 and ChatGPT. As always, there is light and dark, and change is difficult. However, if we issue clear guidelines on the part of the universities, faculties, and individual lecturers, and if lecturers and students use such systems efficiently and responsibly, our higher education system may improve. We see a greatchance for that if we embrace and manage the change appropriately.
Strategic choice of price-setting algorithms
(2023) Schwalbe, Ulrich; Muijs, Matthias; Grüb, Jens; Buchali, Katrin
Recent experimental simulations have shown that autonomous pricing algorithms are able to learn collusive behavior and thus charge supra-competitive prices without being explicitly programmed to do so. These simulations assume, however, that both firms employ the identical price-setting algorithm based on Q-learning. Thus, the question arises whether the underlying assumption that both firms employ a Q-learning algorithm can be supported as an equilibrium in a game where firms can chose between different pricing rules. Our simulations show that when both firms use a learning algorithm, the outcome is not an equilibrium when alternative price setting rules are available. In fact, simpler price setting rules as for example meeting competition clauses yield higher payoffs compared to Q-learning algorithms.
Mind the gap: effects of the national minimum wage on the gender wage gap in Germany
(2022) Schmid, Ramona
With its introduction in 2015, the statutory minimum wage in Germany intends to benefit primarily low-wage workers. Thus, this paper aims at estimating the effectiveness of the implemented wage floor on gender wage gaps in the lower half of the wage distribution. Using administrative data, distinct regional differences regarding magnitudes of wage differentials and responses to the minimum wage are identified. Overall, wage gaps between men and women at the 10th percentile decrease by 2.46 and 6.34 percentage points respectively in the West and East of Germany after 2015. Applying counterfactual wage distributions, the study provides new evidence that around 60% and even 95% of the decline result from the introduction of the minimum wage in each region. Further, group-specific analyses identify concrete responses on the basis of age, educational level and occupational activity. Having yearly data, the study additionally reveals new results on the impact of the successive minimum wage raises in 2017 and 2019. Counterfactual aggregate decompositions of gender wage gaps finally indicate a decrease in discriminatory remuneration structures in the West of Germany due to the introduced wage floor.
Technical change, task allocation, and labor unions
(2022) Marczak, Martyna; Beißinger, Thomas; Brall, Franziska
We propose a novel framework that integrates the task approach" for a more precise production modeling into the search-and-matching model with low- and high-skilled workers, and wage setting by labor unions. We establish the relationship between task reallocation and changes in wage pressure, and examine how skill- biased technical change (SBTC) affects the task composition, wages of both skill groups, and unemployment. In contrast to the canonical model with a fixed task allocation, low-skilled workers may be harmed in terms of either lower wages or higher unemployment depending on the relative task-related productivity profile of both worker types. We calibrate the model to the US and German data for the periods 1995-2005 and 2010-2017. The simulated effects of SBTC on low-skilled unemployment are largely consistent with observed developments. For example, US low-skilled unemployment increases due to SBTC in the earlier period and decreases after 2010.
The return of happiness : resilience in times of pandemic
(2022) Ahlheim, Michael; Kim, In Woo; Vuong, Duy Thanh
Many papers have been written about peoples loss of life satisfaction during the first wave of the COVID-19 pandemic in 2020, but not much has been said about their resilience after the first shock had passed. Were people able to return, at least in part, to their original level of life satisfaction? This amounts to the question to which degree people had shown psychological resilience during the first wave of the COVID-19 crisis. In this context, it is also of interest which internal and external factors supported a persons tendency to prove resilient during the crisis. Based on an online survey conducted in August / September 2020 in Germany we try to answer these questions. We find that after a loss of average life satisfaction during the first three months after the outbreak of the pandemic in Germany many peoples life satisfaction increased again. Roughly 60% of the respondents proved resilient in the sense that eight months after the outbreak of the pandemic they had regained the same or an even higher level of life satisfaction as compared to the situation before the COVID-19 crisis. Our results show that besides socioeconomic characteristics like age and income and certain character traits, peoples personal experience during the crisis and their approval or disapproval of government policy during the crisis had an important influence on their chance to prove resilient. Therefore, a consistent and competent crisis communication building up trust in governments crisis management capacity is essential for peoples resilience in a crisis.
Migration and wage inequality : a detailed analysis for German regions over time
(2022) Schmid, Ramona
This study presents new evidence on immigrant-native wage differentials estimated in consideration of regional differences regarding the presence of Non-German population in metropolitan and non-metropolitan areas between 2000 and 2019 in Germany. Using linked employer-employee-data, unconditional quantile regression models are estimated in order to assess the degree of labor market integration of foreign workers. Applying an extended version of the Oaxaca-Blinder decomposition method, the results provide evidence on driving factors behind wage gaps along the entire wage distribution. There are not only changes in the relative importance of explanatory factors over time, but also possible sources of wage differentials shift between different points of the wage distribution. Differentiating between various areas in Germany, on average, larger wage gaps are revealed in metropolitan areas with at the same time a higher presence of the foreign population. Regarding the size of overall estimated wage gaps, after 2012 a reversal in trend and particular increasing tendencies around median wages are identified.
Occupational regulation, institutions, and migrants labor market outcomes
(2022) Koumenta, Maria; Pagliero, Mario; Rostam-Afschar, Davud
We study how licensing, certification and unionisation affect the wages of natives and migrants and their representation among licensed, certified, and unionized workers. We provide evidence of a dual role of labor market institutions, which both screen workers based on unobservable characteristics and also provide them with wage setting power. Labor market institutions confer significant wage premia to native workers (3.9, 1.6, and 2.7 log points for licensing, certification, and unionization respectively), due to screening and wage setting power. Wage premia are significantly larger for licensed and certified migrants (10.2 and 6.6 log points), reflecting a more intense screening of migrant than native workers. The representation of migrants among licensed (but not certified or unionized) workers is 14% lower than that of natives. This implies a more intense screening of migrants by licensing institutions than by certification and unionization.
Unraveling the spreading pattern of collusively effectivecompetition clauses
(2022) Trost, Michael
Meanwhile, the Industrial Organization literature gives several reasons why retailers adopt competition clauses (CCs) such as price matching or price beating guarantees. The motivations underlying the CCs might affect their forms and spread. In this paper, we unravel the spreading pattern of CCs in markets where they are used as a device to facilitate tacit collusion. It turns out that in homogeneous markets with capacity-constrained retailers, the retailers with the largest capacities are most inclined to adopt CCs. Our finding is in line with results of earlier studies on the formation of price leadership, which suggest that the retailers with the largest capacities take on the leadership position. On the other side, we find that in some market instances, retailers have to resort to CCs of non-conventional forms (i.e., of forms uncommon in real commercial life) to induce the most robust collusion. However, it turns out that this peculiar finding can be resolved for markets with additional characteristics. For example, if there exist market dominant retailers or the residual market demand is specified by efficient rationing, the most resilient collusion can also be enforced by CCs of conventional forms.
Input-output linkages and monopolistic competition : input distortion and optimal policies
(2021) Kohler, Wilhelm; Jung, Benjamin
In this paper, we provide a detailed analysis of a mechanism that distorts production towards too much use of primary factors like labor and too little use of intermediate inputs. The distortion results from two ingredients that are cornerstones of modern quantitative trade theory: monopolistic competition and input-output linkages. The distortion as such is unrelated to trade, but has important consequences for trade policy, including a positive first-order welfare effect from an import subsidy. For a crystal-clear view on the distortion, we first look at it in a single-sector, closed economy where the monopolistic competition equilibrium would be efficient without the presence of input-output linkages. We compare the social-planner-solution with the decentralized market equilibrium, and we identify first-best policies to correct the distortion. To analyze the trade policy implications we then extend our analysis to a setting with trade between two symmetric countries. We identify first-best cooperative policies, featuring nondiscriminatory subsidies of intermediate input use, aswell as non-cooperative trade policies where countries use tariffs to weigh terms of trade effects against benefits from correcting the input distortion.
The rise of Eastern Europe and German labor market reform : dissecting their effects on employment
(2021) Walter, Timo
From the early 1990s until 2005 the unemployment rate rose in Germany from 7.3% to 11.7%. While the unemployment rate reached its peak in 2005, it decreased steadily in the following years. On the one hand, the fourth stage of the German labor market reform (Hartz IV) was implemented in 2005 with the intent to cut the unemployment rate. On the other hand, the productivities in Germany and Eastern Europe grew strongly during the same period, enhancing the joint trade. The “rise of the East”, in terms of rising trade, is likely to have had an ambiguous effect on the German labor market. This paper investigates the employment effects of the “Hartz IV-Reform”. Further, it concentrates on the labor market effects of the German and Eastern European productivity shock. The focus lies on the national and county level (including 402 counties). As the effects on regional labor markets differ and take time, the paper builds on the dynamic and spatial trade model of Caliendo et al. (2019). I find that the “Hartz IV-Reform” and the German productivity contributes positively to the decline of unemployment, whereas the increase in Eastern European productivity is only responsible for a minor increase in unemployment.
The collusive efficacy of competition clauses in Bertrand Markets with capacity-constrained retailers
(2021) Trost, Michael
We study the collusive efficacy of competition clauses (CC) such as the meeting competition clause (MCC) and the beating competition clauses (BCC) in a general framework. In contrast to previous theoretical studies, we allow for repeated interaction among the retailers and heterogeneity in their sales capacities. Besides that, the selection of the form of the CC is endogeneized. The retailers choose among a wide range of CC types - including the conventional ones such as the MCC and the BCCs with lump sum refunds. Several common statements about the collusive (in)efficacy of CCs cannot be upheld in our framework. We show that in the absence of hassle costs, MCCs might induce collusion in homogeneous markets even if they are adopted only by few retailers. If hassle and implementation costs are mild, collusion can be enforced by BCCs with lump sum refunds. Remarkably, these fundings hold for any reasonable rationing rule. However, a complete specification of all collusive CCs is in general impossible without any further reference to the underlying rationing rule.
Entry regulation and competition : evidence from retail and labormarkets of pharmacists
(2021) Unsorg, Maximiliane; Rostam-Afschar, Davud
We examine a deregulation of German pharmacists to assess its effects on retail and labor markets. From 2004 onward, the reform allowed pharmacists to expand their single-store firms and to open or acquire up to three affliated stores. This partial deregulation of multi-store prohibition reduced the cost of firm expansion substantially and provides the basis for our analysis. We develop a theoretical model that suggests that the general limitation of the total store number per firm to four is excessively restrictive. Firms with high managerial effciency will open more stores per furm and have higher labor demand. Our empirical analysis uses very rich information from the administrative panel data on the universe of pharmacies from 2002 to 2009 and their affiliated stores matched with survey data, which provide additional information on the characteristics of expanding firms before and after the reform. We find a sharp immediate increase in entry rates, which continues to be more than five-fold of its pre-reform level after five years for expanding firms. Expanding firms can double revenues but not profits after three years. We show that the increase of the number of employees by 50% after five years and the higher overall employment in the local markets, which increased by 40%, can be attributed to the deregulation.
Price discrimination with inequity-averse consumers : a reinforcement learning approach
(2021) Buchali, Katrin
With the advent of big data, unique opportunities arise for data collection and analysis and thus for personalized pricing. We simulate a self-learning algorithm setting personalized prices based on additional information about consumer sensi- tivities in order to analyze market outcomes for consumers who have a preference for fair, equitable outcomes. For this purpose, we compare a situation that does not consider fairness to a situation in which we allow for inequity-averse consumers. We show that the algorithm learns to charge different, revenue-maximizing prices and simultaneously increase fairness in terms of a more homogeneous distribution of prices.
Endogenous life expectancy and R&D-based economic growth
(2021) Tscheuschner, Paul
We propose an overlapping generations framework in which life expectancyis determined endogenously by governmental health investments. As a nov-elty, we are able to examine the feedback effects between life expectancy andR&D-driven economic growth for the transitional dynamics. We find that i)higher survival induces economic growth through higher savings and higherlabor force participation; ii) longevity-induced reductions in fertility hampereconomic development; iii) the positive life expectancy effects of larger savingsand higher labor force participation outweigh the negative effect of a reductionin fertility, and iv) there exists a growth-maximizing size of the health caresector that might lie beyond what is observed in most countries. Altogether,the results support a rather optimistic view on the relationship between lifeexpectancy and economic growth and contribute to the debate surroundingrising health shares and economic development.
Automation, robots and wage inequality in Germany : a decomposition analysis
(2020) Schmid, Ramona; Brall, Franziska
We analyze how and through which channels wage inequality is affected by the rise in automation and robotization in the manufacturing sector in Germany from 1996 to 2017. Combining rich linked employer-employee data accounting for a variety of different individual, firm and industry characteristics with data on industrial robots and automation probabilities of occupations, we are able to disentangle different potential causes behind changes in wage inequality in Germany. We apply the recentered influence function (RIF) regression based Oaxaca-Blinder (OB) decomposition on several inequality indices and find evidence that besides personal characteristics like age and education the rise in automation and robotization contributes significantly to wage inequality in Germany. Structural shifts in the workforce composition towards occupations with lower or medium automation threat lead to higher wage inequality, which is observable over the whole considered time period. The effect of automation on the wage structure results in higher inequality in the 1990s and 2000s, while it has a significant decreasing inequality effect for the upper part of the wage distribution in the more recent time period.
Occupational licensing and the gender wage gap
(2020) Rostam-Afschar, Davud; Pagliero, Mario; Koumenta, Maria
We use a unique survey of the EU labor force to investigate the relationship between occupational licensing and the gender wage gap. We find that the gender wage gap is canceled for licensed self-employed workers. However, this closure of the gender wage gap is not mirrored by significant changes in the gender gap inhours worked. Our results are robust using decomposition methods, quantile regressions, different datasets, and selection correction.
Encompassing tests for value at risk and expected shortfall multi-step forecasts based on inference on the boundary
(2020) Schnaitmann, Julie; Liu, Xiaochun; Dimitriadis, Timo
We propose forecast encompassing tests for the Expected Shortfall (ES) jointly with the Value at Risk (VaR) based on flexible link (or combination) functions. Our setup allows testing encompassing for convex forecast combinations and for link functions which preclude crossings of the combined VaR and ES forecasts. As the tests based on these link functions involve parameters which are on the boundary of the parameter space under the null hypothesis, we derive and base our tests on nonstandard asymptotic theory on the boundary. Our simulation study shows that the encompassing tests based on our new link functions outperform tests based on unrestricted linear link functions for one-step and multi-step forecasts. We further illustrate the potential of the proposed tests in a real data analysis for forecasting VaR and ES of the S&P 500 index.

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