The authors provide a comprehensive overview of codetermination, that is, worker representation in firms’ governance and management. The available micro evidence points to zero or small positive effects of codetermination on worker and firm outcomes and leaves room for moderate positive effects on productivity, wages, and job stability. The authors also present new country-level, general-equilibrium event studies of codetermination reforms between the 1960s and 2010s, finding no effects on aggregate economic outcomes or the quality of industrial relations. They offer three explanations for the institution’s limited impact. First, existing codetermination laws convey little authority to workers. Second, countries with codetermination laws have high baseline levels of informal worker voice. Third, codetermination laws may interact with other labor market institutions, such as union representation and collective bargaining. The article closes with a discussion of the implications for recent codetermination proposals in the United States.

This dissertation is about questions on how German institutions of industrial relations shape plant-level outcomes, and how this influences employer wage differentials. Employer wage differentials point toward imperfect labor markets in which both, employers and employees, benefit from employment rents. It puts the employer at the center of explaining wage differences and how employer characteristics influence these, over which individual employees have only limited control. Arguably, how employers and employees split these rents depend on industrial relations. The German dual model of industrial relations consists of collective bargaining at the industry level and worker co-determination through works councils at the plant level. This dissertation illuminates different aspects of industrial relations and how rent-sharing mechanisms can explain wage inequality in Germany. It does not only focus on how industrial relations shape labor market power and whether labor market power translates into the level and dispersion of employer wage premia. It also contributes to questions that explain differences in plant-level outcomes relating to industrial relations. These include the role of worker co-determination on assortative matching. It is further investigated how works councils affect plant-level reactions during economy-wide shocks. In addition, it offers new causal evidence of rent-sharing mechanisms in Germany. The insights of this dissertation are relevant for policy and economic research alike. It contributes to a better understanding of the role of organized labor in imperfect labor markets and its determinants of employer wage differentials. It approaches the role of worker co-determination from different angles that are important at times of erosion of formal organized labor but gaining interest in worker representation.

The economy is a complex system because market participants do not act independently but adjust their behavior to other agents and to the outcome which emerges from their joint actions (Arthur, 2014). Dependencies among participants can impede policy makers capabilities to influence or steer the course of the economy. Kambhu et al. (2007) argue that to influence developments in financial markets, for instance to prevent crises from spreading, there are only “coarse or indirect options” available for policy makers. Similar to crises which propagate through a complex system, interventions might result in unintended side effects which can also disseminate through the system. Thus, in a complex system, unintended consequences of policy efforts may well be the rule. Policy makers try to ward off or mitigate negative consequences for the economy and society during periods of crisis. For instance, during the Covid crisis large scale support programs for firms in Western economies were set up to avoid bankruptcies. Similarly, during the sovereign debt crisis in the Eurozone, the European Central Bank (ECB) set up large scale asset purchase programs as well as additionally longer-term refinancing operations (LTRO) which provided immediate support to financial market participants’ liquidity positions and thereby prevented a melt-down of the financial system. During these periods, immediate and abundant liquidity supply is of utmost importance. Meanwhile, crisis measures, due to their massive scale and non-specific target group, may entail unknown or unintended side effects for instance on competition among market participants, firms’ investment behavior, or changes in lending strategies and risk taking behavior of banks. Likewise, new regulatory frameworks such as the introduction of new markets can have consequences previously not thought of. For policy makers it is important to know direct effects of policy interventions but also to be aware of the possibility and impact of indirect or unexpected side effects in order to evaluate measures taken and to learn for future design of regulation or intervention.

We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. The nonlinear Phillips curve in our model arises due to a quasi-kinked demand schedule for goods produced by firms. Our model can jointly account for the modest decline in inflation during the Great Recession and the surge in inflation during the Post-Covid period. Because our model implies a stronger transmission of shocks when inflation is high, it generates conditional heteroscedasticity in inflation and inflation risk. Hence, our model can generate more sizeable inflation surges due to cost-push and demand shocks than a standard linearized model. Finally, our model implies that the central bank faces a more severe trade-off between inflation and output stabilization when inflation is high.

This paper generates a technical optimum of bank liquidity creation benchmark by tracing an efficient frontier in liquidity creation (bank intermediation) and questions why some banks are more efficient than others in such activities. Evidence reveals that medium size banks are most correlated to efficient frontier. Small (large) banks—focused on traditional banking activities—are found to be the most (least) efficient in creating liquidity in on-balance sheet items whereas large banks—involved in non-traditional activities—are found to be most efficient in off-balance sheet liquidity creation. Additionally, the liquidity efficiency of small banks is more resilient during the 2007-2008 financial crisis relative to other banks.

Bank regulators interfere with the efficient allocation of resources for the sake of financial stability. Based on this trade-off, I compare how different capital requirements affect default probabilities and the allocation of market shares across heterogeneous banks. In the model, banks‘ productivity determines their optimal strategy in oligopolistic markets. Higher productivity gives banks higher profit margins that lower their default risk. Hence, capital requirements indirectly aiming at high-productivity banks are less effective. They also bear a distortionary cost: Because incumbents increase interest rates, new entrants with low productivity are attracted and thus average productivity in the banking market decreases.

This paper offers a novel framework, combining firm operational risk, IPO pricing risk, and market risk, to model IPO failure risk. By analyzing nearly a thousand variables, we observe that prior IPO failure risk models have suffered from a major missing-variable problem. Evidence reveals several key new firm-level determinants, e.g., the volatility operating performance, the size of its accounts payable, pretax income to common equity, total short-term debt, and a few macroeconomic variables such as treasury bill rate, and book-to-market of the DJIA index. These findings have major economic implications. The total value loss from not predicting the imminent failure of an IPO is significantly lower with this proposed model compared to other established models. The IPO investors could have saved around $18billion over the period between 1994 and 2016 by using this model.

Using representative linked employer-employee data for Germany, this paper analyzes short- and long-run differences in labor market performance of workers joining start-ups instead of incumbent firms. Applying entropy balancing and following individuals over ten years, we find huge and long-lasting drawbacks from entering a start-up in terms of wages, yearly income, and (un)employment. These disadvantages hold for all groups of workers and types of start-ups analyzed. Although our analysis of different subsequent career paths highlights important heterogeneities, it does not reveal any strategy through which workers joining start-ups can catch up with the income of similar workers entering incumbent firms.

We argue that the COVID epidemic disproportionately affected the economic well-being and health of poor people. To disentangle the forces that generated this outcome, we construct a model that is consistent with the heterogeneous impact of the COVID recession on low- and high-income people. According to our model, two-thirds of the inequality in COVID deaths reflect preexisting inequality in comorbidity rates and access to quality health care. The remaining third stems from the fact that low-income people work in occupations where the risk of infection is high. Our model also implies that the rise in income inequality generated by the COVID epidemic reflects the nature of the goods that low-income people produce. Finally, we assess the health-income trade-offs associated with fiscal transfers to the poor and mandatory containment policies.

Non-clearing goods markets are an important driver of capacity utilisation and total factor productivity (TFP). The trade-off between goods prices and household search effort is central to goods market matching and therefore drives TFP over the business cycle. In this paper, I develop a New-Keynesian DSGE model with capital utilisation, worker effort, and expand it with goods market search-and-matching (SaM) to model non-clearing goods markets. I conduct a horse-race between the different capacity utilisation channels using Bayesian estimation and capacity utilisation survey data. Models that include goods market SaM improve the data fit, while the capital utilisation and worker effort channels are rendered less important compared to the literature. It follows that TFP fluctuations increase for demand and goods market mismatch shocks, while they decrease for technology shocks. This pattern increases as goods market frictions increase and as prices become stickier. The paper shows the importance of non-clearing goods markets in explaining the difference between technology and TFP over the business cycle.