Chemnitz Economic Research Seminar

Join Antonella Stirati in her lecture "Beyond NAIRU" as she delves into the intricacies of the concept of the Non-Accelerating Inflation Rate of Unemployment (NAIRU), dissecting its definition, exposing analytical and empirical flaws, and engaging in a critical discussion on hysteresis. Explore alternative perspectives highlighting persistent effects of aggregate demand, the conflict over income distribution and inflation, and the implications for policy-making, all while tracing connections to the theories of Godley and Tobin.

We assess the impact of mandating data-sharing in economics journals on two dimensions of research credibility: statistical significance and excess statistical significance (ESS). ESS is a necessary condition for publication selection bias. Quasi-experimental difference-in-differences analysis of 20,121 estimates published in 24 general interest and leading field journals shows that data-sharing policies have reduced reported statistical significance and the associated t-values. The magnitude of this reduction is large and of practical significance.We also find suggestive evidence that mandatory data-sharing reduces ESS and hence decreases publication bias.

There exists substantial controversy on how the energy transition towards net zero emissions affects growth and investment. Those concerned about costs of the transition including loss of competitiveness fear growth losses while those emphasizing strong investment in renewables and substitution of imported energy inputs via clean domestic energy production expect higher GDP growth. In order to address this question, we set up a small open economy model for Germany distinguishing between a non-energy sector, and an energy sector which is disaggregated into fossil and renewable energy. The simple structure allows us to highlight the main transmission mechanisms of various energy policy measures. We calibrate the model such that it can replicate important German macroeconomic ratios. In addition we use observed technology trends over the recent past, such as aggregate TFP growth, the decoupling between energy and GDP since the 90s and the rising share of renewables to parameterize the model. Based on this information we create a no-policy scenario, which serves as a baseline for two alternative balanced budget energy transition policy scenarios aiming to achieve net zero emissions in 2050. In the first policy scenario a fossil tax is introduced with revenues returned fully to households. In a second scenario the fossil fuel revenues are used entirely to subsidize renewables. We show that both scenarios are costly since they both increase the energy price and have negative effects on capital intensity in the non-energy sector. However import substitution will nevertheless increase GDP growth during the transition period because of high domestic investment needs in the renewable production sector. Irrespective of the investment and GDP impacts of the energy transition we find that the transition has a cost in terms of lower consumption. Interestingly the intertemporal consumption loss increases with policies fostering higher investment (subsidies for renewables).

Wir untersuchen das Nachhaltigkeitsmanagement von Nichtregierungsorganisationen sowie dessen Bewertung mit Hilfe eines Reifegradmodells. Für die Entwicklung des Reifegradmodells wird ein Mixed-Methods-Ansatz in einem sequenziellen Mischdesign verwendet, bestehend aus einer systematischen Literaturrecherche, qualitativen Experteninterviews, qualitativen Inhaltsanalysen, einem quantitativen Fragebogen und einer deskriptiven statistischen Datenanalyse. Wir analysieren mit Hilfe des entwickelten und teilweise evaluierten Modells den Reifegrad des Nachhaltigkeitsmanagements von 35 deutschen Nichtregierungsorganisationen.

This paper presents a political contest model analyzing strategic interactions between two presidential candidates, wherein one emerges victorious and the other assumes an oppositional role. The model captures the dynamics of traditional electoral competitions where candidates adjust their policy platforms to optimize electoral prospects, particularly driven by the pursuit of unredistributed national wealth, conceptualized as exogenous rents. The electorate is divided into a rich minority and a less affluent poor majority, with the former group exhibiting clear preferences for one candidate due to material incentives linked to promised post-election transfers. This dynamic establishes a reciprocal favor exchange system between influential societal groups and the candidates. The competition is characterized as non-cooperative, with candidates competing for majority support through customized transfer policies, aiming not only for victory but also to minimize these transfers to maximize rent extraction post-election. The equilibrium of this political contest is influenced by the size of the rich minority, candidate popularity, and the magnitude of additional transfers the rich demand for their support.

The WebSight Observatory at the University of Milano-Bicocca is a just-established research center aiming to exploit corporate websites as novel, unconventional information sources to study SMEs’ performance, as an alternative to conventional sources like financial statements, surveys, or patents. Specifically, we are working on two research lines: predicting SMEs’ innovative capacity on the one hand, and their probability to go bankrupt on the other. While the recent literature on the topic focuses on the textual content of these web-pages, we hypothesize that how the HTML code of the web-page is designed reveals something about the, otherwise unobservable, organizational and technological capabilities of an SME. In a recently submitted manuscript, we use a pool of Italian manufacturing small businesses to show that the websites of innovative SMEs are more complex and use a more updated coding style compared to those of otherwise comparable, non-innovative ones. Regarding bankruptcy prediction, our preliminary findings on a similar sample of Italian SMEs suggest that website data can complement financial statement data, with different performances across sectors. Even though more limited in their predictive power, compared to traditional data sources, we believe that corporate websites offer a constantly up-to-date, easily accessible, and available for any firm size information source that, as such, would be of interest to policymakers and managers to measure SMEs’ performance.

Central banking has significantly evolved, driven by changing economic, financial, and societal dynamics and new ideologies. Historically focused on price stability and inflation control, central banks shifted towards targeting specific inflation rates post-20th century. The 2008 global financial crisis further diverted their focus to financial stability, leading to the adoption of macroprudential tools and unconventional policies like quantitative easing. Integrating climate change considerations has recently become paramount, reflecting increased societal and environmental concerns. Using Hall’s theory, this paper explores these shifts towards green central banking, emphasizing the growing importance of environmental sustainability in central banking policies. Understanding these paradigmatic changes is crucial for future economic and environmental planning, offering vital insights for economists, policymakers, and global economic stakeholders.

Meta-analyses in economics frequently exhibit considerable overlap among primary samples. If not addressed, sample overlap leads to efficiency losses and inflated rates of false positives at the meta-analytical level. Bom and Rachinger (2020) propose a generalized-weights approach to handle sample overlap. This approach effectively approximates the correlation structure between primary estimates using information on sample sizes and overlap degrees in the primary studies. This paper demonstrates the application of the generalized-weights method to economics meta-analyses, addressing practical challenges that are likely to be encountered. We account for variations in data aggregation levels, estimation methods, and effect size metrics, among other issues. We derive explicit covariance formulas for different scenarios, evaluate the accuracy of the approximations, and employ Monte Carlo simulations to demonstrate how the method enhances efficiency and restores the false positive rate to its nominal level.

This talk will present three works on the impact of Large Language Models, in particular impact on digital public goods, labor markets, and potential to model economic behaviour. First, we will look at how ChatGPT may be diminishing the flow of publicly shared, human-generated content on platforms like Stack Overflow, crucial for programming insights. Our analysis reveals a 16% decrease in weekly contributions, threatening the future of AI training data and open knowledge sharing. This trend underscores concerns about the preservation of digital public resources and competitive markets. Second, we will delve into preliminary results on LLMs' influence on job demand, highlighting a 34% reduction in roles LLMs can replace and an 8% fall in those they can enhance. These findings contest the notion that technological progress always boosts labor demand for augmented skills, suggesting a more nuanced reality. Finally, we compare the behaviour of LLM agents interacting in markets with positive and negative feedback with those of human participants in experiments. We find that under certain parameters, behaviour is qualitatively equal and quantitatively similar.