The Unassuming Economist

From a paper by Anita Szymanska, and Małgorzata Zielenkiewicz:

“Growing income inequality currently poses a significant threat to sustainable development.
Hence, it is important to monitor this phenomenon, in particular to identify determinants favouring
the deepening of income inequality. One of the significant determinants in this respect is the declining
labour income share in national income. The theoretical justification of the presumption of a negative
relationship between the share of labour in the national income and income inequality has strong
logical foundations. Existing studies indicate, however, some ambiguities as to the strength of this
relationship and the existence of various factors cancelling this relationship. The following study
attempts to verify the existence, direction, and intensity of the relationship between the labour
income share and income inequality in a relatively homogeneous group of 33 OECD countries
studied in 1990–2018. The main hypothesis verified in the study is the assumption that there is
a negative relationship between labour share and income inequality. Our results show that the
relationship between the share of employees’ and self-employed workers’ income in the national
income and income inequality at the general level (i.e., in a group study of 33 countries in total) exists,
is negative and statistically significant, but has a very small share in explaining the behaviour of
income inequality.”

From a paper by Shuang Ma, Baoling Mo, and Xiaoyu Meng:

“We examine the impact of minimum wage increases on labor self-funded training by first constructing a theoretical model that explores the effects under both perfectly and imperfectly competitive market conditions. We then empirically analyze the impact using data on training enterprise registrations and household spending on training. Theoretically, we find an increase in the minimum wage is expected to suppress demand for low-skilled labor, leading affected workers to engage in self-funded training to compete for a limited number of job positions. Empirically, a minimum wage increase significantly boosts the number of newly registered training enterprises and household expenditures on skill training. Mechanism analysis reveals that a higher minimum wage increases labor costs for enterprises, leading them to raise skill requirements during recruitment, thereby encouraging job market participants to pursue self-funded skill training.”

From a paper by Ullrich Heilemann and Roland Schuhr:

“Okun’s misery index (MI), the sum of unemployment rate and inflation rate, is a popular measure of the state of the economy and thus of (macro) ” Economic Discomfort” as well as of government per-formance. We calculate the MI and some augmentations for Germany (until 1990: West Germany) for the period 1951–2021 and test them against a survey-based indicator of government performance (“ZDF-Politbarometer-Index”). The results support Okun’s choice of variables, but reject its augmenta-tion by the growth rate and the deficit ratio. Just as importantly, the effect of unemployment is almost twice as large as that of inflation, and both change considerably over time, as stability tests show. In assessing the performance of governments, MI rankings differ from those of their augmentations. Since the mid-1970s, however, the differences are limited. Barro’s Misery Index, a comparative ap-proach to assessing governments that is an alternative to MI, reaches opposite judgments than MI, but lacks empirical support. The implications for policymakers are both sobering and reassuring: as policy simulations and implied Phillips type trade-offs reveal, the sensitivity of MIs to macroeconomic policy is very low. This may not only hold for Germany given similar international evidence on MIs. The fact that the MI covers the two main macroeconomic objectives, is based on the latest official data, easy to calculate and internationally comparable makes Okun’s Misery Index a useful indicator of Economic Discomfort for Germany as well.”

From a paper by Nicolò Fraccaroli, Vincent Arel-Bundock, and Mark Blyth:

“The 2021 debate over the causes of inflation was dominated by contrasting narratives around the drivers of, and solutions to, rising prices. But how these ideas did or did not penetrate central banks, the politically independent institutions responsible for keeping prices stable, remains unclear. In this paper we investigate how the Bank of England, European Central Bank, and Federal Reserve discussed and deployed specific inflation narratives over time in their attempts to diagnose and treat the inflation of the period. We focus on four narratives that identify the main drivers of inflation in (1) excessive public spending, (2) higher wages in the labour market than warranted by productivity, (3) supply side disruptions to critical markets such as energy, and (4) corporate profit margin expansion. We use a large language model to tag central banks’ speeches with relevant narratives at sentence level, which allows us to quantify how much each central bank discussed each narrative. The results shed new light on how these three central banks interfaced with the recent debate around inflation.”

From a paper by Jordan Kjosevski:

“This study examines the impact of venture capital (VC) investments in artificial intelligence (AI) on unemployment rates across 27 EU member states, distinguishing between old and new EU countries. Utilizing annual data from 2012 to 2023, we explore whether AI investments significantly influence unemployment and how these effects vary between advanced economies and those still developing their digital infrastructure. Employing the two-step system Generalized Method of Moments (GMM), we effectively address endogeneity and the dynamic nature of unemployment, making this method well-suited for our panel dataset covering 27 countries over 12 years. Our findings reveal that AI investments correlate with higher unemployment in old EU countries while positively impacting job creation in new EU member states. Based on these results, we recommend targeted policies to enhance AI adoption, improve digital infrastructure, and promote workforce training, particularly in new member states, to optimize the benefits of AI investments and mitigate potential job displacement.”