In this paper, we consider random dynamical systems formed by concatenating maps acting on the unit interval $[0,1]$ in an independent and identically distributed (i.i.d.) fashion. Considered as a stationary Markov process, the random dynamical system possesses a unique stationary measure $\nu $. We consider a class of non-square-integrable observables $\phi $, mostly of form $\phi (x)=d(x,x_0)^{-{1}/{\alpha }}$, where $x_0$ is a non-recurrent point (in particular a non-periodic point) satisfying some other genericity conditions and, more generally, regularly varying observables with index $\alpha \in (0,2)$. The two types of maps we concatenate are a class of piecewise $C^2$ expanding maps and a class of intermittent maps possessing an indifferent fixed point at the origin. Under conditions on the dynamics and $\alpha $, we establish Poisson limit laws, convergence of scaled Birkhoff sums to a stable limit law, and functional stable limit laws in both the annealed and quenched case. The scaling constants for the limit laws for almost every quenched realization are the same as those of the annealed case and determined by $\nu $. This is in contrast to the scalings in quenched central limit theorems where the centering constants depend in a critical way upon the realization and are not the same for almost every realization.

I develop a dynamic model to investigate how labor mobility impacts firms’ decisions. In the model, firms make investment and financing decisions, hire labor with different skill and mobility levels, and set wages through bargaining. The model predicts that, in response to an increase in labor mobility, high-skill firms operate with lower financial leverage, become less responsive to investment opportunities, and invest at lower rates, while low-skill firms remain unaffected. I confirm these predictions in the data using shocks to workers’ mobility across firms. The results are useful in understanding the effects of labor mobility changes driven by government policies or technological shocks, such as the rise of remote work.

This study analyzes meetings of firms with policymakers at the European Commission (EC). Meetings with Commissioners are associated with positive abnormal equity returns for U.S. firms. Firms of the European Union (EU), however, do not experience significant value increases. We identify regulatory outcomes as a channel that can rationalize this difference in value effects of political access. U.S. firms with meetings are more likely to receive favorable decisions in their EC merger decisions than their EU peers. The results suggest that cross-border political access can alleviate uncertainties and alleged discriminatory behavior of regulators in foreign markets.

As an emerging science and technology (EST), stem cell therapy presents a highly dynamic and complex landscape, posing significant challenges for the Chinese central government and requiring substantial policy learning. Delving into the realm beyond the traditional literature on Chinese government's policy learning, which primarily focuses on conventional policy areas and local government experiments, this article examines how the technical and interest complexities, along with the fragmented authoritarian structure of central departments, influence policy learning in the field of stem cell therapy. The findings reveal a recurring pendulum swing pattern, wherein top decision makers direct central departments to engage in multiple rounds of policy swings, navigating between developmental objectives and regulatory objectives.

Use of both cannabis and synthetic cannabinoids has been regularly linked to the development of psychotic illness. Thus, semisynthetic cannabinoids such as hexahydrocannabinol (HHC), which have a similar neurobiological profile to delta-9-THC, may also be expected to lead to psychotic illness. However, no such relationship has yet been reported in scientific literature. HHC is readily available online and in many vape shops in Ireland. Here, we present two cases of psychotic illness which appear to have been precipitated by use of legally purchased HHC and discuss its psychotogenic role and factors linked to its current widespread availability.

We test the neutrality of nominal interest rates taking advantage of recent advances in quantitative financial history using the Schmelzing (2022) global nominal interest rate and inflation rate series (across eight centuries), for France, Germany, Holland, Italy, Japan, Spain, the United Kingdom, and the USA. We pay attention to the integration and cointegration properties of the variables and use the bivariate autoregressive methodology proposed by King and Watson (1997). We argue that meaningful long-run neutrality tests can be performed only for three countries—Japan, Spain, and the United Kingdom—and we find no evidence consistent with the neutrality of nominal interest rates.

We present novel cross-sectional and longitudinal claim count models for vehicle insurance built upon the combinedd actuarial neural network (CANN) framework proposed by Wüthrich and Merz. The CANN approach combines a classical actuarial model, such as a generalized linear model, with a neural network. This blending of models results in a two-component model comprising a classical regression model and a neural network part. The CANN model leverages the strengths of both components, providing a solid foundation and interpretability from the classical model while harnessing the flexibility and capacity to capture intricate relationships and interactions offered by the neural network. In our proposed models, we use well-known log-linear claim count regression models for the classical regression part and a multilayer perceptron (MLP) for the neural network part. The MLP part is used to process telematics car driving data given as a vector characterizing the driving behavior of each insured driver. In addition to the Poisson and negative binomial distributions for cross-sectional data, we propose a procedure for training our CANN model with a multivariate negative binomial specification. By doing so, we introduce a longitudinal model that accounts for the dependence between contracts from the same insured. Our results reveal that the CANN models exhibit superior performance compared to log-linear models that rely on manually engineered telematics features.

This article analyzes tweets in the Turkish language from November 2020 to May 2021 in which Kurds are explicitly mentioned that feature negative animalization directed toward Kurds and pro-Kurdish organizations. It systematically compares ways of animalization attribution, to what entities the animalization is attributed mostly, and the attributors (actors) of animalization. First, it argues that animalizing dehumanization directed at Kurds in the data set principally occurs for attributing the lack of four human traits: agency, civility, morality, and rationality. Second, it shows in what different ways the lack of these traits is attributed to Kurdish people in general and to major pro-Kurdish groups such as HDP (the largest pro-Kurdish legal political party) and PKK (the largest pro-Kurdish armed group). Finally, it discloses three main political networks among Twitter users within the data set and characterizes how negative animal references to Kurds, pro-Kurdish groups, and each other were used by these actors. Thus, this research seeks to establish a framework to study other ethnic conflicts from the perspective of animalization and invites further research on whether the trends that were found imply a general tendency around the world.

The National Environmental Isotope Facility (NEIF) Radiocarbon Laboratory at the Scottish Universities Environmental Research Centre (SUERC) performs radiocarbon measurement of a wide range of sample matrices for applications in environmental research. Radiocarbon is applied to palaeoenvironmental, palaeoceanographic, and palaeoclimatic investigations, as well as work to understand the source, fate, turnover, and age of carbon in the modern carbon cycle. The NEIF Radiocarbon Laboratory supports users in the development and deployment of novel sampling techniques and laboratory approaches. Here, we give an overview of methods and procedures used by the laboratory to support the field collection, laboratory processing, and measurement of samples. This includes in-house development of novel and/or specialized methods and approaches, such as field collection of CO2 and CH4, hydropyrolysis, and ramped oxidation. The sample types covered include organic remains (e.g., plant material, peat, wood, charcoal, proteins), carbonates (e.g., speleothems, foraminifera, mollusc shell, travertine), waters (dissolved organic and inorganic carbon), gases (CO2 and CH4), soils and sediments (including sub-fractions).

Let $K\subset {\mathbb {R}}^d$ be a self-similar set generated by an iterated function system $\{\varphi _i\}_{i=1}^m$ satisfying the strong separation condition and let f be a contracting similitude with $f(K)\subseteq K$. We show that $f(K)$ is relatively open in K if all $\varphi _i$ share a common contraction ratio and orthogonal part. We also provide a counterexample when the orthogonal parts are allowed to vary. This partially answers a question of Elekes, Keleti and Máthé [Ergod. Th. & Dynam. Sys. 30 (2010), 399–440]. As a byproduct of our argument, when $d=1$ and K admits two homogeneous generating iterated function systems satisfying the strong separation condition but with contraction ratios of opposite signs, we show that K is symmetric. This partially answers a question of Feng and Wang [Adv. Math. 222 (2009), 1964–1981].