Building on Prospect Theory, we apply the concept of loss aversion to the formation of inflation perceptions and test empirically for non-linearities in the inflation-perceptions relation for a panel of 10 Euro area countries. Specifically, under the assumption of loss aversion, inflation...

This paper proposes a quantile regression estimator for a heterogeneous panel model with lagged dependent variables and interactive effects. The paper adopts the Common Correlated Effects (CCE) approach proposed by Pesaran (2006) and Chudik and Pesaran (2015) and demonstrates that the extension...

We discuss some conceptual and practical issues that arise from the presence of global energy balance effects on station level adjustment mechanisms in dynamic panel regressions with climate data. The paper provides asymptotic analyses, observational data computations, and Monte Carlo...

We propose a new model in which relationship-specific supply and demand shocks are non-parametrically identified in bipartite data under mild assumptions. For example, separate heterogeneous supply shocks are identified for each firm to which a bank lends. We show that a simple estimator is...

This paper investigates the impact of income on an individual's subjective self-assessment of own health. We employ recently developed methods in the non linear panel data literature to account for the endogeneity of income and the presence of individual heterogeneity. We examine a panel data...

An interaction in a fixed effects (FE) regression is usually specified by demeaning the product term. However, this strategy does not yield a genuine within estimator. Instead, an estimator is produced that reflects unit-level differences of interacted variables whose moderators vary within...

Objective: Even in highly regulated and advanced health care markets, treatment costs and outcome quality substantially vary across facilities. Interhospital variation - particularly when it is not attributable to different patient compositions - might indicate inefficiencies in the health care...

A novel spatial autoregressive model for panel data is introduced, which incorporates multilayer networks and accounts for time-varying relationships. Moreover, the proposed approach allows the structural variance to evolve smoothly over time and enables the analysis of shock propagation in...

We develop a network-based vector autoregressive approach to uncover the interactions amongfinancial assets by integrating multiple realized measures based on high-frequency data. Undera restricted parameter structure, our approach allows the capture of cross-sectional and time ependencies...