Title: Monetary policy, information, and country risk shocks in the euro area.

Title: Top Flight - How responsive are top earners to tax rates?

Title: Optimally informative monetary policy

Title: BETWEEN TWO WORLDS: EDUCATION-OCCUPATION MISMATCH FOR SECOND-GENERATION IMMIGRANTS IN THE UK

Authors

Subhasish Dey, University of Warwick

Mahima Kapoor, University of Warwick

Anirban Mukherjee, University of Calcutta

Abstract:

This study assesses the quality of occupations that second-generation immigrants are employed in relative to natives in the UK. Based on the concept of education-occupation mismatch, we investigate whether the utilization of workers’ skills is commensurate with those required under the job. Using the multinomial logistic regression model to fit data from the Understanding Society: UK Household Longitudinal Study, we show that second-generation immigrants have a higher probability of being over-educated than natives and evaluate the mechanisms driving the results. We further explore the presence of double penalty along the overlap of legal and social identities. The findings direct attention towards the unique context of second-generation immigrants and inform policy efforts.

Title: On the Inconsistency of Cluster-Robust Inference and How Subsampling Can Fix It

Abstract: Conventional methods of cluster-robust inference are inconsistent in the presence of unignorably large clusters. We formalize this claim by establishing a necessary and sufficient condition for the consistency of the conventional methods. We find that this condition for the consistency is rejected for a majority of empirical research papers. In this light, we propose a novel score subsampling method that achieves uniform size control over a broad class of data generating processes, covering that fails the conventional method. Simulation studies support these claims. With real data used by an empirical paper, we showcase that the conventional methods conclude significance while our proposed method concludes insignificance.

Title: Social Influence in Online Reviews: Evidence from the Steam Store

Abstract: How good are reviews as signals of product quality for consumers? Using a data-set derived from the popular Steam gaming platform I investigate the ‘priming’ of quality judgements as based on pre-existing consumer assessments. A policy reform on Steam in 2019 changed the average level of exposure to previous consumer quality ratings, with this randomly occurring within a game and reviewer’s life cycle. I find that removing the exposure of a reviewer to a product’s average rating leads to a 35% drop in the dependency of their review on such a rating. This is not driven by selection effects, and is robust to a wide range of alternate specifications and measures. The effect is heavily asymmetric: negativity compounds to inflate the gap between poorly-rated and well rated games. This is driven by users who are less experienced both within and across games. Finally, using estimates of owner data, I run a simple structural model of game choice based on rating. A 1% increase to product rating is equivalent to a 2.5 dollar sale price reduction, suggesting this effect has large implications for buyers and sellers.

Title to be advised.

Title to be advised.

Title to be advised.

Title to be advised.

Title to be advised.

Title to be advised.

Title to be advised.

Title to be advised.