ElasticSearch Score: 11.048721
We develop a principal-agent model of cyber-attacking with fee-paying clients who delegate security decisions to financial platforms. We derive testable implications about clients’ vulnerability to cyber attacks and about the fees charged.
ElasticSearch Score: 11.0034
We measure systemic risk in the network of financial market infrastructures (FMIs) as the probability that two or more FMIs have a large credit risk exposure to the same FMI participant.
ElasticSearch Score: 10.927417
Standard new trade models depict producers as heterogeneous in total factor productivity. In this paper, I adapt the Eaton and Kortum (2002) model of international trade to incorporate tradable intermediate goods and producer heterogeneity in value-added productivity.
ElasticSearch Score: 10.787354
We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does.
ElasticSearch Score: 10.784592
The present paper shows that, everything else equal, some transactions to transfer portfolio credit risk to third-party investors increase the insolvency risk of banks. This is particularly likely if a bank sells the senior tranche and retains a sufficiently large first-loss position.
ElasticSearch Score: 10.676266
Multi-stage production is widely recognized as an important feature of the modern global economy. This feature has been incorporated into many state-of-the-art quantitative trade models, and has been shown to deliver significant additional gains from international trade.
ElasticSearch Score: 10.671299
Should managers be paid in stock options if they provide stock-market participants with information about the firm? This paper studies how firm owners trade off the benefit of stock-price incentives and better-informed market participants against the cost of potential stock-price manipulation.
ElasticSearch Score: 10.509641
We estimate the effects of economic uncertainty on time use and discuss its macroeconomic implications. We develop a model to demonstrate that substitution between market and non-market work provides an additional insurance margin to households, weakening precautionary savings and labour supply and lowering aggregate demand, ultimately amplifying the contractionary effects of uncertainty.
ElasticSearch Score: 10.389395
Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.
ElasticSearch Score: 10.210008
This paper relaxes the Bayesian Nash equilibrium (BNE) assumption commonly imposed in empirical discrete choice games with incomplete information. Instead of assuming that players have unbiased/correct expectations, my model treats a player’s belief about the behavior of other players as an unrestricted unknown function. I study the joint identification of belief and payoff functions.