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Working Paper
Optimizing Credit Gaps for Predicting Financial Crises: Modelling Choices and Tradeoffs
Credit gaps are good predictors for financial crises, and banking regulators recommend using them to inform countercyclical capital buffers for banks. Researchers typically create credit gap measures using trend-cycle decomposition methods, which require many modelling choices, such as the method used, and the smoothness of the underlying trend. Other choices hinge on the tradeoffs implicit in how gaps are used as early warning indicators (EWIs) for predicting crises, such as the preference over false positives and false negatives. We evaluate how the performance of credit-gap-based EWIs for ...
Working Paper
Growth and Welfare Gains from Financial Integration Under Model Uncertainty
We build a robustness (RB) version of the Obstfeld (1994) model to study the effects of financial integration on growth and welfare. Our model can account for the empirically observed heterogeneity in the relationship between growth and volatility for different countries. The calibrated model shows that financial integration leads to significantly larger gains in growth and welfare for advanced countries than developing countries, with some developing countries experiencing growth and welfare loss in financial integration. Our analytical solutions help uncover the key mechanisms by which this ...
Working Paper
Production and Inventory Dynamics under Ambiguity Aversion
We propose a production-cost smoothing model with Knightian uncertainty due to ambiguity aversion to study the joint behavior of production, inventories, and sales. Our model can explain four facts that previous studies find difficult to account for simultaneously: (i) the high volatility of production relative to sales, (ii) the low ratio of inventory-investment volatility to sales volatility, (iii) the positive correlation between sales and inventories, and (iv) the negative correlation between the inventory-to-sales ratio and sales. We find that the stock-out avoidance motive (Kahn 1987) ...
Working Paper
A Robust Method for Microforecasting and Estimation of Random Effects
We propose a method for forecasting individual outcomes and estimating random effects in linear panel data models and value-added models when the panel has a short time dimension. The method is robust, trivial to implement and requires minimal assumptions. The idea is to take a weighted average of time series- and pooled forecasts/estimators, with individual weights that are based on time series information. We show the forecast optimality of individual weights, both in terms of minimax-regret and of mean squared forecast error. We then provide feasible weights that ensure good performance ...