flora lutz

We propose a small open economy model where agents borrow internationally and invest in liquid foreign assets to insure against liquidity shocks, which temporarily shut out the economy of short-term credit markets. Due to a pecuniary externality individual agents overborrow and hold too little liquid assets relative to a social planner. This inefficiency rationalizes macroprudential policy intervention in the form of reserve accumulation at the central bank to stabilize trade and the real exchange rate. Our model quantitatively matches the depreciation of the real exchange rate and contractions in output, gross trade flows, and foreign reserve holdings during Sudden Stops.

Publications

Financial Stability Regulation under Liquidity and Borrowing Externalities

Journal of the European Economics Association (2021): 19(2),1000-1040, with Paul Pichler (University of Vienna)

We study financial stability regulation in an environment with pecuniary externalities and where banks face both a liability choice (between private money creation and long-term borrowing) and an asset choice (between liquid and illiquid investments). Return risk on illiquid assets gives rise to liquidity risk, because banks that learn to have low future returns find themselves unable to roll over “money-like” debt. Privately optimal borrowing and investment decisions by banks lead, in general, to socially inefficient outcomes. The nature of inefficiency depends critically on the degree to which liquidity risk is systemic: When risk is highly systemic, banks hold the socially optimal amount of liquid assets, but create an excessive amount of money and overinvest in risky assets; when risk is not highly systemic, banks hold too little liquidity, create insufficient private money, and underinvest in risky assets. Quantity- and price-based regulations to address the identified inefficiencies are discussed.

Sudden Stops and Reserve Accumulation in the Presence of International Liquidity Risk

Journal of International Economics (2023): Volume 141, with Leopold Zessner-Spitzenberg (Humboldt University, Berlin)

We propose a small open economy model where agents borrow internationally and invest in liquid foreign assets to insure against liquidity shocks, which temporarily shut out the economy of short-term credit markets. Due to a pecuniary externality individual agents overborrow and hold too little liquid assets relative to a social planner. This inefficiency rationalizes macroprudential policy intervention in the form of reserve accumulation at the central bank to stabilize trade and the real exchange rate. Our model quantitatively matches the depreciation of the real exchange rate and contractions in output, gross trade flows, and foreign reserve holdings during Sudden Stops.

Macroprudential Policy and Exchange Rates in Financially Fragile Economies

IMF Working Paper (2023): WP/23/51

I provide an integrated analysis of monetary and macroprudential policies in a model economy featuring a financial friction and a nominal wage rigidity. In this set-up, the monetary authority faces a trade-off between macroeconomic and financial stability: While expansionary counter-cyclical monetary policy prevents involuntary unemployment, it also amplifies an inefficient reallocation of capital across sectors. The main contribution of the analysis is threefold: First it highlights a novel channel through which monetary policy can impact financial stability. Second, it shows that, by itself, monetary policy can significantly mitigate the wedge between the constrained efficient and the competitive allocation. Third, regardless of the availability of macroprudential tools, stabilizing demand is usually not optimal for monetary policy.

Work in Progress

Predicting the use of IMF Resources: A Machine Learning Approach

joint with S. He, J. Leslie, T. Batsuuren and R. Hu [Forthcoming IMF Working Paper]

This study applies state-of-the-art machine learning (ML) techniques to forecast IMF program requests by countries, analyzes the ML prediction results relative to traditional econometric approaches, explores non-linear relationships among predictors indicative of IMF program requests, and evaluates model robustness with regard to different feature sets and time periods. ML models consistently outperform traditional methods in out-of-sample prediction of new IMF arrangements with key predictors that align well with the literature and show consensus across different algorithms. The analysis underscores the importance of incorporating a variety of external, fiscal, real, and financial features as well as institutional factors like membership in regional financial arrangements. The findings also highlight the varying influence of data processing choices such as feature selection, sampling techniques, and missing data imputation on the performance of different ML models and therefore indicate the usefulness of a flexible, algorithm-tailored approach. Additionally, the results reveal that models that are most effective in near and medium-term predictions may tend to underperform over the long term, thus illustrating the need for regular updates or more stable – albeit potentially near-term suboptimal – models when frequent updates are impractical.

The Public Perception of Canada's Investment Climate

joint with Yuanchen Yang [Forthcoming IMF Working Paper]

Housing Booms and Productivity

joint with Yuanchen Yang and Lucy Liu [Forthcoming IMF Working Paper]

Variation Margins, Fire Sales and Liquidity