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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.

Macroeconomics --- Economics: General --- Labor --- Finance: General --- Money and Monetary Policy --- Externalities --- Employment --- Unemployment --- Wages --- Intergenerational Income Distribution --- Aggregate Human Capital --- Aggregate Labor Productivity --- Financial Markets and the Macroeconomy --- Monetary Policy --- Policy Objectives --- Policy Designs and Consistency --- Policy Coordination --- Portfolio Choice --- Investment Decisions --- Price Level --- Inflation --- Deflation --- Economic & financial crises & disasters --- Economics of specific sectors --- Labour --- income economics --- Finance --- Monetary economics --- Asset prices --- Prices --- Monetary expansion --- Monetary policy --- Liquidity --- Asset and liability management --- Asset liquidity --- Currency crises --- Informal sector --- Economics --- Economic theory --- Economic policy --- Income economics

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This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML prediction results relative to traditional econometric approaches, explores non-linear relationships among predictors indicative of IMF-supported programs, 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-supported 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 financing 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.

Capital and Ownership Structure --- Computer Programs: General --- Crisis management --- Currency crises --- Data capture & analysis --- Data Collection and Data Estimation Methodology --- Data Processing --- Data processing --- Diffusion Processes --- Early warning systems --- Economic & financial crises & disasters --- Economic and financial statistics --- Economic assistance --- Economics of specific sectors --- Economics --- Economics: General --- Electronic data processing --- Emergency assistance --- Exports and Imports --- Financial Crises --- Financial crises --- Financial Risk and Risk Management --- Financial Risk Management --- Financing Policy --- Forecasting and Other Model Applications --- Foreign Aid --- Foreign aid --- General Outlook and Conditions --- Global financial crisis of 2008-2009 --- Global Financial Crisis, 2008-2009 --- Goodwill --- Informal sector --- Intelligence (AI) & Semantics --- International economics --- Machine learning --- Macroeconomic Aspects of International Trade and Finance: Forecasting and Simulation --- Macroeconomics --- Neural Networks and Related Topics --- Studies of Particular Policy Episodes --- Technological Change: Choices and Consequences --- Technology --- Value of Firms