Working Papers
2020
January 17, 2020
Monetary Policy Is Not Always Systematic and Data-Driven: Evidence from the Yield Curve
Description: Does monetary policy react systematically to macroeconomic innovations? In a sample of 16 countries – operating under various monetary regimes – we find that monetary policy decisions, as expressed in yield curve movements, do react to macroeconomic innovations and these reactions reflect the monetary policy regime. While we find evidence of the primacy of the price stability objective in the inflation targeting countries, links to inflation and the output gap are generally weaker and less systematic in money-targeting and multiple-objective countries.
January 16, 2020
Crime and Output: Theory and Application to the Northern Triangle of Central America
Description: This paper presents a structural model of crime and output. Individuals make an occupational choice between criminal and legal activities. The return to becoming a criminal is endogenously determined in a general equilibrium together with the level of crime and economic activity. I calibrate the model to the Northern Triangle countries and conduct several policy experiments. I find that for a country like Honduras crime reduces GDP by about 3 percent through its negative effect on employment indirectly, in addition to direct costs of crime associated with material losses, which are in line with literature estimates. Also, the model generates a non-linear effect of crime on output and vice versa. On average I find that a one percent increase in output per capita implies about ½ percent decline in crime, while a decrease of about 5 percent in crime leads to about one percent increase in output per capita. These positive effects are larger if the initial level of crime is larger.
January 3, 2020
Debt Is Not Free
Description: With public debt soaring across the world, a growing concern is whether current debt levels are a harbinger of fiscal crises, thereby restricting the policy space in a downturn. The empirical evidence to date is however inconclusive, and the true cost of debt may be overstated if interest rates remain low. To shed light into this debate, this paper re-examines the importance of public debt as a leading indicator of fiscal crises using machine learning techniques to account for complex interactions previously ignored in the literature. We find that public debt is the most important predictor of crises, showing strong non-linearities. Moreover, beyond certain debt levels, the likelihood of crises increases sharply regardless of the interest-growth differential. Our analysis also reveals that the interactions of public debt with inflation and external imbalances can be as important as debt levels. These results, while not necessarily implying causality, show governments should be wary of high public debt even when borrowing costs seem low.
2019
December 27, 2019
Autonomous Factor Forecast Quality: The Case of the Eurosystem
Description: The publication of liquidity forecasts can be understood as part of central banks’ push toward greater transparency regarding monetary policy implementation. However, the advantages of transparency can only be realized if the information provided is accurate and reliable. This paper (1) provides an overview of the international practice of publishing the forecasts; (2) proposes and implements a framework to evaluate the accuracy and reliability of forecasts using the long history of Eurosystem forecasts as a case study; and (3) analyzes the Eurosystem forecast errors to determine the factors influencing forecast quality. A supporting factor for a high-quality forecast is the contemporaneousness of the information used, whereas money market segmentation can weigh on forecast quality.
December 27, 2019
Post-Crisis Changes in Global Bank Business Models: A New Taxonomy
Description: The Global Financial Crisis unleashed changes in the operating and regulatory environments for large international banks. This paper proposes a novel taxonomy to identify and track business model evolution for the 30 Global Systemically Important Banks (G-SIBs). Drawing from banks’ reporting, it identifies strategies along four dimensions –consolidated lines of business and geographic orientation, and the funding models and legal entity structures of international operations. G-SIBs have adjusted their business models, especially by reducing market intensity. While G-SIBs have maintained international orientation, pressures on funding models and entity structures could affect the efficiency of capital flows through the bank channel.
December 27, 2019
Innovate to Lead or Innovate to Prevail: When do Monopolistic Rents Induce Growth?
Description: This paper extends the Schumpeterian model of creative destruction by allowing followers’ cost of innovation to increase in their technological distance from the leader. This assumption is motivated by the observation the more technologically ad- vanced the leader is, the harder it is for a follower to leapfrog without incurring extra cost for using leader’s patented knowledge. Under this R&D cost structure, leaders innovate to increase their technological advantage so that followers will eventually stop innovating, allowing leadership to prevail. A new steady state then emerges featuring both leaders and followers innovating in few industries with low aggregate growth.
December 27, 2019
The Role of Board Oversight in Central Bank Governance: Key Legal Design Issues
Description: This paper discusses key legal issues in the design of Board Oversight in central banks. Central banks are complex and sophisticated organizations that are challenging to manage. While most economic literature focuses on decision-making in the context of monetary policy formulation, this paper focuses on the Board oversight of central banks—a central feature of sound governance. This form of oversight is the decision-making responsibility through which an internal body of the central bank—the Oversight Board—ensures that the central bank is well-managed. First, the paper will contextualize the role of Board oversight into the broader legal structure for central bank governance by considering this form of oversight as one of the core decision-making responsibilities of central banks. Secondly, the paper will focus on a number of important legal design issues for Board Oversight, by contrasting the current practices of the IMF membership’s 174 central banks with staff’s advisory practice developed over the past 50 years.
December 27, 2019
Completing the Market: Generating Shadow CDS Spreads by Machine Learning
Description: We compared the predictive performance of a series of machine learning and traditional methods for monthly CDS spreads, using firms’ accounting-based, market-based and macroeconomics variables for a time period of 2006 to 2016. We find that ensemble machine learning methods (Bagging, Gradient Boosting and Random Forest) strongly outperform other estimators, and Bagging particularly stands out in terms of accuracy. Traditional credit risk models using OLS techniques have the lowest out-of-sample prediction accuracy. The results suggest that the non-linear machine learning methods, especially the ensemble methods, add considerable value to existent credit risk prediction accuracy and enable CDS shadow pricing for companies missing those securities.
December 27, 2019
Do Fiscal Rules Cause Fiscal Discipline Over the Electoral Cycle?
Description: This paper estimates the causal effect of fiscal rules on political budget cycles in a sample of 67 developing countries over the period 1985–2007. We exploit the geographical pattern in the adoption of fiscal rules to isolate an exogenous source of variation in the adoption of national fiscal rules. Based on a diffusion argument, we use the number of other countries in a given subregion that have fiscal rules in place to predict the probability of having them at the country level. We find that in election years with fiscal rules in place, public consumption is reduced by 1.6 percentage point of GDP as compared to election years without these rules. This impact is equivalent to a reduction by a third of the volatility of public consumption in our sample. Furthermore, the effectiveness of these rules depends on their type, their institutional design, whether they have been in place for a long time and finally on the degree of competitiveness of elections.
December 27, 2019
Sovereign Asset and Liability Management in Emerging Market Countries: The Case of Uruguay
Description: This paper provides an overview of the strategic and operational issues as well as institutional challenges, related to the implementation of the Sovereign Asset and Liability Management (SALM) approach. Application of an SALM framework allows the authorities to identify and monitor sovereign exposure mismatches; increase resilience to foreign currency and interest rate risks; and thus, strengthen financial stability; and implement more cost-effective management of the public-sector debt. The analysis is based on emerging market (EM) countries and illustrated by the experience of Uruguay, using data as of end-2017.