Annual Energy Outlook

This paper examines the relationship between low interests maintained by advanced economy central banks and credit booms in emerging economies. In a model with crossborder banking, low funding rates increase credit supply, but the initial shock is amplified through the risk-taking channel of monetary policy where greater risk-taking interacts with dampened measured risks that are driven by currency appreciation to create a feedback loop. In an empirical investigation using VAR analysis, we find that expectations of lower short-term rates dampen measured risks and stimulate cross-border banking sector capital flows.

Capital Flows and the Risk-Taking Channel of Monetary Policy

World Population Prospects, the 2010 Revision: Estimation and projection methodology

A common assumption in the academic literature and in the actual supervision of banking systems worldwide is that franchise value plays a key role in limiting bank risk-taking. As the underlying source of franchise value is assumed to be market power, reduced competition has been considered to promote banking stability. Boyd and De Nicolo (2005) propose an alternative view where concentration in the loan market could lead to increased borrower debt loads and a corresponding increase in loan defaults that undermine bank stability. Martinez-Miera and Repullo (2007) encompass both approaches by proposing a nonlinear relationship between competition and bank risk-taking. Using unique datasets for the Spanish banking system, we examine the empirical nature of that relationship. After controlling for macroeconomic conditions and bank characteristics, we find that standard measures of market concentration do not affect the ratio of non-performing commercial loans (NPL), our measure of bank risk. However, using Lerner indexes based on bank-specific interest rates, we find a negative relationship between loan market power and bank risk. This result provides evidence in favor of the franchise value paradigm.

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How Does Competition Impact Bank Risk-Taking?

This paper offers an empirical evaluation of the output contribution of infrastructure. Drawing from a large data set on infrastructure stocks covering 88 countries and spanning the years 1960-2000, and using a panel time-series approach, the paper estimates a long-run aggregate production function relating GDP to human capital, physical capital, and a synthetic measure of infrastructure given by the first principal component of infrastructure endowments in transport, power, and telecommunications. Tests of the cointegration rank allowing it to vary across countries reveal a common rank with a single cointegrating vector, which is taken to represent the long-run production function. Estimation of its parameters is performed using the pooled mean group estimator, which allows for unrestricted short-run parameter heterogeneity across countries while imposing the (testable) restriction of long-run parameter homogeneity. The long-run elasticity of output with respect to the synthetic infrastructure index ranges between 0.07 and 0.10. The estimates are highly significant, both statistically and economically, and robust to alternative dynamic specifications and infrastructure measures. There is little evidence of long-run parameter heterogeneity across countries, whether heterogeneity is unconditional, or conditional on their level of development, population size, or infrastructure endowments.

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Is infrastructure capital productive ? a dynamic heterogeneous approach

We document the cyclical dynamics in the balance sheets of US leveraged financial intermediaries in the post-war period. Leverage has contributed more than equity to fluctuations in total assets. All three variables are several times more volatile than GDP. Leverage has been positively correlated with assets and (to a lesser extent) GDP, and negatively correlated with equity. These findings are robust across financial subsectors. We then build a general equilibrium model with banks subject to endogenous leverage constraints, and assess its ability to replicate the facts. In the model, banks borrow in the form of collateralized risky debt. The presence of moral hazard creates a link between the volatility in bank asset returns and bank leverage. We find that, while standard TFP shocks fail to replicate the volatility and cyclicality of leverage, volatility shocks are relatively successful in doing so.

Bank Leverage Cycles

The aim of this paper is to analyse the impact of the so-called "shale oil revolution" on oil prices and economic growth. We employ a general equilibrium model of the world oil market in which Saudi Arabia is the dominant firm, with the rest of the producers as a competitive fringe. Our results suggest that most of the expected increase in US oil supply due to the shale oil revolution has already been incorporated into prices and that it will produce an additional increase of 0.2 percent in the GDP of oil importers in the period 2010-2018. We also employ the model to analyse the collapse in oil prices in the second half of 2014 and conclude that it was mainly due to positive unanticipated supply shocks.

/pdf/quantitative-effects-of-the-shale-oil-revolution-ddk59t8s87.pdf

Quantitative Effects of the Shale Oil Revolution

In this paper we document two features that have made Saudi Arabia dierent from other oil producers. First, it has typically maintained ample spare capacity. Second, its production has been quite volatile even though it has witnessed few domestic shocks. These features can be rationalised in a general equilibrium model in which the oil market is modelled as a dominant producer with a competitive fringe. We show that the net welfare eect of oil taris on consumers is null. The reason is that Saudi Arabias's monopolistic rents fall entirely on fringe producers. Saudi Arabia is one of the largest players in the global oil market: it produces more than a tenth of the world's oil output and owns a quarter of the world's proven reserves. The Kingdom is also a key OPEC member, typically playing a central role in OPEC's decision-making. Indeed, authors such as Mabro (1975) have gone so far as to claim that 'OPEC is Saudi Arabia'. And according to Adelman (1995), 'the Saudis have acted as what they are: the leading …rm in the world oil market'. Are these claims exaggerations? In this paper we document two features that have made Saudi Arabia dierent from the rest of producers. First, it systematically restricts its production. In fact, its spare capacity is much larger than the aggregate spare capacity of the rest of world producers. Second, its production is quite volatile. The variance of Saudi oil output has been very high compared to that of the rest of producers, even though the Kingdom itself has witnessed few domestic shocks aecting oil production directly. We show that one can rationalise the behaviour of Saudi Arabia as that of a dominant producer with competitive fringe. In the spirit of Salant (1976), we build an industrial organization model into a general equilibrium framework, assuming that the dominant supplier internalises a la Stackelberg the behavioural � Anton Nakov thanks the European Central Bank for its hospitality during the …rst drafts of this paper. The views expressed here are those of the authors and do not necessarily coincide with the views of the the Eurosystem or the Federal

Saudi Arabia and the Oil Market

Este trabajo presenta un modelo DSGE no lineal con un sector financiero y hogares heterogeneos. En el modelo, las interacciones entre la oferta de bonos del sector financiero y la demanda de precaucion de los hogares produce un riesgo endogeno significativo. Este riesgo induce un proceso de cambio de regimen endogeno para la produccion, el diferencial de rentabilidad, la deuda y el apalancamiento. Este cambio de regimen genera: i) distribuciones multimodales para estas variables; ii) niveles variantes en el tiempo de la volatilidad y el sesgo de aquellas, y iii) superciclos de deuda y desapalancamiento. La version del modelo con un agente representativo, en comparacion, no puede generar ninguna de estas caracteristicas, lo que destaca el papel central de la heterogeneidad en nuestro analisis. Metodologicamente, se discute como los modelos DSGE no lineales con agentes heterogeneos pueden resolverse de manera eficiente empleando tecnicas de aprendizaje automatico (machine learning) y como pueden estimarse mediante una funcion de verosimilitud, empleando inferencia con difusiones.

/pdf/financial-frictions-and-the-wealth-distribution-4j82ppmx5e.pdf

Financial frictions and the wealth distribution

https://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/15/Fich/dt1518e.pdf

Galo Nuño

Papers

Bank Leverage Cycles

Quantitative Effects of the Shale Oil Revolution

Saudi Arabia and the Oil Market

Financial frictions and the wealth distribution

Quantitative effects of the shale oil revolution