Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting

We develop the methodology and a detailed case study in use of a class of Bayesian predictive synthesis (BPS) models for multivariate time series forecasting. This extends the recently introduced foundational framework of BPS to the multivariate setting, with detailed application in the topical and challenging context of multi-step macroeconomic forecasting in a monetary policy setting. BPS evaluates-- sequentially and adaptively over time-- varying forecast biases and facets of miscalibration of individual forecast densities, and-- critically-- of time-varying inter-dependencies among them over multiple series. We develop new BPS methodology for a specific subclass of the dynamic multivariate latent factor models implied by BPS theory. Structured dynamic latent factor BPS is here motivated by the application context-- sequential forecasting of multiple US macroeconomic time series with forecasts generated from several traditional econometric time series models. The case study highlights the potential of BPS to improve of forecasts of multiple series at multiple forecast horizons, and its use in learning dynamic relationships among forecasting models or agents

Asymmetric effects of monetary policy in regional housing markets

The responsiveness of house prices to monetary policy shocks depends on the nature of the shock – expansionary versus contractionary – and on local housing supply elasticities. These findings are established based on a panel of 263 US metropolitan areas. We test and find supporting evidence for the hypothesis that expansionary monetary policy shocks have a larger impact on house prices when supply elasticities are low. Our results also suggest that contractionary shocks are orthogonal to supply elasticities, as implied by downward rigidity of housing supply. A standard theoretical conjecture is that contractionary shocks have a greater impact on house prices than expansionary shocks, as long as supply is not perfectly inelastic. For areas with high housing supply elasticity, our results are in line with this conjecture. However, for areas with an inelastic housing supply, we find that expansionary shocks have a greater impact on house prices than contractionary shocks. We provide evidence that the direction of the asymmetry is related to a momentum effect that is more pronounced when house prices are increasing than when they are falling

Has the Fed responded to house and stock prices? : a time-varying analysis

En este trabajo utilizamos un modelo VAR estructural con parámetros variables en el tiempo y volatilidad estocástica para investigar si la Reserva Federal ha respondido sistemáticamente a los precios de los activos y si esta respuesta ha cambiado con el tiempo. Para recuperar el componente sistemático de la política monetaria, interpretamos la ecuación de la tasa de interés en el VAR como una regla extendida de política monetaria que responde a la inflación, el output gap, los precios de la vivienda y los precios de las acciones. Detectamos variación temporal en los coeficientes de precios de la vivienda y precios de las acciones, mientras que los coeficientes de la inflación y el output gap son bastante estables en el tiempo. Nuestros resultados indican que el componente sistemático de la política monetaria en Estados Unidos i) tuvo un peso positivo sobre el crecimiento real de los precios de la vivienda, que disminuyó antes de la crisis y eventualmente volvió a aumentar, y ii) solo tuvo en cuenta el crecimiento real de los precios de las acciones en momentos concretos del tiempoIn this paper we use a structural VAR model with time-varying parameters and stochastic volatility to investigate whether the Federal Reserve has responded systematically to asset prices and whether this response has changed over time. To recover the systematic component of monetary policy, we interpret the interest rate equation in the VAR as an extended monetary policy rule responding to infl ation, the output gap, house prices and stock prices. We find some time variation in the coefficients for house prices and stock prices but fairly stable coefficients over time for inflation and the output gap. Our results indicate that the systematic component of monetary policy in the US, i) attached a positive weight to real house price growth but lowered it prior to the crisis and eventually raised it again, and ii) only episodically took real stock price growth into accoun

The Price Responsiveness of Shale Producers: Evidence from Micro Data

We show that shale oil producers respond positively to favourable oil price signals, and that this response is mainly associated with the timing of production decisions through well completion and refracturing, consistent with the Hotelling theory of optimal extraction. This finding is established using a novel proprietary data set consisting of more than 200,000 shale wells across ten U.S. states spanning almost two decades. We document large heterogeneity in the estimated responses across the various shale wells, suggesting that aggregation bias is an important issue for this kind of analysis. Our empirical results call for new models that can account for a growing share of shale oil in the U.S., the inherent flexibility of shale extraction technology in production and the role of shale oil in transmitting oil price shocks to the global economy.publishedVersio

Has the fed responded to house and stock prices? : a time-varying analysis

Published: 8 March 2017In this paper we use a structural VAR model with time-varying parameters and stochastic volatility to investigate whether the Federal Reserve has responded systematically to asset prices and whether this response has changed over time. To recover the systematic component of monetary policy, we interpret the interest rate equation in the VAR as an extended monetary policy rule responding to inflation, the output gap, house prices and stock prices. We find some time variation in the coefficients for house prices and stock prices but fairly stable coefficients over time for inflation and the output gap. Our results indicate that the systematic component of monetary policy in the US i) attached a positive weight to real house price growth but lowered it prior to the crisis and eventually raised it again and ii) only episodically took real stock price growth into account

Oil Price Shocks and Monetary Policy in a Data-Rich Environment

This paper examines the impact of different types of oil price shocks on the U.S. economy, using a factor-augmented VAR (FAVAR) approach. The results indicate that when examining the effects of oil price shocks, it is important to account for the interaction between the oil market and the macroeconomy. I find that oil demand shocks are more important than oil supply shocks in driving several macroeconomic variables, and that the origin of demand shocks matter. Specifically, the U.S. economy and monetary policy respond differently to global demand shocks that have the effect of raising the price of oil and to oil-specific demand shocks.publishedVersio

Oil Price Shocks and Monetary Policy in a Data-Rich Environment

This paper examines the impact of different types of oil price shocks on the U.S. economy, using a factor-augmented VAR (FAVAR) approach. The results indicate that when examining the effects of oil price shocks, it is important to account for the interaction between the oil market and the macroeconomy. I find that oil demand shocks are more important than oil supply shocks in driving several macroeconomic variables, and that the origin of demand shocks matter. Specifically, the U.S. economy and monetary policy respond differently to global demand shocks that have the effect of raising the price of oil and to oil-specific demand shocks

The demand for cash in Norway

Summary The purpose of this paper is to provide an econometric model which can be used to explain and determine the demand for cash in Norway, and to use this model to forecast the demand for cash in the period 2004.3-2007.4. From a central banks perspective, there is particularly one reason to be interested in the demand for cash. The central bank is the issuer of notes and coins. Since one of its objectives is to satisfy the demand for cash, it is of the central banks interest to ensure that they supply the society with notes and coins in the most efficient way. Obviously this is also of great importance for the society. For the central bank to do this, an efficient amount of notes and coins must be produced. In order to be able to plan the production in the best way, it is therefore of interest to investigate closer what determines the demand for cash. Further, one may also argue that it is of interest to investigate the demand for cash for monetary policy purposes. The reason for this is that the amount of cash held for transaction purposes is closely related to domestic spending, and hence to domestic price developments. The demand for cash increased steadily year by year until 1999, and has decreased somewhat since then. In the same period the use of alternative payment instruments, such as payment cards, increased rapidly. One would therefore expect that the use of cash should have been reduced dramatically, something that has not yet happened. This paper studies the determinants of cash demand in Norway during the period 1980-2004. A thorough discussion of the different determinants for cash demand is carried out. The starting point for the discussion is the concept of money and its role, the evolution of the payment system and theoretical models of money demand. Since most of the theoretical models of money demand focus on a quite narrow concept of money, it is believed that some of these models are also relevant when investigating the demand for cash. This seems to especially be the case for models considering the private households demand for money. Based on this discussion, empirical models of demand for real cash are developed. Rather than estimating the theoretical models themselves, they are used to determine which explanatory variables that should be considered when an empirical model is specified. In the empirical analysis, quarterly data and a general-to-specific approach are used. For this analysis I have used the software programs PcGive 10.1 and TSP 4.5. Due to problems with autocorrelation in the residuals and lack of data, a VAR model seems not appropriate to use for estimating the demand for cash. Instead a single equation equilibrium correction model is used. Considering different initial models, eliminating insignificant variables and applying different statistical tests, suggests that there are two competitive, but also quite similar, models of relevance. Both models have only private point-of-sale consumption and real deposit interest rate as significant explanatory variables in addition to a linear trend, seasonal variables and impulse dummies. The rapid evolution in the payment system seems to have a negative effect on the demand for cash, which may dampen the increase in the demand for real cash. This effect is represented in the models by a negative linear trend. The estimation results show that the two models short-run effects differ slightly, while the long-run effects are quite similar. The long-run elasticity for consumption was found to be approximately 0.63 and the semi-elasticity for the interest rate was found to be approximately 0.02 in both models. These results differ compared to the results obtained by Fischer, Köhler and Seitz (2004) for the Euro area. The explanatory variables were found to be weakly exogenous with respect to all parameters in the structural equation for real cash, validating a single equation approach. In addition to this, the highly significant equilibrium correction term suggests that an equilibrium correction model is appropriate. In order to choose between one of the two competitive models, parameter stability and ex post forecasting properties are investigated. However, this does not lead to a clear conclusion of which model to choose. Both models seem to have parameters that are reasonable stable. On the other side, both models have some problems when it comes to forecasting in the sample period 2002.1-2004.2. An explanation for this may be that this forecasting period was a rather turbulent period for the Norwegian economy. The main reason for this was probably that the economy needed some time to adjust to the change in the monetary policy regime in March 2001. Since the model selection analysis gives no clear suggestion of which model to choose, both models are treated on an equal basis. For given evolution paths of the exogenous variables, ex ante forecasts for the period 2004.3-2007.4 are obtained by the two models. In addition to this forecasts produced by a simple AR(8) model are also considered. The forecasts produced by the two competitive models that are developed, suggest that the demand for real cash will rise for the next couple of years, and then slowly decrease from the end of 2006. In contrast to this the simple AR(8) model suggests that the demand for cash will increase throughout the whole forecasts period. In order to make the forecasts more robust for potential breaks, forecasts with intercept correction are conducted. Finally, I produce forecasts under alternative assumptions of the evolution paths of the exogenous variables