THE ROLE OF INVENTORIES AND SPECULATIVE TRADING IN THE GLOBAL MARKET FOR CRUDE OIL

We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short‐run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil. Copyright © 2013 John Wiley & Sons, Ltd.     

Oil Prices and Personal Consumption Expenditures: Does the Source of the Shock Matter?

This paper studies the effect of structural oil shocks on personal consumption expenditures (PCE). First, we estimate a nonlinear simultaneous equation model, compute impulse responses by Monte Carlo integration, and conduct a test of the symmetry of the impulse response functions. We find that aggregate PCE responds asymmetrically to positive and negative oil‐specific demand shocks. Second, we find that aggregate PCE responds negatively to positive oil demand shocks, while adverse oil supply shocks are of limited effect. Third, we find important heterogeneity in the magnitude, sign and timing of the disaggregate PCE responses to structural shocks in the crude oil market. Our results clearly indicate that the response of PCE to an unexpected oil price increase depends on the source of the oil price shock. Our findings are robust to different nonlinear transformations for the real price of oil.     

Crude oil price dynamics with crash risk under fundamental shocks

Our paper presents a crude oil price model in which the price is confined in a wide moving band. A price crash occurs when the price breaches the lower boundary where a smooth-pasting condition is imposed. Using an asymmetric mean-reverting fundamental (supply/demand) shock, the solution derived from the oil price equation for the model shows the oil price follows a mean-reverting square-root process, which is quasi-bounded at the boundary. The oil price dynamics generates left-skewed price distributions consistent with empirical observations. A weakened mean-reverting force for the price increases the probability leakage for the price across the boundary and the risk of a price crash. The empirical results show the oil price dynamics can be calibrated according to the model, where the mean reversion of the price dynamics is positively co-integrated with the oil production reaction to negative demand shocks, and with the risk reversals of the commodity currencies, the Canadian dollar and the Australian dollar in currency option markets. The results are consistent with an increased price crash risk with negative demand shocks and negative risk reversals. The forecasting performance of the oil price model is better than the futures-spread models and random walk models during the crash periods. While the price of oil was above the lower boundary for most of the time, the conditions for breaching the boundary were met in 2008 and 2014 when the price fell sharply.     

How should monetary policy respond to changes in the relative price of oil? Considering supply and demand shocks

This paper examines optimal monetary policy in a New Keynesian model where supply and demand shocks affect the price of oil. Optimal policy fully stabilizes core inflation when wages are flexible. The nominal rate rises (falls) in response to the demand (supply) shock. With sticky wages core inflation falls (rises) in response to the demand (supply) shock. Impulse response functions from a VAR estimated with post-1986 U.S. data show minimal movement in core inflation in response to both shocks. The federal funds rate rises (falls) in response to the demand (supply) shock, consistent with the predictions from the theoretical model for policy that stabilizes core inflation.     

The effects of oil price shocks on inflation in the G7 countries

This study examines the effects of three types of oil price shocks on inflation in the G7 countries with a new method of isolating oil price shocks. Based on monthly data from January 1997 to January 2019, we find that each oil price shock has the largest effect on U.S. inflation among the G7 countries and each country’s response to oil price shocks is different. Moreover, a rolling-window analysis shows that supply shocks, demand shocks and risk shocks have dynamic effects on inflation. The effect of supply shocks on inflation is strong before the financial crisis, but weakens during the crisis. However, the effect of demand shocks increases sharply in this time. The effect of risk shocks mainly occurs during the financial crisis and the European debt crisis. In addition, this study uses two ways to verify the robustness of the results. Our empirical results have important implications for policymakers and manufacturers, since the results provide a good explanation for the response of inflation in the G7 countries to the oil price shocks from different sources.     

THE ROLE OF TIME‐VARYING PRICE ELASTICITIES IN ACCOUNTING FOR VOLATILITY CHANGES IN THE CRUDE OIL MARKET

There has been a systematic increase in the volatility of the real price of crude oil since 1986, followed by a decline in the volatility of oil production since the early 1990s. We explore reasons for this evolution. We show that a likely explanation of this empirical fact is that both the short‐run price elasticities of oil demand and of oil supply have declined considerably since the second half of the 1980s. This implies that small disturbances on either side of the oil market can generate large price responses without large quantity movements, which helps explain the latest run‐up and subsequent collapse in the price of oil. Our analysis suggests that the variability of oil demand and supply shocks actually has decreased in the more recent past, preventing even larger oil price fluctuations than observed in the data. Copyright © 2012 John Wiley & Sons, Ltd.     

Oil price shocks and credit spread: Structural effect and dynamic spillover

This study analyzes the heterogeneous response of U.S. credit spread to global oil price shocks by building an extended structural vector autoregressive model (SVAR), which can distinguish among the U.S. and non-US oil supply shocks, aggregated demand shocks and oil market-specific demand shocks behind the real oil prices. Meanwhile, a spillover index model developed by Diebold and Yilmaz (2012) (hereafter D.Y. (2012)) is used to estimate the link between oil price shocks and the U.S. credit spread over time. The results show that (i) the credit spread does not respond to global oil supply shocks and non-US oil supply shocks, but has a negative reaction to the U.S. oil supply shocks, aggregate demand shocks, and oil-market-specific demand shocks. (ii) There exists a close connectedness between oil price shocks and the U.S. credit spread, and the link fluctuates cyclically and relates to the economic cycle and the U.S. shale oil revolution. (iii) The spillover from different oil price shocks to the U.S. credit spread shows significant heterogeneity over time. Our findings suggest that policymakers and investors can better track the U.S. credit spread changes using oil price information.     

Empirical evidence on the reaction speeds of housing prices and sales to demand shocks

This article studies the co-movement and dynamics between price movements and transactions in the housing market using data for the period 1988–2008 from Finland. While the previous related literature examines the reactions of sales and prices to an interest rate shock only, this study investigates the responses to income and debt shocks as well. The empirical estimations show that the response of prices to demand shocks is substantially slower than that of sales. The estimated reactions of sales substantially differ from those reported in the earlier literature. The reaction patterns can create the kind of strong positive co-movement between price movements and sales volume and the kind of negative correlation between price level and sales that have been found in several housing markets.     

DISENTANGLING DEMAND AND SUPPLY SHOCKS IN THE CRUDE OIL MARKET: HOW TO CHECK SIGN RESTRICTIONS IN STRUCTURAL VARS

Sign restrictions have become increasingly popular for identifying shocks in structural vector autoregressive (SVAR) models. So far there are no techniques for validating the shocks identified via such restrictions. Although in an ideal setting the sign restrictions specify shocks of interest, sign restrictions may be invalidated by measurement errors, data adjustments or omitted variables. We model changes in the volatility of the shocks via a Markov switching (MS) mechanism and use this device to give the data a chance to object to sign restrictions. The approach is illustrated by considering a small model for the market of crude oil. Earlier findings that oil supply shocks explain only a very small fraction of movements in the price of oil are confirmed and it is found that the importance of aggregate demand shocks for oil price movements has declined since the mid 1980s. Copyright © 2013 John Wiley & Sons, Ltd.     

Oil structural shocks,bank-level characteristics,and systemic risk: Evidence from dual banking systems

By performing a structural VAR analysis on oil price shocks, we provide an evidence on how the origins of oil price shocks impact the risk level of banks in oil-exporting countries and whether bank-level characteristics can influence the sensitivity of risk to oil shocks. When conducting panel regression analysis, we document the following findings. First, not all shocks have the same effect on bank risk. Due to oil supply shocks, the increase in oil price raises bank risk, whereas the similar increase in price due to economic expansion or oil-market specific demand reduces that risk. Second, the business model (whether the bank is Islamic or conventional), size, income diversification, profitability, and financial leverage influence the bank risk exposure to oil shocks differently. Third, the two major recent crises (global financial crises and COVID-19 pandemic) magnified bank risk exposure to oil supply shocks and speculative oil demand shocks. Overall, the structural oil shocks explain a large fraction of the variation in financial stability in GCC countries.     

我国新建住宅长期供给价格弹性估算——基于35个大中城市的实证研究

大多数住宅模型和政策分析,都直接或间接依赖于住宅供给价格弹性的估计值：为了应对市场需求冲击,是多供给住房还是提高住宅价格？基于Mayo（1981）构建的模型,估算了我国35个主要大中型城市的新建住宅供给价格弹性。根据流量模型,2000-2007年我国的新建住宅价格弹性系数在4-11之间,2008到2013年的价格弹性在5-13之间。而存量调整模型得到了截然不同的估算结果：2008-2013年我国的新建住宅供给价格弹性在1-6之间,更精确的估算出了我国新建住宅供给市场的价格弹性。     

Investigating properties of commodity price responses to real and nominal shocks

This paper studies dynamic adjustments of 49 world commodity prices in response to innovations in the nominal exchange rate and the world real GDP. After we estimate the dynamic elasticity of the prices with respect to these shocks, we obtain the kernel density of our estimates to establish stylized facts on the adjustment process of the commodity price toward a new equilibrium path. Our empirical findings imply, on average, that the law of one price holds in the long-run, whereas the substantial degree of short-run price rigidity was observed in response to the nominal exchange rate shock. The real GDP shock tends to generate substantial price fluctuations in the short-run because adjustments of the supply can be limited, but have much weaker effects in the long-run as the supply eventually counterbalances the increase in the demand. Overall, we report persistent long-lasting effects of the nominal exchange rate shock on commodity prices relative to those of the real GDP shock.     

House price synchronization across the US states: The role of structural oil shocks

This paper analyzes the impact of disentangled oil shocks on the synchronization in housing price movements across all the US states plus DC. Using a Bayesian dynamic factor model, the house price movements are decomposed into national, regional, and state-specific factors. We then study the impact of oil-specific supply and demand, inventory accumulation, and global demand shocks on the national factor using linear and nonlinear local projection methods. The impulse response analyses suggest that oil-specific supply and consumption demand shocks are most important in driving the national factor. Moreover, as observed from the regime-specific local projection model, these two shocks are found to have a relatively stronger impact in a bearish rather than a bullish national housing market. Our results have important policy implications.     

Identifying credit demand,financial intermediation,and supply of funds shocks: A structural VAR approach

In this paper, we identify three exogenous shocks to credit market: demand for credit, supply of funds into the financial system, and the willingness to lend of financial institutions (financial intermediation), and also, determine the contribution of these shocks to fluctuations in the credit market and overall economic activity. We estimate a structural vector autoregression model where the three credit shocks are identified with a set of sign restrictions motivated by a simple partial equilibrium model of financial intermediation. We find that the credit demand shock explains significantly the variations in the long-term loan rate proxied by the Moody’s Baa corporate bond yield, while the supply of funds shock contributes to most of the fluctuations in the short-term commercial paper rate. The financial intermediation shock drives most of the fluctuations in the quantity of loans as well as the spread between the Baa and commercial paper rates. Of the credit shocks, we find that the financial intermediation shock has the largest impact on real economic activity. In fact, our analysis implies that the sharp decline in output during the 2007–2009 financial crisis is largely attributable to the financial intermediation shock, along with shocks originating outside of the financial system.     

Macroeconomic Uncertainty and Oil Price Volatility

This paper shows that higher macroeconomic uncertainty causes higher oil price volatility. Regimes of low and high uncertainty are identified in a threshold VAR model in which the effects of structural oil demand and supply shocks are estimated. The results show that higher macroeconomic uncertainty, as measured by global industrial production volatility, significantly increases the sensitivity of oil prices to shocks in oil demand and supply. This occurs as uncertainty lowers the price elasticity of oil demand and supply. The difference in the estimated oil price elasticities is economically meaningful as the price impact of a similar change in oil production might double when it hits the economy in uncertain times. As such, varying uncertainty can explain why oil price volatility is typically higher during periods such as financial crises and recessions, and why oil price volatility changes over time more generally.     

Speculation in the Oil Market

The run‐up in oil prices since 2004 coincided with growing investment in commodity markets and increased price co‐movement among different commodities. We assess whether speculation in the oil market played a role in driving this salient empirical pattern. We identify oil shocks from a large dataset using a dynamic factor model. This method is motivated by the fact that a small‐scale vector autoregression is not informationally sufficient to identify the shocks. The main results are as follows. (i) While global demand shocks account for the largest share of oil price fluctuations, speculative shocks are the second most important driver. (ii) The increase in oil prices over the last decade is mainly driven by the strength of global demand. However, speculation played a significant role in the oil price increase between 2004 and 2008 and its subsequent collapse. (iii) The co‐movement between oil prices and the prices of other commodities is mainly explained by global demand shocks. Our results support the view that the recent oil price increase is mainly driven by the strength of global demand but that the financialization process of commodity markets also played a role. Copyright © 2014 John Wiley & Sons, Ltd.     

Gasoline prices,transport costs,and the U.S. business cycles

The effects of gasoline prices on the U.S. business cycles are investigated. In order to distinguish between gasoline supply and gasoline demand shocks, the price of gasoline is endogenously determined through a transportation sector that uses gasoline as an input of production. The model is estimated for the U.S. economy using five macroeconomic time series, including data on transport costs and gasoline prices. The results show that although standard shocks in the literature (e.g., technology shocks, monetary policy shocks) have significant effects on the U.S. business cycles in the long run, gasoline supply and demand shocks play an important role in the short run.     

The nonlinear effect of oil price shocks on financial stress: Evidence from China

This paper examines the nonlinear effects of different types of oil price shocks on China’s financial stress index (FSI). For this purpose, we use newly proposed framework by Ready (2018) to decompose oil prices into supply, demand and risk shocks. Then, we use a Markov regime-switching (MRS) model to investigate the nonlinear effects of these oil price shocks on China’s FSI. The empirical results show that the effects of three oil price shocks are nonlinear under different regimes. In particular, oil supply shocks mainly have a significantly positive effect on China’s FSI in the low-volatility state; demand shocks have negative effects on China’s FSI in different regimes, but this effect is larger in the low-volatility state; the effect of risk shocks on China’s FSI is the opposite, and it is positive in the high-volatility state but negative in the low-volatility state.     

A monetary business cycle model with unemployment

To reproduce key features of the post-war U.S. data, most monetary business cycle models must assume there are high price markups and that agents have high labour supply elasticities despite the existence of contradictory microeconomic evidence. This paper eliminates the need for these assumptions by introducing imperfectly observed effort into a limited participation model. The estimated model is better able to capture the sluggish price response to a monetary policy shock than the standard model, and is consistent with evidence regarding the qualitative responses of the U.S. economy to technology shocks, fiscal policy shocks and monetary policy shocks.     

Supply constraints and housing market dynamics

Although the volatility of house prices is often ascribed to demand-side factors, constraints on housing supply have important and little-studied implications for housing dynamics. I illustrate the strong relationship between the volatility of house prices and the regulation of new housing supply. I then employ a dynamic structural model of housing investment to investigate the mechanisms underlying this relationship. I find that supply constraints increase volatility through two channels: First, regulation lowers the elasticity of new housing supply by increasing lags in the permit process and adding to the cost of supplying new houses on the margin. Second, geographic limitations on the area available for building houses, such as steep slopes and water bodies, lead to less investment on average relative to the size of the existing housing stock, leaving less scope for the supply response to attenuate the effects of a demand shock. My estimates and simulations confirm that regulation and geographic constraints play critical and complementary roles in decreasing the responsiveness of investment to demand shocks, which in turn amplifies house price volatility.