Does excess futures market demand affect the spot price of oil?

Despite Hicks' demonstration nearly twenty years ago of the equivalence between liquidity-preference and loanable-funds theories of interest, thte debate on this issue continues to fill the pages of the journals. Indeed, on this issue the 1950's have seen a revival of the polemics of the 1930's. It is not my purpose here to provide a systematic survey of this revival. Instead I shall restrict myself to two arguments that have been advanced in implicit or explicit rebuttal of Hicks' demonstration-and will show why they are invalid. The first argument bases itself on the distinction between stock and flow analysis -and will be discussed in Section 1. The second bases itself on the distinction between static and dynamic analysis-and this will be discussed in Section 2.2 The argument of both these sections is carried out on the assumption of full employment; a generalization-under certain assumptions-to the case of unemployment is presented in Section 3. 1. Let us start with Hicks' classic demonstration.3 This can be restated in the form of the following two propositions: 1 (a) Consider an economy with n goods, consisting of n-2 commodities (inclusive of services), bonds (perpetuities), and money. In the corresponding system of n excess-demand equations, one of the equations is redundant and can be eliminated-that is, if any n-i excess-demand equations are satisfied, the remaining one must also be satisfied. This will be called Walras' Law. (b) It follows that a general-equilibrium analysis of the commodity and bond markets yields exactly the same equilibrium rate of

Every sector in every country faces a cash flow (budget) constraint. The cash flow constraints facing the individual sectors in a country, when aggregated across that country’s sectors, yield a community or countrywide cash flow constraint. The terms in this constraint may then be arranged to produce an equation that may be interpreted as a form of Walras’s Law. In general, Walras’s Law states that in a model containing n markets, the sum of the excess demands across the n markets must be equal to zero identically. In particular, if n-1 markets happen to be in equilibrium (characterized by excess demands equal to zero in those markets), then the nth market must also be in equilibrium. In the present context, it states that the excess demand for the money issued in that country plus the excess demand for bonds issued in that country plus that country’s ex ante balance of payments deficits with each of the other two countries must be equal to zero identically. Importantly, the excess demands in the product markets do not appear explicitly in the community’s budget constraint and therefore do not appear in the corresponding statement of Walras’s Law for that country. The reason is that since the imperfectly competitive firms decide production and announce product price before product demand is revealed, they may experience unplanned changes in inventories by the end of the period. Since the firms do not engage in net business saving in this model, they absorb the excess supply or demand for their product by financing (or reducing their end-of-period debt) in their own bond market the unplanned investment or disinvestment. Consequently, any excess demand in a product market automatically becomes incorporated in that country’s bond market.

The key to estimation of the above disequilibrium labor market model is the indicator equation, $$\text{L}_{\text{t}}^{\text{d}}-\text{L}_{\text{t}}^{\text{s}}={{\text{ }\!\!\delta\!\!\text{ }}_{0}}\text{(}{{\text{z}}_{\text{t}}}\text{-z}{}_{\text{t}}^{\text{E}}\text{)}$$ (24) which relates the unobservable excess demand for labor to an observable market statistic. There is a large literature, almost all of it in the context of Phillips curve analysis, that discusses the measurement of excess demand in the labor market. The standard Phillips curve plots the rate of inflation associated with a given level of unemployment under the rationale that a greater excess demand for labor (low unemployment) leads to greater wage inflation (and hence price inflation). In the 1970’s, this curve was widely reported to be econometrically unstable. One strictly empirical response has been to claim that of much this instability occurs in the relationship between unemployment and actual excess labor demand and not between excess labor demand and wage inflation. Clearly, if unemployment is not a stable indicator of labor market tightness, the usual formulation of the Phillips curve will not be stable even if there exists some underlying true relationship. Thus, other measures of unsatisfied labor demand have been used in place of unemployment in the estimation of a Phillips curve. Among these are productivity and work effort measures (discussed by Taylor (1973) and Fortin and Newton (1982)), the index of help wanted advertising and the rate of job quits (Medoff and Abraham (1982)), and the rate of employment layoffs (Baily (1982b)).1

Money and the Consumption Goods Market in China

Money and the consumption goods market in China

This paper studies the relations between money and other macroeconomic variables as well as excess demand in the consumption goods market in the case of China, 1954–1983. We explicitly recognize the endogeneity of money in the CPE and do not impose (but instead test) some common restrictive assumptions; we assess the extent of aggregate excess demand (supply) in a macroeconomic disequilibrium model; and we allow at the macro level for the possible coexistence of micro markets in different states of excess demand or supply (shortages or slacks). We find bidirectional causality between money and income; that M0 behaves in a manner more suited to building simple, conventional models than does M2; and that there has been a mixed pattern of excess supplies and demands over the three decades. J. Comp. Econ., September 1987, 11(3), pp. 354–371. Birkbeck College, London W1P 1PA, England.

This dissertation considers different aspects of crude oil research, primarily based on four independent empirical analyses, interconnected through a common denominator: Time-series analysis methods applied to global oil prices. The first three chapters are of introductory nature. They present the developments on global oil markets since the end of World War II and review the literature on crude oil. More importantly, they show how to estimate global models using vector autoregressive (VAR) and structural vector autoregressive (SVAR) models. The latter allow for the disentanglement and estimation of unexpected oil price shocks required for later analyses. The first analysis reviews the question, originally at the center of economic research on crude oil: How are macroeconomic performance and oil price shocks interrelated? New insights based on longer sample series as well as developments in SVAR models allow to complement the existing literature by estimating global models of oil. Based on a broad set of monthly macroeconomic variables for the United States and Germany, the analysis shows that these two industrialized economies react differently to oil price shocks. The disentanglement of the underlying causes of unexpected oil price movements is crucial. The second empirical analysis concerns the effects of oil embargoes against oil producing countries The same SVAR models are applied in the framework of the sanctions that were imposed on Iran by the international community late 2011 and early 2012. The estimation results show that the direct effects of the Iran sanctions on global oil prices were limited and temporary. By estimating and analyzing the unexpected oil price changes before the implementation of sanctions, we find evidence that sanctions might have important price increasing effects through market expectations long before their official implementation. Departing from the same global model that includes the real price of crude oil as an endogenous variable, the third analysis is concerned with its oil price forecasting properties. We are able to improve the forecasting accuracy by applying regularization methods for variable selection. Originating from the machine learning literature, these methods are now widely used in economic research, especially in cases, where a large number of variables are included in the model. Furthermore, typical lag selection methods, used in the estimation of global models of oil are compared. Finally, the core variable set is augmented by a wide range of possibly relevant regressors as suggested by the literature. The fourth and final analysis concerns another aspect of oil price forecasting when using crude oil futures as forecasts for the spot price of oil. We estimate whether forecasting preferences are asymmetric in a sense that a positive forecast error has a different cost than a negative forecast error of the same magnitude. Using different model specifications and a wide range of instrument sets inspired by the literature on futures, we find robust evidence for asymmetric loss. The market has a preference to underestimate the spot price of crude oil through futures pricing. This indicates the existence of a risk premium on crude oil futures.

This paper examines the short- and long-term dynamic relationship between spot and forward oil prices. We highlight the finding that producers are bound by forward contracts for future deliveries of oil with forward prices which deprives them of any immediate increase in production and therefore have an effect on spot prices. We will process daily spot and futures prices data during the period from January 20, 2017 to December 13, 2021.The results of the causality test indicate that the relationship between spot and futures prices is bidirectional, which means that the causality is mutual. Indeed, in the short term, spot prices caused futures prices and vice versa in the medium and long term. In addition, spot oil prices have been affected by changes in the spot price at a minimal level. A spot price shock has an insignificant negative impact on oil futures prices while the impulse response of pot prices to a futures price shock was positive. Finally, we will find that the impact of extreme volatility in futures prices, when they reach their lowest level in history on April 20, 2020, on spot prices was insignificant. The results of this research contribute to the oil decision-making process.

The aim of the current paper is to estimate spot prices’ next-day volatility of the two largest kinds of crude oil, European Brent oil and American WTI oil, and examine differences due to selected global incidents. Daily data for oil spot prices are from May 1987 till January 2015. The contribution of the study is in a comparison of oil spot prices’ development and impacts of the Euro sovereign debt crises, recent global financial crises, and also the historical affairs as the military conflict in the Persian Gulf in 1990, or particular incidents after the start of the new millennium. The estimation method for short-run forecasting is the volatility model GARCH (1,1). While it has been proven that there was higher volatility during the global financial crisis within American WTI oil prices, higher errors were examined within European Brent oil prices. There was no higher volatility due to the euro crisis in the last 4 years. Nonetheless, both investigated oil prices were affected by highest volatility during military conflict in 1990 in our estimated period. It was clearly concluded that military conflicts can affect oil prices in a much higher way than recent financial crises.

The study sought to contribute to the extant literature on the interconnectedness between commodity spot prices and futures prices by covering daily data from 2001-2019. Employing the OLS and the QR, different dynamics of the relationship between commodity spot and futures prices emerged from the study. For oil and gold prices, OLS estimator revealed that neither spot nor futures prices of the commodities had a significant effect on the other. Quantile regression estimators however suggested otherwise. For oil prices, futures prices were found to have a significant positive effect on spot oil prices at the 60th and 75th percentile whereas spot oil prices were found to have a significant positive effect on the futures oil prices at the lower tail (0.1, 0.2, and 0.25 quantiles). For gold prices, futures gold prices had a significant positive effect on spot gold prices at the 75th percentile (3rd quantile) marked as the upper tail of the distribution whereas a significant negative effect was revealed at the middle quantile (50th percentile). For cocoa prices, both the OLS and the QR estimators were significant in either direction. A significant positive effect of futures (spot) cocoa price on spot (futures) cocoa price was observed across all quantiles in both directions. The results suggest that speculators and arbitrageurs in the commodity market must be concerned about the causality moving from one direction to another and take appropriate investment positions that protect their interests.

We can observe excess capital demands in the financial market for the creative industry that includes gaming, animation, character licensing, music, fashion, and broadcasting. The excess demands seem to arise from information asymmetries between capital demanders and capital providers. Capital market polices can be critical, as capital providers tend to take account only of collaterals that capital demanders provide. In the paper, we estimate the amount of an excess capital demand in the Korean creative industry. We adopt an estimate strategy by European Commission (2013) that studies capital financing GAPs for small and medium-sized enterprises. Using various scenarios, we provide several estimates; the estimates range from KRW 2.1 trillions to KRW 5.7 trillions. The estimated financing gap can deliver critical information for designing industry polices.

PurposeAgricultural producers rely on debt capital to support many functions of their enterprise, yet private credit markets are frequently characterized by an imbalance between supply and demand. As a result, a number of public lending programs exist to mitigate the perceived market failures of private credit markets that serve agricultural producers. The paper aims to discuss these issues.Design/methodology/approachThis study uses a structural disequilibrium model to examine the potential for excess demand or supply in the private market for non-real estate farm loans between 1978 and 2014.FindingsThe model demonstrates that the market is frequently characterized by disequilibrium, fluctuating between periods of excess demand and excess supply. These disequilibrium periods motivate the discussion of public intervention as a policy proposal within the agricultural sector.Originality/valueThis study uses traditional disequilibrium modeling to evaluate the private credit market for agriculture lending in a manner that has not been attempted previously in the literature. The model uses maximum likelihood methods with non-linear solution algorithms to investigate excess supply and demand in the sector.

This paper considers the role of hedging and speculation on future oil prices. In July 2008, oil prices topped over $140/bbl then tanked to below $50/bbl by December of the same year. Many including officials, suppliers and consumers blamed futures markets, especially the speculators, for the oil price volatility (Buyuksahin 2012). Shenoy (2011) relates the increase of non-commercial traders and contract volumes to the price fluctuation. Further, Shenoy (2011) disregards the market fundamentals and claims they cannot justify the high prices. However, others find market fundamentals to be more important. U. S. Energy Information Administration (EIA) (2007) and Krugman (2013) cite activities that have caused oil prices to increase and state reasons that support market fundamentals. These factors include geopolitics, rapid world economic growth, decreasing production, little surplus oil production capacity and inelastic oil demand. In this paper we investigate whether we agree with these latter papers that the big price increase from 2007 to mid-2008 is better explained by market fundamentals. Financial theory shows us that for speculators and the futures market to raise current cash prices, they must induce shifts in demand or supply in the cash market. Such shifts can come from inventory changes in the cash market or from producers shifting their production profiles. Thus, if futures prices are bid up by speculators and high futures prices are causing commercials in the cash market to increase inventories or producers to reduce production, then speculators are contributing to the price increase. There are three links in the chain that we need to investigate to support the speculator story. First, speculator positions in the futures market must be reinforcing the futures price changes; they must be buying when prices are increasing and selling when prices are falling. Second, the futures price must be inducing players in the cash market to be shifting their positions in a pattern consistent with changing future prices. If future prices are higher, buyers of crude should be buying and putting crude into inventories and sellers of crude should be withholding production and increasing spare capacity. If future prices are lower, crude buyers should reduce purchases now and run down inventories, and sellers should increase production and lower their surplus capacity. Finally, the futures price and the spot price movements need to be lined up. Thus, we expect higher futures prices to coincide with rising spot prices and lower futures prices to coincide with lower spot prices. To support the market fundamental hypothesis, we will explain the fundamentals of how hedging and speculation affect oil prices. Such fundamentals will clarify many misconceptions and show when hedging and speculation reduce price volatility and make the market more efficient and when they do not. Finally, we will consider oil price volatility since 2004 with particular emphasis on the oil price spike in 2008, which was followed by a significant collapse. We will consider if the three links in the chain above hold and support the hypothesis that speculators were responsible for the big price run-up and collapse as well as other less notable price movements since 2004.

The effects of futures markets on oil spot price volatility in regional US markets

Monetary Policy Report - October 2022