Spot prices or front-month futures prices for energy commodities can exhibit occasional sharp peaks and drops (even to negative values), accompanied by large backwardations or contangos and unusually low or high levels of working stocks. We present a model of storage arbitrage that rationalizes such episodes, relevant for markets for energy commodities such as petroleum, natural gas, or storable electricity, where free disposal is not available. Based on price data only, we offer an empirical approach to estimate key parameters that determine the dynamics of prices, including endogenous price thresholds that indicate lower and upper bounds on discretionary stocks. Price movements in the regime within these bounds are moderated by responses of speculative storage. In the two regimes where price is respectively above or below threshold prices, sharp price jumps are more likely. We are the first to prove consistency and asymptotic normality of a method of estimating this model on prices with endogenous jumps. We explore the behavior of our estimator for small samples, and illustrate its application using petroleum prices. Although the model structure and the distributions of the disturbances in the Euler equation are quite complex, a nice feature of our estimator is its simplicity; it is straightforward non-linear least squares. Moreover, our estimation approach is robust to the demand functional form and the distribution of the shocks.

Nonlinearities, exponential trends, and Euler equations are three key features of standard dynamic volatility models of speculation, economic growth, or macroeconomic fluctuations with occasionally binding constraints and endogenous state-dependent volatility. A natural way to estimate a model with all such three features could be to use the observed nonstationary data in a single step without preliminary linearization, log-linearization, or preliminary detrending. Adoption of this natural strategy confronts a serious challenge that has been neither articulated nor solved: a dichotomy in the empirical model implied by the Euler equation. This leads to a discontinuity in the regression in the limit, rendering the approaches employed in available proofs of consistency inapplicable. We characterize the problem and develop a novel method of proof of consistency and asymptotic normality. Our methodological contribution establishes a foundation for consistent estimation and hypothesis testing of nonstationary models without resorting to preliminary detrending, an a priori assumption that any trend is exactly zero, linearization, or other restrictions on the model.

Examiners' instructions and academic studies on patent validity determination focus on identification of "blocking" citations that invalidate claims in applications as non-novel or obvious, generally ignoring the non-blocking majority as irrelevant to validity. Recently available datasets allow us to identify, for the first time, "forward" citations received by applications before grant, as well as "backward" citations in those applications, and distinguish those identified by the examiner as blocking (submitted mainly by examiners), as well as non-blocking examiner and applicant citations. Categorical analysis confirms that blocking citations in an application strongly negatively predict its grant, but positively predict grant of the cited blocking applications. Non-blocking applicant and examiner citations in an application equally strongly predict its grant, but do not predict grant of cited applications. We test whether expected value - measured by applicant forward citations to the application prior to its grant - affects probability of grant, with negative results. These findings expand our understanding of the scope of examiners' and applicants' roles as mediators of validity-relevant information in applications.

Wheat is a globally important crop and one of the "big three" US field crops. But unlike the other two (maize and soybean), in the United States its development is commercially unattractive, and so its breeding takes place primarily in public universities. Troublingly, the incentive structures within these universities may be hindering genetic improvement just as climate change is complicating breeding efforts. "Business as usual" in the US public wheat-breeding infrastructure may not sustain productivity increases. To address this concern, we held a multidisciplinary conference in which researchers from 12 US (public) universities and one European university shared the current state of knowledge in their disciplines, aired concerns, and proposed initiatives that could facilitate maintaining genetic improvement of wheat in the face of climate change. We discovered that climate-change-oriented breeding efforts are currently considered too risky and/or costly for most university wheat breeders to undertake, leading to a relative lack of breeding efforts that focus on abiotic stressors such as drought and heat. We hypothesize that this risk/cost burden can be reduced through the development of appropriate germplasm, relevant screening mechanisms, consistent germplasm characterization, and innovative models predicting the performance of germplasm under projected future climate conditions. However, doing so will require coordinated, longer-term, inter-regional efforts to generate phenotype data, and the modification of incentive structures to consistently reward such efforts.

study of the seasonality and overall quantity and quality of Chinese patenting, including international comparisons, suggests that government planning and annual targets encouraged gaming of the system, which increased patent counts but negatively affected patent quality.

The dynamics of consumption and stocks are crucial for analysis of commodity prices and policies. But empirical application of the standard storage model has been derailed by failure to replicate high real price autocorrelation. Our proposed storage model is the first empirical model to recognize the full implications of nonstationarity for price behavior and speculative arbitrage with an occasionally binding non-negativity constraint, a challenge shared by DSGE models in macroeconomics and growth. Our consistent least squares strategy estimates first the endogenous price trend induced by a latent trend in production and then the interest rate and a target separating two distinct dynamic regimes. In one, price has a stochastic trend with drift equal to the interest rate; in the other, price exhibits expected jumps from current price to a trending target price in the stockout region. Neglect of small trends can increase measured price autocorrelation and variation to the high observed levels.

We compare the effects of two functions of the patent system application publication and confirmation of grant - on licensing of academic inventions. Application publication eighteen months after filing significantly increases the license hazard for exclusively licensed patents, and for inventions in the larger of the two major technology groups that we study (chemical, drugs and medical), implying an informational role of publication additional to that of academic publication. For the other major aggregate (computers, communications, electrical, electronic and mechanical), which necessarily includes a high proportion of nonexclusively licensed patents, we find no significant response. Patent grant has a generally insignificant effect on licensing hazard, consistent with efficient contingent pre-grant contracting, which significantly accelerates transfer in important technology fields. (C) 2017 Elsevier B.V. All rights reserved.

There is a widespread impression, reflected in recent legislation, that US Patent Office examiners issue many patents of dubious validity, and are insufficiently informed to distinguish these from other valid applications. We address this issue using related application outcomes at the European Patent Office as indicators for patent weakness. We create a proxy for potentially citable prior art using latent semantic analysis of US patent documents, and use this to construct a measure of examiner search effort. We find that US examiners tend to devote more search effort to weaker patents, implying that they can identify a substantial portion of the weak patents that they issue. Why the patent system fails to make better use of examiners' ability to identify weak patents is a question that merits further investigation.

Neglect of trends has unrecognized implications for interpretation of autoregressions. In nonparametric analysis of instructive samples of commodity price series, correspondences relating current price to the following price are linear, and returns appear independent of current price. After detrending current price, these relationships appear highly nonlinear, suggestive of the implications of a model of storage arbitrage. In such a model, any trend is not revealed in expected returns on positive stocks but in expected jumps from boom prices. We implement a new approach to consistent estimation of nonlinear empirical models with a trend in price that might not be zero.

We identify two issues with the reverse regression approach as implemented in several classic reconstructions of past climate fluctuations from dendroclimatologcical data series. First, instead of estimating the causal relationship between the proxy, which is measured with significant error, as function of climate and formally inverting the relationship, most papers estimate the inverted relationship directly. This leads to biased coefficients and reconstructions with artificially low variance. Second, we show that inversion of the relationship is often done incorrectly when the underlying causal relationship is dynamic in nature. We show analytically as well as using Monte Carlo experiments and actual tree ring data, that the reverse regression method results in biased coefficients, reconstructions with artificially low variance and overly smooth reconstructions. We further demonstrate that correct application of the inverse regression method is preferred. However, if the measurement error in the tree ring index is significant, neither method provides reliable reconstructions.

Agricultural economics has a proud tradition of developing practical tools that can quantify the gains and losses from changes in policies or programs. These tools have driven home the point that the redistribution achieved by policy changes usually dominates the efficiency effect. Consequently, political forces tend to reflect the concentrated interests in prospective gross benefits or losses more effectively than the diffused interests in net gains. Land grant universities in the United States and public universities in Australia, New Zealand, and the United Kingdom have produced generations of applied economists working mostly in public institutions. These economists, working in the public interest, have staved off many bad policy proposals, initiated beneficial modifications of others, and, in the case of New Zealand, seized the moment to initiate wholesale agricultural policy transformation. The recent increased numbers of economists working as private sector employees or as paid consultants on agricultural policy have generated or supported new useful initiatives and reforms. However, it seems that many, wittingly or unwittingly, engage in research that places a veneer of respectability over indefensible policies. Crop and disaster programs are discouraging examples. The financial clout of private interests of insurers and the farm lobby and the public consultancies needed to regulate rampant moral hazard and adverse selection have diverted many (but not all) qualified economists from the mission to eliminate such programs in the public interest. We are learning that public programs can be much harder to control if they employ, or encourage employment of, private agents in ill-designed and often nontransparent contractual relationships, and those private agents influence economists as well as politicians.

We present a Maximum Likelihood estimator for the standard commodity storage model with stockouts, based on prices only. While it imposes no additional assumptions on the model, the Maximum Likelihood estimator has small sample properties superior to those of the Pseudo Maximum Likelihood approach. We provide a proof that is crucial for applying our estimator to the model with normal harvests and possibly unbounded prices, thereby eliminating an inconsistency in the empirical storage model literature. Applying our Maximum Likelihood estimator to a series of annual sugar prices from 1921 to 2009 provides new evidence for the empirical relevance of the standard storage model. Our results imply a cutoff price at which discretionary stocks go to zero, which is higher than the price obtained by applying the Pseudo Maximum Likelihood estimator to the same data. The implied frequency of stockouts is lower, and price correlations, skewness, and kurtosis implied by the model closely match those seen in the annual sugar price data. We find the price of sugar to be highly responsive to small changes in consumption. When inventories are not available to buffer the effects of negative supply shocks on consumption, prices must increase sharply to induce the consumption changes needed to clear the market. Our results show why production shocks are not necessarily aligned with price spikes; the same production shock can give rise to very different price responses, depending on whether or not there are sufficient stocks to buffer its impact.

High and volatile prices of major commodities have generated a wide array of analyses and policy prescriptions, including influential studies identifying price bubbles in periods of high volatility. Here we consider a model of the market for a storable commodity in which price expectations are unbounded. We derive its implications for price time series and empirical tests of price behavior. In this model commodity price is equal to marginal consumption value, and hence bubbles as defined in financial economics cannot occur. However the model generates episodes of price runs that could be characterized as “explosive” and might seem to be bubble-like. At sufficiently long holding periods, a price path can yield average returns consistent with mean reversion, even though the long run expectation of price is infinite.

Brian D. Wright and colleagues present data challenging the assumption that corporate-funded academic research is less accessible and useful to others.

Academic inventions are key drivers of technical progress in modern economies, and exclusive licensing has become the dominant means of transfer to the private sector. However, the strong licensee incentives generated by exclusive academic licensing are generally assumed to come at the expense of discouragement or diversion of research by nonlicensees. In a first test of this highly intuitive assumption, using data from university campuses and national research laboratories, we find that after exclusive licensing forward citations by private sector nonlicensees actually increase. An unanticipated exclusive license appears to be a signpost pointing out commercially relevant innovation pathways that nonlicensees follow with successful patented research. Tests using pre-license information disclosures support this signaling hypothesis.

The onset of the grain price spikes in late 2007 heralded a heated discussion among economists and policy makers on the source of the problem and appropriate policy responses. The subsequent rounds of price surges hit landless poor consumers hard, and transferred billions of dollars from them to landowners worldwide. Economists offered a list of highly plausible explanations for the recent jumps in grain price levels. Key findings included the large harvest shortfalls caused by climate change, energy prices, and fertilizer prices, as well as demand increases due to the large and persistent annual income increases in India and China. Several declared various combinations of the above factors to be a perfect storm' in grain markets. In fact little more than a quick series of online searches easily reveals that only the last is plausible as a major cause of recent grain price jumps. In particular there was no major global grain production shortfall. On the other hand biofuels mandates, relatively neglected in many studies, introduced a new source of grain demand that tightened markets and drove up prices. The disconnect between economic analysis and easily verified facts is a disturbing feature of recent economic analyses of grain markets.