The Housing Boom and Its Effect on Farmland Acreage

This paper examines farmers land ownership decision to keep their farmland or sell the acreage to a non-agricultural enterprise. The boom in housing demand during the early 21st century caused a subsequent rise in land demand by housing construction companies. This, in turn, has significant effects on farmers choice to sell their farmland endowment and leave farming. Data from several public sources, including the USDA-NASS, U.S. Census, BLS, and BEA-REIS, is used to analyze the relationship of farm acreage with housing permit values. The Arellano-Bond dynamic panel estimator is used within a GMM framework to examine land ownership behavior of forward-looking farmers. Results indicate that a rise in demand for new housing significantly influences a farmers behavior to transfer agricultural acreage out of farming.farmland ownership, housing values, dynamic panel estimator, GMM, forward-looking farmer, Land Economics/Use,

The Impact of the Internet on Information Searching and Demand for Traditional Information Resources

The Internet is an efficient information search tool whose growth may have caused a structural change in information search and acquisition behaviors. This study investigates the effects of growing Internet accessibility on these behaviors. Using U.S. public library circulation counts to quantify changes in the use of information resources, the analysis indicates that greater Internet accessibility contributes to increased demand for traditional information sources. That is, a complementary relationship exists between Internet and traditional sources. Further, the results suggest that limiting Internet access can reduce the demand for traditional content. These outcomes imply that improvements in Internet accessibility can have profound effects on human capital development.

Spatial Analysis of Market Linkages in North Carolina Using Threshold Autoregression Models with Variable Transaction Costs

In North Carolina, where soybeans and corn are the two primary crops, the recent increase in the demand for U.S. corn has triggered a shift of farm acreage from soybeans to corn, leading to a rapid rise in prices of both commodities. However, the rate of the price changes, as well as the price level, is significantly different in markets that are located in different parts of the state. This study extends the literature that examines linkages between spatially separated markets by using a threshold autoregressive model with a less restrictive assumption for estimating the transaction cost neutral band -- the band within which trade is not profitable. This generalization allows the neutral band of transactions costs to change according to various external factors, including fuel costs and seasonality. The estimation results indicate that for longer time series data, variable thresholds models statistically outperform the constant thresholds specification, and may provide a better representation of corn and soybean price data. Additionally, impulse response functions that use the asymmetric variable threshold model parameters indicate that the magnitude of the shock as well as the time-to-price-parity-equilibrium in the linked markets may be underestimated if a constant thresholds specification is implemented.threshold autoregression, spatially separated markets, impulse response, neutral band, Demand and Price Analysis, Marketing, Q11, Q13,

SURE Impact? An Empirical Investigation of Moral Hazard and Adverse Selection Behavior

The Supplemental Revenue Assistance Payments (SURE) program, enacted under the 2008 Farm Bill, is intended to provide indemnity payments to producers whose crop losses exceed 50% of their historical average yields. However, indemnification does not require that the farm is located in a region designated a disaster relief area -- a provision that can create significant moral hazard incentives. This study is the first to perform an empirical analysis of possible moral hazard behavior in corn, soybean, and wheat markets in response to the SURE program. Results suggest that an increase in crop insurance demand after the enactment of SURE may be due to the program's moral hazard incentives.Agricultural and Food Policy, Farm Management,

Automatic Discovery of Prior Art: Big Data to the Rescue of the Patent System, 16 J. Marshall Rev. Intell. Prop. L. 44 (2016)

In this research, we offer a fresh approach as to determining prior art. We do this by using Big Data methods. More specifically, we apply a model which constructs the semantic space of patents, in which all published patents and patent applications are arranged according to semantic similarities between each other. Our model provides a clear indication of how closely patents stand in relation to existing technologies, which we refer to as Near Inventions (“NI”). Our model exposes a certain level of deficiency when it comes to the disclosure, by patent applicants, of NIs. One conclusion which we draw from this approach is that there is no consistency among applicants when it comes to citing NIs. Another conclusion is that the more “densely populated” the semantic neighborhood of an invention is, the more rigorous the examination needs to be regarding its patentability

Basis Volatilities of Corn and Soybean in Spatially Separated Markets: The Effect of Ethanol Demand

The 2006 spike in corn-based ethanol demand has contributed to the increase in basis volatility in corn and soybean markets across the United States, which has, to a significant degree, led to the observed large jumps in the prices of the two commodities. Despite the overall rise in basis volatility, there remain differences in the degree of volatility that exists across spatially separated markets, which might be caused by factors such as transportation costs, seasonality, and time-to-delivery. The focus of this study is threefold first, this work models basis data for six corn and soybean markets by using a multivariate GARCH model that incorporates the spatial linkages of these markets; next, the model is used to investigate whether the increase in ethanol demand has significantly aided in the rise of basis volatilities; and last, the spatio-temporal linkages among basis volatilities in different markets are examined under various scenarios of spot-price shocks.basis, spatially separated markets, multivariate GARCH, volatility, Agricultural Finance, Demand and Price Analysis, Q11, Q14, G13,

HOMOTOPY CONTINUATION METHODS FOR PHASE RETRIEVAL

In this dissertation, we discuss the problem of recovering a signal from a set of phaseless measurements. This type of problem shows up in numerous applications and is known for its numerical difficulty. It finds use in X-ray Crystallography, Microscopy, Quantum Information, and many others. We formulate the problem using a non-convex quadratic loss function whose global minimum recovers the phase of the measurement.Our approach to this problem is via a Homotopy Continuation Method. These methods have found great use in solving systems of nonlinear equations in numer- ical algebraic geometry. The idea is to initialize the solution of a related system at a known global optimal, then continuously deform the criterion and follow the solution path until we find the minimum of the desired loss function. We analyze convergence properties and asymptotic results for these algorithms, as well as gather some numerical statistics. The main contribution of this thesis is deriving conditions for convergence of the algorithm and an asymptotic rate for when these conditions are satisfied. We also show that the algorithm achieves good numerical accuracy. The dissertation is split into several chapters, and further divided by the real and complex case. Chapter 1 gives some background to Abstract Phase Retrieval and Homotopy Continuation Methods. Chapter 2 covers the nature of the algorithm (named the Golden Retriever), gives a summary and description of the theoretical results, and shows some numerical results. Chapter 3 covers the details of the derivation and results in the real case, and Chapter 4 covers the same for the complex case