Network dependence in multi-indexed data on international trade flows

Faced with the problem that conventional multidimensional fixed effects models only focus on unobserved heterogeneity, but ignore any potential cross-sectional dependence due to network interactions, we introduce a model of trade flows between countries over time that allows for network dependence in flows, based on sociocultural connectivity structures. We show that conventional multidimensional fixed effects model specifications exhibit cross-sectional dependence between countries that should be modeled to avoid simultaneity bias. Given that the source of network interaction is unknown, we propose a panel gravity model that examines multiplenetwork interaction structures, using Bayesian model probabilities to determine those most consistent with the sample data. This is accomplished with the use of computationally efficient Markov Chain Monte Carlo estimation methods that produce a Monte Carlo integration estimate of the log-marginal likelihood that can be used for model comparison. Application of the model to a panel of trade flows points to network spillover effects, suggesting the presence of network dependence and biased estimates from conventional trade flow specifications. The most important sources of network dependence were found to be membership in trade organizations, historical colonial ties, common currency, and spatial proximity of countries.Series: Working Papers in Regional Scienc

Cycle-Level Products in Equivariant Cohomology of Toric Varieties

In this paper, we define an action of the group of equivariant Cartier divisors on a toric variety X on the equivariant cycle groups of X, arising naturally from a choice of complement map on the underlying lattice. If X is nonsingular, this gives a lifting of the multiplication in equivariant cohomology to the level of equivariant cycles. As a consequence, one naturally obtains an equivariant cycle representative of the equivariant Todd class of any toric variety. These results extend to equivariant cohomology the results of Thomas and Pommersheim. In the case of a complement map arising from an inner product, we show that the equivariant cycle Todd class obtained from our construction is identical to the result of the inductive, combinatorial construction of Berline-Vergne. In the case of arbitrary complement maps, we show that our Todd class formula yields the local Euler-Maclarurin formula introduced in Garoufalidis-Pommersheim.Comment: 15 pages, to be published in Michigan Mathematical Journal; LaTe

Conventional versus network dependence panel data gravity model specifications

Past focus in the panel gravity literature has been on multidimensional fixed effects specifications in an effort to accommodate heterogeneity. After introducing conventional multidimensional fixed effects, we find evidence of cross-sectional dependence in flows. We propose a simultaneous dependence gravity model that allows for network dependence in flows, along with computationally efficient Markov Chain Monte Carlo estimation methods that produce a Monte Carlo integration estimate of log-marginal likelihood useful for model comparison. Application of the model to a panel of trade flows points to network spillover effects, suggesting the presence of network dependence and biased estimates from conventional trade flow specifications. The most important sources of network dependence were found to be membership in trade organizations, historical colonial ties, common currency and spatial proximity of countries.Series: Working Papers in Regional Scienc

Estimates of the impact of static and dynamic knowledge spillovers on regional factor productivity

We develop an empirical approach to examine static and dynamic knowledge externalities in the context of a regional total factor productivity relationship. Static externalities refer to current period scale or industry-size effects which have been labeled localization externalities or region-size effects known as agglomeration externalities. Dynamic externalities refer to the relationship between accumulated or prior period knowledge and current levels of innovation, where past learning-by-doing makes innovation positively related to cumulative production over time. Our empirical specification allows for the presence of both static and dynamic externalities, and provides a way to assess the relative magnitude of spillovers associated with spillovers from these two types of knowledge externalities. The magnitude of own-region impacts and other-region (spillovers) can be assessed using scalar summary measures of the own- and cross-partial derivatives from the model. We find evidence supporting the presence of dynamic externalities as well as static, and our estimates suggest that dynamic externalities may have a larger magnitude of impact than static externalities.

Building a prosperous future in which agriculture uses and produces energy efficiently and effectively

Our new challenge, opportunity, and responsibility, is energy. The USDA is determined to apply the talent and technology of agriculture to bioenergy, and others should make a point of directing their energies to support this. The road forward toward our energy future is Science and Education. This is how we can move beyond a petroleum economy to make oil dependence a thing of the past, and safeguard our environment for future generations. The USDA has started the process of getting researchers together for a large, long-term cooperative effort. We all must take actions to make sure lab results get moved toward the market, with technology transfer partnerships with industry or university spin-off startup