The Claiborne Corridor: Mid-Anchor Business Profiles 2014

The New Orleans Business Alliance and the Mayor’s Office of Place-based Planning are working closely with the Livable Claiborne Communities Initiatives to encourage the maintenance, development and expansion of businesses throughout the city with a special focus on the LCC. The reports that follow identify mid-anchor businesses that have contributed to the social and economic wealth of the City of New Orleans for, in some cases, hundreds of years. The hope is that these businesses will be supported through new City initiatives to improve façades, marketability and expand employment opportunities. The research and resources provided by the students at UNO will support these efforts and hopefully contribute to the reinvestment and redevelopment of the new New Orleans

The Claiborne Corridor: Mid-Anchor Business Profiles 2014

The New Orleans Business Alliance and the Mayor’s Office of Place-based Planning are working closely with the Livable Claiborne Communities Initiatives to encourage the maintenance, development and expansion of businesses throughout the city with a special focus on the LCC. The reports that follow identify mid-anchor businesses that have contributed to the social and economic wealth of the City of New Orleans for, in some cases, hundreds of years. The hope is that these businesses will be supported through new City initiatives to improve façades, marketability and expand employment opportunities. The research and resources provided by the students at UNO will support these efforts and hopefully contribute to the reinvestment and redevelopment of the new New Orleans

Potential Impacts of Free Trade Areas and Common Currency on Sustainable Agricultural Export in Africa

Peer reviewedPublisher PD

Estimating Panel Data Models in the Presence of Endogeneity and Selection

We consider estimation of panel data models with sample selection when the equation of interest contains endogenous explanatory variables as well as unobserved heterogeneity. We offer a detailed analysis of the pooled two-stage least squares (pooled 2SLS) and fixed effects-2SLS (FE-2SLS) estimators and discuss complications in correcting for selection biases that arise when instruments are correlated with the unobserved effect. Assuming that appropriate instruments are available, we propose several tests for selection bias and two estimation procedures that correct for selection in the presence of endogenous regressors. The first correction procedure is valid under the assumption that the errors in the selection equation are normally distributed, while the second procedure drops the normality assumption and estimates the model parameters semiparametrically. In the proposed testing and correction procedures, the error terms may be heterogeneously distributed and serially dependent in both selection and primary equations. Correlation between the unobserved effects and explanatory and instrumental variables is permitted. To illustrate and study the performance of the proposed methods, we apply them to estimating earnings equations for females using the Panel Study of Income Dynamics data and perform Monte Carlo simulations.Fixed Effects, Instrumental Variables, Sample Selection, Mills Ratio, Semiparametric

Can complexity help us better understand risk?

Undesirable rare and new events are hard to predict and their costs are hard to quantify. The science of complex systems gives deep insights into why some events are impossible to predict in the long term. Computer simulation is evolving as a way to understand the behaviour of complex systems and can be used to investigate distributions of rare events and risks. Simulation has its own risks; for example, the “ can you trust it? ” problem means that simulations can be misleading. Many complex systems have multi-dimensional multi-level structure, with Type-1 dynamics represented by changes in numerical functions, and Type-2 dynamics, represented by changes in relational structure. This may help to analyse and manage risk. The science of complex systems will increasingly inform those who design, manage, plan, and control complex systems, and it undoubtedly can contribute to the science of risk