Profit Related Loans for Economically Disadvantaged Regions

There is an increasing recognition that economically disadvantaged areas do not have an inherent capacity to regenerate economic activity or to deliver automatically socially propitious outcomes. In such circumstances, there might be a strong case for public sector intervention of various types. In what follows we a case for the provision of financial resources for the establishment or consolidation of community social, and other, regional enterprises. The circumstances underlying the impotence of markets to solve financing issues are explored, and some attention is given to historical attempts to address the problem. Most importantly, we outline a potential new approach for the public sector in this area. An important and novel aspect of the exercise involves the government providing some proportion of the required finance in the form of a loan to be repaid by the enterprise only when and if the project becomes economically successful. This form of government intervention, known as income related loans, is designed to limit the extent of economic risks faced by the relevant enterprise, and has the desirable equity characteristic of repaying to taxpayers some return to their investment. Through reference to the Higher Education Contribution Scheme it is explained that the essential bases of this form of public sector approach to financing investment is well established, both conceptually and in administrative terms.community investment; income related loans

Comparison of Optimal Control Solutions in a Labor Market Model

In this paper a variety of computational optimal control techniques are compared on a complicated nonlinear discrete-time model. We use a labor market model with the objective of trying to obtain an unemployment rate objective, using an active labor market program as a control. In reality the control is constrained as only limited proportion of the unemployment can attend the labor market program. A variety of computational optimal control techniques are applied. The techniques include numerically linearizing the model and using standard linear quadratic optimal control and applying this to the nonlinear model; model based predictive control; and stacking the model over time and using optimisation techniquesLabour market policies; Optimal Control.

REVERSE SHOOTING IN A MULTI-DIMENSIONAL SETTING

This paper investigates the properties of dynamic solutions that have been derived using the well-known reverse-shooting algorithm. Given an arbitrary large-scale model about which we have limited information, how successful is the algorithm likely to be in solving this model? We address this question using a range of investment models, both linear and non-linear. By extending the investment models to allow for multidimensional specifications of the capital stock, we are able to examine the computational efficiency of the reverse shooting algorithm as the dimensionality of the capital stock is allowed to increase. Our approach provides insights into how the complexity of the solutions to a broad range of macroeconomic models increases with the dimensionality of the models.Macroeconomics; Reverse shooting; Saddlepath instability; Computational techniques; Investment models

Solving Macroeconomic Models with "Off-the-Shelf" Software: An Example of Potential Pitfalls

When working with large-scale models or numerous small models, there can be a temptation to rely on default settings in proprietary software to derive solutions to the model. In this paper we show that, for the solution of non-linear dynamic models, this approach can be inappropriate. Alternative linear and non-linear specifications of a particular model are examined. One version of the model, expressed in levels, is highly non-linear. A second version of the model, expressed in logarithms, is linear. The dynamic solution of each model version has a combination of stable and unstable eigenvalues so that any dynamic solution requires the calculation of appropriate “jumps” in endogenous variables. We can derive a closed-form solution of the model, which we use as our "true" benchmark, for comparison with computational solutions of both linear and non-linear models. Our approach is to compare the "goodness of fit" of reverse-shooting solutions for both the linear and non-linear model, by comparing the computational solutions with the benchmark solution. Under the basic solution method with default settings, we show that there is significant difference between the computational solution for the non-linear model and the benchmark closed-form solution. We show that this result can be substantially improved using modifications to the solver and to parameter settings.Solving non-linear models, reverse-shooting, computational economics, computer software

Reverse-Shooting versus Forward-Shooting over a Range of Dimensionalities

This paper investigates the properties of dynamic solutions that have been derived using the well-known reverse-shooting and forwardshooting algorithms. Given an arbitrary large-scale model about which we have limited information, how successful are the algorithms likely to be in solving this model? We address this question using a range of investment models, both linear and non-linear. By extending the investment models to allow for multi-dimensional specifications of the capital stock, we are able to examine the computational efficiency of the competing algorithms as the dimensionality of the capital stock is allowed to increase. Our approach provides insights into how the complexity of the solutions to a broad range of macroeconomic models increases with the dimensionality of the models.Macroeconomics; Reverse-shooting; Forward-shooting; Saddlepath instability; Computational techniques; Investment models.

The Two Unanswered Questions of Illinois v. Caballes: How to Make the World Safe for Binary Searches

This Article discusses the recent Supreme Court decision Illinois v. Caballes, which held that the Fourth Amendment does not bar the use of drug-detection dogs, even in the absence of reasonable suspicion. It argues that the Caballes case paves the way for widespread and indiscriminant use of a new type of surveillance known as a binary search. A binary search is defined as a search which provides the law enforcement official with no information about the subject other than whether or not illegal activity is present. Drug-detection dogs are one example of a binary search, but there are many others which are being developed, such as portable gun detectors or software protocols that sift through all e-mails passing through an internet service provider looking for child pornography. Since the Caballes case did very little in the way of defining binary searches and discussing the appropriate limitations (if any) on their use, the Article seeks provide some guidance to courts in evaluating the constitutionality of binary searches in the future. The Article begins by discussing the history of the binary search doctrine, focusing on its application to drug-detection dogs, which up until now have been the most common form of binary search in use. The Article then analyzes the Caballes decision itself, examining what it does and does not resolve about the constitutionality of binary searches. Finally, the Article attempt to resolve the important unanswered questions in Caballes: first, how accurate does a surveillance technique have to be in order to be considered a binary search, and second, how does the Fourth Amendment prohibition against unreasonable seizures limit or prevent the widespread use of binary searches

Information Visualization Of An Agent-Based Financial System Model

This paper considers the application of information visualization techniques to an agent-based model of a financial system. The minority game is a simple agent-based model which can be used to simulate the events in a real-world financial market. To aid understanding of this model, we can apply information visualization techniques. Treemap and sunburst are two such information visualization techniques, which previous research tells us can effectively represent information similar to that generated by the minority game. Another information visualization technique, called logical fisheye-lens, can be used to augment treemap and sunburst, allowing users to magnify areas of interest in these visualizations. In this paper, treemap and sunburst, both with and without fisheye-lens, are applied to the minority game, and their effectiveness is evaluated. This evaluation is carried out through an analysis of users performing various tasks on (simulated) financial market data using the visualization techniques. A subjective questionnaire is also used to measure the users’ impressions of the visualization techniques.Dynamic Models, Minority Game, Visualization

A formalized object oriented user driven approach using business forms

Although object-orientation exhibits many promises, there exists many fundamental areas that need to be addressed. Two of these areas are the widespread acceptance of the object mindset, and interactive user involvement in the object oriented business system development process. First, the mindset must grow and be extended not only by the engineering industry but also by the ever expanding service industry. Second, effective, efficient, flexible user driven tools must be developed, in the form of development approaches to reduce the reliance on scarce human resources. In order to accomplish both areas, the technology user is the key element. This research in progress concentrates on the development of a formalized business form user-driven approach using an object oriented analysis view. The resulting analysis produces an initial conceptual object model that is used by the users and designers for further object analysis, object design, design evolution, and object oriented application domain identification