Land Ownership, Working Capital, and the Agricultural Output: Egypt, 1913-1958.

A simple model is constructed in which short-term credit is needed to finance the purchase of inputs, in which there is bankruptcy risk, and in which we argue were important characteristics of Egyptian agriculture during the first half of this century, result in aggregate agricultural output being dependant on the distribution of land ownership. The main theorical insight is that aggregate agricultural output will be increased by a decrease in the inequality of the distribution of land ownership when returns to scale are decreasing. Testable short- and long-run empirical propositions are formulated and carefully tested on Egyptian data for the 1913-1958 period. We find that, controlling for factor inputs, there is no tradeoff between equity and efficiency for Egyptian agriculture - they go hand in hand in the short run.

The Wage Rate and the Profit Rate in the Price of Production Equation: a New Solution to an Old Problem

The aim of this paper is to demonstrate that, even if Marx's solution to the transformation problem can be modified, his basic concusions remain valid.

The Transmission of Monetary Policy in a Multi-Sector Economy

This paper constructs and estimates a sticky-price, Dynamic Stochastic General Equilibrium model with heterogenous production sectors. Sectors differ in price stickiness, capital-adjustment costs and production technology, and use output from each other as material and investment inputs following an Input-Output Matrix and Capital Flow Table that represent the U.S. economy. By relaxing the standard assumption of symmetry, this model allows different sectoral dynamics in response to monetary policy shocks. The model is estimated by Simulated Method of Moments using sectoral and aggregate U.S. time series. Results indicate 1) substantial heterogeneity in price stickiness across sectors, with quantitatively larger differences between services and goods than previously found in micro studies that focus on final goods alone, 2) a strong sensitivity to monetary policy shocks on the part of construction and durable manufacturing, and 3) similar quantitative predictions at the aggregate level by the multi-sector model and a standard model that assumes symmetry across sectors.

Macroemesures in Computable General Equilibrium Models: a Probabilistic Treatment with an Application to Morocco.

With the help of an illustrative general equilibrium (CGE) model of the Moroccan Economy, we test for the significance of simulation results in the case where the exact macromesure is not known with certainty. This is done by computing lower and upper bounds for the simulation resukts, given a priori probabilities attached to three possible closures (Classical, Johansen, Keynesian). Our Conclusion is that, when there is uncertainty on closures several endogenous changes lack significance, which, in turn, limit the use of the model for policy prescriptions.

How Prescribed Policy Can Mislead when Data Are Defective: a Follow-Up to Srinivasan (1994) Using General Equilibrium.

We highlight an example of considerable bias in officially published input-output data (factor-income shares) by an LDC (Turkey), which many researchers use without question. We make use of an intertemporal general equilibrium model of trade and production to evaluate the dynamic gains for Turkey from currently debated trade policy options and compare the predictions using conservatively adjusted, rather than official, data on factor shares.

Land Ownership, Working Capital, and the Agricultural Output: Egypt, 1913-1958.

A simple model is constructed in which short-term credit is needed to finance the purchase of inputs, in which there is bankruptcy risk, and in which we argue were important characteristics of Egyptian agriculture during the first half of this century, result in aggregate agricultural output being dependant on the distribution of land ownership. The main theorical insight is that aggregate agricultural output will be increased by a decrease in the inequality of the distribution of land ownership when returns to scale are decreasing. Testable short- and long-run empirical propositions are formulated and carefully tested on Egyptian data for the 1913-1958 period. We find that, controlling for factor inputs, there is no tradeoff between equity and efficiency for Egyptian agriculture - they go hand in hand in the short run.

Durable Goods, Inter-Sectoral Linkages and Monetary Policy

Barsky, House and Kimball (2007) show that introducing durable goods into a sticky-price model leads to negative sectoral comovement of production following a monetary policy shock and, under certain conditions, to aggregate neutrality. These results appear to undermine sticky-price models. In this paper, we show that these results are not robust to two prominent and realistic features of the data, namely input-output interactions and limited mobility of productive inputs. When extended to allow for both features, the sticky-price model with durable goods delivers implications in line with VAR evidence on the effects of monetary policy shocks.

Analysis of a New Compact Microstrip

A new compact microstrip antenna element is analyzed. The analysis can accurately predict the resonant frequency, input impedance, and radiation patterns. The predicted results are compared with experimental results and excellent agreement is observed . These antenna elements are more suitable in applications where limited antenna real estate is available

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

A policy model for secure information flow

When a computer program requires legitimate access to confidential data, the question arises whether such a program may illegally reveal sensitive information. This paper proposes a policy model to specify what information flow is permitted in a computational system. The security definition, which is based on a general notion of information lattices, allows various representations of information to be used in the enforcement of secure information flow in deterministic or nondeterministic systems. A flexible semantics-based analysis technique is presented, which uses the input-output relational model induced by an attacker's observational power, to compute the information released by the computational system. An illustrative attacker model demonstrates the use of the technique to develop a termination-sensitive analysis. The technique allows the development of various information flow analyses, parametrised by the attacker's observational power, which can be used to enforce what declassification policies.

Modelling and control of Hammerstein system using B-spline approximation and the inverse of De Boor algorithm

In this article a simple and effective controller design is introduced for the Hammerstein systems that are identified based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a B-spline neural network. The controller is composed by computing the inverse of the B-spline approximated nonlinear static function, and a linear pole assignment controller. The contribution of this article is the inverse of De Boor algorithm that computes the inverse efficiently. Mathematical analysis is provided to prove the convergence of the proposed algorithm. Numerical examples are utilised to demonstrate the efficacy of the proposed approach.

Wavelet based detection of changes in the composition of RLC networks

The current work discusses the compositional analysis of spectra that may be related to amorphous materials that lack discernible Lorentzian, Debye or Drude responses. We propose to model such response using a 3-dimensional random RLC network using a descriptor formulation which is converted into an input-output transfer function representation. A wavelet identification study of these networks is performed to infer the composition of the networks. It was concluded that wavelet filter banks enable a parsimonious representation of the dynamics in excited randomly connected RLC networks. Furthermore, chemometric classification using the proposed technique enables the discrimination of dielectric samples with different composition. The methodology is promising for the classification of amorphous dielectrics.

Cobrança pelo uso da água e o setor de saneamento no Estado de São Paulo

A partir dos objetivos propostos pelas políticas nacionais de saúde, ambientais e de saneamento básico buscou-se analisar os efeitos da cobrança pelo uso da água no setor de saneamento básico, visando identificar possíveis variações causadas por este instrumento econômico no acesso à água, na qualidade do produto ofertado e na qualidade do serviço prestado. Ainda, por se tratar de um serviço público, analisamos a performance técnica das empresas paulistas do setor de saneamento básico na prestação deste serviço por meio da metodologia Data Envelopment Analysis. Esta ferramenta resulta em um indicador de desempenho, com base na melhor relação input/output, ao estabelecer um ranking de eficiência médio a partir das práticas mais eficientes de cada unidade produtiva.

The role of profits in wage determination: evidence from US manufacturing

We estimate the effect of firms' profitability on wage determination for the American economy. Two standard bargaining models are used to illustrate the problems caused by the endogeneity of profits-per-worker in a real wage equation. The profit-sharing parameter can be identified with instruments which shift demando Using information from the input-output table, we create demand-shift variables for 63 4-digit sectors of the US manufacturing sector. The LV. estimates show that profit-sharing is a relevant and widespread phenomenon. The elasticity of wages with respect to profits-per-worker is seven times as large as OLS estimates here and in previous papers. Sensitivity analysis of the profit-sharing parameter controlling for the extent of unionization and product market concentration reinforces our results.

The manufacturing industry in Brazil in the era of global value chains

This article presents a comprehensive and detailed overview of the international trade performance of the manufacturing industry in Brazil over the last decades, emphasizing its participation in Global Value Chains. It uses information from recent available global inputoutput tables such as WIOD (World Input-output database) and TIVA (Trade in Value Added, OECD) as well as complementary information from the GTAP 8 (Global Trade Analysis Project) database. The calculation of a broad set of value added type indicators allows a precise contextualization of the ongoing structural changes in the Brazilian industry, highlighting the relative isolation of its manufacturing sector from the most relevant international supply chains. This article also proposes a public policy discussion, presenting two case studies: the first one related to trade facilitation and the second one to preferential trade agreements. The main conclusions are twofold: first, the reduction of time delays at customs in Brazil may significantly improve the trade performance of its manufacturing industry, specially for the more capital intensive sectors which are generally the ones with greater potential to connection to global value chains; second, the extension of the concept of a “preferential trade partner” to the context of the global unbundling of production may pave the way to future trade policy in Brazil, particularly in the mapping of those partners whose bilateral trade relations with Brazil should receive greater priority by policy makers.