Inequality, Transfers and Growth: New Evidence from the Economic Transition in Poland

This paper challenges the conventional wisdom that inequality in Poland increased markedly during the economic transition that began in 1989-90. Using micro data from the Household Budget Surveys, we find that, after a brief spike in 1989, income and consumption inequality actually declined to below pre-transition levels during 1990-92 and then increased gradually, rising only moderately above pre-transition levels by 1997. In sharp contrast, inequality in labor earnings increased markedly and consistently throughout the 1990-97 period. We find that social transfer mechanisms, including pensions, played an important role in mitigating increases in both overall inequality and poverty. We argue that, from a political economy perspective, transfer mechanisms were well-designed to reduce political resistance to market-oriented reforms in the early years of transition, paving the way for rapid growth. Finally, we provide cross-country evidence from the transition economies that is consistent with our interpretation of the Polish experience and is also consistent with recent work in growth theory which suggests that redistribution that reduces inequality can enhance growth.

Growth and Volatility in an Era of Globalization

We extend the analysis in Kose, Prasad, and Terrones (2005) to provide a comprehensive examination of the cross-sectional relationship between growth and macroeconomic volatility over the past four decades. We also document that while there has generally been a negative relationship between volatility and growth during this period, the nature of this relationship has been changing over time and across different country groups. In particular, we detect major shifts in this relationship after trade and financial liberalizations. In addition, our results show that volatility stemming from the main components of domestic demand is negatively associated with economic growth. Copyright 2005, International Monetary Fund

Stochastic Model and Computational Measures of Batch Process Queuing System with Hetero Multiservers

Multiprocessor system models at present are very important and widely used in modelling transaction processing systems, communication networks, mobile networks, and flexible machine shops with groups of machines. Heterogeneous processors system with one main server and several identical servers are studied. In this paper, reconfiguration and rebooting delays are considered to study the performance measures for both bounded and unbounded system. Numerical results are presented for various performability parameters

The true reinforced random walk with bias

We consider a self-attracting random walk in dimension d=1, in presence of a field of strength s, which biases the walker toward a target site. We focus on the dynamic case (true reinforced random walk), where memory effects are implemented at each time step, differently from the static case, where memory effects are accounted for globally. We analyze in details the asymptotic long-time behavior of the walker through the main statistical quantities (e.g. distinct sites visited, end-to-end distance) and we discuss a possible mapping between such dynamic self-attracting model and the trapping problem for a simple random walk, in analogy with the static model. Moreover, we find that, for any s>0, the random walk behavior switches to ballistic and that field effects always prevail on memory effects without any singularity, already in d=1; this is in contrast with the behavior observed in the static model.Comment: to appear on New J. Phy

A Monopole-Antimonopole Solution of the SU(2) Yang-Mills-Higgs Model

As shown by Taubes, in the Bogomol'nyi-Prasad-Sommerfield limit the SU(2) Yang-Mills-Higgs model possesses smooth finite energy solutions, which do not satisfy the first order Bogomol'nyi equations. We construct numerically such a non-Bogomol'nyi solution, corresponding to a monopole-antimonopole pair, and extend the construction to finite Higgs potential.Comment: 11 pages, including 4 eps figures, LaTex format using RevTe

RTL Implementation of image compression techniques in WSN

The Wireless sensor networks have limitations regarding data redundancy, power and require high bandwidth when used for multimedia data. Image compression methods overcome these problems. Non-negative Matrix Factorization (NMF) method is useful in approximating high dimensional data where the data has non-negative components. Another method of the NMF called (PNMF) Projective Nonnegative Matrix Factorization is used for learning spatially localized visual patterns. Simulation results show the comparison between SVD, NMF, PNMF compression schemes. Compressed images are transmitted from base station to cluster head node and received from ordinary nodes. The station takes on the image restoration. Image quality, compression ratio, signal to noise ratio and energy consumption are the essential metrics measured for compression performance. In this paper, the compression methods are designed using Matlab.The parameters like PSNR, the total node energy consumption are calculated. RTL schematic of NMF SVD, PNMF methods is generated by using Verilog HDL