Chinese Wall Security Policy

This project establishes a Chinese wall security policy model in the environment of cloud computing. In 1988 Brewer and Nash proposed a very nice commercial security policy in British financial world. Though the policy was well accepted, but the model was incorrect. A decade later, Dr. Lin provided a model in 2003 that meets Brewer & Nash’s Policy. One of the important components in Cloud computing is data center. In order for any company to store data in the center, a trustable security policy model is a must; Chinese wall security policy model will provide this assurance. The heart of the Chinese Wall Security Policy Model is the concept of Conflict of Interest (COI). The concept can be modeled by an anti-reflexive, symmetric and transitive binary relation. In this project, by extending Dr. Lin’s Model, we explore the security issues in the environment of cloud computing and develop a small system of the Chinese Wall Security Model

Majority-efficiency and Competition-efficiency in a Binary Policy Model

We introduce a general framework in which politicians choose a (possibly infinite) sequence of binary policies. The two competing candidates are exogenously committed to particular actions on a subset of these issues, while they can choose any policy for the remaining issues to maximize their winning probability. Citizens have general preferences over policies, and the distribution of preferences may be uncertain. We show that a special case of the model, the weighted-issue model, provides a tractable multidimensional model of candidate competition that can generate (i) policy divergence in pure and mixed strategies, (ii) adoption of minority positions, and (iii) inefficient outcomes.multidimensional policy, voting, citizen-candidate, normative analysis of political competition

A Study of Panel Logit Model and Adaptive Neuro-Fuzzy Inference System in the Prediction of Financial Distress Periods

The purpose of this paper is to present two different approaches of financial distress pre-warning models appropriate for risk supervisors, investors and policy makers. We examine a sample of the financial institutions and electronic companies of Taiwan Security Exchange (TSE) market from 2002 through 2008. We present a binary logistic regression with paned data analysis. With the pooled binary logistic regression we build a model including more variables in the regression than with random effects, while the in-sample and out-sample forecasting performance is higher in random effects estimation than in pooled regression. On the other hand we estimate an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and Generalized Bell (Gbell) functions and we find that ANFIS outperforms significant Logit regressions in both in-sample and out-of-sample periods, indicating that ANFIS is a more appropriate tool for financial risk managers and for the economic policy makers in central banks and national statistical services

CONJOINT ANALYSIS OF GROUNDWATER PROTECTION PROGRAMS

Three conjoint models-a traditional ratings model, a ratings difference specification, and a binary response model-were used to value groundwater protection program alternatives. The last, which is virtually identical to a dichotomous choice contingent valuation specification, produced the smallest value estimates. This suggests that the conjoint model is very sensitive to model specifications and that traditional conjoint models may overestimate economic value because many respondents are not in the market for the commodity being valued.Resource /Energy Economics and Policy,

Modeling Violence against Women in India: Theories and Problems

This paper examined the following issues: 1. Is ‘violence against women’ a variable? What kind of variable is it? 2. Is it theoretically plausible to model ‘violence against women’? 3. If it is theoretically plausible to model ‘violence against women’, then is it feasible to estimate such a model and perform simulation exercises? Following are findings: 1. The decision to perpetrate ‘violence against women’ is a binary variable, which takes value unity (1) when the decision is ‘yes’ and zero (0) when the decision is ‘no’. 2. It is theoretically plausible to construct the models of estimating and forecasting the probability of occurrence of ‘violence against women’ facing a typical woman in a particular society on the basis of necessary information. 3. It is not feasible in practice to apply above models for the purposes of policy-formulation and policy-simulation in India because of absence of compilation or systematic compilation of the data on ‘violence against women’ and the variables determining ‘violence against women’

An Inflated Ordered Probit Model of Monetary Policy: Evidence from MPC Voting Data

Even in the face of a continuously changing economic environment, interest rates often remain unadjusted for long periods. When rates are moved, the norm is for a series of small unidirectional discrete basis-point changes. To explain these phenomena we suggest a two-equation system combining a “long-run” equation explaining a binary decision to change or not change the interest-rate, and a “shortrun” one based on a simple monetary policy rule. We account for unobserved heterogeneity in both equations, applying the model to unique unit-record level data on the voting preferences of Bank of England Monetary Policy Committee (MPC) members.Interest rates; voting; discrete data; ordered models; inflated outcomes; monetary policy committee

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEBIJAKAN HEDGING DENGAN MENGGUNAKAN INSTRUMEN DERIVATIF VALUTA ASING (Studi Empiris pada Perusahaan Non-finansial yang Terdaftar di BEI Periode 2010-2014)

This study aimed to examine the effect of leverage, growth opportunity, firm size, liquidity, institutional ownership, and managerial ownership on probability of hedging policy. Sample of this study used non-financial companies listed on Indonesia Stock Exchange during 2010-2014. The sampling technique used in this research is purposive sampling method covering 44 companies as samples. Hypothesis testing is using binary logistic regression models which the dependent variabel in categories. The category from companies that use hedging policy and companies that not use hedging policy. The analysis method used in this study is Overall Model Fit, Nagelkerke’s R Square, Hosmer Lemesehow Goodness of Fit Test, Classification Table and binary logistic regression Analysis. Based on the results using binary logistic regression analysis, leverage and growth opportunity has positive effect and significant on probability of hedging policy as well as managerial ownership variable had significant negative effect on probability of hedging policy. In addition, the results did not support that firm size, liquidity, and institutional ownership had significant effect on probability of hedging policy. Moreover it found that the value of the nagelkerke’s R square is 20,8%. This means that 79,2% is explained by other variables outside the model

Spatial random multiple access with multiple departure

We introduce a new model of spatial random multiple access systems with a non-standard departure policy: all arriving messages are distributed uniformly on a finite sphere in the space, and when a successful transmission of a single message occurs, the transmitted message leaves the system together with all its neighbours within a ball of a given radius centred at the message's location. We consider three classes of protocols: centralised protocols and decentralised protocols with either ternary or binary feedback; and analyse their stability. Further, we discuss some asymptotic properties of stable protocols

Wages and employment in non-farm agricultural activities: a livelihood strategy in Nicaragua.

This article analyzes the indices for nonfarm agricultural activities, which combine agricultural activities with both employment and wages. They were made with panel data of the Living Measurement Standard Survey (1993, 1998, 2001 and 2005) and they were processed with econometric model as a parametric technique (Binary dependent variable model). The trend indices explain the varied combination of nonfarm and farming agricultural activities. In summary, when the economic public policy makers promote preventative measures in the labour market, we see that indices for nonfarm agricultural activities grow. In fact, small farmers use first, second and third nonfarm employment as livelihood strategies for clashing the public policy restrictive.RMEA, RMNFA, RSEA, RSENFA, RTEA, RTNFA, RMWAI, RMWNFAI, RSWAI, RSWNFAI, RTWAI, RTWNFAI, Community/Rural/Urban Development, Labor and Human Capital, Research Methods/ Statistical Methods,