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Abstract-Software effort estimation is the process of predicting the number of persons required to build a software system. Effort estimation is calculated in terms of person per month for the completion of a project. If any new project is launched into a market or in industry, then cost and effort of a new project will be estimated. In this context, a number of models have been proposed to construct the effort and cost estimation. Accurate software effort estimation is a challenge within the software industry. In this paper we propose a novel method, Grey Relational Analysis (GRA) to estimate the effort of a particular project. To estimate the effort of a project, traditional methods have been used as algorithmic models to evaluate the parameters of the basic model i.e. basic COCOMO model. In this paper, to show the minimum error rate we have used Grey Relational Analysis (GRA) to predict the effort estimation on Kemerer dataset. When compared to the traditional techniques for estimation, the proposed method proved better results. The efficiency of the proposed system is illustrated through experimental results.

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This study examines the role of financing constraints in explaining outward foreign direct investment (FDI) using unique firm-level panel data on Indian manufacturing during the period 2007–2014. We consider the role of both internal and external finance, and employ instrumental variable probit and Tobit models to examine financing constraints in outward FDI decisions and intensity. We find that internal finance impacts the likelihood of outward FDI. Further, using count data models, we examine financing constraints in determining strategies regarding a firm's number of affiliates abroad. Our findings reveal that firms with greater cash flows and liquidity are likely to have more foreign affiliates.

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