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The purpose of this paper is to build an easy to implement, pragmatic and parsimonious yet accurate model to determine an exposure at default (EAD) distribution for CCL (contingent credit lines) portfolios.

Using an algorithm similar to the basic CreditRisk+ and Fourier Transforms, the authors arrive at a portfolio level probability distribution of usage.

The authors perform a simulation experiment which illustrates the convolution of two portfolio segments to derive an EAD distribution, chosen randomly from Moody's Default Risk Service (DRS) database of CCLs rated as of 12/31/2008, to derive an EAD distribution. The standard deviation of the usage distribution is found to decrease as we increase the number of puts used, but the mean value remains relatively stable, as the extreme points converge towards the mean to produce a shrinkage in the spread of the distribution. The authors also observe, for the sample portfolio, that an increase in the additional usage rate level also increases the volatility of the associated exposure distribution.

This model, in conjunction with internal bank financial institution research, can be used for banks' EAD estimation as mandated by Basel II for bank CCL portfolios, or implemented as part of a Solvency II process for insurers exposed to credit sensitive unfunded commitments. Apart from regulatory requirements, distributions of stochastic exposure generated can be inputs for different economic capital models and stress testing procedures used to capture an accurate risk profile of the portfolio, as well as providing better insights into the problem of managing liquidity risk for a portfolio of CCLs and similar exposures.

In‐spite of the large volume of CCLs in portfolios of financial institutions all (for commercial banks holding these as well as for insurance companies having analogous exposures), paucity of EAD models, unsuitability of external data and inconsistent internal data with partial draw‐downs have been a major challenge for risk managers as well as regulators in managing CCL portfolios.

The chapter's scope focuses on examining the manufacturing and consumption practices of plastic-related materials, which are nature-resistant and do not decompose quickly, and the efforts of formal institutions to encourage the recycling of these materials for the environmental sustainability of the metropolis. The chapter examined how effective recycling policies have been in enabling the reuse of plastics and related materials and their effects on the environment. This chapter uses the green theory as a theoretical approach to explain the relationship between man and the environment. The chapter employed a qualitative approach to research with reliance on secondary sources of data. This chapter's findings revealed that while policies are geared towards improving the recycling culture in Lagos, Nigeria, those policies needed to be adequately enacted by the government with the appropriate structure to enable them to achieve the stated objectives, thus rendering them ineffective. In this chapter, recommendation centers, amongst others, that the government of Lagos state, Nigeria, should adopt extended producer responsibility (EPR) to hold manufacturers and importers accountable for the product's life cycle and invest in quality public–private partnerships (PPPs) in recycling to ensure environmental sustainability of the metropolis.

The Unorganised Manufacturing Sector (UMS) in India is a diverse and vibrant segment of the economy, encompassing a wide array of enterprises that vary significantly in terms of input base, financial resources, and technical expertise. This sector is responsible for producing a broad spectrum of products, ranging from traditional clay pots and intricately embroidered garments to sophisticated mobile chips and essential motor vehicle components. This production not only caters to the consumer goods market but also supplies intermediate products to larger manufacturing industries. Furthermore, many of these products are integral to the global value chain, highlighting the sector's extensive reach and significance. Over the past three decades, the UMS has navigated through two distinct policy landscapes: a ‘protectionist’ regime until the mid-1980s and a ‘liberalised’ regime commencing in 1991. Recognising the challenges these units face in the competitive landscape ushered in by economic liberalisation, the government has implemented various direct policy measures since 2000 aimed at supporting the sector. Against this backdrop, this study aims to scrutinise the growth performance of the UMS in India focussing on employment, gross value added, and labour productivity at the two-digit activity level utilising unit-level data from the National Sample Survey Office (NSSO) spanning from 1984–85 to 2015–16. It also seeks to classify these activities based on their performance in terms of labour productivity and employment generation. Furthermore, the study endeavours to identify distinguishing characteristics of activities that have been successful in generating new employment in recent years.