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This paper investigates the impact of CO2 vs CO2 “equivalents” (CO2e) by analyzing fugitive emissions, with a particular focus on Fluorinated gases (F-gases), arising from refrigerant leakages in buildings. F-gases are an especially powerful set of GHGs with a global warming potential hundreds to thousands of times greater than that of CO2.

The significant impact of CO2e is tested by means of an empirical study with current consumption data from German food retail warehouses. This evaluation involves the analysis of the Carbon Risk Real Estate Monitor's country- and property-type specific pathway, coupled with a paired samples t-test to examine the hypotheses. The assessment is undertaken by evaluating the type of gas and the amount of leakage reported in the baseline year, subsequently converting these values to CO2e units.

On average, F-gases account for 40% of total building emissions and nearly 45% of cumulative emissions until 2050. In light of ongoing climate change and the rising number of Cooling Degree Days (CDDs), it becomes imperative to assess both the environmental and economic impact of F-gases and to transition toward environmentally friendly refrigerants.

The analysis sheds light on the seldom-addressed threats posed by CO2e emissions stemming from refrigerant losses. By identifying these threats, investors can devise strategies to mitigate potential future costs and carbon risks.

Energy poverty is a global phenomenon, but its prevalence is enormous in most African countries, with a potential impact on quality of life. This study aims to investigate the impact of energy poverty on the shadow economy.

The study uses panel data from 45 countries in Africa over a period of 1996–2018. Using panel cointegrating regression and panel vector auto-regression model in the generalized method of moments technique.

This study provides that energy poverty deepens the size of the shadow economy in Africa. It also documents that there is a bidirectional causality between shadow economy and energy poverty. Therefore, the two variables can predict each other.

The study suggests that lack of access to clean and modern energy services contributes to the depth of the shadow economy in Africa. African authorities are advised to strengthen rural and urban electrification initiatives by providing adequate energy infrastructure so as to reduce the level of energy poverty in the region. To ensure energy sustainability delivery, the study proposes that the creation of national and local capacities would be the most effective manner to guarantee energy accessibility and affordability. Also, priorities should be given to the local capital mobilization and energy subsidies for the energy poor. Energy literacy may also contribute to the sustainability and the usage of modern energy sources in Africa.

Previous studies reveal that income inequality contributes to the large size of shadow economy in developing economies. However, none of these studies analyzed the role of energy poverty and its implications for underground economic operations. Inadequate access to modern energy sources is likely to deepen the prevalence of informality in developing nations. Based on this, this study provides fresh evidence on the implications of energy deprivation on the shadow economy in Africa using a heterogeneous panel econometric framework. The study contributes to the literature by advocating that the provision of affordable modern energy sources for rural and urban settlements, and the creation of good energy infrastructure for the firms in the formal economy would not only improve the quality of life but also important to discourage underground economic operations in developing economies.

Improving the competitiveness of East Africa's rice industries necessitates increased and viable production of rice of the quality desired by consumers. This paper aims to understand consumer preferences for rice quality attributes in Uganda and Kenya to inform the countries' rice breeding programs and value chain development interventions.

Rice samples are obtained from retail markets in various districts/counties across the two countries. The samples are analyzed in a grain quality laboratory for the rice's physicochemical characteristics and the resulting data are used to non-parametrically estimate hedonic price functions. District/county dummies are included to account for potential heterogeneity in consumer preferences.

Ugandan consumers are willing to pay a price premium for rice with a relatively high proportion of intact grains, but the consumers discount chalkiness. Kenyan consumers discount high amylose content and impurities. There is evidence of heterogeneity in consumer preferences for rice in Mbale, Butaleja and Arua districts of Uganda and in Kericho and Busia counties of Kenya.

The study makes a novel contribution to the literature on consumer preferences for rice in East Africa by applying a hedonic pricing model to the data generated from a laboratory analysis of the physicochemical characteristics of rice samples obtained from the market. Rather than base our analysis on consumers' subjective sensory assessment of the quality characteristics of rice, standard laboratory methods are used to generate the data, which enables a more objective assessment of the relationship between market prices and the quantities of attributes present in the rice samples.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency is determined by the configuration of factor prices. A dynamic model of the firm is developed under the assumption that managerial skill contributes to technical efficiency. Dynamic analysis shows that the firm can never be technically efficient if it maximizes profits, the steady state is always inefficient, and it is locally stable. In terms of empirical analysis, we show how likelihood-based methods can be used to uncover, in a semi-non-parametric manner, important features of the inefficiency-management relationship using a flexible functional form accounting for the endogeneity of inputs in a production function. Managerial compensation can also be identified and estimated using the new techniques. The new empirical methodology is applied in a data set previously analyzed by Bloom and van Reenen (2007) on managerial practices of manufacturing firms in the UK, US, France and Germany.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

Global warming exacerbates sea level rise and extreme weather events that cause severe flooding, resulting in lost productivity and property damage. To reduce the impact of flooding, residents are avoiding purchasing homes in high-risk areas. There are numerous studies on the relationship between flood hazards and housing prices in developed countries, but few in developing countries. Therefore, this study aims to investigate the relationship between flood hazards and housing prices in Hat Yai, Songkhla, Thailand.

This study uses spatial-lag, spatial error and spatial autoregressive lag and error (SARAR) models to analyze the effect of flood risk on property prices. The main analysis examines the degree of flood risk and housing rental prices from our survey of 380 residences. To test the robustness of the results, the authors examine a different data set of the same samples by using the official property valuation from the Ministry of Finance and the flood risk estimated by the Southern Natural Disaster Research Center.

The SARAR model was chosen for this study because of the occurrence of spatial dependence in both dependent variable and the error term. The authors find that flood risk has a negative impact on property prices in Hat Yai, which is consistent with both models.

This study is one of the first to use spatial econometrics to analyze the impact of flood risk on property prices in Thailand. The results of this study are valuable to policymakers for benefit assessment in cost–benefit analysis of flood risk avoidance or reduction strategies and to the insurance market for pricing flood risk insurance.

This study aims to address three research questions pertaining to climate neutrality within the supply chain of metal and mining industry: (1) How can an organization implement practices related to climate neutrality in the supply chain? (2) How do members of the supply chain adopt different measures and essential processes to assist an organization in responding to climate change-related concerns? (3) How can the SAP-LAP framework assist in analyzing and proposing solutions to attain climate neutrality?

To address the proposed research questions concerning climate neutrality, this study employs a case study approach utilizing the SAP-LAP (situation, actor, process–learning, action, performance) framework. Within the SAP-LAP framework, adopting a natural resource-based perspective, the study thoroughly examines the intricacies and interactions among existing situations, pertinent actors and processes that impact climate initiatives within a metal and mining company.

The study's findings suggest that organizations can achieve the objective of climate neutrality by prioritizing resources and capabilities that lead to reduced GHG emissions, lower energy consumption and optimal resource utilization. The study further proposes key elements that significantly influence the pursuit of climate neutrality within enterprises.

This study is one of the earliest contributions to the development of a holistic understanding of climate neutrality in the supply chain of the metal and mining industry.

The study will assist practitioners and policymakers in comprehending the present circumstances, actors and processes involved in enterprises' supply networks in order to attain climate neutrality in supply chains, as well as in taking the right steps to enhance performance.

This study presents a climate neutrality model and provides valuable insights into emission management, contributing to the achievement of the climate neutrality objective.