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This paper aims to answer the following important questions: Is public debt in Sub-Saharan African (SSA) countries sustainable? What are the determinants of public debt sustainability in these countries, and do these determinants exhibit heterogeneity due to regional, natural resource, and income differences among SSA countries?

This study analyzes the public debt sustainability in SSA countries using the theoretical model known as the Present Value Budget Constraint (PVBC) model developed by Hamilton and Flavin (1986), and adopts the econometric testing method proposed by Trehan and Walsh (1991). Moreover, to empirically investigate the determinants of public debt sustainability in SSA countries, the System-Generalized Method of Moments (System-GMM) method is applied. Furthermore, this study conducts heterogeneity analysis by categorizing the sample based on different regions, natural resource endowments, and income levels. The data of this study are sourced from the IMF and World Bank databases for 45 SSA countries from 2005 to 2021.

Findings reveal that public debt in SSA countries is not sustainable in the long run, with factors such as the previous government debt, long-term debt ratio, debt repayment capacity, economic growth rate, inflation rate, export to GDP, and government fiscal deficit rate influencing sustainability. Additionally, the factors exhibit heterogeneity attributed to regional, natural resource, and income variations among SSA countries.

The findings of our study will serve as a catalyst for policymakers in the SSA countries to embrace and sustain robust fiscal consolidation and debt stabilization measures. Moreover, countries with distinct characteristics should implement tailored approaches. Additionally, policymakers in SSA countries should implement economic measures to address public debt issues. These measures include improving the macroeconomic structure, promoting economic transformation and diversification of industries, fostering sustainable economic growth, ensuring price stability, and strengthening resilience against external shocks and debt risks. Specifically, countries endowed with indigenous species, resources, and tourism potential should adopt a well-coordinated strategy that utilizes agriculture, tourism, ecotourism, and the hospitality industry as instruments for sustainable local community and rural development.

Firstly, it assesses the sustainability of public debt and its determinants for countries in SSA, which distinguishes it from previous studies that only focus on either debt sustainability or determinants of debt separately. Secondly, by including multiple SSA countries in the analysis, this study stands out from prior research that predominantly concentrates on specific nations. Thirdly, the utilization of the System-GMM method for analyzing determinants adds a novel dimension to this study, departing from earlier literature primarily focused on debt thresholds. Lastly, the heterogeneity analysis conducted in this study provides an empirical foundation for tailoring policies to different countries, addressing a facet often overlooked in earlier literature.

This study examines how the introduction of mobile money transfers, while making it efficient and convenient to access funds, has affected rural households’ savings behavior and the banking sector.

This study utilizes Fiji’s most recent agricultural census data to model the agricultural household’s saving decision. The study estimates an probit model to examine rural households' savings behavior. Furthermore, it utilizes time series secondary data to examine how funds transfer has been channeled to rural households in Fiji.

Firstly, the results demonstrate that with the mobile money transfer platform launch, the banking sector has lost substantial money previously used to pass through its system, thus losing service fees and interest income. Furthermore, the findings demonstrate that those using mobile wallet platforms to receive money are more likely not to have a savings account with the bank. Noting the cultural systems and social settings of the native households and the ease of payments via the mobile platform, they tend to spend more on consumption rather than saving, thus making these households more vulnerable during shocks such as natural disasters.

While mobile money transfer is hailed as a revolution, no research has yet picked up the downside to it, that of undermining the very effort by policymakers to get low-income rural households to save. Secondly, this study also highlights how mobile money transfer deprives the banking system of a significant transfer fee income and a source of funds to pool and lend to earn interest income. Furthermore, this study brings to the forefront a dichotomy about how a rural indigenous community sees the welfare and prosperity of their community much differently than what economics textbooks portray.

This study aims to estimate the synergy effect of agricultural dual-scale management (ADM) on farmers' total household income, its heterogeneous effects and its mechanisms.

This study constructs a theoretical analysis framework based on the division of labor and synergy theory, empirically assesses the impact of ADM on farmers' income, and further discusses the heterogeneity and mechanisms using the propensity score matching (PSM) and quantile treatment effect (QTE) models. Data is collected from 1,076 households across 4 cities in Liaoning Province of China in 2021.

ADM can improve the total household income of farmers, and the impact force is greater than that of the single-scale management mode. ADM is more conducive to improving the income of farmers with low income and low labor endowment. Moreover, ADM can improve agriculture production efficiency, increase net grain production income. Nevertheless, it has no significant effect on farmers' off-farm employment income.

Previous studies have mainly focused on the income effect of land scale management or service scale management. To the best of our knowledge, this study is the first to identify the synergy effect of ADM on farmers' income in China. It provides new insights into the process of agricultural production and management mode transitions in rural China.

This study investigates whether, how and under what circumstances off-farm work induces farmland abandonment, which is of great importance for developing countries to cope with food security.

Exploiting large-scale panel data from the newly released Chinese Family Database, this study employs a two-way fixed effects model to empirically estimate the causal relationship between off-farm work and farmland abandonment.

In the context of large-scale labor migration in rural China, current off-farm work leads to an increase in the probability and area of farmland abandoned due to insufficient agricultural labor. However, off-farm work does not harm farm households in plain areas, or villages with land rental markets, abundant agricultural labor, and agricultural machinery, while it harms others. Moreover, farmers who work off-farm in the local area are less likely to abandon their farmland than those in other areas. Additionally, when the number of off-farm workers in a household exceeds two, the probability and area of farmland abandonment will miraculously decline, as the household will no longer live entirely on agriculture.

This study may fill the gap in clarifying the relationship between off-farm work and farmland abandonment, and identify scenarios where off-farm work may not cause farmland abandonment through multiple dimensions, providing insights into the governance of farmland abandonment during rural-urban transformation in developing countries.

This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.

Surprisingly little is known of the various methods of security analysis used by financial analysts with industry-specific knowledge. Financial analysts’ industry knowledge is a favored and appreciated attribute by fund managers and institutional investors. Understanding analysts’ use of industry-specific valuation models, which are the main value drivers within different industries, will enhance our understanding of important aspects of value creation in these industries. This paper contributes to the broader understanding of how financial analysts in various industries approach valuation, offering insights that can be beneficial to a wide range of stakeholders in the financial market.

This paper systematically reviews existing research to consolidate the current understanding of analysts’ use of valuation models and factors. It aims to demystify what can often be seen as a “black box”, shedding light on the valuation tools employed by financial analysts across diverse industries.

The use of industry-specific valuation models and factors by analysts is a subject of considerable interest to both academics and investors. The predominant model in several industries is P/E, with some exceptions. Notably, EV/EBITDA is favored in the telecom, energy and materials sectors, while the capital goods industry primarily relies on P/CF. In the REITs sector, P/AFFO is the most commonly employed model. In specific sectors like pharmaceuticals, energy and telecom, DCF is utilized. However, theoretical models like RIM and AEG find limited use among analysts.

This is the first paper systematically reviewing the research on analyst’s use of industry-specific stock valuation methods. It serves as a foundation for future research in this field and is likely to be of interest to academics, analysts, fund managers and investors.

The purpose of this study is to examine the welfare effects of product standards (which fall under Non-Tariff Barriers (NTBs)) on an exporting country when the country by its own choice prefers to follow the null standard for the domestic market, which is not possible due to high set up cost at two different standards. The model has used a theoretical framework to analyze the effects and has derived some important results. If the standard is not linked with a true negative externality, the exporting country, given the assumptions of the model will always prefer to be discriminated by “tariff” and the importing country will prefer to protect its market by “tariff” rather than going for NTB. The typical assumptions taken here resemble the trade between developed and developing countries when the developed country imposes some minimum standard on a product but becomes relatively “costly” for the developing country to comply with. As the importing country is not free to set tariffs, it will use NTB as a minimum standard (as it is welfare-improving than free trade). However, the minimum standard also affects the exporting country's local producers and consumers. So NTB leads to a worse situation for both countries and definitely worst for the exporting country. Using a game theoretic framework, the study shows that the imposition of standards which does not address any real externality can be an optimum response for an importing country leading to a loss in the global welfare compared to a free trade situation.

The purpose of this study is to examine empirically the impacts of gender differences, telecommunication technology (ICT) and other determinants on private savings in 28 selected Asia–Pacific countries.

This study employs the panel data from 2010 to 2017 across 28 selected Asia–Pacific countries. To enhance robustness and address the possibility of endogeneity issue, the present study utilises the fixed effect instrumental variable (IV) estimator to estimate the private savings model for Asia–Pacific region.

The present study finds that private savings is positively related to disposable income and ICT, but it is negatively associated with the degree of dependency. However, the association between interest rates and private savings are inconclusive as both positive substitution and negative income effects on private savings were observed. Moreover, the results also indicate that working females tend to save less than working males and that of the educated female, despite their impacts are varied across educational attainment levels.

This study provides a novel insight into private savings patterns by focussing upon the gender differences and ICT aspects. In stark contrast to previous literature on the issue, the authors find that working and educated females negatively impact private savings in Asia–Pacific economies due to income inequality and consumption habits. However, the results show that ICT accelerates private savings as it provides easy access to financial services and the requisite frameworks, such as e-business platforms, for generating passive income as well as provide the modalities for more cost-efficient shopping such as price and product comparison frames that yield costs savings which can then be potentially channelled into private savings.

This paper aims to explore the promotion decisions of heterogeneous sellers on a decentralized platform under competitive conditions and analyze how seller behaviors impact platform profit, seller revenue, buyer surplus and social welfare.

This paper considers a Cournot model consisting of a platform charging a commission rate and two sellers with different conversion rates and browsing costs. Promotion efforts by sellers can increase traffic, but they also incur promotion costs for sellers. The sellers decide on promotion effort by weighing these two effects. The authors also explore the equilibrium when the platform charges a fixed usage fee.

The seller’s profit improves as its conversion rate increases and worsens as browsing costs increase. Also, increasing the commission rate charged by the platform makes the seller invest less in promotional efforts. Therefore, the platform must consider this trade-off to determine an optimal rate. The analysis shows that the seller with a high conversion rate and high browsing cost plays a greater role in generating more overall revenue. When the market favors such a seller, the platform tends to charge less in order not to impair its profitability.

This paper incorporates conversion rate, buyer’s browsing cost, unit promotion cost and the fee charged by the platform into the model to study sellers’ promotion decisions on decentralized platforms.

Nowadays, there is a strong public interest in promoting transparency to be informed about the actions of the public sector. At the same time, there has been a significant change in society’s perceptions and concerns about sustainable development, with a marked increase in attention to this area. In this context, our main objective is to investigate the impact of transparency practices in local government on the implementation of the Sustainable Development Goals (SDGs) in Spanish municipalities.

We will analyse a sample of 84 municipalities, using the Dynamic Transparency Index published by Dyntra to measure transparency. For the level of implementation of the SDGs, we will use an index specifically created using data from the report “The SDGs in 100 Spanish Cities”, published by the Spanish Network for Sustainable Development in 2020.

Municipalities with a larger dependent population tend to achieve higher SDG levels. Municipalities with lower financial surpluses and more self-generated resources show better SDG implementation. Progressive political parties lean more towards sustainability, and coalition governments show higher SDG implementation than majority governments. Gender appears to play a minor role in SDG implementation, but male leadership is associated with higher levels. Factors such as population density and government transfers do not have a significant impact on SDG implementation levels.

This study seeks to address the lack of empirical research on the potential impact of transparency on the achievement of the SDGs, while also taking into account other socio-economic, financial and political aspects of the municipality. In doing so, it also contributes to the limited empirical literature on the determinants of the level of SDG implementation in local governments.