It has become commonplace to describe publicly provided infrastructure as being in a sorry state and to advance public-private partnership as a possible remedy. This essay adopts a skeptical but not a cynical posture toward those claims. The paper starts by reviewing the comparative properties of markets and politics within a theory of budgeting where the options are construction and maintenance. This analytical point of departure explains how incongruities between political and market action can favor construction over maintenance. In short, political entities can engage in an implicit form of public debt by reducing maintenance spending to support other budgetary items. This implicit form of public debt does not manifest in higher interest rates but rather manifests in crumbling bridges and other infrastructure due to the transfer of maintenance into other budgetary activities.
This study investigated the influence of infrastructure spending, government debt, and inflation on GDP in South Africa from 1995 to 2023. Motivated by the need for sustainable growth amid fiscal and inflationary pressures, this research addresses gaps in understanding how these factors shape economic performance. The primary objective was to assess these variables’ individual and combined effects on GDP and offer policy recommendations. Using an ARDL model, the study explored long- and short-term relationships among the variables. Results indicate that infrastructure spending positively impacts GDP, promoting long-term growth, while government debt hinders GDP in both short and long runs. Moderate inflation supports growth, but excessive inflation poses risks. These findings imply the need for targeted infrastructure investments, strict debt management practices, and inflation control measures to sustain economic stability and growth. Policy recommendations include expanding public investment in productive infrastructure, implementing fiscal rules to prevent unsustainable debt levels, and maintaining inflation within a controlled range. Ultimately, these policies could help South Africa build a resilient, balanced economy that addresses both immediate growth needs and long-term stability.
considering the rate of the currency channel, this study aims to analyze the effect of government foreign debt on labour demand in Indonesia. The Real Effective Exchange Rate (REER) is used to quantify the exchange rate, while estimates of the labour force participation rate characterize labour demand. this study expands upon the cobb-Douglass production function by including public debt as an integral element of the statistical model. The current study examines time series data from 1994 to 2022 and uses the Vector Error Correction Model (VECM) for estimation. in conclusion, the results suggest that an increase in government external debt would result in a decline in labour demand, especially during economic shock associated with an expansion of the government deficit. Moreover, the Real Effective Exchange Rate has a beneficial long-term impact on labour demand. enhancing the purchasing power and stimulating investment through the appreciation of the domestic currency against foreign currencies will consequently increase economic productivity.
Amidst an upsurge in the quantity of delinquent loans, the financial industry is experiencing a fundamental transformation in the approaches utilised for debt recovery. The debt collection process is presently undergoing automation and improvement through the utilisation of Artificial Intelligence (AI), an emergent technology that holds the potential to revolutionise this sector. By leveraging machine learning, natural language processing, and predictive analytics, automated debt recovery systems analyse vast quantities of data, generate forecasts regarding the likelihood of recovery, and streamline operational processes. Debt collection systems powered by AI are anticipated to be compliant, precise, and effective. On the other hand, conventional approaches are linked to increasing expenditures and inefficiencies in operations. These solutions facilitate efficient resource allocation, customised communication, and rapid data analysis, all while minimising the need for human intervention. Significant progress has been made in data analytics, predictive modelling, and decision-making through the application of artificial intelligence (AI) in debt recovery; this has the potential to revolutionize the financial sector’s approach to debt management. The findings of the research underscore the criticality of artificial intelligence (AI) in attaining efficacy and precision, in addition to the imperative of a data-centric framework to fundamentally reshape approaches to debt collection. In conclusion, artificial intelligence possesses the capacity to profoundly transform the existing approaches utilized in debt management, thereby guaranteeing financial institutions’ sustained profitability and efficacy. The application of machine learning methodologies, including predictive modelling and logistic regression, signifies the potential of the system.
The distress of commercial companies is considered one of the most critical stages leading to the liquidation and termination of the business. This danger increases in the context of poor management, stagnation, and the occurrence of crises and external circumstances that affect the company’s ability to cope. Rules regarding financial restructuring of distressed commercial companies may be regarded as the most prominent legal framework adopted by Emirati, Kuwaiti and French legislators to address the instability and distress of commercial enterprises and to provide solutions to mitigate the risk of bankruptcy and liquidation. It is a preventive measure aimed at reaching an agreement between the debtor and creditors to resolve the disturbances or difficulties faced by the company, which may affect its obligations to others. Therefore, financial restructuring is considered a mean of prevention and rescue for commercial companies, and the success of this rescue is linked to the debtor’s cooperation and seriousness in overcoming such issue.
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