Search Results (145)

Global supply chains often face uncertainties in production lead times, fluctuating exchange rates, and varying tariff regulations, all of which can significantly impact total profit. To address these challenges, this study formulates a multi-country supply chain problem as a Semi-Markov Decision Process (SMDP), integrating both currency variability and tariff levels. Using a Q-learning-based method (SMART), we explore three scenarios: (1) wide currency gaps under a uniform tariff, (2) narrowed currency gaps encouraging more local sourcing, and (3) distinct tariff structures that highlight how varying duties can reshape global fulfillment decisions. Beyond these baselines we analyze uncertainty-extended variants and targeted sensitivities (quantity discounts, tariff escalation, and the joint influence of inventory holding costs and tariff costs). Simulation results, accompanied by policy heatmaps and performance metrics, illustrate how small or large shifts in exchange rates and tariffs can alter sourcing strategies, transportation modes, and inventory management. A Deep Q-Network (DQN) is also applied to validate the Q-learning policy, demonstrating alignment with a more advanced neural model for moderate-scale problems. These findings underscore the adaptability of reinforcement learning in guiding practitioners and policymakers, especially under rapidly changing trade environments where exchange rate volatility and incremental tariff changes demand robust, data-driven decision-making. Full article

Exchange rate volatility poses significant challenges for emerging markets, influencing trade balances, inflation, and capital flows. South Africa’s Rand is particularly vulnerable to global risk sentiment, gold price fluctuations, and interest rate differentials, yet prior studies often analyse these factors in isolation. This study integrates them within an autoregressive distributed lag framework, using monthly data from 2005 to 2023 to capture both short-term fluctuations and long-term equilibrium effects. The findings confirm that higher global risk sentiment triggers immediate Rand depreciation, driven by capital outflows to safe-haven assets. Conversely, rising gold prices and favourable interest rate differentials stabilise the Rand, strengthening trade balances and attracting capital inflows. These results underscore the interconnected nature of global financial conditions and exchange rate movements. This study highlights the importance of economic diversification, foreign reserve accumulation, and proactive monetary policies in mitigating currency instability in emerging markets. Full article

Exchange rate volatility has emerged to be one of the most critical determinants of price stability for countries operating in multicurrency systems with their own currency in the basket of currencies. This study empirically examined the impact of exchange rates (official and parallel market rates) on inflation in Zimbabwe during the multicurrency system for the period 2014 to 2024, together with comparing the impacts of the official and parallel market exchange rates on inflation. Time series and monthly data were used to examine the short and long run impact of exchange rates on inflation in an ARDL estimation framework. Findings revealed a short run and long run positive relationship between both the official and parallel market exchange rates and inflation, with the parallel market exchange rate being the most significant variable. Other control variables used, such as domestic productivity, have a highly significant negative impact on inflation through the official and parallel exchange rate models in both the short and the long run. Money supply, real interest rate, trade balance, foreign prices, foreign output, stock market prices and foreign currency reserves have varied impacts through either the official or parallel market exchange rate models. Policy recommendations include a contractionary Monetary and expansionary Fiscal policy mix that will result in exchange rate appreciation and stability, productivity growth, trade surplus, growth in reserves, and ultimately low prices. The exchange rate policy recommended in this study is to shelve discard the local currency in the multicurrency system until industrial capacity utilization exceeds 50% to add the local currency to the basket of currencies and 75% for mono-local currency (de-dollarization). Full article

This paper explores the impact of trade openness and exchange rate volatility on South Africa’s industrial growth from 1980 to 2024 through a hybrid econometric framework combining Autoregressive Distributed Lag (ARDL) and Structural Vector Autoregression (SVAR) models. It captures both long-term relationships and short-term economic patterns; the analysis reveals that gross domestic product (GDP) is the most significant and consistent driver of industrial value added (IVAD), while trade openness and currency volatility exert limited standalone effects. Structural shocks, notably the 2008 global financial crisis and the COVID-19 pandemic, had significant negative short-term impacts on industrial performance, highlighting systemic vulnerabilities. Robustness tests, including rolling window ARDL and first-difference GDP estimation, confirm the persistence of these relationships. Impulse response functions and forecast error variance decomposition underscore the transient and moderate influence of external shocks compared with the dominant role of internal macroeconomic fundamentals. These findings indicate that liberalisation and exchange rate flexibility must be embedded within a broader developmental strategy underpinned by institutional strength, resilience building, and sustainability principles. This study provides fresh insights supporting policy frameworks that prioritise domestic industrial capacity, macroeconomic stability, and alignment with Sustainable Development Goal 9—inclusive and sustainable industrialisation. Full article

In this paper, the Balassa–Samuelson–Tariffi effect is revisited. This research first aims to explain that the behaviour of the real exchange rate shows structural breaks in the short term. A partial equilibrium model “á la Rogoff” is formally formulated where there are relative prices of non-tradable goods in terms of tradable goods in the supply side. Secondly, a general equilibrium model is built after a utility function is added to the partial equilibrium model. It is presented as a mathematical mechanism that shows a stationary state in the real exchange rate considering not only non-tradable goods but also tradable goods both in the domestic market and the foreign market. It is explained that any change in a currency’s price in terms of another currency in real terms is transitory in the long run, thereby disappearing after a certain period of time. In the general equilibrium model, any price’s change in non-tradable goods will be compensated by either a price’s change in tradable goods or changes in the nominal exchange rate. Therefore, this study’s main contribution is to show theoretically that the real exchange rate is constant over time in the long run. Full article

The location of housing has a significant influence on its pricing. Generally, spatial self-correlation and spatial heterogeneity phenomena affect housing price data. Additionally, time is a crucial factor in housing price modeling, as it helps understand market trends and fluctuations. Currency market fluctuations also directly affect housing prices. Therefore, in addition to the physical features of the property, such as the area of the residential unit and building age, the rate of exchange (dollar price) is added to the independent variable set. This study used the real estate transaction records from Iran’s registration system, covering February, May, August, and November in 2017–2019. Initially, 7464 transactions were collected, but after preprocessing, the dataset was refined to 7161 records. Unlike feedforward neural networks, the generalized regression neural network does not converge to local minimums, so in this research, the Geographically, Temporally, and Characteristically Weighted Generalized Regression Neural Network (GTCW-GRNN) for housing price modeling was developed. In addition to being able to model the spatial–time heterogeneity available in observations, this algorithm is accurate and faster than MLR, GWR, GRNN, and GCW-GRNN. The average index of the adjusted coefficient of determination in other methods, including the MLR, GWR, GTWR, GRNN, GCW-GRNN, and the proposed GTCW-GRNN in different modes of using Euclidean or travel distance and fixed or adaptive kernel was equal to 0.760, 0.797, 0.854, 0.777, 0.774, and 0.813, respectively, which showed the success of the proposed GTCW-GRNN algorithm. The results showed the importance of the variable of the dollar and the area of housing significantly. Full article

This study expands the tourism development literature by examining how currency valuation and financial sector maturity influence the tourism–growth relationship. While prior research emphasizes direct or bidirectional causality, this study distinguishes itself by exploring the mediating and moderating roles of financial development and exchange rate stability. Using an instrumental variables approach and empirical data from Africa, we find that exchange rates and financial development partially mediate tourism’s effect on economic growth, particularly in economies with weaker currencies and more developed financial systems. Our results challenge the tourism–growth neutrality hypothesis by demonstrating that exchange rates not only influence tourism demand but also actively shape its growth effects. A panel ARDL analysis confirms bidirectional causality, which reinforces the interdependence between tourism and growth. However, unlike previous studies that view tourism as an isolated driver of growth, we demonstrate that its economic impact depends on a country’s financial maturity and exchange rate competitiveness. Policy recommendations aimed at enhancing economic growth through improved tourism and financial infrastructure are offered. Full article

This study examined how uncertainty and global risk affect financial markets in emerging economies, focusing on foreign investment, CDS spreads, exchange rates, and stock return volatility. Using over 8.6 million ticker transaction observations and structural vector autoregression (VAR) models, the research found that increases in Economic Policy Uncertainty (EPU) significantly reduce foreign net buys, more than global market volatility (VIX). While global volatility drives CDS spreads, these spreads influence exchange rates, causing currency depreciation. The findings highlight the interconnectedness of uncertainty, global risk, and market instability, offering insights for managing risks in opaque markets and improving financial stability. Full article

In the past, South African monetary policy aimed to protect the external value of the domestic currency (Rand); however, these efforts failed. Later, its monetary policy approach changed to allow the foreign exchange rate market to determine the exchange rates. In such a change, the South African Reserve Bank (SARB) aimed to stabilize the demand for the Rand in the foreign exchange market by providing information to stabilize market expectations and create favorable market conditions. However, South African policymakers have struggled with currency depreciation since the early 60s, increasing the uncertainty of South African exports. This study aims to examine the effect of currency depreciation on exports using the Threshold Autoregressive (TAR) model. Additionally, this study created and validated the supply chain activity/disruption index to capture the sea trade activity. The sample period for the analysis is 2009 to 2023. The study finds that currency depreciation does not improve trade between South Africa and its trading partners over time. Furthermore, the currency depreciation was found to be asymmetric to the effect of international trade across the different regimes. The supply chain activity index shows that the effect of supply chain activity/disruption on exports is regime-dependent. This implies that the effect on exports is dependent on the economic environment. Full article

This study compared standard VAR, SVAR with short-run restrictions, and SVAR with long-run restrictions to investigate the effects of oil price shocks and the foreign exchange rate (ZAR/USD) on consumer prices in South Africa after the 2008 financial crisis. The standard VAR model revealed that consumer prices responded positively to oil price shocks in the short term, whereas the foreign exchange rate (ZAR/USD) revealed a fluctuating currency over time. That is, the South African rand (ZAR) initially appreciated against the US dollar (USD) in response to oil price shocks (periods 1:7), followed by a depreciation in periods 8:12. Imposing short-run restrictions on the SVAR model revealed that the foreign exchange rate (ZAR/USD) reacted to oil price shocks in a manner similar to the VAR model, with ZAR appreciating during the initial periods (1:7) and subsequently depreciating in the later periods (8:12). Consumer prices responded positively to oil price shocks, causing consumer prices to increase in the short run, which is consistent with the VAR findings. However, imposing long-run restrictions on our SVAR model yielded results that contrasted with those obtained under short-run restrictions and the standard VAR model. That is, oil price shocks had long-lasting effects on the foreign exchange rate, resulting in the depreciation of ZAR relative to USD over time. Additionally, oil price shocks reduced consumer prices, resulting in a deflationary effect in the long run. This study concluded that South Africa’s position as a net oil importer with a floating exchange rate renders the country vulnerable to short-term external shocks. Nonetheless, in the long term, the results indicated that the economy tends to adapt to oil price shocks over time. Full article

The Ornstein–Uhlenbeck process is widely used in modeling biological systems and, in financial engineering, is commonly employed to describe the dynamics of interest rates, currency exchange rates, and asset price volatilities. As in any stochastic model, influential observations, such as outliers, can significantly influence the accuracy of statistical analysis and the conclusions we draw from it. Identifying atypical data is, therefore, an essential step in any statistical analysis. In this work, we explore a set of methods called local influence, which helps us understand how small changes in the data or model can affect an analysis. We focus on deriving local influence methods for models that predict interest or currency exchange rates, specifically the stochastic model called the Vasicek model. We develop and implement local influence diagnostic techniques based on likelihood displacement, assessing the impact of the perturbation of the variance and the response. We also introduce a novel and simple way to test whether the model’s variability stays constant over time based on the Gradient test. The purpose of these methods is to identify potential risks of reaching incorrect conclusions from the model, such as the inaccurate prediction of future interest rates. Finally, we illustrate the methodology using the monthly exchange rate between the US dollar and the Swiss franc over a period exceeding 20 years and assess the performance through a simulation study. Full article

This paper explores a development strategy for peripheral economies by advocating for a paradigm shift from traditional economic models that rely on accumulating foreign reserves. It proposes the job guarantee (JG) policy, an automatic stabilizer based on a reserve pool of employed individuals, as a cornerstone for fostering sustainable and inclusive growth. Grounded in modern monetary theory (MMT), this study critiques the conventional approach that prioritizes external reserves and highlights the potential of MMT in offering a more autonomous development path for developing countries. A systematic review of the literature, using the PRISMA methodology, reveals significant divergence between MMT advocates and critics, particularly regarding monetary sovereignty and the feasibility of implementing macroeconomic policies in peripheral economies. This study emphasizes that while external constraints remain, the MMT perspective calls for flexible exchange rates, low interest rates, and capital controls as part of a broader strategy to reduce dependency on foreign currencies. The proposed approach prioritizes full employment, the mobilization of domestic resources, and structural transformation through policies like import substitution. Although the shift may involve the slower accumulation of capital, it offers a more equitable and stable development path. Ultimately, this analysis underscores the potential of MMT to expand the external constraint and enable sustainable development, despite challenges in implementation and political resistance. Full article

Every economy’s prosperity is determined by the quantity of tax income it receives. Over the years, studies have demonstrated that inflows from foreign investments and openness to international trade are important contributors to a country’s tax income. Based on this assumption, this study seeks to examine the impact of foreign direct investment (FDI) and open trade on tax income in a number of sub-Saharan African nations. The World Bank Development Indicators data on tax revenue, FDI, exports, imports, and exchange rates from 1990 to 2022 are used in the study. We also use the pooled mean group/panel autoregressive distributed lag approach to examine the data gathered for this inquiry. The results reveal that, in the long term, FDI has a significant negative impact on tax income; nevertheless, in the short run, Ghana’s tax revenue collection suffers while other nations profit from FDI. The results reveal that Nigeria’s exporting is detrimental to tax revenue collection, but South Africa’s export of goods and services is beneficial. However, imports and currency rates benefit Nigeria, Ghana, and South Africa in the near term. Thus, the research suggests improving tax rules and administration to prevent the movement of resources by foreign investors out of the host countries in order to avoid the imposition of huge tax burdens on their firms. Countries with low exports, such as Nigeria, are urged to enhance local manufacturing to meet international export standards in order to alleviate the continual negative balance of payments, which is primarily fixed by the adequate export of products and services. Full article

This study sought to ascertain a machine learning algorithm capable of predicting crises in the African stock market with the highest accuracy. Seven different machine-learning algorithms were employed on historical stock prices of the eight stock markets, three main sentiment indicators, and the exchange rate of the respective countries’ currencies against the US dollar, each spanning from 1 May 2007 to 1 April 2023. It was revealed that extreme gradient boosting (XGBoost) emerged as the most effective way of predicting crises. Historical stock prices and exchange rates were found to be the most important features, exerting strong influences on stock market crises. Regarding the sentiment front, investors’ perceptions of possible volatility on the S&P 500 (Chicago Board Options Exchange (CBOE) VIX) and the Daily News Sentiment Index were identified as influential predictors. The study advances an understanding of market sentiment and emphasizes the importance of employing advanced computational techniques for risk management and market stability. Full article

The purpose of this study is to find symmetries and asymmetries in the exchange rate and macroeconomic fundamentals of advanced European markets, namely Denmark, the Euro Area, and United Kingdom, for the period of 2011 to 2022 via application of the NARDL technique. The findings reveal that interest rate affects DKK exchange rate asymmetrically in the long and short run, whereas money supply affects it in the short run. Foreign reserves are found to be helpful for all three currencies in stabilizing the exchange rate. A decline in gold price weakens GBP, DKK, and EUR in the long run. Previous studies suggest that the existence of asymmetrical relationships justifies the selection of NARDL for empirical analysis. This study makes a contribution to the existing literature, as it proves that forecasting via NARDL is also robust for analysis. The findings have significant policy implications for financial applications. Full article