Exchange Rate Research Articles

By their nature, inflation expectations are an unobservable variable. In the framework of economic theory and practice, proxy indicators of inflation expectations (mainly based on surveys) are used as the most important variables for analyzing and forecasting inflationary processes. At the same time, when implementing the inflation targeting regime, regulators primarily focus on managing inflation expectations through monetary policy communications. In this respect, their special, dual character is manifested. Today, the use of alternative estimates of inflation expectations, including search query statistics, continues to grow in popularity. The selection of keywords for quantifying the expectations of the population remains a conceptual issue. The purpose of the study is to develop a methodologically sound approach to selecting keywords for search queries, statistics on which can be used as proxy variables of inflationary expectations. Within the framework of the article, this goal is achieved on the basis of text analysis of communications of the Bank of Russia using machine learning models (especially NLP). Based on the frequency analysis (Baseline approach), as well as the use of advanced NLP models (the T5 family of models ("Text-to-Text Transfer Transformer"), four groups of keywords ("inflation", "Central Bank", "exchange rate", "key rate") were identified using which the regulator can shape the inflation expectations of the Russian population (top-down approach). Due to recent changes in the policy of accessibility of historical data, as well as the popularity of the search network among residents of Russia, special emphasis is placed on the data of the Yandex search network. It is assumed that tracking the dynamics of requests for the "inflation" and "Central Bank" groups provides operational information everywhere, and for the "exchange rate" and "key rate" groups - in crisis and/or changing economic conditions. The results obtained on the search statistics of the selected keywords were tested as proxy indicators in the framework of forecasting inflation at the level of the Russian Federation based on a set of ARIMAX family models. The results indicate that it is advisable to use keyword statistics as explanatory variables to minimize forecast errors within the framework of inflation forecasting models.

Foreign Direct Investment (FDI) plays a vital role in the economic development of a country. Basically, Foreign Direct Investment is an investment where a foreign company or investor invests capital in the business of a domestic or host country. Foreign Direct Investments can be made in various ways, that is, by establishing a new company, or by merging or acquiring a company or by joint ventures. Foreign Direct Investment helps in increasing capital for domestic countries, creating job opportunities, increases exports and helps maintain exchange rate stability. Through this research paper, the author has made an attempt to what Foreign Direct Investment refers to and what is its impact on employment and technology transfer.

Agricultural exports in Nigeria have been adversely affected by fluctuations in macroeconomic indicators. Insufficient private agricultural investment and limited public expenditure directed toward the sector have resulted in inadequate productivity and suboptimal export performance. This study investigates the macroeconomic determinants of agricultural exports in Nigeria. A multiple regression model is specified, with agricultural exports (as a percentage of total merchandise exports) as the dependent variable. The independent variables are national output (economic growth rate), inflation rate, interest rate, exchange rate, and tariff rate. The analysis employs descriptive statistics, correlation, stationarity, and cointegration tests. After confirming the absence of multicollinearity, heterogeneity, autocorrelation, and nonstationarity in the time series data, the variables are deemed suitable for regression analysis. The model is estimated using ordinary least squares, and the results are interpreted at the 5% significance level. The findings indicate that all macroeconomic indicators, except the tariff rate, significantly influence agricultural exports. It is recommended that Nigerian policymakers reassess the effects of macroeconomic policies on the country's external balance, with particular attention to agricultural exports.

This research explores how several monetary policy and commodities market influence the movement of the Indonesia Composite Index (IHSG). Monetary policy is a set of actions taken by the central bank to regulate the currency and the economy, variable proxy is Rupiah Exchange Rate (Jisdor) and Indonesia Overnight Index Average (indONIA). Commodity markets are places where commodities are traded in physical or futures, the needs of the world still depend on certain commodities so that commodity prices can be related to economic conditions, variable proxy of comodities market is Gold, Crude Oil WTI, Coal Newcastle. Indonesia Composite Index is a index that reflects the price movements of all stocks listed on the Indonesia Stock Exchange.The study analyzes monthly data from January 2019 to December 2023, a period before the global disruption of the COVID-19 pandemic, the period during the pandemic and the gradual economic rebound that followed. Using multiple linear regression analysis, the study assesses the direction and statistical relevance of each variable’s effect on the Indonesia Composite Index. The results suggest that Indonesia Overnight Index Average and Crude Oil WTI prices have a significant positive impact on the index, the Rupiah Exchange Rate has a significant negative impact on the index, while Gold and Coal Newcastle have no significant impact on the index. These findings can serve as a useful reference for both investors and policymakers in understanding and anticipating movements in Indonesia’s capital market, especially in relation to monetary policy and global commodity trends.

ABSTRACT This paper explores how exchange rate exposure influences firm innovation, with particular attention to the intervening effect of corporate social responsibility (CSR). Using A-share listed firms from 2010–2020, we document that exchange rate exposure significantly reduces innovation investment. However, CSR effectively counteracts this effect through two key mechanisms: alleviating financial constraints and enhancing employee-driven innovation productivity. The buffering effect of CSR is particularly pronounced for firms with overseas revenue exposure, those operating in eastern regions, high-tech industries, and competitive markets. These findings highlight CSR’s strategic value in sustaining innovation during macroeconomic turbulence, offering new insights into non-financial risk management in emerging markets.

While so far, the focus of Mr. Trump’s international economic policies has been on trade policy a number of his advisers have made proposals that would dramatically affect the operation of the international monetary system. These are often referred to as the Mar-a-Lago proposals named after Mr. Trump’s Florida home. This paper offers critiques of these proposals and argues that many of them are based on fantasies and implementing many of them would end in tragedies for the United States as well as the rest of the world. The proposals are frequently based on fallacies including that trade deficits are always bad, that the role of the dollar has made a major rather than minor contribution to the US trade deficits and that tariffs and exchange rate changes alone would be sufficient to close the trade deficit without major macroeconomic adjustments. Such arguments ignore both the Lerner Symmetry Theorem, which shows that barriers to imports will also reduce exports and the role of international capital flows in affecting the trade balance. They generally fail to note the important contributions that the huge US fiscal deficits have made to the trade deficits. Their emphasis on unilateral actions and disregard of international agreements show a distressing lack of knowledge of international monetary history and the benefits of international cooperation.

Background Limited-stage small-cell lung cancer (LS-SCLC) has suboptimal long-term survival despite standard chemoradiotherapy. Durvalumab, an anti-PD-L1 antibody, demonstrated survival benefits in the ADRIATIC Phase III trial, but its cost-effectiveness in China remains uncertain. This study evaluates the economic value of durvalumab as consolidation therapy for LS-SCLC post-chemoradiotherapy. Methods A Markov model was constructed using data from the ADRIATIC trial (NCT03703297), simulating three health states: progression-free survival (PFS), progressive disease (PD), and death state, transition probabilities were derived from trial outcomes. A 10-year horizon, 5.0% discount rate, and willingness-to-pay (WTP) thresholds (1-3×per capita gross domestic product (GDP): $12,569.82-$37,709.46/QALY) were applied. All costs were converted to unified currency using the average exchange rate of 1 USD = 7.11 CNY, based on exchange rates from 1 January 2024, to 31 October 2024. Results The study results demonstrated that while durvalumab provided clinical benefits by extending quality-adjusted life years (QALYs) by 0.44 compared to placebo (2.24 vs. 1.80), its high cost resulted in poor cost-effectiveness within China’s healthcare system. The incremental cost reached $108,609.45, yielding an ICER of $245,591.59 per QALY, exceeding China’s standard willingness-to-pay thresholds. Sensitivity analyses revealed drug pricing as the most influential factor, where a 30% price reduction could improve the ICER by 30.3%. The negative incremental net monetary benefit (-$107,394.34) further confirmed the economic challenges. These findings suggest that despite its clinical advantages, durvalumab’s current pricing makes it economically unviable for routine use in China’s LS-SCLC treatment without substantial cost reductions or alternative reimbursement strategies. Conclusion Durvalumab improves survival in LS-SCLC but lacks cost-effectiveness under current pricing in China. Drug costs and health utilities are critical determinants. Policy measures, such as price negotiation, risk-sharing agreements, or subgroup targeting, may enhance affordability. Balancing clinical benefits with economic burden is essential for optimizing durvalumab’s role in LS-SCLC management.

This study assesses the connection between environmental degradation, agro-climate financing, and economic growth in Sub-Saharan Africa (SSA) using yearly time series data from 2000 to 2022. The system generalized method of moments (GMM) was employed to tackle endogeneity issues, with robustness checks performed using DOLS and FMOLS to address cross-sectional dependence through robust standard errors. This method revealed important insights into the dynamics of economic growth. The findings show a significant positive connection between the economy’s past success and its current growth. CO2 emissions negatively impact economic growth, demonstrating the detrimental effects of environmental degradation. Agricultural finance has a positive influence on economic growth by boosting productivity and fostering economic growth. However, climate financing has a short-term negative impact on growth owing to high initial costs and inefficiencies, but it promotes long-term growth when combined with agricultural finance. The interaction between CO2 emissions and agricultural finance shows that increasing emissions reduces the benefits of agricultural investments, underscoring the vulnerability of agriculture-dependent economies. Conversely, the interaction of agricultural finance with climate finance enhances economic growth, demonstrating the relevance of combining climate and agricultural investments. Additionally, the study finds that exchange rate stability positively affects growth, while inflation has a negative impact. Robustness checks validate these findings and underscore the need for varied analytical methods to capture economic interactions comprehensively. The study recommends comprehensive policy measures to tackle environmental, agricultural, and climate challenges, promote sustainable growth, and leverage integrated financial solutions for long-term development in Sub-Saharan Africa.

Transition metal complexes have been widely utilized as cellular imaging tools. To impart organelle specificity, ligand architecture is usually modified to modulate properties like overall charge and lipophilicity. In many such designs, the metal identity and its intrinsic properties are often ignored. To address this gap, in this study, we explored the effects of changing the metal center on the localization patterns of isostructural complexes. To this end, we employed the thiosemicarbazone Dp44mT to synthesize coumarin-conjugated complexes of Au(III), Pt(II), and Pd(II). Although the metal centers in these compounds share a formal d8 configuration, they differ in properties such as ionic radius, charge density, and ligand exchange rates, which can affect their subcellular localization patterns. In addition, we synthesized a second set of analogous complexes using BODIPY as the conjugating fluorophore to assess the influence of using a different dye on the cellular distribution. Confocal imaging revealed that the complexes exhibited distinct intracellular distributions. For instance, while the coumarin-conjugated Pt(II) complex localized specifically in lysosomes, the corresponding lipophilic Pd(II) complex lacked this specificity and instead followed a diffusely cytosolic distribution. Similarly, the more lipophilic BODIPY conjugated complexes were non-specific in their cellular distribution as well. Overall, the findings of this study highlight the interplay of metal identity and lipophilicity in determining the localization patterns of Dp44mT-based metal complexes, offering fresh insights into the design of new metal-based imaging tools.

ABSTRACT To evaluate the clinical and economic outcomes in pediatric patients hospitalized with invasive pneumococcal disease (IPD). This is a retrospective study that included hospitalized patients under 18 years of age from three participating hospitals between 2014 and 2024, all of whom had a definitive diagnosis and laboratory confirmation of invasive pneumococcal disease (IPD). Descriptive statistics and multivariable analyses were used to evaluate outcome measures, including in-hospital mortality, length of stay (LOS), direct cost per admission and vaccination status, and the serotypes were also explored. A total of 141 pediatric patients from January 2014 to July 2024 were included. Of these, 83 (58.9%) were male, and 72 (51.5%) were aged 2–5 years. Forty-one (29.1%) patients required hospitalization for over 14 days, and 3 (2.1%) had received vaccination. Among the 97 serotypes identified, 86 (88.7%) were PCV13 vaccine-type serotypes (VT-Serotypes). The most common disease was bacteremia (54.6%), followed by bacteremic pneumonia (23.4%). The observed mortality, median LOS, and median direct cost were 0.7%, 8 days, and $1122.66 (based on the RMB-USD exchange rate in 2025), respectively. Factors influencing cost included LOS and the type of IPD. Longer LOS, influenced by IPD types, was associated with higher costs, and patients diagnosed with meningitis incurred greater costs per admission compared to those with bacteremia. IPD poses a significant clinical and economic burden on children. Promoting pneumococci vaccination is essential to mitigate the IPD burden and associated costs in China.

As a core precious metal with dual commodity and financial attributes, gold price fluctuations are profoundly influenced by macroeconomic policies, monetary conditions, and market supply-demand dynamics. As the global benchmark for gold pricing, the COMEX gold futures market generates price signals that hold significant reference value for investors asset allocation decisions, central banks reserve management practices, and the stability of the global bulk commodity market. Against this backdrop, this study focuses on the dynamic linkage between COMEX gold futures prices and key macroeconomic variables, aiming to quantitatively analyze the short-term impact effects and long-term equilibrium relationships of the U.S. dollar exchange rate, real interest rates, and inflation rates on gold prices. Methodologically, the Vector Autoregression (VAR) model, this research uses monthly data of COMEX gold futures prices, U.S. Dollar Index (DXY), U.S. 10-year Treasury real yields, and U.S. core PCE inflation rate from 2015 to 2024 as the research sample.

As a member of the Gprotein-coupled receptor superfamily, the μ-opioid receptor (MOR) activates heterotrimeric G proteins by opening the Gα α-helical domain (AHD) to enable GDP-GTP exchange, with GDP release representing the rate-limiting step1,2. Here, using pharmacological assays, we show that agonist efficacy correlates with decreased GDP affinity, promoting GTP exchange, whereas antagonists increase GDP affinity, dampening activation. Further investigating this phenomenon, we provide 8 unique structural models and 16 cryogenic electron microscopy maps of MOR with naloxone or loperamide, capturing several intermediate conformations along the activation pathway. These include four GDP-bound states with previously undescribed receptor-G protein interfaces, AHD arrangements and transitions in the nucleotide-binding pocket required for GDP release. Naloxone stalls MOR in a 'latent' state, whereas loperamide promotes an 'engaged' state, which is structurally poised for opening of the AHD domain and subsequent GDP release. These findings, supported by molecular dynamics simulations, identify GDP-bound intermediates and AHD conformations as key determinants of nucleotide exchange rates, providing structural and mechanistic insights into G protein activation and ligand efficacy with broad implications for Gprotein-coupled receptor pharmacology.

ABSTRACT Economic sanctions can significantly destabilize exchange rates, creating challenges for targeted economies. This study examines how sanctions—specifically export, import, and financial sanctions—affect exchange rate volatility, and explores the moderating role of Foreign Direct Investment (FDI). Using panel data from 21 heavily sanctioned countries between 2000 and 2021, we apply both static and dynamic models, including Panel-Corrected Standard Errors (PCSE) and Generalized Method of Moments (GMM). The results show that sanctions considerably increase exchange rate volatility, particularly in smaller economies. However, FDI inflows mitigate these negative effects, providing a stabilizing influence. The study further contributes to exchange rate literature by refining key theoretical frameworks such as the Uncovered Interest Rate Parity (UIP) and the Balance of Payments (BOP) approach, integrating sanctions intensity and FDI. These insights offer practical implications for policymakers in geopolitically sensitive contexts, highlighting the importance of attracting FDI to buffer the currency market against external shocks.

This study examines the interplay of price transmission mechanisms, climate shocks, and exchange rate dynamics in Turkey’s walnut market using a Vector Autoregression (VAR) model. Analyzing monthly data on domestic producer prices, import prices, and production volumes, we uncover a counterintuitive inverse relationship between import and domestic prices: a 1% rise in import prices reduces domestic producer prices by 2.3% within two months, with a cumulative effect of 4.1% over five months. This suggests domestic producers lower prices to compete with higher-cost imports, revealing an "import competition effect" unique to this market. Exchange rate volatility amplifies this dynamic, with a 10% depreciation of the Turkish Lira raising import prices by 7.2%, accounting for 22% of their variance. Climate shocks further disrupt market equilibrium asymmetrically. Frost events trigger immediate production declines (−14.7%) and rapid price spikes (+5.3% within one month), while droughts cause protracted supply reductions (−8.4% over six months). Critically, climate shocks double the elasticity of domestic prices to import price changes (−0.47 vs. −0.23) and accelerate transmission, peaking within one month instead of two. Policy implications emphasize exchange rate stabilization (e.g., central bank currency swaps could reduce pass-through by 31%), climate adaptation (drought-resistant cultivars and drip irrigation may cut production volatility by 17–23%), and hybrid trade policies (seasonal tariffs with quotas). These findings underscore the vulnerability of perennial crop markets in emerging economies to global and climatic shocks, offering a framework for building resilience in analogous agricultural sectors.

This study is devoted to investigating the asymmetric effects of geopolitical risks (GPRs) on Vietnam’ exports during the period from January 2010 to December 2024. Using a nonlinear Autoregressive Distributed Lag (NARDL) bounds testing model, the study documented that in the short-run, GPRs have asymmetric effects on Vietnam’s exports. Specifically, negative changes in GPRs have a significantly negative influence on the exports while positive changes in the GPRs have no significant effects on exports. In the long-run, the same effects of GPRs on exports are also found from the NARDL model. Specifically, negative changes in GPRs have a significantly adverse effect on exports, while positive changes in GPRs have no significant influence on exports in the long-run. Moreover, the empirical findings reveal that, in the long-run, the real exchange rate (RER) has a significantly positive impact on exports, suggesting that the depreciation of the VND (Vietnamese Dong) boosts Vietnam’s exports. Finally, the findings obtained from the error correction model show that 34.82 percent of the divergence from the long-run equilibrium caused by a shock in month n will be corrected and adjusted back toward equilibrium in month n + 1.

External Debt Servicing, Exchange Rate Volatility, and Construction Sector Performance in Nigeria: Macro-Financial Transmission Channels and Sectoral Vulnerability

Inflation is a pivotal economic indicator that influences business activities and livelihoods. The escalating trend of inflation rates globally has led to business closures and widespread economic hardship. This study employs the Box-Jenkins methodology to develop predictive SARIMA and SARIMAX models for Ghana’s monthly inflation rates. The models capture both seasonal and non-seasonal inflation rate components, as well as the impact of external factors such as the Ghana-US exchange rates. Our findings indicate that the SARIMA model provides more accurate inflation rate predictions. The results have significant implications for monetary policy and inflation targeting in Ghana. Furthermore, the methodology is universally applicable to macroeconomic forecasting problems.

Aim of the Study: Using cointegration techniques it’s well established that there is a negative relationship between domestic demand and the Overall exports. Then domestic demand is an unfavorable determinant to the Overall exports performance along with the Real Exchange Rate while the Overall production is an favorable determinant to this performance. Adopting a sectoral Approach what could be for manufactures exports performance in CEMAC? This is the main question, here. Methodology: To overcome this kind of issue of economic policy relying on trade equations, we rely more on the parameters significance of the estimates than the direction of these estimates. In fact, the time frame is the same as in the case of Overall exports but the CEMAC area as Africa as a whole is a subset where the differences between the Overall and the manufactures exports is great according to the international trade theories. Major Findings: Using a dynamic panel data model with an error correction mechanism between 1974-2021 on 4 (of the 6) CEMAC’s countries considering data availability we found that in CEMAC Real Exchange Rate affects manufactures exports with a positive elasticity and the domestic demand impacts negatively manufactures exports in CEMAC while the value added of manufactures (take as the measure of manufacture production) effect’s is ambigouos. Conclusion: As well as for the Overall export performance than the sectoral approach with the manufactures exports performance the domestic demand is an short run determinant while the Real Exchange Rate and production are long run determinants.

Type of the article: Research ArticleAbstract Between 2019 and 2023, the Peruvian sol showed an accumulated nominal variation of approximately 12.9%, reflecting moderate depreciation influenced by both external and domestic factors, although in 2022 it appreciated by 4.6%, positioning itself as one of the most stable currencies in the region. The objective of this study was to estimate the impact of exchange rate volatility on Peru’s foreign trade during this period of global and domestic turbulence, employing a quantitative correlational design with secondary data from the Central Reserve Bank of Peru (BCRP) and the National Superintendence of Customs and Tax Administration (SUNAT), analyzed through regression models and statistical tests in SPSS. The results indicate that exchange rate variability explains 61.1% of changes in export volume, 49.8% in import volume, and 45.9% in terms of trade (all p < 0.01), while inflation and GDP also show significant associations with exports and imports, with R² values ranging from 24.5% to 60.4% (p < 0.01). These findings confirm that macroeconomic volatility, particularly exchange rate dynamics, significantly shapes trade performance. From a theoretical perspective, this study provides evidence from a primary-exporting economy, enriching the literature on exchange rate fluctuations in emerging markets, while from a practical standpoint, it underscores the importance of adopting economic and trade policies that mitigate external vulnerability, stabilize exchange rate fluctuations, and strengthen competitiveness. In conclusion, exchange rate volatility exerts a decisive influence on Peru’s foreign trade, reinforcing the need for integrated and sustainable policy measures to ensure stability and long-term growth.

Mung beans are believed to be the key to Indonesia's food security in facing the food crisis in the future. This study aims to analyze the factors that influence the volume of mung bean imports in Indonesia. The factors studied include domestic production, import prices, exchange rates, domestic prices, and government policies. The data used are secondary data from 2007 to 2022, obtained from Statistics Indonesia (BPS), the Ministry of Agriculture, and UN Comtrade. Multiple linear regression was used to determine the effect of each independent variable on the volume of mung bean imports. Based on the EViews regression output, three variables were found to have a significant effect on the volume of mung bean imports in Indonesia: domestic production (negative effect), real domestic prices (positive effect), and import policy (significant effect). Meanwhile, real import prices and the exchange rate of the Rupiah against the US Dollar showed negative but statistically insignificant effects. These findings indicate that fluctuations in mung bean imports in Indonesia are more strongly influenced by domestic production levels, internal price dynamics, and government policies rather than external factors such as import prices and currency exchange rates.