From the Bretton Woods system to the global non-system: The trials and tribulations of slow learning

In this paper we analyse why an understanding of the global ‘non-system', in which we now live, took so long to arrive after the Bretton Woods system collapsed in 1971. We first describe how knowledge of how an inflation-targeting regime would operate—what we call ‘Taylor-rule macroeconomics'—was only gradually created during the 1970s, 1980s, and 1990s. We then describe how, subsequent to this, an awareness emerged, also gradually, of how the international non-system might work, depending, as it does, on Taylor-rule macroeconomics being already in place. We then discuss the Great Moderation, making clear that a well-functioning global non-system would require not just inflation targeting and floating exchange rates in each country, but also adequate fiscal discipline, and a satisfactory form of financial regulation. We describe how a well-functioning version of this global non-system would actually fit together. We then discuss how this non-system has responded to two enormous challenges of the last 15 years, namely the Global Financial Crisis and the Covid pandemic. This discussion of what has happened in the recent past provides the background to a discussion, in the companion paper by Subacchi and Vines in this issue of the Oxford Review of Economic Policy, of the challenges that the global non-system will face in the future. © The Author(s) 2023. Published by Oxford University Press.

Determinants of Foreign exchange exposure during the COVID-19 crisis: A Multi-country evidence

The research question of which firm-level factors make firms more vulnerable to exchange rate fluctuations during periods of crisis has rarely been explored by prior literature. Using a large sample of 1577 firms from 9 developed and 11 emerging countries, this study presents a comprehensive analysis of how firm-level factors affect firms' foreign exchange exposure before and during the COVID-19 crisis. The results provide evidence of a substantial increase in firms' linear exposure during the COVID-19 period. The cross-sectional analysis reveals that the effects of firm-level variables on exposure are more pronounced during crisis periods and are different from non-crisis periods. Firms that have effective asset utilization or large operating profit margins remain less exposed during times of stress. Contrary to hedging theory, firms that have high incentives to hedge such as firms with high financial leverage become highly exposed to currency fluctuations during crisis periods. The interaction analysis provides further evidence that firms with high leverage can limit their foreign exchange exposure during periods of crisis if they have high asset turnover or high operating profits. The results offer important practical implications to firms for risk management during periods of crisis.

Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies

This paper investigates the extreme dependence and risk spillovers between Bitcoin and the currencies of the BRICS and G7 economies. We find time-varying dependence between Bitcoin and all currencies. Moreover, when analysing risk spillovers from Bitcoin to currencies, we find that Bitcoin exercises significant power over most currencies, with the South African rand and Brazilian real holding both the highest downside and upside risk before and during the COVID-19 pandemic period, respectively. When considering risk spillovers from currencies towards Bitcoin, the Japanese yen exhibits the highest downside spillovers. Importantly, we find asymmetric spillovers between extreme upward and downward movements. • We study dependencies between Bitcoin and the currencies of the BRICS and G7 economies. • We find time-varying dependence between Bitcoin and all of the fiat currencies. • Bitcoin exercises significant power over most of the considered currencies. • We find asymmetric spillovers between extreme upward and downward movements. [ FROM AUTHOR] Copyright of Emerging Markets Review is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Effect of Remittance Inflows on External Debt in Developing Countries

This paper analyzes the effect of remittance inflows on external debt in developing countries, by identifying international reserves as a potential transmission channel. Using panel data over the period 1970–2017 and covering 50 low-and middle-income countries worldwide, we find a positive and significant effect of remittance inflows on the external debt-to-GDP ratio. We also find a negative and significant effect of international reserves on external debt. After controlling for international reserves, the effect of remittance inflows on external debt increases;it remains positive and significant. The results suggest that the role of international reserves as a self-insurance mechanism, and the Dutch disease effect related to remittance inflows are at play. In addition, we find negative and significant effects of economic growth and savings-investment gap on external debt. We also find positive and significant effects of the nominal exchange rate and the United States lending interest rate on external debt. We discuss the policy implications of these findings, while highlighting factors that policymakers should focus on for containing external debt in developing countries in the post-COVID-19.

The Course of the Russian Ruble Exchange Rate During the COVID-19 Pandemic: Trends and Influencing Factors

This article analyzes the impact of the following major factors influencing the Russian ruble exchange rate: oil prices, inflation, the balance of payments flows, and volatility, which are all considered against the background of the COVID-19 pandemic. The analysis reveals that all these factors continued to play a role in 2020, though the shock of the pandemic exhibited certain specific features.

Trade-based money laundering and informal remittance services: implications on the sustainability of the balance of payments of a small open economy

PurposeThis study aims to discuss the consequences of trade-based money laundering (TBML) and informal remittance services on the sustainability of the position of balance of payments and net foreign assets of a small open economy.Design/methodology/approachThis paper uses a case study design using facts related to TBML and informal remittance services on the balance of payment and net foreign assets of Sri Lanka.FindingsThe contextual analysis reveals that the growth of the informal economy promotes informal remittance services in Sri Lanka. The policy decision to peg local currency to US dollars as a result of a shortage of foreign exchange had forced people to use informal channels for different purposes. The unclear and vague customer due diligence process of the anti-money laundering and countering the financing of terrorism (AML/CFT) regime also has forced people to use informal remittance services. Criminals especially drug traffickers have grabbed the promoted informal remittance services to transfer proceeds from Sri Lanka to overseas drug suppliers. On the other hand, systematic deficiencies in monitoring and regulation of movement of fund transfers and merchandise across borders provide opportunities for criminals to use different TBML techniques to transfer funds. These limitations force policymakers and regulators to think of developing a comprehensive payment ecosystem to prevent money laundering and terrorist financing. Therefore, the global initiative is required to move towards a payment ecosystem from a recommendation-based AML/CFT regime to reduce global crimes.Research limitations/implicationsThis study was designed to discuss the implications of TBML and informal remittance services on the balance of payments and net foreign assets in a small open economy. The structure and size of the economy, the strength of the overall economy and the AML/CFT regime will play an important role in controlling criminal activities and combating money laundering of an economy;hence, the impact of TBML and informal remittance services will vary accordingly across the countriesOriginality/valueThis paper is an original work done by the authors, which discusses the implications of TBML and informal remittance services on the balance of payments and net foreign assets of an emerging market context.

BIST Tourism and BIST Electricity Index Relationship

In this study, which is based on daily data, the relationship between BIST electricity index and BIST tourism index was measured between 2012:M9 – 2022:M9 periods. The aim of the study is to measure the relationship between BIST electricity index and BIST tourism index. VAR Granger causality test was applied to determine whether there is any causal relationship between the variables. It has been determined as a result of the analysis that the BIST electricity index has no effect on the BIST tourism index. Two-way ineffectiveness was determined among the variables. In addition, it was obtained as a result of the analysis that the applied correlation relationship was weak between these variables. The results obtained from the study are important in terms of measuring the effects among BIST indices.

ANALYSIS OF THE EFFECT OF MACROPRUDENTIAL AND MACROPRUDENTIAL INDICATORS ON THE STOCK PRICE INDEX OF ISLAMIC BANKS IN INDONESIA USING THE ERROR CORRECTION MODEL

The experience of various crises that have occurred, including the impact of the Covid-19 pandemic, presents a challenge to implement macroprudential policies to ensure the financial system survives and continues to carry out its function in driving the economy. The existing macroprudential policies tend to be individual and focus on prudent banking and other financial institutions. Economic fluctuations that occur on the macro side will greatly impact, either directly or indirectly, the stock price index, as well as the company's internal indicators which are considered to have a major influence on the decisions of investors and potential investors to take action on the stock exchange. The type of research used in this research is quantitative research. The nature of this research is descriptive with a quantitative approach. The data collection technique in this research is Literature Study. The test carried out in this study is the multiple linear regression analysis test (multiple linear regression method), this study uses the ECM model to obtain the best model which includes the classical assumption test. The results of this study based on the partial short-term relationship test, it can be concluded that the Exchange Rate, Inflation, and TPF in the short term have no significant effect on the PNBS Stock Price Index. Meanwhile, short-term CAR has a significant positive effect on the PNBS Stock Price Index. Based on the results of the partial long-term relationship test, it can be concluded that in the long term, the Exchange Rate has a significant negative effect and TPF and CAR have a significant positive effect on the PNBS Stock Price Index while Inflation has no significant effect on the PNBS Stock Price Index. Based on the output results of the simultaneous short-term and long-term F test, it shows that all independent variables simultaneously have a significant effect on the PNBS Stock Price Index in the short term. Based on the provisions of the MUI DSN through the issued fatwas related to the Sharia capital market and Sharia shares, it is explained that Sharia stock investment to invest according to the perspective of Sharia economic law is allowed. [ FROM AUTHOR] Copyright of Jurnal Syntax Admiration is the property of Ridwan Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Computational mathematics applied in the identification of the risk of indirect contagion of COVID-19 in university classrooms

This exploratory study evaluated the risk of contagion from airborne diseases, such as coronaviruses, in schools. For three days, the concentration of carbon dioxide in two university classrooms was monitored for 90 minutes, while the students took their math classes. We use these values to validate a first-order model for carbon dioxide concentration and calculate the air exchange rate indirectly (avoiding the need for expensive measurement equipment). The air exchange rate obtained allowed us to assess whether the usual ventilation systems (both natural and mechanical) are sufficient to guarantee a low risk of contagion of aerosols due to respiration. The results show that the risk of contagion is low if three factors are considered: the level of conversation within the classroom, the usage of a moisture extraction system, and the lecture duration. The risk is low if the lecture time is less than 50 minutes, the level of conversation is moderate, and a moisture extraction system is available. If these conditions are not met the risk is considerably higher even if mechanical ventilation is employed.

Pass-through with volatile exchange rates and inflation targeting

As central banks struggle against high inflation in the aftermath of the Covid-19 pandemic and the war in the Ukraine, it is essential to understand the open economy aspects of inflation determination. Using a Bayesian VAR with time-varying parameters and stochastic volatility, we analyze the behavior of pass-through across time and in relation to macroeconomic variables. Pass-through increases with the size of the volatility of the exchange rate and the level, variance and persistence of shocks to domestic prices, which is in line with theory. The persistence of exchange rate shocks is associated with higher pass-through only for observations with low inflation. Furthermore, the effect of inflation persistence on pass-through is much higher for exchange rate appreciations than for depreciations.

Analysis of the Czech Intraday Electricity Market During COVID-19 Pandemic from the Multifractal Perspective

This paper investigates a progress of the maturity of the Czech intraday electricity market during the COVID-19 pandemic by employing the multifractal analysis. Our results indicate that since intraday electricity returns display multifractal property originating both from long-range correlations and fat-tailed distribution, a sole use of the Hurst exponent is not sufficient, and multifractality characteristics should be used. The quantities describing a multifractal behavior indicate in some periods higher stage of market development operating on short temporal scales compared to the larger temporal scales, especially the MLM index. In some periods, they are in close agreement with the Hurst approach (e.g., July 2020). Moreover, the ADL models indicate a positive association of the Hurst exponent on short temporal scales with its lagged values and new cases of the COVID-19. On short temporal scales, the rate of new COVID-19 cases was positively related to the strength of multifractality, i.e., smaller degree of maturity, both by singularity spectrum width and MLM index. We found a nonlinear relationship between the government stringent policy and the Hurst exponent on long temporal scales, singularity spectrum width and the MLM index on short temporal scales, indicating that the loose anti-COVID policies are associated with more mature market and vice versa. On the contrary, on its long counterpart, the relationships are weaker and opposite in signs.

The relationship between crude oil futures and exchange rates in the context of the Covid-19 shock: a tale of two markets

We examine the high-frequency intraday return and volatility transmission between crude oil futures prices and exchange rates during the 2020 Covid-19 pandemic in the context of two markets: the newly established renminbi-denominated Shanghai International Energy Exchange in China and the US-dollar-denominated Brent market in the United Kingdom. By controlling for the influence of the stock markets, our findings reveal significant disparities in return linkages, yet fairly comparable volatility transmission patterns. The International Energy Exchange shows no return linkages with exchange rates except before the shock, while Brent consistently shows return spillovers from crude oil futures prices to exchange rates. In both markets, the volatility spillovers from exchange rates to crude oil futures prices are unidirectional prior to the shock but become bidirectional as a result of the shock. Nevertheless, both the return and volatility spillover patterns in China resemble those in the United Kingdom when utilizing offshore instead of onshore exchange rates. Such similarities in return and volatility spillovers can also be observed during the 2022 Covid-19 shock that emerged in Shanghai. These findings have significant practical implications. © Infopro Digital Limited 2023.

The global financial cycle and capital flows during the COVID-19 pandemic.

We estimate the heterogeneous effect of the global financial cycle on exchange rates and cross-border capital flows during the COVID-19 pandemic, using weekly exchange rate and portfolio flow data for a panel of 59 advanced and emerging market economies. We estimate a global financial cycle (GFC) index at the weekly frequency with data through the end of 2021. We then estimate the country-specific sensitivities of exchange rates and capital flows to fluctuations in the GFC. The ability of the GFC to explain fluctuations in exchange rates and capital flows increased dramatically during the pandemic. There is significant cross-country heterogeneity in the response of exchange rates or capital flows to fluctuations in the GFC. During the pandemic, high-frequency indicators like weekly changes in Covid cases and vaccination rates were just as important as standard macroeconomic fundamentals like the current account, reserves, and net foreign assets in explaining this heterogeneity.

Uncertain hypothesis test for uncertain differential equations

Uncertain hypothesis test is a statistical tool that uses uncertainty theory to determine whether some hypotheses are correct or not based on observed data. As an application of uncertain hypothesis test, this paper proposes a method to test whether an uncertain differential equation fits the observed data or not. In order to demonstrate the test method, some numerical examples are provided. Finally, both uncertain currency model and stochastic currency model are used to model US Dollar to Chinese Yuan (USD–CNY) exchange rates. As a result, it is shown that the uncertain currency model fits the exchange rates well, but the stochastic currency model does not.

Quantile connectedness between oil price shocks and exchange rates

Oil is an energy resource and a driver of global economic activities. The increasing need for oil amplifies its trade and places pressure on the current account balance, which causes exchange rate fluctuations. We transcend the mean-based connectedness measures to explore the oil shocks-exchange rates nexus from an asymmetric perspective. With daily data from 07-03–1996 to 22-08-2022, we analyse the quantile dynamic spillovers between oil price shocks and exchange rates of oil-exporting and oil-importing economies. We show that shock sizes shape the system returns and volatility connectedness, with lower-tailed and upper-tailed shocks having a greater influence on the system connectedness than shocks modelled at the conditional median. By demonstrating asymmetry, the findings emphasise that for a detailed comprehension of the oil shocks-exchange rates connectedness under extreme shocks, it is necessary to go beyond mean-based connectedness metrics. The implications of our findings are important for investors, policymakers, and practitioners.

Do the macro and global economic factors drive the nonperforming loans in GCC economies?

PurposeThe current study aims to investigate the determinants of nonperforming loans (NPLs) in the GCC economies during the period spanning 2000 to 2018. It also examines whether the worldwide financial crisis of 2007–2008, which brought the issue of non–performing loans to the greater attention of academics and policymakers, had a substantial impact on NPLs in this region.Design/methodology/approachThe sample consists of 53 conventional banks from GCC countries, and the basic data for the study is obtained from various sources such as Bankscope, IMF World Economic Outlook, World Bank and Chicago Board of Options Exchange Market Volatility Index. The estimations were done by dynamic panel data regression modeling using system generalized methods of moments.FindingsThe findings reveal that both, the non-oil real GDP growth rate and inflation have favorable effects on NPLs. On the other hand, domestic credit to the private sector and the volatility index have an adverse effect on NPLs. Furthermore, the period-wise analysis shows that the relevance and significance of the determinants of NPLs vary between the precrisis and postcrisis periods. It is also reflected through the intercept dummy, which is found to be significant, indicating that the financial crisis, as a global economic factor, had a significant impact on NPLs. A number of robustness tests are applied, which indicate that the results are mostly robust and consistent in terms of the significance of the explanatory variables and the direction of their relationship with the dependent variable.Practical implicationsPolicymakers and bank authorities must strive to maintain a healthy economy and implement macroprudential policies to improve the financial stability of banks and reduce credit risk.Originality/valueTo the best of the authors' knowledge, this is likely the first study that empirically investigates the influence of the financial crisis on NPLs in the context of GCC economies. In addition, the research spans 19 years to produce more conclusive results.

Influence of the global environment on capital flows in the London Office market

PurposeThe London office market is a major destination of international real estate capital and arguably the epicentre of international real estate investment over the past decade. However, the increase in global uncertainties in recent years due to socio-economic and political trends highlights the need for more insights into the behaviour of international real estate capital flows. The purpose of this study is to evaluate the influence of the global and domestic environment on international real estate investment activities within the London office market over the period 2007–2017.Design/methodology/approachThis study adopts an auto-regressive distributed lag approach using the real capital analytics (RCA) international real estate investment data. The RCA data analyses quarterly cross-border investment transactions within the central London office market for the period 2007–2017.FindingsThe study provides insights on the critical differences in the influence of the domestic and global environment on cross-border investment activities in this office market, specifically highlighting the significance of the influence of the global environment in the long run. In the short run, the influence of factors reflective of both the domestic and international environment are important indicating that international capital flows into the London office market is contextualised by the interaction of different factors.Originality/valueThe authors provide a holistic study of the influence of both the domestic and international environment on cross-border investment activities in the London office market, providing more insights on the behaviour of global real estate capital flows.

ARIMA Model based Time Series Modelling and Prediction of Foreign Exchange Rate against US Dollar

Exchange rate forecasting has proven challenging for players like traders and professionals in this current financial industry. Econometric and statistical models are often utilized in the analysis and forecasting of foreign exchange rate. Governments, financial organizations, and investors prioritize analyzing the future behaviour of currency pairs because this analyzing technique is being utilized to understand a country's economic status and to make a decision on whether to do any transactions of goods from that country. Several models are used to predict this kind of time-series with adequate accuracy. However, because of the random nature of these time series, strong predicting performance is difficult to achieve. During the Covid-19 situation, there is a drastic change in the exchange rate worldwide. This paper examines the behaviour of Australia's (AUD) daily foreign exchange rates against the US Dollar from January 2016 to December 2020 and forecasts the 2021 exchange rate using the ARIMA model. For better accuracy, technical indicators such as Interest Rate Differential, GDP Growth Rate and Unemployment Rate are also taken into account. In exchange rate forecasting, there are various types of performance measures based on which the accuracy of the forecasted result is computed. This paper examines seven performance measures and found that the accuracy of the forecasted results is adequate with the actual data. © 2022 IEEE.

Price Volatility Modeling for the Lumber Futures Market: A Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling Approach

Lumber is one of the most essential forest products in the United States. During the first year of the COVID-19 pandemic, lumber prices almost quadrupled, and fluctuations reached record levels. Although market experts have pointed to various drivers of such high price volatility, no firm conclusions have been drawn yet. Using the generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) framework, this study assesses the potential drivers of lumber price volatility, with predictors including the Google Trends Web Search Index, housing starts, US lumber production quantity, and VIX index, representing public attention, housing demand, lumber supply, and macroeconomic concerns, respectively. We have found that housing demand is the key driver of lumber price volatility, followed by public attention. It is worth noting that US lumber supply and macroeconomic concerns have played a modest role in explaining lumber price volatility. Also, forecasting lumber price by using the housing demand variable substantially outperforms others. Market participants, including lumber mills, wholesalers, and home builders can get valuable information from the housing market to manage lumber price risk.Study Implications: The findings of this study can be used to improve hedging strategies, design option pricing formulas, and setting margin requirements. Critical information for price risk management on the lumber market can be gained by lumber market participants from the housing market. For forest management decisions by landowners, giving close attention to housing market would provide valuable information on the appropriate time for timber harvesting, because changes in the housing market affect lumber price that will indirectly affect the demand for timber, which is the most important factor of production for lumber mills.

Reaction of the USD/PLN currency pair exchange rate to the published macroeconomic data

The results of the research presented in the article regard the importance of publication of macroeconomic data from the United States for the short-term USD/PLN currency pair exchange rate volatility. The main purpose of the research was to indicate what macroeconomic data is important for the short-term USD/PLN exchange rate volatility. The following research questions have been posed does the USD/PLN exchange rate react to the published macroeconomic data from the American economy and second could greater USD/PLN exchange rate volatility be observed during the COVID pandemic and has the war in Ukraine impacted the USD/PLN exchange rate volatility. International Foreign Exchange Market is the largest and most dynamically developing financial market in the world. In the globalized world the exchange rates are mainly influenced by economic factors. The most significant economic factors that impact short-term exchange rate volatility are primarily macroeconomic data from the American economy. Therefore in this article the author attempts to analyze macroeconomic data and their impact on short-term USD/PLN exchange rate volatility. Data based on which the research was made is as follows: Consumer Price Index, Non-Farm Payrolls (NFP), Services PMI, Manufacturing PMI, Empire State Manufacturing Index or Retail Sales. The analysis of connections between the publication of macroeconomic data and the reaction of exchange rates was carried out using the linear regression model with GARCH process for the random parameter. Conclusions of this research is exchange rate volatility USD/PLN was higher after publications of the macroeconomic data from Americans economy. The strongest exchange rate reaction was after publication of data regarding inflation, Manufacturing PMI and Retail Sales. In the COVID (1.03.20-14.02.22) period we observed increased USD/PLN exchange rate volatility. Exchange rate volatility was expressly larger in the period of war in Ukraine (15.02.22 - end of experiment).