Economic Uncertainty Research Articles

Navigating Economic Uncertainties: The Role of Technological Innovations in Enhancing Supply Chain Resilience

This study explores the multifaceted impact of economic indicators, financial market dynamics, and technological innovations on supply chain efficiency and resilience. Through comprehensive quantitative analyses, including panel data regression, multivariate regression, and time-series analysis, we dissect the relationship between GDP growth rates, inflation, unemployment rates, interest rate fluctuations, exchange rate volatility, stock market trends, and supply chain performance metrics. Our findings highlight a significant correlation between economic growth and supply chain efficiencies, the exacerbating effect of inflation and unemployment on supply chain costs and demand, and the nuanced impacts of financial market dynamics on supply chain financing and operational strategies. Moreover, we delve into the transformative potential of digitalization, automation, blockchain technology, and advanced analytics in mitigating risks associated with economic fluctuations and financial uncertainties. The empirical evidence suggests that technological innovations not only enhance supply chain resilience but also offer strategic advantages in navigating the complexities of global economic landscapes. This study underscores the critical need for adaptive strategies that leverage technological advancements to sustain supply chain competitiveness in an era of economic and financial volatility.

A Holistic Review on Impact of Demonetization on Animal Husbandry Sector

The impact created in the year 2016 by demonetization policy on India's animal husbandry industry analyse different effects which are critically analysed using different studies. The goal of demonetization, which invalidated ₹500 and ₹1000 banknotes, was to suppress corruption, burden the use of counterfeit money, and encourage online transactions [1,2]. Animal husbandry holds as strongest pillar of India's rural economy, and the current study of demonetization examines the short- and long-term effects on it. The short term effects like Price volatility, lack of liquidity, and decreased market demand particularly impacted small-scale livestock, dairy, and poultry producers [3]. The studies also suitably reveal that farmers faced many significant challenges, including loss of livelihood, disrupted supply chains, and restricted access to banking facilities, increased debt, and limited farm investments [4]. The Long-term effects included a rise in the use of formal banking, a move toward digital payments, and structural modifications to cooperatives. The present agriculture and allied industries scenario, which mainly depends on cash transactions, experienced significant disruptions in labor payments, input procurement, and livestock sales etc [2]. The report also assesses government actions, such as initiatives to promote digital payments, sector-specific relief programs, and financial inclusion The policy recommends the need for more efforts to raise digital literacy in rural communities, improved rural banking infrastructure in order to improve the sector's adaptability to future economic uncertainties [5,3].

Financial well-being, anxiety and payment delinquency among student loan holders in the United States: insights from the COVID-19 pandemic

PurposeThe COVID-19 pandemic presented unprecedented challenges, particularly intensifying the financial and psychological burden for individuals with student loans in the United States. Firstly, this study examined the association between student loan ownership and financial well-being during the pandemic. Secondly, among student loan holders, we tested the association of financial anxiety and payment delinquency with COVID-19 shocks and financial knowledge. Lastly, we investigated the associations between the recipients of student loans and their financial well-being, anxiety and behaviors concerning student loans.Design/methodology/approachUtilizing data from the 2021 National Financial Capability Study, we explored how unprecedented economic disruptions have affected student loan holders' financial well-being, levels of debt anxiety and payment delinquency, considering financial knowledge as a critical factor. We conducted Ordinary Least Squares (OLS) and logistic regressions to examine the associations addressed in the purpose of the study.FindingsThe results of regression analyses indicate that individuals with student loans generally experienced lower financial well-being than those without loans. Among student loan holders, COVID-19 shocks were positively associated with student loan anxiety and payment delinquency. Additionally, subjective financial knowledge showed a positive association, while objective financial knowledge displayed a negative association with loan delinquency. Lastly, respondents who secured loans for themselves exhibited lower levels of financial well-being than other student loan holders.Originality/valueThis study represents one of the initial efforts to investigate the issues of financial well-being, debt anxiety and payment delinquency among student loan holders, along with their associations with the potential COVID-19 shocks they experienced. The research shed light on the acute financial stress and mental health challenges faced by student loan holders during global crises, highlighting the significance of effective policy development for student debt management and borrower support during times of economic uncertainty.

Uncertainties of Economic Policy and Government Management Stability Played Important Roles in Increasing Suicides in Japan from 2009 to 2023.

Standardized suicide mortality rates per 100,000 (SMRs) in Japan consistently decreased from 2009 to 2019 but increased from 2020. The causes of these temporal SMR fluctuations remain to be clarified. Therefore, this study was conducted to identify the causalities underlying the recently transformed fluctuations of suicide mortality in Japan. Monthly suicide numbers disaggregated by sex and social standing, and political uncertainty indices, such as economic policy uncertainty (EPU) and government management instability (AENROP), were obtained from Japanese government databases. Interrupted time-series analysis was performed to analyze temporal fluctuations of SMRs disaggregated by sex/social standing associated with the three General Principles of Suicide Prevention Policy (GPSPP) periods and the COVID-19 pandemic. Panel data and vector autoregressive analyses were conducted to investigate causalities from political uncertainties to SMRs. During the first and second GPSPPs (2009-2017), all SMRs disaggregated by sex and social standing decreased, whereas those of unemployed females did not change. During the third GPSPP (2017-2022), decreasing trends in all SMRs were attenuated compared to previous periods. All female SMRs, except unemployed females, showed sharp increases synchronized with the pandemic outbreak. No male SMRs showed sharply increasing at the pandemic outbreak. SMRs of unemployed males/females drastically increased in the later periods of the pandemic, while SMRs of employed and multiple-person/single-person household males did not increase during the pandemic. SMR of unemployed males was positively related to AENROP but not EPU. Other male SMRs were positively related to EPU/AENROP. On the contrary, not all female SMRs were related to EPU/AENROP. Increasing AENROP generally contributed to increasing male SMRs throughout the observation period; however, susceptibility to AENROP and/or political information might have unexpectedly contributed to suppressing the sharply increasing male SMRs induced by large-scale social shocks (the COVID-19 pandemic outbreak) in Japan.

Economic policy uncertainty and narrative R&D disclosures

This study examines the impact of economic policy uncertainty on narrative R&D disclosure. Analyzing 10-K reports from 1997 to 2020, we find that the quantity of R&D disclosure increases with economic policy uncertainty. We also document that firms provide more forward-looking R&D disclosure during uncertain periods. Finally, we find that such impact is more pronounced for the firms with high return volatility and firms in the early-stage of business cycle. We contribute to the literature by showing how managers adjust R&D disclosures in response to economic policy uncertainty.

Bank loan maturity and corporate investment

This study analyzes bank loan maturity and corporate investment linkage by using novel firm-level data covering the universe of all incorporated firms in Türkiye over the last decade. The results of the panel regression model with multi-dimensional fixed effects reveal that loan maturity has a significant positive association with investment, indicating that longer debt maturity fosters corporate investment. The results reveal that the positive linkage between longer debt maturity and investment is more pronounced for small and medium-sized enterprises (SMEs). This is also the case for young firms and firms with high growth opportunities. Considering the evidence provided in the literature that bank lending conditions, including maturity structure, are highly cyclical and vulnerable to financial conditions and economic policy uncertainties, our findings highlight the importance of reducing the policy uncertainties as well as the importance of policies that make equity financing more attractive and deepen the capital markets.

Analysis of Financial Stability in Indian Automobile Industry

The Indian automobile industry plays a pivotal role in the nation's economic landscape, contributing significantly to GDP, employment, and technological advancement. In recent years, the sector has faced considerable challenges, including shifting consumer preferences, regulatory changes, economic uncertainties, and the impact of global disruptions such as the COVID-19 pandemic. This paper aims to analyze the financial stability of the Indian automobile industry by evaluating key financial indicators, such as profitability, liquidity, and solvency. It also explores the industry's adaptability in the face of macroeconomic challenges, including supply chain disruptions, rising input costs, and changing regulatory landscapes related to environmental standards. Furthermore, the paper assesses the influence of government initiatives like the Production-Linked Incentive (PLI) scheme and electric vehicle adoption on the overall financial health of the sector. By employing both qualitative and quantitative analyses, the study provides insights into the sustainability and resilience of the Indian automobile industry, highlighting the critical factors that determine its financial stability and its potential for future growth in a dynamic economic environment.

COMPARATIVE ANALYSIS OF TIME SERIES FORECASTING MODELS USING ARIMA AND NEURAL NETWORK AUTOREGRESSION METHODS

Gold price fluctuations have a significant impact because gold is a haven asset. When financial markets are volatile, investors tend to turn to safer instruments such as gold, so gold price forecasting becomes important in economic uncertainty. The novelty of this research is the comparative analysis of time series forecasting models using ARIMA and the NNAR methods to predict gold price movements specifically applied to gold price data with non-stationary and non-linear characteristics. The aim is to identify the strengths and limitations of ARIMA and NNAR on such data. ARIMA can only be applied to time series data that are already stationary or have been converted to stationary form through differentiation. However, ARIMA may struggle to capture complex non-linear patterns in non-stationary data. Instead, NNAR can handle non-stationary data more effectively by modeling the complex non-linear relationships between input and output variables. In the NNAR model, the lag values of the time series are used as input variables for the neural network. The dataset used is the closing price of gold with 1449 periods from January 2, 2018, to October 5, 2023. The augmented Dickey-Fuller test dataset obtained a p-value = 0.6746, meaning the data is not stationary. The ARIMA(1, 1, 1) model was selected as the gold price forecasting model and outperformed other candidate ARIMA models based on parameter identification and model diagnosis tests. Model performance is evaluated based on the RMSE and MAE values. In this study, the ARIMA(1, 1, 1) model obtained RMSE = 16.20431 and MAE = 11.13958. The NNAR(1, 10) model produces RMSE = 16.10002 and MAE = 11.09360. Based on the RMSE and MAE values, the NNAR(1, 10) model produces better accuracy than the ARIMA(1, 1, 1) model.

Re-Visiting the Co-movement between FinTech, Economic Policy Uncertainty, Governance Quality and Bank Variability in Pakistan: A Wavelet Coherence Approach

The recent literature about FinTech services in Pakistani commercial banks has grabbed much attention as these services have increased rapidly in the last few decades. This paper examines the co-movement between FinTech, economic policy uncertainty, bank- variability, and governance quality. The data was obtained from 2014-2020 on a monthly frequency. To address the relationship and co-movement, we have applied more advanced and sophisticated econometric models, autoregressive distributed lag model (ARDL), and continuous wavelet (CTW) to investigate the relationship between the variables. These approaches provide flexibility of assumptions for time-series data and provide robust results. The results indicate a short and long-run symmetric relationship with a significant co-movement between the variables.

EXCHANGE RATE DYNAMICS AND THEIR IMPLICATIONS

This research paper explores the dynamics of exchange rate fluctuations and their far-reaching implications for the global economy. Exchange rates are pivotal in shaping trade balances, inflation, and capital flows, making them a critical factor for policymakers, multinational corporations, and investors. By examining both theoretical frameworks and empirical evidence, this study analyzes the effects of exchange rate movements on key economic variables such as inflation rates, gross domestic product (GDP), foreign direct investment (FDI), and international trade balances. The paper employs a combination of econometric modeling and historical data analysis to evaluate how these fluctuations have influenced emerging and developed economies over the past two decades. Results indicate that exchange rate volatility can lead to inflationary pressures in import-dependent economies, disrupt trade balances, and influence FDI inflows. The findings also underscore the importance of stable exchange rate policies to mitigate economic uncertainty. This study concludes with recommendations for future research, particularly regarding the influence of digital currencies and geopolitical tensions on exchange rate stability.

Fintech and Economic Policy Uncertainty Integration: Driving Efficiency in Commercial Banks through the Lens of ARDL Approaches

The financial landscape of Pakistan is changing due to the increased accessibility, affordability, and security of FinTech services. This change is essential for raising the standard of living for Pakistan's economic prospects and certain contributing factors to FinTech. This paper investigates the symmetric and asymmetric relationship between Fintech and economic policy uncertainty, bank variability, and governance quality in commercial banks of Pakistan from 2014 to 2020, considering linearity and non-linearity in the data. The data has been converted to monthly frequency, and the Autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (N- ARDL) models have been applied to address long- and short-run associations. The study results reveal that EPU and bank variability have an asymmetric relationship with Fintech during the long run. In contrast, bank variability is connected during the long and short run. Furthermore, governance quality shows a symmetric relationship with Fintech in the long and short run. However, based on the findings of the error correction framework, there is no significant association in the long run. This paper concludes that Fintech, economic policy uncertainty, and bank variability have an asymmetric relationship, while GQ and Fintech are symmetrically associated. Moreover, it contributes to the existing literature by shedding light on the factors affecting Fintech services in commercial banks along with the financial and economic implications for investors, government, regulatory authorities, policymakers, and banks being institutional investors.

Prospects for the development of foreign economic activities of the Russia banking sector in China

Relevance. In modern conditions of economic uncertainty and difficulties of doing business in connection with the application of sanctions, banks need to look for effective tools and ways to increase the effectiveness of mutual cooperation with other states to overcome the prevailing circumstances. During the work, the main aspects of opening and functioning of a bank branch in China were considered, as well as competitors at both the macro and micro levels were analyzed. Based on the SWOT analysis, the paper identifies the strengths and weaknesses, opportunities and threats of introducing a branch of a Russian bank into the Chinese banking market. The study identifies promising regions for the development of foreign economic activity and forms a range of banking services that contribute to the sustainable development of the branch of the Russian bank in the foreign market.The purpose of the study is to substantiate the need to develop the foreign economic activity of a Russian commercial bank in China.Objectives: Based on a comprehensive analysis and acceptability of the Chinese banking services market, an assessment of the current state of PJSC Expobank, an analysis of competitors in the proposed region and the specifics of a specific location, to develop a plan for opening a bank branch in China.Methodology. The study is aimed at achieving this goal and is based on a review of scientific research by both domestic and foreign economists, as well as an analysis of a number of requirements for opening a bank branch in China.Results. In the course of the work, the process of opening a bank branch in China for carrying out activities was analyzed, the advantages and disadvantages of expanding the boundaries of presence were identified, and promising areas for starting foreign economic activity were proposed.Conclusions. The conducted research gives grounds to conclude that the expansion of the geographical presence in China will allow PJSC Expobank to gain access to world economic centers and expand the boundaries of its activities.

Research on the Predictive Ability of Economic Policy Uncertainty on Stock Returns of Industries

In recent years, the emergence of economic policy uncertainty has had a certain impact on stock returns. It can be used as a research object to explore whether economic policy uncertainty can significantly predict future stock returns. This paper studies the predictive ability of economic policy uncertainty based on relevant data from major industries in the United States from January 1985 to December 2023, including Food industry (Food), Retail Stores industry (Rtail), Fabricated Products industry (FabPr), Drugs, Soap, Perfumes, Tobacco industry (Cnsum), Construction and Construction Materials industry (Cnstr), Consumer Durables industry (Durbl), Automobiles industry (Cars), Textiles, Apparel & Footwear industry (Clths), Machinery and Business Equipment industry (Machn), Chemicals industry (Chems), and Transportation industry(Trans), Utilities industry (Utils), Steel Works Etc industry (Steel), Mining and Minerals industry(Mines), Oil and Petroleum Products industry (Oil), and Banks, Insurance Companies, and Other Financials industry (Finan). Through both in-sample and out-of-sample examines, it is found that economic policy uncertainty is a reliable indicator for predicting stock returns, and its predictive performance is better in Food industry, Retail Stores industry, Fabricated Products industry, Transportation industry, Construction and Construction Materials industry, Consumer Durables industry, Automobiles industry, Textiles, Apparel & Footwear industry, Machinery and Business Equipment industry, Chemicals industry, and Drugs, Soap, Perfumes, Tobacco industry than in Utilities industry, Steel Works Etc industry, Mining and Minerals industry, Oil and Petroleum Products industry, and Banks, Insurance Companies, and Other Financials industry. Meanwhile, by replacing the measurement indicator of economic policy uncertainty, conducting long-horizon forecasting, and using different evaluation periods for robustness checks, it is found that the research conclusions are robust.

Navigating economic policy uncertainty: The role of digital transformation in export product switching

Navigating economic policy uncertainty: The role of digital transformation in export product switching

Do election results resolve economic uncertainty? Evidence from Indian election 2024

We examine the immediate short-term effects of the election results using event study analysis on 1546 NSE-listed firms and find significant adverse market reactions around the counting day. However, the market recovers with expectations of a stable government. Sectoral analysis showed varied recovery across sectors. Cross-sectional analysis indicates that larger firms and those with better fundamentals manage uncertainties better, while volatile and highly-priced stocks suffer more. The findings theoretically contribute to the semi-strong form of the efficient market and uncertain information hypotheses.

Harbor in the storm: How Bitcoin navigates challenges of climate change and global uncertainties

Understanding Bitcoin's (BTC) performance and hedging effects under various uncertainties is crucial. This study combines time-varying Granger causality (TVGC) tests and wavelet time-varying parameter vector autoregression (TVP-VAR) methods to examine the relationship between Bitcoin (BTC) and climate uncertainty (SOI), geopolitical risk (GPR), economic policy uncertainty (EPU), crude oil volatility (OVX), and market volatility (VIX) across both time and frequency domains, from December 19, 2017, to October 16, 2023. The results show that in recent years, the long-term impact of SOI on BTC, as well as political and economic uncertainties, is hard to ignore, but BTC cannot serve as a safe-haven asset against SOI. Wavelet decomposition indicates that during extreme events, BTC exhibits a leading positive co-movement with EPU, GPR, VIX, and OVX in the long term, showing potential as a hedging asset. However, TVGC and wavelet decomposition spillover results further suggest that BTC's hedging capacity against different economic and political uncertainties may be limited during certain extreme events.

Impact of economic policy uncertainty on systemic risk of real enterprises: Evidence from China

This work examines the impact of economic policy uncertainty on the systemic risk of Chinese real firms from the perspectives of financing constraints and external guarantees. The findings suggest that economic policy uncertainty significantly enhances the systemic risk of real firms. The mechanism test shows that economic policy uncertainty will enhance the level of systemic risk of enterprises by exacerbating their financing constraints and expanding the scale of external guarantees. Heterogeneity analysis shows that the negative impact of economic policy uncertainty on systemic risk is more obvious in enterprises with investment and financing maturity mismatches and poorer corporate governance.

A machine learning algorithm to explore the drivers of carbon emissions in Chinese cities

As the world’s largest energy consumer and carbon emitter, the task of carbon emission reduction is imminent. In order to realize the dual-carbon goal at an early date, it is necessary to study the key factors affecting China’s carbon emissions and their non-linear relationships. This paper compares the performance of six machine learning algorithms to that of traditional econometric models in predicting carbon emissions in China from 2011 to 2020 using panel data from 254 cities in China. Specifically, it analyzes the comparative importance of domestic economic, external economic, and policy uncertainty factors as well as the nonparametric relationship between these factors and carbon emissions based on the Extra-trees model. Results show that energy consumption (ENC) remains the root cause of increased carbon emissions among domestic economic factors, although government intervention (GOV) and digital finance (DIG) can significantly reduce it. Next, among the external economic and policy uncertainty factors, foreign direct investment (FDI) and economic policy uncertainty (EPU) are important factors influencing carbon emissions, and the partial dependence plots (PDPs) confirm the pollution haven hypothesis and also reveal the role of EPU in reducing carbon emissions. The heterogeneity of factors affecting carbon emissions is also analyzed under different city sizes, and it is found that ENC is a common driving factor in cities of different sizes, but there are some differences. Finally, appropriate policy recommendations are proposed by us to help China move rapidly towards a green and sustainable development path.

АНАЛІТИКА ДІЯЛЬНОСТІ ПІДПРИЄМСТВ УКРАЇНИ З ВИРОБНИЦТВА ЦЕМЕНТУ В УМОВАХ СИСТЕМНИХ ВИКЛИКІВ

The article examines the activity of Ukrainian cement production enterprises in conditions of systemic challenges. The steady growth of the cement market in Ukraine in 2021 relative to 2020 has been determined. However, the full-scale war in Ukraine significantly affected the activities of cement manufacturing enterprises. The hostilities on the territory of the country have led to a decrease in the demand for cement due to the suspension of construction projects and infrastructure works, as well as due to instability and economic uncertainty. This was reflected in the decrease in business activity in the cement market in Ukraine. In 2022, the number of active cement production entities decreased by 22.2% compared to 2021. The decrease in the number of business entities in the cement industry of Ukraine led to a decrease in the number of employees, particularly, the number of employees decreased by 21.8% in 2022 compared to 2021. Such trends continued in the reduction of personnel costs of cement production enterprises by 25.1% over the last year under review. It has been proven that the most noticeable negative impact of the war on the development of the cement industry in Ukraine can be traced in the dynamics of the volumes of products sold (goods, services) of enterprises in 2022 compared to 2021: the value of this indicator decreased by UAH 7,499,298.9 thousand. or more than a third. As a result, the financial results of cement production enterprises in 2022 significantly worsened compared to 2021. In general, the level of profitability of the operational activities of cement production enterprises in 2022 significantly decreased compared to the previous three years. The most significant decrease was in profitability of operational activity resulting in a reduction of this indicator to the level of -25.6% in 2022. In general, the system challenges for the development of the cement market in Ukraine derived from war require adequate strategic decisions to support this exceptionally important activity for the post-war recovery of Ukraine. The further research of business responses for the current challenges is a perspective of the further studies in the field.

Modernizing Utility Collections through Customer Analytics and AI

The 2020 COVID‐19 pandemic introduced economic calamity and uncertainty in America that had not been seen since the 2007–2008 financial crisis. What began as an uncertain period for individual well‐being soon translated into broader economic issues for the American economy. Businesses facing months of lost revenue, deficits, and uncertainty began weakening financially and, as a result, were forced to reduce staff. In the years that have followed, industries which have historically been able to count on stable revenue, such as utilities, particularly suffered. Struggling households and small businesses began missing consecutive monthly payments, and customer debt climbed to unprecedented levels. As of March 2023, “one in six households across the country were behind on their electric bills.”1 Additionally, instances of non‐residential customers falling behind on their payments emerged. Historic levels of arrears continue to mount pressure on the industry, and traditional approaches to arrear collection are not working.