Macroeconomic Risk Research Articles

The impact of liquidity conditions on the time-varying link between U.S. municipal green bonds and major risky markets during the COVID-19 crisis: A machine learning approach

In this study, we aim to investigate the role of the liquidity risk channel in affecting the dynamic conditional correlations (DCCs) between the U.S. municipal green bonds and risky assets (energy commodities and stocks) by accounting for other macroeconomic risks and uncertainties during the COVID-19 crisis period. To explore the underlying mechanism behind the DCCs, we first derive the DCCs and then use novel machine learning techniques, such as CatBoost, Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) models and select the most effective one based on its performance metrics. We also employ the Shapley Additive Explanations (SHAP) method to gain a greater understanding of machine learning predictions. The baseline findings suggest the critical role of the rising term spread in increasing the DCCs between the U.S. municipal green bonds and risky assets during the COVID-19 crisis. Equally important, we observe that this role is more pronounced at high levels of the term spread and that the term spread frequently interacts with funding liquidity conditions (TED spread). Our analysis holds valuable implications for the implementation of informed policy sets and the development of optimal portfolio diversification strategies in global markets.

Learning about the consumption risk exposure of firms

We structurally estimate an investment-based asset pricing model, in which firms' exposure to macroeconomic risk is unknown. Bayesian beliefs about this parameter are updated from firms' and industry peers' comovement between their productivity and consumption growth. The model implies that discount rates rise endogenously with the perceived risk exposure of firms, thereby depressing investment and valuation ratios. We test these predictions in the data and find strong support for them. We also confirm that cross-sectional learning from peers is crucial and that alternative Bayesian risk estimates, which ignore peer observations, do not predict firm variables.

Macroeconomic Risks and Monetary Policy in Central European Countries: Parallels in the Czech Republic, Hungary, and Poland

Changes in interest rates, inflation, and exchange rates are the main components of macroeconomic risks (financial risks) in projects evaluation. However, the conduct of monetary policy as well as its impact on the economic environment is seldom considered as an important component of macroeconomic risks. In this paper, we offer a simple framework to analyze the conduct of monetary policy. We examine the stabilizing properties of monetary policy, its impact, and the parallels in the monetary policy approaches taken in the Czech Republic, Hungary, and Poland until the pandemic. We provide a simple theoretical background to motivate the main elements of the debate and the choice of policy strategy. We then rationalize the adoption of a form of flexible inflation targeting (FIT). It is characterized by an explicit concern over exchange rates. The empirical evidence, consisting of calibrated and extended Taylor rules, together with local projections estimates, suggests that monetary policy has been practiced with considerable flexibility by all three central banks and has contributed to business cycle stabilization in the region. Most notably, the exchange rate plays an important role in the conduct of monetary policy.

Macroeconomic Determinants of Financial Failure Risk in Airlines

The objective of this study is to identify the macroeconomic factors that influence the risk of financial failure in the aviation industry. Within the parameters of the study, a sample of 11irline firms operating between 2009 and 2019 was analyzed to determine the factors influencing the likelihood of financial failure. The cost of fuel, interest rates, inflation rates, and currency rates were utilized as macroeconomic variables that could have an impact on airline enterprises' ability to meet ends. Financial data and macroeconomic data of the airline companies in the sample were obtained from Thomson Reuters Eikon Datastream. The methodology of the study consists of 2 stages. In the first stage, Altman Z'' Score method is used. Then, panel data analysis method is preferred to reveal the relationship between financial failure and macroeconomic factors. According to the findings of the random effects panel data study, exchange rates and interest rates have a negative impact on financial failure. The results of the changes in interest and exchange rates suggest that governments and airlines should concentrate on policies that will strengthen the aviation sector’s financial viability. To manage these risks more effectively, financial managers must closely examine the effects of rising macroeconomic risk and the corresponding financial failure effects. Airline managers, private and institutional investors should monitor policy uncertainty, assuming that exchange rate uncertainty is a driving force in financial failure. In addition, airline companies should review their hedging strategies against exchange rate risk.

Holding the economy by the tail: analysis of short- and long-run macroeconomic risks

We put forward a macro-financial empirical modeling framework that can examine the tails of distributions of macroeconomic variables and the implied risks. It does so without quantile regression, also allowing for non-normal distributions. The framework offers a number of relevant insights into higher moments of the US output growth distribution, as well as the effects of monetary policy and financial (risk premia) shocks on downside macroeconomic risk. This is not only from the short-run perspective but also from the long-run perspective, which has remained largely unexamined in the existing Macro-at-Risk literature. In particular, we estimate the short-run (conditional) and long-run US output growth distributions and study their evolution. The short-run analysis finds that monetary policy and financial shocks render the conditional output growth distribution asymmetric. As such, they affect downside risk over and above their impact on the conditional mean that policymakers routinely focus on. The long-run analysis indicates that US output growth left-tail risk showed a general downward trend in the two decades preceding the Global Financial Crisis (GFC), but this trend got reversed post-2008. Our examination strongly points to the adopted unconventional monetary policy framework featuring quantitative easing as a potential source of elevated long-run downside tail risk in the post-GFC period.

An Associative Analysis Method to Estimate Impact between Financial Market Risk and Macroeconomic Risk

The intertwining and close correlation between financial market risk and macroeconomic risk have been a focal point of academic research. By constructing financial stress index and macroeconomic risk index, and employing the Time-Varying Parameter Vector Autoregression (TVP-VAR) model, this study analyzes the complex dynamic interactions between financial market risk and macroeconomic risk. The results indicate a bidirectional and intersecting relationship between financial market risk and macroeconomic risk. Financial market risk exerts a relatively significant impact on macroeconomic risk, and its accumulation exacerbates the downward pressure on the macroeconomy, while its alleviation does not promptly lead to economic prosperity. Moreover, there exists a significant time-varying correlation between financial market risk and macroeconomic risk, with macroeconomic risk continuously augmenting its promoting effect on financial market risk.

Private ownership and management control decisions in infrastructure from the perspective of Transaction Cost Theory: Evidence from emerging economies

AbstractFrom the perspective of Transaction Cost Theory, this paper proposes a conceptual model to assess ownership and management control decisions of private partners in public‐private partnerships for infrastructure with regard generic risk factors, namely asset specificity, demand risk, environmental risk, social risk, macroeconomic risk, and governance or behavioral risk. Using an ordinal logistic model, hypotheses are tested on data covering 2152 projects in 12 emerging countries for the period 2010–2019. Overall results indicate that the extent of private ownership and management control is negatively related to risks, the marginal effects of which are moderated by high‐quality public institutions.

Regulatory policy uncertainty, banking industry innovations and financial development among emerging markets

PurposeThis study examines the extent to which regulatory policy uncertainty, macroeconomic risk, banking industry innovations, etc. influence variability in financial sector development among emerging economies in sub-Sahara Africa (SSA).Design/methodology/approachData for the empirical inquiry were compiled from a sample of 25 economies from the subregion from 2010 to 2020. Empirical estimates examining the relationships noted above were carried out using the two-step system generalized method of moments estimation technique.FindingsResults the empirical estimates suggest that regulatory policy uncertainty and macroeconomic risk adversely influence or constrain financial sector development among the economies examined in the study. Banking industry innovations on the other hand is found to positively influence the development of the financial sector in these economies. Furthermore, moderating empirical analysis suggests that effective governance positively moderates the relationship between banking industry innovations and financial development among economies in the subregion.Originality/valueThis study’s approach to the mechanics of financial development among economies in SSA is designed to offer different perspectives to those found in the existing literature on financial development in three fundamental ways. First, although the verification of the role of banking industry innovations in financial development may not be new, it is important to point out that the approach used in this study is based on an index for innovations with different constituents or principal components in its construction; making the variable significantly different from what has been examined in the literature. In addition, the review of regulatory policy uncertainty and macroeconomic risk (both variables are multifaceted constructs using the principal component analysis procedure) further brings into this study’s analysis, a different approach to examining conditions influencing variability in financial development among developing economies.

Geopolitical risk and stock market development

While previous literature has documented adverse impacts on financial markets in the days following individual acts of terrorism or conflict-related events, we consider the more general, ongoing uncertainty those events contribute to: geopolitical risk (GPR). Using a sample of 37 countries spanning 1975–2019, we provide evidence of a strong, negative relationship between GPR and stock market development. To support our main results we run a series of robustness and endogeneity checks, in the process demonstrating that the impact of GPR is distinct from other macroeconomic risks such as economic policy uncertainty. We also consider several dimensions of heterogeneity among countries that cause the effects of GPR on stock market development to vary, providing more insight into those effects. In particular, we find that GPR’s negative impact is stronger for those in North America and Europe as compared to Asia. We also find that GPR’s effect is stronger for economies with higher levels of investment, which is consistent with our theory of investment as a mechanism for GPR’s influence on stock market development.

The role of major markets in predicting the U.S. municipal green bond market performance: New evidence from machine learning models

This study aims to examine the impact of major markets (conventional bond, stock, and energy commodity markets) on the performance of U.S. municipal green bonds, accounting for economic risk factors. We also investigate the interactions between major markets and economic risk factors. In our analysis, we employ machine learning techniques, such as Random Forest (RF), Extreme Gradient Boosting (XGBoost), CatBoost, and Light Gradient Boosting Machine (LightGBM) models and choose the best one depending on its performance measures. The analysis considers two sub-periods: the pre-COVID-19 and COVID-19 crisis periods. The Shapley Additive Explanations (SHAP) method is used to better interpret machine learning predictions. The main results indicate that, on the one hand, higher values of conventional bond market performance lead to higher municipal green bond market performance levels for the pre-COVID-19 period. On the other hand, compared to the impact of the conventional bond market, the stock and energy commodity markets have a more significant impact on the U.S. municipal green bonds during the COVID-19 crisis period. Last but not least, we find that major markets interact frequently with some macroeconomic risks and uncertainties during the COVID-19 crisis. Our research provides new insights into the investment potential of municipal green bonds.

Is the cash-returns relationship risk induced?

Whether there is a cash anomaly and what drives the cash–returns relationship are unclear. By constructing a cash risk factor, this study explores the cash–returns relationship and the mechanisms underlying it. We find that the cash factor is pervasive and captures co-movement in stock returns, indicating a significant cash–returns relationship. The factor loading cannot predict returns after controlling for the cash characteristic and has a negative relationship with the implied cost of capital. Also, the cash factor does not reflect future macroeconomic risk. These results are not consistent with rational capital asset pricing theories and cast doubts on the role of the risk explanation while supporting the role of the mispricing effect in the cash–returns relationship.

Transformation of Household Savings in the Russian Federation in Conditions of High Macroeconomic Risks in 2022

In the context of growing macroeconomic risks in 2022 caused by the financial and economic consequences of the global pandemic, the application of unprecedented sectoral and personal sanctions against the Russian Federation has led to the formation of new trends in the functioning of the finances of Russian households. The factors mentioned above change their income level, socio-economic motivation, consumer attitudes and, as a result, the volume and structure of citizens' savings. The study used the decile method of household income analysis in 2022. As a result of the study, the following trends were revealed: the incomes of households with the lowest incomes in 2022 practically did not fall due to the active social support of the state; the incomes of households with relatively high wages decreased by 2–3 %; during 2022, the value of organized savings decreased, and the value of unorganized savings on the contrary increased, especially in foreign currency; income analysis has shown that two thirds of households are actually unable to form savings, creates small insurance reserves.

Ризики монетарної політики: “нова реальність”

Introduction. The COVID-19 pandemic has forced central banks to make a significant correction of their monetary policy, which has been discussed in many academician publications. At the same time, much less attention has been paid to the question of the risks that arise. Problem Statement. The coronavirus pandemic was the first wave of new disruptive forces that created new and seriously exacerbated some existing risks, including economic ones, and, in particular, those that arise during the implementation of monetary policy, or significantly affect it. Further events caused by the full-scale invasion of Russian troops into Ukraine became the second wave, which became felt throughout the world and only cemented the state of the “new reality”. Purpose. Analysis and systematization of existing risk assessments that arise in connection with the modification of monetary policy in response to the threat of the COVID-19 pandemic, independent identification of additional risks and a comprehensive qualitative assessment of the degree of threats arising from these risks. Methods. The methodology of the system approach, factual, situational analysis and synthesis, and the event analysis method, which is traditional for analyzing whether the relevant event has a significant impact on a certain activity (in our case, monetary policy), were used. Results. The “new reality” caused by the coronavirus pandemic and established by the full-scale invasion of Russian troops into Ukraine led to the emergence of a number of macroeconomic risks that were a direct result of these events (“panic risk”) or its consequences, caused not so much by, for example, the pandemic itself, but ill-conceived, sometimes inadequate anti-pandemic measures resorted to by governments and, to a lesser extent, monetary authorities (risks of economic crisis and stagflation). At the same time, the triggers of these macroeconomic risks, in addition to panic, were some specific financial risks (credit, currency, interest), insufficient attention to the manifestation of which in the conditions of the “new reality” led to the emergence of a serious systemic risk in some countries. In general, however, it was possible to keep the situation under control, which, however, forced the fiscal and monetary authorities to take extraordinary measures. Conclusions. The coronavirus pandemic caused serious upheavals in the field of monetary relations and created new and increased traditional risks for actors in this industry (which, to one degree or another, includes all participants in economic relations). However, considering the qualitative side of the problem, it can be indicated that the mentioned risks are divided, first of all, into i) risks for monetary policy itself and ii) risks arising from the conduct of monetary policy, which pose threats to the relevant sectors of the economy (most often , for the financial and banking system) and return to the monetary authorities in the form of new challenges that will require a certain correction of their policy in the field of monetary relations.

Transitory and permanent shock transmissions between real estate investment trusts and other assets: Evidence from time‐frequency decomposition and machine learning

AbstractWe evaluate asset returns and volatility connectedness using the time‐frequency connectedness model and machine learning approaches. Using 48 years of monthly indices of equity real estate investment trusts (EREITs), mortgage real estate investment trusts (MREITs), stocks, commodities, and bonds, we find that shocks to EREIT, and MREIT returns have a transitory impact on other assets. However, asset volatility connectedness among assets occurs at lower frequencies as markets slowly process pricing information. Therefore, shocks to EREIT and MREIT decay gradually and spill over to the other three assets for long periods. We also find that the intensity of the time‐frequency connectedness of returns and volatility varies with business cycles and significant domestic and global non‐recession events. We attribute the dominance of real estate investment trusts (REITs) in destabilising the financial system through long‐term volatility transmission to the heavy linkage of REITs to highly illiquid underlying direct real estate markets and high REITs leverage, making them more sensitive to real estate fundamentals, monetary shocks and macroeconomic risks than stocks and bonds. The result of the algorithm‐based machine learning model broadly supports the dominance of EREITs in the transmission of returns and volatility and shows that commodities have more explanatory power in the transmission of volatility than in returns. The empirical findings have implications for strategic and tactical asset allocation and policy design for market stability.

Using interest rates to predict economic growth: Are corporate bonds better?

AbstractWe consider whether government bonds, through the term structure, or corporate bonds, through the default yield, provide predictive power for output, consumption and investment growth in the United States. Such predictive power will allow policy‐makers to use the information as a leading indicator for macroeconomic performance and will improve our understanding of the links between real and financial markets. Full sample results suggest that both interest rate series exhibit predictive power for each of the macroeconomic growth series. Time‐variation in the predictive coefficient reveals the waning influence of the term structure and the rising influence of the default yield. Forecast results, which are obtained from a rolling window approach, likewise suggest both series have information content for macroeconomic conditions, but there is a change in their relative strengths. These results may arise as interest rates have declined since the highs of the early to mid‐1980s thus reducing the information content of government yields, whereas corporate bonds respond more to investor views of macroeconomic risk, which affects a firm's ability to repay its debt. Furthermore, short‐term rates are largely held unprecedently low since the dotcom crash.

The Impact of Capital Account Opening on RMB Internationalization

At this stage, the internationalization of RMB is inseparable from the opening of capital account, and in this process, it is bound to face the challenge of systemic financial risks. Based on SV-TVP-VAR model, this paper makes a time variant analysis on the systemic financial transmission mechanism of capital account opening Affecting RMB internationalization. It is found that the opening of capital account promotes the development of RMB internationalization, and the international use of RMB will force the expansion of capital account opening. Further research shows that the current capital account is not easy to fully open, capital account convertibility intensifies the spillover of macroeconomic risks and external market risks, and macro prudential supervision needs to be improved. The restraint of capital account opening on monetary liquidity risk and asset bubble risk shows time varying characteristics, and the long-term development of RMB internationalization urgently needs to deepen the reform of financial system.

The Relationship between the Budgetary Fiscal Policy and Macroeconomic Indicators, a Comparative Study of Germany-France versus Romania-Bulgaria

Abstract Fiscal-budgetary policy in the current economic context is a challenge for all EU27 governments. The literature, although consistent on this topic, still does not provide sufficient modeling-based solutions for decision-makers. The objectives of the study are to identify relevant indicators for fiscal-budgetary policy analysis, to build a related statistical database, to conceptualize a fiscal-budgetary policy efficiency model, to test and validate this model and the working hypotheses, to formulate relevant conclusions on the influence of macroeconomic indicators on fiscal-budgetary policy elements and to establish a ranking of fiscal-budgetary efficiency at the level of the four Member States in the European context. As a result, our scientific approach becomes necessary and is based on econometric research on the correlations between fiscal-budgetary policy elements and the evolution of macroeconomic indicators. The main results of the study are the conceptualization of the regional model of correlation between budgetary fiscal policy and macro indicators and the identification of the differentiated influences of macroeconomic elements on the fiscal-budgetary policy according to the level of development of the Member States. The results are useful for supranational decision-makers in setting medium- and long-term fiscal and budgetary policy measures, as well as for economic entities that can adjust their macroeconomic risk behavior and future economic development strategies based on this information.

Forecasting of financial risks of decline in profit and profitability of companies in the retail industry on the basis of correlation and regression analysis of macroeconomic factors

Aim. Development and realization of the innovative approach to forecasting of financial risks of profit and profitability decrease of retail industry companies on the basis of correlation and regression analysis of macroeconomic factors.Tasks. To identify and substantiate the macroeconomic risk factors of decrease in the retail trade turnover of the Russian companies of the retail industry; to develop a methodology of construction and build regression dependence of the total turnover of the companies of the retail trade industry in the Russian Federation (RF) on the macroeconomic factors; to define parameters of the analytical dependence of the retail trade turnover of the leading Russian retailers on the macroeconomic factors; to reveal and argue the position concerning the restrictions of application of correlation and regression analysis.Methods. The authors applied a systematic approach, providing a comprehensive study of the impact of macroeconomic factors on financial risks of profit and profitability reduction, as well as the correlation and regression analysis, methods of mathematical statistics and econometrics.Results. The methodology of estimation and forecasting of financial risks of profit and profitability decrease of the retail industry companies under the influence of external macroeconomic risk factors based on the use of the regression dependence of the retail industry companies turnover on the selected and grounded macroeconomic factors built in the present article is offered.Conclusions. The methodology of building regression dependences of retail turnover on external macroeconomic factors and the methodology of assessing the impact of these factors on the financial risks of reduced profit and profitability indicators proposed in the study are a methodological basis for forecasting changes in the results and efficiency of economic activities of companies in the retail industry and developing preventive measures aimed at reducing the financial risks of such companies. The quantitative assessments of the impact of macroeconomic factors on the retail turnover of leading Russian retailers obtained in the work allow to identify the most significant external macroeconomic risk factors for each of the companies and give a reasonable forecast of changes in retail turnover, profit and profitability indicators of these companies under the influence of macroeconomic factors.

Governance, regulatory quality and financial institutions: emerging economies perspective

PurposeThe study evaluates the effects of governance and other regulatory structures on the development of financial institutions in the subregion of sub-Saharan Africa (SSA).Design/methodology/approachData for the analyses were compiled from relevant sources from 1996 to 2019 from a sample of 36 countries in the subregion. Empirical analyses were carried out using the Prais-Winsten panel corrected standard errors panel estimation technique augmented by pooled ordinary least squares with Driscoll and Kraay (1998) standard errors model.FindingsFindings from the study suggest that governance and institutional quality index, as well as individual governance and regulatory variables, have positive effect on the development of financial institutions among economies in SSA. Further empirical estimates show that output growth volatility has negative moderating impact on the relationship between effective governance, control of corruption, rule of law, regulatory quality, voice and accountability, and development of financial institutions. Additionally, the results show that during periods of heightened macroeconomic risk, financial institutions could benefit from improved governance and effective regulatory structures.Originality/valueCompared to related studies that have reviewed the discourse on financial institutions, this study rather focuses on how governance structures and institutions influence development of financial institutions instead of the impact of financial institution on the broader economy. The authors further augment this interaction by examining how the relationship in question may be moderated by macroeconomic shocks.

Implications of macroeconomic risks on NHFC'S incremental housing finance in South Africa

PurposeThe challenge of accessibility to adequate housing in several countries by a large percentage of citizens has given rise to different housing programs designed to facilitate access to affordable housing. In South Africa, the National Housing Finance Corporation (NHFC) was created to provides housing loans to low- and middle-income earners. Thus, the purpose of this study was to evaluate the implication of the macroeconomic risk elements on the performance of the NHFC incremental housing finance.Design/methodology/approachThis study used a mixed-method approach to examine the time-series data of the NHFC over 17 years (2003–2020), relative to selected macroeconomic indicators. Additionally, this study analysed primary data from a 2022 survey of NHFC Executives.FindingsThis study found that incremental housing finance addresses a housing affordability gap, caters to disadvantaged groups, adapts to changing macroeconomic conditions and can mitigate default risk. It also finds that the performance of the NHFC’s incremental housing finance is premised on the behaviour of the macroeconomic elements that drive its strategy in South Africa.Originality/valueUnlike previous works on housing finance, this case study of the NHFC considers the implication of macroeconomic trends when disbursing incremental housing finance to low- and middle-level income earners as a risk mitigation measure for the South African market. Its mixed method use of quantitative and qualitative data also allows a robust insight into trends that drive investment in incremental housing finance in South Africa.