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This study aims to explore potential paradigm shift in how “global economies” react to adverse macroeconomic conditions from key dominant economies such as the US and the Chinese economies. This is done by examining how economic activities within key economies around the world react to, or are impacted by, modeled adverse macroeconomic condition emanating from the Chinese and the US economies.

To verify potential paradigm shift in how external macroeconomic uncertainty impacts “global” industrial productivity and overall gross domestic product (GDP) growth within selected economies, this study opts for seemingly unrelated regression (SUR) model. Adoption of this method has been influenced by the potential for correlated error terms between modeled adverse macroeconomic condition, industrial productivity and GDP growth variables being tested in a two-equation system.

Empirical results based on SUR analysis find no evidence of this potential paradigm shift within the time frame examined in the study. Estimated results suggest that notwithstanding the recent growth surge of the Chinese economy, macroeconomic happenings within the US economy still exert significantly more influence on key economies around the world. For instance, this study finds that macroeconomic uncertainty associated with the US economy significantly constrains both industrial productivity and overall GDP growth within most of the economies tested, whereas the same condition emanating from the Chinese economy seems to rather have a weak positive impact on the same macroeconomic variables.

Research results are strictly limited to the focus time frame for this study; it is likely that expanded data involving more years beyond what was analyzed in this study could yield different results.

This study is an original research based on data from a reputable US federal institution.

In this chapter I characterize the relationship between macroeconomic variables and the terms structure of interest rates using the recent macro-finance approach adapted to the case of an emerging economy and applying it to Brazil. I find that macro variables help to explain the dynamics of the yield curve in emerging markets, specially in periods of high volatility. Moreover, the notion of great external vulnerability of emerging economies is confirmed by the strong role of the nominal exchange rate change, which explains up to 37% of the variation in yields in Brazil. However, the model does a poor job in forecasting yields during the financial crisis of 2008. This fact seems to be related to the strong fall in international commodity and industrial goods prices (in dollar terms), which limited the passthrough from the strong depreciation of the exchange rate to inflation.

Following Ang and Piazzesi’s (2003) study, the authors use an affine term structure model to study the relevance of macroeconomic (domestic and foreign) factors for Peru’s sovereign yield curve in the period from November 2005 to December 2015. The paper aims to discuss this issue.

Risk premia are modeled as time-varying and depend on both observable and unobservable factors; and the authors estimate a vector autoregressive model considering no-arbitrage assumptions.

The authors find evidence that macro factors help to improve the fit of the model and explain a substantial amount of variation in bond yields. However, their influence is very sensitive to the specification model. Variance decompositions show that macro factors explain a significant share of the movements at the short and middle segments of the yield curve (up to 50 percent), while unobservable factors are the main drivers for most of the movements at the long end of the yield curve (up to 80 percent). Furthermore, the authors find that international markets are relevant for the determination of the risk premium in the short term. Higher uncertainty in international markets increases bond yields, although this effect vanishes quickly. Finally, the authors find that no-arbitrage restrictions with the incorporation of macro factors improve forecasts.

To the authors’ knowledge this is the first application of this type of models using data from an emerging country such as Peru.

This chapter proposes a vector autoregressive VAR model with structural shocks (SVAR) that are identified using sign restrictions, and whose distribution is subject to time varying skewness. The authors also present an efficient Bayesian algorithm to estimate the model. The model allows tracking joint asymmetric risks to macroeconomic variables included in the SVAR, and provides a structural narrative to the evolution of those risks. When faced with euro area data, our estimation suggests that there has been a significant variation in the skewness of demand, supply and monetary policy shocks. Such variation can explain a significant proportion of the joint dynamics of real GDP growth and inflation, and also generates important asymmetric tail risks in those macroeconomic variables. Finally, compared to the literature on growth- and inflation-at-risk, the authors find that financial stress indicators are not enough to explain all the macroeconomic tail risks.

The study examines the effect of macroeconomic risk, inflation uncertainty and instability associated with key macroeconomic indicators on the efficiency of financial institutions among economies in sub-Saharan Africa (SSA).

Data for the empirical inquiry were compiled from 35 SSA economies from 1996 to 2019. The empirical estimates were carried out using pooled ordinary least squares (POLS) with Driscoll and Kraay’s (1998) standard errors.

Reported empirical estimates show that macroeconomic risk and exchange rate volatility constrain the efficiency of financial institutions. Further results suggest that inflation uncertainty has a significant influence on the efficiency of financial institutions among economies in the subregion. Additionally, reviewed empirical estimates show that institutional quality positively moderates the nexus between inflation uncertainty and financial institution efficiency. At the same time, political instability is found to worsen the adverse effect of macroeconomic risk on the efficiency of financial institutions.

For policymakers and governments, improved institutional structures are recommended to ensure the operational efficiency of financial institutions, especially during an inflationary period. For decision-makers among financial institutions, the study recommends policies that have the potential to make their institutions less vulnerable to macroeconomic risk and exchange rate fluctuations.

The approach adopted in this study differs significantly from related studies in that the study examines and reviews interactions and relationships not readily found in the reviewed literature.

The study evaluates the effects of governance and other regulatory structures on the development of financial institutions in the subregion of sub-Saharan Africa (SSA).

Data 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.

Findings 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.

Compared 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.

Empirical work in macroeconomics almost universally relies on the hypothesis of rational expectations (RE).

This chapter departs from the literature by considering a variety of alternative expectations formation models. We study the econometric properties of a popular New Keynesian monetary DSGE model under different expectational assumptions: the benchmark case of RE, RE extended to allow for “news” about future shocks, near-RE and learning, and observed subjective expectations from surveys.

The results show that the econometric evaluation of the model is extremely sensitive to how expectations are modeled. The posterior distributions for the structural parameters significantly shift when the assumption of RE is modified. Estimates of the structural disturbances under different expectation processes are often dissimilar.

The modeling of expectations has important effects on the ability of the model to fit macroeconomic time series. The model achieves its worse fit under RE. The introduction of news improves fit. The best-fitting specifications, however, are those that assume learning. Expectations also have large effects on forecasting. Survey expectations, news, and learning all work to improve the model's one-step-ahead forecasting accuracy. RE, however, dominate over longer horizons, such as one-year ahead or beyond.

Research on high-growth firms (HGFs) or gazelles is expanding due to their significant contribution to job growth and economic development. However, the knowledge about the conditions and factors that set these firms on their rapid growth trajectory remains fragmented. Therefore, this chapter provides an abreast inventory of the surging gazelle studies by systematically reviewing the international gazelle growth literature and consolidating firm-level, industry-level, and macroeconomic-level growth factors and their interactions as elaborated in the studies. Based on the review of 62 international empirical studies, this chapter finds that the gazelle growth is complex and multidimensional in its scope and nature. The firm’s growth intention and entrepreneurial nature emerge as necessary but not sufficient conditions to guarantee rapid growth as it results from the impact of and interaction between various firm-level and external factors. The different growth-influencing factors are summarized using a theoretical gazelle growth model, which supports the rare and temporal nature of the gazelle growth.