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Trade relations between China and the USA have been marked by conflict, especially since China’s membership in the World Trade Organization (WTO). These conflicts have been analyzed from a variety of perspectives, including the loss of jobs in the USA due to Chinese imports, competition in high technology sectors and the balance of trade. Conceptual frameworks have employed models of domestic differences as well as models of international power distribution. Among domestic differences examined are the existence of state-owned enterprises in China compared to the domination of the USA economy by private firms, the large role of the Communist Party in China and the influence of labor and environmental and labor groups in the USA. Power distribution theories focus on the systemic effects of the distribution of power on trade openness and on the pattern of intra-bloc versus between-bloc trade. This paper aims to examine the role of macroeconomic policy factors in China and the USA, in particular, the role of national patterns of savings, investment and consumption (both private and government). The paper concludes that insofar as the balance of trade is an important component of the trade conflict, domestic macroeconomic factors continue to be important. The resolution of the conflict will have to take into account the respective macroeconomic policies of China and the USA.

The design is an analytic case study of US–China trade relations with a particular focus on the balance of trade. The conceptual framework employed involves an analysis of macroeconomic policy categories, especially the overall pattern of savings (household, firm and government), investment and consumption. Process tracing over time since China's membership in the WTO is carried out with an eye toward the relationship between the balance of trade and macroeconomic policy.

The main findings are that there is a strong relation between the respective macroeconomic policies of the USA and China and their trade relations. The domestic political economy of the USA encourages consumption and a low rate of savings. The opposite is true of China where household income is low by design and national savings are high. China depends on the USA to consume what is not consumed domestically. The USA depends on Chinese imports for additional consumption encouraged by its low rate of savings. The two economies are locked in a mutual dependence.

Key research implications are that there should be more focus on domestic macroeconomic policies since these are the root causes of the trade imbalance. This is not to say that trade frictions centering on jobs, subsidies and competition in high technology are unimportant. However, without the resolution of differences in the management of macroeconomic policies, trade conflicts between the USA and China will continue.

Practical implications are huge, in some ways much more important than the academic implications. Macroeconomic policy differences in savings, investment, government spending, taxation and infrastructure are important. Furthermore, there are available tools in both China and the USA to manage the macroeconomy, particularly, monetary and fiscal policy.

One implication of this paper is that satisfaction or dissatisfaction of workers is dependent on income distribution which in turn affects trade. Treatment of people in different socioeconomic categories, such as the elderly, the young, and those at working age are a function of macroeconomic policies.

Many people have written about macroeconomics. It is a conventional subfield of economics. The originality of this paper lies in its advocacy of a shift of focus and attention and in the argument that traditional macroeconomics is related to trade. Despite its importance, macroeconomics has not been the center of attention for most political scientists, though economists have made it more central.

Many studies have analysed the impact of various variables on the ability of companies to raise capital. While most of these studies are sector-agnostic, literature on the effects of macroeconomic variables on sectors that established over the last 20 years like property technology and financial technology, is scarce. This study aims to identify macroeconomic factors that influence the ability of both sectors and is extended by real estate variables.

The impact of macroeconomic and real estate related factors is analysed using multiple linear regression and quantile regression. The sample covers 338 observations for PropTech and 595 for FinTech across 18 European countries and 5 deal types between 2000–2001 with each observation representing the capital invested per year for each deal type and country.

Besides confirming a significant impact of macroeconomic variables on the amount of capital invested, this study finds that additionally the real estate transaction volume positively impacts PropTech while the real estate yield-bond-gap negatively impacts FinTech.

For PropTech and FinTech companies and their investors it is critical to understand the dynamic with mac-ro variables and also the real estate industry. The direct connection identified in this paper is critical for a holistic understanding of the effects of measurable real estate variables on capital investments into both sectors.

The analysis fills the gap in the literature between variables affecting investment into firms and effects of the real estate industry on the investment activity into PropTech and FinTech.

Digitalization is one of the major factors that fosters economic growth across the world. However, the level of digitalization varies significantly between developed and developing countries, with the latter often lagging behind. To bridge this gap, it is crucial to pinpoint the drivers of digitalization, specifically from the macroeconomic and country-level governance dimensions. Therefore, this study aims to investigate the determinants of digitalization, particularly for countries in Asia and the Pacific region.

Our study utilizes unbalanced panel data from 46 Asian and Pacific countries for the period of 2001–2021. Initially, we analyzed the data using conventional econometric methods, such as pooled ordinary least squares (POLS), random-effects model (REM) and fixed-effects model (FEM). Moreover, we employed endogeneity-corrected techniques and alternative proxies to enhance the robustness and reliability of our findings.

Our findings reveal that economic development progress, government expenditure relative to country size and political stability are key drivers of digitalization. In contrast, corruption at the country level emerges as a significant impediment. Notably, our results remain robust to endogeneity-corrected techniques and alternative proxies of digitalization. Overall, these insights can inform policymakers, helping them to understand the macroeconomic and governance factors shaping digitalization and guide their decision-making toward effective policy interventions.

This study’s empirical findings add significant value to the existing literature by quantifying the impact of macroeconomic and governance factors on digitalization in selected countries. This offers valuable insights for policymakers, particularly in nations with lower levels of digitalization.

This paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper evaluates the dynamic relationship between digital financial innovation measures and financial system development using time series data from COMESA countries for the period 1997–2019.

A dynamic autoregressive distributed lag model (ARDL) was adopted and the mean group (MG), pooled mean group (PMG) and dynamic fixed effect (DFE) of the model were estimated to evaluate the short- and long-run impact. In addition, the dynamic generalized method of moments (DGMM) was adopted for a robustness check. The Hausman test results show PMG to be the most consistent and efficient estimator, while the coefficient of lagged dependent variable of different GMM is less than the fixed effect coefficient, and, as such, suggests system GMM is the most suitable estimator. Data for the study were sourced from World Bank Development Indicator (WDI, 2020), World Governance Indicator (WGI, 2020) and World Bank Global Financial Development Database (GFD, 2020).

The result shows that digital financial innovation significantly impacts financial system development in the long run. As such, the evidence revealed that automated teller machines (ATMs), point of sale (POS), mobile payments (MP) and mobile banking are significant and contribute positively to financial system development in the long run, while mobile money (MM) and Internet banking (INB) are insignificant but exhibit positive and inverse relationship with financial development respectively. Further investigation revealed that institutional quality and a stable macroeconomic environment including their interactive term are significantly imperative in predicting financial system development in the COMESA region.

Researchers recommend a cohesive and conscious policy that would checkmate the divergence in the short run and suggest a common regional innovative financial strategy that could be pursued to incentivize technology transfer needed to promote financial system development in the long run. More so, plausible product and process innovations may be adapted to complement innovative institutions in the different components of the COMESA financial system.

Digital financial innovation services if well managed increase the inherent benefits in financial system development.

To the best of the authors’ knowledge, this paper presents new background information on digital financial innovation that may stimulate the development of the financial system, particularly in the COMESA region. It also exposes the relevance of digital financial innovation, institutional quality and stable macroeconomic environment as well as their interactive effect on COMESA financial system development.

This study seeks to examine the relationship between macroeconomic shock indicators, namely geopolitical risk (GPR), global economic policy uncertainty (GEPU) and financial stress (FS), and returns as well as volatilities on seven carefully selected stock markets in Africa. Specifically, the study intends to unravel the co-movement and interdependence between the respective macroeconomic shock indicators and each of the stock markets under consideration across time and frequency.

This study employed wavelet coherence approach to examine the strength and stability of the relationships across different time scales and frequency components, thereby providing valuable insights into specific periods and frequency ranges where the relationships are particularly pronounced.

The study found that GEPU, Financial Stress (FS) and GPR failed to induce significant influence on African stock market returns in the short term (0–4 months band), but tend to intensify in the long-term band (after 6th month). On the contrary, stock market volatilities exhibited strong coherence and interdependence with GEPU, FSI and GPR in the short-term band.

This study happens to be the first of its kind to comprehensively consider how the aforementioned macro-economic shock indicators impact stock markets returns and volatilities over time and frequency. Further, none of the earlier studies has attempted to examine the relationship between macro-economic shocks, stock returns and volatilities in different crisis periods. This study is the first of its kind in to employ data spanning from May 2007 to April 2023, thereby covering notable crisis periods such as global financial crisis (GFC) and the COVID-19 pandemic episodes.

This study aims to examine the factors that influence the relationship between sustainability and financial performance (FP) of the European listed companies.

This study analyzed data from 795 companies in 21 European countries by applying linear mixed-effects multilevel regressions, a two steps system generalized method of moments and quantile regression models to uncover the links between sustainability and FP.

The past four decades have witnessed abundant research to determine the relationship between corporate sustainability and FP. Thus, conducting further research in 2023 could be seen as “reinventing the wheel.” Yet, earlier research considered firms as isolated entities with sustainability and FP being dependent only on that firm’s actions. By contrast, with the help of network governance theory, this study shows that a firm’s sustainability and FP depend on an interplay among interorganizational actors, such as institutional qualities, macroeconomic factors and an embrace of sustainability. Here, large firms play an essential role. Three significant findings are drawn. First, sustainability performance has a significant impact on FP in the European context. Second, the institutional quality (IQ) of the rule of law and control of corruption plays a crucial role in enhancing sustainability and FP, and finally the interaction of IQ and economic growth helps to increase companies’ market value (Tobin’s Q). The consistent and empirically robust findings offer key lessons to policymakers and practitioners on the interplay among multiple actors in corporate sustainability and FP.

A synergetic multifaced relationship between governmental institutions and corporations is inevitable for ensuring sustainable development. The degree of intimacy in the relationship, of course, will be determined by the macroeconomic environment.

In this research, this study theoretically and empirically identified that corporate sustainability and FP are not solely dependent on corporate operation. Rather, it is transformed, modified and shaped through an interaction of multiple actors’ trajectories in the macro business environment.

This study investigates (1) whether democratization drives sovereign credit ratings (SCR) changes (the “democratic advantage”) or whether SCR changes affect democratization, (2) whether the degree of democratization in sub-Saharan African (SSA) countries affects the associations and (3) whether the associations are significantly affected by resource dependence.

This study investigates the effects of SCR changes on democracy in 22 SSA countries over the period of 2000–2020 VEC Granger causality/block exogeneity Wald tests, and impulse responses and variance decomposition analyses with Cholesky ordering and Monte Carlo standard errors in a panel VECM framework.

The full sample impulse responses find that a SCR shock has a long-run detrimental effect on the democracy and political rights but only a short-run positive impact on civil liberties. Among the sub-samples, it is found that the extent of natural resource dependence does not affect the magnitude of SCR shocks on democratization mentioned above but it is found that a SCR shock affects long-run democracy in SSA countries that are relatively more democratic but is more likely to drive democratic deepening in less democratic SSA countries. The full sample variance decompositions further finds that the variance of SCR to a political rights shock outweighs the effects of all the macroeconomic factors, whereas in more diversified SSA countries, the variances of SCR are much greater for democracy and political rights shocks, which suggests that democratization and political rights in diversified SSA economies are severely affected by SCR changes. In the case of the high and low democracy sub-samples, it is found that the variance of SCR in the relatively higher democracy sub-sample is greater than in the low democracy sub-sample.

These results have three implications for democratization in SSA. First, the effect of a SCR change is not a democratically agnostic and impacts political rights to a greater extent than civil liberties. Second, SCR changes have the potential to spark a negative cycle in SSA countries whereby a downgrade leads to a deterioration in socio-political stability coupled with increased financial economic constraints that in turn drive further downgrades and macroeconomic hardship. Finally, SCR changes are potentially detrimental for democracy in more democratic SSA countries but democratically supportive in less democratic SSA countries. Thus, SSA countries that are relatively politically sophisticated are more exposed to the effects of SCR changes, whereas less politically sophisticated SSA countries can proactively shape their SCRs by undertaking political reforms.

This study is the first to examine the associations between SCR and democracy in SSA. This is critical literature for the Africa’s scholarly work given that the debate on unfair rating actions and claims of subjective rating methods is ongoing.

The purpose of this study is to examine herd behaviour under different market conditions, examine the potential impact of the firm size and stock characteristics on this relationship, and explore how herding affects market prices in the German market.

The authors apply a method that does not rely on theoretical models, thus eliminating the biases inherent in their application. This technique is based on the assumption that macro herding manifests itself in the synchronicity (comovement) of stock returns.

The study’s findings show that herding is more pronounced in down markets and is more pronounced when market returns reach extreme levels. Additionally, the authors have found that there is stronger herding among large companies compared to small companies, and that stock characteristics considered have no effect on the degree of macro herding. Results also suggest that the contemporaneous market-wide information drives macro herding and that macro herding facilitates the incorporation of market-wide information into prices.

The study’s results strongly support the idea of directional asymmetry, which holds that stocks react quickly to negative macroeconomic news while small stocks react slowly to positive macroeconomic news. Additionally, the study’s results suggest that the contemporaneous market-wide information drives macro herding and that macro herding facilitates the rapid incorporation of market-wide information into prices.

To the best of the researchers’ knowledge, this is the first study that examines macro herding for a major financial market using a herding measure based on the co-movement of returns that does not rely on theoretical models.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.