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The purpose of this study is to examine the dynamic relationship between intellectual capital (IC) and its components on financial performance of banks within the selected eight countries of Association of Southeast Asian Nations (ASEAN).

The study utilizes the balanced panel data of 37 publicly listed banks from eight leading ASEAN economies for the period of 2017–2021. In this sense, the authors applied the Ante Pulic's typology, i.e. value-added intellectual coefficient (VAIC™) to evaluate the efficiency of intangible and tangible assets. While, investigating the dynamic nature of relationship, the authors employed the generalized system method of moments because of its power to account for the problem of endogeneity and heteroscedasticity.

The results of the study demonstrate that banks in ASEAN countries shed a varied degree of a spotlight on VAIC™ and its components to create value. The findings revealed that structural capital efficiency is significantly associated with earning per share (EPS), return on assets (ROA) and return on equity (ROE), compared to human capital efficiency (HCE) and capital employed efficiency of ASEAN banks. These results endorse the importance of resource- and knowledge-based views of organizations to leverage the financial performance of banks. However, contrary to theoretical expectations, this study found no positive relationship between HCE with ROA and ROE. Whereas, the relationship of VAIC™ is positive and significant with EPS and ROE but it remains statistically very marginal.

There are some inherent limitations in this study that could be opportunities for future research. The current study uses the VAIC™ typology, but future researchers can use the modified value-added intellectual coefficient (MVAIC) or triangulation approach to enhance the validity and reliability of the study. Additionally, future research can investigate the similarities and differences among countries in terms of their cultural backgrounds and regulatory frameworks regarding the disclosure of intangibles. Furthermore, future research can increase the length and sample size of the study to enhance its generalizability.

The robust empirical findings extend the academic debate on IC by unveiling the dynamic nature of relationship between IC and financial performance in context of ASEAN banking sector. The findings provide plausible recommendations for policy makers (managers, regulators and stakeholders) to understand how to increase the IC efficiently, especially human capital as a source to evaluate the firms’ ability in determining value-added and financial performance. Further, findings of this study also suggest that how can policy makers get the benefit by investing more on structural capital as a valuable strategic source to guarantee the optimal performance returns.

Prior studies on IC have been country- and firm-specific, utilizing cross-sectional research designs. However, this research contributes to the limited literature by investigating the dynamic nature of the relationship between IC and financial performance of banks in the context of ASEAN countries using micro-panel data.

The authors empirically aim to study the implications of uncertainty generated by oil price volatility on some key macroeconomic variables, including production, exchange rates and interest rates, of both oil-exporting and oil-importing countries. Using a block exogeneity structural Vector Auto Regression (VAR) model that mutes the effects of domestic variables on global factors and that is suitable for small open economies because of significant differences in the responses of domestic production in oil-importing countries will most likely decrease through reducing planning horizons, postponing investment projects and relocating resources more inefficiently.

The authors integrated into the structural vector autoregressive (SVAR) model the block exogeneity feature since all the countries in this study are small open economies that cannot influence the global economic variables. The block exogeneity feature imposes the restriction that the domestic variables have neither a contemporaneous nor a lagged impact on the global variables. This model has eight variables: oil price volatility, world demand and federal funds rate as the global variables; and domestic production, monetary aggregate, inflation rate, exchange rate and interest rate as domestic variables. The authors assemble the data for 12 developing countries for which the necessary data for the analysis are available: six oil exporting countries (Russia, Saudi Arabia, Iran, Kazakhstan, Mexico and Colombia) and six oil importing countries (Turkey, India, Philippines, Poland, South Africa and Indonesia).

The results point out significant differences in the responses of macroeconomic variables to oil price volatility shocks between oil-exporting and oil-importing countries. Furthermore, the local currencies of these countries depreciate due to concerns about possible current account worsening. In response to the shock, domestic interest rates are reduced so as to alleviate the negative exposure of the shock on domestic economic activity. While domestic production in some oil-exporting countries (i.e. Russia, Saudi Arabia and Iran) increases during oil price uncertainty; in some other countries (i.e. Mexico, Kazakhstan and Colombia), domestic production decreases.

Several components of the study contribute to its novelty. One of them is the period under consideration. The time frame that encompasses the most significant geopolitical and financial events, such as the Middle East Spring and the global financial crisis of 2007–2008. The research was conducted using the block-exogeneity SVAR model, which includes 12 oil exporting and importing developing countries. With this model, the global dynamics, particularly the energy market, that these nations may influence and are influenced by, i.e. global and nonglobal factors can be constrained. This makes it easy to determine the various effects prices have on macroeconomic variables.

1. Oil prices and volatility still matter to the global economy

2. Monetary and fiscal policy interventions in response to oil price volatility create uncertainty and impede investment activity

3. The response of macroeconomic variables to volatility shocks in oil prices varies across oil importers and exporters

4. Interest rates help stabilize production in oil-importing economies that have well-functioning financial markets

Oil prices and volatility still matter to the global economy

Monetary and fiscal policy interventions in response to oil price volatility create uncertainty and impede investment activity

The response of macroeconomic variables to volatility shocks in oil prices varies across oil importers and exporters

Interest rates help stabilize production in oil-importing economies that have well-functioning financial markets

The aims of the current study were twofold: first, to rank the world’s emerging economies based on a novel National Intellectual Capital Index (NICI) and its components; and second, to examine the impact of NICI and its components on economic growth, measured in terms of real GDP per capita.

We employed principal component analysis (PCA) to construct the novel NICI based on five key socio-economic indicators including (1) national human capital, (2) national structural capital, (3) national relational capital, (4) national informational capital and (5) national innovational capital. These indicators are publicly available for many countries. The index was generated by considering the most appropriate socio-economic indicators as precise measures of NIC from the Penn world table (version 10.0), the World Bank’s database of world governance and development indicators and the KOF globalization across the selected emerging economies.

The empirical findings revealed that national human capital is a significant driver of NIC, corresponding to higher economic growth. This is followed by national informational capital, national relational capital, national innovation capital and national structural capital. Furthermore, results indicate that the contribution of national structural capital is marginal compared to other critical strands of NIC.

NIC is generally considered the most valuable strategic resource for driving knowledge economies, especially in the Industry 5.0 revolution. Ranking emerging economies based on the NICI sheds light on the accumulated stock of NIC and how it contributes to and improves the economic growth of these economies. The stock of NIC is considered a critical success factor for measuring both current and future economic prosperity. Therefore, using the socio-economic indicators of KOFGI as accurate measures of NICI will assist policymakers in formulating and implementing relevant policies to enhance the accumulation of knowledge-based capital, which are critical components of NIC.

To the best of the authors' knowledge, this is the first study of its kind, both theoretically and empirically, to measure the National Intellectual Capital Index (NICI) using the most nascent socio-economic indicators of NIC. Moving forward, this study evaluates the impact of NICI and its components on economic growth, which is a relatively sparse area of research in the context of emerging knowledge economies.