Purpose This study aims to investigate the causal impact of exports on firm-level innovation in Vietnam, focusing on how participation in international markets shapes both product and process innovation in an emerging economy context. Design/methodology/approach The study uses firm-level data from the World Bank Enterprise Surveys spanning 2005–2023 and an instrumental variable (IV) probit model to address potential endogeneity and identify the causal effect of exports on innovation. Findings The results show that exporting firms are significantly more likely to engage in innovation, with a stronger and more robust effect on process innovation than on product innovation. This pattern suggests that firms primarily upgrade through efficiency improvements, quality enhancement and compliance with international standards, consistent with Vietnam’s position in low- to medium-technology segments of global value chains. The effects are heterogeneous across firms. Export-induced innovation is stronger among large firms and among domestic and private firms, whereas the effect is more limited for foreign-owned firms. In addition, although female-led firms exhibit higher innovation performance, they derive smaller innovation gains from export participation than male-led firms. Research limitations/implications Although the study provides robust evidence from Vietnam, the findings may be context-specific. Policy implications include promoting export facilitation, enhancing SMEs’ absorptive capacity, implementing sector-specific strategies based on ownership structures and reducing structural barriers that limit the ability of female-led firms to benefit from export-related learning. Originality/value This study contributes to the literature by providing causal firm-level evidence on the export–innovation nexus in a developing economy. The findings highlight the conditional nature of learning-by-exporting and underscore the central role of process innovation as a key channel for technological upgrading in emerging markets.
Purpose This study aims to analyze Mongolia’s export growth by decomposing it into extensive and intensive margins, examines how trade partners shape export outcomes, investigates trade-cost channels and reports robustness and interaction analyses, with a particular focus on China. Design/methodology/approach This study applies the export growth decomposition method of Amiti et al. (2010) and uses a structural gravity framework, using both the remoteness index and importer fixed effects to account for importer multilateral resistance, estimated with OLS and Poisson pseudo-maximum likelihood methods. Findings Mongolia’s export growth is shaped by the intensive and extensive margins, with the extensive margin playing a larger role for nonmineral exports and diversification outside China. Distance constrains exports, while larger partner economies and proximity to neighbors’ support both export value and product variety. Institutional quality, logistics performance and broadband connectivity reduce trade costs and facilitate diversification. China dominates the intensive margin, whereas other partners’ income and proximity are more important for introducing new products. Effective trade facilitation and institutional improvements are critical to supporting Mongolia’s export diversification and resilience. Research limitations/implications This study has several limitations that suggest directions for future research. First, the decomposition of exports does not distinguish between changes driven by prices and those driven by quantities. Second, the use of a dummy variable for diplomatic and consular presence (Dip_miss) could be improved by using a continuous measure to better address potential endogeneity. Finally, the study focuses only on goods exports due to data limitations, although incorporating services could provide a more comprehensive analysis of trade expansion. Practical implications Mongolia should deepen engagement with China while diversifying exports, strengthen the extensive margin through trade facilitation and market intelligence, enhance logistics and institutional quality domestically and target large and well-governed partner markets. Originality/value This study provides new evidence on export outcomes in a small, landlocked, resource-dependent economy, highlighting the roles of partner characteristics, neighborhood effects and trade costs.
Purpose This study aims to examine patterns of apparel imports from Asian Developing Countries (ADCs) to China, focusing on similarities and differences between ADCs’ apparel and domestically produced apparel in China at the product level. Design/methodology/approach A logistic regression analysis was performed on 8,000 apparel Stock Keeping Units (SKUs) sold in China’s retail market from January 2023 to December 2024, including their detailed product features, assortments and market pricing information. Findings ADCs’ apparel imports into China were statistically more likely to be priced below the market average, to consist of staple fashion items that need replenishment, to offer fewer color and size options and to be less diverse in fiber content. However, no statistical evidence suggested that ADCs’ products were less varied in product categories than those domestically made. In addition, ADCs’ products were statistically more likely to use recycled and organic textile materials. Research limitations/implications The findings suggest that China has become and could continue to expand its role as a growing export opportunity for many ADCs. The findings also revealed that ADCs as a whole have developed a more competitive and enhanced apparel production capacity than previous studies suggested. Originality/value The study’s findings generated important new knowledge about the emerging patterns of China’s apparel imports from ADCs and enhanced our understanding of the evolving competitiveness of ADCs and China as apparel production bases beyond traditional import markets like the United States and Europe.
Purpose This study aims to investigate the structural transformation in India's sectoral export diversification to Gulf Cooperation Council (GCC) countries, focusing on agriculture, manufacturing and industrial sectors descriptively and through a concentration index in the econometric framework. It aims to identify key determinants influencing India-GCC exports and evaluate their impact on India's export trajectory. Design/methodology/approach The analysis uses the fractional logit model to assess the impact of selected variables on India's export concentration. Export data are classified using the Harmonized System (HS) code 2-digit commodity classification and the Herfindahl-Hirschman concentration index measures sectoral concentration across the three sectors. Findings India's exports to GCC countries are highly concentrated in specific commodities across agriculture, manufacturing and industry as measured by the Herfindahl-Hirschman index. The gross domestic product (GDP) and per capita GDP of GCC countries positively influence export concentration, indicating that economic growth in partner countries strengthens India's focus on certain commodities. Increases in trade openness lead to export concentration. The exchange rate between the Indian rupee and partner currencies shows no significant effect on export concentration. Originality/value This study provides new insights into India's export dynamics with GCC countries by analyzing sectoral concentration through a fractional logit model. It highlights the role of economic and trade factors in shaping export patterns, offering valuable implications for policymakers aiming to enhance India's export diversification and economic resilience.
Purpose China's dominant role in global value chains means that disruptions to its production schedule have widespread effects. This study aims to examine the Chinese New Year (CNY) holiday as a recurring and predictable shock to African trade, reframing it not as a seasonal adjustment but as a meaningful macroeconomic event. It aims to quantify the effects of CNY-related production pauses in China on African trade performance across regions and economic groupings.Design/methodology/approach Using a high-frequency panel data set of 26 African economies from 2020 to 2025, the study uses fixed-effects models, rolling-window regressions and event-study analysis to estimate the causal impact of the CNY holiday on monthly trade flows, including total trade, imports and exports. It further explores heterogeneous effects across income levels, resource intensity, geography and political stability.Findings The results reveal significant contractions in trade during CNY months, particularly in South, Central and North Africa. Low-income, coastal, non-resource-intensive and politically stable economies experience the strongest disruptions, while resource-intensive, landlocked and fragile states show smaller or insignificant effects. Rolling-window estimates indicate that the shocks peaked in 2022 - during the post-COVID recovery - before moderating in later years.Originality/value To the best of the authors' knowledge, this paper provides one of the first empirical assessments of the CNY holiday as a macroeconomic shock to African economies. By quantifying the trade implications of a culturally rooted, calendar-based production pause, it extends the literature on seasonal trade shocks and global value-chain vulnerabilities, offering actionable insights for trade policy, forecasting and supply-chain resilience planning.
PurposeThis study aims to examine South Asia's revealed comparative advantage (RCA) in services trade from 2010 to 2023, analysing both static and dynamic patterns. It maps sectoral specialisation across eight economies and identifies structural and policy factors driving competitiveness. By distinguishing persistent advantages from emerging opportunities, the study addresses gaps in understanding the region's evolving role in global services trade.Design/methodology/approachUsing OECD-WTO BaTIS data, the RCA and Dynamic RCA indices are calculated for 12 service sectors grouped into three categories. A differenced panel two-way GMM framework evaluates determinants, such as capital formation, education, human capital, digital readiness, institutional quality and governance, controlling for country-specific heterogeneity and time dynamics.FindingsResults reveal structural diversity and uneven competitiveness: India dominates ICT and business services despite declining RCA intensity, while Sri Lanka diversifies and Afghanistan and Bangladesh lose earlier advantages. Determinants vary by service category, physical infrastructure drives traditional services, digital innovation sustains knowledge-intensive sectors and institutional quality anchors government-related services. Persistent RCA indicates cumulative capabilities, with structural rather than price factors shaping competitiveness.Originality/valueThe study integrates static and dynamic RCA analysis with econometric evidence, providing a nuanced understanding of South Asia's service trade competitiveness. It highlights sector-specific drivers, resilience of established ecosystems and shifts towards new service specialisations, offering policy-relevant insights for fostering sustainable growth beyond traditional comparative advantages.
PurposeThis paper aims to examine how Chinese firms adjust outward foreign direct investment (OFDI) location choices as geoeconomic fragmentation reshapes global value chains, focusing on how host-country geopolitical alignment, institutional quality and firm ownership jointly influence location decisions.Design/methodology/approachUsing OFDI transactions of 939 Chinese listed firms in 101 host countries between 2008 and 2022, the authors build a firm-year two-way fixed-effects model. Host economies are classified as US friend-shoring or neutral, institutional quality is proxied by rule-of-law indices and political embeddedness and high-tech status are introduced as moderators. Instrumental-variable regressions address endogeneity.FindingsIn neutral countries, private firms invest more in destinations with stronger rule of law, whereas state-owned enterprises (SOEs) invest more in institutionally weaker markets, leveraging policy finance and bilateral cooperation. In friend-shoring countries, institutional quality has no significant effect on OFDI for either ownership group. Political embeddedness amplifies private firms' preference for high-quality institutions and SOEs' tolerance of weaker ones in neutral markets, but does not offset geopolitical constraints in friend-shoring contexts. High-tech investments face tighter scrutiny, even in formally neutral economies.Originality/valueBy embedding ownership and political embeddedness in a geoeconomic-fragmentation framework, the paper extends the institution-based and resource-dependence views and refines the OLI paradigm. It shows that geopolitical alignment conditions how Chinese firms use political and institutional capabilities to manage location risk and opportunity.
Purpose This study examines the primary drivers of India’s merchandise trade with 48 African countries from 2000 to 2023. It examines how economic size, governance effectiveness, regulatory quality and corruption shape bilateral trade flows within a rapidly evolving South–South economic partnership. By analysing both formal and informal institutional factors, this paper aims to clarify their relative influence on trade and provide evidence-based insights for policies that can strengthen and sustain India–Africa economic cooperation. Design/methodology/approach Structural gravity model estimated using Poisson pseudo-maximum likelihood, enabling robust treatment of heteroskedasticity and zero-trade observations. Findings Gross domestic product (GDP) of India and its African partners is the strongest predictor of bilateral trade. Governance effectiveness and regulatory quality have significant positive effects, underscoring the importance of institutional capacity. The analysis also identifies a short-term “greasing the wheels” effect of corruption, where higher corruption levels accompany increased trade, revealing a more complex institutional landscape than conventional views suggest. Model-based projections indicate continued growth in India–Africa trade. Originality/value This paper presents one of the few systematic assessments of India–Africa trade, using a modern structural gravity framework that incorporates institutional quality. By identifying a nuanced corruption effect alongside positive governance impacts, it challenges standard assumptions and highlights the interaction of formal and informal institutions in South–South trade. The results offer clear policy guidance for enhancing governance and regulatory environments to deepen India–Africa economic engagement.
Purpose The purpose of this study is to investigate how China’s economic policy uncertainty (CEPU) affects trade dynamics between China and Sub-Saharan Africa (SSA). This is particularly critical given that China has surpassed the USA to become Africa’s leading trade partner. Design/methodology/approach Using a nonlinear autoregressive distributed lag framework, the study investigates the asymmetric effects of CEPU on trade with six selected SSA economies – South Africa, Nigeria, Kenya, Angola, Tanzania and Ghana – over the period 2000Q1 to 2022Q4. The authors also analyse the asymmetric impact on imports from China into these economies. Findings The study finds that in the long run, both rising and declining CEPU levels promote Chinese trade with Kenya, Ghana and Tanzania, though only Ghana sees significant import gains. In the short run, rising and declining CEPU similarly tend to boost trade flows from China. However, only rising CEPU exerts a significant positive effect on imports in Ghana, while the impact of declining CEPU on imports remains largely negligible. Policy implications arising from these findings were discussed. Originality/value The study, unlike previous studies, examines how CEPU is influencing trade flows between China and her six largest trading partners in SSA. It also investigates whether these trade flows respond asymmetrically to increases and decreases in CEPU.
PurposeEnvironmental variables like natural resource availability, distance and landlockedness are important locational determinants of foreign direct investment (FDI). This paper aims to determine the effect of environmental variables on African countries' attractiveness to Chinese FDI.Design/methodology/approachA two-stage approach was used to analyze and explain the attractiveness of African countries to Chinese FDI using averaged annual data from 2005 to 2022. In the first stage of the analysis, this paper employed data envelopment analysis (DEA) to estimate the technical efficiency of FDI flow to 42 African countries. In this case, the estimated technical efficiency represents the attractiveness of countries to FDI. In stage two of the analysis, they applied a Tobit model to analyze the environmental determinants of the estimated efficiency scores.FindingsBased on constant returns to scale technology, five of the 42 countries analyzed are technically efficient, and the average efficiency score is 85%. The Tobit model shows that distance has a negative and significant effect, whereas landlockedness has a positive and significant effect on the attractiveness of Chinese FDI to Africa. The effect of natural resource availability is not significant.Research limitations/implicationsTwo major weaknesses can be identified. First, focusing on Chinese FDI does not give a general picture of the efficiency of FDI flow to Africa. Extant empirical literature has shown that Chinese FDI is peculiar owing to, inter alia, the significant component of state-owned enterprises among Chinese MNCs, which makes it sensitive not only to the economic circumstances of host countries but also to China's political objectives. Empirical analysis focusing on FDI from the global north is, therefore, required for comparative purposes.Practical implicationsThe findings suggest that policies seeking to promote Chinese FDI should focus on ameliorating the negative effects of geographical distance, while acknowledging the confounding effect of sovereign debt.Social implicationsThe findings of this study have implications for the formulation and targeting of investment promotion policies. Through the DEA-based performance ranking, the less efficient or less attractive countries have an opportunity to learn from the more efficient peers. The other implication for policy is that FDI promotion strategies targeting Chinese FDI should focus more on ameliorating the adverse effects of distance as the other environmental variables have no significant influence.Originality/valueThe use of efficiency analysis to estimate the attractiveness of countries to FDI is still new in the FDI literature. The contribution of this paper is twofold: the use of data envelopment analysis to estimate attractiveness of host countries to FDI, and the use of environmental variables to explain the observed attractiveness and efficiency.
PurposeThis study aims to investigate the role of the Hainan Free Trade Port, a uniquely experimental institutional design, in shaping regional entrepreneurial dynamics in China.Design/methodology/approachUsing province-level panel data from 2003 to 2023, the authors used a synthetic control method to evaluate the policy's effect on new firm registrations. To ensure robustness, they conduct spatial and temporal placebo tests, synthetic difference-in-differences estimations and incorporate staggered adoption designs.FindingsThe findings show that the Hainan FTP significantly increased new firm registrations. Industry-level heterogeneity analysis indicates that the effects are more pronounced in knowledge-intensive and modern service sectors, pointing to improvements not only in the quantity but also in the quality of entrepreneurial activity. Additionally, the policy enhanced the local fiscal capacity and contributed to the growth of new productive forces.Research limitations/implicationsFirst, while it identifies a significant positive impact of the Hainan FTP on entrepreneurship, it does not fully disentangle the underlying mechanisms, such as improvements in institutional quality, talent inflow or financial accessibility. Second, the analysis relies on province-level panel data, which restricts the exploration of firm-level or entrepreneur-specific heterogeneity.Practical implicationsThis study offers practical implications for institutional reform and entrepreneurship policy. It demonstrates how the Hainan FTP boosts both the scale and quality of entrepreneurship, strengthens local fiscal capacity and fosters new productive forces. The findings provide actionable insights for designing free trade port policies, optimizing industrial support strategies and building dynamic evaluation frameworks to guide adaptive governance.Social implicationsThe Hainan FTP showcases the social impact of building a uniquely positioned offshore free trade port, fostering institutional innovation, international connectivity and entrepreneurship-driven development. It serves as a model for balancing openness with local resilience, enhancing China's global integration while supporting inclusive regional transformation.Originality/valueTo the best of the authors' knowledge, this study is the first to use the synthetic control method to empirically evaluate the entrepreneurial impact of China's only offshore Free Trade Port. It provides novel evidence on how high-level institutional openness stimulates entrepreneurship, enriching the literature on place-based economic reforms. The study highlights the unique institutional design of the Hainan FTP, which, unlike traditional free trade.
PurposeThe purpose of this study is to investigate the impact of digital economy (DE) on China's manufacturing upgrading (MU), as well as examine the role of human capital (HC) in this process.Design/methodology/approachUsing a balanced panel data set comprising annual data from 30 provinces in China for the period between 2011 and 2022, this study uses the fixed effects, mediating effects and threshold effect models to assess the impact of DE development on MU in China.FindingsThe research findings indicate that: DE has a significant positive impact on the overall upgrading of the MU in China. DE promotes MU through HC. The relationship between the DE and MU exhibits a non-linear characteristic. Moreover, the influence of the DE on MU presents a trend of nonlinear enhancement. When the development of the DE surpasses a certain threshold, its positive impact on MU becomes significantly more pronounced. In regional heterogeneity analysis, DE significantly promotes MU in medium-low gross domestic product (GDP) regions, but its impact is insignificant in high GDP regions.Originality/valueThis study moves beyond the conventional assumption of a simple linear relationship between the DE and MU, proposing a more complex and realistic model. This study addresses a research gap by investigating the critical yet understudied role of HC as a factor in how the DE drives MU. This study introduces a more economically meaningful method for regional analysis within China by categorising provinces into high-GDP and medium-to-low-GDP groups.
PurposeThis study aims to investigate whether short-term financial spillovers exist within a green supply chain by analyzing the dynamic stock price linkage between Tesla Inc. and its Taiwanese upstream supplier, Innolux Corporation. The research examines how Tesla's daily price movements, particularly sustainability-related negative shocks, affect the supplier's short-term stock performance.Design/methodology/approachThis study uses daily stock price data for Tesla and Innolux from 2014 to 2024. A long short-term memory (LSTM) deep learning model is used to forecast short-term price patterns, while a decision tree model identifies nonlinear threshold responses that characterize spillover transmission within a green supply chain. A regression model is further applied to statistically validate the cross-firm linkage and quantify the magnitude of Tesla's influence on its supplier.FindingsThe results demonstrate that Tesla's prior-day price movements have a significant predictive effect on Innolux's next-day closing price. The LSTM model shows strong forecasting accuracy (RMSE = 0.4760; R-2 = 0.9121), while the decision tree identifies a critical threshold indicating that when Tesla's daily decline exceeds 1.4%, Innolux is highly likely to experience a price drop. The regression analysis further confirms a strong linear relationship between the two firms' stock price dynamics (R-2 = 0.992). Together, these findings provide robust evidence of short-term financial spillovers from a leading EV manufacturer to its upstream supplier within a green supply chain ecosystem.Research limitations/implicationsThis study analyzes only a single upstream supplier in Tesla's green supply chain, which may constrain the generalizability of its findings. In addition, external influences - such as macroeconomic fluctuations, policy shocks and geopolitical events - were not incorporated into the models. Future research may broaden the scope to include multiple firms across different tiers of the supply chain, integrate sustainability-related news or sentiment data, and apply nonlinear or regime-switching models to capture more complex spillover dynamics.Practical implicationsThis study offers investors and portfolio managers actionable insights into short-term financial spillovers within green supply chains. The identified predictive linkage between Tesla and its upstream supplier, Innolux, provides a basis for timely risk assessment and threshold-based trading strategies, particularly during periods of sustainability-related negative shocks. The findings also support policymakers by underscoring the importance of improving data transparency, refining ESG disclosure mechanisms and promoting digital finance tools that enhance the resilience of sustainable industrial ecosystems.Social implicationsThis study highlights the societal importance of transparency and resilience in sustainable supply chains. By revealing the financial interdependence between a leading global EV manufacturer and a Taiwanese upstream supplier, the findings emphasize the role of cross-border collaboration in advancing sustainability objectives. Enhanced data openness and the use of AI-based analytical tools can empower investors, firms, and policymakers to make informed decisions that support environmental responsibility and positive social impact.Originality/valueTo the best of the authors' knowledge, this study is among the first to examine short-term financial spillovers within a green supply chain using deep learning techniques. By focusing on Tesla and its Taiwanese upstream supplier, Innolux, it presents a novel case-based analytical framework that integrates LSTM forecasting, decision tree threshold identification and regression validation. The research contributes to the green finance and sustainable supply chain literature by uncovering previously unobserved, short-horizon spillover mechanisms between leading EV firms and their suppliers within a sustainability-oriented industrial ecosystem.
PurposeThe purpose of this paper is to analyze food fertilizer products' trade networks among Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) member nations during 2005-2022.Design/methodology/approachTo explore the nature of revealed comparative advantage, intra-sectorial trade specialization and intra-industry trade, this paper used Balassa, Lafay and Grubel-Lloyd indexes. On the other hand, economic networks were used to investigate fertilizer trade centrality in global trade networks.FindingsThis paper concluded that Thailand and India have the most diversified fertilizer trade markets. In contrast, Nepal and Bhutan exhibited high import centrality toward a few source regions. Hence, significant scope exists to diversify fertilizer export and import markets within BIMSTEC member nations to avoid region-specific dependence on international trade.Originality/valueThis paper lies apart in its precise emphasis on linking national resource security issues with import-export policy formulation for food fertilizers, where earlier studies have not been examined. Dealing with this intersection allows the existing paper to offer a reenergized perspective on harmonizing resource sustainability with economic objectives. Hence, this fills a primary void in the existing literature by suggesting hands-on strategies and expanding current knowledge.
PurposeThe construction industry faces a significant challenge because of the lack of digital tools and collaborative platforms for managing recycled materials and fostering a circular economy (CE) throughout a building's life. This study aims to mitigate the environmental impact of the construction industry by integrating building information modelling (BIM) with CE principles.Design/methodology/approachIn this research, Python and Microsoft Visual Studio were used to introduce a bidirectional data-sharing process and integrate material passports (MPs) within the Autodesk Revit framework. A case study was conducted to check the efficacy of the developed prototype in a real-world project of NEOM City. A total of 12 industry experts have validated the developed prototype named BIM-circular economy system (BIM-CES) through a demonstration, followed by a semi-structured interview, and further analysed using importance-performance analysis (IPA).FindingsThe prototype demonstrated a framework for using wood material-related MP within a BIM model. IPA revealed that BIM-CES effectively addresses key issues of lack of collaboration, technological solutions, technical skills and circular design, ranking high in importance and performance.Originality/valueUnlike previous studies that primarily focus on celebrity attributes in the food sector, this research integrates socio-psychological factors, providing a broader perspective on how these attributes influence consumer behaviour.
PurposeProvided that Egypt is the world's largest wheat importer, the conflict between its primary suppliers presents significant challenges to its trade stability and food security. This paper aims to investigate the impacts of the Russia-Ukraine (RU) war on Egypt's trade dynamics, with a particular focus on wheat imports over the period 1995-2023.Design/methodology/approachThe study uses the Fully Modified Ordinary Least Squares (FMOLS) model to estimate the relationship between macroeconomic variables and Egypt's trade performance, as well as agricultural determinants and wheat import dynamics.FindingsThe empirical results show that Egypt's GDP growth rate and its exchange rate have negative and statistically significant impacts on both the growth rate of imports and total trade with Russia and Ukraine. Conversely, Egypt's inflation and the GDP of Russia and Ukraine show a positive and significant effect on Egypt's imports and total trade. This indicates Egypt's vulnerability to both domestic inflationary pressures and foreign economic activity. Importantly, the inclusion of a war dummy variable capturing the RU war shows a negative and significant impact on Egypt's total trade and wheat imports, underscoring the geopolitical shock's disruptive effects.Research limitations/implicationsThe findings offer critical insights for policymakers to enhance trade resilience, diversify import sources and strengthen domestic agricultural capacity in the wake of global trade disruptions.Practical implicationsThe findings imply that Egypt should implement comprehensive policy reforms in wheat pricing mechanisms, introduce targeted incentives to enhance private sector efficiency in agricultural production, and foster the adoption of innovative and sustainable farming practices.Social implicationsSocial implications extend to reducing food insecurity in Egypt, containing food inflation through improved supply stability, and advancing inclusive growth by ensuring equitable access to affordable staple commodities.Originality/valueThis study offers a distinctive contribution by examining Egypt's short-term adaptive responses to the Russia-Ukraine war-a period characterized by exceptional disruption in global wheat markets. It provides empirical insights into how Egypt, an import-dependent economy navigated concurrent external shocks, including trade blockages, logistical constraints, and unprecedented price surges, thereby revealing the mechanisms underpinning trade resilience under crisis conditions.
Purpose This study aims to examine the relationship between export diversification and economic growth by diving into Harmonised System (HS) six-digit level of disaggregation which provides greater details regarding the composition of India’s export product mix. Design/methodology/approach Using data from 1991 to 2023, the study uses Theil index to measure the magnitude of diversification in export basket and employs an Auto Regressive Distributed Lag (ARDL) model to unveil the long run relationship between export diversification and economic growth in India. Findings The results provide evidence that export diversification enhances growth both in the short and long run and also acts as a shield against concentration and induced volatility. Further analysis indicates that both human capital and labour force growths are conducive to economic expansion while inflation and FDI has detrimental effects. Research limitations/implications The study period starts in 1991 because data on FDI prior to that period is unavailable as the liberalisation of Indian economy formally initiated in 1990–1991. However, the study also brings out the relevance of export diversification as a source of sustainable economic development and the growth promoting as well as risk mitigating character in the context of India. It also calls for policies to enhance human capital and labour force and the means of combating inflation and to best use FDI for economic growth. Originality/value The study contributes to the existing knowledge through various ways: First, unlike previous studies which uses Herfindahl–Hirschman Index (HHI) index which is exposed to various limitations, the present study uses Theil index and considered HS six digit level of product classification to account for greater details while measuring diversification. Second, the long run relationship between economic growth and export diversification is modelled using the Auto Regressive Distributed Lag (ARDL) bounds testing approach and effect of export diversification on economic growth is also moderated controlling various economic growth influencing variables such as, gross capital formation, labour force participation, human capital, FDI and inflationary effect.
PurposeThe agricultural sector in South Africa has gained traction in recent years, with increasing emphasis on expanding international presence, particularly in the export market, including BRICS countries, in which South Africa and China are members of intergovernmental organizations that want to increase their influence in the global economy. The rising demand for forage has brought renewed attention to the export of Lucerne hay to China, prompting an empirical study on South Africa's competitive advantage and market demand analysis for Lucerne hay in the Chinese market. This study aims to explore potential opportunities in the global market that South Africa could capitalize on.Design/methodology/approachTo evaluate the competitiveness of Lucerne hay exports from South Africa, the study measured the revealed comparative advantage and competitive advantage employing the Balassa and Vollrath indices. To analyze the demand for South African Lucerne hay imports in China from 2019 to 2023, the study applied an Almost Ideal Demand System (AIDS) to examine the demand parameters and elasticities.FindingsSouth Africa exhibited a comparative advantage and a comparative disadvantage in the export of Lucerne hay. The AIDS model revealed that South Africa's market share in China is not influenced by its own or competitors' Lucerne hay export prices. Furthermore, China considers the USA and Australian Lucerne hay to be complementary, with demand increasing despite the rise in price and with own and cross-price elasticities for South African Lucerne hay remaining unresponsive. However, additional Chinese expenditure on Lucerne hay imports would benefit South African Lucerne hay suppliers. Thus, given the existing market conditions, South African Lucerne hay exports cannot be enhanced through price changes but through an increase in export supply as Chinese imports are expected to shift from dependence on the USA.Research limitations/implicationsThe findings provide valuable insights for South African policymakers to enhance decision-making regarding promoting Lucerne hay exports to the Chinese market. While adding to the scientific literature and expanding empirical knowledge, it also serves as a reference point for analyzing trade competitiveness and demand for new and nontraditional agricultural markets within the BRICS. The study provides a policy entry point for South African policymakers to support export-oriented initiatives that align with South Africa's National Development Plan (NDP) goals while capitalizing on the BRICS relationship. From China's perspective, the research sheds light on the interconnections between its Lucerne hay market and other emerging export markets, with a particular focus on South Africa. This approach yields significant policy implications and contributes to the existing body of knowledge in this field.Originality/valueNumerous studies have explored China's demand for various commodities and South Africa's export and marketing strategies, but this research offers a unique contribution. The trade of Lucerne hay between South Africa and China has seldom been subjected to empirical analysis. Moreover, this study introduces a novel estimate of import demand elasticities for Lucerne hay.
PurposeThis study aims to explore fresh insights into risk spillovers and linkages between the Shanghai Composite Index and Chinese sectoral equity markets.Design/methodology/approachUsing the wavelet-time-varying parameters-vector autoregressive (TVP-VAR) approach, this study explores fresh insightful risk spillovers and linkages between the Shanghai Composite Index and the Chinese sectoral equity markets. The sample period covered the major US global crises, the Chinese market volatility and the COVID-19 stress subsamples.FindingsThis study identified health-care and building materials sector as the biggest dynamic spillover receivers in various crises, whereas the Shanghai Composite Index is the major risk transmitter. Moreover, the health-care and construction industries have the largest spillover receivers, and the Shanghai Composite Index is the main risk transmitter of short- and long-term volatility. The authors interface the Shanghai Composite Index as the primary and significant risk spillover transmitter to all sectors, which reduces their returns. The Shanghai Composite Index and Chinese sectors, excluding health care and pharm-bio, have declining demand supply and adjusting the risk-return patterns in the markets for investors during the outbreak of COVID-19. Furthermore, the health-care and construction material sectors had a greater negative effect and received the most significant risks from the Shanghai and Chinese sectors during the COVID-19 pandemic.Research limitations/implicationsThis study has significant implications for investors, speculators, market analysts and policymakers.Originality/valueThis study uses the wavelet-TVP-VAR approach to analyze risk spillovers between the Shanghai Composite Index and Chinese sectoral markets, with a focus on key crises, such as the US global crises, the Chinese market volatility and the COVID-19 pandemic.
