The impact of macroeconomic shocks on Vietnams textile and garment exports based on a structural VAR analysis

As a labour-intensive export sector that provides large-scale employment for low- and semi-skilled workers, Vietnam’s textile and garment industry plays a central role in the country’s sustainable development. This paper develops a structural vector autoregression (SVAR) model to examine the impact of macroeconomic shocks on Vietnam’s textile and garment exports using monthly data from 2015M01 to 2024M12. The analysis incorporates five key variables: the real effective exchange rate (REER), the world oil price (OIL), the consumer price index (CPI), the policy interest rate (INR), and total textile and garment exports (TGE ). The methodological framework includes unit root testing, seasonal adjustment, lag selection based on information criteria, stability testing, and impulse response and variance decomposition analyses. Robustness checks are performed using alternative recursive identification orderings and different lag structures. The results reveal that policy interest rate shocks exert the strongest contractionary effect on exports, reducing growth by approximately 2.5–4.0% within the first few months. Inflation shocks follow, lowering exports by around 1.5–2.0%, while oil price and exchange rate shocks have relatively mild and short-lived impacts. Variance decomposition highlights the dominant role of monetary and price shocks in explaining short-term fluctuations in exports. These findings underscore the crucial importance of maintaining monetary stability and controlling inflation to support Vietnam’s textile and garment export capacity, complemented by fiscal investment in logistics, supporting industries, human capital development, and safeguarding export-led, employment-intensive growth in line with Vietnam’s broader sustainable development strategy and SDG commitments. The paper concludes with policy recommendations and suggests future research directions to address limitations related to data frequency, sample size, and structural identification assumptions.