Constructing a Composite Demand and Trade Pressure Index and Assessing Its Impact on Growth and Inflation in Syria

Abstract

This study constructs a composite index of demand and trade pressures in Syria over 1971–2022 and examines its dynamic effects on economic growth and inflation within a long-run time-series framework. The methodological design aggregates five real variables at constant 2000 prices that represent key demand and trade channels, namely government expenditure, private consumption, exports, imports, and investment. Principal Component Analysis is then employed to extract a latent index that captures the common movement across these variables and mitigates multicollinearity. The adequacy of the data for index construction is supported by a Kaiser–Meyer–Olkin value of 0.717 and a statistically significant Bartlett’s test (p = 0.000), while the first principal component explains approximately 66.7% of total variance, justifying the use of the composite measure as a summary indicator of the underlying pressure factor. Time-series properties are assessed using the Phillips–Perron test, showing that the TAD index and inflation are integrated of order one, I(1), whereas economic growth is stationary at level, I(0). A Structural Vector Autoregression (SVAR) model is subsequently estimated after selecting an optimal lag length of two according to the majority of information criteria, and shock transmission is evaluated through impulse response functions. The results indicate that a positive shock to the TAD index generates a short-run expansionary effect on economic growth that dissipates quickly without persistent statistical significance in the medium term, while producing a statistically significant short-run disinflationary effect that weakens over subsequent horizons. Overall, the proposed index offers an operational quantitative tool for tracking pressure waves in the Syrian economy and for informing policy trade-offs between supporting real activity and maintaining price stability under heightened uncertainty and volatility.