Abstract
How large are the macroeconomic effects of financial sanctions and how one can distinguish the sanction shocks from other aggregate shocks affecting the economy at the same time? We employ a Bayesian (S)VAR model to estimate the effects of the Western financial sanctions imposed on the Russian economy in 2014 (first wave) and 2017 (second wave). The sanctions decreased the Russia's corporate external debt and raised the country spread, but their effects were confounded by falling oil prices in 2014 (negative terms-of-trade, TOT, shock) and rising oil prices in 2017.
We begin disentangling the sanction and TOT effects with a conditional forecasting approach, in which we simulate pseudo out-of-sample projections of domestic macroeconomic variables conditioned (i) solely on the oil price changes and then (ii) on both oil prices and external debt deleveraging. For each endogenous variable, we treat the difference between the two projections as the effect of sanctions.
We then apply a structural approach to identify sanction shocks. Our results consistently indicate that the sanction effects were negative and non-negligible across the two sanction waves, being sizeable for the financial variables (real interest rate and corporate external debt) and moderate for the real variables (output, consumption, investment, trade balance, and the ruble real exchange rate).
We argue that the estimated effects of sanctions are in line with the theoretical predictions from the literature on country spread shocks in open economies.