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Abstract

Even though Sweden over 2020–2021 had a lower excess mortality rate than most European countries, five studies employing the Synthetic Control Method (SCM) concluded that Sweden would have experienced significantly lower mortality had it imposed a mandatory lockdown in early 2020. I argue that the large mortality reductions attributed to lockdowns in these studies are not policy effects at all, but rather are the artifacts of unbalanced time-varying confounding and early-shock omitted-variable bias, mechanically absorbed into model fittings. Their findings are artifacts of short pre-lockdown windows which are epidemiologically uninformative. I demonstrate that SCM yields highly divergent estimates for Swedish regions with identical policies, indicating that the method captures stochastic variation in viral seeding rather than the causal effect of lockdowns. I show that the SCM studies often report biologically implausible effects (sometimes appearing before the virus could have killed) and often fail standard donor-based placebo tests for statistical significance of their estimates. These findings cast serious doubt on the reliability of SCM in this setting. Sweden’s low excess mortality in the end suggests that Sweden’s state epidemiologist, Anders Tegnell, was right all along.