Abstract
Societies are facing numerous grand challenges and leaders are increasingly counted on to provide solutions. Top-level institutional leaders are implicitly assumed to have an effect on important social and organizational outcomes. But can top-level leaders affect outcomes that unfold across space and time via various pathways? Some research streams have suggested that organizational outcomes may not be caused by, but are simply ascribed to the leader; leadership may merely be a social construction. We provide a rigorous test to determine whether leaders matter by exploiting a very controlled, though unusual leadership context, where leader discretion is large; that of U.S. state governors. This context allows us to estimate precisely what role top-level leaders may play in determining institutional outcomes, measured on a standard metric. We quantify the “leadership effect” in a sample of 500 governors across the 50 states of the U.S. and the district of Columbia. We use a custom likelihood function to implement state-of-the-science methodical advances in variance decomposition on a sample of 2,985 governor-time observations, covering the periods 1963 to 2019, to explain variance in real yearly Gross Domestic Product (GDP) growth. After having partialed out time effects (0.47 of the variance in real yearly GDP growth), we show that governors are responsible for 4.45% of the variation in real GDP growth, while state-effects only account for 1.45% of the variation in real yearly GDP growth. Our results contradict earlier research suggesting that top-level leadership may not matter (e.g., Salancik & Pfeffer, 1977). Keywords: Leadership, Variance decomposition, Economic growth, Leader performance, GDP, Political Leadership, Maximum likelihood, Autoregression.
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