Say’s Law, often summarised by the phrase “supply creates its own demand,” is one of the most debated principles in the history of economic thought. At its core, it asserts that production is the source of demand: the act of producing goods generates incomes that enable equivalent purchasing power, thereby ensuring that general overproduction, or a “general glut,” is impossible. Although sometimes caricatured, Say’s Law has played a central role in shaping classical and neoclassical economic theory, as well as in providing a foil for later critiques, most notably from John Maynard Keynes.
Read MoreModern Monetary Theory (MMT) is one of the most provocative schools of thought to emerge in contemporary economics. It challenges conventional wisdom about government spending, taxation, and deficits, reframing the debate on fiscal policy in countries that issue their own fiat currency. At its heart, MMT argues that such governments are not financially constrained in the same way as households or firms. Instead, they have the sovereign capacity to create money, and therefore cannot “run out” of their own currency. This radical reorientation has profound implications for how we think about the limits of public spending, the role of taxation, and the relationship between fiscal and monetary policy.
Read MoreThe theory of marginalism stands as one of the most important turning points in the history of economic thought. At its core, marginalism concerns the idea that economic decisions are made at the margin—that is, the value of goods, services, or productive factors is determined not by their total or average contribution, but by the incremental benefit or cost associated with a small change in their use. This approach, which gained prominence in the late nineteenth century, transformed classical political economy into modern economics by introducing a new analytical framework for understanding value, utility, and decision-making.
Read MoreOne of the most fundamental concepts in time series econometrics is stationarity. A stationary time series is one whose statistical properties—such as mean, variance, and autocorrelation—remain constant over time. This concept may appear technical, but it is central to the validity of econometric inference. Much of modern applied econometrics, from forecasting inflation to modelling asset prices, rests on the assumption of stationarity. When this condition is violated, standard results collapse, leading to spurious regressions, misleading inferences, and flawed policy conclusions.
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