Running towards

How economics can help us understand even the bleakest of histories

Meet Carel. In February 1834, on a farm outside Worcester, a 55-year-old enslaved coppersmith slipped his owner’s grip and disappeared. He had done it before. Sometime, somewhere along the way, he had picked up an Irish-sounding alias: ‘Mr Paddy’. Under that Irish pseudonym he hired himself out to one employer after another – a forge here, a building site there – living and working as if the law had never named him another man’s property. His owner, Schalk Willem van der Merwe, eventually placed an advert in the Government Gazette of 7 March 1834. It listed Carel’s height, his bald head, the burn marks on his arm, the fluency of his Dutch. Van der Merwe never recovered him. The next entry in his slave register simply ends.

Why did Carel run when he did? You can answer that with cruelty. You can answer it with longing. Both answers are true, and both are insufficient.

In a paper just published in the Asia-Pacific Economic History Review, Karl Bergemann, Gabriel Brown and I offer a third answer that sits alongside those other two. Carel ran when he did because the labour market had shifted under his feet – and he was the kind of man best placed to take advantage of the shift. Here’s why it matters: even under the most brutal of institutions, people still respond to economic incentives. Histories that ignore those incentives end up underselling the agency of the very people they want to honour. Economics, used carefully, gives us a lens onto choices that the archive otherwise leaves dark.

Start with a simple question. Why does anyone bother to coerce labour at all? It is, after all, expensive. You have to pay for overseers, walls, advertisements, recapture. The economist Daron Acemoglu and Alexander Wolitzky asked exactly this in a 2011 paper, and their answer is short: coercion pays only when workers have nowhere better to go. The moment a worker’s outside option – the wage they could earn somewhere else, the place they could blend in, the legal crack they could slip through – improves, the maths of coercion changes. The cost of holding people in place rises. People start to leave. Owners start to look for cheaper ways to get the work done.

That gave us a sharp, testable prediction for the Cape in the 1830s. Britain’s Slavery Abolition Act came into force at the Cape in December 1834, but it did not deliver freedom on that day. Instead, it began a four-year apprenticeship: the legal status changed, but the work continued. Wage labour, however, started to expand. Free Black and Khoe workers were already moving across the colony as masons, harvesters, wagon drivers, smiths. Recaptured Africans were finishing their indentures. Punishment books and guardian offices were chipping away at owners’ arbitrary power. None of this added up to liberation. It did, however, add up to a real improvement in the outside option for someone bold enough to try the wage economy without permission.

If the model is right, the most skilled enslaved people should have been the ones who ran first after December 1834. They had the most to gain by selling their hands as free workers. The least skilled, by contrast, should not have run any more than before – and might even have run a little less, since full freedom was now only four years away.

Testing this needed two pieces of data that nobody had ever combined before.

The first was a hand-built dataset of 689 runaway adverts placed between 1830 and 1838 in the colony’s two leading newspapers, De Zuid Afrikaan and the Cape of Good Hope Government Gazette. These adverts are not perfect. Owners only paid to advertise the runaways they thought worth recovering. But for the people they did describe, they described in detail: name, age, skills, clothing, the names of farmers who had hired them, even the pseudonyms they used.

The second was the Cape’s slave emancipation dataset, compiled from valuation rolls drawn up in 1834 to calculate the compensation paid to owners. Every enslaved person on it has an official price. That price was set by assessors using auction records: skilled workers were valued more, unskilled less, the sick and elderly less again. Imperfect, yes. But for our purposes, valuation is a usable proxy for the wage someone could plausibly earn outside slavery. We matched 344 of the runaway adverts to individuals in the emancipation dataset.

That gave us the building blocks of a difference-in-differences design – a workhorse tool of empirical economics. The idea is straightforward. Take two groups: one expected to respond to the change (high-valuation enslaved people) and one not (low-valuation). Compare how their escape rates moved before and after December 1834. The ‘high minus low’ comparison sweeps out anything common to both groups – weather, harvest cycles, the colony’s wider unrest. What remains is the differential response. That residual is what the model says should jump.

The picture is the argument. Before 1834, the two lines move roughly together. Both rise as the 1830s wear on. After December 1834, they separate. Escapes among low-valuation enslaved people drop sharply: they no longer have much to gain from a dangerous flight when legal freedom is only a few years away. Escapes among high-valuation enslaved people, however, stay high for two more years – before falling again as 1838, the date of full emancipation, comes within sight.

Translated into numbers: across the full 1830–1838 window, the diff-in-differences estimate is a 38 to 61 per cent rise in escapes for the higher-valued group, depending on the specification. But this average understates the moment itself. When we zoom in tightly on the months either side of December 1834 – using a separate technique called regression discontinuity in time, designed precisely to catch sharp breaks – the high-valuation jump is over 100 per cent above the pre-emancipation mean. The effect then fades, gradually, as full freedom approaches and the gain from running early shrinks back to nothing.

In short: when freedom-on-paper arrived in December 1834, the people best placed to earn a wage outside slavery moved first. The model called the shot.

It is entirely reasonable to push back here. Does this mean cruelty did not matter? Of course it does not. The sheer number of low-valuation runaways – women, children, the elderly, the unskilled – is testament to the desperation that drove flight throughout the colony’s history. Our estimates capture only the marginal response to a change in incentives. They do not, and cannot, explain every flight. The data have their limits too: adverts only record runaways their owners thought worth advertising; valuations capture skill imperfectly; and we cannot cleanly separate the channels through which outside options improved – legal reform, expanded wage demand, easier passing as free.

What the result does say is that even under chains, the calculus of the labour market reached the people inside it. Carel’s flight was not random. It was the choice of a man with rare skills, walking towards the place those skills could feed him.

Economics is often accused of speaking only about prices and markets, and of having little to say about the parts of life that actually weigh on us. Slavery is the hardest case. And yet here it is the economic lens – outside options, incentives, marginal response – that lets us read a fragment of the lives of people the colonial archive usually buries beneath the words of their owners. Those people noticed when their world changed. They acted on the change.

That is the discipline at its best: a way of taking seriously the choices of people in markets, including the people the law refused to count as people. We have many of these stories still to tell. Karl is currently writing a book that will tell more of them.