Nowhere is this contrast sharper than in the context of how development economists think about the credit market. The role of capital (with a capital K and the honorific Das, if you like) in economic development and how it is allocated in a market economy remains as contested a terrain within mainstream economics as ever.
Until recently, mainstream economics did not pay much attention to the issue of economic advantages from being rich. Someone who has the skills and the drive but not the resources would be able to borrow, start a business, make profits, pay off the loan, and everyone will be better off.
Compared to someone who owned the resources, an individual who has to repay a loan will have a lower level of net earnings. However, through savings and bequests, such disparities will disappear over time. This is the convergence view due to Robert Solow: initial disparities will disappear over time and those that persist reflect differences in ability and preferences (for example, propensity to save, work hard).
Therefore, if the situation is one of equal opportunity or no entry barriers, someone with resources would have no extra advantages in the long-run. A well-functioning credit market plays a vital role in this argument. It allows those who have surplus savings to lend it to those who have skills, talents and ideas. In addition it allows those who are born poor to acquire skills through education and move up the economic ladder.
Contrast this with the opposite scenario: suppose for some reason credit markets do not exist. In that case unless someone inherits wealth, he or she cannot enter into professions or businesses or acquire skills that require large capital investments. Two individuals with identical preferences and abilities will end up with very different levels of income because of resource constraints. In this situation initial inequalities are likely to persist in the long-run even if everyone has the same preferences and abilities. This is the poverty trap view.
It is still possible for someone poor to keep saving until he or she (or some distant descendant) has the threshold level of wealth to enter these professions. But this is highly implausible. If a subsistence level of consumption is to be ensured, the rate of saving will be lower for poorer households. In reality credit markets are unlikely to be either frictionless or completely absent.
But the poverty trap argument goes through so long as the poor face tougher terms in the credit market, whether it is the likelihood of getting a loan, the size of the loan, or the interest charges.
How does this square off with the fact that poorer borrowers are likely to be much more eager to borrow Typically, customers who value something more are willing to outbid others for it. This has to do with the peculiar nature of credit as a commodity. When someone buys credit, unlike spot transactions such as buying an apple, all that the lender gets in exchange of giving out money is a promise (to pay back in the future). Richer borrowers can make this promise more credibly than poorer borrowers, since they can offer collateral.
The policy implications of these views are drastically different. The poverty-trap based view immediately implies that redistributive policies that relax borrowing constraints can be good for both efficiency and equity reasons. In contrast, the convergence-based view suggests the standard trade-off between equity and efficiency.
So the question is, are credit markets indeed imperfect Even though it seems like a simple-minded question (as my mother would say, nothing in this world is perfect, son) and the answer might seem self-evident (why try to prove something that a quick glance outside your office window would seem to settle), empirical micro-economists are a really hard-nosed and hard-to-convince bunch.
If you say that the size of the domestic credit market is strongly positively correlated with per capita income across countries (as suggested by Table 1), they will say that the causality could be the other way round: richer countries have larger markets for everything, including credit. Also, both per capita income and size of the credit market could be driven by other factors, such as good government policies, so that this correlation does not necessarily suggest a causal relationship.
If you say, well, interest rates are very high in developing countries they will say that it reflects scarcity. If you say that there are big differences in interest rates that are not being equalised by arbitrage, they would say that is because the underlying risk-profiles of the borrowers and the costs of financial intermediation are different.
If you say that longitudinal data sets in the US and the UK that track individuals over a long period, show that those with more inherited wealth are more likely to become an entrepreneur, they will say factors that affect a familys ability to save and leave bequests to their children (for example, ability, work ethic) also affect the ability to become an entrepreneur.
You might say that rates of return to capital in firms estimated using data on firm earnings and capital stock are high, and exceed significantly the formal or informal interest rates available. If returns from capital significantly exceed its cost, firms should be expanding their capital stock, and if they arent that means they are credit constrained. Not necessarily, they will say. The ability of entrepreneurs affect both the choice of the capital stock, and the rate of return (for example, smart guys need less capital and can generate more returns), and without controlling for it, these are biased estimates. In particular, we dont know whether we are measuring the returns to ability or to capital and whether the capital stock is optimally chosen given the entrepreneurs ability, or the firm is credit-constrained.
OK, since ability is notoriously hard to measure, you would think that this is the point at which economists would give up. No. Suresh de Mel of University of Peradeniya in Sri Lanka, Christopher Woodruff of the University of California at San Diego, and David McKenzie of the World Bank have come up with a direct and ingenious approach.1: Why not take a random sample of firms and then randomly give some of them some extra capital and measure the difference with those who did not get it
This is similar to randomised control trials in medicine where some patients are randomly chosen and given a treatment and others are given a placebo and the average difference in the outcome of the two groups is attributed to the treatment. These studies are becoming increasingly popular in development economics.
The authors randomly distributed small capital grants worth $100 and $200 to a sample of small enterprises (with less than $1,000 in capital) in Sri Lanka. Since by design the grants were given randomly, both talented and not-so-talented entrepreneurs would get them. If we measure the effect of these grants, it will capture the average effect across all talent levels. In particular, we will not have to worry that the extra capital generated by the grant to a firm is correlated with the ability of its entrepreneur and so we will be measuring the effect of extra capital only.
Table 2 suggests that the treatment and control groups are roughly similar in all respects, starting with initial level of profits, initial capital stock, various characteristics of the entrepreneur (age, education) and the firm. This confirms the validity of their randomisation strategy.
The authors then estimate the effect of these two types of treatments on capital stock and profits. The difference between the capital stock and the profit levels of the treatment firms relative to the control firms are displayed in Table 3. They estimate the returns to capital to be around 4% per month, or 60% per year. This is substantially higher than market interest rates. This suggests the firms are indeed credit-constrained.
Credit is due to the authors for this innovative study, and to millions of small businesses in developing countries. What policies can achieve that That is another story.
The author is professor of economics at the London School of Economics