(1) Economics

 Introduction to Economics, LSE

University of London


Becky’s world

Becky, who is 10 years old, lives with her parents and an older brother Sam in a suburban town in America’s Midwest. Becky’s father works in a firm specializing in property law. Depending on the firm’s profits, his annual income varies somewhat, but is rarely below 145,000 US dollars ($145,000). Becky’s parents met at college. For a few years her mother worked in publishing, but when Sam was born she decided to concentrate on raising a family. Now that both Becky and Sam attend school, she does voluntary work in local education. The family live in a two-storey house. It has four bedrooms, two bathrooms upstairs and a toilet downstairs, a large drawing-cum-dining room, a modern kitchen, and a family room in the basement. There is a plot of land at the rear – the backyard –which the family use for leisure activities.

Although their property is partially mortgaged, Becky’s parents own stocks and bonds and have a saving account in the local branch of a national bank. Becky’s father and his firm jointly contribute to his retirement pension. He also makes monthly payments into a scheme with the bank that will cover college education for Becky and Sam. The family’s assets and their lives are insured. Becky’s parents often remark that, because federal taxes are high, they have to be careful with money; and they are. Nevertheless, they own two cars; the children attend camp each summer; and the family take a vacation together once camp is over. Becky’s parents also remark that her generation will be much more prosperous than theirs.Becky wants to save the environment and insists on biking to school. Her ambition is to become a doctor.


Desta’s world


Desta, who is about 10 years old, lives with her parents and five siblings in a village in subtropical, southwest Ethiopia. The family live in a two-room, grass-roofed mud hut. Desta’s father grows maize and teff (a staple cereal unique to Ethiopia) on half a hectare of land that the government has awarded him. Desta’s older brother helps him to farm the land and care for the household’s livestock, which consist of a cow, a goat, and a few chickens. The small quantity of teff produced is sold so as to raise cash income, but the maize is in large measure consumed by the household as a staple. Desta’s mother works a small plot next to their cottage, growing cabbage, onions, and enset (a year-round root crop that also serves as a staple). In order to supplement their household income, she brews a local drink made from maize. As she is also responsible for cooking, cleaning, and minding the infants, her work day usually lasts 14 hours. Despite the long hours, it wouldn’t be possible for her to complete the tasks on her own. (As the ingredients are all raw, cooking alone takes 5 hours or more.) So Desta and her older sister help their mother with household chores and mind their younger siblings. Although a younger brother attends the local school, neither Desta nor her older sister has ever been enrolled there. Her parents can neither read nor write, but they are numerate. Desta’s home has no electricity or running water. Around where they live, sources of water, land for grazing cattle, and the woodlands are communal property. They are shared by people in Desta’s village; but the villagers don’t allow outsiders to make use of them. Each day Desta’s mother and the girls fetch water, collect fuel wood, and pick berries and herbs from the local commons. Desta’s mother frequently complains that the time and effort needed to collect their daily needs has increased over the years.

There is no financial institution nearby to offer either credit or insurance. As funerals are expensive occasions, Desta’s father long ago joined a community insurance scheme (iddir) to which he contributes monthly. When Desta’s father purchased the cow they now own, he used the entire cash he had accumulated and stored at home, but had to supplement that with funds borrowed from kinfolk, with a promise to repay the debt when he had the ability to do so. In turn, when they are in need, his kinfolk come to him for a loan, which he supplies if he is able to. Desta’s father says that such patterns of reciprocity he and those close to him practise are part of their culture. He says also that his sons are his main assets, as they are the ones who will look after him and Desta’s mother in their old age.

Economic statisticians estimate that, adjusting for differences in the cost of living between Ethiopia and the United States (US), Desta’s family income is about $5,500 per year, of which $1,100 are attributable to the products they draw from the local commons.

However, as rainfall varies from year to year, Desta’s family income fluctuates widely. In bad years, the grain they store at home gets depleted well before the next harvest. Food is then so scarce that they all grow weaker, the younger children especially so. It is only after harvest that they regain their weight and strength. Periodic hunger and illnesses have meant that Desta and her siblings are somewhat stunted. Over the years Desta’s parents have lost two children in their infancy, stricken by malaria in one case and diarrhoea in the other. There have also been several miscarriages. Desta knows that she will be married (in all likelihood to a farmer, like her father) five years from now and will then live on her husband’s land in a neighbouring village. She expects her life to be similar to that of her mother.


The economist’s agenda


That the lives people are able to construct differ enormously across the globe is a commonplace. In our age of travel, it is even a common sight. That Becky and Desta face widely different futures is also something we have come to expect, perhaps also to accept.

Nevertheless, it may not be out of turn to imagine that the girls are intrinsically very similar. They both enjoy playing, eating, and gossiping; they are close to their families; they turn to their mothers when in distress; they like pretty things to wear; and they both have the capacity to be disappointed, get annoyed, be happy.

Their parents are also alike. They are knowledgeable about the ways of their worlds. They also care about their families, finding ingenious ways to meet the recurring problem of producing income and allocating resources among family members – over time and allowing for unexpected contingencies. So, a promising route for exploring the underlying causes behind their vastly different conditions of life would be to begin by observing that the opportunities and obstacles the families face are very different, that in some sense Desta’s family are far more restricted in what they are able to be and do than Becky’s.

Economics in great measure tries to uncover the processes that influence how people’s lives come to be what they are. The discipline also tries to identify ways to influence those very processes so as to improve the prospects of those who are hugely constrained in what they can be and do. The former activity involves finding explanations, while the latter tries to identify policy prescriptions. Economists also make forecasts of what the conditions of economic life are going to be; but if the predictions are to be taken seriously, they have to be built on an understanding of the processes that shape people’s lives; which is why the attempt to explain takes precedence over forecasting.

The context in which explanations are sought or in which prescriptions are made could be a household, a village, a district, a country, or even the whole world – the extent to which people or places are aggregated merely reflects the details with which we choose to study the social world. Imagine that we wish to understand the basis on which food is shared among household members in a community. Household income would no doubt be expected to play a role; but we would need to look inside households if we are to discover whether food is allocated on the basis of age, gender, and status. If we find that it is, we should ask why they play a role and what policy prescriptions, if any, commend themselves. In contrast, suppose we want to know whether the world as a whole is wealthier today than it was 50 years ago. As the question is about global averages, we would be justified in ironing out differences within and among households.

Averaging is required over time as well. The purpose of the study and the cost of collecting information influence the choice of the unit of time over which the averaging is done. The population census in India, for example, is conducted every ten years. More frequent censuses would be more costly and wouldn’t yield extra information of any great importance. In contrast, if we are to study changes in the volume of home sales across seasons, even annual statistics would miss the point of the inquiry. Monthly statistics on home sales are a favourite compromise between detail and the cost of obtaining detail.

Modern economics, by which I mean the style of economics taught and practised in today’s leading universities, likes to start the enquiries from the ground up: from individuals, through the household, village, district, state, country, to the whole world. In various degrees, the millions of individual decisions shape the eventualities people face; as both theory, common sense, and evidence tell us that there are enormous numbers of consequences of what we all do. Some of those consequences have been intended, but many are unintended. There is, however, a feedback, in that those consequences in turn go to shape what people subsequently can do and choose to do. When Becky’s family drive their cars or use electricity, or when Desta’s family create compost or burn wood for cooking, they add to global carbon emissions. Their contributions are no doubt negligible, but the millions of such tiny contributions sum to a sizeable amount, having consequences that people everywhere are likely to experience in different ways. It can be that the feedbacks are positive, so that the whole contribution is greater than the sum of the parts. Strikingly, unintended consequences can include emergent features, such as market prices, at which the demand for goods more or less equals their supply.

Earlier, I gave a description of Becky’s and Desta’s lives. Understanding their lives involves a lot more; it requires analysis, which usually calls for further description. To conduct an analysis, we need first of all to identify the material prospects the girls’ households face – now and in the future, under uncertain contingencies. Second, we need to uncover the character of their choices and the pathways by which the choices made by millions of households like Becky’s and Desta’s go to produce the prospects they all face. Third, and relatedly, we need to uncover the pathways by which the families came to inherit their current circumstances.

These amount to a tall, even forbidding, order. Moreover, there is a thought that can haunt us: since everything probably affects everything else, how can we ever make sense of the social world?

If we are weighed down by that worry, though, we won’t ever make progress. Every discipline that I am familiar with draws caricatures of the world in order to make sense of it. The modern economist does this by building models, which are deliberately stripped down representations of the phenomena out there. When I say ‘stripped down’, I really mean stripped down. It isn’t uncommon among us economists to focus on one or two causal factors, exclude everything else, hoping that this will enable us to understand how just those aspects of reality work and interact.

The economist John Maynard Keynes described our subject thus: ‘Economics is a science of thinking in terms of models joined to the art of choosing models which are relevant to the contemporary world.’

As economists deal with quantifiable objects (calories consumed, hours worked, tonnes of steel produced, miles of cable laid, square kilometres of equatorial forests destroyed), the models are almost always mathematical constructs. They can be stated in words, but mathematics is an enormously efficient way to express the structure of a model; more interestingly, for discovering the implications of a model. Applied mathematicians and physicists have known this for a long time, but it was only in the second half of the 20th century that economists brazenly adopted that research tactic; as have related disciplines, such as ecology. The art of good modelling is to generate a lot of understanding from focusing on a very small number of causal factors. I say ‘art’, because there is no formula for creating a good model. The acid test of a model is whether it discriminates among alternative explanations of a phenomenon.

Those that survive empirical tests are accepted – at least for a while – until further evidence comes along that casts doubt on them, in which case economists go back to their drawing board to create better (not necessarily bigger!) models. And so on.

The methodology I have sketched here, all too briefly, enables economists to make a type of prediction that doesn’t involve forecasting the future, but instead to make predictions of what the data that haven’t yet been collected from the contemporary world will reveal. This is risky business, but if a model is to illuminate, it had better do more than just offer explanations after the events. Until recently, economists studied economic history in much the same way historians study social and political history. They tried to uncover reasons why events in a particular place unfolded in the way they did, by identifying what they believed to be the key drivers there. The stress was on the uniqueness of the events being studied. A classic research topic in that mould involved asking why the first industrial revolution occurred in the 18th century and why it took place in England. As you can see, the question was based on three presumptions: there was a first industrial revolution; it occurred in the 18th century; and it was based in England. All three premises have been questioned, of course, but there was an enormous amount of work to be done even among those who had arrived at those premises from historical study. In the event, the literature built round those questions is one of the great achievements of economic history.

In recent years economists have added to that a statistical approach to the study of the past. The new approach stays close to economic theory, by laying emphasis on the generality of the processes that shape events. It adopts the view that a theory should uncover those features that are common among economic pathways in different places, at different times. Admittedly, no two economies are the same, but modern economists work on the commonality in the human experience, not so much on its differences. Say, you want to identify the contemporary features in Desta’s and Becky’s worlds that best explain why the standard of living in the former is so much lower than in the latter. A body of economic models tells you that those features are represented by the variables X, Y, and Z. You look up international statistics on X, Y, and Z from a sample of, perhaps, 149 countries. The figures differ from country to country, but you regard the variables themselves as the explanatory factors common to all the countries in the sample. In other words, you interpret the 149 countries as parallel economies; and you treat features that are unique to each country as idiosyncrasies of that country. Of course, you aren’t quite at liberty to model those idiosyncrasies any way you like. Statistical theory – which in the present context is called econometrics – will set limits on the way you are able to model them. On the basis of the data on the 149 countries in your sample, you can now test whether you should be confident that X, Y, and Z are the factors determining the standard of living. Suppose the tests inform you that you are entitled to be confident. Then further analysis with the data will also enable you to determine how much of the variation in the standard of living in the sample is explained by variations in X in the sample, by variations in Y, and by variations in Z. Those proportions will give you a sense of the relative importance of the factors that determine the standard of living. Suppose 80% of the variation in the standard of living in those 149 countries can be explained by the variation in X in the sample; the remaining 20% by variations in Y and Z. You wouldn’t be unjustified to conclude, tentatively, that X is the prime explanatory variable.

There are enormous problems in applying statistics to economic data. For example, it may be that your economic models, taken together, suggest that there could be as many as, say, 67 factors determining the standard of living (not just X, Y, and Z). However, you have a sample of only 149 countries. Any statistician will now tell you that 149 is too small a number for the task of unravelling the role of 67 factors. And there are other problems besetting the econometrician. But before you abandon statistics and rush back to the narrative style of empirical discourse, ask yourself why anyone should believe one scholar’s historical narrative over another’s. You may even wonder whether the scholar’s literary flair may have influenced your appreciation of her work. Someone now reassures you that even the author of a historical narrative has a model in mind. He tells you that the author’s model influenced her choice of the evidence displayed in her work, that she chose as she did only after having sifted through a great deal of evidence. You ask in response how you are to judge whether her conceptual model is better than someone else’s. Which brings us back to the problem of testing alternative models of social phenomena. We will discover that historical narratives continue to play an important role in modern economics, but they are put to work in conjunction with model-building and econometric tests.

There are implicit assumptions underlying econometric tests that are hard to evaluate (how the country-specific idiosyncrasies are modelled is only one of them). So, economic statistics are often at best translucent. It isn’t uncommon for several competing models to co-exist, each having its own champion. Model-building, data availability, historical narratives, and advances in econometric techniques reinforce one other. As the economist Robert Solow expresses it, ‘facts ask for explanations, and explanations ask for new facts’.

I first want to give you a feel for the way economists go about uncovering the economic pathways that shape Becky’s and Desta’s lives. I shall do that by addressing the three sorts of questions that were identified earlier as our concern. I shall then explain why we need economic policies and how we should go about identifying good ones. We will certainly build models as we go along, but I shall mostly use words to describe them. I shall also refer to empirical findings, from anthropology, demography, ecology, geography, political science, sociology, and of course economics itself. But the lens through which we will study the social world is that of economics. We will assume a point of view of the circumstances of living that gives prominence to the allocation of scarce resources – among contemporaries and across the generations. My idea is to take you on a tour to see how far we are able to reach an understanding of the social world around us and beyond.





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