Lecture 2: The Data of MicroeconomicsTextbook Chapter 2The word data is Latin for ‘things that aregiven’ – thus, if you passed the salt to a Latinspeaker at your dinner-table, the grains of saltwould technically be data. This might seem anodd choice of phrase for something that in themodern world is synonymous with‘information’, but as it turns out, it is actually These aren’t the Data we’re looking for.rather appropriate.The world provides us daily with an uncountable amount of information. Far from being difficult to acquire, data, in general, is given to us with in embarrassingly large volumes. The trick, of course, is to find the particular fact you want in the middle of a veritable flood of them. This is what takes effort, training and concentration: knowing how to find, recognize and extract valuable information.Moreover, if one is a scientist, finding a few bits of relevant data often aren’t enough. Suppose a doctor wants to find out if jelly beans cause cancer. If he finds a few stories of people who loved jelly beans and got cancer, and others who hated jelly beans and didn’t get cancer, that isn’t enough evidence on which to start pulling candy off store shelves. These are anecdotes: interesting tales which point the way but in and of themselves aren’t enough to allow the definitive settling of an issue. It might be that those jelly bean eaters would have gotten cancer anyway, and that the non-jelly-bean eaters only avoided cancer through coincidence and accident. To obtain a scientifically acceptable result, the doctor would probably have to collect thousands or hundreds of stories about specific individuals’ tastes for jelly beans and their propensities to die of cancer. The next step would then be to catalogue and analyze the relationships through some understood, rigorous method – most likely statistics. Looking at large amounts of carefully collectedinformation allows us to distinguish between what is coincidence and what isn’t, between a fluke and a pattern.It’s an old joke among econometricians that ‘data’ is the plural of ‘anecdote’, and that isn’t too far from the truth. What separates the two is that anecdotes are collected casually, while data is collected in a rigorous, systematic and goal-directed fashion. By ‘rigorous’, I mean that the collection method follows strict, understood rules. By ‘systematic’, I mean that the data is gathered in a regular, ordered fashion. By goal-directed, I mean that the data is acquired on purpose, rather than by accident. (Though occasionally, information gathered by accident may prove useful as data.)In this chapter, we will look at the results of data collection by statisticians, whose job it is to create the numbers that economists and econometricians work with. In particular, we will be looking at the statistics called the Gross Domestic Product, the Consumer Price Index and the Unemployment rate. You’ll already have seen these before, and at great length, in the pre-requisite to this course. Keeping that in mind, your focus this chapter should be in realizing that these numbers aren’t pulled out directly from the economy, but are created by specialists out of many different bits of data, and in understanding why we choose to stitch together these statistics, instead of many of the others we could have come up with.I. Gross Domestic Producta. What does it mean?‘Gross’ comes from the French ‘gros’, or ‘big’, and is often used – as in this case, and in ‘gross profits’ – to indicate that we are dealing with the general aspects of something, and not the specific detail.‘Domestic’ comes from the Latin ‘domesticus’, or ‘belonging to the household’. As we’ve already seen, the ‘households’ that macroeconomics deals with are entire countries.‘Product’ simply refers to anything that is produced, or made.Putting the three together, we find that Gross Domestic Product refers to a broad measure of everything that’s produced within a given country.b. What does it measure?GDP does its best to count the dollar value of everything produced in a country in a year. This is trickier than it sounds – your textbook has an excellent discussion of GDP measurement in Chapter 2, and I encourage (and expect) you to read it.c. Why do we use it?Despite the many problems with GDP measurement described in your textbook, we use this statistic because it seems to keep track of what’s most important in an economy, in a fairly reasonable fashion.Not only is it a measure of what’s produced within the borders of a country; it’s also a measure of how much is earned by people in that country in a year. This is because anything produced is eventually sold, in one form or another – and the payment the seller receives is income. Suppose a country consists of a bottled water firm and its workers. The workers buy water from the company which pays the workers who buy water, and so on.Money might not buy happiness, but it certainly helps do such things as keep people from starving or dying from exposure to the elements – and it does this by allowing the purchase of ‘stuff’ such as food, clothing or housing, all of which must be produced before they may be enjoyed by a consumer. Thus, GDP is a rough-and-ready measure of how well a country is doing in a general sense.As a measure of welfare, it leaves much to be desired, of course. A country where all the money goes to one person and the rest starve might have exactly the same GDP as a country where all income is distributed equally. Similarly, the ‘stuff’ produced might not be very useful to the country, its inhabitants or the residents of the nations it trades with. Still, GDP represents the possibilities available to a country; the raw ‘stuff’and income ithas to work with.Also, the fact remains that we can measure it. ‘Stuff that’s been made’ is something easier to count and turn into a number on a yearly basis than other things which might seem more relevant to well-being, such as health, knowledge, happiness, culture and environmental quality.That most countries calculate GDP yearly is very important, as it allows us to track changes in a country’s economy over time. This is made easier by the fact that GDP is expressed in the form of a single number; by simply plotting it we can spot depressions, recessions and booms – times of extraordinary economic activity which have definite and strong consequences on businesses and consumers. These affect employment, income, and to a lesser extent, the choice consumers have in what they buy. (Small specialty shops may close during a recession or depression.)Economic growth, which we’ll be looking at very closely over the coming weeks, consists of a sustained increase in the amount of stuff produced in a country over time (controlling for population growth) and hence, with a few tweaks to be described below, can be described as an increase in GDP per person over time.Just as the fact that a child is growing doesn’t guarantee that it is healthy, the existence of economic growth doesn’t necessarily mean that a country is ‘doing well’. However, in both cases a failure to grow, or a shrinking, implies that something’s wrong, and a specialist should be consulted to examine the case and determine if treatment is necessary.The biggest obstacle in measuring growth through GDP liesin the fact that GDP is calculated in terms of dollars (orpesos, or euros, or Yuan…), and the value of money itselfchanges. A bottle of Coca Cola cost five cents in 1900, and today the same amount of the drink costs about $1.25. If the Canadian economy produced nothing but one bottle of Coke, year after year, it would look like GDP had skyrocketed during the 20th century, while in fact the amount of stuff produced in the country had stayed the same! Thus,looking at raw yearly GDP values to calculate growth is like trying to measure changes in the height of a child with a ruler that keeps stretching and shrinking.Thankfully, we can correct for that. The way to do it is to put together a ‘basket’ of basic goods bought by the typical person in the economy, and track the value of this collection of items over time. This is called the consumer price index, or CPI. Then, correct the value of GDP by a factor that will make the value of the basket stay the same in different years. In our example, the obvious basket consists of one bottle of Coca-Cola. Since it cost five cents in 1900 and $1.25, or 25 times 5 cents, in 2005, we divide 2005 GDP by 25 to obtain real GDP – a value that allows us to compare stuff produced in two different years. In this case, we would call this divisor of 25 the ‘deflator’, because it removes the effects of ‘inflation’, or the rise in the cost of living, from GDP. GDP that hasn’t been corrected for inflation is called nominal GDP, from the Latin ‘nomine’, or name, because it is GDP in name only, and doesn’t really tell us the amount of stuff produced in a way that allows us to compare this value across years. Incidentally, the words ‘inflation’ and ‘deflator’ are used because the effect of a rise in prices on GDP is very much like the effect of air in a balloon – the balloon expands, or inflates, but the amount of stuff that it is made of doesn’t actually change. If we were to poke a pin into an inflated balloon, then it would rather quickly (and loudly!) deflate.In our example, real GDP in our one-Coke economy was the same in 1900 and 2005: 5 cents in 1900 dollars, or $1.25 in 2005 dollars. If instead, Canada had produced two bottles of Coke in 2005, then real GDP in 2005 would have been 10 cents, in 1900 dollars (or, alternatively, real GDP would have been $1.25 in 1900 and $2.50 in 2005, in 2005 dollars).It’s not so simple in real economies, of course. First of all, in a real economy we would probably not use the CPI as the deflator – instead, for the purposes of correcting GDP for inflation, we would use a ‘basket’ that consisted of all goods produced in the country in a given year (see the section entitled ‘The CPI Versus the GDP Deflator’ in Chapter 2 of your textbook). We would still use the CPI whenever a measure of how the cost of livingfor the average consumer changed was important, and indeed we’d likely have a whole bunch of indexes for other purposes – such as a producer price index when we’re interested in looking at how the costs businesses face has changed over time. This would be created by a creating a basket of raw materials that the typical firm buys.The problem here is that neither consumers, nor firms, nor even countries stay still with regards to what they make, use and buy. The average Canadian today might buy a lot of DVDs, which were unavailable in 1900, or might buy a lot less lard than the average consumer in the 1950s did, when the health consequences of a fatty diet weren’t well understood. Both of these show that occasionally, the basket has to change; either to include new goods, to eliminate those not produced anymore, or to change the amount of one product or another. Similar concerns apply to producer price indexes. You should read Section 2-3 of the text for more detail on the implications of these changes.Unemployed Miners Finally, a brief comment on the final statistic dealt with in the chapter: the unemployment rate. The unemployment rate measures the number of people looking for work and not able to find it as a percentage of the total number of people in the economy who are willing and able to work (known as the labour force). People might lack a job and still not be counted as unemployed, either because they’re unwilling or unable to work (they’re out of the labour force), or because they have given up looking for work (discouraged workers). Section 2-4 of your textbook gives a more thorough explanation of the concept.。
