Unemplyment impacts on business

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Discuss different types (frictional, structural and cyclical) of unemployment and the impact of each type of unemployment on businesses. Are all three types of unemployment undesirable? Explain. Minimum 300 words, APA Format. References also cited in APA Format. Reading material is attached. Chapter 2, pages 38-52 and pages 58-61.

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M PRA Munich Personal RePEc Archive Macroeconomic Theory and Policy (2nd Edition) David Andolfatto Simon Fraser University 1. January 2008 Online at http://mpra.ub.uni-muenchen.de/6403/ MPRA Paper No. 6403, posted 19. December 2007 17:56 UTC MACROECONOMIC THEORY & POLICY 2nd Edition David Andolfatto Simon Fraser University 2008 Chapters Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter 1: 2: 3: 4: 5: 6: 7: 8: 9: The Gross Domestic Product Output and Employment Uncertainty and Expectations Unemployment Consumption and Saving Fiscal Policy Capital and Investment Money and Inflation Growth and Development ............................................ ............................................ ............................................ ............................................ ............................................ ............................................ ............................................ ............................................ ............................................ 1 38 63 77 99 129 155 172 210 Chapter Contents 1. The Gross Domestic Product. National Income and Product Accounting. Measurement Issues. Nominal versus Real GDP. Trends and Cycles. Schools of Thought. 2. Output and Employment. The Market for Goods and Labor. General Equilibrium in a Static Income-Leisure Model. A Neoclassical Interpretation of the Business Cycle. Welfare-Reducing Stabilization Policy. 3. Uncertainty and Expectations. Decision-Making Under Uncertainty. Ex ante versus ex post outcomes. Rational and Irrational Expectations. Multiple Equilibria and Animal Spirits. Welfare-Improving Stabilization Policy. 4. Unemployment. Labor Market Flows. A Simple Indivisible-Labor Model of Employment Choice. Reservation Wages. Modeling Unemployment. Government Insurance Policies. 5. Consumption and Saving. A 2-Period Endowment Model. International Borrowing and Lending. The Real Rate of Interest. The Intertemporal Budget Constraint. Consumer Demand and Desired Domestic Saving. The Current Account and the Trade Balance. Transitory, Anticipated, and Persistent Productivity Shocks. Reverse Causality. 6. Fiscal Policy. Accounting and Data. Government Spending and Taxation in a Static Model. Lump-Sum versus Distortionary Taxation. Government Transfer Policies. Government Deficits in a 2-Period Model. The Intertemporal Government Budget Constraint. The Ricardian Equivalence Theorem. Transitory Government Expendenture Shocks and TaxSmoothing Policy. Tax versus Bond-Financed Increases in Government Purchases. 7. Capital and Investment. Domestic Investment Demand in a 2-Period Model. A Small Open Economy with Saving and Investment. Interpreting the Cyclical Behavior of the Trade Balance. Closed Economy Analysis and the Determination of the Real Rate of Interest. The IS Curve and the Keynesian Cross. Interpreting Policy Implications Based on Conventional Wisdom. 8. Money and Inflation. A Simple Overlapping Generations Model. The Demand for Real Money Balances. Monetary Equilibrium. The WelfareEnhancing Role of Monetary Exchange. Money Neutrality and NonNeutrality. Inflation, Seigniorage, and War Finance. The Laffer Curve. A Simple Model of Money and Banking. Government versus Private Supply of Money. International Monetary Systems. Nominal Exchange Rate Indeterminacy. Multilateral and Unilateral Fixed Exchange Rate Regimes. Speculative Attacks. Monetary Union. 9. Economic Growth and Development. Long-Run Evidence. A Malthusian Model with Fertility Choice. Children as an Investment Good. Private Property Rights and Asset Markets. Accounting for the Great Transition. Recent Development Patterns. Special Interests. 4 Preface There is today a large discrepancy in the way macroeconomic theory is practiced by researchers and in the way it is taught to undergraduates. I am not exactly sure why this is the case. Perhaps some instructors—trained in older methods—feel that modern macroeconomic theory, with its insistence on microeconomic rigor, obscures the forest for the trees. Perhaps some instructors— trained in modern methods—feel that the modern approach is simply too complicated (mathematical) for the average undergraduate to absorb. Whatever the reasons, I believe that they are all wrong. While modern methods can indeed be complicated, the basic economic forces embedded within a (say) dynamic, stochastic, general equilibrium model can be expressed in a very simple and intuitive manner. Moreover, this can be done largely with the aid of diagrams of the form: A This is not a complicated diagram. In mathematical terms, it requires nothing more than highschool alegebra to analyze formally (if the simple calculus is first provided—something I would recommend for introductory or intermediate level courses). For better or worse (and I would argue the former), this simple diagram summarizes the essential ingredients of any economic theory. And yet, its presence is strangely absent in the way macroeconomics is commonly taught. There is no reason for why this should be the case. The diagram above represents ideas that are familiar to any economist. The first is that people have preferences defined over different commodities; and they they are generally willing to substitute across commodities. The second is that people face constraints; and that these constraints dictate the ability to substitute across commodities. Individual behavior is presumed to reflect the interaction between preferences and constraints. Aggregate behavior constitutes a collection of individual behaviors that are in some sense consistent with each other. That is, we construct Leviathan (cover) by adding up his individual pieces. This simple way of organizing thought is at the same time intuitive and remarkably flexible. It is intuitive because almost anyone can relate to the idea that incentives influence behavior. It is flexible because “commodities” can be defined in any number of ways; so that the diagram can be brought to bear on almost any economic phenomenon. For example, I use this diagram to develop theories of labor supply, consumption and saving, money demand, and fertility choice. There is one other great benefit associated with the diagram. In particular, because it makes explicit reference to peoples’ preferences, it can be used to evaluate the welfare consequences of government policy. Exactly how one is to do this without reference to individual preferences escapes me entirely. Moreover, by being explicit about individual preferences, one quickly learns to be cautious in terms of relating conventional measures of macroeconomic activity to any sensible notion of social welfare. A higher GDP or a higher current account surplus, for example, do not necessarily imply a higher level of welfare; and Leviathan may find it optimal to allow for some positive level of unemployment. I should like to offer a response to a criticism that one sometimes hears in relation to the modern macroeconomic analysis. Throughout the text, I make liberal (but not exclusive) use of to so-called “representative agent” assumption. This I do primarily for pedagogical purposes. In fact, the modern approach in no way depends on the representative agent formulation (there is nothing that prevents one from introducing as much heterogeneity as desired). While some conclusions are no doubt sensitive to the assumption, there are many others that are not (and it is these latter conclusions that deserve emphasis). In any case, I find it ironic that the criticism of this abstraction is most often leveled by those who prefer the older methodology; which, by its very nature, is typically cast in terms of a representative agent (e.g., in the form of aggregate behavioral relationships that make no reference to individual differences). There is something else that I should point out. I make virtually no attempt in the text to describe what has become a highly influential branch of modern macroeconomic theory; the so-called New-Keynesian approach. This is regretable primarily because so much of what we read every day in the newspaper pertaining to monetary policy appears to be couched in this language. Nevertheless, I choose to omit it for the following reasons. First, I am not a big fan of the approach (there are better ways, in my view, to investigate the key questions in monetary policy). Sticky prices and wages may be important at some level, but probably do not factor into the “big” economic questions. And I still do not know what an “inflation shock” is supposed to represent in reality. Second, there are already many textbooks out there that do an adequate job of explaining the approach, so that there is no need to repeat things here. On the other hand, I do take the time to take seriously some key Keynesian insights (Keynes was not a New-Keynesian). Contrary to what some may believe, the modern approach can be used to make precise Keynes’ notion of coordiation failure and animal spirits. In short, the modern approach does not preclude the possibility that macroeconomic stabilization policies are in some way desirable. Being explicit about the circumstances in which this may be the case, however, makes clear the assumptions required to generate the result (and the real world limitations that are likely to impinge on policymakers in designing their policies). At this stage, I would like to thank all my past students who had to suffer through preliminary versions of these notes. Their sharp comments have contributed to a much improved text. I would especially like to thank Sultan Orazbayez and Dana Delorme, both of whom have spent long hours documenting and correcting the typographical errors in earlier drafts. Thoughtful comments were also received from Bob Delorme, Janet Hua Jiang, and many others that are too numerous to mention here. Thank you all very much. David Andolfatto Burnaby, British Columbia December, 2007 CHAPTER 1 The Gross Domestic Product 1. Introduction The Gross Domestic Product (GDP) is an economic statistic that one hears quoted frequently in the news and elsewhere. But what exactly is this GDP thing supposed to measure? And why should anyone care about whether it is measured at all? Most people have at least a vague idea that the GDP represents some measure of ‘economic performance.’ One often hears, for example, that a country with a higher GDP is performing better than one with a lower GDP; or that a rapidly growing GDP is better than a stable, or declining GDP. This idea of the GDP as a measure of economic performance is held so widely and (at times) accepted so uncritically, that on these grounds alone, it probably deserves closer scrutiny. Before we can talk sensibly about GDP and why it might matter, we should have a clear understanding of how the term is defined and measured. Most countries in the world have a government agency (or agencies) responsible for collecting and aggregating measures of economic activity. You can find a list of these agencies at the following website (the United Nations Statistics Division): http://unstats.un.org/unsd/methods/inter-natlinks/sd_natstat.htm In Canada, our national statistical agency is called Statistics Canada.1 Among other things, Statistics Canada maintains a system of national Income and Expenditure Accounts (IEA). The following quote, taken from the Statistics Canada webpage, sums up their own (somewhat naive) view of the world: The Income and Expenditure Accounts are the centre of macroeconomic analysis and policy-making in Canada. They are a means by which Canadians can view and assess the performance of the national economy. The accounts provide both a planning framework for governments and a report card on the results of the plans that governments carry out. At the core of the Income and Expenditure Accounts (IEA) is the concept of Gross domestic product (GDP) and its components. 1 See: http://www.statcan.ca/ 1 The statement above makes clear that GDP is considered a core concept. So let’s take some time to investigate its measurement and potential usefulness. 2. Definition of GDP Here is a standard definition of GDP: GDP: The total value of final goods and services produced in the domestic economy over some given period of time. From this definition, we gather that the GDP represents some measure of the level of production in an economy. For this reason, the GDP is commonly referred to as output. Keep in mind that output constitutes a flow of goods and services. That is, it represents the value of what is produced over some given interval of time (e.g., a month, a quarter, or a year). Food, clothing, and shelter services produced over the course of a year all contribute to an economy’s annual GDP. Let us now examine the definition of GDP more carefully. Note first of all that the GDP measures the ‘value’ of output. We will discuss the concept of ‘value’ in some detail later on; but for now, assume that value is measured in units of ‘dollars’ (feel free to substitute your favorite currency). When output is measured in units of money, it is referred to as the nominal GDP (at current prices). Output takes the form of goods and services. What is the difference between a good and a service? A good is an object that can be held as inventory; while a service is an object that cannot be stored. Think of the difference between an orange and a haircut. Note that any good is likely valued only to the extent that it yields (or is expected to yield) a service flow; as when I consume that orange, for example. Next, note that the definition above makes reference to final goods and services. A final good is to be distinguished from an intermediate good. An intermediate good is an object that is produced and utilized as a input toward the production of some other good or service within the time period of consideration. An example may help clarify. Imagine that last year, an economy produced $200 of vegetables, $150 of fertilizer, $100 of bread, and $50 of flour. Imagine further that all of the fertilizer was used in the production of vegetables and all of the flour was used in the production of bread. One might be tempted to conclude that the annual GDP for this economy is $500, but this would be wrong. In fact, the GDP is equal to $200 + $100 = $300; that is, the total value of the final goods produced (bread and vegetables). The value of the intermediate goods is excluded from this calculation because their value is already embedded in the value of the final goods. That is, when you pay $2.00 for a bundle of 2 carrots at the supermarket, $1.50 represents the value of the fertilizer that was used to grow these carrots. The example above suggests an alternative (but equivalent) definition of GDP. Define value-added as the value of a good or service net of the cost of any intermediate inputs used to produce it. Then one can define the GDP as the total valued-added. In the context of the example above, we have $150 of fertilizer and $50 of flour (both of which use no intermediate inputs), together with the value added in the production of vegetables ($50) and bread ($50); the sum of which is $300. Moving along, observe that the definition above makes reference to the domestic product. The domestic product is to be distinguished from the national product; otherwise known as the Gross National Product (GNP). The difference is as follows. The GDP measures the value of output produced within the borders of a domestic economy, whether or not this production takes place with foreign-owned factors of production. The GNP, on the other hand, measures the value of output produced by the factors of production owned by the ‘citizens’ of a domestic economy, whether or not these factors of production reside on domestic soil or not. For countries like Canada and the United States, the difference between GDP and GNP is relatively small. For countries like Turkey and Mexico, on the other hand—with many citizens living and working abroad—the discrepancy between GDP and GNP can be significant. Finally, consider the term gross in the definition of GDP. Here, the gross domestic product is to be distinguished from the net domestic product (NDP). The NDP is defined as the GDP net of capital consumption. Capital consumption simply refers to the value of capital that is consumed (i.e., destroyed or depreciated) in the act of production. A case could be made that the NDP is a better measure of actual production. For example, if construction workers destroy $20,000 worth of equipment in the process of building a $100,000 house, most people would probably agree that $80,000 constitutes a better measure of the value added to the economy. Environmentalists are particularly fond of an NDP measure modified to include ‘environmental degradation’ and ‘resource depletion’ as components of capital depreciation. Exercise 1.1: Consider the example above, of an economy that produces $200 in vegetables, $150 in fertilizer, $100 in bread, and $50 in flour over the course of one year. As before, assume that the entire amount of fertilizer and flour is consumed in the process of producing vegetables and bread. But imagine now that the fertilizer and flour were not produced this year; that is, suppose that they were produced last year and brought over into this year as inventory (capital). Does the fertilizer and flour in this example fit the definition of an intermediate good? Compute the GDP and NDP for this economy. 3 3. Consumption vs. Investment Consider all the millions of goods and services produced in an economy over the course of some time interval. Economists have found it useful to divide this vast and heterogeneous flow of output into two categories: consumption goods (and services); and investment goods (and services). What are the distinguishing characteristics of these two types of output and why is it useful to make such a distinction? Consumption represents that part of the output flow that is consumed (i.e., destroyed) for the purpose of augmenting current material living standards. By ‘current,’ I mean over the course of a given time-interval, like one month or one year. Investment represents that part of the output flow that is destined to augment the future production of output (and ultimately, future material living standards). Investment is sometimes also referred to as the production of new capital goods and services. Note that new capital goods are to be distinguished from old capital goods—or, the stock of existing capital—which is presumably employed in the production of current output (along with other factors of production). Consumption: That branch of the output flow that is consumed (destroyed) for the purpose of augmenting current material living standards. One should keep in mind that the distinction between consumption and investment is not always so clear-cut; and in particular, the distinction may depend on the time-interval under consideration. Suppose, for example, that I hire the kid next door to mow my lawn one sunny afternoon. The kid’s labor (together with his lawnmower capital) is used to produce ‘lawn-enhancement services.’ I pay the kid $10 and let him have a sip of my beer (when his mother isn’t looking). Now, this $10 in lawn-enhancement services—does it constitute output in the form of consumption or investment? The answer depends on the time-interval under consideration. Imagine that the benefit I derive from the freshly-cut lawn lasts for one week (the lawn needs to be mowed again after this period of time). If the time-interval under consideration is one day, then one could well argue that the lawn-enhancement service constituted a form of investment that generated a flow of consumption for several periods (i.e., days). On the other hand, if the time-interval under consideration is one week (or more), then one might argue that the lawn-enhancement service simply constituted consumption (as the output depreciates fully after one week). Thus, one way to distinguish to between consumption and investment is to fix the time-interval under consideration and ask whether newly-produced output is expected to last longer than this time interval. If the answer is no, then the output constitutes consumption. If the answer is yes, then the output 4 constitutes a form of investment that augments the stock of existing capital (with capital generating a flow of future services). Investment: That branch of the output flow that augments the existing stock of capital. The most common time-intervals used in macroeconomic analysis are one quarter (3 months) and one year. With these time-intervals, a large class of goods and services can be clearly categorized as either consumption or investment. The construction of a new house, a new piece of machinery, a new car, for example, would seem to constitute new capital goods (additions to the existing stock of capital). The same could be said of many medical procedures (from hernia operations to breast implants) and education services (to the extent that students can be expected to hold on to what they have learned beyond the final exam). In contrast, the production of perishable food products, transportation services, haircuts, shelter services, etc., would seem to constitute consumption. However, there remain other forms of output that are not so easily classified; for these objects, a judgement call must be made. It is important to keep in mind that the term ‘investment’ as it is used here differs from the way it is commonly used in everyday language. Imagine, for example, that you are currently living in a rented apartment but decide to purchase a home. Most people would regard this purchase as an ‘investment’ in real estate. But whether this purchase is counted as investment in the IEA depends on whether the home you purchased is an old home or a new home. An old home is considered to be part of the existing (residential) capital stock. The purchase of an old home simply represents a change of ownership in the existing stock of capital and hence is not counted as investment for the economy as a whole. A new home, on the other hand, represents a new addition to the existing stock of residential capital; a new home is counted as investment for the economy as a whole. The IEA definition of investment generally differs from the way people commonly understand the term. Why is the distinction between consumption and investment important? This distinction is important because the manner in which an economy divides its output flow across consumption and investment ultimately determines the ‘long-run’ living standards of its inhabitants. Consider, for example, an economy consisting of farmers producing perishable food products year after year at some given level. This level of production determines living standards now and off into the indefinite future. Suppose now that some of these farmers become construction workers employed in the production of greenhouses and irrigation 5 systems. This diversion of labor necessarily entails a temporary decline in food production (and hence current living standards) as the new capital that is constructed takes time to be productive. But in the ‘long-run,’ the new capital has the effect of enhancing agricultural output and hence future living standards beyond the initial level. In this way, investment entails a sacrifice of current consumption in exchange for higher levels of future consumption. On the Concept and Measurement of Capital The term capital appears to mean different things to different people. To an economist, capital refers to a durable factor of production and inventory. It does not, in particular, refer to financial assets, which simply represent claims to future objects. The most obvious form of capital is what is called physical capital. Examples of physical capital include objects like machinery, computers, buildings, land, automobiles, highways, sewage systems, and inventories of goods. Even physical objects such as these are difficult to measure. For example, in measuring the stock of residential capital, is it appropriate to count the number of houses and apartments, or the square footage of living space? And is a 3000 square foot home made of brick the same thing as a 3000 square foot home made out of rice paper? Furthermore, how does one add together a house and a printing press to arrive at an aggregate measure of physical capital? In principle, perhaps the only way to measure capital consistently is by market value. In this way, we could say that a brick home valued at $400,000 and a printing press valued at $100,000 together make up $500,000 worth of capital. The ‘problem’ with this approach is that the value of capital may vary even without any change in its physical quantity. On the other hand, perhaps it makes sense to think of more valuable capital as constituting more ‘effective’ capital.2 In practice, it appears that the aggregate stock of physical capital is measured using a ‘perpetual inventory method.’ The way this is done is to take the investment flow (measured at market value) in each of various asset classes, applying a constant depreciation rate (that varies with asset class) and then adding the results across investment years and asset classes. A major problem with this method is that it values the existing capital stock at book value (historical market value of past investment) instead of current market value. Presumably, this is done because it is difficult to ascertain the current market value of all forms of capital. Unfortunately, the measurement of capital problem is in fact much worse than this. The reason for this lies in the fact that physical capital is not the only—or even most important—form of capital in an economy. One could reason 2 See, for example: Black, Fischer (1995), Exploring General Equilibrium, The MIT Press, London, England (pp. 31—34). 6 by analogy that every human being is a kind of durable machine. In a very real sense, each person can be thought of as an owner-operator of human capital that generates a (potential) stream of labor services over time. Like a machine or a house, we need to be maintained and (at times) repaired. In the IEA, maintenance and repair is considered a form of investment. In contrast, all personal expenditures on food, clothing, shelter and medical services are treated as consumption. Does this make sense? This is to say nothing about the investments that people make to improve their skill (again, education is treated as a form of consumption instead of investment), or the investments that parents make in raising their children. What is the value of human capital? In theory, the market value of a person’s human capital is the present value of one’s lifetime wage stream net of the present value of any direct investments in human capital (the same principle holds for the valuation of any form of capital). In practice, direct claims on human capital are rarely exchanged in markets, making the value of human capital more difficult (but not impossible) to estimate. Another important form of ‘intangible’ capital exists in the form of (disembodied) technology. The modifier ‘disembodied’ here is used in reference to ‘knowledge’ or ‘technological know-how’ that exists separately from what may be embodied in either physical or human capital. Some examples that come to mind here may include things like ‘organizational capital’ (the way production activities and distribution networks are organized, or other ‘best-practice’ techniques), or even the introduction of new products (e.g., the sudden availability of computers is not the same thing as having more factory space). As you may have guessed, the value of these ‘intangible’ objects is often difficult to measure. Nevertheless, this does not diminish their potential importance. Firms can and do spend significant resources toward ‘figuring things out.’ The most obvious example is R&D expenditure. R&D spending is clearly a form of investment, even if the value of what is produced by such spending is difficult to measure. But for some strange reason, R&D spending (and other forms of investment in ‘intangible’ capital) is not counted as investment in the IEA. It is, however, counted as part of the GDP. Implicitly then, R&D spending is counted as form of consumption. The upshot of all this is that the IEA essentially ignores human and intangible capital, so that care must be exercised in interpreting the measured stock of capital as the true stock of productive capital. Likewise, one must be careful in interpreting measured investment as reflecting the true level of investment in an economy (e.g., see Figure 1.1). 7 Figure 1.1 8 4. How the GDP is Calculated Statistics are a lot like sausages: both are best enjoyed when one does not see how they are made. As the son of Italian immigrants, I have had the pleasure of participating in the process of sausage-making from the ground up (including the initial slaughter). Believe me, this is an experience you can definitely afford to miss (I have never looked at my breakfast sausage in quite the same way ever since). And while I have never worked at a statistical agency, I have friends who have. From what I can gather, they now view ‘official statistics’ much in the same way I view my breakfast sausage. The IEA report two measures of GDP, both of which should add up to the same number in theory (but in practice differ by a relatively small number called a ‘statistical discrepancy’). These two measures are based on two different approaches: an income approach, and an expenditure approach. Below, I discuss each approach in turn. The Expenditure Approach The expenditure approach to computing the GDP relies on the following fact: Everything that is produced must also be purchased. At first blush, this might seem like a strange thing to assert. What if, for example, a manufacturer produces an automobile that is not delivered to a dealer? In this case, the newly produced automobile is treated as a purchase of inventory by the manufacturer. The value of this inventory investment is based on the market price of the automobile (i.e., the market value of similar automobiles that are sold on the market). Thus, the expenditure approach calculates GDP as the total spending on all domestically-produced final goods and services. The GDP calculated in this manner is sometimes referred to as the Gross Domestic Expenditure (GDE). Mathematically, this is done as follows. Let xit denote the quantity of good (or service) i that is sold at date t at market-price pit . Then the value of this expenditure (measured in dollars) is simply pit xit . If there are Q such goods and services, then the GDE is given by: GDEt ≡ Q X pit xit . (1) i=1 Again, note that expenditures on intermediate goods and services are not included in this calculation (why not?).3 3 The notation x ≡ y means that x is equivalent (or by definition ) equal to y. Note that 9 Actually, this is not quite how it’s done. The way it is done in practice is to first compute total spending on all (newly produced) final goods and services, whether or not they are domestically produced. Of course, this figure will include expenditures on imports, which are goods and services that are not produced domestically. To arrive at the GDE then, one must subtract from this figure the total value of all imported goods and services. Largely as the result of an historical accident, the national income and product accounts organize the expenditure components of the GDP into four broad categories that depend on the sector in which the expenditure is undertaken. This classification is somewhat arbitrary in that there is no unique way in which to define ‘sector.’ Nevertheless, the way this is done in practice is to define four sectors as follows: [1] the household sector; [2] the business sector; [3] the government sector; and [4] the foreign sector. Sometimes, [1] and [2] are combined to form the domestic private sector. The government sector includes all levels of government (i.e., federal, provincial, state, local, etc.). The foreign sector includes both foreign private and government agencies. Having defined sectors in this way, let Ht denote household spending; let Bt denote business spending; let Gt denote government spending; and let Xt denote foreign sector spending (on domestically-produced goods and services). As the spending on Ht , Bt and Gt includes imports, we have to subtract off the value of these imports Mt to calculate spending on domestically-produced output. Using these expenditure categories, the GDE may equivalently be calculated as: GDEt ≡ Ht + Bt + Gt + Xt − Mt . (2) Since this is probably not your first macro class, you’ve likely seen something similar to (2) before. It doesn’t quite look right though, does it? This is because every macroeconomics textbook in existence (that I am aware of) uses slightly different notation; and instead writes (2) in the following way: GDEt ≡ Ct + It + Gt + Xt − Mt . (3) Obviously, (2) and (3) are equivalent if we define Ct ≡ Ht and It ≡ Bt . There is nothing wrong in using whatever notation we wish, as long as the notation does not detract from clear thinking. Unfortunately, the widely-used notation in (3) does at times appear to detract from clear thinking. Let me explain. Get your hands on any macro text currently on the market and flip to the section on national income accounting. Now look for the expenditure identity (3). In the discussion that surrounds this identity, you will invariably find statements asserting that Ct denotes consumption expenditure and It denotes investment expenditure. These statements are misleading (a product of bad notation) because Ct in fact represents household this is not the same as stating x = y. The latter is an equation while the former is an identity. For example, if x denotes ‘supply’ and y denotes ‘demand,’ then it is not true that x ≡ y. However, it is true that x = y at a market-clearing price. 10 sector spending on both consumption and investment (in the form of durables and human capital investments) and It represents only one component of investment (i.e., each of Ct , Gt and Xt also include expenditures on investment goods and services). Table 1.1 provides the expenditure components of GDP based on (2) for Canada. A number of observations are in order here. First, as remarked earlier, note that one should refrain from interpreting the subtotal C as consumption. That is, a significant component of household expenditures on goods are in the form of durable and semi-durable goods. Furthermore, one can guess that a significant component of the purchase of services is also in the form of investment services (broadly defined). Second, again as remarked earlier, note that the IEA only appears to count business sector spending I in the form of additions to physical capital (and not any investments in intangible capital). Third, note that a portion of government purchases G is in the form of new capital goods. It is probably the case, however, that some of the spending categorized as ‘current’ goods and services might be better labelled as investment. Fourth, note that expenditures on exports X generally consist of both consumption and investment goods and services. Table 1.1 Gross Domestic Product: Expenditure-Based Canada 2005 (millions of dollars) Household Sector Durable and semi-durable goods Non-durable goods Services Subtotal (C) Business Sector Residential structures Non-residential structures Machinery and equipment Inventory investment Subtotal (I) Government Sector Current goods and services Investment Subtotal (G) Foreign Sector Exports of goods Exports of services Subtotal (X) Imports of goods Imports of services Deduct: Subtotal (M ) Gross Domestic Expenditure Source: Statistics Canada, CANSIM table 380-0017. 11 164,815 189,213 407,934 761,962 89,595 63,938 91,354 9,469 254,356 262,369 35,156 297,525 443,401 64,855 518,256 386,749 77,281 464,030 1,368,069 Exercise 1.2: Can you think of an example of an individual who might belong to (i.e., makes purchases that would be reflected in) each of the four sectors described in Table 1.1? The Income Approach The income approach to computing the GDP relies on the following fact: Every purchase of a good or service must constitute income to the agent (or agency) selling it. The GDP calculated in this manner is sometimes referred to as the Gross Domestic Income (GDI). In principle, this can be done in any one of a number of ways. The most obvious way to calculate aggregate income would be to define an individual (or household) as the basic economic unit. In general, each individual has multiple sources of income, including income on domestically-employed human capital w (wages), income on domestically-employed capital d (dividends, retained earnings, interest income on bonds), and income on assets employed in the foreign sector, f (this could include wages earned outside of the country). In the computation of GDP, this latter source of income is left out (although, it is included in the measure of GNP). Thus, if there are N domestic residents, one could compute: N X GDIt ≡ (wit + dit ). (4) i=1 Note that taxes and transfers to and from the government are not included in this measure. Why is this? Let’s think about it. Suppose that the government collects taxes τ it from individual i. Note that this tax measure includes taxes from all sources, including sales taxes, property taxes, and income taxes (including corporate income, at least, on that fraction of the domestic business sector owned by domestic residents). What does the government do with these taxes? It uses them to pay the wages and salaries of government sector employees, which shows up in wjt for some government worker j. It also uses these taxes to make transfers to individuals in the economy. Note that these transfers do not count toward the GDP as they do not constitute any production of new good or service (they serve simply to redistribute output across members of society). Nevertheless, you should keep the following in mind: The fact that government transfers are not counted in the measure of GDP does not imply that government transfer programs have no effect on GDP. When one computes the GDP in this manner, it is interesting to note that most of the income generated in the economy accrues to human capital. For many economies, the income share of human capital ranges between 65—75%. 12 Naturally, this common-sense way of reporting income is not the way the IEA typically does things. Instead, the IEA reports the breakdown in income according to Table 1.2: Table 1.2 Gross Domestic Product: Income-Based Canada 2005 (millions of dollars) Wages and Salaries Corporate Profits (before tax) Government Business Enterprises (before tax) Net Interest Income Net Income (farm) Net Income (unincorporated farm) Inventory Valuation Adjustment Taxes less subsidies on factors of production NDP (at factor cost) Taxes less subsidies on products Capital Cost Allowance Gross Domestic Income 678,925 193,936 13,370 61,240 1,551 84,666 —442 59,961 1,093,207 94,750 181,427 1,369,384 Source: Statistics Canada, CANSIM table 380-0001. As you can see from Table 1.2, it is somewhat cryptic (not to mention, amusing). Let’s try to figure out what’s going on here. First, I am guessing that wages and salaries refers to wage income net of taxes. The reason I believe this is because there is also a category called taxes less subsidies on factors of production. Presumably, factors of production here refers only to human capital, as I notice that the income generated by the physical capital owned by the business and government sectors is reported on an after-tax basis. Note that corporate profits include earnings that are both retained and distributed as dividends, and is net of depreciation costs (which is why the capital cost allowance is added later on). There is an issue here as to how the income of unincorporated (non-farm) businesses is treated. Presumably, this is just lumped in with wages and salaries, although properly speaking, at least a part of this should actually be recorded as capital income. It is rather amusing to see that there are separate categories for the farm sector (why?). Presumably, the net income from farms represents capital income. However, the net income of unincorporated farms includes both wage income and capital income (no attempt is made to separate out these components). The NDP represents the net (of depreciation) domestic production. At factor cost means that the incomes were calculated net of ‘indirect’ taxes (like sales taxes). Thus, to compute the GDP, both capital consumption and indirect taxes must be added to the NDP figure. The Income-Expenditure Identity 13 So far, we have established that GDP ≡ GDI and GDP ≡ GDE. From these two equivalence relations, it follows that GDE ≡ GDI. In other words, aggregate expenditure is equivalent to aggregate income, each of which are equivalent to the value of aggregate production. Again, the way to understand why this must be true is as follows. First, any output that is produced must also be purchased (additions to inventory are treated purchases of new capital goods, or investment spending). Hence the value of production must (by definition) be equal to the value of spending. Second, since spending by one individual constitutes income for someone else, total spending must (by definition) be equal to total income. The identity GDI ≡ GDE is sometimes referred to as the income-expenditure identity. Letting Y denote the GDI, most introductory macroeconomic textbooks express the income-expenditure identity in the following way: Y ≡ C + I + G + X − M. (5) Note that since the income-expenditure identity is an identity, it always holds true. A natural inclination is to suppose that since the identity is always true, one can use it to make theoretical or predictive statements. For example, the identity seems to suggest that an expansionary fiscal policy (an increase in G) must necessarily result in an increase in GDP (an increase in Y ). In fact, the income-expenditure identity implies no such thing. The Income-Expenditure Identity does not imply that an increase in G leads to an increase in Y. To understand why this is the case, what one must recognize is that an identity is not a theory about the way the world works. In particular, the income-expenditure identity is nothing more than a description of the world; i.e., it is simply categorizes GDP into to its expenditure components and then exploits the fact that total expenditure is by construction equivalent to total income. To make predictions or offer interpretations of the data, one must necessarily employ some type of theory. As we shall see later on, an increase in G may or may not lead to an increase in Y , depending on circumstances. But whether or not Y is predicted to rise or fall, the income-expenditure identity will always hold true. 5. Other Measurement Issues We’ve already talked a bit about some of the measurement problems concerning the classification of output into its consumption and investment components. That discussion, however, was predicated on the assumption that the concept 14 of ‘output’ was well-defined and consistently measured. As we dig deeper into the sausage-making machinery, however, we find that both of these assumptions need to be viewed with caution. From the definition of GDP, we know—in principle, at least—that the GDP is supposed to represent some measure of the ‘value’ of what an economy produces in the way of (final) goods and services; or ‘output,’ for short. The easiest and most consistent way of aggregating the value of different goods (or factors of production) is by adding up their values on the basis of market prices—which are usually denominated in units of the national currency. Of course, such an exercise first presumes the existence of markets for different forms of output and factors of production; and second, presumes that prices and the quantities exchanged in these markets are somehow observable to national statistical agencies. One might suppose that in the so-called developed world, that there a sufficient number of markets to price most forms of goods and services. But even in this best-case scenario, statisticians are confronted with a number of conceptual and practical problems. The Government Consider, for example, government ‘purchases’ of output. Some of this output is purchased from the private sector (e.g., military purchases from private defense contractors). But a large component of government ‘purchases’ is in the form of output that it produces itself and then transfers to the private sector at zero (or close to zero) prices; e.g., medical services, law enforcement services, education services, etc. How does one measure the market value of services such as these that are not sold on markets? Since market prices do exist for private medical care and private education, one approach would involve trying to impute the value of this government production using the market prices of close substitutes available in the private sector. This method of imputation may not available for a large class of nonmarketed goods and services, however (e.g., what is the market value of the services provided by the court system)? In practice, the way this is handled by the IEA is simply to assume that the market value of government production is equal to its factor cost. For example, if a judge is paid $150,000 per annum by the government, then this $150,000 figure is assumed to be the market value of the judicial services produced by the judge’s labor input. This method of imputing the market value of government production may not be a bad approximation at most times and for most countries. Nevertheless, one should be aware of the potential pitfalls with this method. To see what can go wrong, consider the following stark example. Imagine an economy in which labor is the only factor of production and assume that workers are either employed in the private or government sector. The private sector produces 15 and sells (at market prices) output Yp at the wage cost Wp , which yields profit Πp = Yp − Wp . The government produces output Yg at the wage cost Wg and simply ‘gives’ Yg away, financing its wage bill with a tax T. Using conventional IEA methods, the imputed value of government production is calculated as Yg = Wg . Calculating GDP by the expenditure approach in this economy would yield GDE = Yp + Yg . Calculating GDP by the income approach would yield GDI = Wp + Πp + Wg . You should be able to convince yourself that GDE = GDI. Now, imagine in fact that the market value of Yg is zero; that is, government production is considered to be a complete waste. In this case, the true GDP in this economy is given by Yp . However, the measured GDP continues to be Yp +Yg . In this case, government production should in fact be counted as a transfer of resources (from private sector employees to government sector employees); it should not be counted as adding value to the economy as a whole. Note that this type of problem is absent in computing the GDP generated by the private sector. Suppose, for example, that the business sector makes a ‘mistake’ in producing output that nobody values. In this case, the market value of Yp is equal to zero. The expenditure-based GDP number is now given by Yg ; and the income-based GDP number is now given by Wp +Πp +Wg . Since Yp = 0, the business sector now makes a loss (negative profits) equal to Πp = −Wp < 0. Hence, GDI = Wg and GDE = Yg , with GDI = GDE measuring the true value-added in this economy. Home Production Time-use studies reveal that out of the total amount of time available to individuals, only a relatively small fraction of this is devoted toward activities that produce goods and services that are sold in markets (or given away by governments). In other words, there is likely a significant amount of time (labor) devoted toward activities that generate home production, defined to be goods and services that are produced and consumed (or invested) within a household (and hence, not exchanged on any market). In addition to labor, households also generally have available a stock of capital that is likewise employed in home production (e.g., owner-occupied housing and consumer durables). To see what sort of issues arise here, consider the following examples. Imagine that you own a house that you rent out at $1500 per month. Then this $1500 is counted toward the GDP, since it constitutes capital income for you (and generates $1500 per month worth of shelter services, which is consumed by your tenants). Imagine now that you decide to move into this home. Then you no longer report $1500 in rental income on your tax return. However, it still remains the case that the home is generating $1500 worth of shelter services that are now consumed by yourself. Consistency demands that the IEA impute the market value of these shelter services as valued-added. In fact, this is what 16 many statistical agencies do. In practice, however, statistical agencies often treat the valuation of home production inconsistently. Consider, for example, what happens if you own and operate an automobile. Your purchase of the automobile is recorded as an expenditure on a consumer durable. This durable good generates a flow of transportation services, the value of which should be recorded as valued-added. In fact, this is typically not the case. In contrast, if a taxi company purchases the same automobile, it is treated as investment and the revenue the taxi company earns from this asset is recorded as capital income. Similarly, consider two households, one of which is ‘traditional,’ and the other which is ‘modern.’ By a traditional household, I mean one in which the father goes to work and spends a considerable amount of time around the home engaged in activities like mowing the lawn, cleaning the gutters, painting the house, repairing his automobile, etc. As well, the mother stays at home, raising the kids, cooking meals, cleaning the house, etc. By a modern household, I mean one in which both parents are employed and contract out extensively for services that ‘self-produced’ by a traditional family (e.g., they hire a nanny to cook, clean, and look after the kids; they hire contractors to effect home renovations, car repairs, and maintain the home, etc.). Imagine that the two households described above are more or less similar in age structure, number of kids, education level of the parents, and other attributes. Then the true valued-added generated by each household is likely to be similar. But the measured value-added of the modern household is likely to be much higher, as many of its time-use activities are formally exchanged on markets (together with the fact that the IEA does not impute a value to household production in the form of raising kids, home maintenance, etc.). The simple example described above warns us to be careful in interpreting time-series evidence of the growth in GDP as reflecting an increased level of production. In particular, to the extent that ‘household structure’ changes over time (from traditional to modern), much of the growth in GDP may simply reflect a measurement phenomenon (rather than reflecting true growth in production). A similar caveat is in order when one is making cross-country comparisons of GDP, especially between developed and underdeveloped countries. Much of the output that is produced in underdeveloped countries is likely to take the form of home production and hence not counted toward official GDP measures. Exercise 1.3: According to this website: www.globalissues.org/ TradeRelated/ Facts.asp, half the world (nearly 3 billion people) manage to live on less than $2 a day. While these unfortunate souls are undoubtedly poor by any measure, explain why the $2 a day figure likely overstates the true extent of their poverty. One might argue that conceptually, the GDP should measure the market value of ‘marketable’ output, even if it is not actually ‘marketed.’ That is, if 17 I decide to clean the gutters of my home one fall morning, the IEA should (in principle) count this cleaning service toward the GDP. While I did not market out for this service, it is clearly a service that I could have contracted out for. This then raises the question of whether there are goods or services that are ‘non-marketable.’ In fact, one could argue that there are. An immediate example that comes to mind is sleep. One can produce and consume sleep and individuals clearly value sleep (a minimum amount of which is necessary to maintain the health of one’s human capital). It is impossible, however, to contract out for sleep services; i.e., I cannot get someone to sleep for me. The same might be said of learning. You cannot get someone to learn the contents of this text for you. Most forms of leisure activities appear to be non-marketable as well; e.g., having someone take a vacation on my behalf just doesn’t seem right. Of course, one could—in principle, at least—attempt to impute a market value for non-marketable production as well. For example, the value of the time one spends producing leisure could be valued at the opportunity cost of this time (i.e., the wage that is foregone by consuming time in the form of leisure). For better or worse, the production/consumption of leisure is not viewed as contributing to GDP (even conceptually). Since people obviously do value leisure, however, the GDP cannot be considered the sole determinant of what determines individual well-being. The Underground Economy The underground economy refers to economic activity that is beyond the scope of government regulation and measurement. Underground activity typically takes place in well-defined markets, so that it is relatively easy to measure the market prices goods and services transacted in these markets. It is more difficult—if not impossible—however, to measure the volume of transactions, since they are purposely hidden. Underground activities may either be legal or illegal. If they are legal, they are hidden primarily for the purpose of evading taxes. For example, if you would like drywall installed in your basement, a drywall contractor may offer you two prices depending on whether you are willing to pay by cash or cheque (you will get a cheaper price if you pay with cash). If they are illegal, they are obviously hidden to avoid legal ramifications. In some jurisdictions, for example, purchasing and selling sex and certain forms of drugs is illegal. By their very nature, underground economies are difficult to measure, so that any estimate of their size is necessarily imprecise. Nevertheless, some estimates do exist. According to one Economist Magazine article, for example, the underground economy in Italy is estimated to be between !5-27% of (measured) GDP.4 According to this article, underground businesses are widespread 4 www.economist.com/countries/Italy/profile.cfm?folder=Profile-Economic%20Structure 18 in agriculture, construction and services. Once again, the presence of such unmeasured output should lead us to view official GDP numbers with a fair amount of caution as they likely understate the true value of production by a considerable margin. On the other hand, while the level of GDP may be understated, its growth rate may not be—at least, to the extent that underground (and other unmeasured) activity remains a relatively constant proportion of measured activity. Likewise, cross-country comparisons of GDP are likely to be more meaningful if the set of measured activities is more or less the same. We have no a priori reason, however, to believe that either of these conditions are met in reality. Exercise 1.4: Imagine that a government suddenly enacts into legislation an oppressive tax regime on its citizens (e.g., a 100% tax on all income). Explain why the economy’s measured GDP is likely to fall by much more than the true level of GDP. 6. Nominal versus Real GDP GDP was defined above as the value of output (income or expenditure). The definition did not, however, specify in which units ‘value’ is to be measured. In everyday life, the value of goods and services is usually stated in terms of market prices measured in units of the national currency (e.g., Canadian dollars). For example, the dozen bottles of beer you drank at last night’s student social cost you $36 (and possibly a hangover). The 30 hours you worked last week cost your employer $300; and so on. If we add up incomes and expenditures in this manner, we arrive at a GDP figure measured in units of money; this measure is called the nominal GDP. If market prices (including nominal exchange rates) remained constant over time, then the nominal GDP would make comparisons of GDP across time and countries an easy task (subject to the caveats outlined above). Unfortunately, as far as measurement issues are concerned, market prices do not remain constant over time. So why is this a problem? The value of either income or expenditure is measured as the product of prices (measured in units of money) and quantities. It seems reasonable to suppose that material living standards are somehow related to quantities; and not the value of these quantities measured in money terms. In most economies (with some notable exceptions), the general level of prices tends to grow over time; such a phenomenon is known as inflation. When inflation is a feature of the economic environment, the nominal GDP will rise even if the quantities of production remain unchanged over time. For example, consider an economy that produces nothing but bread and that year after year, bread production is equal to 100 loaves. Suppose that the price of bread ten years ago was equal 19 to $1.00 per loaf, so that the nominal GDP then was equal to $100. Suppose further that the price of bread has risen by 10% per annum over the last ten years. The nominal GDP after ten years is then given by (1.10)10 ($100) = $260. Observe that while the nominal GDP is 2.6 times higher than it was ten years ago, the ‘real’ GDP (the stuff that people presumably care about) has remained constant over time. Thus, while measuring value in units of money is convenient, it is also problematic as far as measuring material living standards. But if we can no longer rely on market prices denominated in money to give us a common unit of measurement, then how are we to measure the value of an economy’s output? If an economy simply produced one type of good (as in our example above), then the answer is simple: Measure value in units of the good produced (e.g., 100 loaves of bread). In reality, however, economies typically produce a wide assortment of goods and services. It would make little sense to simply add up the level of individual quantities produced; for example, 100 loaves of bread, plus 3 tractors, and 12 haircuts does not add up to anything that we can make sense of. So we return to the question of how to measure ‘value.’ As it turns out, there is no unique way to measure value. How one chooses to measure things depends on the type of ‘ruler’ one applies to the measurement. For example, consider the distance between New York and Paris. How does one measure distance? In the United States, long distances are measured in ‘miles.’ The distance between New York and Paris is 3635 miles. In France, long distances are measured in ‘kilometers’. The distance between Paris and New York is 5851 kilometers. Thankfully, there is a fixed ‘exchange rate’ between kilometers and miles (1 mile is approximately 1.6 kilometers), so that both measures provide the same information. Just as importantly, there is a fixed exchange rate between miles across time (one mile ten years ago is the same as one mile today). The phenomenon of inflation (or deflation) distorts the length of our measuring instrument (money) over time. Returning to our distance analogy, imagine that the government decides to increase the distance in a mile by 10% per year. While the distance between New York and Paris is currently 3635 miles, after ten years this distance will have grown to (1.10)10 (3635) = 9451 miles. Clearly, the increase in distance here is just an illusion (the ‘real’ distance has remained constant over time). Similarly, when there is an inflation, growth in the nominal GDP will give the illusion of rising living standards, even if ‘real’ living standards remain constant over time. There are a number of different ways in which to deal with the measurement issues introduced by inflation. Here, I describe one approach that is commonly adopted by statistical agencies. Following the discussion surrounding the expenditure-based GDP measure, we have GDP given by (1); which I reproduce here for convenience: Q X GDEt ≡ pit xit . i=1 20 As this measure relies on current (i.e., date t) prices (whether actual or imputed), it is sometimes referred to as the GDP measured at current prices; or simply, the nominal GDP. Now, choose one year arbitrarily (e.g., t = 1997) and call this the base year. Then, the real GDP (RGDP) for any year t is calculated according to the following formula: Q X RGDPt ≡ pi1997 xit . i=1 This measure is called the GDP measured at base year prices. In other words, the value of the GDP at date t is now measured in units of 1997 dollars (instead of current, or date t dollars). Note that by construction, RGDP1997 ≡ GDE1997 . Figure 1.2 Nominal vs. Real GDP Canada 1961-2005 1400 Billions of CDN $ per annum 1200 1000 800 600 Real GDP 400 200 Base Year 1997 Nominal GDP 0 65 70 75 80 85 90 95 00 05 Source: CANSIM II; series V3860085 (real GDP); V646937 (nominal GDP). As a by-product of this calculation, one can calculate the average level of prices (technically, the GDP Deflator or simply, the price level) Pt according to the formula: GDEt Pt ≡ . RGDPt 21 Figure 1.3 GDP Deflator (1997 = 1) Canada 1961-2005 1.2 1.0 0.8 0.6 0.4 Base Year 1997 0.2 0.0 65 70 75 80 85 90 95 00 05 Note that the GDP deflator is simply an index number; i.e., it has no economic meaning (in particular, note that P1997 = 1 by construction). Nevertheless, the GDP deflator is useful for making comparisons in the price level across time. That is, even if P1997 = 1 and P1998 = 1.10 individually have no meaning, we can still compare these two numbers to make the statement that the ‘average’ level of prices rose by 10% between the years 1997 and 1998. The methodology just described above is not fool-proof. In particular, the procedure of using base year prices to compute a measure of real GDP assumes that the structure of relative prices remains constant over time. To the extent that this is not true (it most certainly is not), then measures of the growth rate in real GDP can depend on the arbitrary choice of the base year.5 Finally, it should be noted that making cross-country comparisons is complicated by the fact that nominal exchange rates tend to fluctuate over time as well. In principle, one can correct for variation in the exchange rate, but how well this is accomplished in practice remains an open question. Real per capita GDP In general, the real GDP of any economy may rise (or fall) owing to: [1] a 5 Some statistical agencies have introduced various ‘chain-weighting’ procedures to mitigate this problem. 22 rise (or fall) in population; and/or [2] a rise (or fall) in the output produced per person. To get a sense of how material living standards for the ‘average’ person in an economy, it makes sense to divide an economy’s total real GDP by population size. The resulting number is called the real per capita GDP; or more commonly, the real per capita income. It cannot be stressed enough that extreme caution should be exercised in interpreting real per capita GDP as a measure of material living standards or as a measure of economic welfare. First, one should keep in mind all of the measurement issues discussed at length above. Second, as far as material living standards are concerned, theory suggests that consumption is likely to constitute a better measure (or perhaps even wealth, to the extent that consumption is related to wealth). One would not want to judge the material living standards of a student with zero income, for example, solely on the basis of his or her income. Finally, there is good reason to believe that economic welfare depends not only on one’s consumption flow, but also on other things (e.g., leisure time spent with one’s family and friends).6 With the appropriate caveats in place, let us examine the behavior of real per capita GDP for Canada. Figure 1.4 plots the evolution of Canada’s population and Figure 1.5 plots the real per capita GDP. 6 For an interesting discussion on the history of work and leisure, see: Hill, Roger B. (1999). History of Work Ethic, www.coe.uga.edu/~rhill/workethic/hist.htm 23 Figure 1.4 Population of Canada 1961:1 - 2005:1 36 Millions of Persons 32 28 24 20 16 65 70 75 80 85 90 95 00 05 00 05 Source: Statistics Canada, table 510005 Figure 1.5 Real per capita GDP Canada 1961:1 - 2005:1 36000 32000 1997 CDN $ 28000 24000 Recession 1990:1 - 1992:4 20000 Recession 1981:2 - 1982:4 16000 12000 65 70 75 80 85 90 95 Source: CANSIM II, Series V1992067 (divided by population). 24 7. Growth and Business Cycles The pattern of economic development displayed in Figure 1.5 for Canada is typical among many countries, especially for those that occupy the so-called ‘developed world.’ The most striking feature of Figure 1.5 is the trend rate of growth in real per capita income. In 1961, income per capita was approximately $13,100. By the end of the sample in 2005, income per capita had grown by a factor of 2.7 (to $35,600). This represents an average annual growth of approximately 2.2%. Now, 2.2% may not sound like a large number to you. And you may be tempted into thinking that it really does not matter very much whether an economy grows at 1.2%, 2.2%, or 3.2%. In fact, even seemingly small differences in long-run growth rates such as these can translate into huge differences in the level of income over time. The reason for this lies in the power of compound interest. To appreciate the power of compound interest, imagine that there are three economies A, B, and C that are currently generating $10,000 in per capita income. Economy A grows at g = 1.2%, economy B at g = 2.2%, and economy C at g = 3.2% per annum. What will be the level of per capita income at the end of 20 years? The answer is provided in Table 1.3. Table 1.3: Power of Compound Interest Economy A (g = 1.2) Economy B (g = 2.2) Economy C (g = 3.2) Initial GDP GDP after 20 years Change $10,000 $10,000 $10,000 $12,694 $15,453 $18,776 27% 55% 88% A useful formula to keep in mind is the so-called Rule of 72. This rule states that if an economy grows at a rate of g% per annum, then the number of years it takes to double income is given by n: n= 72 . g (6) Thus, an economy that grows at 2% per annum will increase its living standards by 100% in 36 years. An economy that grows at 4% per annum will double its living standards in only 18 years. 25 Any factor (including government policy) that may affect an economy’s long-run growth rate by even a small amount can ultimately result in very large differences in living standards over prolonged periods of time. Since our current high living standards depend in large part on past growth, and since our future living standards (and those of our children) will depend on current and future growth rates, understanding the phenomenon of growth is of primary importance. The branch of macroeconomics concerned with the issue of long-run growth is called growth theory. A closely related branch of macroeconomics, which is concerned primarily with explaining the level and growth of incomes across countries, is called development theory. Traditionally, macroeconomics has concerned itself more with the issue of ‘short run’ growth, or what is usually termed the business cycle. The business cycle refers to the cyclical fluctuations in GDP around its ‘trend,’ where trend may defined either in terms of levels or growth rates. From Figure 1.5, we see that while per capita GDP tends to rise over long periods of time (at least, in Canada and some other countries), the rate of growth over short periods of time can fluctuate substantially. In fact, there appear to be (relatively brief) periods of time when the real GDP actually falls (i.e., the growth rate is negative). When the real GDP falls for two or more consecutive quarters (six months), the economy is said to be in recession (i.e., the shaded regions in Figure 1.5). It is important to keep in mind that while it is tempting to dichotomize a pattern of economic development like Figure 1.5 into its ‘trend’ and ‘cycle’ components, there is in fact no a priori reason to believe that such a decomposition makes any sense theoretically (although, one could certainly perform such a decomposition statistically). Because what I’ve said here is important and not widely appreciated, let me elaborate. When viewing a diagram like Figure 1.5, the natural inclination is to draw a smooth line through the data and interpret this as ‘trend.’ The difference between the actual data and the trend line is then interpreted as ‘cycle.’ Unfortunately, there is no unique or obvious way to detrend time-series data. In Figures 1.6, I display the trend and cycle components of Canadian GDP using one particular method (a cubic trend). 26 Figure 1.6 Real per capita GDP Cubic Trend and Cycle Canada 1961:1 - 2005:1 10.6 Deviation from Cubic Trend Real per capita GDP (log) Cubic Trend 10.4 10.2 10.0 .08 9.8 .04 9.6 .00 9.4 -.04 -.08 -.12 65 70 75 80 85 90 95 00 05 There is nothing inherently wrong in detrending time-series data. The mistake that people commonly make, however, is to assume a smooth trend line— estimated on historical data—actually represents a trend that can be expected to prevail into the foreseeable future. To put things another way, people commonly make the mistake of assuming that a smooth trend line represents something ‘real’ or ‘fundamental’ about the way an economy functions. In fact, a smooth trend line may be nothing more than a statistical illusion. To make what I am saying more concrete, consider the following argument. Let yt denote the (log) real per capita GDP and assume that you and I know underlying data generating process (DGP) for the economy. Imagine further that this DGP is given by: yt+1 = γ + yt + et+1 , (7) where et+1 is a random variable, representing an unforecastable ‘shock’ to the economy’s GDP. We can assume that et+1 takes one of two values, each of which is determined by the flip of a coin. Or, to be slightly more sophisticated, we can assume that et+1 is determined by a draw from a Normal distribution with mean μ and standard deviation σ. If we set μ = 0, then the expected value of et+1 as of date t is given by Et et+1 = 0. In fact, the expected value of et+j for any j = 1, 2, 3, ... is given by Et et+j = 0. The DGP in (7) is an example of what is called a random walk with drift. The ‘drift’ parameter γ represents the expected rate of growth of (log) GDP. We 27 can simulate an equation like (7) by assigning parameter values and generating the ‘shocks’ et using a random number generator. Suppose, for example, that we set y1961:1 = 9.48 (its value for the Canadian economy in 1961). Let γ = 0.0055 (which generates an annual expected growth rate of 2.2%. As well, choose a standard deviation σ = 0.015. Figure 1.7 displays two simulated time-series for yt (along with the actual Canadian data). One thing that should strike you from viewing Figure 1.7 is how the simulated series resemble the actual data; in fact, it would be very hard to tell (without knowing beforehand) which series was generated by our model (7) and which was generated by the economy. Figure 1.7 Log GDP: Actual and Simulated 10.8 10.6 log scale 10.4 10.2 10.0 9.8 Canadian Data Simulation 1 Simulation 2 9.6 9.4 65 70 75 80 85 90 95 00 05 Now, imagine that we handed our simulated data to an econometrician and asked him or her to estimate a smooth trend line the way that was done in Figure 1.6. One could certainly do this; and we would be left with a diagram similar to Figure 1.6. But does the estimated trend line represent anything ‘fundamental’ about the manner in which our model economy functions? In particular, is there any reason to believe that future GDP levels will revert back to the estimated trend line? Can we use the estimated trend line to forecast the future level of GDP? The answers to these questions is no. The reasons for why we can be so certain of this are twofold: [1] unlike the econometrician, we know the true DGP generating our simulated series; and [2] 28 given that we know the true DGP, we can compute the theoretical trend and show that does not correspond to a smooth line. The theoretical (i.e., true) trend behavior displayed by our model economy can be calculated as follows. Using (7), we can deduce that: yt+2 = γ + yt+1 + et+2 ; = 2γ + yt + et+1 + et+2 . Similarly, yt+3 = γ + yt+2 + et+3 ; = 3γ + yt + et+1 + et+2 + et+3 . Continuing on in this way, we have: yt+n = nγ + yt + et+1 + et+2 + ... + et+n , for any arbitrary n > 0. Now, suppose we are at date t and wish to estimate the future level of GDP at date t + N, where N is some number large enough to be considered the ‘longrun;’ e.g., N = 40 quarters (ten years) off into the future. Then we can ask the question: what is the expected value of yt+N , given what we know at date t? The answer is given by: Et yt+N = N γ + yt . (8) This ‘long-run’ (N −period ahead) forecast of GDP can be thought of the model’s ‘trend’ for the (log) level of GDP. In other words, the ‘long-run’ level of GDP is determined by the current level of GDP yt plus an expected growth term N γ. Note that since yt changes over time, so does the trend level of GDP. In fact, since yt is a random variable, our model displays what is known as a stochastic trend. Needless to say, a stochastic (random) trend line is not going to look anything like the smooth deterministic trend line drawn in Figure 1.5. There is, in fact, no reason to believe that yt will ever revert back to a smooth trend line estimated with historical data. The estimated trend line is simply a figment of the econometrician’s imagination (we know this, but he doesn’t). Why is this important to understand? It is important for the following reasons. First, as mentioned earlier, there is a tendency for people to believe that a smoothly drawn line through the data represents something ‘fundamental’ about the way an economy functions in the long-run. In other words, there is a tendency to believe that an economy will eventually revert back to some given trend behavior. As the example above demonstrates, such a belief is not necessarily correct (and can easily be incorrect, given how similar the simulated series in Figure 1.7 resemble the actual data). Second, by assuming that the economy does possess a smooth trend, one is implicitly assuming that growth and business cycle phenomena are independent 29 of each other. That is, one is easily led to the conclusion that we can use a growth theory to understand trend behavior and a business cycle theory to understand deviations from trend, with each theory bearing no relation to one another. In fact, it may very well be the case that the so-called ‘business cycle’ is nothing more than a by-product of the process of economic development (as suggested by our model). In other words, we may be wrong in thinking (as people commonly do) that we can understand the business cycle without understanding the process of growth itself. Fluctuations in GDP may largely be a by-product of a random growth process (a shifting trend); i.e., the ‘business cycle’ may be inextricably linked to the process of economic development itself. The basic lesson here is to be careful in assuming that an economy has a smooth trend and that GDP will eventually return to this trend. To demonstrate the potential pitfall of this commonly held view, consider Figure 1.8, which plots the real per capita GDP for Japan from1960—2004. Imagine that an econometrician living in the year 1973 wants to estimate the ‘trend’ for Japanese GDP based on the historical data 1960-73. The dashed line (a simple linear trend) in Figure 1.8 appears to fit the historical data reasonably well. Unfortunately, the forecast of GDP far off into the future would have been off a tad. 30 Figure 1.8 Real per capita GDP Japan 1960-2004 40000 36000 2002 USD using PPP 32000 28000 24000 20000 16000 12000 Real per Capita GDP Linear Trend estimated in 1973 8000 4000 60 65 70 75 80 85 90 95 00 Source: U.S. Department of Labor BLS www.bls.gov/fls/flsgdp.pdf The trend is your friend... ...until it ends. 8. Schools of Thought The reason for why aggregate economic activity fluctuates the way it does, even in relatively stable institutional environments, remains largely an unresolved puzzle. It should come as no surprise then to learn that there are many different hypotheses that offer different interpretations of observed patterns. At the end of the day, the lines of debate are drawn across the following two questions: • What are the primary shocks that are the ultimate source of aggregate fluctuations? • What is the mechanism by which an economy responds to any given shock? 31 Strictly speaking, a shock refers to a ‘surprise’ event that is determined by God or nature (i.e., an event that is beyond the control of any economic agent or agencies). A tsunami that wipes out a significant fraction of a region’s stock of human and physical capital constitutes a possible example. The sudden appearance of new technology—like the internet—may be another. Unfortunately, the interpretation of shock events is not entirely unambiguous. For example, some religious groups contend that the December 26, 2004 tsunami that afflicted southeast Asia was in fact brought forth by God as a punishment for the region’s sins (sex and drugs). According to this interpretation, the inhabitants (and tourists) in southeast Asia brought the tsunami on by their own debaucherous behavior. This view requires that we take as exogenous (i.e., unexplained) two things: [1] God’s law; and [2] preferences for debaucherous activities (that violate God’s law). Nevertheless, one might still argue that while the tsunami itself should have been expected, the exact date of its arrival could not have been forecasted. Thus, the actual arrival of the tsunami is still usefully interpreted as a shock. The same sort of argument can be made with respect to a technology shock. That is, let us take as exogenous two things: [1] the law of nature governing the process of discovery; and [2] preferences for higher living standards. Then one might reasonably argue that the idea behind the internet was in fact the product of human behavior (e.g., R&D activity). As with the tsunami, however, no one can reasonably be expected to forecast the exact arrival date of any technological advancement. When knowledge is discovered then, it comes as a shock. In a sense, any economic theory constitutes an explanation of how a set of endogenous variables Y is determined in relation to a set of exogenous variables X. Thus, in abstract terms, any theory can be thought of taking the following form: X →L Y, where →L denotes the logic underlying the explanation. A shock then can be thought of as some exogenous change in X and denoted ∆X. The theory then provides an explanation for the mechanism by which a change in X might be expected to influence the endogenous variables Y ; i.e., ∆X →L ∆Y. At issue then is what to include in X and how to think about ∆X (assuming that few people will argue with →L or the form of logic to be used in connecting assumptions with predictions). Ultimately, one would hope for a theory that could explain everything in terms of an X that was ‘truly’ exogenous. Unfortunately, the nature of economics (and of science in general) is such that a ‘grand unifying theory’ of this form is unlikely to found anytime soon. In the meantime, we have to make due with what must be considered only ‘partial’ explanations that will (hopefully) be improved upon as the science progresses. 32 Thus, there is at present a long list of candidates for what might be included in ∆X. Some theories assert the existence of government spending shocks or monetary policy shocks, as if the behavior of the government or its affiliated agencies is beyond comprehension (i.e., determined by God or nature). The Bank of Canada, for example, emphasizes domestic shocks that arise from political uncertainty (e.g., will Québec separate from Canada or not) and international shocks like the 1973 OPEC oil crisis and the 1997 Asian financial crisis.7 Economic commentators and analysts on television are fond of pointing to price shocks (e.g., the stock market, interest rates, inflation, exchange rates) as if these objects too are somehow not determined by conscious human behavior in reaction to more fundamental disturbances. In many cases, it can make sense to view particular events such as sudden price changes or financial crisis as an exogenous shock, even if we know (or suspect) that prices and financial market behavior are not truly exogenous. For example, we may want to frame a question in the following way: How might the domestic economy react given the financial crisis in Asia? The answer to such a question, while useful for some purposes, is ultimately unsatisfying as it leaves unexplained the crisis itself. Economists have different hypotheses concerning the ultimate source of such disturbances, and these different views help define various schools of thought. At the risk of oversimplifying, one might usefully categorize macroeconomic theory into two broad schools of thought, each of which is characterized primarily by the particular set of shocks and mechanisms that tend to be emphasized. I label the first school conventional wisdom, as variants of this view are held so widely among market analysts, politicians, central bankers, and a good part of the academic community. I label the second school neoclassical; this view is not nearly so widely-held, but is nevertheless influential among academic economists. Conventional Wisdom The conventional wisdom owes its intellectual debt primarily to the work of John Maynard Keynes, whose views on the business cycle were shaped to a large extent by the events of the Great Depression.8 The primary legacy of this view is twofold: [1] that shocks are ultimately the result of exogenous changes in private sector expectations (animal spirits); and [2] that market economies are sufficiently dysfunctional as to make well-designed government stabilization policies desirable. The way these ideas have evolved into conventional wisdom are as follows. First, growth is explained as the product of a relatively smooth process of technological development, so that one can infer from the data a relatively stable 7 See: www.bankofcanada.ca/en/monetary_mod/factors/index.html John M. (1936). The General Theory of Employment, Interest and Money, MacMillan, Cambridge University Press. 8 Keynes, 33 trend that determines an economy’s ‘long-run’ fundamentals. The business cycle then, constitutes fluctuations around this trend (with movements in GDP eventually reverting back to trend). The trend level of GDP is sometimes referred to as supply or potential GDP, with the actual level of GDP referred to as demand.9 Having identified a relatively stable trend (supply) and then observing that actual GDP (demand) fluctuates around trend, one is led to the conclusion that business cycles are caused by demand shocks (i.e., unexplained and random changes in desired spending patterns emanating from various sectors of the domestic and foreign economy). While the root cause of these shocks is not usually discussed, it seems clear enough from the language used to describe them that they are thought to be the product of exogenous (and irrational) swings in market sector expectations (animal spirits). A strong quarter, for example, might be explained as resulting from the ‘strength of the consumer;’ which in turn may lie in the behavior of ‘consumer confidence’ (high expectations of future earnings). Similarly, business sector behavior may be described as being the product of ‘irrational exuberance’ (high expectations concerning the future return to investment). To the extent that demand shocks are ‘irrational,’ they have adverse consequences that can last a long time. A bad investment today, for example, will have implications for GDP many periods into the future. These shocks are further exacerbated by various market imperfections—for example, in the form of ‘sticky’ nominal prices and wages—that prevent markets from adjusting rapidly to shocks (which explains why ‘supply’ is not usually equated to ‘demand’). Given this interpretation of the cycle, it should come as no surprise that this view also advocates the use of various government stabilization policies (active monetary and fiscal policy) to mitigate the adverse consequences of the cycle.10 Neoclassical View The neoclassical view is closer in spirit to those expressed by another great economist, Joseph Schumpeter.11 The primary legacy of this view is that technology shocks—the very shocks that contribute to the general rise in living standards—are at the same time responsible for generating the fluctuations that are commonly interpreted as the business cycle. 9 This language has even found its way into the IEA. For example, the expenditure-based measure of GDP is often labelled ‘final demand.’ The implication, of course, is that the final demand computed in this manner does not necessarily measure ‘final supply.’ 1 0 It is interesting to note that Keyne’s (1936) own views differ significantly from those that evolved from his work. In particular, while he emphasized the role of ‘animal spirits,’ he viewed these exogenous changes in expectations as being rational in the sense of constituting ‘self-fulfilling prophesies.’ Further, the concept of ‘sticky’ prices or wages played no role in his theory; except peripherally and as a mechanism that potentially dampened the adverse consequences of demand shocks. 1 1 Schumpeter, Joseph A. (1939). Business Cycles: A Theoretical, Historical and Statistical Analysis of the Capitalist Process, New York, McGraw-Hill. 34 According to the neoclassical view then, the distinction between ‘growth’ and ‘cycles’ is largely an artificial one. Almost everyone agrees that long-run growth is the product of technological advancement. But unlike the conventional wisdom, which views trend growth as being relatively stable, the neoclassical view asserts that there is no God-given reason to believe that the process of technological advancement proceeds in such a ‘smooth’ manner. Indeed, it seems more reasonable to suppose that new technologies may appear in ‘clusters’ over time. These ‘technology shocks’ may cause fluctuations in the trend rate of growth through what Schumpeter called a process of creative destruction. That is, technological advancements that ultimately lead to higher productivity may, in the short run, induce cyclical adjustments as the economy ‘restructures’ (i.e., as resources flow from declining sectors to expanding sectors). Further, there is no guarantee that all new technologies work out exactly as planned or expected. What may have looked promising at one date, may in fact turn out to be a disaster later on (resulting in an observed negative technology shock). As with the conventional wisdom, the neoclassical view admits that sudden changes in private sector expectations may lead to sudden changes in desired household and business sector spending. But unlike the conventional wisdom, these changes are interpreted as reflecting the ‘rational’ behavior of private sector decision-makers in response to perceived real changes in underlying economic fundamentals (i.e., technology shocks, or other real factors). In other words, changes in market sentiment are the result and not the cause of the business cycle. It is important to keep in mind when evaluating this perspective that the concept of ‘rational’ expectations does not imply that individuals never make ‘mistakes.’ It simply means that expectations are formed in the ‘best’ way possible, using whatever relevant information is currently at one’s disposal. More often than not, actual outcomes will differ from those that are expected. According to the neoclassical view, the business cycle is an unfortunate but largely unavoidable product of the process of economic development. Market imperfections play little or no role in exacerbating economic fluctuations; indeed, even a well-functioning ‘planned’ economy (if such an object were to exist) would exhibit similar fluctuations. Given this interpretation, it should come as no surprise to learn that the policy implication here is that government attempts to stabilize the cycle are likely to do more harm than good. 9. The Plan Ahead In the chapters that follow, I plan to lay out—hopefully, in easily digestible bits and pieces—the various key elements that constitute modern macroeconomic theory. This endeavor is not meant to be an exercise in pure theory; throughout the book I try to demonstrate how the theory can be used to interpret and understand various aspects of real-world economies. The book is designed so that, by the end of it, a conscientious (and patient) 35 reader will have a reasonably good idea of basic theory (and how the various bits and pieces I present can ultimately be tied together in a more advanced theoretical treatment), together with an idea as to how modern macroeconomic theory can be applied toward interpretation, prediction, and the evaluation of policy. 36 Problems 1. While Americans constitute a relatively small fraction of the world’s population (less than 5%), they spend approximately 20% of the world’s income. This fact is sometimes used as evidence of American ‘greed.’ Provide a different interpretation of this fact based on your knowledge of the relationship between aggregate expenditure and output. 2. We often read that ‘the consumer’ drives the economy because consumption accounts for 60% of GDP. On the other hand, it is also true that ‘the laborer’ accounts for 75% of GDP; yet we seldom (if ever) hear of stories relating to how the GDP depends on the supply of labor. Why do you think this may be the case? 3. Why do you think it is important to distinguish between consumption and investment goods? 4. Explain why government transfers are not counted as a part of an economy’s GDP (it will be useful to first define the GDP). 5. Explain why ‘overpaid’ government employees will lead to an overstatement of GDP, whereas ‘overpaid’ private sector employees will not. 6. Explain the conceptual difference between a statistical trend and a theoretical trend. 7. Consider two economies A and B that each have a real per capita GDP equal to $1,000 in the year 1900. Suppose that economy A grows at 2% per annum, while economy B grows at 1.5% per annum. The difference in growth rates does not seem very large, but compute the GDP in these two economies for the year 2000. In percentage terms, how much higher is the real GDP in economy A compared to economy B? 37 CHAPTER 2 Output and Employment 1. Introduction A central feature of the business cycle is the comovement between output (real per capita GDP) and employment (or hours allocated to work activities per capita). In the short-run, output and employment tend to move in the same direction. In fact, much of the change in GDP over the cycle is attributable to changes in the level of employment. This makes a lot of sense since, as more individuals work to produce output (or as employed individuals work longer hours), one would expect the level of output to increase. But understanding this fact alone does not help us understand the business cycle, as it does not explain why employment should change in the first place. Most economists would probably agree that the cyclical variation in employment is driven by fluctuations in the demand for labor. There is, unfortunately, considerably less agreement on what forces are responsible for generating the volatility in labor demand. Since labor productivity and real wages tend to by procylical (i.e., move in the same direction as GDP), some economists stress the role played by productivity shocks (recall the discussion in Chapter 1). The basic idea here is that temporal variation in the productivity of labor is a natural phenomenon in a growing economy. When productivity is high (relative to trend), the business sector demands more labor to exploit the high return to labor. This shift in labor demand puts upward pressure on real wages, which serves to draw more individuals into the labor force. The reverse holds true when productivity is low (relative to trend). The primary goal of this chapter is to formalize the intuition above in terms of an explicit (i.e., mathematical) theory. Developing a formal model will prove useful for a number of reasons. First, it will allow us to check whether the intuition expressed above survives a logical analysis. (There are times when simple intuition only holds under some very specific conditions—or perhaps not at all). Second, we can use the logic contained in the theory to help us evaluate the potential role for government policy. Third, the simple theory developed here will serve as useful groundwork for the more elaborate theories to be developed later on in the text. To this end, we will construct a model economy, populated by individuals that make economic decisions to achieve some specified goal. The decisions that people make are subject to a number of constraints so that inevitably, achieving any given goal involves a number of trade-offs. If these trade-offs fluctuate over time owing to any sort of exogenous shock, then individuals are likely to change their behavior accordingly. The question here is whether exogenous changes 38 in productivity might generate changes in behavior that imply business cycle activity that is qualitatively similar to what is observed in reality (i.e., procylical employment and real wages). 2. A Simple Model The model I consider here is a very simple one indeed; in particular, it makes a lot of simplifying assumptions. Many of these assumptions will appear to be highly unrealistic. You should resist the natural inclination to judge a model solely on the basis of its assumptions. In particular, one might note that we use unrealistic models every day for useful ends. The common roadmap as an abstract representation of the countryside is one example. We judge a roadmap not on the fact that it (unrealistically) abstracts from atmospheric conditions; we judge a roadmap on its ability to help guide us through unknown territory. The same principle should be used to evaluate economic models (abstract representations of the real economy). In any case, you can rest assured of two things: [1] the model can be easily extended in a number of interesting (and more complicated) ways—some of which we will explore later on; and [2] the basic forces highlighted in the simple model continue to hold in much more general (and realistic) environments. We begin by stating a number of simplifying assumptions. Since employment behavior plays an important role in the business cycle, we want to think of how to model the labor market. To this end, we want to model a household sector (from which stems the supply of labor) and a business sector (from which stems the demand for labor). So to begin, let us assume that the economy consists only of these two sectors; i.e., assume that there is no government or foreign sector. From our knowledge of the income-expenditure identity, we know that this assumption implies G = X = M = 0, so that C + I = Y. If we assume further that all output is in the form of consumer goods and services, then I = 0 and C ≡ Y. In other words, all income in this model will take the form of claims against domestically-produced consumer goods and services. In short, we are dealing here with a closed economy, with no government, no foreign sector, and no investment. These assumptions will be relaxed in later chapters. Let us think next of the people that occupy our hypothetical world. We want to think of an economy consisting of a ‘large’ number of people, each of whom belong to the household sector. In reality, people obviously differ along many dimensions. On the other hand, people also seem to share many things in common, including a general desire to advance their material well-being. Our strategy here will be to focus on these common attributes and downplay the differences. For simplicity, we take this to the extreme by assuming the existence of a representative household (i.e., we assume that households are 39 all identical along economically relevant dimensions).12 Let us now think about the business sector. We want to think of the business sector as consisting of a ‘large’ number of competitive firms. It is important to note that firms are not people; they are simply legal entities (operated by people) that organize production. Again for simplicity, we will assume that all firms are identical so that there exists a representative firm. Assume that firms are owned by members of the household sector (to which all individuals belong) and that firms are motivated by a desire to maximize shareholder wealth. Finally, we want to consider an assumption that will simplify decisionmaking considerably. In particular, we consider here what is called a static model. The word ‘static’ should not be taken to mean that the model is free of any concept of time. What it means is that the decisions focussed on here have no intertemporal dimension (which allows us to abstract from financial markets). The restriction to static decision-making allows us, for the time-being, to focus on intratemporal decisions (such as the allocation of time across competing uses over the course of a year). As such, one can interpret the economy as generating a sequence of static outcomes over time. 2.2 The Household Sector The representative household has preferences defined over two objects: [1] a basket of consumer goods and services (consumption), which we denote by c; and [2] a basket of home-produced goods and services (leisure), wh...
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Running head: UNEMPLOYMENT IMPACT IN BUSINESS

Unemployment impact in business
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UNEMPLOYMENT IMPACT IN BUSINESS

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Frictional unemployment
Frictional unemployment is the unemployment that results from people moving from one
business to another. It occurs when workers are looking for jobs in a healthy economy. In the
growing economy friction, unemployment is very low and there is a demand for high
employment. It causes slow economic growth due to a high demand for employment. It is caused
by workers holding much to their job unless they find a new job. Some workers may leave jobs
as they move to their spouse, othe...


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