1960s: Experiments with Fiscal Policy [PDF]

1960s: Experiments with Fiscal Policy "Involuntary unemployment is the most dramatic sign and disheartening consequence of underutilization of productive capacity…. We cannot afford to settle for any prescribed level of unemployment…." John F. Kennedy

Overview Keynesians turned macroeconomic theory and policy completely around in the 1960s as they shifted the focus from the long run to the short-run, from the supply to the demand-side of the economy, from a handsoff to a hands-on policy of government management of the economy. As the decade began Kennedy noted, "Involuntary unemployment is the most dramatic sign and disheartening consequence of underutilization of productive capacity…. We cannot afford to settle for any prescribed level of unemployment …," and Keynesians "promised" full employment through managing aggregate demand. In this unit we examine the following four aspects of the theoretical and policy developments of the decade related to demand management, but first let’s look at that Keynesian experiment that defined the macroeconomics of the decade.

The Keynesian Experiment The 1960s was a decade where the US experimented with the fiscal policies rooted in Keynes' work. At least on the 'books' the government was committed to macroeconomic management of the economy since passage of the Employment Act of 1946 established the maintenance of full employment as a responsibility of the government and the Council of Economic Advisors to oversee this process. According to the law, "The Congress hereby declares that it is the continuing policy and responsibility of the Federal Government to . . . promote maximum employment, production and purchasing power." The Act would not provide the basis for aggressive Keynesian policies, as was evident in the Eisenhower presidency. Eisenhower's contractionary fiscal policies slowed economic growth and by 1960 evidence was mounting that Europe and Japan were growing faster than the US.22 The slow growth provided little cushion for the two severe recessions of 1953-54 and 1957-1958 and a general upward trend in unemployment that peaked 1960 opened the door for John F. Kennedy who promised to "get the country moving again." While some would claim Kennedy's victory over vice president Richard Nixon hinged on Kennedy's effectiveness in the new medium of TV, there is no doubt the state of the macroeconomy hurt Nixon's chances. The American people had been sensitized to the macroeconomic performance of the economy and they were ready to sign on to Kennedy who would lead the US into the New Frontier.i Kennedy surrounded himself with academic economists well trained in Keynesian macroeconomic theory under the leadership of Walter Heller, Chairman of the Council of Economic Advisors. This was the beginning of what Heller saw as "the completion of the Keynesian revolution - 30 years after John Maynard Keynes fired the opening salvo."ii. Armed with their theory of the macroeconomy and new data, policies could be established to steer the economy toward full employment. Just as managers would guide the operation of the large corporations, economists would manage the macroeconomy - and there was every reason to believe we were entering what Robert Heilbroner called the "Golden Age of Capitalism." Kennedy clearly thought discretionary macro policy be used to fine-tune the economy, as we could see in the 1962 Economic Report of the President.iii Until we restore full prosperity and the budget-balancing revenues it generates, our practical choice is not between deficit and surplus but between two kinds of deficits: between deficits born of waste and weakness and deficits incurred as we build our strength...

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The result was Kennedy's peacetime tax cut, an idea that first surfaced in the spring of 1961 with Heller leading the call.iv In June Kennedy delivered a speech at Yale in which he declared "economic independence" from "economic mythology" of the past - a prelude to his call for a massive tax cut in 1963. As Kennedy had stated in a message to Congress outlining his program for economic recovery and growth on February 2, 1962, "The federal budget can and should be made an instrument of prosperity and stability, not a deterrent to recovery." The Revenue Act of 1964 contained the Kennedy peacetime tax cut, and it worked as planned. Arthur Okun, president Johnson's economic advisor, was so confident in the successes of the revolution that he claimed recessions "are now generally considered fundamentally preventable, like airplane crashes and hurricanes." There may have been room for refinement, but even President Nixon, a conservative Republican, announced, "Now I am a Keynesian." The completeness of the Keynesian victory was apparent to all when on December 31, 1965 Keynes appeared on the cover of Time magazine and the cover story identified his theories as the "prime influence on the world's free economies..." Policy makers had "used Keynesian principles not only to avoid the violent cycles of prewar day but to produce phenomenal economic growth and to achieve remarkably stable prices." The 1960s was a very good time to be an economist - especially a liberal macroeconomist. If Keynesians were to defeat the business cycle and deliver on the promise of taming the business cycle a prerequisite would be a better understanding of the macro economy. There would be a need to work through some of the "details" that could be ignored during the Depression. We begin our analysis with a more detailed discussion of aggregate demand, which Keynesians saw as driving the economy. Developments in the 1960s also prompted some important modifications to the Keynesian analysis including a more complete account for inflation and timing issues, which we also examine. And the growth of interest in fine-tuning the economy created a whole new 'growth sector' in the economics profession short-term macroeconomic forecasting became an essential piece of the stabilization policies, so the unit closes with a brief overview of macroeconomic forecasting.

A detailed treatment of demand Keynesians believed effective management of aggregate demand was the way to achieve full employment. If the economy was operating at less than full employment then aggregate demand could be “managed” so as to create enough demand to bring back the unemployed to work to satisfy the additional demand. Because of the centrality of aggregate demand, economists devoted a considerable amount of time and effort to studying the five components of aggregate demand - Consumption, Investment, eXports, iMports, and Government expenditures. This is why one of the few equations you should keep on your short-list of important equations is the equation for aggregate demand (AD).

AD = C + I + G + X - M Research efforts focused primarily on the first two of these and in this section we will examine in some more detail Consumption and Investment spending.

Consumption spending Consumption spending is important because it is by far the largest component of AD, and this has not been lost on policy makers who have attempted to manipulate it in an effort to manage the macroeconomy. This is why Kennedy targeted consumers to jump start the economy and why George Bush appealed directly to the American people to do their patriotic duty to get out there and spend after the shock of 9/11 and at the onset of the 2008 recession. Consumption spending includes expenditures on Durables, Nondurables, and Services.

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Durables are items that can be inventoried and have an average life of at least three years (autos, appliances, computers...), nondurables are items that cannot be inventoried and have an average life of less than three years (food, clothing...), and services are items that cannot be inventoried and are consumed at the place and time of purchase (education, health, legal...). Since 1960 the component of consumption that has grown most rapidly has been services - things like education and health care. There has also been a substantial increase in consumer durables, a refection of the rise of those electronic gadgets such as cell phones, flat-panel TV, DVDs..... You can also see in the graph that in the recessions of the early 1980s, early 1990s, and the Great Recession of the late 2008-2009 it was consumer durables that suffered declines as households cut back on big-ticket items. In 2009, the allocation of spending among the three categories was 10% on durables, with about 30% of that in autos; 22% in nondurables, with about 1/3rd of that in food; and 67% in services, with nearly 25% of that in medical care.

Theoretical analysis of consumption began with Keynes who assumed income was the most important determinant of consumption spending, and the scatter diagram based on post WWII data provides strong evidence of this relationship between income (horizontal axis) and consumption expenditures (vertical axis). In fact it is a VERY good relationship we could capture in a linear equation where the slope would be the MPC that was important in the multiplier formula.v Not everyone agreed with this analysis, however, especially conservative economists with roots in Classical economic theory. One alternative was conservative economist Milton Friedman’s Permanent Income Hypothesis in which lifetime earnings were the primary determinant of consumption. According to Friedman, in a recession individuals would not substantially adjust downward their estimates of lifetime income and therefore they would adjust to the temporary income loss with lower saving rather than lower consumption spending. This weakened the link between consumption and current income that translated into a smaller MPC, a smaller multiplier, and reduced effectiveness of fiscal policy. This model also introduced the wealth effect – the idea that wealth should be a determinant of consumption spending; during a boom in asset prices (stocks and homes) consumption spending would rise, while a collapse such as we experienced in stock prices in 2000-01 and home prices in 2008-09 would push consumption spending lower. It also helps explain what drove the savings rate down in the 2000s. As people’s home prices rose they felt wealthier regardless of their paycheck and opened up their wallets to spend. Other factors that contributed to the falling savings rate have been financial innovation (easier to borrow), Social Security and macroeconomic stability (bigger SS and more stable economy reduce need to save for a rainy day), and demographics (aging of baby boomers). As for the impact of the two major assets

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on spending, the marginal propensity to spend housing wealth is .09 and the marginal propensity to spend stock market wealth is .04. It is also true that the marginal propensity to spend housing wealth increases with age through age 65.vi

A different slant on the problem was provided by the Life-Cycle Model of consumption built on the assumptions that spending today depends on expected lifetime earnings and the spending decisions are based on a preference for avoiding large changes in spending. Like the Permanent Income Model, this model highlights the importance of expectations as a determinant of demand and the differences between temporary and permanent income changes. What is added by the Life-Cycle model as an influence on consumption spending is age structure, which helps explain the difficulties Japanese officials experienced in the late 1990s in attempting to get aging Japanese consumers to spend money to stimulate aggregate demand. The Japanese worried about their retirement and continued to save for retirement despite the government's efforts to get them spending. The model also explains how fear of nuclear war affects consumption spending. If you expect nuclear war, you expect to die earlier and therefore you will save less for your retirement.

Investment spending Investment spending is a relatively small component of aggregate demand that is important for three reasons. First, because it represents the annual additions to the nation's capital stock, business spending on structures and equipment is considered important to the welfare of the economy because it has both a supply-side AND demand-side effect on the economy. Expenditures on structures and equipment generate demand initially, but the expansion and modernization of the capital stock will translate into higher productive capacity in the future. It is for this reason that so much attention in recent years has been focused on tax policies such as investment tax credits and accelerated depreciation aimed at increasing investment expenditures. Second, given its volatility, investment spending is the component of demand we look to for keys in understanding of the short-run dynamics of business cycles. Third, investment expenditure is sensitive to interest rates, which we see later is important for the functioning of monetary policy. An example would be Alan Greenspan's reduction of interest rates in 2001 to stimulate investment spending to offset the negative effects of 9/11 (2001).vii There are three components of investment spending. The largest is Nonresidential fixed investment that measures business spending on Structures and Producer's durable equipment - the new factories, offices and machinery that help make US workers the most productive in the world. The second is Residential construction - the construction of those new homes that can be quite volatile. The final component is Change in Business Inventories, which is a residual term that ensures total demand equals total supply. For example, if GM produces too many cars and these cars pile up on the lots of dealers, then they are counted as inventory investment. They are considered to be cars that GM produced to be sold at a later date. Inventory investment is important because it is recognized as a leading indicator in the economy. If for example, inventories are rising, this suggests aggregate demand is inadequate and a slowdown in the economy can be expected as production will need to be cut back to bring demand and supply in line.

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Demand for nonresidential (NR) equipment was by far the fastest growing component of investment since 1990, a reflection of the Internet boom and the fear of the Y2K at the millennium that fueled demand for information and communications equipment. It also tends to be a volatile component of aggregate demand rising in good times and falling in bad. You can see this in the slight dip in the early 1990s recession and the substantial drop in the early 2000s triggered by businesses cutting back on IT investments after Y2K passed without any major problems. Residential investment in new homes has historically been quite volatile, but it was barely affected by the early 2000s recessions. Residential construction is important for psychological reasons since there is probably no better sign of economic growth then the construction of new homes and offices. A construction boom will be accompanied by a growing optimism, reflected in measures of consumer sentiment, and firming of housing prices which will increase household wealth, a determinant of consumption expenditures. Inventory investment is important because it is one of the components in the index of leading indicators published monthly by the Conference Board.viii If, for example, there is an undesired build-up of inventories, then this is likely to send a signal to producers to cut back on production to bring their inventories back to desired levels. The build-up in inventories will 'lead' to eventual reductions in output and employment and rising unemployment. The major weakness of inventory investment as a leading indicator is there is no way to decompose the published statistics on inventory investment into the desired and undesired components, and it is only the latter that would be useful to forecast the direction of the economy. As for the other two components of demand, we will examine them in some detail at later times - net export spending in the 1970s unit and government spending in the 1990s unit. For now, we acknowledge that the government's share of aggregate demand is approximately 18% - about what it was in 1950. What this stability masks are substantial shifts in the nature of that spending. Spending by state and local governments has been rising more rapidly than federal spending and since 1970 state and local spending has exceeded federal spending. In fact, state & local governments' spending grew nearly 50% between 1990 and 2005, while federal government demand was up about 10%. Within the federal government there was also a substantial shift in spending patterns away from defense after the Vietnam War in the 1960s, a reversal during the Reagan military build-up in the 1980s, another reversal in the 1990s when defense spending fell after the Soviet Union collapsed, and the build-up under Bush II. As for net exports, between 1960 and 2008 the value of imports and exports both increased substantially faster than GDP. Of the two, imports grew more rapidly so a trade surplus of .6% of GDP in 1960 was transformed into a trade deficit of more than 5% of GDP by 2008. This has caused considerable concern in

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Washington on the issues of competitiveness of American workers and unfair trading practices, and we will look more closely at the international data in the unit on the foreign exchange market.

Economic forecasting What does the future hold? This is a question we all would like to know the answer to, which may help explain why business is good for Tarot card readers, why meteorologists have their spot on prime-time news, and why each election is accompanied by pollsters forecasting election results. In his 1990 book Searching for Certainty: What Scientists Can Know About the Future, John Casti evaluated a wide array of forecasting efforts - from evolutionary biologists to celestial mechanics to economics, and economists were given a D for their efforts.ix Two examples of where they got it wrong were the late 1980s when Japan was being forecast to be the next world power, just before it fell into a decade long depression in the 1990s, and in the mid 1990s when the stories of Asian economic growth miracles provided no advance warning for the economic crashes of the 1997-98. And then there was Professor Franklin Fisher's opinion that stock prices had reached "what looks like a permanently high plateau" that he offered in 1929 just before the stock market crashed.x The fact is that forecasting is certainly not an exact science and Mark Twain had it right when he wrote: "The art of prophecy is very difficult – especially with respect to the future." A few of my favorites are listed below.xi •

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"The improvement in city conditions by the general adoption of the motor car can hardly be overestimated. Streets clean, dustless, and odorless, with light rubber tired vehicles moving swiftly and noiselessly over their smooth expanse, would eliminate a greater part of the nervousness, distraction, and strain of modern metropolitan life." Scientific American, 1899 "This 'telephone' has too many shortcomings to be seriously considered as a means of communication. The device is inherently of no value to us." Western Union internal memo, 1876 "Rail travel at high speeds is not possible because passengers, unable to breathe, would die of asphyxia." Dionysius Lardner, 1828 "The problem with television is that people must sit and keep their eyes glued on a screen; the average American family hasn't time for it." NYT 1939 “The Japanese don’t make anything the people in the US would want.” (Secretary of State John Foster Dulles in 1954 "And for the tourist who really wants to get away from it all, safaris in Vietnam." Newsweek's 1963 prediction of popular holidays for the late 1960s. "I think there is a world market for maybe five computers." Thomas Watson, chairman of IBM 1943 "There is no reason anyone would want a computer in their home." Ken Olsen, founder of Digital 1977 "I see little commercial potential for the Internet for at least 10 years." Bill Gates Comdex 1994

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So maybe economic forecasts aren't so bad and maybe the poor grade isn't quite justified. But we are not going to quibble over the grade - we are going to look at what it is that economists are getting graded on. In this unit we will be looking at economic forecasts – what they forecast and how they do it.

When in the future? The work of the earliest economists focused on the long-term - what will happen in twenty, fifty, or one hundred years, but in the 1960s short-term forecasting was getting all the attention. This shift can be attributed to four factors - the theory, the numbers, the machine, and the market. The theory was John Maynard Keynes' multiplier that provided the rationale for a government to attempt to manage the economy. If you were going to manage the economy, however, you needed numbers - and by the mid 1960s the US government had created the data needed to construct the statistical forecasting models.xii The machine was the computer, and by the late 1960s and early 1970s early versions of computer were making possible the statistical analysis needed to develop these forecasts. As for the market for forecasts, in his books The New Industrial State and The Affluent Society John Kenneth Galbraith noted that the rise of the mega corporation raised the level of investment spending, which in turn generated demand for forecasts to avoid potentially expensive mistakes. When forecasting, you must begin by recognizing that there are three separate components of any timeseries graph - the seasonal, cyclical, and trend effects. For example, retail sales peak each year in December and collapse in January, while unemployment rates on Cape Cod rise in the winter months and fall during the summer months. These are seasonal variations and we can see a distinct seasonal pattern in retail sales for jewelry stores because it is actual data and not seasonally adjusted (NSA) data. In the graph below we see jewelry sales peak in February for Valentines Day, May for Mothers' Day, and December for Christmas. If you are not interested in seasonal patterns, you may use seasonally adjusted data that eliminates the seasonal patterns.

The second component is the ups and downs that tend to be associated with business cycles. These movements tend to be longer than a year, but shorter than five years. In the graph of the unemployment rate booms and busts of the period is very clear. The unemployment peaks in 1993, 2003, and 2010 reflect the economic slow down in recessions, while the decline from 1993 to 2001 and 2003 to 2007 reflects the good times during the Internet and housing booms. During this boom the unemployment rate fell to under 4%, before rising quickly to 6% after the Internet bubble burst in the early 2000s, and in the Great recession of 2007 the unemployment rate reached 10%.

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The final component is the trend - the long-term direction in which the curve is going. In the dollar/yuan exchange rate graph, there are three separate trends. In the first the value of the dollar is rising as it takes more yuan to buy a dollar, then it levels out, which indicates it has been fixed by government action, and after 2005 the dollar has declined relative to the yuan. Now we will turn our attention to the how question.

How do economists forecast? To highlight the different forecasting techniques, let's look at the situation at Itzibitzi motorcycles. The company wants to forecast sales for the next 5-6 years to evaluate the decision to invest in a new production facility. We will look at three techniques: time-series analysis (the Ruler), econometrics (the Relationship), and barometric forecasting (the Experts).

Itzibitzi Motors Year

Sales (units) 1960

9073

1961

9287

1962

9853

1963

10094

1964

10500

1965

11321

1966

12216

1967

12315

1968

12970

1969

13320

1970

14038

1971

14580

1972

15057

1973

15951

1974

18120

1975

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The first step is to graph these data where the upward trend in sales is clearly visible, as is the upturn (faster growth) toward the end of the period. Time-series analysis (the ruler) The basic assumption underlying time-series forecasting is the only information needed to forecast the future of X is information on the past performance of X. In the diagram below you will see the red line that could be the result of someone using a ruler to draw a straight line that closely follows the trend in the historical data. Although the analysis can get quite sophisticated, it essentially is reduced to an equation where the value of sales next period (S+1) is dependent upon the value of sales this period (S). A linear version of the equation appears below. Once you have the value of sales today (S) you can forecast the value of sales next period (S+1).

Equation S+1 = a + b S

Econometric Models (the relationship) A second approach is based on uncovering a relationship between economic variables. For example, if we can explain past consumption spending in terms of income, then once we have a forecast for income, we can generate a forecast for consumption spending. There are two steps to the approach. First, you must estimate a relationship between the two variables based on historical data. In the Itzibitzi problem, you start by developing a list of what you think would explain sales of motorcycles. One variable that would be important for a five-year forecast would be the number of potential buyers. An obvious choice in the Itzibitzi problem would be to have sales (S+1) dependent on the size of the population aged 16-25 (P+1). More people means more sales.

Equation S+1 = a + b*P+1

We'll keep it simple and assume the BEST explanation of the actual pattern of Itzibitzi's sales and population is given by the following equation.

S = -3299 + .546*P

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The estimated equation is the red line in the graph above and looks very much like the estimated line in the time-series graph because population generally grows rather steadily - just as time does. The estimated equation does a reasonable job of explaining the actual pattern of sales, but once again the acceleration in sales in the mid 1970s is not picked up in the econometric analysis - at least not with the population variable. It could be picked up with another variable, possibly the price of gas that changed sharply in that period, and if we wanted to explore this link we would collect the gas price data and re-estimate the equation. The second step would be to generate a forecast of the population (P+1) and plug this into the equation to generate a forecast of sales (S+1). Another likely 'driver' for the forecast would be GDP which gives us a measure of the ability to pay - the higher the level of GDP, the higher the level of income to support the purchases of the motorcycles.

Barometric forecasts (the experts and leaders) The third approach to forecasting would be to turn to the experts for their opinions - a decision that would lead you in two directions. One possibility would be consensus forecasts such as the Blue Chip Indicators that provide forecasts on an array of macro variables based on surveys of economic forecasters. The second possibility would be to look for leading indicators. It would be wonderful if we were interested in forecasting a variable (blue line) and we had information on some other variable (red line) that followed a similar pattern, but simply did it a bit earlier. In the diagram below, you can see A is a very good leading indicator of B because it allows us to forecast what will happen four years in the future. For example, if we knew the leading indicator reached a turning point at A, then we would be able to forecast a turning point of B for the variable in which we are interested.

Unfortunately, the indicators that exist are not this good. The Conference Board, a private sector organization, took over the job once held by the US Department of Commerce and now publishes the Index of Leading Indicators for the US as well as other countries. A few of the variables included in the index are building permits, the money supply, and change in manufacturers’ unfilled orders, durable goods, and these variables should give us advance warning of impending changes in the economy. For example, building permits would provide an indicator of what levels of construction activity would be expected in the next few months, while a faster growth in the money supply could be expected to work its way into the economy where it would eventually lead to economic growth.xiii For those interested in something closer to home, you should check out Glen Ramsay's Index of leading Indicators for RI that the Providence Journal publishes monthly. Now let's look at an omission in the early Keynesian model, the issue of timing.

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Building in Timing The Kennedy tax cut in the early 1960s worked just as the theorists predicted and this success converted many doubters to the Keynesian "religion." By 1968, with inflation exceeding 6%, it was time to use fiscal policy to put the brakes on the economy. The problem facing president Johnson was tax increases are unpopular, especially when the taxes would fund the unpopular Vietnam War.xiv There was no way Johnson could propose a permanent tax increase to finance the war, so he turned to a temporary tax surcharge as the solution. It seemed to make good political and economic sense - a one-time tax increase to defeat inflation was something with which American people could live. Unfortunately it did not work because all tax cuts are not the same.xv When confronted with a temporary tax change people see it as temporary and try to "get through" it and maintain their standard of living by digging into their savings. Only permanent tax changes affect the consumption spending of individuals, which is what we saw with Kennedy. A temporary tax cut to businesses, meanwhile, could work quite well if it prompts businesses to redirect their spending to take advantage of the tax cut. If, for example, the government allows businesses to write off 10% of the costs of the investment, then spending $100,000 on the investment would lower taxes by $10,000, which would reduce the cost of the investment to $90,000. If the tax cut were a one-year deal, then firms would compare spending $90,000 today versus $100,000 a year from now - and some would certainly move their expenditures to take advantage of the tax cut. There are also some serious concerns about the timeliness of discretionary fiscal and monetary policies, which was ignored in our earlier discussion of the multiplier. In fact there are three of lags that must be acknowledged when we discuss efforts to fine-tune the economy. First, is the Recognition lag. In The Business Cycle graph below we need the expansionary impact of macro policy to ‘arrive’ as the economy heads into a recession at point A. As the economy slows it would be a great time for the new federal spending on highways to begin, but if it takes two quarters of declining GDP before we can even call it a recession, then it would take a minimum of six months to even recognize the problem. This recognition lag could be reduced if economists could forecast turning points in the economy. This was the situation faced by Fed chairs Alan Greenspan in early 2000 and Ben Bernanke in 2006 when they raised interest rates because of a fear the economy was heading towards inflation, even though there was no evidence of inflation when they made the decisions.

Once there is a general awareness of a problem, the debate shifts to one over the appropriate policy action the Discussion lag. A perfect example would be the Kennedy tax cut that was years in the making. Do we need an expansionary policy? If we need an expansionary policy, should it be a tax cut or a spending increase? If it should be a tax cut, should the cut go to...? It could take months or years to agree on the appropriate policy. In 2001-2002 there were lengthy discussions about the "fiscal stimulus" needed to offset the effects of recession after 9/11, and in 2008-09 there were heated debates about how big the stimulus

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should be, how much of it should be in tax cuts and how much in spending increases, and who should get the tax breaks and on what should we increase spending. Once the decision has been made to implement an expansionary macro policy, it would then take time for the policy to take effect - the Action lag. If expansionary monetary policy is effective at driving down interest rates, for example, it will be a while before the decline in interest rates is translated into additional spending and employment. Fiscal policy is thought to have a much shorter action lag, but in 2009 there was concern about the long action lag because much of the agreed upon stimulus had not been spent. The problem caused by these lags, as pointed out by Milton Friedman, is that discretionary policy might be valid in "theory," but in "practice," it too often could turn out to be counterproductive and could exaggerate the business cycle.xvi What we do know is the recognition lag tends to be the same for both monetary and fiscal policies since everyone has access to similar data, the implementation lag is shorter for monetary policy, and the action lag is shorter for fiscal policy. Even without discretionary policy tools, however, the government could still exert a stabilizing effect on the economy through the operation of Automatic Stabilizers. There are a number of government programs for which the level of spending is automatically countercyclical. For example, government unemployment benefits automatically increase in a recession while income taxes automatically rise during good years. As people lose their jobs they receive unemployment benefits that reduce the decline in income experienced by these newly unemployed so they will not have to make drastic cuts in their consumption spending. As the economy expands, meanwhile, unemployment benefits fall and payroll and income tax payments rise which should act as a brake on consumer spending. Right on queue, the government would inject increased spending in the form of unemployment benefits into the economy as the economy slowed, and just as the economy began to expand taxes would rise - precisely the slowing of spending that the Keynesians want to see. The 1960s taught us that timing could not be ignored, and it prompted Keynesian economists to extend their analysis to incorporate time. If you accept the fact that policy lags exist, then there will be a need to anticipate turning points in the economy. The 1960s also taught us that inflation could not be ignored.

Building in Inflation When Keynes wrote his General Theory inflation was not an issue for those searching for ways out of the Great Depression, which is why there was no explicit treatment of inflation in the 1930s unit. You could see this in the AS-AD model where the AS curve is horizontal indicating that changes in AD would have no impact on the price level. By the mid 1960s, though, inflation had become an issue and by the end of the decade the rate had reached a troubling 7%. Inflation needed to be addressed by policy makers, but for this to happen the prevailing economic theory needed to be modified to include an analysis of inflation. The modification was captured best in the Phillips Curve - a concept named after a London School of Economics professor who wrote a very influential article in which he created a scatter diagram based on nearly 100 years of data that looked very much like what you see here - inverse relationship between the rate of unemployment and the rate of increase in wages.xvii

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The logic was straightforward. As unemployment rates decreased, the balance of power between workers and employers shifted in favor of the workers who would use this new found power to raise their wages and businesses would pass on the higher wages as higher prices. Similarly, when business was bad, when the economy was in a recession, the balance of power shifted to the employers and there would be little, if any, power to raise wages. The result is a negative relationship between the rate of wage growth and the unemployment rate In the US the relationship was modified slightly - wage growth was replaced by growth in the price level but the logic remained the same. Returning to the AS-AD diagram can see the nature of the relationship between inflation and unemployment rates. On the left side we have the AS-AD diagram where an increase in AD shits the AD curve outward. This increase in AD moves the economy to the northeast, from point A to point B. This move would produce a higher price level (inflation) and higher output, which would translate into more jobs and a lower unemployment rate. If the demand curve shifts further to the right, we would find an even higher price level (higher inflation) and higher output level (lower unemployment rate). If we plotted the relationship between the inflation rate and the unemployment rate, we would have the curve on the right - the Phillips curve. As long as the “shocks” to the macroeconomy are from the demand side, we will see the Phillips Curve limiting policy choices.

Derivation of Phillips Curve AS-AD Diagram Phillips Curve

The evidence from the 1960s in the US seemed to confirm what Phillips had found in England. There was a very definite, although not perfect, negative relationship between the inflation rate and unemployment rate. This curve became viewed as a constraint on policy makers - another example of the "no-free lunch" concept. If policy makers wanted to reduce the unemployment rate, it would come at a cost of higher inflation. At this time professors were telling their students that Republicans favored macro policies to move the economy to point A because their supporters were not adversely affected by unemployment, while Democrats favored point B on the Phillips Curve because their constituents were adversely affected by higher unemployment. The 1960s was also a time where discussions focused on the definition of full employment and on policies to shift the Phillips curve. In the left side graph below, let's assume the economy has unemployment and inflation rates of 6 and 4%. Traditional macroeconomic policies could move the economy towards point B where we have been able to "buy" a lower inflation rate (4%) with a higher unemployment rate (6%). You could also use macro policy to buy lower unemployment with higher inflation (point A).

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As you know from your earlier discussion of the production possibility curves, there is another option - to alter the tradeoff by moving the Phillips curve inward. In the right-side graph the new Phillips Curve makes it possible to attain a 4% unemployment rate with inflation of 4% - clearly a preferred situation. But how do you do it? To understand the discussions of policies needed to shift the curve we need to recognize that all unemployed are not equal. A very popular classification scheme decomposed all unemployment into three components - frictional, cyclical, and structural unemployment. •

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Frictional unemployment is the unemployment resulting from people shifting jobs - the New England schoolteacher who moves to California, the car salesman who becomes a computer salesman, and the student who graduates and moves into the labor market. This has never been a concern of policy makers, and in fact it is taken as an indicator of the health of the economy since a healthy, vibrant, growing economy will require the continual movement of resources to the growing sectors. If the economy were to grow and change, there would always be some transitional unemployment, and this unemployment was viewed as the full employment rate of unemployment. Kennedy, in one of his speeches, pegged full employment as a 4% unemployment rate, and it tended to stick. Cyclical unemployment is the unemployment that occurs in recessions as output declines. The auto worker laid off because of inadequate auto demand, the construction worker who can find no work because of a slowdown in housing construction, the machine tool operator who lost her job as the decline in auto demand eliminated machine tool orders are examples of the cyclically unemployed. This is the unemployment that traditional monetary and fiscal policies were designed to minimize. In the Phillips Curve diagram, the movement of the economy into a recession would be seen as a movement along the curve from point A to point B. Structural unemployment is the unemployment resulting from significant structural changes in the economy. The agricultural worker whose work is now being done by a machine, the textile worker whose work is now being done by a worker in the Philippines, the auto worker whose job disappeared as imports from Asia soared, the inner city workers who have seen their jobs move to the suburbs and exurbs, and the high school graduates who cannot find work because low skilled jobs have disappeared are examples of structural unemployment. Even at the peak in a business cycle there are going to be some individuals who simply live in the wrong place or have the wrong skills. They experience severe difficulty finding employment and the level of this type of unemployment will not be as easily corrected by monetary and fiscal policies.xviii

So, how do we shift the curve inward? To see how this might happen, consider the situation in the mid 1980s when thousands of Americans were moving to Texas following the dreams of wealth and opportunity sold in the popular television show "Dallas." Unfortunately, these migrants found little opportunity in Texas that was in a severe recession. The nightly news was filled with stories of broken dreams, unemployment, and families who had moved to Texas for jobs living in their cars. The question facing policy makers was: how could we lower unemployment among these workers without increasing aggregate demand? One possibility would have been better information for the decision makers.

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Unemployment in Texas was the result of people making poorly informed decisions. If they had better labor market information, they may not have given up their jobs, or they may have known California was actually experiencing more rapid growth than Texas at that time and moved to California. A national clearinghouse for employment opportunities would certainly improve the tradeoff as people would be less likely to make the wrong choices that resulted in unemployment. A second possibility would be to raise the costs / lower the benefits of unemployment. Returning to our Texas example, if local officials put the unemployed up in the local Holiday Inn as they searched for work, they would take their time searching and remain unemployed for a longer time. Unemployment rates would therefore be reduced if people spent less time unemployed, which they would do with lower unemployment benefits. The increase in unemployment rates attributable to the widespread availability of unemployment benefits is an example of where there can be substantial unintended side effects associated with public policies. For the structurally unemployed there is a third possibility - worker retraining. Moving the structurally unemployed workers back into the labor market is the equivalent of trying to fit square pegs into round holes. Firms are looking for workers with a certain set of characteristics - good computer skills for example - and the structurally unemployed possess a very different array of skills. If the unemployed had the opportunity to retrain, then their stay on unemployment would be shorter and the unemployment rate lower. When confronted with a limited budget, however, the policy makers face a difficult choice. Do they use the limited funds to help the really needy, those beyond rehabilitation, or should they use the funds to help those living on the margin pass above the margin? Unfortunately, there is no easy answer and this problem will always plague retraining policies. Another troubling question was: what should be the target rate of unemployment? What would we define as full employment, which the Employment Act of 1946 set as the target for government policies? What was full employment? It certainly did not mean a zero unemployment rate, and by the early 1960s there was a general acceptance of the fact that 2% was unrealistic when John Kennedy set 4% as the level of full employment. In the 1980s the full employment rate of unemployment became a hotly debated issue, with conservatives pushing for a higher rate of full employment unemployment and liberals arguing for a lower one, but more about that in the 1980s unit. In addition to debates over the ability to shift the curve and the appropriate full employment target, there was also a debate about its slope. A steep Phillips Curve meant it would take large increases in inflation to reduce the unemployment rate, while a flat curve meant unemployment could be reduced with only small increases in inflation. Now think for a minute to think about what conservatives and liberals would say about the slope? Conservatives tended to favor the steep curve because it showed how difficult, or costly, it was to try to manage unemployment, while liberals favored a flatter curve, and in the 1970s this debate heated up. For those interested in getting a better understanding of the theory behind the Phillips Curve slope, you can read the next section before heading to the 1970s where we will see what happens when the world experiments with monetary policy.

Building in Expectations: A New Phillips Curve? (optional) By the end of the 1960s inflation had become a regular feature of the economy and some researchers picked up on the importance of expectations. Few would argue with the notion that expectations matter, and once we accept the importance of expectations, there is a need to explain how to build them into macroeconomic analysis. As a first step toward building in expectations, ask yourself the question: what will the weather be tomorrow? The simplest answer would be: tomorrow will be just like today. Your forecast for tomorrow is just what it is today. There's nothing exciting about this, but it is one way of capturing expectations and it was the dominant view among Keynesians. The formation of expectations on past experience is called adaptive expectations. For example, consider the problem of forecasting inflation. Inflation next period (i+1) would simply be equal to the current inflation rate (i). If the inflation rate last year was 5%, then you would expect it would be 5% this year.xix

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Adaptive expectations i+1 = i One of the weaknesses of this model of expectations is it is backward looking and people are always going to get fooled by any changes. If it was sunny yesterday and you brought no umbrella today, you would not enjoy your walk across campus in the rain. Unfortunately, with the adaptive expectations model, there was no way of anticipating the rain. Milton Freidman, in his presidential address to the American Economic Association in December of 1967, introduced inflationary expectations into macroeconomic thinking - a way of dealing with this backward looking problem - and what he "proved" was the policy tradeoff between inflation and unemployment - the Phillips Curve - was an illusion. The possibility of "buying" lower unemployment with inflation existed, but it was only temporary. It was the result of unexpected inflation "fooling" decision makers whose expectations adjusted to reality only slowly. The situation envisioned by Friedman is depicted in the diagram below. Let's start at point A with an unemployment rate of 5% and an inflation rate of 5%, a rate accepted as the prevailing inflation rate. If a policy maker wanted to lower the inflation rate to 3%, the Phillips curve provided a guide to the cost, which would be higher unemployment as the economy moved toward point B. The inflation rate was pushed below the expected rate (3% < 5%) and the unemployment rate rose to 6% as the economy contracted. How did this happen? It happened by fooling decision makers who were banking on an inflation rate of 5%. Workers bargaining for wage increases would want to be compensated for inflation so they would ask for wage increases of at least 5%. Businesses would pay the higher wages if their prices were also going up, but because inflation slowed to 3% their prices would be rising slower than wages. In this situation businesses would see the real cost of labor rise by 2% so they would hire fewer workers at the higher "real wage." The result is what the Phillips Curve predicted - lower inflation rates, higher unemployment, and lower employment (movement from pt. A to pt. B).

Phillips Curve II

But, those workers who were fooled this year, would build in the lower inflation rate of 3% when they bargain for wages next year. With prices and wages rising at 3%, we find businesses expanding employment and eventually we end up at the same level of employment, and unemployment, but now with a 3% inflation rate (movement from pt. B to pt. C). Once the new lower inflation rate has been built into the expectations, unemployment returns to its "natural rate" with a lower inflation rate and there would be a new short run Phillips curve depicted by the green dotted line. As Friedman noted in his analysis, Abraham Lincoln was correct when he said "you can fool all of the people some of the time, you can fool some of the people all of the time, but you can't fool all of the people all of the time." In the long run, however, there was no trade-off between inflation and unemployment because eventually people would "catch on" to the higher inflation rates. The result was a very different Phillips Curve - the vertical long-run Phillips Curves the red line labeled LR in the diagram. In the long run the economy simply moved from point A to point C, hence the belief that there was no trade-off.

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This innovation focused attention on the determinants of the natural rate of unemployment - the rate that would be sustainable and what became known as the nonaccelerating inflation rate of unemployment (NAIRU). It also focused attention on disinflation strategies - how do we move the economy from point A to C. What was clear from the analysis was that any effort to reduce inflation from 5% to 3% with traditional macro policy tools would get us to point C via point B, if the natural rate were 5%. For those wanting unemployment below 5%, the only way this could happen was with continually accelerating inflation so decision makers were continually fooled. The only sustainable unemployment rate was the natural rate, and any efforts to reduce unemployment below 5% required sustained increases in the inflation rate. So the liberal conservative debate shifted to the natural rate, with liberals seeing it as lower than conservatives. For example, if conservatives saw 5% as the natural rate and liberals saw 4% as that rate, then conservatives would say leave things alone if the unemployment rate was 5%, while liberals would push for a stimulus package. Unfortunately, it is easier to talk about the natural rate than it is to determine its actual value, and as a result the natural rate became a hotly debated issue - conservatives tending to push the rate upwards and Keynesians pushing the rate downwards. Friedman, in fact, in an article in the Wall Street Journal in 1996, stated: "[t]he natural rate is a concept that does have a numerical counterpart-but that counterpart is not easy to estimate and will depend on particular circumstances of time and place." Of equal importance was the speed of adjustment. The prospect of a painful, slow adjustment downward in inflationary expectations that we would get in a world with adaptive expectations would tend to limit the use of discretionary policies designed to wring inflation out of the system. The gradualism of Carter's anti inflation policies was grounded in a belief that lower inflation's short-term cost was high: if inflation was to be reduced, it would come at a substantial cost as the economy slowly adjusted its inflationary expectations. The problem was American people had come to expect inflation and built it into their thinking with workers building it into their wage demands and bankers building it into their interest rates. This was the sentiment reflected in Jacob Viner's statement: "In a world organized in accordance with Keynes' specifications, there would be a constant race between the printing press and the business agents of trade unions, with the problem of unemployment largely solved if the printing press could maintain a constant lead…" The limits to macro policies, both monetary and fiscal, were becoming evident by the late 1970s as the speed of the racers accelerated. It sounded so simple, a little money here - a little tax increase there and we could keep the economy on the straight and narrow growth track. But as we saw in the 1970s things didn't quite work out as planned. One of the problems we will look into is the policy dilemma faced by the Fed. Should the Fed worry about interest rates or money supply, because as we will see now, it could not worry about both.

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1960s Keynes II A considerable amount of information including audio of some important Kennedy speeches is available on-line at the JFK Library site. ii Walter Heller, New Dimensions of Political Economy, 1966 (1-2) iii Others, however, were less convinced of the merits of discretionary fiscal policy and the budget deficits associated with it. The concerns of the opponents are reflected in the testimony of Dan Throop Smith, former Assistant Secretary of the Treasury for Tax Policy under Eisenhower, before Senate Finance Committee in October of 1963. As Throop saw it, "The tax bill before you, ... seems on balance to be a bad piece of legislation. ... The country cannot afford economic experiments, which are almost certain at some time or other to weaken confidence in the dollar, both internally and externally.... [D]eficit spending...was tried and presumably discredited in the 1930s.... Not only is a large tax reduction foolhardy, it is also likely to be futile in dealing with the most serious aspects of our very real problem of unemployment. In recent months there has been increasing recognition of the fact that unemployment is concentrated in particular groups of the population... and [m]onetary and fiscal measures cannot solve the problems of structural...unemployment..." iv Kennedy had also been embroiled in a heated debate with steel industry executives after they ignored the guidepost programs for wages and prices and raised steel prices in April of 1962. Although Kennedy faced down the executives, the general outlook was grim. A sense of urgency was added in the summer of 1962 after the stock market sustained its sharpest single-day decline since 1929. v This is why you see a consumption function of the form C = a + b*Y become a standard feature of macroeconomic models. If you look at the scatter diagram and think about drawing a line that passes through the points, a would be the intercept and b would be the slope. Of these two parameters, it was the slope Keynesians focused attention on since this was the marginal propensity to consume (MPC) at the center of the Keynesian multiplier concept. But there were some potential problems. First, there was the fear of stagnation that seemed to be the logical conclusion to be drawn from the model. To understand the nature of the perceived problem, let us simply divide the consumption equation above by Y to obtain the equation specifying consumption's share of total income. C/Y = a/Y + b As the economy expands, consumption's share of total income will fall because the term a/Y declines as Y increases. If this happens, then one of the other components of aggregate demand would need to increase faster than the economy to keep the economy from stagnating. Stated a bit differently, since the MPC was less than 1, as income increase consumption would increase more slowly. If the economy was to continue to expand, there would need to be above average increases in the other components of aggregate demand or growth would be slowed. The logical choice would have been the government, but this triggered concerns about the growth in the size and scope of government involvement in the economy. vi Once we accept the intertemporal nature of consumption decisions, another factor exerting a potential impact on consumption spending is the structure of the capital market. If it is easy to borrow funds, you would expect that consumption spending would tend to be higher. If you think of social security as a policy designed to make it very easy for individuals to live beyond their earned income after retirement, then you would expect that social security systems would lower savings and increase consumption. Similarly, the greater down payments that Asian households must pay for their homes reduces current consumption spending and raises savings. The wealth effect has been estimated by Christopher Carroll, Misuzu and Jirka Slacalek and it is in line with other estimates that show housing's wealth effect is about 3 times that of stocks - and the wealth effect from housing is larger in the US, probably because of easier refinancing which makes the homes more liquid, and it has been rising as more people begin to see their homes as investments. Another study appears in the January 19, 2007 FRBSF Economic Letter. vii To understand the relationship between interest rates and investment spending all you need to do is use one of the online financial calculators to determine the influence of interest rates on monthly mortgage payments. I did and here is what I found. If the interest was 7%, then my monthly payment on a 30-year, $250,000 mortgage would be $1,663 a month. If the interest rate dropped to 5%, then the monthly payment drops to $1,342. So I can either now use that extra 4200 a month to buy more "stuff," or I can buy a more expensive house. At 5% interest, I could now afford a house of $300,000 that would give me a monthly payment of $1,610. Either the drop in interest rates would get me to spend on 'stuff" or spend on homes, but in both cases this would lead to more spending and more jobs. And I will let you do the math when the Fed raises interest rates as they did in 2005-2006. viii Inventory investment is the key link between the macro identities outlined earlier and the equilibrium conditions that are at the heart of the macroeconomic models. By definition, any mismatch between production and consumption shows up as a change in inventories. Included here would be desired changes in inventory, such as inventory reductions reflecting the move toward just-in-time production, and undesired changes, such as automobiles that accumulate in GM lots due to a drop in demand. Only when there is no undesired change in inventories, will we find ourselves in equilibrium. We can see the importance of changes in inventory investment with the following equations - one for equilibrium and one an identity. Equilibrium Y = C + Id + G + X - M i

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Identity Y = C + It + G + X - M They look almost identical, the only difference being that the identity includes total investment spending ( It ) and the equilibrium condition includes desired investment (Id). The link between the two is that total investment equals desired plus undesired changes in inventory. Given this definition you can see that equilibrium occurs when there is no undesired change in inventories. ix Casti looked at a wide array of forecasts by researchers / scientists in a number of fields and attempted to evaluate their forecasts. At the head of the class were Quantum mechanics and Celestial mechanics where the forecasters received an A. Those specializing in forecasting the stock market found themselves in the middle of the pack with a grade of C+, slightly better than the C- received by those in the business of forecasting war x The Department of Labor must have been "on the same page" as Fisher when in the same year it forecast "1930 will be a splendid year for employment." And things didn't seem to improve once the crash happened. According to the Chairman of Continental Illinois Bank, “This crash [of 1929] is not going to have much effect on business,” while Samuel Arnot, president of Chicago Board of Free Trade, in his new year’s message in 1930, indicated “This nation has entered an era of vast industrial expansion." For those interested in some additional forecasts that proved to be wide of the mark, you might check out Technology and Change, Famous Predictions From Throughout History, Bold Moves: What Governments might accomplish in the next 50 years, and the OECD International Futures Programme's publication in 2000, Looking back at looking forward. xi A few others I enjoy. • "there will be no epidemics. There will be no incurable diseases." Ladies Home Journal 1931 • "Why on earth would you care about the personal computer? It has nothing to do with office automation... in my opinion we don't belong in the personal computing business." IBM official 1980 • "In reaching a saturation point in the demand for possessions, we are already facing unemployment. This could rise to 50% of the population by 2000." M/ W. Thuring in Man, Machines, and Tomorrow 1973. • "Television won't be able to hold on to any market it captures after the first six months. People will soon get tired of staring at a plywood box every night." Darryl Zanuck, head of 20th Century Fox 1946 • "The wireless music box has no imaginable commercial value. Who would pay for a message sent to nobody in particular? David Sarnoff's associates response to his urgings for investment in radio on the 1920s. • "I see no advantage whatsoever to the graphical user interface." Bill Gates 1983 • sewife [in the year 2000] cleans house she simply turns the hose on everything." Popular Mechanics in 1950 • "By 2000... Sonic cleaning devices and air-filtering systems will banish dirt and just about eliminate dusting, scrubbing, and vacuuming... Dishwashing will be a thing of the past, since disposable dishes will be made from powdered plastic for each meal by a machine in the kitchen." Wall Street Journal 1966 • "I predict the Internet will go spectacularly supernova & catastrophically collapse on 1996." Bob Metcalfe, inventor of ethernet at InfoWorld 1995. • "Electric light will never take the place of gas." Werner von Siemens • "Anyone suggesting that artificial satellites will ever become inexpensive enough to permit cost-effective global communications needs to have their head examined..." NYT 1948 • "By the turn of the century we will live in a paperless society." Roger Smith, chairman of GM 1986 • "The question has been raised whether the cost of manufacture in a country like Germany might reach the point where, through evolution, motor cars could be produced and sold in competition in the American market... In my opinion it is impossible to reach the conclusion that competition from without can ever be any factor." Alfred Sloan, President of GM in 1929 • "Remote shopping, while entirely feasible, will flop because women like to get out of the house, like to handle merchandise, like to be able to change their minds." Time Magazine 1966 As bad as these forecasts were, they may not be the worst. In terms of picking winners, things seemed to be especially bad in the entertainment industry where the new technologies and stars were often missed. • "Who the hell wants to hear actors talk?" H. M. Warner, Warner Brothers 1927 • "It will be gone by June." Variety magazine on rock 'n roll in 1955 • "You ain't going nowhere son - you ought to go back to driving a truck." Jimmy Denny, Manager of Grand Ole Oprey, on firing Elvis Presley after one performance in 1954 • "Forget it. No Civil War picture ever made a dime." MGM executive advising against Gone With the Wind 1932 xii If you are interested in long-term forecasts, then you should check out scenario planning at the Shell website's section on scenario planning - Energy Needs, Choices and Possibilities - scenarios to 2050. Another approach to long-term forecasting is proposed by those who believe that all patterns of change should be set against the backdrop of Kondratieff cycles - a concept attributed to the work of a Russian economist. The "short" version of the story is the economy follows a reoccurring cyclical pattern with four phases described by Chapman as follows.

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Inflationary Growth (expansion): - stable to slow rising prices, low commodity prices, low and stable interest rates, rising stock prices. The period might also be characterized by strong and growing corporate profits and technological innovations. 2. Stagflation (recession): - rising prices, rising commodity prices, rising interest rates, stagnant to falling stock prices. Stagnant profits, rising debt. This period usually sees a major war that contributes to the commodity and price inflation, and to the rising debt and misdirects business resources. 3. Deflationary Growth (plateau): - stable to falling prices, falling commodity prices, falling interest rates, sharply rising stock prices, profit growth but probably not as good as in the inflationary growth phase. Sharply rising debt. Possible period of considerable technological innovation. Excess debt contributes to speculative bubbles. 4. Depression (depression): - falling prices, rising commodity prices (particularly gold), stable interest rates, falling stock prices, falling profits, debt collapse. As the stock market collapses numerous scandals will emerge. A major war occurs that helps contribute to end of the depression phase and the start of the new expansion period. With four distinct phases in the K-wave a number of analysts have compared them to the seasons. Spring (inflationary growth, expansion), summer (stagflation, recession), autumn (deflationary growth, plateau) and winter (depression). At the Evolutionary World Politics Homepage you will find the following description of three features of the Kondratieff (K-waves). 1. K-waves unfold as phased processes that imply S-shaped growth (or learning) curves, including for each particular sector, and over a period of some 50-60 years, a period of slow start-up, followed by fast growth, and ultimate leveling-off. That is why they are waves of economic activity, each wave different in kind from the last one, rather than cycles, seen as mechanical fluctuations in attainment of some uniform quantity. The start-up period of the next leading sector is also the period of flattening growth rates, declining profits, and severe competition for the previous lead industry; this transition between two leading sectors peak may be known as downswing, and takes the form of generalized slow-down and in the 1930s, of the Great Depression. 2. K-waves arise from the bunching of basic innovations that launch technological revolutions that in turn create leading industrial or commercial sectors. In Schumpeter’s classic formulation, such innovations concern new products, services, and methods of production, the opening of new markets and sources of raw materials, and the pioneering of new forms of business organization. In that sense, K-waves are caused by the demand for solutions to new problems, and the supply of such solutions by innovative firms. Each such wave therefore has its own individual innovative character, and can be named accordingly (consult Table 1 for such a listing). K-waves have their own characteristic location in space and time. Britain’s cotton wave was centered on Manchester. The information K-wave is preferentially seen in such locations as Silicon Valley and Orange County in California. xiii Below is a description appearing in the Conference Board's April 18, 2002 report. Six of the ten indicators that make up the leading index increased in March. The positive contributors to the leading index - from the largest positive contributor to the smallest - were average weekly manufacturing hours, stock prices, interest rate spread, index of consumer expectations, vendor performance, and manufacturers' new orders for consumer goods and materials*. The four negative contributors to the index - beginning with the largest negative contributor were building permits, average weekly initial claims for unemployment insurance (inverted), real money supply*, and manufacturers' new orders for nondefense capital goods*. xiv Walter Mondale made the mistake of telling the American people that the budget deficit would "force" the winner of the 1984 presidential election to raise taxes, while Reagan told them he would not raise taxes. The American people responded by giving Reagan a second term and Reagan responded by raising taxes. Mondale turned out to be right, but he paid the ultimate political price. xv Temporary tax changes were also something Japanese policy makers believed Japan could live with in the 1990s. These officials pinned their hopes on a temporary tax cut for households to jump start Japan's economy mired in a decade long recession. It turned out not to work, just as the Johnson surtax did not work in 1968. To understand the situation, consider what someone would do if the government announced this year they would impose a one-time tax of $200 and compare it to what you would expect to happen if the tax increase were permanent that every year for the rest of your life you would pay an additional $200 in taxes. The key to the answer is one's view of consumption spending, or more specifically, the relationship between income and consumption. As Keynes' ideas were interpreted by the early practitioners, consumption today depended on income today and any change in today's income would change today's consumption. As we saw in the detailed treatment of aggregate demand section, some economists challenged this view and suggested that individuals tend to take a longer view when making their spending decision and attempt to spread their consumption spending out evenly over their lifetime, even if their income was unevenly distributed. Individuals tend to make the most during their middle ages so you could expect that in their younger and older years people would '+,' and during their peak years they would save. Furthermore, individuals have a sense of what they will make over their lifetime and this is what influences their spending. In both cases the link between current consumption and current

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income is weakened. If the income change would not substantially change lifetime, or permanent income, then it would not appreciably change current spending. xvi In the graph below, the expansionary impact of the policy should, in theory, take place at point A, but if it did not take effect until point B when the economy had already turned up, then it would tend to raise the growth trajectory. Similarly, if the decision was made to slow down the economy at point C, but the policy did not take effect until point D, then the contractionary policy would have accentuated the downturn xvii "The Relation between Unemployment and the Rate of Change of Money Wages in the United Kingdom, 18611957" xviii One of the features of the long expansion in the 1990s was the high level of structural change that tended to put downward pressure on employment gains during the years of economic growth. Accompanying the traditional job gains during the expansion were job losses associated with downsizing. xix How about a little more "realistic" approach? What if you saw a trend when you looked backward? Would you assume it would continue and build it into your expectations? You could, and you would have the basis for a slightly more complicated model of adaptive expectations model. According to this model, expected inflation (i +1) is equal to the current rate (i) plus the change in inflation between this year (i) and last (i-1). If the inflation rate last year was 5% and the year before it was 3%, then you would expect that it would be 7% [ 7 = 5 +(5-3)]. Adaptive expectations II i+1 = i + (i - i-1 )

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