Money and Banking Chapter 24 Monetary Policy Transmission Mechanisms

Chapter 24 Monetary Policy Transmission Mechanisms CHAPTER OBJECTIVES By the end of this chapter , students should be able to . Explain why structural models are generally superior to models . Describe the types of evidence that can strengthen researchers conviction that a model has the direction of causation right , say , from money ( to output ( Describe the evidence that money matters . List and explain several important monetary policy transmission mechanisms . URL books 496

Modeling Reality LEARNING OBJECTIVE . Why are structural models generally superior to models ?

We ve learned in the last few chapters that monetary policy is not the and of the economy or even of attempts to manipulate it . But we knew that before . The question before us is , Given what we know and , just how important is monetary policy ?

And how do we know ?

We ve got theories about how changes in sundry variables , like interest rates , create certain outcomes , like changes in prices and aggregate output . But how well do those theories describe reality ?

To answer those questions , we need empirical evidence , good hard numbers . We also need to know how scientists and social scientists evaluate such evidence . Structural models explicitly link initial cause all the way via every intermediate step along the causal chain . evidence makes assertions only about initial causes and ultimate , treating the links in between as an impenetrable black box . The quantity theory makes just such a claim when it asserts that , as the money supply increases , so too does output . In other words , the quantity theory is not explicit about the transmission mechanisms of monetary policy . On the other hand , the assertion that increasing the money supply decreases interest rates , which spurs investment , which leads to higher output , is a structural model . Such a model can be assessed at every link in the chain up , i down , I up , up . If the relationship between and begins to break down , economists with a structural model can try to figure out why . Those touting only a model will be . Structural models also strengthen our confidence that changes in cause changes in . Because they leave so much out , models may point only to variables that are correlated , that rise and fall in tandem over time . Correlation , alas , is not causation the link between variables that are only correlated can be easily broken . All sorts of superstitions are based on mere correlation , as their practitioners eventually discover to their chagrin and loss , like those who wear rally caps to win baseball games . Reverse causation is also rampant . People who see URL books 497

a high correlation between and often think that causes when in fact causes . For example , there is a high correlation between fan attendance levels and home team victories . Some take this to prove that high attendance causes the home team to win by acting as a sixth , tenth , or twelfth player , depending on the sport . Fans have swayed the outcome of a few games , usually by touching baseballs still in play , but the causation mostly runs in the other that win many games tend to attract more fans . Omitted variables can also cloud the connections made by models . Caffeine drinkers have higher rates of coronary heart disease ( than people who don consume caffeine is a model that probably suffers from omitted variables in the form of selection biases . In other words , caffeine drinkers drink caffeine because they don get enough sleep have hectic , stressful lives and so forth . It may be that those other factors give them heart attacks , not the caffeine per se . Or the caffeine interacts with those other variables in complex ways that are difficult to unravel without growing human beings in test tubes ( even more ) Stop and Think Box A recent study shows a high degree of correlation between smoking marijuana and bad life outcomes long stints of unemployment , criminal arrests , higher chance of disability , lower lifetime income , and early death . Does that study effectively condemn pot smoking ?

Not nearly as much as it would if it presented a structural model that carefully laid out and tested the precise chain by which marijuana smoking causes those bad outcomes . Omitted variables and even reverse causation can be at play in the version . For example , some people smoke pot because they have cancer . Some cancer treatments require nasty doses of chemotherapy , the effect of which is to cause pain and reduce appetite . Taking a toke reduces the pain and restores appetite . Needless to say , such people have lower life than people without cancer . Therefore , they have lower lifetime income and a higher chance of disability and unemployment . Because not all states have medical marijuana exceptions , they are also more liable to criminal arrest . Similarly , unemployed people might be more likely to take a little Mary Jane after lunch or perhaps down a couple of cannabis brownies for dessert , again reversing the direction of causation . A possible omitted variable is selection bias people URL books 498

who smoke pot might be less educated than those who abstain from the weed , and it is the dearth of education that leads to high unemployment , more arrests , and so forth . Unfortunately , bad science like this study pervades public discourse . Of course , this does not mean that you should go get yourself a blunt . Study instead . Correlation studies show that studying . KEY TAKEAWAYS Structural models trace the entire causal chain , step by step , allowing researchers to be pretty confident about the direction of causation and to trace any breakdowns in the model to specific relationships . models link initial variables to supposed outcomes via an impenetrable black box . The problem is that correlation does not always indicate causation . may increase and decrease with , although does not cause because may cause ( reverse causation ) or ( an omitted variable ) may cause and models can and have led to all sorts of goofy conclusions , like doctors kill people ( they seem to be ubiquitous during plagues , accidents , and the like ) and police officers cause crime ( the number on the streets goes up during crime waves , and they are always at crime suspicious ) In case you ca tell , I being sarcastic . On the other hand , models are inexpensive compared to structural ones . wiki ca URL books 499

How Important Monetary Policy ?

LEARNING OBJECTIVES . What types of evidence can strengthen researchers conviction that a model has the direction of causation right , say , from to ?

How ?

What evidence is there that money matters ?

Early believed that monetary policy did not matter at all because they could any evidence that interest rates planned business investment . Milton and Anna Schwartz , another , countered with a huge tome called A Monetary History of the United States , 1960 which purported to show that the had it all wrong , especially their kooky claim that monetary policy during the Great Depression had been easy ( low real interest rates and growth ) Nominal rates on risky securities had in fact soared in , the depths of the depression . Because the price level was falling , real interest rates , via the Fisher Equation , were much higher than nominal rates . If you borrowed 100 , you have to repay only 102 in a year , but those 102 smackers could buy a heck of a lot more goods and services a year hence . So real rates were more on the order of to 10 percent , which is pretty darn high . The link between interest rates and investment , the showed , was between investment and real interest rates , not nominal interest rates . As noted above , the early relied on , a model . To strengthen their conviction that causation indeed to or some unknown to Mand , the relied on three types evidence timing , statistical , and historical . Timing evidence tries to show that increases in happen before increases in , and not vice versa , relying on the commonplace assumption that causes occur before their effects . and Schwartz showed that money growth slowed before , but the timing was highly variable . Sometimes slowing money growth occurred sixteen months before output turned south other times , only a few months passed . That is great stuff , but it is hardly foolproof because , as Steve Miller points out , time keeps on slipping , slipping , slipping , into the future . Maybe a decline in output caused the decline in the money supply . Changes in and , in other words , could be causing each other in URL books 500

a sort of virtuous or pernicious cycle or problem . Or again maybe there is a mysterious variable running the whole show behind the scenes . Statistical evidence is subject to the same criticisms plus the old adage that there are three types of untruths ( besides Stephen truthiness , of course ) lies , damn lies , and statistics . By changing starting and ending dates , the difference between statistical significance and economic , manipulating the dates of structural breaks , and introducing who knows how many other subtle little , researchers can make mountains out of , and vice versa . It kinda funny that when used statistical tests , the quantity theory won and money mattered , but when the early conducted the tests , the quantity theory looked , if not insane , at least inane . But and Schwartz had an empirical ace up their sleeves historical evidence from periods in which declines in the money supply appear to be exogenous , by which economists mean caused by something outside the model , thus eliminating doubts about omitted variables and reverse causation . scientists ( you know , physicists , chemists , and so real scientists ) know that variables change exogenously because they are the ones making the changes . They can do this systematically in dozens , hundreds , even thousands of test tubes , Petri dishes , atomic acceleration experiments , and what not , carefully controlling for each variable ( making sure that everything is ) then measuring and comparing the results . As social scientists , economists can not run such experiments . They can and do turn to history , however , for natural experiments . That what the did , and what they found was that exogenous declines in led to ( lower ) every time . Economic and history wins ! Disclaimer One of the authors of this textbook Wright is a historian . While they did not abandon the view that , I , and also affect output , now accept money role in helping to determine . A new group , the theorists associated with the Fed , has recently challenged the notion that money matters , but those folks haven made it into the land of undergraduate textbooks quite yet . KEY TAKEAWAYS Timing , statistical , and historical evidence strengthen researchers belief in causation . URL books 501

Timing evidence attempts to show that changes in occur before changes in . Statistical evidence attempts to show that one model predictions are closer to reality than another . The problem with stats , though , is that those running the tests appear to rig them ( consciously or not ) so the stats often tell us more about the researcher than they do about reality . Historical evidence , particularly natural experiments in which variables change exogenously and hence are analogous to controlled scientific experiments , provide the best sort of evidence on the direction of causation . The showed that there is a strong correlation between changes in the and changes in and also proffered timing , statistical , and historical evidence of a causal link . Historical evidence is the most convincing because it shows that the sometimes changed exogenously , that is , for reasons clearly unrelated to or other plausible causal variables , and that when it did , changed with the expected sign ( if increased , if it decreased ) wiki Truthiness URL books 502

Transmission Mechanisms LEARNING OBJECTIVE . What are monetary policy transmission mechanisms and why are they important ?

Most economists accept the proposition that money matters and have been searching for structural models that delineate the transmission mechanisms between and . The most basic model says the following Expansionary monetary policy ( EMP ) real interest rates down , investment up , aggregate output up The importance of interest rates for consumer expenditures ( especially on like autos , refrigerators , and homes ) and net exports has also been recognized , leading to the following EMP , i , the market value divided by the replacement cost capital , is clearly analogous to i and related to I . When is high , firms sell their highly valued stock to raise cash and buy new physical plant and build inventories . When is low , by contrast , don get much for their stock compared to the cost of physical capital , so they don sell stock to fund increases in I . By increasing stock prices , the may be positively related to . Thus , another monetary policy transmission mechanism may be the following EMF . PST The wealth is a transmission mechanism whereby expansionary monetary policy leads to increases in the prices , homes , collectibles , and other assets , in other words , an increase in individual wealth . That increase , in turn , induces people to consume more EMP , Pa , wealth , The credit view posits several straightforward transmission mechanisms , including bank loans , asymmetric information , and balance sheets EMP , bank deposits , bank loans , I , URL books 503

EMP , net worth , asymmetric information , lending , I , EMP , i , cash , asymmetric information , lending , I , EMP , unanticipated , real net worth , asymmetric information , lending , I , Asymmetric information ( that horrible hound from Hades ) is a powerful and important theory , so scholars in these transmission mechanisms is high . Stop and Think Box The Fed thought that it would quickly squelch the recession that began in March 2001 , yet the downturn lasted until November of that year . The terrorist attacks that September worsened matters , but the Fed had hoped to reverse the drop in well before then . Why was the Feds forecast overly optimistic ?

Hint Corporate accounting scandals at , Arthur , and other were part of the mix . The Fed might not have counted on some major monetary policy transmission mechanisms , including reductions in asymmetric information , being muted by the accounting scandals . In other words , EMP , net worth , asymmetric information , lending , I , EMP , i , cash , asymmetric information , lending , I , EMP , unanticipated , real net worth , asymmetric information , lending , I , became something more akin to the following EMP , net worth , asymmetric information ( or no change ) lending , I , EMP , i , cash , asymmetric information , lending , I , EMP , unanticipated , real net worth , asymmetric , lending , I , because asymmetric information remained high due to the fact that economic agents felt as though they could no longer count on the truthfulness of corporate financial statements . The takeaway of all this for monetary , and those interested in their policies ( including you , as you know from Chapter Money , Banking , and Your World ) is that monetary policy needs URL books 504

to take more into account than just interest rates . need to worry about real interest rates , including rates unexpected changes in the price level the interest rates on risky bonds the prices of other assets , including corporate equities , homes , and the like the quantity of bank loans and the bite of adverse selection , moral hazard , and the problem . Stop and Think Box Japan economy was going gangbusters until about 1990 or so , when it entered a economic funk . To try to get the Japanese economy moving again , the Bank of Japan lowered interest rates all the way to zero for many years on end , to no avail . Why didn the Japanese economy revive due to the monetary stimulus ?

What should the Japanese have done instead ?

As it turns out , i , stayed quite high because the Japanese expected , and received , price . Through the Fisher Equation , we know that i , i , or real interest rates equal nominal interest rates minus expectations . If ne is negative , which it is when prices are expected to fall , ir will be i . So i can be but ir can be , 10 percent per year if prices are expected to decline by that much . So instead of EMP , i . I , the Japanese experienced i , I , Not good . They should have pumped up the much faster , driving from negative whatever to zero or even positive , and thus making real interest rates low or negative , and hence a stimulant . The Japanese made other mistakes as well , allowing land and equities prices to plummet , thereby the and wealth effect transmission mechanisms . They also kept some big shaky banks from failing , which kept levels of asymmetric information high and bank loan levels low , squelching the credit channels . KEY TAKEAWAYS Monetary policy transmission mechanisms are essentially structural models that predict the precise chains of causation between expansionary monetary policy ( EMP ) or tight monetary policy ( and . They are important because they provide central bankers and other monetary with a detailed View of how changes in the affect , allowing them to see why some policies do work as much or as quickly as anticipated . That , in turn , allows them to become better , to the extent that is possible in a world of rational expectations . See Chapter 26 Rational Expectations Redux Monetary Policy Implications . Transmission mechanisms include URL books 505

EMP , EMP , I EMP , Pa , wealth I , WI EMP , bank deposits , bank loans , I I , I EMP , net worth I , asymmetric information , lending I , I I , I EMP , i , cash flow I , asymmetric information , lending , I I , I EMP , unanticipated , real net worth I , asymmetric information , lending I , I , I URL books 506

Suggested Reading , and . Monetary Policy Transmission in the Euro Area . New York Cambridge University Press , 2004 . Milton , and Anna Schwartz . A Monetary History of the United States , Princeton , Princeton University Press , 1971 . and Peter Sinclair . Monetary Transmission in Diverse Economies . New York Cambridge University Press , 2002 . URL books 507