Homework 6 and solution.
December 01, 2011
November 30, 2011
November 29, 2011
November 28, 2011
November 21, 2011
November 16, 2011
November 11, 2011
November 10, 2011
November 09, 2011
November 07, 2011
Class Materials for Lecture 12
Brief Outline of Topics Covered in Lecture 12
Chapter 21 Output, Inflation, and Monetary Policy
The AE curve (also called the IS curve)
- Investment, consumption and the interest rate
- Net exports and the interest rate
- Shifts in the IS curve
- Slope of IS curve
The Monetary Policy Reaction Curve
- The Fed's reaction to inflation and output
- Shifts in the MP curve
- Slope of MP curve
Video:
Additional Reading:
- End Bonuses for Bankers - Nassim Taleb
- Who is Screwing Up More: Europe or the US? - Jeff Frankel
- Bankruptcy of the Greek government vs California - Dani Rodrik
- "What can exports tell us about the economy?" - Econbrowser
- Is Overregulation Driving U.S. Companies Offshore? - NYTimes.com
- The myth of financial innovation and the Great Moderation - Vox EU
- Remaining Risks in the Tri-Party Repo Market - Liberty Street
- Bailouts: Geithner vs Barofsky - Felix Salmon
- Brains Built To Cooperate - Scientific American
- Thinking, Fast and Slow - Bill Easterly
- Autos, housing, and the business cycle - Econbrowser
- Why Spotting Bubbles Is Harder Than It Looks - WSJ.com
- The Polarization of Job Opportunities - David Autor
- Overcoming the Great Disconnect - Thoma - Public Sphere Forum
- The Economics Public Sphere - The Monkey Cage
- Artificial intelligence: Luddite legacy - The Economist
- Economists Debate Slowing Release Of US GDP Report - NASDAQ
- The Lasting Financial Impact of a Layoff - NYTimes.com
Application:
Via the SF Fed:
What Moves the Interest Rate Term Structure?, by Michael Bauer, Economic Letter, FRBSF: To understand the effects of news on bond markets, it is instructive to look beyond individual maturities and consider the entire term structure of interest rates. For example, unexpected changes in monthly nonfarm payroll employment numbers cause large movements at short and medium maturities, but do not affect long-term interest rates. Inflation news affects the long end of the term structure. Monetary policy actions vary in their effects on interest rates, but cause volatility at all maturities, including distant forward rates.
Daily changes in various interest rates are a staple of the financial news. But what causes these constant up-and-down movements? The underlying determinants are factors such as prospects for economic growth, expectations regarding inflation and monetary policy, and compensation for risk. Interest rates change as market participants receive new information about these factors. Often, various interest rates move together in the same direction.
However, there is more to interest rate changes than direction and magnitude. Bonds that mature at different time horizons do not move in lockstep. Much can be learned by looking at changes in the term structure of interest rates, that is, the entire range of rates from short maturities to long. Sometimes short-term interest rates move strongly and the long end of the term structure barely shifts. At other times, the short end remains anchored and the action is only in medium- and long-term rates. Identifying changes in interest rates across the maturity spectrum can be useful when assessing the impact of news on market expectations about the macroeconomy and future monetary policy. This Economic Letter looks at how different types of news affect interest rates across maturities.
Shifts in the term structure of interest rates
Yields on U.S. Treasury securities typically receive the most attention in reporting on the fixed income markets. Treasury security maturities range from less than a month to about 30 years. Gürkaynak, Sack, and Wright (2007) have constructed a useful data set of Treasury security yields and forward rates based on the prices of these securities. The data set is updated every day and publicly available at http://www.federalreserve.gov/econresdata/researchdata.htm.
To get a better picture of the effects of news on interest rates at different time horizons, I look at forward interest rates. Forward rates are rates contracted today for a loan made or security issued at a specified future date. A forward rate with, say, two years maturity is the interest rate that would be contracted for today on an overnight loan to be extended in two years. Conceptually, the forward interest rate is determined by expectations about the real short-term interest rate and the rate of inflation two years in the future. The rate also includes compensation for the interest rate risk of a two-year commitment. Changes in forward rates with different maturities reflect expectations of inflation and monetary policy at specific time horizons.
Figure 1
Interest rate changes on July 8, 2011
For example, consider the employment report released on July 8, 2011, in which the U.S. Bureau of Labor Statistics (BLS) reported that total nonfarm payroll employment increased by 18,000 in June. This fell well short of the consensus forecast for a 105,000 increase in payroll positions and was interpreted as bad news regarding the pace of economic recovery. Figure 1 shows the daily changes between July 7 and July 8, 2011, in hundredths of a percentage point for one- to ten-year Treasury yields and forward rates one to ten years ahead. All yields decreased, but by different magnitudes.
To get a better idea of the interest rate movements across horizons, I consider forward rates instead of yields. A forward rate is about one specific future point in time whereas yields are averages of forward rates. Thus forward rates offer clearer information about different horizons. On July 8, following the BLS employment report, the largest movements occurred in forward rates two to four years ahead. Changes at the longer end of the term structure eight to ten years out were much smaller. To the extent that these yield changes reflect shifting expectations for future short-term interest rates, the June employment report caused market participants to lower their anticipated path for the Federal Reserve’s policy rate, the federal funds rate, most dramatically at the two- to four-year horizon.
Macro surprises and the response of the term structure
Figure 2
Responses of forward rates to surprises
A. Payroll News
B. Core CPI News
The employment report example demonstrates a typical pattern. Interest rates respond to macroeconomic surprises in a pro-cyclical fashion. That is, yields fall in response to weaker-than-expected data and rise in response to stronger-than-expected data. Several empirical studies have documented this pattern. Balduzzi, Elton, and Green (2001) studied the response of some specific Treasury yields to macroeconomic announcements using a now standard event study methodology. The authors constructed a measure of surprise based on the difference between actual data and the median forecast in surveys prior to the data release, standardized to be comparable across different releases. They then performed a statistical exercise to measure the responses of Treasury yields to the macroeconomic surprises. Studies of this sort typically find that short-term yields respond little, but long-term yields react strongly to macroeconomic data surprises.
To go beyond individual yields, I estimate the responses across the entire term structure, and capture changes in all interest rates. Most of the variation in interest rates is captured by just a few underlying statistical factors. Based on this idea, it is possible to build a model that calculates the responses to economic data releases of Treasury security yields and forward rates across the entire term structure (see Bauer 2011).
Figure 2 shows the response of the forward rate curve to surprises in payroll employment and to the core consumer price index (CPI), which excludes food and energy. The dashed lines indicate the model’s predictions with 95% confidence. Forward rates at short and medium horizons show large and significant responses to surprises in nonfarm payrolls. The strongest response, around 0.07 percentage point, occurs at a maturity of about two years. Notably, far-ahead forward rates at horizons longer than six years do not significantly respond to the employment news. On the other hand, responses to core CPI inflation surprises are smaller in magnitude, but extend to the long end of the maturity spectrum. Distant forward rates show a small but statistically significant increase of about 0.015 percentage point to a higher-than-expected core CPI.
Thus, this model suggests an important difference between the effects of employment news and inflation news on interest rates. While employment news causes large responses, only inflation news affects the long end of the term structure (see Bauer 2011). This result contrasts with the findings of other studies regarding the long forward rate response to economic news (see Gürkaynak, Sack, and Swanson 2005).
Monetary policy actions
Monetary policy actions, such as changes in the federal funds target, releases of Federal Open Market Committee (FOMC) statements, or speeches by committee participants, often contain new information relevant to financial markets. Importantly, while the Fed has direct control only over the federal funds rate, it can also affect interest rates at other maturities by changing expectations of future monetary policy. How does monetary policy affect the term structure? In what way does it affect longer-term interest rates, which are crucial in determining lending costs and mortgage rates, and strongly influence economic behavior? Looking at the entire term structure of forward rates reveals how much news about monetary policy changes perceptions of economic fundamentals and affects rates at different horizons. Specifically, changes in the term structure show whether policy actions directly affect distant forward rates or whether the effects die after medium horizons.
An important difference exists between macroeconomic news and monetary policy news. We can quantify economic surprises, but we do not have a measure that satisfactorily captures all aspects of policy surprises. The language of FOMC statements and speeches cannot easily be quantified. To capture the surprise component, researchers have focused on how policy actions affect financial markets (see Kuttner 2001). Thus, to assess the effects of policy actions, I employ the same model-based methodology I used with employment and inflation news, examining changes across the entire term structure of interest rates as policy surprises were made public.
Figure 3
Effects of monetary policy actions on forward rates
Figure 3 shows the effects on forward rates of three Fed moves in 2007 to lower the federal funds target: a half percentage point cut on September 18, a quarter percentage point cut on October 31, and another quarter percentage point cut on December 11. These three easing actions had very different effects on the term structure. In September, the size of the cut surprised market participants. Short-term rates fell, but longer forward rates actually increased, which may have reflected an upward revision in expectations about economic growth. In October, forward rates at short and medium horizons increased on the day of the meeting, probably because markets had expected a larger federal funds rate move or a change in the language of the Fed’s policy statement. Thus, monetary policy was viewed as tighter than previously anticipated. Markets had anticipated the Fed’s December cut, so the short end of the term structure did not move much. But medium and longer-term forward rates fell significantly. Changing statement language apparently led market participants to expect much easier monetary policy over the medium and long horizons.
This variability of term structure shifts is typical of the effects of monetary policy on interest rates. This reflects the fact that policy actions are inherently multidimensional. Markets must consider both a federal funds rate decision or other policy action and an FOMC statement whose language may have changed from previous statements. The effects of policy actions and statements vary based on market expectations. The strongest effects occur when market participants are surprised. This makes monetary policy actions complex objects that affect the term structure of interest rates in highly variable ways. The complexity of monetary policy would also be apparent from the movements of inflation-adjusted interest rates, inflation expectations, and other asset prices.
Figure 4
Forward rate variability
Are there systematic effects of monetary policy on the term structure? Considering policy-driven interest volatility is helpful in answering this question. Figure 4 compares the forward rate volatilities on days of FOMC statements with the volatilities on days without such statements. Days on which the Fed released statements about monetary policy show higher volatilities than other days. Evidently, monetary policy is a key driver of interest rate movements. While most action is in rates at medium maturities of two to three years, policy actions also cause significant volatility in distant forward rates. Of course, this does not tell us whether long rates move in the same direction as shorter-term rates. It does however show that the effects of monetary policy on expectations extend to long horizons and do not die after horizons of a few years.
Conclusion
To understand the effects of macroeconomic data surprises and monetary policy actions on financial markets, it is important to consider how these affect the entire cross section of interest rates. Such an analysis shows where on the time horizon market expectations of economic fundamentals have changed. Similar analysis of the term structures of real interest rates, inflation expectations, and risk premiums has the potential to reveal even more about how changes in economic fundamentals drive the term structure of interest rates.
Reference
Balduzzi, Pierluigi, Edwin J. Elton, and T. Clifton Green. 2001. “Economic News and Bond Prices: Evidence from the U.S. Treasury Market.” Journal of Financial and Quantitative Analysis 36(4), pp. 523–544.
Bauer, Michael D. 2011. “Nominal Interest Rates and the News.” FRBSF Working Paper 2011-20.
Gürkaynak, Refet S., Brian P. Sack, and Eric T. Swanson. 2005. “The Sensitivity of Long-Term Interest Rates to Economic News: Evidence and Implications for Macroeconomic Models.” American Economic Review 95(1), pp. 425–436.
Gürkaynak, Refet S., Brian Sack, and Jonathan H. Wright. 2007. “The U.S. Treasury Yield Curve: 1961 to the Present.” Journal of Monetary Economics 54(8), pp. 2291–2304.
Kuttner, Kenneth N. 2001. “Monetary Policy Surprises and Interest Rates: Evidence from the Fed Funds Futures Market.” Journal of Monetary Economics 47, pp. 523–544
November 02, 2011
October 31, 2011
October 26, 2011
October 24, 2011
October 18, 2011
October 17, 2011
Class Materials for Lecture 7
Brief Outline of Topics Covered in Lecture 7
Chapter 17 Multiple Deposit Creation and the Money Supply Process [cont.]
The Money Supply Model and the Money Multiplier
- Deriving the Money Multiplier
Factors That Determine the Money Multiplier
- Changes in the Required Reserve Ratio, r
- Changes in the Currency Ratio, c = C/D
- Changes in the Excess Reserves Ratio, e = ER/D
Additional Factors That Determine the Money Supply
- Changes in the Nonborrowed Monetary Base, MBn
- Changes in Borrowed Reserves, BR, from the Fed
Chapter 18 Monetary Policy: Stabilizing the Domestic Economy
The Market for Reserves and the Federal Funds Rate
- Supply and Demand in the Market for Reserves
- Tools of monetary policy: Open Market Operations, Discount Policy, and Reserve Requirements
Video:
Technical problems -- no video for this class
Additional Reading:
- Nobel Laureates in Economics, Uneasy With Labels - NYTimes.com
- Could monetary policy mitigate the effects of oil shocks? - Econbrowser
- Volcker Rule Divides Regulators - NYTimes.com
- Google and platforms - Digitopoly
- A Misunderstood Fact About the Job Market - Jared Bernstein
- If Only Our Spacetime Was Five Dimensional - Brad DeLong
- Greece and the euro - The Street Light
- The Critics Of Modern Macro Are Wrong - Paul Krugman
- The 1960s View of Modern Banking - Liberty Street
More here.
Application:
This topic came up in class the other day (see here and here too):
Did Speculation Drive Oil Prices? Market Fundamentals Suggest Otherwise, by Michael D. Plante and Mine K. Yücel, Economic Letter, FRB Dallas: Oil market speculation became an especially popular topic when the price of crude tripled over 18 months to a record high $145 per barrel in July 2008. Of particular interest to many is whether speculators drove oil prices beyond what fundamentals would have otherwise justified. We explore this issue over two Economic Letters. In this article, we look at evidence from the physical market for oil and conclude that fundamentals, and not speculation, were behind the dramatic rise and fall in oil prices. In our companion Economic Letter, we examine the futures market.
Oil prices began their climb in 2002, reaching a record high in mid-2008, and then collapsed at the end of ’08 amid the global recession. As world economic growth picked up, so did oil prices. Overall, the year-over-year change in oil prices has fairly closely tracked world gross domestic product (GDP) growth (Chart 1).
Energy consumption increases as GDP rises; but energy consumption in developing countries increases almost twice as fast as in developed countries. GDP expansion in emerging economies was particularly strong between 2005 and 2007, averaging 8 percent per year. Real GDP in China, for example, grew by an average 12.7 percent annually between 2005 and 2007, while the nation’s oil consumption increased 5.1 percent annually during the period.
From the beginning of 2007 to mid-2008, weekly prices for West Texas Intermediate (WTI) crude oil jumped 152 percent, from $57 to $143 per barrel. It’s possible that growing demand for crude oil might not be the reason for the rise. However, if the increase was due to other factors, oil consumption should have begun falling in response to the higher prices. Instead, there was almost no consumption decline during the period, implying that oil prices were driven by growing world income and demand.
Insensitivity to Price Change
Consumers of oil and oil products are not very sensitive to price changes, especially in the short run. In economic jargon, the price elasticity of demand is very low. This is mainly because oil’s use for transportation purposes accounts for two-thirds of consumption, especially in developed countries, where there are no close substitutes in the short term. When consumers are insensitive to price changes, a shock in the oil market, whether from increased demand or reduced supply, will heighten price volatility.
To see whether rising oil prices from 2007 through mid-2008 are compatible with the elasticities for oil estimated in the energy economics literature, we performed a simple calculation. Taking the developed-world and emerging market GDP growth rates from the International Monetary Fund, and making some assumptions about income elasticities of demand, we can calculate the higher oil demand implied by these growth rates. Then, by comparing actual growth in consumption and the calculated consumption numbers, we can determine the oil price elasticities they imply. We found that these elasticities would have to range from 0.01 to 0.08 for prices to surge as they did in 2007 and 2008—well within the estimated elasticity ranges in the energy economics literature.[1]
OPEC Market Power Firmed Prices
The oil market is not perfectly competitive. The Organization of the Petroleum Exporting Countries (OPEC), since its formation in 1970, has been an oligopolistic producer, trying to boost prices by controlling members’ output (with more success at times of higher demand growth). The remaining non-OPEC producers form a price-taking, competitive fringe. OPEC’s market share has dwindled from 52 percent in the early 1970s to a still hefty 42 percent today. In the 1990s, as the market grew, so did both OPEC and non-OPEC production. However, non-OPEC oil output growth flattened around 2003, while OPEC output continued expanding from 37 percent in 2003 to the current 42 percent level. Increased market power, coupled with rising demand, was a significant factor keeping oil prices high.
Low OPEC Excess Capacity
OPEC’s crude oil production capacity has changed little since the 1970s, rising from 34 million barrels per day in 1973 to 35.5 million barrels per day in 2008. However, increased world consumption greatly diminished the cartel’s excess capacity. OPEC has added capacity slowly, using its restrained output to keep prices high.
It is easier to keep cartel members disciplined and conforming to production quotas when capacity is tight. Moreover, shocks in a tight oil market can increase price volatility because OPEC lacks the ability to offset these shocks, even if it desires to. Chart 2 shows the inverse relationship of oil prices and the cartel’s excess capacity. In mid-2008, when oil prices reached record highs, OPEC excess capacity was down to 1 million barrels per day.[2]
Inventories Did Not Increase
A speculator wanting to drive up the current price of oil would have to buy in the spot market. Since the price is determined in a cash marketplace where transactions are settled with physical oil changing hands, speculative buyers would have to store their purchases, and inventories would rise. Instead, during the oil price run-up in 2007 and 2008, inventories in the U.S. were being depleted. Chart 3 shows WTI prices and U.S. oil inventories and illustrates the workings of an efficient market—as supplies diminish, prices rise and the market tightens.
Another possibility might be speculators using floating storage, keeping oil in tankers at sea and off the market. Floating storage appears to increase in 2008, rising from 68.4 million barrels at the end of October to 97 million barrels in May (Chart 4). However, floating storage declined in June and continued falling throughout the summer.
We would have expected to see floating storage rise significantly during the summer if speculators were in the market; instead, the opposite occurred. Floating storage did rise much later in the year, but that was concurrent with the global recession.
There is one additional type of storage—producers maintaining the oil as reserves and not producing. However, if we look at OPEC output, it clearly rose as oil prices went up, until July 2008. OPEC increased production by 2.4 million barrels per day from the beginning of 2007 to July 2008. Non-OPEC production remained relatively constant and did not rise, though this is largely a function of non-OPEC producers’ zero excess capacity rather than an attempt to restrict output.
Other Commodities Surged
Those believing speculation pushed up prices point to the coincident increase in the number of noncommercial traders in the futures market—for example, speculators—and the rise in oil prices.[3] However, Chart 5 shows that this may not necessarily be the case. It depicts the prices of WTI, Illinois Basin coal, tallow and cobalt. Of these commodities, there is a futures market only for WTI. Yet, prices for Illinois Basin coal, tallow and cobalt increased as fast as oil, if not faster, in 2008 and fell just as quickly when the economy crumbled. Such integrated movement in the prices of these commodities is consistent with a pure demand story, rather than a speculation one.
Fundamentals, Not Speculation
Activity in the futures market increased appreciably in the past decade, as did the number of noncommercial traders. This rise was coincident with the rise in oil prices, leading some to hypothesize that speculation—rather than market fundamentals—drove the price of oil.The tripling of oil prices from early 2007 to mid-2008 is consistent with several market fundamentals, including increased demand from emerging markets, low elasticities of demand and reduced OPEC excess capacity. The behavior of inventories was also consistent with the reality of a tight market, not with a story of speculation-driven hoarding, whether we look at inventories above ground, below ground or floating at sea. Hence, evidence from the physical market for oil, similar to that from the futures market, is consistent with oil-market fundamentals leading to increasing oil prices before the global recession.
Notes
- An elasticity of 0.01 implies that for every 10 percent change in oil prices, consumption falls by 0.1 percent. Estimated short-run price elasticities for oil range from 0.0 to –0.11. See “A Literature Review of Demand Studies in World Oil Markets,” by Frank J. Atkins and S.M. Tayyebi Jazayeri, University of Calgary, Department of Economics Discussion Paper 2004-07, April 2004.
- OPEC excess capacity has ranged from a high of 9.8 million barrels per day in 1985 to a low of 700,000 barrels per day in 2004.
- See “Did Speculation Drive Oil Prices? Futures Market Points to Fundamentals,” by Michael D. Plante and Mine K. Yücel, Federal Reserve Bank of Dallas Economic Letter, vol. 6, no. 10, 2011.
October 13, 2011
October 12, 2011
Class Materials for Lecture 6
Brief Outline of Topics Covered in Lecture 6
Chapter 16 Structure of Central Banks and the Federal Reserve System [cont.]
How Independent is the Fed?Should The Fed Be Independent?
- The Case for Independence
- The Case Against Independence
Chapter 17 Multiple Deposit Creation and the Money Supply Process
Four Players in the Money Supply Process
The Fed’s Balance Sheet
- Liabilities
- Assets
Control of the Monetary Base
- Open Market Operations with Bank
- Open Market Operations with an Individual and shifts between Currency and Deposits
The Money Supply Model and the Money Multiplier
- Deriving the Money Multiplier
Factors That Determine the Money Multiplier
- Changes in the Required Reserve Ratio, r
- Changes in the Currency Ratio, c = C/D
- Changes in the Excess Reserves Ratio, e = ER/D
Additional Factors That Determine the Money Supply
- Changes in the Nonborrowed Monetary Base, MBn
- Changes in Borrowed Reserves, BR, from the Fed
Video:
Materials Related to Class
Central Bank Independence and Inflation
From "Central Bank Independence and Macroeconomic Performance: Some Comparative Evidence," by Alberto Alesina and Lawrence H. Summers, Journal of Money, Credit and Banking, Vol. 25, No. 2. (May, 1993), pp. 151-162 (the link will work on UO net, but I don't expect you to read the paper as it is a bit technical):
This has changed with the adoption of inflation targeting by central banks. Note also that Adam Posen casts doubt on whether causality runs from central bank independence to improved macroeconomic performance in Central Bank Independence and Disinflationary Credibility: A Missing Link?, NY Fed Staff Report, May 1995.
Application:
Christopher Sims and Tests for Causality: To tell the full story of Christopher Sims' contributions to causality, we need to go back to the state of the art in policy evaluation in the 1960s, in particular, to something known as the St. Louis equation:
Yt = c + a0Mt + a1Mt-1 + a3Mt-2 + b0Gt + b1Gt-1 + b2 Gt-2 + et
In this equation, output (Y) is regressed on current and lagged values of money (M) and government spending (G). The idea was to see how output responded historically to changes in money and government spending, and then use these estimates to guide policy. If we know how Y responds to M, then we can use that knowledge to set monetary policy optimally.
Now, there is a fundamental problem with this approach highlighted by the Lucas critique (the negative reaction to the other common approach, using large-scale structural models to evaluate policy, was discussed yesterday). If you change monetary policy you also change the values of the a and b coefficients so that the estimates are no longer reliable, and hence no longer a guide, but that criticism came later. At the time there was another worry.
The worry was something known as simultaneity bias. Consider the Mt term in the equation above. If Mt is "econometrically exogenous," i.e. if it doesn't depend upon Yt, then the estimated value of a0 will be unbiased. But if Mt depends upon Yt , perhaps through and equation such as Mt = h0 + h1Yt + ut, then the estimate of will be biased and hence a poor guide to policy decisions.
The first use of causality tests was to test to see if h1 in the "policy equation" was equal to zero, and Sims was a key player in the development of these tests. Thus, Sims starts his 1972 AER paper with:
This study has two purposes. One is to examine the substantive question: Is there statistical evidence that money is "exogenous" in some sense in the money-income relationship? The other is to display in a simple example some time-series methodology not now in wide use. The main methodological novelty is the use of a direct test for the existence of unidirectional causality.
If there was unidirectional causality from M to Y, then the estimate would be unbiased. But if there was two-way causality, i.e. if Y causes M (h1 is not zero), then the estimate would be problematic.
Sims contributed greatly to this literature, and once this work was largely complete, it quickly became clear that these tests could be used to assess causality more generally, the method was not limited to checking for econometric exogeneity.
But there was also a problem. The basic technique (an F-test on a set of coefficients) to test for causality worked well on 2-variable systems, but it didn't work reliably for systems with three or more equations (the problem was that X can cause Y, and Y can then cause Z so that there is a causal path from X to Z, but the F-test approach will miss this).
Sims Second major paper on causality addresses this problem by providing two new tools to assess causality, impulse response functions and variance decompositions (along the way it was also shown that Sims and Granger causality are equivalent). Impulse response functions, which have since become a key analytical device in macroeconomics, trace out the response of the variables in the model to a shock to another variable in the system (identification restrictions are needed to ensure that the shock is actually a policy shock, see here). If the variable, say output, responds robustly to a shock to, say, the federal funds rate, then we say that the federal funds rate causes output. But if we shock the federal funds rate and output essentially flat-lines in response, then causality is absent.
However, even when there is causality according to the impulse responses, impulse response functions do not tell us how important one variable is in explaining the variation in another variable (the impulse response function could look impressive, but it may be that we are only explaining 1% of the total variation in the other variable so that the response we are seeing is not very important in explaining why the other variable fluctuates over time). Variance decompositions solve this problem. They don't tell you the sign/pattern of the response like impulse response functions do, but the do give an indication of how important one variable is in explaining the variation in another variable (e.g. if M explains 75% of the variance in output, that's impressive and notable, but if it's only 1% then money isn't very important in explaining why output changes over time).
Sims second paper also made another important point. In his first paper, he found that money causes output (so it could not be treated as econometrically exogenous as in the St. Louis equation). But that was in a two-variable system including only M and Y. In his second paper he adds interest rates (i) and prices (P) to get a four variable system, and he finds that this overturns the results in his first paper. Once i is added to the model, M no longer causes Y. Thus, the lesson is that if you leave important variables out of a VAR system, it can produce misleading results.
But Sims' main contributions were, initially, the F-tests for testing causality in bivariate systems, and the addition of IRFs and VDCs to assess causality in higher order systems. In addition, he also provided many of the common "pitfalls of causality testing," -- causality testing can be misleading in a number of ways. One is above, leaving a variable out of a system. If A causes B to change tomorrow, and C to change the next day, a system containing only B and C will look as though B causes C when in fact there is no causality at all, a third variable causes both. Other pitfalls can occur, for example, when there is optimal control or when expectations of future variables are in the model. Identifying the pitfalls of the methods he (and others) developed was also an important contribution to the literature.
Sims' work on causality was highlighted in the Nobel announcement, and I hope this provided some background on this topic. But there's a lot more to be said about Sims' work over and above his work on causality testing discussed above and his work on structural VARs I discussed yesterday, e.g. his recent papers on rational inattention, and I hope to write more about both Sims and Sargent when I can find the time.
October 10, 2011
Class Materials for Lecture 5
Brief Outline of Topics Covered in Lecture 5
Chapter 16 Structure of Central Banks and the Federal Reserve System
Origins of the Federal Reserve System
- Distribute power to geographic regions, the public sector, the private sector, the business sector, and the financial sector
Formal Structure of the Federal Reserve System
- Federal Reserve Banks
- Member Banks
- Board of Governors of the Federal Reserve System
- Federal Open Market Committee (FOMC)
- The Federal Advisory Council (FAC)
Informal Structure of the Federal Reserve System
- How Power Has Been Centralized Over Time
How Independent is the Fed?
Should The Fed Be Independent?
- The Case for Independence
- The Case Against Independence
Chapter 17 Multiple Deposit Creation and the Money Supply Process
Four Players in the Money Supply Process
The Fed’s Balance Sheet
- Liabilities
- Assets
Control of the Monetary Base
- Open Market Operations with Bank
- Open Market Operations with an Individual and shifts between Currency and Deposits
Video:
not yet available
Materials Related to Class
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The Twelve Federal Reserve Districts
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Additional Reading:
- When Virtual Money Saved the Day - Liberty Street
- Agreement Is Reached to Nationalize Belgian Bank - NYTimes.com
- The Subprime Crisis: Was it Government Housing Policy? - Big Picture
- The Depression - If Only Things Were That Good - NYTimes.com
- An Interview with Richard Easterlin - Economics Intelligence
- Is another U.S. recession a 'done deal'? - Econbrowser
- Too Much Caution Hinders a Turnaround - Richard Thaler
- IS-LMentary - Paul Krugman
- Two more job market charts - macroblog
- There's something about macro - Paul Krugman
- Households Pay a Price for China’s Growth - NYTimes.com
Application:
Tim Duy:
Too Early to Sound the All Clear?, by Tim Duy: Last week I wrote:
The economy was not in recession in the third quarter, which means the backward looking data flow through this month will not be particularly dire.
Consistent with this prediction, the September employment report painted a picture of an economy still wading through knee-deep mud, but not in economic collapse. That said, prior to the report, Barry Ritholtz offered some wisdom regarding individual data points versus trends:
What does matter is the overall vector of a given economic sector. Vectors include the rate of acceleration or deceleration, persistency, direction etc. Think overall “trend” and changes thereto. For employment, this means: Are we seeing an increase in the factors that lead to hiring? What is the ratio between hires at big firms vs small firms? Are Wages increasing, staying flat, or decreasing; Temp workers getting hired, total hours worked etc. What are the likely data and modeling errors? Collectively, those factors all add up to an issue of the employment situation roughly improving, maintaining a stability, or getting worse.
Hence, each data point should be looked at in terms of whether it is continuing the overall trend, or suggesting a reversal in trend. Everything else is noise.
With trends in mind, the data did little to dispel my concern that private sector hiring rolled-over earlier this year, especially when combined with last week's read on employment via the ISM nonmanufacturing report:
Trends notwithstanding, Bloomberg offers up some optimisim on the outlook:
A string of stronger-than-projected statistics -- capped by the news on Oct. 7 of a 103,000 rise in payrolls last month --has prompted economists at Goldman Sachs Group Inc. and Macroeconomic Advisers LLC to raise their growth forecasts for third quarter growth to 2.5 percent from about 2 percent. That’s nearly double the second quarter’s 1.3 percent rate and would be the fastest growth in a year.
“The U.S. economy doesn’t look like it’s double-dipping at all,” said Allen Sinai, president of Decision Economics Inc. in New York. “But it is a crummy recovery.”
The article offers up the usual caution on Europe and increasingly tight fiscal policy when the New Year begins. But the bottom line is correct - on the basis of existing data, the recession call looks like a long-shot.
Getting to the recession call requires generally ignoring the incoming data on the real economy and instead focusing on financial markets. Then recognize that in recent experience, financial distress leads to broader economic distress. Moreover, at the moment, the slowdown in US economic growth coupled with the possibility of sovereign default in Europe are combining in such a way as to expose the inherent vulnerabilities in a still-under-capitalised global financial system. See Edward Harrison here.
And although there is optimism the European situation can be resolved in three weeks, they seem to be walking a very fine line between attempting to recapitalize the banking system without undermining sovereign debt ratings while maintaining what effectively amounts to a pegged exchange rate system that is fundamentally inconsistent with the economic needs of more than one nation. In addition, they have an odd situation where every nation needs to issue Euro-denominated debt, but no nation can actually print Euros as a backstop. It's as if each nation issues only foreign-denominated debt, with ultimately no lender of last resort on a national level. Of course, the European Central Bank could fill this role, but will they?
My experience is that when a financial landscape is as ugly as we see here, there is no rescue plan. Things tend to get much worse before they get better. That seems to be what financial market are telling us.
With that cheery thought in mind, I offer another distressing correlation. While I generally find monetary aggregates difficult indicators in the best of time, this caught my attention:
Since the end of the 1990's, there has been a negative correlation between M2 growth and industrial production growth. It appears that financial market disruptions of the current magnitude are sufficient to drive substantial changes in spending. If this correlation continues to hold, then I need to rethink my belief that any recession in the near term will be relatively mild considering the lack of rebound from the last recession. Perhaps underneath today's seemingly comforting data something very ugly is brewing. Which means enjoy these big rallies on Wall Street while you can.
October 06, 2011
October 05, 2011
Class Materials for Lecture 4
Brief Outline of Topics Covered in Lecture 4
Chapter 11 The Economics of Financial Intermediation
Function of Financial Intermediaries [cont.]
- Adverse selection
- Moral hazard
Chapter 16 Structure of Central Banks and the Federal Reserve System
Origins of the Federal Reserve System
- Distribute power to geographic regions, the public sector, the private sector, the business sector, and the financial sector
Formal Structure of the Federal Reserve System
- Federal Reserve Banks
- Member Banks
- Board of Governors of the Federal Reserve System
- Federal Open Market Committee (FOMC)
- The Federal Advisory Council (FAC)
Informal Structure of the Federal Reserve System
- How Power Has Been Centralized Over Time
How Independent is the Fed?
Should The Fed Be Independent?
- The Case for Independence
- The Case Against Independence
Chapter 17 Multiple Deposit Creation and the Money Supply Process
Four Players in the Money Supply Process
The Fed’s Balance Sheet
- Liabilities
- Assets
Control of the Monetary Base
- Open Market Operations with Bank
- Open Market Operations with an Individual and shifts between Currency and Deposits
Video:
Additional Reading:
- The St. Louis Fed Financial Stress Index - MacroMania
- IMF Floats Bond-Buying Proposal in Europe - WSJ.com
- Expanding access to elite education - Vox EU
- Do Financial Markets Separate News from Noise? - Liberty Street
- Inflation expectations: a downward march - MacroMania
- Slow growth continues - Econbrowser
- Keynes and Econometrics - Dave Giles
- The Tribal Dislike of John Hicks and IS-LM - Brad DeLong
- Europe Finds Slope Ahead Is Growing Ever Steeper - NYTimes.com
- Goldman: U.S. recession probability at 40% in 2012 - Calculated Risk
- Economic Outlook and Recent Monetary Policy Actions - Ben Bernanke
Application:
Continuing our recent discussion on inflation expectations:
Inflation expectations: a downward march, by David Andolfatto: This graph is courtesy of my colleague, Kevin Kliesen.
If you squint your eyes near the end of the sample, you'll see that Operation Twist appeared, on impact, to move short and long inflation expectations in opposite directions. The effect did not last long, however. The march downward continues--for now, at least.
October 03, 2011
September 29, 2011
September 28, 2011
September 26, 2011
Class Materials for Lecture 1
Brief Outline of Topics Covered in Lecture 1
Introduction: Why Study Money, Banking, and Financial Markets?
Why Study Money and Monetary Policy?
- Money and Business Cycles
- Money and Inflation
- Money and Interest Rates
- Conduct of Monetary Policy
- Fiscal Policy and Monetary Policy
Why Study Banking and Financial Institutions?
- What Defines Banks and Financial Institutions?
- What is Financial Intermediation?
- Direct versus Indirect Finance
- Why is Financial Intermediation Important?
Why Study Financial Markets?
- Bond Market
- Stock Market
- Foreign Exchange Market
An Overview of the Financial System
Chapter 2 What is Money?
Meaning of Money
Functions of Money
- Medium of Exchange
- Unit of Account
- Store of Value
Video:
Materials related to class:
September 25, 2011
Economics 470
Mark Thoma
Office: PLC 471
Phone: 346-4673
Office Hours: T/Th
11:30 a.m.-12:30 p.m.
and by appointment
Web Page
Email
Economist's View Blog
Department of Economics
University of Oregon 1285
Eugene, OR 97403-1285
GTF Info - 470
GTFs: Scott Mildrum
Office: Knight Lib. 407
Email: smildrum@uoregon.edu
Office Hours: M/W 8:30-9:30 and by appointment
