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December 16, 2016
The Impact of Extraordinary Policy on Interest and Foreign Exchange Rates
Central banks in the developed countries have adopted a variety of extraordinary measures since the financial crisis, including large-scale asset purchases and very low (and in some cases negative) policy rates in an effort to boost economic activity. The Atlanta Fed recently hosted a workshop titled "The Impact of Extraordinary Monetary Policy on the Financial Sector," which discussed these measures. This macroblog post discusses the highlights of three papers related to the impact of such policy on interest rates and foreign exchange rates. A companion Notes from the Vault reviews papers that examined how those policies may have affected financial institutions, including their lending.
Prior to the crisis, central banks targeted short-term interest rates as a way of influencing the rest of the yield curve, which in turn affected aggregate demand. However, as short-term rates approached zero, central banks' ability to further cut their target rate diminished. As a substitute, the central banks of many developed countries (including the Federal Reserve, the European Central Bank, and the Bank of Japan) began to undertake large-scale purchases of bonds in an attempt to influence longer-term rates.
Central bank asset purchases appear to have had some beneficial effect, but exactly how these purchases influenced rates has remained an open question. One of the leading hypotheses is that the purchases did not have any direct effect, but rather served as a signal that the central bank was committed to maintaining very low short-term rates for an extended period. A second hypothesis is that central bank purchases of longer-dated obligations resulted in long-term investors bidding up the price of remaining longer-maturity government and private debt.
The second hypothesis was tested in a paper by Federal Reserve Board economists Jeffrey Huther, Jane Ihrig, Elizabeth Klee, Alexander Boote and Richard Sambasivam. Their starting point was the view that a "neutral" policy would have the Fed's System Open Market Account (SOMA) closely match the distribution of the stock of outstanding Treasury securities. In their statistical tests, they find support for the hypothesis that deviations from this neutrality should influence market rates. In particular, they find that the term premium in longer-term rates declines significantly as the duration of the SOMA portfolio grows relative to that of the stock of outstanding Treasury debt.
The central banks' large-scale asset purchases not only took longer-dated assets out of the economy, but they also forced banks to increase their holdings of reserves. Large central banks now pay interest on reserves (or in some cases charge interest on reserve holdings) at an overnight rate that the central bank can change at any time. As a result, these purchases can significantly reduce the average duration (or maturity) of a bank's portfolio below what the banks found optimal given the term structure that existed prior to the purchases. Jens H. E. Christensen from the Federal Reserve Bank of San Francisco and Signe Krogstrup from the International Monetary Fund have a paper in which they hypothesize that banks respond to this shortening of duration by bidding up the price of longer-dated securities (thereby reducing their yield) to restore optimality.
The difficulty with testing Christensen and Krogstrup's hypothesis is that in most cases central banks were expanding bank reserves by buying longer-dated securities, thus making it difficult to disentangle their respective effects. However, in 2011 the Swiss National Bank undertook a series of three policy moves designed to produce a large, rapid increase in bank reserves. Importantly, these moves were an attempt to counter perceived overvaluation of the Swiss franc and did not involve the purchase of longer-dated bonds. In a follow-up empirical paper , Christensen and Krogstrup exploit this unique policy setting to test whether Swiss bond rates declined in response to the increase in reserves. They find that the third and largest of these increases in reserves was associated with a statistically and economically significant fall in term premia, implying that the increase did lower longer-term rates.
Although developed countries' monetary policy has focused on their domestic economies, these policies can have significant spillovers into emerging countries. Large changes in the rates of return available in developed countries can lead investors to shift funds into and out of emerging countries, causing potentially undesirable large swings in the foreign exchange rate of these emerging countries. Developing countries' central banks may try to counteract these swings via intervention in the foreign exchange market, but the effectiveness of sterilized intervention is the subject of some debate. (Sterilized intervention occurs when the central bank buys or sells foreign currency, but then takes offsetting measures to prevent these from changing bank reserves.)
Once again, determining whether exchange rates are influenced and, if so, by what mechanism can be econometrically difficult. Marcos Chamon from the International Monetary Fund, Márcio Garcia from PUC-Rio, and Laura Souza from Itaú Unibanco examine the efforts of the Brazilian Central Bank to stabilize the Brazilian real in the aftermath of the so-called "taper tantrum." The taper tantrum is the name given to the sharp jump in U.S. bond yields and the foreign exchange rate value of the U.S. dollar after the May 23, 2013, statement by Board Chair Ben Bernanke that the Federal Reserve would slow (or taper) the rate at which it was purchasing Treasury bonds (see a brief essay by Christopher J. Neely). Chamon, Garcia, and Souza's paper takes advantage of the fact that Brazil preannounced its intervention policy, which allows them to separate the impact of the announcement to intervene from the intervention itself. They find that the Brazilian Central Bank's intervention was effective in strengthening the value of the real relative to a basket of comparable currencies.
All three of the studies faced the difficult challenge in linking specific central bank actions to policy outcomes, and each tackled the challenge in innovative ways. The evidence provided by the studies suggests that central banks can use extraordinary policies to influence interest and foreign exchange rates.
December 05, 2016
Using Judgment in Forecasting: Does It Matter?
Many professional forecasters use statistical models when making their near-term projections for real gross domestic product (GDP) growth. A 2013 special survey on the forecasting methods of the Survey of Professional Forecasters found that 18 out of 21 respondents featured a statistical model prominently in their current-quarter economic projections. Nevertheless, there is fairly compelling evidence that many professional forecasters incorporate judgment in their forecasts of the first estimate of real GDP growth for a quarter—even when much of the source data used to construct the GDP estimate are available.
In the October 2016 Wall Street Journal Economic Forecasting Survey (WSJ), the most common panelist projection for annualized third-quarter real GDP growth was 2.5 percent, and the second most common one was 3.0 percent. The first digit after the decimal point, or tenths digit, of these two numbers are "5" and "0." Of the 58 individual forecasts of third-quarter growth in the survey, 21 had a tenths digit of "0" or "5," a total that is almost twice as large as we would expect if all tenths digits were equally likely to be submitted.
This pattern isn't unique to the most recent quarter's GDP forecast. The following chart shows the historical frequency of the tenths digit in past WSJ surveys for first estimates of real GDP growth over the period from the first quarter of 2003 to the third quarter of 2016, made about three weeks before the release.
Almost 40 percent of these 2,390 forecasts have a tenths digit of "0" or "5." In contrast, the historical distribution of published first estimates of real GDP growth from the fourth quarter of 1991 to the third quarter of 2016 and real gross national product (the most common measure of U.S. production in an earlier era) growth from the third quarter of 1965 to the third quarter of 1991 has a tenths digit of either "0" or "5" only 18 percent of the time. The historical Atlanta Fed's GDPNow forecasts have a "0" or a "5" tenths digit only 15 percent of the time.
More formally, one easily can reject the hypothesis at the 1 percent significance level that the tenths digit of the WSJ panelist forecasts are either uniformly distributed or follow the Benford distribution for tenths digits after rounding to the nearest tenth (see this paper by economists Stefan Gunnel and Karl-Heinz Todter, who found similar relative frequencies of "0s" and "5s" in professional forecasts of German GDP growth and consumer price index inflation).
If we assume that near-term GDP growth forecasts with a tenths digit of "0" or "5" typically involve more judgment than forecasts with another tenths digit, a natural question is whether these more judgmental forecasts are less accurate than others. Of the 2,390 WSJ growth forecasts mentioned above, the ones with a tenths digit of "0" or "5" (after rounding to the nearest tenth) had an average error of 0.786 percentage points without regard to sign, and the others had an average error of 0.743 percentage points. These accuracy metrics are not statistically different at even the 10 percent significance level. Moreover, because of the panel nature of WSJ forecasts, we can measure how often a forecaster has a tenths digit of "0" or "5" (after rounding). Of the 44 panelists who submitted at least 30 three-week-ahead GDP forecasts during the period of the first quarter of 2003 through the third quarter of 2016, the correlation of the panelists "0" or "5" tenth digit frequency and their average error without regard to sign is only 0.13 and not significantly different from 0.
Although at least some professional forecasters appear to make judgmental adjustments to their near-term GDP projections, the evidence presented here does not suggest it comes, on average, at the cost of accuracy.
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