Russia’s central bank has unexpectedly raised its key bank interest rate over concerns about inflation and “geopolitical tension”.
The bank’s board decided to raise the interest rate by 50 basis points, or half a percent, to 8% per year.
The Central Bank of Russia said on Friday that it will raise the interest rate on Monday to ease inflationary pressure.
“Inflation risks have increased due to a combination of factors, including, inter alia, the aggravation of geopolitical tension and its potential impact on the rouble exchange rate dynamics, as well as potential changes in tax and tariff policy,” the bank said.
In June, core inflation grew to 7.5%, well above the bank’s forecast of up to 6.5% for the year.
This is the third rate hike within the last half year.
Figure 1: USD/RUB exchange rate (blue, left scale), overnight repo rate, % (red, right scale). Vertical dashed line at 17 July 2014. Source: Pacific exchange service, Central Bank of the Russian Federation.
Previous posts on sanctions and Russia, see here, here, and here. The IMF yesterday released updates for the WEO; the July forecast for Russian growth in 2014 (y/y) is fully 1.1 percentage points lower than the April forecast.
I was at the NBER Summer Institute’s meeting of the International Finance and Macro group where (in addition to finally meeting Jim Hamilton) I had the opportunity to hear two papers on a topic near and dear to me — namely the relationship between the forward premium (the gap between the forward and spot rate, or equivalently in the absence of political risk, the interest differential) and the carry trade. (For discussion of related papers at last year’s IFM, see this post).
Recall, the basic issue is the negative correlation between interest differentials and the ex post depreciation over the corresponding time period. I plot the relationship at the 1 year horizon (for more regarding the data, see Chinn and Quayyum (2012), or this post).
Figure 1: Pooled data for Canadian dollar, euro, Japanese yen, Swiss franc, and British pound against US dollar, 1979Q1-2011Q4. Note: “0.08″ indicates 8%.
Notice that the zero arbitrage profits condition, under risk neutrality and rational expectations implies the slope of the red line should be upward sloping, with slope indistinguishable from unity. In contrast, as is well known, the slope at short maturities is typically negative, and statistically significantly so (see the survey in Chinn (2006)). In the graph above, the slope is -0.54, and statistically significantly different from zero (and from unity).
The first paper was by Tarek Hassan and Rui Mano, “Forward and spot exchange rates in a multi-currency world”. From the abstract:
We decompose violations of uncovered interest parity into a cross-currency, a between time-and-currency, and a cross-time component. We show that most of the systematic violations are in the cross-currency dimension. By contrast, we find no statistically reliable evidence that currency risk premia respond to deviations of forward premia from their time- and currency-specific mean. These results imply that the forward premium puzzle (FPP) and the carry-trade anomaly are separate phenomena that may require separate explanations. The carry trade is driven by static differences in interest rates across currencies, whereas the FPP appears to be driven primarily by cross-time variation in all currency risk premia against the US dollar. Models that feature two symmetric countries thus cannot explain either of the two phenomena. Once we make the appropriate econometric adjustments we also cannot reject the hypothesis that the elasticity of risk premia with respect to forward premia in all three dimensions is smaller than one. As a result, currency risk premia need not be correlated with expected changes in exchange rates.
Another way of putting this is that the carry trade is driven by differences in the constants in the Fama regression (along with what they term dynamic trade, based on variation in between-time-and-currency forward premia), while the forward premium trade relies upon the across-time covariation of exchange rate changes and the forward premia (along with the dynamic trade term).
The comments were various; one observer noted that these were unconditional correlations, while it’s known that some factors — including PPP deviations — are useful in predicting excess returns. My comment was that asymmetries were important — the expected UIP relationship holds when US interest rates are below foreign, and not when above (Bansal and Dahlquist).
Another interesting observation was that the decomposition, while useful, failed to illuminate a key question in the literature — where do these currency fixed effects come from. They’re apparently persistent, but don’t seem to be correlated with any particular observable macro variables.
The second paper was by Hanno Lustig, Andrea Stathopoulos, and Adrien Verdelhan, “The term structure of currency carry trade risk premium”. From the abstract:
We find that average returns to currency carry trades decrease significantly as the maturity of the foreign bonds increases, because investment currencies tend to have small local bond term premia. The downward term structure of carry trade risk premia is informative about the temporal nature of risks that investors face in currency markets. We show that long-maturity currency risk premia only depend on the domestic and foreign permanent components of the pricing kernels, since transitory currency risk is automatically hedged by interest rate risk for long-maturity bonds. Our findings imply that there is more cross-border sharing of permanent than transitory shocks.
One finding (based on a model which assumes importantly complete markets) is that excess returns on the dollar bonds appears as in Figure 1 from the paper.
It is interesting that at a maturity of ten years, the premium is essentially zero. While these pertain to returns, and not yields to maturity, it is interesting that excess returns are zero at a horizon at which Chinn and Meredith (2004) find one cannot typically reject the unbiasedness hypothesis (uncovered interest parity combined with rational expectations). This pattern is shown in Figure 2.
Figure 2: Beta coefficients from Fama regressions at different horizons. Source: Author’s calculations.
However, as pointed by my colleague Charles Engel, there are actually at least two interlinked puzzles regarding interest rates and exchange rates (paper here; post here). The first is the the tendency for exchange rates to appreciate when the interest differential is positive — which is addressed in the Lustig et al. paper. The second is the fact that the exchange rate tends to appreciate when the currency is strong (which pertains to the level of the exchange rate and subsequent change). That puzzle is not addressed in this paper.
I have been thinking about this paper, particularly over the past day:
…Across two studies and two measures of trolling,…[trolls] displayed high levels of the Dark Tetrad [narcissism, Machiavellianism, psychopathy, and sadistic personality] traits and a BFI [Big Five Inventory] profile consistent with those traits. It was sadism, however, that had the most robust associations with trolling of any of the personality measures, including those of the Big Five.
In fact, the associations between sadism and GAIT scores were so strong that it might be said that online trolls are prototypical everyday sadists (Buckels et al., 2013). Note that the Dark Tetrad associations were specific to trolling. Enjoyment of other online activities, such as chatting and debating, was unrelated to sadism. Subsequent analyses confirmed that the Dark Tetrad associations were largely due to overlap with sadism. When their unique contributions were assessed in a multiple regression, only sadism predicted trolling on both measures (trolling enjoyment and GAIT scores). In contrast, when controlling for sadism and the other Dark Tetrad measures, narcissism was actually negatively related to trolling enjoyment. Given that controlling for overall Internet use did not affect these results, personality differences in broader tendencies of Internet use and familiarity cannot explain the findings.
In the final analysis of Study 2, we found clear evidence that sadists tend to troll because they enjoy it. When controlling for enjoyment, sadism’s impact on trolling was cut nearly in half;…
…The Internet is an anonymous environment where it is easy to seek out and explore one’s niche, however idiosyncratic. Consequently, antisocial individuals have greater opportunities to connect with similar others, and to pursue their personal brand of “self expression” than they did before the advent of the Internet.
Here’s the introduction to a new paper I just finished:
This year the oil industry celebrated its 155th birthday, continuing a rich history of booms, busts and dramatic technological changes. Many old hands in the oil patch may view recent developments as a continuation of the same old story, wondering if the high prices of the last decade will prove to be another transient cycle with which technological advances will again eventually catch up. But there have been some dramatic changes over the last decade that could mark a major turning point in the history of the world’s use of this key energy source. In this article I review five of the ways in which the world of energy may have changed forever.
Below I provide a summary of the paper’s five main conclusions along with a few of the figures from the paper.
1. World oil demand is now driven by the emerging economies.
2. Growth in production since 2005 has come from lower-quality hydrocarbons.
3. Stagnating world production of crude oil meant significantly higher prices.4. Geopolitical disturbances held back growth in oil production.
5. Geological limitations are another reason that world oil production stagnated.
And here is the paper’s conclusion:
Although the oil industry has a long history of temporary booms followed by busts, I do not expect the current episode to end as one more chapter in that familiar story. The run-up of oil prices over the last decade resulted from strong growth of demand from emerging economies confronting limited physical potential to increase production from conventional sources. Certainly a change in those fundamentals could shift the equation dramatically. If China were to face a financial crisis, or if peace and stability were suddenly to break out in the Middle East and North Africa, a sharp drop in oil prices would be expected. But even if such events were to occur, the emerging economies would surely subsequently resume their growth, in which case any gains in production from Libya or Iraq would only buy a few more years. If the oil industry does experience another price cycle arising from such developments, any collapse in oil prices would be short-lived.
My conclusion is that hundred-dollar oil is here to stay.
In a recent article, Amity Shlaes asserts official statistics mismeasure how we experience inflation. I’m going to agree, but not for the reasons you might think. It’s not because John Williams’ Shadowstats, which she appeals to, is right (Jim has comprehensively documented why each and every person who cites that source should be drummed out of the society of economists or aspiring economic commentators). Rather it’s because I think people do have biases — i.e., the steady-state rational expectations hypothesis might not be applicable.
Ms. Shlaes writes in “Inflation Vacation”:
…The price zap is an inflation zap. The reason you thought you could afford this vacation in the first place was that you know a little about money. All the official numbers, especially the Consumer Price Index, say that inflation is reasonable. Economists you respect tell you the wages are low because of “misallocation of resources.” Janet Yellen, the new Fed chairman, says she’s not worried. Maybe she will have a good vacation.
But other numbers suggest that inflation is higher than what the official data suggest. One set, from which some of the price bites above were taken, is here. For a more thorough review of why official numbers err, have a look at the work of John Williams, a consultant who has tracked data over the years.
It’s at this point that I believe the findings by Coibion and Gorodnichenko (2013), discussed earlier by Jim, is of interest. They note that households hold noticeably different expectations regarding inflation than do professional forecasters, or markets; in this sense, household expectations are “unanchored” to the extent that they are consistently higher than ex post realizations of inflation.
Source: Figure 6, Panel A, Coibion and Gorodnichenko.
Why does this pattern arise? From the paper:
…why did households hold such different beliefs than professional forecasters? Our suggested answer can be seen in … Figure 7. Household inflation forecasts have tracked the price of oil extremely closely since the early 2000s, with almost all of the short-run volatility in inflation forecasts corresponding to short-run changes in the level of oil prices. From January 2000 to March 2013, for example, the correlation between the two series was 0.74. In contrast, the correlation between SPF inflation forecast and oil price over the same period was -0.12. The strong sensitivity of consumers’ inflation expectations to oil price has historically been strong: the correlation between MSC inflation expectations and real oil price over 1960-2000 was 0.67.
Source: Figure 7, from Coibion and Gorodnichenko.
Households that tend to have more gasoline expenditures tend to be more sensitive to oil prices. This further buttresses the view that expectations differ from professional forecasters, and market based measures which are unbiased. See more on the characteristics of household surveys by R. Waldmann/Angry Bear.
On another count, Ms. Shlaes discounts both hedonics and price index theory:
The Bureau of Labor Statistics or the Fed also argued that the quality of some items (camera, movie) had improved over the years. The technology it took to make X-Men: Days of Future Past is leagues ahead of the technology used for Gladiator. The movie theater itself has better seats. Therefore, the ticket price should be higher. The economists at the BLS say they discount for that: “The hedonic quality adjustment method removes any price differential attributed to change in quality,” they write. But perhaps they use such indexes to hide true price increases.
Decades ago, authorities pointed out that people substitute a cheaper item when what they originally bought was too expensive. They altered the index to capture substitution. If steak is expensive, you buy chicken. The result of their fiddle is that inflation looks lower than it would otherwise. That’s disappointing. No vacation is a true vacation without a really good tenderloin.
On the first point — hedonics — it’s telling that movies were mentioned, but not telecommunications. From my standpoint, I can say there has been a big
de increase in what my smartphone can do relative to my first mobile phone in 2000.
On the second point, this observation is funny because the CPI is a quasi-Laspeyres index (see this post), so it tends to minimize (although not completely eliminate) the effect she speaks of. Now, it’s true that the index weights are updated each two years, but even then, those with an acquaintance of price index theory understand that in the absence of the true underlying utility function of consumers, measuring the “true” rate of inflation is infeasible, and the Laspeyres index tends to over-state the rate of inflation (the chained CPI inflation rate tends to be lower than that obtained using the standard quasi-Laspeyres CPI ).
Actually, I suspect that the reported inflation rate actually understates the inflation relevant to Ms. Shlaes, if her household is in the upper 25% income decile. That’s because the CPI weights are appropriate to a household at the 75% income decile (see this post on plutocratic vs. democratic price indices). Those at lower income levels are likely facing a higher inflation rate than she does.
One point where I do disagree vociferously with Ms. Shlaes assessment is here, where she discusses the Liesman-Santelli exchange (discussed in this post):
If you study the last part of the video, where the CNBC host gets bullied into silence by Steve Liesman, you’ll see the problem. The price today for talking about inflation is itself too high.
Lots of people have been discussing inflation and hyper-inflation for the past six years. I don’t think the costs are that high at all. And in fact I expect to hear more inflation worries, day after day.
Final point: to the extent that the CPI growth has changed over time, it is interesting to consider the price level counterfactual implied by the inflation rate over the 2001M01-2009M01 period. This is shown in Figure 1.
Figure 1: Log CPI (blue) and linear trend estimated over 2001M01-09M01 period (red). Sample period for estimation of trend shaded tan. Source: BLS (May 2014 release) via FRED and author’s calculations.
It certainly looks to me that inflation is lower (i.e., the slope is flatter) post 2008 than before. Biases that existed in the past regarding “zaps” exist now. Indeed, if anything one bias that existed before — due to imputation of owner occupied rent — is probably resulting in an overstatement of inflation right now 
Update, 7/24 3PM Pacific: Lars Jonung points out that he in earlier work found serial correlation in forecast errors from surveys of consumers, and further conjectures that the costs of acquiring data might be the source of the lack of unbiasedness. See Jonung (1981) and Jonung and Laidler (1988). This point is consistent with my statement that the forecast errors from the Michigan survey failed to exhibit behavior consistent with the “steady-state rational expectations hypothesis”. This doesn’t mean the behavior is necessarily irrational; it could be the learning process is slow enough in response to new shocks that errors are serially correlated (near rationality a la Akerlof and Yellen for instance).
Production flows from a given oil field naturally decline over time, but we keep trying harder and technology keeps improving. Which force is winning the race?
An oil reservoir is a pool of hydrocarbons embedded and trapped under pressure in porous rock. As oil is taken out, the pressure decreases and the annual rate of flow necessarily declines. A recent study of every well drilled in Texas over 1990-2007 by Anderson, Kellogg, and Salant (2014) documents very clearly that production flows from existing wells fall at a very predictable rate that is quite unresponsive to any incentives based on fluctuations in oil prices.
If you want to produce more oil, you have to drill a new well, and in contrast to production from existing wells, drilling effort clearly does respond to price incentives.
When a given region is found to be promising, more wells are drilled, and production initially increases. But eventually the force of declining pressure takes over, and we see a broad decline in oil production from a given producing region that additional effort and price incentives can do little to reverse. For example, production from the North Sea and Mexico, which had been quite important in the world total in 2000, have been declining steadily for the last decade despite a huge increase in the price of oil.
It’s also interesting to look at graphs for each of the oil-producing U.S. states. Production from Pennsylvania, where the oil industry began in 1859, peaked in 1891, and in 2013 was at a level only 1/6 of that achieved in 1891. But despite falling production from Pennsylvania after 1891, U.S. production continued to increase, because of the added boost from Ohio (which peaked in 1896) and West Virginia (which peaked in 1900). And so the story continued until 1970, with total U.S. production continuing to increase despite declines from the areas first exploited.
The table below lists the date at which production from an indicated state reached its highest point. Use of horizontal drilling methods in the Bakken and Niobrara shales brought production in North Dakota and Colorado to all-time highs in 2013. Production was also higher in 2013 than in 2005 for 22 of the 31 states graphed above, though 2013 levels were still below the historical peak for all but 3 of these states.
Date of peak
|Louisiana and GOM||1971|
Another perspective on the U.S. trends comes from looking at broader categories of production. The red area in the graph below summarizes field production of conventional crude oil from the lower 48 U.S. states. This peaked in 1970, and today is 5.5 mb/d below the value achieved then. Factors temporarily slowing the trend of declining production were development of offshore oil (in dark blue) and Alaska (in light blue). But the combined contribution of all three of these has nevertheless been falling steadily for the last 20 years.
That downward trend was dramatically reversed over the last few years with the advent of horizontal drilling and fracturing to get oil out of tighter geologic formations, as seen in the green region in the graph above. If success with tight oil formations continues, we may yet see the historical peak production of many of the states above eventually exceeded, and indeed perhaps even for the United States as a whole.
But it’s also worth noting that as we moved through the succession of colors in the graph above we have been turning to increasingly more expensive sources of oil. Today’s frackers would all be put out of business if we were to return to the oil prices of a decade ago.
And even if prices remain high or go higher, eventually that green curve is going to turn around and start falling with the others.
State level employment data will be released by the BLS on Friday, but state agencies have already released data (h/t J. Miller) confirming that Wisconsin private employment performance deteriorates, while Kansas continues to trend sideways. So much for the benefits of a high ALEC-Laffer ranking.
Figure 1: Log private nonfarm payroll employment for Wisconsin (red), Minnesota (blue), California (teal), Kansas (green) and the US (black), all seasonally adjusted, 2011M01=0. Vertical dashed line at beginning of terms for indicated governors. California data from May release. Source: BLS, WI DWD, MN DEED, KS DoL, and author’s calculations.
Figure 2: Log nonfarm payroll employment for Wisconsin (red), Minnesota (blue), California (teal), Kansas (green) and the US (black), all seasonally adjusted, 2011M01=0. Vertical dashed line at beginning of terms for indicated governors. California data from May release. Source: BLS, WI DWD, MN DEED, KS DoL, and author’s calculations.
Given Kansas economic performance, it is unsurprising that there is some angst within the governing party regarding the conduct of policy . As for Wisconsin, total nonfarm employment rose 2400, and private nonfarm employment fell 1200. Both series May entries were revised downward, 400 and 500, respectively.
As noted in this post, based on the Quarterly Census of Employment and Wages (QCEW) which Governor Walker was in favor of citing before he was against citing it (see a chronology here), there is likely to eventually be a substantial downward revision of even these lackluster numbers.
Update, 7/18, 11:40AM Pacific: BLS data are now out; updated versions of Figures 1 and 2 are below.
Figure 1a: Log private nonfarm payroll employment for Wisconsin (red), Minnesota (blue), California (teal), Kansas (green) and the US (black), all seasonally adjusted, 2011M01=0. Vertical dashed line at beginning of terms for indicated governors. Source: BLS, and author’s calculations.
Figure 2a: Log nonfarm payroll employment for Wisconsin (red), Minnesota (blue), California (teal), Kansas (green) and the US (black), all seasonally adjusted, 2011M01=0. Vertical dashed line at beginning of terms for indicated governors. Source: BLS, and author’s calculations.
Further note that the deceleration in growth for Wisconsin and Kansas is statistically significant, as judged using a panel regression of first differences, and a dummy taking on a value of unity from 2011M01 onward. The coefficient estimates on the dummy (with growth relative to the Nation annualized) plus/minus 90% confidence bounds are shown in Figure 3.
Figure 3: Change in annualized m/m growth rates in private employment growth relative to Nation’s, 2011M01-present vs 1990M01-2010M12. Point estimate at bar, line spans 90% confidence interval. Obtained from fixed effects panel regression on four state series. Robust standard errors allowing for panel serial correlation (PCSE). Source: BLS and author’s calculations.
It is useful to recall that Wisconsin and Kansas were 17th and 16th respectively in the 2014 ALEC-Laffer rankings. Minnesota was 46th, and California 47th.
And so the experiment continues.
Oh, and by the way, in order to hit the 250,000 new jobs target that Governor Walker reiterated nearly a year ago, the Wisconsin economy would need to generate about 20 thousand new jobs for each of the next seven months after June. The mean rate of job creation during the first three and a half years of Governor Walker’s term is about 2800 (standard deviation of 4000). Slightly over two years ago, I had an email exchange with a DoR official, who indicated the Walker Administration believed the job gains were “backloaded”, i.e., to appear close to the end of the Governor’s term. I believe I am on safe ground when I conclude that achievement of this promise is unlikely.
Update, 7/19, 10AM Pacific: Reader Bruce Hall, apparently without consulting actual data, writes:
Rates of change are a good comparison… when the starting points are the same. By that I mean the starting point for which the rate is based, not the temporal point.
I’ve made the point before that an F student improving to a C is great news, but doesn’t mean that is a better achievement than another student going from a C to a B or simply maintaining an A. The same thing applies to states that wallowed in unemployment and have improved to less than average.
Bruce Hall has made this statement twice, so I think it useful to show exactly how these states rate in terms of per capita real gross state product. The shaded area pertains to the period in which Governors Brown, Brownback, Dayton, and Walker were in power.
Figure 4: Per capita Gross State Product in Ch.2005$, for Minnesota (blue), Wisconsin (red), Kansas (green) and California (teal). Shaded area pertains to 2011-13. Source: BEA, FRED, author’s calculations.
Note that the recent accelerated downturn in Kansas as measured by the Philadelphia Fed’s coincident indices do not show up in this graph, as these occur primarily in 2014. See this post for a depiction.
In other words, even taking into account starting points, and levels, California and Minnesota appear to be outpacing Wisconsin and Kansas.
Today, we’re fortunate to have Alex Nikolsko-Rzhevskyy, Assistant Professor of Economics at Lehigh University, David Papell and Ruxandra Prodan, respectively Professor and Clinical Assistant Professor of Economics at the University of Houston, as Guest Contributors
The “Federal Reserve Accountability and Transparency Act of 2014″, introduced into Congress on July 7, requires the Fed to adopt a policy rule. It actually specifies two rules. The “Directive Policy Rule” would be chosen by the Fed, and would describe how the Fed’s policy instrument, such as the federal funds rate, would respond to a change in the intermediate policy inputs, presumably inflation and one or more measures of real economic activity such as the output gap, the unemployment rate, and real GDP growth. If the Fed deviated from its rule, the Chair of the Fed would be required to testify before the appropriate congressional committees as to why it is not in compliance. In addition, the report must include a statement as to whether the Directive Policy Rule substantially conforms to the “Reference Policy Rule,” with an explanation or justification if it does not. The Reference Policy Rule is specified as the sum of (a) the rate of inflation over the previous four quarters, (b) one-half of the percentage deviation of real GDP from an estimate of potential GDP, (c) one-half of the difference between the rate of inflation over the previous four quarters and two, and (d) two. This is the Taylor rule, and is obviously not chosen by the Fed. John Taylor has recently discussed this proposed legislation on his blog and in Congressional testimony.
What is the justification for using the Taylor rule as the Reference Policy Rule? We recently presented a paper, “Deviations from Rules-Based Policy and Their Effects,” at a conference on “Frameworks for Central Banking in the Next Century” at the Hoover Institution. Using real-time data on inflation and the output gap from 1965 – 2013, we calculate policy rule deviations, the absolute value of the difference between the actual federal funds rate and the rate prescribed by (1) the “original” Taylor rule described above, (2) a “modified” Taylor rule with a coefficient of one, instead of one-half, on the output gap, and (3) an “estimated” Taylor rule from a regression of the federal funds rate on a constant, the inflation rate, and the output gap. We use the shadow federal funds rate in Wu and Xia (2014) to capture the effects of unconventional monetary policy after 2008. The estimated Taylor rule has almost the same coefficients on inflation and the output gap as the original Taylor rule, but a lower intercept, which is consistent with either an inflation target higher than two or a lower equilibrium real interest rate. Janet Yellen has expressed her preference for the modified Taylor rule over the original Taylor rule.
We identify monetary policy eras by allowing for changes in the mean of the policy rule deviations with tests for multiple structural breaks and tests for multiple restricted structural changes, which restrict the mean of the deviations in the small and large deviations periods to be the same. The results are depicted in Figure 1, with discretionary eras defined by large deviations and rules-based eras defined by small deviations. The original Taylor rule produces rules-based eras for 1966 – 1974 and 1985 – 2000 and discretionary eras for 1974 – 1984 and 2001 – 2013. For the modified Taylor rule, the first discretionary era starts in 1977 and there is a significant break in 2006:Q3, producing an additional rules-based era for 2007 – 2013. With the estimated Taylor rule, the last break for the restricted and unrestricted tests is very different and the last discretionary era runs from 1995 – 2013. The result that policy during 2007 – 2013 is discretionary according to the original Taylor rule and rules-based according to the modified Taylor rule is consistent with Fed policy since 2008 being more stimulative than would be warranted by the original Taylor rule.
Figure 1. Structural Change Tests for Taylor Rule Deviations
A. Original Taylor Rule: Restricted Structural Change Model
B. Modified Taylor Rule: Restricted Structural Change Model
C. Estimated Taylor Rule: Structural Change Model
We proceed to analyze the effects of deviations from rules-based policies by comparing the economic performance between our rules-based and discretionary eras. Using six loss functions involving inflation and unemployment: Okun’s misery index, a linear absolute loss function, and four quadratic loss functions, we show that economic performance is uniformly better in rules-based than in discretionary eras. The results, reported in Columns 1 and 2 of Table 1, hold for all three rules and are robust to specifications of quadratic loss functions that put greater weight on either inflation or unemployment loss and to a specification that puts all weight on inflation loss.
While economic performance is always better in rules-based eras than in discretionary eras, the effects of the deviations differ systematically among the rules. The ratio of the loss during discretionary eras to the loss during rules-based eras is reported in Column 3 of Table 1. The loss ratio is largest for the original Taylor rule, next largest for the modified Taylor rule, and smallest for the estimated Taylor rule. The results in Table 1 are robust to deleting the periods when Paul Volcker raised the federal funds rate more than two percentage points above the Taylor rule benchmark in order to bring down inflation and restore Fed credibility, which arguably should not be classified as part of the discretionary eras. Using the original Taylor rule as a benchmark provides the sharpest evidence of the negative effects of deviating from policy rules.
How does this relate to the proposed legislation? Our evidence that, regardless of the policy rule or the loss function, economic performance in rules-based eras is always better than economic performance in discretionary eras supports the concept of a Directive Policy Rule chosen by the Fed. But our results go further. The original Taylor rule provides the strongest delineation between rules-based and discretionary eras, making it, at least according to our metric and class of policy rules, the best choice for the Reference Policy Rule.
In the current political climate, the proposed legislation will inevitably be interpreted in partisan terms because it was introduced in the House Financial Services Committee by two Republican Congressman. Not surprisingly, the first reporting on the legislation by Reuters was entirely political. This is both unfortunate and misleading. We divided our rules-based and discretionary eras with the original Taylor rule between Republican and Democratic Presidents. If we delete the Volcker disinflationary period, out of the 94 quarters with Republican Presidents, 54 were rules-based and 40 were discretionary while, among the 81 quarters with Democratic Presidents, 46 were rules-based and 35 were discretionary. Remarkably, monetary policy over the past 50 years has been rules-based 57 percent of the time and discretionary 43 percent of the time under both Democratic and Republican Presidents. Choosing the original Taylor rule as the Reference Policy Rule is neither a Democratic nor a Republican proposal. It is simply good policy.
This post written by Alex Nikolsko-Rzhevskyy, David Papell and Ruxandra Prodan.
After the shocker of -2.9% growth (SAAR) in 2014Q1, all eyes have been on Q2. Macroeconomic Advisers released its estimate for May — a 0.2% increase on April (2% on an annualized basis).
Figure 1 presents the Macroeconomic Advisers and e-forecasting estimates, as well as the BEA official figures (3rd release).
Figure 1: GDP from NIPA 3rd release for 2014Q1 (blue bars), Macroeconomic Advisers (red line), and e-forecasting (green line), all SAAR, in billions of Ch.2009$. NBER defined recession dates shaded gray. Source: BEA, Macroeconomic Advisers (7/16), e-forecasting flash estimate (7/11), and NBER.
Macroeconomic Advisers’ nowcast for the quarter is 2.9% (SAAR). The Atlanta Fed’s nowcast as of information available on 7/15 is 2.7%.
Side note – Philadelphia Fed now implements the Aruoba, Diebold, Nalewaik, Schorfheide, and Song GDPplus measure, which indicates a smaller than 3% decline for 2014Q1 (see Diebold’s discussion here).
This is not the most erudite debate, but it pretty much sums up matters.
Reality check: Figure 1 below depicts the evolution of the nominal trade weighted dollar, inflation and Treasurys.
Figure 1: Nominal trade weighted value of the US dollar – broad currency basket, 1973M03=100 (blue, left scale), CPI 12 month inflation (red, right scale), and ten year constant maturity Treasury yields (teal, right scale). Inflation calculated as log differences. NBER defined recession dates shaded gray. Dashed vertical line at 2009M02, passage of American Recovery and Reinvestment Act. Source: Federal Reserve Board for exchange rate, FRED, NBER, and author’s calculations.
By my viewing, the dollar has not collapsed. It’s about 7.6% weaker than when quantitative easing began, while inflation and the interest rate are both lower. I think it incumbent on the Santelli’s of the world to explain the intellectual underpinnings for their Weltanschauung.
Update, 10:10AM Pacific: I see I am way behind the curve. Here is Paul Krugman‘s take on the Liesman-Santelli exchange.
I must confess, I did find it disconcerting when the traders applauded Santelli — not surprised — just sad.
Quick links to a few items I found interesting.
Nowcasts of GDP. Want to know what the latest economic releases imply for the current quarter’s GDP? The Federal Reserve Bank of Atlanta is now making publicly available the forecasts from its GDPnow model which is updated with each new economic release. The July 10 inference is that we might see 2014:Q2 GDP come in at a 2.6% annual growth rate. Private-sector services like Now-casting.com provide estimates based on alternative models for a number of different countries.
Meeting Menzie Chinn. Most people are surprised to learn that although Menzie and I have been working as a cyberspace team and have been in nonstop email communication with each other every week for the last 10 years, we had never met in person until this week. Fate finally brought us together in non-cyberspace reality when we converged in Boston for seminars and discussions hosted by the National Bureau of Economic Research. Photo courtesy of University of Houston Professor David Papell.
From Reuters today:
Russia’s economy is stagnating as data showed on Wednesday that capital worth $75 billion has left the country so far this year following sanctions on Moscow over its involvement in Ukraine.
“We have for now a period of stagnation, or a pause in growth,” Deputy Economy Minister Andrei Klepach was quoted as saying in an interview where he also said that GDP was flat from April to June after shrinking 0.5 percent in the first quarter.
Here are some indicators of stress from political uncertainty, from the IMF’s recent Article IV report on the Russian Federation.
And here is an updated version of GDP growth.
Figure 1: Russian q/q annualized GDP growth, in 2000 prices. Source: OECD via FRED through 2013Q4, Reuters for 2014, and author’s calculations.
From the report:
Net private capital outflows increased significantly in the first quarter of 2014 to US$51 billion (Figure 2 and Box 3). Reserves at the CBR experienced additional downward pressures following the sharp increase in FX intervention in early March. The increased level of FX swaps and correspondent accounts between the CBR and domestic banks has temporarily cushioned the level of reserves, which have not declined by the total amount of interventions. While FX swaps were used to access CBR liquidity, the increase in the level of correspondent accounts at the CBR has reflected increased foreign assets repatriation by domestic banks amidst increasing geopolitical uncertainties.
Geopolitical tensions are negatively weighing on the cost and access to financing. Since March, sovereign and private issuances have declined very sharply, with borrowing rates increasing by an average of 100–150 basis points (Figure 2). The government has also cancelled a number of domestic auctions. Moody’s and Fitch revised the outlook on Russia’s sovereign BBB rating from stable to negative while S&P downgraded the sovereign rating by one notch to BBB-, its lowest investment grade category. This downgrade forced similar ratings cut on major Russian corporations such as Gazprom, Rosneft, and VTB bank, as well as subsidiaries of international banks. The geopolitical uncertainty has also given rise to dollarization pressures.
The outflow of $75 billion means that $24 billion worth of capital left Russia (on net) in the second quarter. While this means the pace of outflows is declining, it also means that the first half of the year witnessed a greater outflow than in the entirety of 2013. For certain, Russia seems on the way to the $100 billion outflow for 2014 that some had warned of.
How much of this outflow, and hence weakness in growth, is due to the imposition of sanctions, or the uncertainty associated with the possibility of additional sanctions? From Reuters:
Deputy Finance Minister Sergei Storchak said on Tuesday that sanctions were having a serious indirect impact” and warned of retaliation against further measures by the West.
“The real damage to the economy is potentially much more serious and comes from the voluntary self-sanctions taken by foreign investors, credit providers and some foreign companies active in Russia,” Chris Weafer, a partner of Macro-Advisory, a consulting firm in Moscow, said in a note published by the European Leadership Network.
“While not compelled legally to restrict activities in Russia it is clear that many investors and big international companies have suspended new deals in Russia and have cut risk exposure.”
In other words, the impact has been greater than some skeptics have asserted, and perhaps more in line with my earlier views 
Reader Rick Stryker writes, after asserting Paul Krugman has misrepresented history:
…apologists fall back on the claim that Obamacare is a conservative idea. … That’s nonsense.
Let me quote from A National Health System for America (Heritage Foundation, 1989), chapter 2, by Stuart A. Butler, Director of Domestic Policy Studies at the Heritage Foundation:
Creating a New Health Care System for Americans
By modifying the existing system, the U.S. can develop a new health care system that will achieve the stated but unfulfilled goals of health care systems overseas — choice, access, and economy.
Element #1: Every resident of the U.S. must, by law, be enrolled in an adequate health care plan to cover major health care costs.
This requirement would imply a compact between the U.S. government and its citizens: in return for the government’s accepting an obligation to devise a market-based system guaranteeing access to care and protecting all families from financial distress due to the cost of an illness, each individual must agree to obtain a minimum level of protection. This means that, while government would take on the obligation to find ways of guaranteeing care fore those Americans unable to obtain protection in the market, perhaps because of chronic health problems or lack of income, Americans with sufficient means would no longer be able to be “free riders” on society by avoiding sensible health insurance expenditures and relying on others to pay for care in an emergency or in retirement.
The requirement to obtain basic insurance would have to be enforced. The easiest way to monitor compliance might be for households to furnish proof of insurance when they file their tax returns. … If the family did not enroll in another plan before the first insurance coverage lapsed and did not provide evidence of financial problems, a fine might be imposed.
The entire Heritage Foundation document is here. Chapter 2, written by Stuart A. Butler, Director of Domestic Policy Studies at the Heritage Foundation, starts at page 35.
From today’s FT:
ECB under pressure to tackle ‘crazy’ euro
Pressure is mounting on the European Central Bank to take action against a persistently strong euro with a leading industrialist calling on Frankfurt to tackle the “crazy” strength of the currency.
Fabrice Brégier, chief executive of Airbus’s passenger jet business, said the ECB should intervene to push the value of the euro against the dollar down by 10 per cent from an “excessive” $1.35 to between $1.20 and $1.25.
Following the euro over time, it’s clear that the euro is fairly strong, although not matching the levels in period just around the financial crisis. Remember, however, the dollar was particularly weak — and hence the euro particularly strong — just before the onset of the recession.
Figure 1: Log trade weighted value of the euro (broad), nominal (blue) and real (red), 2010=0. NBER defined US recession dates shaded gray. Dashed line at Lehman bankruptcy. Source: BIS.
Still, with euro area growth just barely creeping into the positive area, and with inflation far below target range, one could easily see how a weaker euro could help on both counts.
In terms of competitiveness, one would want to look to the unit labor cost deflated measures, rather than the CPI-deflated measure. Here, the same pattern emerges.
Figure 2: Log CPI-deflated trade weighted value of the euro (blue), and relative unit labor cost deflated (red), 2010=0. NBER defined US recession dates shaded gray. Dashed line at Lehman bankruptcy. Source: IMF IFS.
In the past, I (along with Jeff Frieden) have urged an increase in inflation. We didn’t post a mechanism for achieving that higher inflation, although the usual unconventional monetary policy measures — including credit easing– would have been in contention. However, increasing the ECB’s balance sheet faces some difficulties, ranging from legal to operational.
Nonetheless, today’s headline reminded me of Jeff Frankel’s proposal, made back in March.
The ECB should further ease monetary policy. Inflation at 0.8% across the Eurozone is below the target of ‘close to 2%’, and unemployment in most countries is still high. Under the current conditions, it is hard for the periphery countries to bring their costs the rest of the way back down to internationally competitive levels as they need to do. If inflation is below 1% Eurozone-wide, then the periphery countries have to suffer painful deflation.
The question is how the ECB can ease, since short-term interest rates are already close to zero.
What, then, should the ECB buy, if it is to expand the monetary base? It should not buy euro securities, but rather US treasury securities. In other words, it should go back to intervening in the foreign exchange market. Here are several reasons why.
First, it solves the problem of what to buy without raising legal obstacles. Operations in the foreign exchange market are well within the remit of the ECB.
Second, they also do not pose moral hazard issues (unless one thinks of the long-term moral hazard that the ‘exorbitant privilege’ of printing the world’s international currency creates for US fiscal policy).
Third, ECB purchases of dollars would help push the foreign exchange value of the euro down against the dollar.
Frankel discusses some of the challenges to this measure. Certainly, there is some question of how other policymakers would react to such a policy measure; however, given current conditions — particularly the pace of inflation in the euro area — this approach should be given serious consideration.
I am a little slow responding to the stunning revision to the first-quarter GDP estimates that came out two weeks ago, but here are my thoughts about the new estimates.
The Bureau of Economic Analysis announced on June 25 that U.S. real GDP fell at a 2.9% annual rate during the first quarter, compared with an initial estimate of 0.1% growth for the quarter that the BEA had initially put out in April. The revision sets a couple of records. For one, it makes 2014:Q1 the worst quarter for GDP since World War II that was not part of an economic recession. The next closest contenders were a drop of almost 2.9% in the second quarter of 1981 and a 2.2% drop in the third quarter of 1973. Each of those was followed by a single quarter of solid GDP growth after which the economy fell into a full-blown recession, constituting some of the evidence behind Jeremy Nalewaik’s claim that the economy often reaches a stall speed just before falling into a recession.
A second record was noted by the White House’s Council of Economic Advisors Chair Jason Furman:
the estimates of GDP growth for 2014:Q1 represent the largest revision from an advance estimate to a third estimate, as well as the largest revision from a second estimate to a third estimate, in the roughly thirty years the Bureau of Economic Analysis has done these estimates.
The biggest single source of discrepancy from the earlier estimates came in health care services, which account for 1/6 of total personal consumption expenditures. Last month the BEA had claimed that health care added 1 percentage point to the Q1 GDP growth rate, whereas the new estimate is that it instead subtracted 0.2 percentage points. Jason Furman explains that the main survey that the BEA uses to track health care spending was not available until this month, and hence there was considerable guesswork in the original estimate. MFR’s Joshua Shapiro nevertheless opines:
This is a crazy-sized revision, and speaks very loudly to the fact that nobody has a real handle on how the introduction of Obamacare has affected these data, nor for how long the distortions may last until things settle down.
The second most important factor in the revision is that the Q1 deterioration of exports is now seen as even worse than originally reported, with lower exports subtracting 1.2 percentage points from the GDP growth rate. Part of this may be payback for unusually strong export numbers for 2013:Q4. But if it signals a weakening in China or other key trading partners it could be more worrisome.
Jason Furman makes a convincing case that some of the other weaknesses in the U.S. first-quarter GDP numbers represent a temporary effect of the unusually severe winter in much of the U.S., as evidenced for example in the March rebound from the January-February dip down in indicators such as light vehicle sales, core retail and food sales, and core capital goods shipments.
So 2014:Q1 does not mark the beginning of a new recession. As for whether it could turn out to be a replay of 1981:Q2 or 1973:Q3, we’ll have to wait and see.
“…SNAP and Medicaid. These are programs for People Who Do Not Work.”
Is this statement true?
Stigma associated with the SNAP program has led to several common misconceptions about how the program works and who receives the benefits. For instance, many Americans believe that the majority of SNAP benefits go towards people who could be working. In fact, more than half of SNAP recipients are children or the elderly. For the remaining working-age individuals, many of them are currently employed. At least forty percent of all SNAP beneficiaries live in a household with earnings. At the same time, the majority of SNAP households do not receive cash welfare benefits (around 10% receive cash welfare), with increasing numbers of SNAP beneficiaries obtaining their primary source of income from employment.
According to Garber/Collins (2014):
Prior to the waiver approval, working parents up to 16 percent of poverty were eligible for Medicaid…Currently, working parents under 33 percent of poverty and individuals ages 19 and 20 under 44 percent of poverty are eligible for Medicaid.
Now it is true that, as CBPP notes, many working poor do not qualify for Medicaid under the old provisions (and in states that refused to expand Medicaid):
In the typical (or median) state today, a working-poor parent loses eligibility for Medicaid when his or her income reaches only 63 percent of the poverty line (about $12,000 for a family of three in 2012). An unemployed parent must have income below 37 percent of the poverty line (about $7,100 in 2012) in the typical state in order to qualify for the program.
The irony is that Medicaid expansion would eliminate disincentives to earn income through working. As outlined here, most of the beneficiaries of a Medicaid expansion in those states that have not yet taken the offer would be working poor — between nearly 60 to 66% in Virginia, Missouri and Utah.
I don’t typically cite anecdotes, but this one seemed sufficiently illustrative to merit quotation. From an October 2013 NYT article:
About half of poor and uninsured Hispanics live in states that are expanding Medicaid. But Texas, which has a large Hispanic population, rejected the expansion. Gladys Arbila, a housekeeper in Houston who earns $17,000 a year and supports two children, is under the poverty line and therefore not eligible for new subsidies. But she makes too much to qualify for Medicaid under the state’s rules. She recently spent 36 hours waiting in the emergency room for a searing pain in her back.
“We came to this country, and we are legal and we work really hard,” said Ms. Arbila, 45, who immigrated to the United States 12 years ago, and whose son is a soldier in Afghanistan. “Why we don’t have the same opportunities as the others?”
Update, 7/5, 12:10PM: Just to be sure we are in agreement, I want to remind readers of how many of the people you meet on a day to day basis working at their job are on SNAP (Bloomberg, October 25, 2013):
America’s low-wage, fast-food workers have been making a lot of news lately. Researchers at Berkeley released a report calculating that 52 percent of families of fast-food workers are enrolled in at least one public-assistance program, at a cost to taxpayers of about $7 billion a year. McDonald’s employees, working for the biggest burger chain in the country, accounted for about $1.2 billion of that total.
Now a McDonald’s (MCD) help line for employees, called McResource Line, has come to broader attention, courtesy of an advocacy group called Low Pay Is Not OK. In a taped conversation published online, a help-line representative is heard offering to help one McDonald’s worker access a range public resources, from food stamps to Medicaid.
The employee, Nancy Salgado, earns $8.25 an hour after working for a decade at a McDonald’s in Chicago. She can be heard describing the two kids she is raising on her own and asks for help to make ends meet. The McResource representative does her job well: She’s matter-of-fact about Salgado’s predicament, calmly explains the benefits Salgado might be eligible for, and answers all her questions. During the entire 14-minute conversation reviewed by Bloomberg Businessweek, Salgado doesn’t ask why the McDonald’s franchisee pays her less than she needs to raise a family, and the McResource representative never suggests Salgado should be paid more.
So, I will hazard a guess that there is not an inconsequential number of people on SNAP who “work”.
Rapid and broad based employment growth
Figure 1: Log nonfarm payroll employment from establishment series (blue), and from household series adjusted to conform to NFP concept (red), 2007M12=0, seasonally adjusted. NBER defined recession dates shaded gray. Source: BEA, NBER, and author’s calculations.
It is of interest to note that the household adjusted series — touted by conservatives during the G.W. Bush era as a better measure of nonfarm payroll employment — first exceeded the previous peak in January 2014, with no apparent mention by those same individuals. By that metric, total nonfarm employment has exceeded its previous peak by nearly one percent.
Figure 2: Log private nonfarm payroll employment from establishment series (blue), and aggregate hours (red), 2007M12=0, seasonally adjusted. NBER defined recession dates shaded gray. Source: BEA, NBER, and author’s calculations.
Not only has growth (by either total or private employment) over the past five months matched or exceeded 200K, revisions are typically to the upside.
Figure 4: Private nonfarm payroll employment January release (blue), February release (red), March release (green), April release (black), May release (teal), and June release (purple). Source: BLS.
A reassuring point, made by Jason Furman at the CEA, is that the advance in employment is broad based.
Figure 5: Source: Furman/CEA.
None of the foregoing should be viewed as a triumph of macroeconomic policy. For once I agree with Joint Economic Committee Chair Kevin Brady who stated “Today’s strong jobs report comes as a welcome relief to Americans on Main Street. Unfortunately, as good as today’s report is, the rate of job growth still isn’t sufficient to eliminate the private sector jobs gap by the time President Obama leaves office.” And the reason for that, in addition to the hangover from the debt binge of the 2000′s, is the imposition of too-early and unwise fiscal contraction (think sequester, cutting off extended unemployment, failure to extend SNAP, and failure to undertake additional infrastructure investments). Had there been less single-minded obstructionism, fiscal policy would have been much more counter-cyclical in nature, and the employment recovery accelerated.
With the acceleration in employment growth, there is ample discussion of tightening labor market and — without too much evidence — rising compensation costs.  The latest release does not provide much additional evidence of accelerating wage costs.
Figure 6: 12-month percent change in average hourly earnings for private sector production and nonsupervisory workers (blue), and for all private sector workers (red), and for CPI-all, all calculated as 12 month log differences. NBER defined recession dates shaded gray. Source: BLS via FRED, NBER, and author’s calculations.
Many reporters have been pushing the meme that:
Consumers will pay the highest Fourth of July gasoline prices in six years.
That’s true, though as the EIA noted today:
Although this is the highest average heading into the Fourth of July holiday since 2008, gasoline prices in 2014 have remained well below the spring peaks reached in each of the previous three years.
|New Jersey Historical Gas Price Charts Provided by GasBuddy.com|
Oil prices have actually moved lower over the last three weeks, meaning that as long as the situation in Iraq does not deteriorate further, U.S. retail gasoline prices are likely headed down, not up over the next few weeks.
But we wouldn’t want to let the facts get in the way of trying to make a story sound more interesting, would we?
I’ve just returned from two highly stimulating conferences in Beijing. The first was a Columbia-Tsinghua conference on “Capital Flows and International Financial Systems”, organized by Jiandong Ju and Shang-Jin Wei, and the second a NBER-China Center for Economic Research conference on “China and the World Economy”, organized by Yang Yao, Shang-Jin Wei, and Chong-En Bai.
The RMB Exchange Rate, Capital Market Openness, and Financial Reforms in China
Figure 1: Aizenman-Chinn-Ito trilemma indices for China. ERS (blue) is exchange rate stability, inverse of standard deviation of exchange rate changes; MI (red) is monetary independence, inverse of correlation of policy interest rate with base country interest rate; KAOPEN is Chinn-Ito financial openness index. See here. Source: ACI
A policy panel at the Columbia-Tsinghua conference was chaired by Chaired by Shang-Jin Wei (Chief Economist Designate, Asian Development Bank, Professor of Economics at Columbia University, and NBER). The participants were:
- Joshua Aizenman (Professor of Economics and International Relations, University of Southern California and the NBER)
- Menzie Chinn (Professor of Public Affairs and Economics, University of Wisconsin, Madison, and NBER)
- Pierre-Olivier Gourinchas (Professor of Economics, University of California Berkeley and NBER)
- Fan He (Professor and Associate Dean, The Institute of International Economics and Politics, The Chinese Academy of Social Science)
- Jiandong Ju (Professor and Director, Center for International Economic Research at Tsinghua University)
- Jun Ma (Chief Economist, Research Department, People’s Bank of China; former Chief Economist for Greater China, Deutsche Bank)
The presentations were not made available online, and I can’t do justice to all the presentations. However, one surprising aspect of the discussion was the widespread agreement that capital account liberalization was an undertaking that needed to be conducted very slowly and deliberately. Aizenman (presentation), Gourinchas and He highlighted the potential for financial or balance of payments crises should capital account and domestic financial liberalization be improperly sequenced. Gourinchas further noted that the benefits of capital account openness were uncertain, and apparently relatively small, so the urgency for liberalization was not so great. (Update: Gourinchas’s points here.)
Both He and Ma noted that capital account liberalization had already progressed to a certain extent, with Ma making the case more forcefully. Ju argued that premature liberalization of the capital account could lead to capital flight and and domestic financial crisis as the housing market collapsed. Some discussion of the Ma, He, and Ju presentations are reported in the People’s Daily.
The major point of my presentation was that development of the RMB as an international currency was not costless, despite the pride that might be engendered by such a outcome. In particular, an internationalized currency exposes an economy to external shocks, and some loss of monetary autonomy if other countries peg to it. Such already seems to be the case for China. Some of these points are discussed in this paper.
International Economics (Columbia-Tsinghua)
I couldn’t attend all the sessions at the Columbia-Tsinghua conference (there were at times parallel sessions), but here are some of the papers I caught.
Jing Zhang (FRB Chicago) presented “Saving Europe?: The Unpleasant Arithmetic of Fiscal Austerity in Integrated Economies” (with E. Mendoza and L. Tesar).
What are the macroeconomic effects of tax adjustments in response to large public debt shocks in highly integrated economies? The answer from standard closed-economy models is deceptive, because they underestimate the elasticity of capital tax revenues and ignore crosscountry spillovers of tax changes. Instead, we examine this issue using a two-country model that matches the observed elasticity of the capital tax base by introducing endogenous capacity utilization and a partial depreciation allowance. Tax hikes have adverse effects on macro aggregates and welfare, and trigger strong cross-country externalities. Quantitative analysis calibrated to European data shows that unilateral capital tax increases cannot restore fiscal solvency, because the dynamic Laffer curve peaks below the required revenue increase. Unilateral labor tax hikes can do it, but have negative output and welfare effects at home and raise welfare and output abroad. Large spillovers also imply that unilateral capital tax hikes are much less costly under autarky than under free trade. Allowing for one-shot Nash tax competition, the model predicts a “race to the bottom” in capital taxes and higher labor taxes. The cooperative equilibrium is preferable, but capital (labor) taxes are still lower (higher) than initially. Moreover, autarky can produce higher welfare than both Nash and Cooperative equilibria.
Yinqiu Lu (IMF) presented “Emerging Market Local Currency Bond Yields and Foreign Holdings in the Post-Lehman Period – a Fortune or Misfortune?” (with C. Ebeke):
The paper shows that foreign holdings of local currency government bonds in emerging
market countries (EMs) have reduced bond yields but have somewhat increased yield volatility in the post-Lehman period. Econometric analyses conducted from a sample of 12 EMs demonstrate that these results are robust and causal. We use an identification strategy exploiting the geography-based measure of EMs financial remoteness vis-à-vis major offshore financial centers as an instrumental variable for the foreign holdings variable.The results also show that, in countries with weak fiscal and external positions, foreign holdings are greatly associated with increased yield volatility. A case study using Poland data elaborates on the cross country findings.
Likun Wang (Goethe University Frankfurt) presented “Exchange rate, risk premium and factors: what can term structure of interest rates tell us about the dynamics of the exchange rate?”:
In this paper, I investigate the role of expectations on the current and future status of economies in determining the dynamics of the exchange rate, through the channel of risk premium for holding a currency. The risk premium is introduced as an additional term to a best-fit time series model and is instrumented by bilateral latent factors obtained from the term structure of interest rates. Results show that it can significantly improve the baseline model in terms of in-sample goodness of fit and out-of-sample accuracy of forecast in exchange rate changes. The non-linearity of the risk premium in latent factors further renders state-dependent and time-varying response of change in exchange rate to an identified monetary policy adjustment. Above findings hold for seven out of eight advanced-economy currency pairs (AUD, CAD, GBP, JPY, NOK, NZD, SEK against USD). Once included in the Fama regression, the risk premium can also help in solving the UIP Puzzle, which has been detected in the cases of GBP/USD and JPY/USD.
Other presentations (w/o papers online):
- Jie Li (Central University of Finance and Economics), “Volatility of capital flows: the role of financial reforms” (with Z. Shen).
- Xiaoqiang Cheng (Hong Kong Monetary Authority), “Market segmentation, fundamentals or contagion? Assessing competing explanations for CNH-CNY pricing differentials” (with M. Funke, Chang Shu, and S. Eraslan.
- Oliver Hossfeld (Deutsche Bundesbank), “Carry funding and safe haven currencies: a threshold regression approach” (with R. MacDonald).
- Menzie Chinn (University of Wisconsin Madison, and NBER), “Global Supply Chains and Macroeconomic Relationships” (based on this paper)
- Joshua Aizenman (University of Southern California and the NBER), “The Housing Sector – Too Big and Too Bubbly to Ignore” ([presentation], related paper Real Estate Valuation, Current Account and Credit Growth Patterns, Before and After the 2008-9 Crisis”)
- Pierre-Olivier Gourinchas (University of California Berkeley and NBER), “External Adjustment, Global Imbalances, Valuation Effects” (based on External Adjustment, Global Imbalances, Valuation Effects)
- Pol Antràs (Harvard University and NBER), “Contracts and Global Value Chains” (based on this paper)
picture here (Ju, Chinn, Antràs, Gourinchas, Wei)
International Finance (NBER-CCER)
[my inexact summaries in brackets when the paper is not available online]
- Menzie Chinn (Wisconsin, Madison and NBER), “The Trilemma and Reserves: Measurement and Policy Implications” (presentation)
- Yang Yao (CCER), “Financial Structure and Current Account Imbalances” (not online) [growth differentials in the context of overlapping generations model explain current account imbalances between the US and China]
Jianguo Xu (CCER): China A-share Stock Valuation: Fundamental Risk and Speculation premium (based on this paper).
- Pierre-Olivier Gourinchas (UC Berkeley and NBER), “Global Safe Assets” (based on this chapter)
- JU Jiandong (Tsinghua), “A Dynamic Structural Analysis of Real Exchange Rate and Current Account Imbalances: Theory and Evidences from China” (with J. Lin, LIU Q., and SHI K.) (not online) [a three sector exportables/importables/nontradables model with excess labor supply explains real exchange rate changes prior to the Lewis turning point]
- Pol Antràs (Harvard University and NBER), “Contract Theory and Global Value Chains” (related presentations, here)
- Shang-Jin Wei (Columbia University and NBER), “Sizing up Market Failures in Export Pioneering Activities” (not online) [structural estimation of export pioneers in the electronics industry; are there enough or too many export pioneers?]
- Miaojie Yu (CCER), “Multiproduct Firms, Export Product Scope, and Trade Liberalization: The Role of Managerial Efficiency” (with L.D. Qiu).
Financial Markets (NBER-CCER)
- Rene Stulz (Ohio State and NBER), “Bank Performance during a Crisis” (not online) [determinants of bank performance during the global financial crisis, including governance, leverage, other factors]
- Joshua Aizenman (NBER and USC), “Real Estate Valuation in the Open Economy” [presentation] (related paper Real Estate Valuation, Current Account and Credit Growth Patterns, Before and After the 2008-9 Crisis”)
- Yiping Huang (CCER), “Financial Liberalization and the Middle-income Trap: What Can China Learn from Multicountry Experience?” (related summary; paper)
I’ve focused my review on the international/macro topics. Other fascinating issues in economics were also covered, including intergenerational mobility, retirement and higher education. For those, see the agenda.
The Extreme Supply-Sider one in Topeka, that is. Josh Barro notes how tax cuts failed to result in entrepreneurial renaissance that would result in revenue increases; Wonkblog further observes (I did before) that employment growth has collapsed utterly and completely. Paul Krugman has dissected the social dynamics underpinning the adherence to patently unsupported ideas, but it is always useful to reiterate the facts of the case.
Kansas is doing so poorly in terms of private employment growth since 2011M01 — the beginning of Governor Brownback’s administration — that it rivals in (poor) performance Wisconsin .
Figure 1: Log private nonfarm payroll employment for Wisconsin (red), Minnesota (blue), California (teal), Kansas (green) and the US (black), all seasonally adjusted, 2011M01=0. Vertical dashed line at beginning of terms for indicated governors. Source: BLS, and author’s calculations.
It turns out that broader measures of economic activity confirm the collapse in growth. The recently released Philadelphia Fed coincident index shows May activity lower than that in January of the year. This means the cumulative growth gap (from 2011M01) between national activity and Kansas has widened to 2.8% (log terms).
Figure 2: Log coincident indices for Kansas (blue) and the US (black), seasonally adjusted, 2011M01=0. Implied levels from leading indices for Kansas (blue square) and US (black triangle) for 2014M11. Dashed lines at 2011M01 (beginning of Brownback administration). Tan shading denotes period that tax cuts apply to. Source: Philadelphia Federal Reserve May releases for coincident indices and leading indices, author’s calculations.
Forward looking indicators from the Philadelphia Fed indicate that over the next six months, the gap will widen — to 3.8% (Figure 2). Figure 3 depicts where Kansas sits in the distribution of state six month growth rates (not annualized). The wisdom of Moody’s decision to downgrade Kansas government bonds in April seems to have been borne out. 
Figure 3: Frequency distribution of six month non-annualized growth rates. Solid red line at Kansas growth rate; solid black line at US growth rate. Source: Philadelphia Fed leading indices, May release.
Kansas sits in the bottom quarter of the distribution. The gap between the US and Kansas non-annualized six month growth is over a percentage point. The corresponding gap over the entire period which the Philadelphia Fed has been tabulating the coincident indices is about a quarter of a percentage point (this is essentially a state-specific “fixed effect”). (Note: one cannot appeal to antediluvian views on the negative impact of minorities on growth, as in this comment, since Kansas is relatively homogeneous.)
Concluding thoughts: After three years of an experiment in ALEC-Laffernomics, Kansas lags the US economy significantly. This should be no surprise to anyone. Over thirty years ago, I interviewed Arthur Laffer for the Harvard International Review about the supply-side scenario. I was skeptical then. I see no reason, from the experience of Kansas, to be any less skeptical now (See this post for a statistical analysis, and links to more comprehensive empirical analyses).
Addendum, 5:50PM Pacific: Bruce Hall, who previously asserted Wisconsin’s negative performance with respect to Minnesota was partly due to the higher minority population in Wisconsin, now asserts California’s outperformance with respect to Kansas is comparable ‘to an F student who raises his grade to a C to an A student who just “plods along.”’, where Kansas is the A student because its government is “well run”.
I have calculated the log ratio of Kansas to California coincident index, taken the first difference and multiplied by 12 (so the coefficients are interpretable as impact on annual growth rates) regressed it on a constant, time trend, and a dummy that takes on a value of one when Governor Brownback comes into office. The time trend thus accounts for the alleged poorly run policies of California. Here are the results:
Δz = -0.020 + 0.00004×time – 0.016×BrownbackDummy
Adj-R2 = 0.02, SER = 0.03. Bold face entries denote significance at the 5% MSL.
The results indicate that relative annual growth is 1.6 percentage points slower under Governor Brownback.