Does news about future productivity cause business cycle fluctuations? What other effects might it have? Barsky, Basu, and Lee explore the answer to this question using semi-structural vector autoregressions (VARs) where "news" is defined as the innovation in the expectation of total factor productivity (TFP) at a fixed horizon in the future. They find that systems incorporating a number of forward-looking variables, including stock prices, consumption, consumer confidence, and inflation, robustly predict two outcomes. First, following a news shock, TFP rises for several years. Second, inflation falls immediately and substantially, and stays low, often for ten quarters or more. Consumption typically rises following good news about the future, but investment, consumer durables purchases, and hours worked typically fall on impact. All the quantity variables subsequently rise, as does TFP. Depending on the specification of the reduced form VAR, the activity variables may lead TFP to some extent, possibly lending support to the hypothesis of news-driven business cycles, or they may move in lockstep with productivity. For the most part, the quantity and inflation responses are quite consistent with the predictions of a standard flexible price real business cycle model augmented with a Taylor rule for the nominal interest rate. In such models, news shocks typically play at most a small role in explaining business cycle fluctuations.
The financial crisis and ensuing Great Recession left the U.S. economy in an injured state. In 2013, output was 13 percent below its trend path from 1990 through 2007. Only a small part of this shortfall--1.8 percentage points of real GDP--was the result of lingering slackness in the labor market in the form of abnormal unemployment and substandard weekly hours of work. The single biggest contributor was a shortfall in business capital, which accounted for 5 percentage points. The second largest was a shortfall of 3.4 percentage points in total factor productivity. The third was a shortfall of 2.5 percentage points in labor force participation. Hall discusses these four sources of the injury in detail, focusing on identifying state variables that may or may not return to earlier growth paths. The conclusion is optimistic about the capital stock and slackness in the labor market, and pessimistic about reversing the declines in total factor productivity and the part of the participation shortfall not associated with the weak labor market.
In addition to the conference paper, the research was distributed as NBER Working Paper w20183, which may be a more recent version.
U.S. labor and total factor productivity growth slowed several years prior to the Great Recession. Fernald argues that the timing rules out stories related to disruptions from the Great Recession, and that industry and state data rule out "bubble economy" stories related to housing or finance. In industry and state data, the slowdown is especially pronounced for industries that use information technology (IT) intensively as well as for IT producers. These results are consistent with a return to more normal productivity growth after nearly a decade of extraordinary gains associated with IT. A calibrated growth model suggests trend productivity growth is similar to its 1973-95 trend. Slower underlying productivity growth also has implications for current assessments of economic slack. As of 2013, two alternatives to the benchmark Congressional Budget Office measure imply lower potential output and smaller output gaps. About three-quarters of the shortfall of actual output from (overly optimistic) pre-recession estimates of trend reflects a reduction in the level of potential.
In addition to the conference paper, the research was distributed as NBER Working Paper w20248, which may be a more recent version.
Chung, Herbst, and Kiley explore the importance of the nature of nominal price and wage adjustment for the design of effective monetary policy strategies, especially at the zero lower bound. Their analysis suggests that sticky-price and sticky-information models fit standard macroeconomic time series comparably well. However, the model with information rigidity responds differently to anticipated shocks and persistent zero lower bound episodes, which is important to a degree for monetary policy and for understanding the effects of fundamental disturbances when monetary policy cannot adjust. Despite these differences, many aspects of effective policy strategy are common across the two models. In particular, highly inertial interest rate rules that respond to nominal income or to the price level perform well even when hit by adverse supply shocks or by large demand shocks that induce the zero lower bound. By contrast, rules that respond to the level or change in the output gap can perform poorly under those conditions.
Vodenska and Chambers study the VIX Index, often referred to as "the investor's fear gauge," relative to the observed volatility of the S&P 500 Index to investigate the relationship between these two measures of financial market variability and to understand the directionality of their influence on each other. Calculated as a weighted average of put and call options on the S&P 500 Index, the VIX is considered a forecasting indicator of the S&P 500 Index's volatility over a one-month period. The authors examine the daily VIX and S&P 500 Index volatility data for the 20-year period between 1990 and 2009 and find that VIX lags the S&P 500 one-month volatility for the period studied. Furthermore, they analyze the VIX Index and S&P 500 volatility for different time periods, when the financial markets exhibit: 1, higher levels of stability with volatility below two standard deviations from the mean; and 2, lower stability regimes with volatilities above two standard deviations from the mean. The authors find that in general, the VIX overestimates S&P 500 Index volatility during stable financial market regimes, and underestimates S&P 500 Index volatility throughout high volatility periods.
Hassan and Mertens solve and quantitatively analyze a canonical noisy rational expectations model (Hellwig 1980) within the framework of a conventional real business cycle model. Each household receives a private signal about future productivity. In equilibrium, the stock price serves to aggregate and transmit this information. The authors find that dispersed information about future productivity affects the quantitative properties of their real business cycle model in three dimensions. First, households' ability to learn about the future affects their consumption-savings decision. The equity premium falls and the risk-free interest rate rises when the stock price perfectly reveals innovations to future productivity. Second, when noise trader demand shocks limit the stock market's capacity to aggregate information, households hold heterogeneous expectations in equilibrium. However, for a reasonable size of noise trader demand shocks, the model cannot generate the kind of disagreement observed in the data. Third, even moderate heterogeneity in the equilibrium expectations held by households has a sizable effect on the level of all economic aggregates and on the correlations and standard deviations produced by the model. For example, the correlation between consumption and investment growth is 0.29 when households have no information about the future, but 0.41 when information is dispersed.
Large numbers of workers in the middle of the skill distribution lost their jobs in the Great Recession. Middle-skill occupations have also faced the weakest job growth during the past several decades because of the "polarization" of job growth at the ends of the skill distribution. To what extent are these two facts related? Search-based models of the labor market imply that firms and workers will take account of poor long-run prospects when considering efficient job separations. Rising wages in high-skill jobs may have also encouraged the efficient dissolution of middle-skill matches. However, using a newly constructed dataset of historical occupation-level employment and unemployment, Foote and Ryan find that recent middle-skill job losses were not far out of line with those in other postwar recessions once the large drop in GDP is taken into account. Using more recent microdata to assess relevant alternatives for unemployed middle-skill workers, the authors find that few of them are able to transition directly to high-skill jobs, in large part because they lack the formal education to do so. This inability to obtain high-skill jobs, combined with the lower wages paid in low-skill service occupations such as custodial work and food preparation, suggests that large numbers of middle-skill workers will respond to polarization by dropping out of the labor force. An investigation of changes in participation rates for prime-age and older males supports this assertion. All told, these findings suggest that large middle-skill losses in recessions--including the most recent one--owe more to the cyclical nature of the industries that employ middle-skill workers than to optimal job-search considerations.
Whither News Shocks?
Effective Monetary Policy Strategies in New Keynesian Models: A Re-examination
Productivity and Potential Output Before, During, and After the Great Recession
Information Aggregation in a DSGE Model
Costs and Benefits to Phasing Out Paper Currency