Information rigidity in growth forecasts: Some cross-country evidence

We document information rigidity in forecasts of real GDP growth in 46 countries over the past two decades. We also investigate: (i) whether rigidities differ across countries, particularly between advanced countries and emerging markets; (ii) whether rigidities are lower around turning points in the economy, such as in times of recessions and crises; and (iii) how quickly forecasters incorporate news about growth in other countries into their growth forecasts, with a focus on the way in which advanced countries’ growth forecasts incorporate news about emerging market growth, and vice versa.     

How common are common return factors across the NYSE and Nasdaq?

We entertain the possibility of pervasive factors that are not common across two (or more) groups of securities. We propose and implement a general procedure to estimate the space spanned by common and group-specific pervasive factors. In our empirical analysis, we study the factor structure of excess returns on stocks traded on the NYSE and Nasdaq using our methodology. We find that there are only two common pervasive factors that govern the returns for both NYSE and Nasdaq. At the same time, the NYSE and Nasdaq each have one more group-specific factor that is not the same across the two exchanges. Our results point to the absence of complete similarity between the factors driving the returns on these exchanges.     

Are US macroeconomic series difference stationary or trend-break stationary?

This article tests for the presence of a unit-root in all time series included in the extended Nelson–Plosser data set using the statistics devised by Zivot and Andrews, Perron and Murray and Zivot. It specifies the mixed model characterization of the trend-break stationary alternative that allows for a simultaneous break in both the intercept and slope of the trend-function. It rejects the unit-root null hypothesis for real GNP, nominal GNP, real per capita GNP, industrial production, employment, GNP deflator, nominal wages, interest rate and common stock prices. Use of appropriate critical values to assess the significance of the trend-function coefficients reveals that the slope-break should be included in real GNP, nominal GNP, real per capita GNP, nominal wages, interest rate and common stock prices. The results indicate that there is less evidence against the unit-root hypothesis with the extended Nelson–Plosser data compared to the original Nelson–Plosser data.     

What Lies beneath? A Sub-National Look at Okun’s Law in the United States

We find that Okun’s Law holds quite well for most U.S. states but the Okun coefficient—the responsiveness of unemployment to output—varies substantially across states. We are able to explain a significant part of this cross-state heterogeneity on the basis of the state’s industrial structure. Our results have implications for the design of state and federal policies and may also be able to explain why Okun’s Law at the national level has remained quite stable over time despite an enormous shift in the structure of the U.S. economy from manufacturing to services.     

The Impact of Trades on Daily Volatility

This article proposes a trading-based explanation for the asymmetriceffect in daily volatility of individual stock returns. Previousstudies propose two major hypotheses for this phenomenon: leverageeffect and time-varying expected returns. However, leveragehas no impact on asymmetric volatility at the daily frequencyand, moreover, we observe asymmetric volatility for stocks withno leverage. Also, expected returns may vary with the businesscycle, that is, at a lower than daily frequency. Trading activityof contrarian and herding investors has a robust effect on therelationship between daily volatility and lagged return. Consistentwith the predictions of the rational expectation models, thenon-informational liquidity-driven (herding) trades increasevolatility following stock price declines, and the informed(contrarian) trades reduce volatility following stock priceincreases. The results are robust to different measures of volatilityand trading activity. (JEL C30, G11, G12)     

Long-run performance following quality management certification

Public firms that seek and successfully receive certification of quality management, type ISO 9000, seem to experience different post-announcement share-price drifts depending on their size. This result is not consistent with the notion that companies seeking to implement a quality management system may be reducing agency problems between managers and shareholders, which are among corporate governance and control goals of any well management company. Otherwise, we should have observed material and positive abnormal share-price changes, following ISO 9000 registration announcements, independently of company size. Our results show that only stocks of large-size firms, experience positive average significantly abnormal returns over the post-announcement 1-, 2-, and 3-year horizons. On the other hand, stocks of small-size firms experience negative average significantly abnormal returns, and stocks of mid-size firms do not show any material gain over the same horizons. Although there is a rich finance literature that has studied the long-run abnormal stock-price returns following several major corporate events, this study seems to be the only one that have examined the potential long-run impact of this certification-event, despite the fact that those standards have been around since the middle 1980s.

Assessing Project Risk

Finding the appropriate discount rate, or cost of capital, for evaluating investment projects requires an accurate estimate of project risk. This can be challenging because project risk cannot be estimated directly using the CAPM, but must instead be inferred from a set of traded securities, typically the equity betas of comparable firms in the same industry. These equity betas are then unlevered to undo the effect of comparable companies' financial leverage and obtain estimates of “asset” betas, which are then used to estimate project risk. The authors show that asset betas estimated in this way are likely to overestimate project risk. The equity returns of companies are risky not only because of their existing projects but also because of their growth opportunities. Such growth opportunities often include embedded “real options,” such as the option to delay, expand, or abandon a project. Because such real options are similar to leveraged positions in the underlying project, a company's growth opportunities are typically riskier than its existing projects. Therefore, to properly assess project risk, analysts must also unlever the asset betas derived from comparable company stock returns for the leverage contributed by their growth options. The authors derive a simple method for unlevering asset betas for growth options leverage in order to properly assess project risk. They then show that standard methods for assessing project risk significantly overestimate project costs of capital—by as much as 2–3% in industries such as healthcare, pharmaceuticals, communications, medical equipment, and entertainment. Their method should also be applied to stock return volatility to derive project volatility, an important input for determining the value of a firm's growth opportunities and the appropriate time for investing in these opportunities.     

An Empirical Investigation of the Campbell-Cochrane Habit Utility Model

Abstract:  This paper tests whether the Campbell and Cochrane (1999) habit utility model generates a valid stochastic discount factor for the 25 Fama-French size/book-to-market and size/momentum sorted portfolios. Campbell and Cochrane (1999) derive a consumption based habit utility asset pricing model and calibrate it to aggregate US stock market data. However, they do not test whether their model is consistent with a larger cross section of asset returns. We test their model using the methodology of Hansen and Jagannathan (1991) and Burnside (1994) . In contrast to previous studies, we find that for reasonable parameter values, the model's stochastic discount factor is inside the Hansen-Jagannathan bounds and therefore satisfies the necessary conditions for a valid stochastic discount factor. We trace the difference between our results and previous studies to the method used to estimate the model's parameters and the parameter values themselves.