This paper tests Mincer's minimum-wage model by estimating reduced-form wage and employment equations for both the covered and uncovered sectors in nine regions of the United States. As theory predicts, in regions with comparatively small covered-sector demand elasticities, the northern and midwestern regions, the uncovered-sector wage increases after a minimum-wage hike; and in regions with comparatively large demand elasticities, the southern and western regions, the uncovered-sector wage decreases. Because of data limitations the uncovered-sector employment effect could not be estimated sharply, and so its relationship to the covered-sector demand elasticity is weak.

[Motivated by the implications from a stylized self-contained general equilibrium model incorporating the effects of time-varying economic uncertainty, we show that the difference between implied and realized variation, or the variance risk premium, is able to explain a nontrivial fraction of the time-series variation in post-1990 aggregate stock market returns, with high (low) premia predicting high (low) future returns. Our empirical results depend crucially on the use of "model-free," as opposed to Black-Scholes, options implied volatilities, along with accurate realized variation measures constructed from high-frequency intraday as opposed to daily data. The magnitude of the predictability is particularly strong at the intermediate quarterly return horizon, where it dominates that afforded by other popular predictor variables, such as the P/E ratio, the default spread, and the consumption-wealthratio.]

The paper examines the role of stability constraints in estimation by dynamic simulation. In particular, it analyzes the behavior of the objective function on either side of the boundary of the stability region of the parameter space. The main finding is that stability constraints may be ignored because the simulation-based objective function contains a built-in penalty to enforce stability. A key caveat, however, is that the dynamic stability of the auxiliary model that defines the moment conditions must be checked and enforced. An attempt to fit via simulation to moments defined by a dynamically unstable auxiliary model can be expected to lead to an ill-behaved objective function.

George Tauchen, An Investigation of Transactions Data for NYSE Stocks: Discussion, The Journal of Finance, Vol. 40, No. 3, Papers and Proceedings of the Forty-Third Annual Meeting American Finance Association, Dallas, Texas, December 28-30, 1984 (Jul., 1985), pp. 739-741

Stock market volatility clusters in time, appears fractionally integrated, carries a risk premium, and exhibits asymmetric leverage effects. At the same time, the volatility risk premium, defined by the difference between the risk-neutral and objective expectations of the volatility, features short memory. This paper develops the first internally consistent equilibrium-based explanation for all these empirical facts. Using newly available high-frequency intraday data for the S&P 500 and the VIX volatility index, the authors show that the qualitative implications from the new theoretical continuous-time model match remarkably well with the distinct shapes and patterns in the sample autocorrelations and dynamic cross-correlations actually observed in the data.

[We undertake a comprehensive investigation of price and volume co-movement using daily New York Stock Exchange data from 1928 to 1987. We adjust the data to take into account well-known calendar effects and long-run trends. To describe the process, we use a seminonparametric estimate of the joint density of current price change and volume conditional on past price changes and volume. Four empirical regularities are found: (i) positive correlation between conditional volatility and volume; (ii) large price movements are followed by high volume; (iii) conditioning on lagged volume substantially attenuates the "leverage" effect; and (iv) after conditioning on lagged volume, there is a positive risk-return relation.]

This paper develops a discrete state space solution method for a class of nonlinear rational expectations models. The method works by using numerical quadrature rules to approximate the integral operators that arise in stochastic intertemporal models. It is particularly useful for approximating asset pricing models and has potential applications in other problems as well. An empirical application uses the method to study the relationship between the risk premium and the conditional variability of the equity returns under ARCH endowment processes.

This paper tests Mincer's minimum-wage model by estimating reduced-form wage and employment equations for both the covered and uncovered sectors in nine regions of the United States. As theory predicts, in regions with comparatively small covered-sector demand elasticities, the northern and midwestern regions, the uncovered-sector wage increases after a minimum-wage hike; and in regions with comparatively large demand elasticities, the southern and western regions, the uncovered-sector wage decreases. Because of data limitations the uncovered-sector employment effect could not be estimated sharply, and so its relationship to the covered-sector demand elasticity is weak.