This paper investigates the uncertainty in variance and covariance of asset returns. It is commonly believed that these second moments can be estimated very accurately. However, time varying volatility and nonnormality of asset returns can lead to imprecise variance estimates. Using CRSP value...

This paper investigates the uncertainty in variance and covariance of asset returns. It is commonly believed that these second moments can be estimated very accurately. However, time varying volatility and nonnormality of asset returns can lead to imprecise variance estimates. Using CRSP value...

Strong seasonality in demand, a short product life cycle, and the absence of any price competition make the release date of first-run movies one of the main strategic decisions taken by movies' distributors. Movies are typically released on a Friday within a short release season, thus making the...

In this paper we extend the setting analysed in Hahn and Hausman (2002a) by allowing for conditionally heteroscedastic disturbances. We start by considering the type of conditional variance-covariance matrices proposed by Engle and Kroner (1995) and we show that, when we impose a GARCH...

This paper develops a dynamic stochastic model to examine the joint patent application and renewal behavior under an international patent protection regime. This framework makes it possible to utilize both the cross-sectional (multi-country filing) and the time-series (patent renewal) dimensions...

This paper extends the linear lasso estimators to non-linear case. We are especially interested in GMM type of Lasso estimators. Lasso estimators are generalization of ridge regression in least squares. With this setup we can deal with identification problem introduced by weak instruments. When...

In examining the likely consequences of nonsense relationship, Granger and Newbold (1974) made it clear that the differencing is not the universal sure solution to the problem of spurious regression models. This has prompted the discovery of the cointegration regression estimation by Engle and...

The use of the Beveridge Nelson decomposition in macroeconomic analysis involves the truncation and estimation of infinite weighted sums of random variables, whereas the single source of error (SSE) state space approach provides a simple and effective framework that leads to exactly the same...

In many countries we observe a gap between macroeconomic and microeconomic statistics. In order to explain the underreporting observed in microeconomic statistics, the present paper tests the misreporting hypothesis through the double hurdle model. The misreporting hypothesis is based on some...

Abstract In many areas of economic analysis, economic theory restricts the shape as well as other characteristics of functions used to represent economic constructs. Obvious examples are the monotonicity and curvature conditions that apply to utility, profit, and cost functions. Commonly, these...