Teun Kloek

Further experience in Bayesian analysis using Monte Carlo Integration

Abstract An earlier paper [Kloek and Van Dijk (1978)] is extended in three ways. First, Monte Carlo integration is performed in a nine-dimensional parameter space of Kleins model I [Klein (1950)]. Second, Monte Carlo is used as a tool for the elicitation of a uniform prior on a finite region by making use of several types of prior information. Third, special attention is given to procedures for the construction of importance functions which make use of nonlinear optimization methods.

A contribution to event study methodology with an application to the Dutch stock market

Abstract This paper proposes an extended market model for event studies based on daily stock returns. For actual data the assumptions of the simple market model are violated. The return distribution is not normal and neither the variance of the error term nor the risk parameter beta are constant. Our model incorporates the generalized autoregressive conditional heteroskedasticity (garch) model with t-distributed errors and a time-dependent beta. We test for anomalies by adding dummy variables in the regression equation. Our model is fairly general and could be used in a wide variety of event study situations. We illustrate the model by an analysis of the weekend and the option-expiration effect. We use return data from the Dutch stock market. The weekend effect on stock returns is significant, but no expiration effect could be detected.

Efficient estimation of income distribution parameters

The parameters of several families of distributions are estimated by means of minimum χ2; use is made of random samples taken from Dutch income-earning groups in 1973. The numerical search routine used, is the Complex method due to Box. The χ2 function is evaluated by standard numerical integration procedures. The lognormal and the Gamma families are rejected because of a poor fit. The log t and the log Pearson IV families are introduced. This results in a considerable improvement of χ2 critical levels. The generalized Gamma and the Champernowne function describe the income distribution reasonably well in some cases.

Outlier robust analysis of long-run marketing effects for weekly scanning data

We consider econometric modeling of weekly observed scanning data on a fast moving consumer good (FMCG), with a specific focus on the relationship between market share, distribution, advertising, price, and promotion. Such data can show non-stationary characteristics. Therefore, we use cointegration techniques to quantify the long-run effects of marketing efforts. Since weekly scanning data can contain aberrant observations due to, e.g., out-of-stock situations or measurement errors, we favor an outlier robust cointegration method, which we outline in detail. In our illustrative FMCG example, we find different results across robust and non-robust methods for the long-run marketing effects.

Stock Selection, Style Rotation, and Risk

Using US data from June 1984 to July 1999, we show that the impact of firm-specificcharacteristics like size and book-to-price on future excess stock returns varies considerably overtime. The impact can be either positive or negative at different times. This time variation ispartially predictable. We investigate whether the partial predictability signals security mispricing orrisk compensation by formulating alternative modeling strategies. The strategies are comparedempirically, In particular, we allow for a state-dependent choice of investment styles rather than aonce-and-for-all choice for a particular style, for example based on high book-to-price ratios orsmall market cap values. Using alternative ways to correct for risk, we find significant and robustexcess returns to style rotating investment strategies. Business cycle oriented approaches exhibitthe best overall performance. Purely statistical models for style rotation or fixed investment stylesreveal less robust behavior.

Posterior moments computed by mixed integration

A flexible numerical integration method is proposed for the computation of moments of a multivariate posterior density with different tail properties in different directions. The method (called mixed integration) amounts to a combination of classical numerical integration and Monte Carlo integration. Mixed integration is parsimonious in the sense that is makes use of the same parameters as the more restrictive multivariate normal importance function. The method is applied in order to compute the posterior scores of three candidates for a professorship in operations research, taking into account four different decision criteria.

An empirical two market disequilibrium model for Dutch manufacturing

Abstract We develop an empirical version of the aggregate two market fixprice model due to Barro and Grossman. Maximum likelihood estimation of the model appears to be difficult as a large number of local maxima occurs. The number of local maxima is considerably reduced by the introduction of prior information on some of the standard deviations of the disturbance terms in the model. Satisfactory estimation results are obtained this way. The model closely reproduces the post war Dutch trade cycle, although some problems remain, especially with the seventies.

Outlier Robust Gmm Estimation of Leverage Determinants in Linear Dynamic Panel Data Models

The GMM estimator that is usually employed in the panel data literature, has an unbounded influence function. This means that the estimator is easily influenced by outliers in the data. This paper develops a variant of the GMM estimator that is less sensitive to anomalous observations. Conditions for consistency and asymptotic normality of the robust estimator are presented. The robustness properties of the new estimator are investigated by means of simulation. An empirical illustration is provided, in which the determinants of a firms capital structure are investigated using a panel of American firms. The application shows that the robust GMM estimator can be a very useful tool in empirical model building.

INTERNATIONAL COMPARISONS OF PRICES AND QUANTITIES CONSUMED

The importance of international comparisons in the area of prices and consumption has increased substantially in the last decade due to the increase of tourism and of work carried out abroad. The problem is not at all new; it has been considered fairly recently by, for example, Gilbert and Kravis (undated).

Monte Carlo Analysis of Skew Posterior Distributions: An Ilustrative Econometric Example

The posterior distribution of a small scale illustrative econometric model is used to compare symmetric simple importance sampling with asymmetric simple importance sampling. The numerical results include posterior first and second order moments,- numerical error estimates of the first order moments, posterior modes, univariate marginal posterior densities and bivariate marginal posterior densities plotted in three-dimensional figures.