http://repub.eur.nl/res/concept/jel-C25/ Recent publications classified by JEL Code C25 en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/25708/ 2011-07-13T00:00:00Z This paper examines which macroeconomic and financial variables are most informative for the federal funds target rate decisions made by the Federal Open Market Committee (FOMC) from a forecasting perspective. The analysis is conducted for the FOMC decision during the period January 1990 - June 2008, using dynamic ordered probit models with a Bayesian endogenous variable selection methodology and real-time data for a set of 33 candidate predictor variables. We find that indicators of economic activity and forward-looking term structure variables as well as survey measures have most predictive ability. For the full sample period, in-sample probability forecasts achieve a hitrate of 90 percent. Based on out-of-sample forecasts for the period January 2001 - June 2008, 82 percent of the FOMC decisions are predicted correctly. Hauwe, S. van den Dijk, D.J.C. van Paap, R. http://repub.eur.nl/res/pub/34805/ 2011-01-01T00:00:00Z Wagner, N. http://repub.eur.nl/res/pub/17100/ 2009-01-01T00:00:00Z Health care reforms in several European countries provide health insurers with incentives and tools to become prudent purchasers of health care. The potential success of this strategy crucially depends on insurers' bargaining leverage vis-à-vis health care providers. An important determinant of insurers' bargaining power is the willingness of consumers to consider alternative providers. In this paper we examine to what extent consumers are willing to switch hospitals when they are fully covered for hospital services, which is typical for many European countries. Since prices do not matter to these patients, we estimate time-elasticities to assess hospital substitutability. Using data from a large Dutch health insurer on non-emergency neurosurgical outpatient hospital visits in 2003, we estimate a conditional logit model of patient hospital choice taking both patient heterogeneity and hospital characteristics into account. We use the parameter estimates to simulate the demand effect of an artificial increase in travel time by 10% for every patient, holding all other hospital attributes constant. Overall, the resulting point estimates of hospitals' time-elasticities are fairly high, although variation is substantial (-2.6 to -1.4). Sensitivity tests reveal that these estimates are very robust and differ significantly across individual hospitals. This implies that all hospitals in our study sample have at least one close substitute which is an important precondition for effective hospital competition. Varkevisser, M. Geest, S.A. van der Schut, F.T. http://repub.eur.nl/res/pub/13557/ 2008-09-01T00:00:00Z We offer an alternative explanation for follow-the-leader behavior in foreign investment decisions based on Bayesian learning by rival firms. We test the implications of the model through a panel count data sample of MNEs that have invested in Central and Eastern Europe over the period 1990–1997. Interacting the measure of rivals' investment in country-industry pairs with uncertainty, we are able to identify the channel of Bayesian learning about revenue postulated by the model as the only one consistently generating the detected follow-the-leader behavior of foreign investments. The empirical findings are robust with respect to different model specifications. Altomonte, C. Pennings, H.P.G. http://repub.eur.nl/res/pub/8533/ 2007-02-06T00:00:00Z In this paper we consider the situation where one wants to study the preferences of individuals over a discrete choice set through a survey. In the classical setup respondents are asked to select their most preferred option out of a (selected) set of alternatives. It is well known that, in theory, more information can be obtained if respondents are asked to rank the set of alternatives instead. In statistical terms, the preferences can then be estimated more efficiently. However, when individuals are unable to perform (part of) this ranking task, using the complete ranking may lead to a substantial bias in parameter estimates. In practice, one usually opts to only use a part of the reported ranking. In this paper we introduce a latent-class rank-ordered logit model in which we use latent segments to endogenously identify the ranking capabilities of individuals. Each segment corresponds to a different assumption on the ranking capability. Using simulations and an empirical application, we show that using this model for parameter estimation results in a clear efficiency gain over a multinomial logit model in case some individuals are able to rank. At the same time it does not suffer from biases due to ranking inabilities of some of the respondents. Dijk, A. van Fok, D. Paap, R. http://repub.eur.nl/res/pub/8072/ 2006-10-06T00:00:00Z Estimators of regression coefficients are known to be asymptotically normally distributed, provided certain regularity conditions are satisfied. In small samples and if the noise is not normally distributed, this can be a poor guide to the quality of the estimators. The paper addresses this problem for small and medium sized samples and heavy tailed noise. In particular, we assume that the noise is regularly varying, i.e., the tails of the noise distribution exhibit power law behavior. Then the distributions of the regression estimators are heavy tailed themselves. This is relavant for regressions involving financial data which are typically heavy tailed. In medium sized samples and with some dependency in the noise structure, the regression coefficient estimators can deviate considerably from their true values. The relevance of the theory is demonstrated for the highly variable cross country estimates of the expectations coefficient in yield curve regressions. Mikosch, T. Vries, C.G. de http://repub.eur.nl/res/pub/1203/ 2004-04-01T00:00:00Z We develop a procedure to collect experimental choice data for estimating consumer preferences with a special focus on consumer price evaluations. For this purpose we employ a heteroskedastic mixed logit model that measures the effect of the way prices are specified on the variance of choice. Our procedure is based on optimal design ideas from the statistics literature and on some algorithms for constructing choice designs published in marketing journals. In an empirical application on mobile phone preferences we find evidence that the way prices are specified significantly affects the variance of choice. In a simulation study we show that our design is significantly more efficient than randomly generated designs., which can be regarded as equivalent to most commonly used experimental designs in the literature. Sándor, Z. Franses, Ph.H.B.F.