Search

Latent variables in structural equation models do not have an observable scale. Hence researchers resort to scaling methods, such as fixed marker, effects coding, or fixed factor, to assign scales to the latent variables. The use of such procedures results in numerically different estimates, in spite of a single underlying population model. In this paper, we provide a framework which not only allows for a translation between estimates obtained under different scaling methods, but also helps to explore the relation between the underlying population parameters and their estimates, thus providing a basis for the interpretation of estimated parameters. Addition- ally, the framework proves useful for demonstrating that the choice of scaling method affects the power of the Wald test for testing parameters’ significance.

It is becoming increasingly popular in applications of standard synthetic control methods to include the entire pretreatment path of the outcome variable as economic predictors. We demonstrate both...

We investigate how the selection process of a leader affects team performance with respect to social learning. We use a lab experiment in which an incentivized guessing task is repeated in a star network with the leader at the center. Leader selection is either based on competence, on self-confidence, or made at random. Teams with random leaders do not underperform compared to rather competent leaders, and they even outperform teams whose leader is selected based on self-confidence. The reason is that random leaders are better able to use the knowledge within the team, i.e., the wisdom of crowds. We can show that it is the declaration of the selection procedure which makes non-random leaders overly influential. The central position in the communication network already makes a leader highly influential. Knowing that the leader is not selected at random pushes team members to weigh the leader’s opinion even more. We set up a horse race between several rational and naive models of social learning to investigate the micro-level mechanisms. We find that overconfidence and conservatism contribute to the fact that too confident leaders mislead their team in finding good estimates.

Using elicited expectations of future gross salaries, we evaluate characteristics causing German students to make larger or smaller estimation errors. While students seem to underestimate actual salaries by 18 percent, we show that these errors are highly attributable to misconceptions of the progressive income tax. Developing a suitable adjustment procedure, we correct students’ estimates and find that errors decline by 12 percentage points. Conducting regression analyses, we reveal strong connections with students’ age, gender, work experience, secondary school track, and knowledge about student loans. These results change notably if not controlling for students’ misconceptions of the tax system.

In this paper, we explain the reasons behind constraint interaction, which is the phenomenon that the results of testing equality constraints may depend heavily on the scaling method used. We find that the scaling methods interfere with the testing procedures because scaling methods determine which transformations of population quantities model parameters actually estimate. We therefore also develop rules on how to correctly interpret estimates of model parameters under alternative scaling methods.

Given that existing implementations of synthetic control methods are plagued by serious weaknesses, new methods are offered for calculating synthetic control units. In particular, it is shown how to detect and handle important special cases that have yet to be addressed. Numerical methods for fast and reliably solving the nested optimization associated with the standard case are also discussed. An open source implementation of the presented methods is provided with the R package MSCMT, which can also be applied to generalizations of ‘standard’ synthetic control methods.

We introduce synthetic control methods (SCM) as a forecasting technique. Using (i) as economic predictors solely the outcome itself, i.e. lagged values of the dependent variable, and (ii) lagged time series of the outcome to build the donor pool, we let SCM choose and weight appropriate values in order to come up with a sensible forecast of the US GDP growth. This procedure performs competitively viable compared with alternative forecasting methods.

We present a model of opinion formation where individuals repeatedly engage in discussion and update their opinion in a social network similarly to the DeGroot model. Abstracting from the standard assumption that individuals always report their opinion truthfully, agents in our model may state an opinion that differs from their true opinion. The incentive to do so is induced by agents' preferences for conformity. We model opinion formation as a dynamic process and identify conditions for convergence to a consensus. Studying the consensus in detail, we show that an agent's social influence on the consensus opinion is increasing in network centrality and decreasing in the level of conformity. Thus, lower conformity fosters opinion leadership. Moreover, assuming that the initial opinion is a noisy signal about some true state of the world, we study how conformity affects the efficiency of information aggregation or the ``wisdom'' of the society. We show that the society becomes wiser, in the sense of a smaller mean squared error of their estimate, if players who are well informed (relative to their network importance) are less conform, while uninformed players (relative to their network importance) conform more with their neighbors.

Using the Baker et al. (2013) index of policy uncertainty for six developed countries, this paper estimates spillovers of policy uncertainty. We find that spillovers account for slightly more than one-fourth of the dynamics of policy uncertainty in these countries, with this share rising to one half during the financial crisis. The US and UK are responsible for a large fraction of the spillovers since the financial crisis, while the remaining countries are all net receivers of policy uncertainty shocks during and after this period.

SUMMARY Diebold and Yilmaz (Economic Journal 2009; 119; 158–171) introduce the spillover index to measure linkages between international financial markets. As their index depends on the ordering of the variables in the underlying VAR model, they check robustness by computing the index for a small number of randomly chosen permutations, stating that it was impossible to explore the huge number of renumerations. Building on a new divide-and-conquer strategy, we provide an algorithm for swiftly calculating the spillover index's maximum and minimum over all renumerations. Using this new algorithm, we find that the true range of the spillover index can be up to three times as large as estimated by Diebold and Yilmaz. Copyright © 2013 John Wiley & Sons, Ltd.

We introduce a model for stock prices consisting of a fundamental price process and a news impact curve, which allows for either overreaction, underreaction, or correct response to changes of the fundamental value. We further develop statistics based on OHLC data, which separately measure upside and downside overreaction. The distribution of these statistics under the hypothesis of correct response and fundamental prices following Brownian motions is used to derive tests for upside and downside overreaction. We show that more realistic and frequently used fundamental price processes with correct response leave the distribution of the test statistics widely unaffected or lead to conservative tests. Empirical application to different stock markets provides strong evidence for intraday overreaction, particularly to bad news. The economic significance of the discrimination induced by the proposed statistics is further illustrated by analyzing the performance of a simple buy on bad news strategy.

New tests are proposed for the specification of the intraday price process of a risky asset, based on open, high, low, and close prices. Under the null of a Brownian process we derive two stochastically independent, unbiased volatility estimators. For a Hausman specification test we prove its equivalence with an F-test, consider its robustness against variation in drift and volatility, and analyze the power against an Ornstein–Uhlenbeck process, as well as a random walk with alternative distributions.

The UEFA Champions League Round of 16 is characterized by restrictions that prevent teams from the same preliminary group and the same nations from matches against each other. Together with the draw procedure currently employed by UEFA, this leads to odd probabilities: in 2012/2013, there were more outcomes of the draw with German Schalke 04 facing Ukrainian Shakhtar Donetsk than there were results where they were matched with Galatasaray Istanbul. In contrast, the probability of Schalke being drawn against Galatasaray exceeded that of playing Shakhtar. We show that this strange effect is due to the group restriction and the mechanism used by UEFA for the draw. Additionally, we provide procedures with which UEFA could produce adequate probabilities for the draw.

We present a model of opinion formation where individuals repeatedly engage in discussion and update their opinion in a social network similarly to the DeGroot model. Abstracting from the standard assumption that individuals always report their opinion truthfully, agents in our model interact strategically in the discussion such that their stated opinion can differ from their true opinion. The incentive to do so is induced by agents' preferences for conformity. Highly conforming agents will state an opinion which is close to their neighbors' while agents with low level of conformity may be honest or even overstate their opinion. We model opinion formation as a dynamic process and identify conditions for convergence to consensus. Studying the consensus in detail, we show that an agent's social influence on the consensus opinion is increasing in network centrality and decreasing in the level of conformity. Thus, lower conformity fosters opinion leadership. Moreover, assuming that the initial opinion is a noisy signal about some true state of the world, we consider the mean squared error of the consensus as an estimator for the true state of the world. We show that a society is "wise", i.e. the mean squared error is smaller, if players who are well informed are less conform, while uninformed players conform more with their neighbors.

In den Kapiteln 2 bis 4 wurden etliche Komponenten des Zustands-Praferenz-Ansatzes kritisch hinterfragt: die Usual Conditions, die Modellierung der Information durch σ-Algebren sowie die Bedeutung von ℱ und P. Wahrend beginnend mit Kapitel 6 gezeigt wird, das man die Theorie der Bewertung derivativer Finanzinstrumente auch ohne die Usual Conditions entwickeln kann, werden in diesem Kapitel Alternativen vorgeschlagen, welche die Schwierigkeiten im Zusammenhang mit der Informations-Modellierung sowie ℱ und P umgehen.

In diesem Kapitel wird die Bedeutung von ℱ sowie P unter die Lupe genommen. Zunachst beschaftigt sich der erste Abschnitt kritisch mit den Interpretationen von ℱ, die im ersten Kapitel zwar angesprochen, jedoch nicht naher untersucht wurden. Der anschliesende zweite Abschnitt ist dann der Frage gewidmet, welche Bedeutung dem Wahrscheinlichkeitsmas P eines Akteurs zukommt.

Dieses Kapitel ist der Darstellung des aktuellen Standes der Grundlagen der Theorie der Bewertung derivativer Finanzinstrumente gewidmet. Ziel dieser Darstellung ist dabei lediglich die Wiedergabe der gegenwartig sowohl in der Forschungsais auch in der Lehrbuch-Literatur gangigen Konzepte und deren Motivationen, wahrend eine kritische Auseinandersetzung hiermit dem nachsten Kapitel vorbehalten bleibt.

Mit den Ergebnissen des vorangegangenen Kapitels ist der Weg geebnet, um das in den Abschnitten 1.2 und 5.3 diskutierte Modell zu komplettieren: es fehlt immer noch eine prazise Beschreibung der Handelsmoglichkeiten der Akteure

Bei der Vorstellung der Usual Conditions in Abschnitt 1.2 (siehe S. 18) wurde bereits darauf hingewiesen, das es sich hierbei um technische Bedingungen handelt, welche in der Theorie der stochastischen Integration benotigt werden und fur die in der Literatur bis auf einzelne Ausnahmen weder Interpretation noch Motivation gegeben werden. In diesem Kapitel soll diese Lucke geschlossen werden, indem jeder der drei Bestandteile der Usual Conditions separat auf seine Tauglichkeit im Rahmen des Zustands-Praferenz-Ansatzes untersucht wird.

In diesem Kapitel wird der Frage nachgegangen, wie man im Rahmen des Zustands-Praferenz-Ansatzes die den Akteuren zur Verfugung stehende Information modelliert. Dabei wird zunachst anhand eines Beispiels im ersten Abschnitt verdeutlicht, welche Probleme auftreten konnen, wenn hierfur σ-Algebren zum Einsatz kommen.