Tinbergen Institute

About: Tinbergen Institute is a education organization based out in Rotterdam, Netherlands. It is known for research contribution in the topics: Volatility (finance) & Competition (economics). The organization has 565 authors who have published 3157 publications receiving 82800 citations.

Time Series Analysis by State Space Methods

Abstract: This excellent text provides a comprehensive treatment of the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbence terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. The book provides an excellent source for the development of practical courses on time series analysis.

Time Series analysis by state space methods

Abstract: This excellent text provides a comprehensive treatment of the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbence [sic] terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. The book provides an excellent source for the development of practical courses on time series analysis.

The Impact of Entrepreneurship Education on Entrepreneurship Skills and Motivation

Abstract: This paper analyzes the impact of a leading entrepreneurship education program on college students’ entrepreneurship skills and motivation using an instrumental variables approach in a difference-in-differences framework We exploit that the program was offered to students at one location of a school but not at another location of the same school Location choice (and thereby treatment) is instrumented by the relative distance of locations to parents’ place of residence The results show that the program does not have the intended effects: the effect on students’ self-assessed entrepreneurial skills is insignificant and the effect on the intention to become an entrepreneur is even negative

Cross-Country Differences in Productivity: The Role of Allocation and Selection

Abstract: This paper investigates the effect of idiosyncratic ( firm-le vel) policy distortions on aggregate outcomes. Exploiting harmonized firm - level data for a number of countries, we show that there is substantial and systematic cross - country variation in the within-industry covariance between size and productivity. We develop a model in which heterogeneous firms face adjustment frictions (overhead labor and quasi-fixed capital) and distortions. The model can be readily calibrated so that variations in the distribution of distortions allow matching the observed cross-country moments. We show that the differences in the distortions that account for the size-productivity covariance imply substantial differences in aggregate performance. (JEL D24, L25, O47) A vast theoretical and empirical literature has been devoted to identify the sources of the large and persistent differences in productivity across countries. At the same time, a parallel strand of research has emerged over the past decade suggesting large and persistent heterogeneity in firm-level productivity, even in narrowly defined industries, in a variety of countries (e.g., Bartelsman, Haltiwanger, and Scarpetta 2004).

Heterogeneous Agent Models in Economics and Finance

Abstract: This chapter surveys work on dynamic heterogeneous agent models (HAMs) in economics and finance. Emphasis is given to simple models that, at least to some extent, are tractable by analytic methods in combination with computational tools. Most of these models are behavioral models with boundedly rational agents using different heuristics or rule of thumb strategies that may not be perfect, but perform reasonably well. Typically these models are highly nonlinear, e.g. due to evolutionary switching between strategies, and exhibit a wide range of dynamical behavior ranging from a unique stable steady state to complex, chaotic dynamics. Aggregation of simple interactions at the micro level may generate sophisticated structure at the macro level. Simple HAMs can explain important observed stylized facts in financial time series, such as excess volatility, high trading volume, temporary bubbles and trend following, sudden crashes and mean reversion, clustered volatility and fat tails in the returns distribution.