Merger Policy to Promote Global Players? A Simple Model

We use a simple framework where firms in two countries serve their respective domestic markets and a world market to analyze under which conditions cost-reducing mergers will be beneficial for the merging firms, the home country, and the world as a whole. For a national merger, the policies enacted by a national merger authority tend to be overly restrictive from a global efficiency perspective. In contrast, all international mergers that benefit the merging firms will be cleared by either a national or a regional regulator, and this laissez-faire approach is also globally efficient. Finally, we derive the properties of the endogenous merger equilibrium

Discussion of The Forward Search: Theory and Data Analysis by Anthony C. Atkinson, Marco Riani, and Andrea Ceroli

The Forward Search Algorithm is a statistical algorithm for obtaining robust estimators of regression coefficients in the presence of outliers. The algorithm selects a succession of subsets of observations from which the parameters are estimated. The present note shows how the theory of empirical processes can contribute to the understanding of how the subsets are chosen and how the sequence of estimators is changing.empirical processes; Huber's skip; least trimmed squares estimator; one-step estimator; outlier robustness

Asymptotic theory for iterated one-step Huber-skip estimators

Iterated one-step Huber-skip M-estimators are considered for regression problems. Each one-step estimator is a reweighted least squares estimators with zero/one weights determined by the initial estimator and the data. The asymptotic theory is given for iteration of such estimators using a tightness argument. The results apply to stationary as well as non-stationary regression problems.Huber-skip; iteration; one-step M-estimators; unit roots

An analysis of the indicator saturation estimator as a robust regression estimator..

An algorithm suggested by Hendry (1999) for estimation in a regression with more regressors than observations, is analyzed with the purpose of finding an estimator that is robust to outliers and structural breaks. This estimator is an example of a one-step M-estimator based on Huber's skip function. The asymptotic theory is derived in the situation where there are no outliers or structural breaks using empirical process techniques. Stationary processes, trend stationary autoregressions and unit root processes are considered.

An analysis of the indicator saturation estimator as a robust regression estimator

An algorithm suggested by Hendry (1999) for estimation in a regression with more regressors than observations, is analyzed with the purpose of finding an estimator that is robust to outliers and structural breaks. This estimator is an example of a one-step M-estimator based on Huber’s skip function. The asymptotic theory is derived in the situation where there are no outliers or structural breaks using empirical process techniques. Stationary processes, trend stationary autoregressions and unit root processes are considered.Empirical processes, Huber’s skip, indicator saturation, M-estimator, outlier robustness, vector autoregressive process.

Maximum A Posteriori Covariance Estimation Using a Power Inverse Wishart Prior

The estimation of the covariance matrix is an initial step in many multivariate statistical methods such as principal components analysis and factor analysis, but in many practical applications the dimensionality of the sample space is large compared to the number of samples, and the usual maximum likelihood estimate is poor. Typically, improvements are obtained by modelling or regularization. From a practical point of view, these methods are often computationally heavy and rely on approximations. As a fast substitute, we propose an easily calculable maximum a posteriori (MAP) estimator based on a new class of prior distributions generalizing the inverse Wishart prior, discuss its properties, and demonstrate the estimator on simulated and real data.Comment: 29 pages, 8 figures, 2 table

The Taxation of Interest in Europe: A Minimum Withholding Tax?

This paper provides an analysis of the proposal for introducing a minimum withholding tax on interest in the EU. We present a model with three countries: a typical EU country, an 'inside' tax haven, and an 'outside' tax haven. In the initial non-cooperative solution, the former two countries impose withholding taxes on interest. We investigate what happens to welfare in these countries, if the 'inside' tax haven is forced to raise its withholding tax. From the model we proceed to a broader evaluation of the minimum withholding tax proposal.

Taxes and Venture Capital Support

In this paper we set up a model of start-up finance under double moral hazard. Entrepreneurs lack own resources and business experience to develop their ideas. Venture capitalists can provide start-up finance and commercial support. The effort put forth by either agent contributes to the firm’s success, but is not verifiable. As a result, the market equilibrium is biased towards ine.ciently low venture capital support. The capital gains tax becomes especially harmful, as it further impairs advice and causes a first-order welfare loss. Once the capital gains tax is in place, limitations on loss offset may paradoxically contribute to higher quality of venture capital finance and welfare. Subsidies to physical investment in VC-backed startups are detrimental in our framework.venture capital, capital gains taxation, double moral hazard