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International audience; Existence of a cointegration relationship between two time series in the time domain imposes restrictions on the series zero‐frequency behaviour in terms of their squared coherence, phase and gain, in the frequency domain. I derive these restrictions by studying cross‐spectral properties of a cointegrated bivariate system. Specifically, I demonstrate that if two difference stationary series, X(t) and Y(t), are cointegrated with a cointegrating vector [1 b] and thus share a common stochastic trend, then at the zero frequency, the squared coherence of (1 ‐ L)X(t) and (1 ‐ L)Y(t) will equal one, their phase will equal zero, and their gain will equal |b|.

Für neugegründete und etablierte Unternehmen gelten im Innovationsprozeß unterschiedliche Ausgangs- bzw. Rahmenbedingungen. Vor diesem Hintergrund stellt sich die Frage, welche Implikationen dies auf das betriebliche Innovationsverhalten hat und inwieweit sich beide Unternehmensgruppen hinsichtlich betriebsinterner und umfeldbezogener Einflussfaktoren signifikant voneinander unterscheiden. Mit Hilfe der Diskriminanzanalyse wird herausgearbeitet, welche Variablen zur Beschreibung von signifikanten Gruppenunterschiede herangezogen werden können. Die empirischen Untersuchungen zeigen deutliche Unterschiede im Innovationsverhalten zwischen neugegründeten und etablierten Unternehmen. Am stärksten differieren beide Unternehmensgruppen im Ressourceninput der F&E- und Innovationsphase. Die Variablen ‚Personalausgaben je Beschäftigte‘, Investitionsausgaben je Beschäftigte‘‚ F&E-Beschäftigungsintensität‘ sowie ‚Innovationsausgaben in der Markteinführungsphase je Beschäftigte‘ weisen die höchsten Diskrimininanzkoeffizienten auf. Aber auch der Umsatzanteil neuer Produkte als Indikator für den betrieblichen Innovationsoutput zeichnet sich durch eine signifikante Trennkraft aus. Eine geringe diskriminatorische Bedeutung besitzen hingegen Umfeldfaktoren des Innovationsverhaltens (Technologieniveau des Wirtschaftszweiges, Kooperationsbeziehungen). For newly-founded and established firms different initial or prevailing conditions apply in the innovation process. Against this background, the question arises as to what implications this has for a firm‘s innovation behaviour and to what extent both groups of companies differ significantly from each other as regards internal and environment-related influences. The present contribution takes this as its starting point. With the aid of discrimination analysis it is established which variables can be drawn on to describe significant group differences. Empirical investigations show clear differences in innovation behaviour between start up firms and incumbent firms. Both groups of companies differ most greatly in resource input during the R&D and innovation phase. The variables, ‚personnel expenditure per employee‘, ‚investment expenditure per employee‘, ‚R&D employment intensity‘and ‚innovation expenditure per employee in the launch phase‘ display the highest discrimination coefficients. But also the sales share of new products as an indicator of the firm‘s innovation output is characterized by a significant separatory power. Environmental factors of innovation behaviour, on the other hand, (technological level of the industry, R&D cooperation behaviour) possess minor discriminatory significance.

Large-scale environmental programs generally commit substantial societal resources, making the evaluation of their actual effects on the relevant outcomes imperative. As the example of the subsidization of energy-saving appliances illustrates, much of the applied environmental economics literature has yet to confront the problem of proper attribution of effects to underlying causes on a convincing methodological basis. This paper argues that recent results in the econometrics and statistics literature on program evaluation could be utilized to advance considerably in this context. In particular, the construction of a credible counterfactual situation is at the heart of the formal statistical evaluation problem. Even when controlled experiments are not a viable option, appropriate approaches might succeed where traditional empirical strategies fail to uncover the effects of environmental interventions.

In the second part of the 1990?s Switzerland conducted an ambitious active labour market policy (ALMP) encompassing a wide variety of programmes. We evaluate the effects of these programmes on the individual employment probability of potential participants. Our econometric analysis uses unusually informative data originating from administrative unemployment and social security records. We apply a matching estimator adapted for the case of multiple programmes. We find substantial positive effects for one particular programme that is a unique feature of the Swiss ALMP. It consists of a wage subsidy for temporary jobs in the regular labour market that would otherwise not be taken up by the unemployed. We also find large negative effects for traditional employment programmes operated in sheltered labour markets. For training courses the results are mixed.

This study analyses the effects of public sector sponsored vocational training on individual unemployment and employment duration in East Germany. The data is taken from the German Socio-Economic Panel (GSOEP). The empirical analysis is limited to training measures that took place between July 1990 and June 1993. To resolve the intriguing sample selection problem, i.e. to find an adequate control group for the group of trainees, we employ matching methods. The training effect is be estimated by using a discrete time hazard rate model. In the empirical analysis no evidence can be found to show that participation in public vocational training significantly decreases unemployment duration or increases employment duration.

This paper provides a brief survey of the bootstrap and its use in econometrics. As an introduction, the paper gives a description of the basics of the method, with a special emphasis on boostrap testing. A fairly large amount of space is devoted to discuss why bootstrap tests provide refinements compared to equivalent asymptotic tests. A series of recent different applications in the econometrics literature is then surveyed, in order to give a picture of this rapidly evolving research field.

Since interventions by the public sector generally commit substantial societal resources, the evaluation of effects and costs of policy interventions is imperative. This paper outlines why program evaluation should follow well-respected scientific standards and why it should be performed by independent researchers. Moreover, it outlines the three fundamental elements of evaluation research, the choice of the appropriate outcome measure, the assessment of the direct and indirect cost associated with the intervention, and the attribution of effects to underlying causes. The paper proceeds to outline in intuitive terms that the construction of a credible counterfactual situation is at the heart of the formal statistical evaluation problem. It introduces several approaches, based on both experiments and on non-experimental data, that have been proposed in the literature to solve the evaluation problem, and illustrates them numerically.

The traditional econometric techniques for frontier models, namely the Stochastic Frontier Approach (SFA), the Thick Frontier Approach (TFA) and the Distribution Free Approach (DFA) have in common that they depend on a priori assumptions that are, whether feasible or not, difficult to test. This paper introduces the Recursive Thick Frontier Approach (RTFA) to the estimation of technology parameters when panel data is available. Our approach is based on the assertion that if deviations from the frontier of X-efficient companies are completely random then one must observe for this group of firms that the probability of being located either above or below the frontier is equal to one half. This hypothesis can be tested for panel data sets but requires sorting of the full sample into a group of X-inefficient firms and a group of X-efficient (best practice) firms. The cost frontier is estimated using only the observations of the latter category.

The assumption that the assignment to treatments is ignorable conditional on attributes plays an important role in the applied statistic and econometric evaluation literature. Another term for it is conditional independence assumption. This paper discusses identification when there are more than two types of mutually exclusive treatments. It turns out that low dimensional balancing scores, similar to the ones valid in the case of only two treatments, exist and be used for identification of various causal effects. Therefore, a comparable reduction of the dimension of the estimation problem is achieved and the approach retains its basic simplicity. The paper also outlines a matching estimator potentially suitable in that framework.

Today, the increasing importance of waste management and the question of its efficiency is a broadly discussed topic, both on the theoretical and practical level. The present paper provides the results of a comprehensive analysis of the competitiveness of the environment with regard to waste management in the Czech Republic, Olomouc Region, while focusing on its effects on municipal waste management expenditure. The main goal of the paper is to examine and evaluate the impact of the competitiveness of the environment on cost-effectiveness of municipal waste management expenditure by using the Herfindahl-Hirschman Index (HHI) and a competition index of our own design. We compare expenditure per capita for several municipality size groups. Moreover, the data have also been analysed separately for the each of the five districts of the Olomouc Region in order to identify whether there are any significant differences among the districts within the region. The analysed period covers 5 years - from 2010 to 2014 - and the sample consists of all 399 municipalities of the Olomouc Region. The HHI results confirm that the competitive environment has a significant impact on municipal expenditure, but our competition index results show impact of competition as ambiguous.