Evaluating active labour market policies evaluations

In this paper we carry out a meta evaluation of the international evaluation literature regarding active labour market policies (ALMPs). Many attempts have been made to estimate the net impact of reintegration measures on the individual job entry chance. So, the question is what conclusions can be drawn from the literature. How big is the net effect of reintegration measures? Our paper differs from earlier meta analyses of ALMP impact evaluations in the fact that we try to make inferences about the size of the net effect. To that end we analyze the size distribution of the net impact estimates resulting from the international evaluation literature. In our analysis we distinguish between different types of reintegration measures. Furthermore, we carry our regression analyses in which we explain the estimated effect found in individual studies from the type of measure, the labour market context and characteristics of the evaluation method used.In diesem Papier nehmen wir eine Meta-Evaluation der internationalen Literatur zur Evaluationsforschung aktiver Arbeitsmarktpolitik vor. Zahlreiche Versuche wurden unternommen, um den Nettoeffekt von Reintegrationsmaßnahmen auf die individuelle Arbeitszugangschance abzuschätzen. Somit ergibt sich die Frage, welche Schlussfolgerungen aus der Literatur gezogen werden können. Wie groß ist der Nettoeffekt von Reintegrationsmaßnahmen? Unser Papier unterscheidet sich von früheren Meta-Analysen zur Evaluation des Effekts aktiver Arbeitsmarktpolitik dahingehend, dass wir versuchen, Interferenzen hinsichtlich der Größe des Nettoeffekts auszumachen. In dieser Hinsicht analysieren wir die Größenverteilung der Nettoeffektschätzungen, die sich aus der inter-nationalen Evaluationsliteratur ergeben. In unserer Analyse unterscheiden wir zwischen verschiedenen Typen von Wiedereingliederungsmaßnahmen. Darüber hinaus nehmen wir Regressionsanalysen vor, in denen wir den geschätzten Effekt, der in einzelnen Untersuchungen ermittelt wurde, mit dem Typ der Maßnahme, dem Arbeitsmarktkontext und den Charakteristika der verwendeten Evaluationsmethode erklären

Evaluating active labour market policies evaluations

"In diesem Papier nehmen wir eine Meta-Evaluation der internationalen Literatur zur Evaluationsforschung aktiver Arbeitsmarktpolitik vor. Zahlreiche Versuche wurden unternommen, um den Nettoeffekt von Reintegrationsmaßnahmen auf die individuelle Arbeitszugangschance abzuschätzen. Somit ergibt sich die Frage, welche Schlussfolgerungen aus der Literatur gezogen werden können. Wie groß ist der Nettoeffekt von Reintegrationsmaßnahmen? Unser Papier unterscheidet sich von früheren Meta-Analysen zur Evaluation des Effekts aktiver Arbeitsmarktpolitik dahingehend, dass wir versuchen, Interferenzen hinsichtlich der Größe des Nettoeffekts auszumachen. In dieser Hinsicht analysieren wir die Größenverteilung der Nettoeffektschätzungen, die sich aus der inter-nationalen Evaluationsliteratur ergeben. In unserer Analyse unterscheiden wir zwischen verschiedenen Typen von Wiedereingliederungsmaßnahmen. Darüber hinaus nehmen wir Regressionsanalysen vor, in denen wir den geschätzten Effekt, der in einzelnen Untersuchungen ermittelt wurde, mit dem Typ der Maßnahme, dem Arbeitsmarktkontext und den Charakteristika der verwendeten Evaluationsmethode erklären. Ein Problem der Analyse liegt darin, dass unterschiedliche Studien unterschiedliche Effekte messen. Den theoretischen Rahmen von Risikomodellen nutzend analysieren wir, in welchem Ausmaß die verschiedenen Ansätze miteinander in Bezug gesetzt werden können und ob es sinnvoll ist, diese verschiedenen Untersuchungen in einer Meta-Analyse zu kombinieren. Die Ergebnisse belegen, dass der Nettoeffekt von Reintegration im Durchschnitt vergleichsweise gering ist. Als ein Ergebnis kann festgehalten werden, dass sich die Reintegrationschancen wohl kaum um mehr als 3 Prozentpunkte erhöht haben. Am überzeugendsten stellt sich der Fall bei beruflicher Aus- und Weiterbildung sowie bei der Arbeitsberatung dar: mit durchschnittlichen Nettoeffekten, die von 5,7 bis 9,7% reichen. Die positiven Ergebnisse für Ausbildung sind überraschend. Allerdings enthält unser Sample kaum experimentelle Evaluationen von solchen Maßnahmen, die üblicherweise als die verlässlichsten Evaluationen gelten. Generell haben wir herausgefunden, dass die Nettoeffektschätzung dann geringer ist, sobald ein Experiment für die Evaluation eingesetzt wurde. Deshalb können die Ergebnisse hinsichtlich Aus- und Weiterbildung zu rosig anmuten. Wenn wir die verwendete Methode berücksichtigen, stellt sich Ausbildung weniger gut dar, während Sanktionen (die als ein Maßnahmentyp behandelt werden) besser erscheinen. Lohnkostenzuschüsse und Arbeitsbeschaffungsmaßnahmen erwiesen sich als mangelhaft. Ferner haben wir herausgefunden, dass der Nettoeffekt aktiver Arbeitsmarktpolitik von der sozio-ökonomischen Situationen abhängt: Er ist tendenziell bei niedriger Arbeitslosigkeit geringer als während einer Rezessionsphase. Wir betrachten dieses Papier als einen ersten Schritt und möchten weitere Literatur auswerten. In jüngster Zeit sind etliche Studien erschienen, die eine mehr entwickelte Methodologie zur nichtexperimentellen Evaluation benutzen. Es wird interessant werden zu sehen, in welchem Ausmaß die Einbeziehung dieser Studien in die Meta-Analyse die Ergebnisse verändert." (Autorenreferat"In this paper we carry out a meta evaluation of the international evaluation literature regarding active labour market policies (ALMPs). Many attempts have been made to estimate the net impact of reintegration measures on the individual job entry chance. So, the question is what conclusions can be drawn from the literature. How big is the net effect of reintegration measures? Our paper differs from earlier meta analyses of ALMP impact evaluations in the fact that we try to make inferences about the size of the net effect. To that end we analyze the size distribution of the net impact estimates resulting from the international evaluation literature. In our analysis we distinguish between different types of reintegration measures. Furthermore, we carry our regression analyses in which we explain the estimated effect found in individual studies from the type of measure, the labour market context and characteristics of the evaluation method used. A problem with the analysis is that different studies measure different things. Using the theoretical framework of hazard models, we analyze to what extent the different approaches can be related to each other and whether it makes sense to combine the different studies in one meta analysis. The results indicate that on average the net impact of reintegration measure is fairly small. As a result of reintegration job entry chances are probably not increased by more than 3 percentage points on average. The case is most convincing for training and counseling with average net effects ranging from 5.7 to 9.7 percentage points. The positive results for training are surprising. However, our sample hardly contains experimental evaluations of training, which are usually seen as the most reliable evaluations. Overall we find that the net effect estimate tends to be smaller if an experiment is used for the evaluation. Hence, the results for training may be too rosy. If we account for the method used training comes out less well, while sanctions (which are treated as one type of measures) perform better. Wage subsidies and job creation come out poorly. We also find that the net impact of ALMPs depends on the socio-economic situation: it tends to be lower when unemployment is low than during a recession period. We see this paper as a first step and want to exploit the literature further. Recently, a lot of studies using a more developed methodology for non-experimental evaluation have appeared. It will be interesting to see to what extent inclusion of these studies in the meta analysis will alter the results." (author's abstract

Econometric Advances in Diffusion Models

This thesis gives new and important insights in modeling diffusion data in marketing. It addresses

Modeling Seasonality in New Product Diffusion

Although high frequency diffusion data is nowadays available, common practice is still to only use yearly figures in order to get rid of seasonality. This paper proposes a diffusion model that captures seasonality in a way that naturally matches the overall S-shaped pattern. The model is based on the assumption that additional sales at seasonal peaks are drawn from previous or future periods. This implies that the seasonal pattern does not influence the underlying diffusion pattern. The model is compared with alternative approaches through simulations and empirical examples. As alternatives we consider the standard Generalized Bass Model and ignoring seasonality by using the basic Bass model. One of our main findings is that modeling seasonality in a Generalized Bass Model does generate good predictions, but gives biased estimates. In particular, the market potential parameter will be underestimated. Ignoring seasonality gives the true parameter estimates if the data is available of the entire diffusion period. However, when only part of the diffusion period is available estimates and predictions become biased. Our model gives correct estimates and predictions even if the full diffusion process is not yet available

Modeling seasonality in new product diffusion

We propose a method to include seasonality in any diffusion model that has a closed-form solution. The resulting diffusion model captures seasonality in a way that naturally matches the original diffusion model's pattern. The method assumes that additional sales at seasonal peaks are drawn from previous or future periods. This implies that the seasonal pattern does not influence the underlying diffusion pattern. The model is compared with alternative approaches through simulations and empirical examples. As alternatives, we consider the standard Generalized Bass Model (GBM) and the basic Bass Model, which ignores seasonality. One of the main findings is that modeling seasonality in a GBM generates good predictions but gives biased estimates. In particular, the market potential parameter is underestimated. Ignoring seasonality in cases where data of the entire diffusion period are available gives unbiased parameter estimates in most relevant scenarios. However, ignoring seasonality leads to biased parameter estimates and predictions when only part of the diffusion period is available. We demonstrate that our model gives correct estimates and predictions even if the full diffusion process is not yet available

Software Multihoming to Distal Markets: Evidence of Cannibalization and Complementarity in the Video Game Console Industry

Steady software supply is a crucial driver of platform sales. While publishers benefit from releasing software across multiple platforms to tap a greater market, platform manufacturers often seek exclusive release to differentiate from competitors. Research has examined such software multihoming across competing platforms of the same technology generation (i.e., the proximal market); however, publishers increasingly multihome software to platforms in distal markets. In the video game console industry, these include previous-generation consoles, handhelds, or mobile devices. This study investigates multihoming to distal markets in the seventh and eighth game console generations. Whereas multihoming to previous-generation consoles cannibalizes focal console sales, multihoming to mobile devices exerts complementary effects. Software quality and console age moderate these relationships, with negative spillovers from multihoming to previous-generation consoles being rooted in lower-quality games and games released later in the console’s lifecycle. By contrast, multihoming to mobile devices is most beneficial early on

The impact of the business cycle on service providers:Insights from international tourism

For service providers, it is essential to understand how their business is affected by the macroeconomy. This is especially pressing for the tourism sector, the world’s largest export service, because the number of incoming visitors is likely to be strongly determined by the business cycles in the countries of origin. Utilizing state-of-the-art business-cycle metrics, we derive novel insights on the relationship between international tourism and the business cycle. We find an excess sensitivity of the sector to economic cycles based on a multidecade data set of international visitors to New Zealand coming from multiple counties and with various visitor purposes. However, we find no asymmetries in the speed of adjustment across contractions and expansions, suggesting a quicker recovery than many other (nonservice) sectors. Moreover, a higher cyclical volatility results in higher growth in the long run. A robustness check for two more destination countries (Australia and Japan) yields comparable insights. The results underscore the need to closely monitor the cyclical sensitivity and long-term growth prospects of the various visitor streams into the country, in order to (i) better tailor the accommodations and services to these streams and (ii) exploit diversification opportunities to reduce the overall cyclical volatility

The impact of the business cycle on service providers: Insights from international tourism

For service providers, it is essential to understand how their business is affected by the macroeconomy. This is especially pressing for the tourism sector, the world’s largest export service, because the number of incoming visitors is likely to be strongly determined by the business cycles in the countries of origin. Utilizing state-of-the-art business-cycle metrics, we derive novel insights on the relationship between international tourism and the business cycle. We find an excess sensitivity of the sector to economic cycles based on a multidecade data set of international visitors to New Zealand coming from multiple counties and with various visitor purposes. However, we find no asymmetries in the speed of adjustment across contractions and expansions, suggesting a quicker recovery than many other (nonservice) sectors. Moreover, a higher cyclical volatility results in higher growth in the long run. A robustness check for two more destination countries (Australia and Japan) yields comparable insights. The results underscore the need to closely monitor the cyclical sensitivity and long-term growth prospects of the various visitor streams into the country, in order to (i) better tailor the accommodations and services to these streams and (ii) exploit diversification opportunities to reduce the overall cyclical volatility.status: publishe

On the determination of the own and competitive effects of different platforms and content on market shares

Although the attention of academic literature about the relationship between social media and brand sales has grown, literature is still lacking analyses on competitive effects amongst brands. Additionally, effects of firm-generated content (FGC) is often generalized to the volume of posts, which combines the effects of different types of content and use of different platforms. We adopte a differential effects Market Share Attraction (MSA) model to capture different effects across brands allowing also for different effects across two social media platforms. We use a unique dataset covering 4 yoghurt brands in the Italian market spanning over 3 years, for which we focus on the social media posts of the brands (i.e., FGC) on both Twitter and Facebook, while controlling for the engagement (i.e., user-generated content derived from FGC) these posts create, as well as for traditional marketing-mix variables. We extend this analysis by looking at differences in effectiveness based on the type of content of the post (Informational, Emotional, and Activating), and consider whether effectiveness changed over time by employing a Dynamic Linear Model version of the MSA. Our preliminary findings indicate that different brands use different strategies over time and that the content of the message might influence the effectiveness in terms of market shares