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The purpose of this paper is to outline and demonstrate a method for screening and selection of potential portfolio companies (PCs) during the screening phase in corporate venture capital.

The use of the data envelopment analysis (DEA) enables the consideration of individual, heterogeneous and multidimensional decision criteria in portfolio selection and the preceding screening process by the investor.

The result of this method is a relative ranking of the PCs, with all the PCs considered serving as peer group. A weighting of individual criteria is not necessary because it is part of the functionality of DEA. The authors validate the proposed approach in a case study and show that it can be well combined with other models and theoretical frameworks.

The method is particularly useful in two cases. First, if a highly specialized investor wishes to use a variety of individual selection criteria for portfolio selection. Second, if an investor only has insufficient (financial) data on potential PCs, but still wants to make a (pre-) selection based on observable (qualitative) characteristics. This model helps to make consistent, intersubjectively comprehensible decisions based on valid decision criteria and helps to optimize the decision-making process in the context of portfolio selection in CVC.

This method allows the systematic selection of an attractive group from a large number of potential PCs, based on observable characteristics and taking into account individual strategic investment objectives, without having to make assumptions about underlying distributions or weights of decision criteria.

The purpose of this paper is twofold, namely, to investigate if living and working abroad influences the (subjective) health of return migrants and to understand if there are any spillovers of return-migrant members onto health conditions of the family members left behind.

To that end, this paper uses the DoTM (Development on the Move) Migration Survey 2009, as well a propensity score matching to address selectivity on observables and IV (instrumental variables) for the selectivity on unobservables.

Results suggest that when equalized on observables, return migrants have better health than non-migrants. However, the reverse causality channel (less healthy individuals are more inclined to return) works to attenuate the true effect of return migration on health. Results further suggest a positive spillover effect of return migration on the health of the family members left behind, being mainly driven by the work of remittances sent while abroad, and not by the returned wealth or by the health knowledge transfer.

This paper offers at least two novelty lines to contribute to the current sparse of knowledge. First, it is among the scarce papers, and probably the only quantitative one, to investigate the nexus between return migration and health outcomes. Second, it heavily dwells on the role of selectivity (both on observables and unobservables) in determining the true (causal) effect of return migration on health.

Lechner and Miquel (2001) approached the causal analysis of sequences of interventions from a potential outcome perspective based on selection-on-observables-type assumptions (sequential conditional independence assumptions). Lechner (2004) proposed matching estimators for this framework. However, many practical issues that might have substantial consequences for the interpretation of the results have not been thoroughly investigated so far. This chapter discusses some of these practical issues. The discussion is related to estimates based on an artificial data set for which the true values of the parameters are known and that shares many features of data that could be used for an empirical dynamic matching analysis.

This paper estimates the financial returns to higher education quality in the UK. To account for the selectivity of students to institution, we rely on a selection on observable assumption. We use several estimates including the Generalised Propensity Score (GPS) of Hirano and Imbens, which relies on a continuous measure of institutional quality. This highlights that the returns to quality are heterogeneous and mostly driven by high-quality institutions. Moving from an institution in the third quality quartile to a top quality institution is associated with a 7% increase in earnings.

The purpose of this paper is to evaluate the state funded business counselling on firm growth.

A quasi-experimental difference-in-difference estimation of treatment effects, using a matched sample of comparable untreated firms.

Firms that have been granted counselling vouchers have a higher growth in value added than comparable untreated firms. This effect is mainly due to increased use of labour and capital, rather than increased efficiency. Results are upwardly biased due to sample selection among treated firms.

An improved strategy for identifying potential comparison firms from the pool of all firms may be necessary for further impact evaluations on business development programmes.

Policy makers may have to reconsider the programme design, since the programme currently suffer from a large potential for crowding-out, and low additional value of business counselling.

The paper uses a matching procedure in order to infer causal effects of business counselling and compares the effect of, respectively, contamination and selection on estimated impact on firm growth and survival. The data used are an original, rich micro-level data set on state investment support to businesses.

The purpose of this paper is to quantify the labor market outcomes of people with disabilities (PwD) in Indonesia and compares them to people without disabilities. It first studies the labor force participation of PwD before examining the large and persistent wage gaps they face. It explores whether these wage gaps are explained by differences in productivity, a distinction which has important implications for policies addressing these gaps.

The analysis is based on the Indonesian Family Life Survey Wave 5, which includes unique questions allowing for several definitions of disability. Multinomial logistic regression is used to study differences in type of employment for PwD. Wage gaps are estimated and corrected for selection using propensity score matching, supported by a Heckman selection model and Oaxaca–Blinder decomposition. Comparisons with other physically disadvantaged subgroups and the analysis of heterogeneity by job requirements and sector of work explore whether productivity gaps help explain wage gaps.

PwD generally have lower unconditional labor force participation, but disparities largely disappear when controlling for characteristics. Moreover, patterns vary depending on whether the measure of disability used depends on prior medical diagnosis. PwD that do not require prior diagnosis tend to work in more vulnerable employment. When they are employed for wages, people with these types of disabilities face lower wages, up to 22% lower. Meanwhile, (surprisingly) those with medically diagnosed conditions face no difference or a wage premium. This paper finds compelling evidence that, where a wage penalty exists, a substantial part is unexplained by observable characteristics.

Previous literature on disability has been mostly based on studies of high-income economies. This paper extends the literature to Indonesia, which differs from high-income contexts due to lack of mental healthcare resources and assistive technologies, as well as weaker rule of law. It provides unique insights based on types of disability and the salient dimensions of disability in the workplace. It also provides evidence that productivity differences do not explain the wage gap.

The purpose of this paper is to identify the impact of international student mobility (ISM) on the first wages of tertiary education graduates in Poland.

The author uses data from the nationwide tracer survey of Polish graduates (2007 Graduate Tracer Study) and regresses the hourly net wage rate of salaried workers in their first job after graduating from a higher education institution on a rich set of individual characteristics. In order to reduce the bias due to selection to ISM, the author includes a set of variables representing abilities and skills, characteristics of studies, and international experience as control variables. The author addresses the possible selection to employment bias by using the Heckman correction.

After controlling for observed heterogeneity, the author finds that Polish graduates who studied abroad for at least one month earn on average 22 per cent more in their first job than those who studied in Poland only. However, the author also finds that this wage premium is explained by international economic migration after graduation. Studying abroad brings a wage premium only if it is followed by working abroad. Those who perform their first job in Poland do not obtain any wage premium from ISM.

The main contribution of the paper is that it identifies international economic migration after graduation as another mechanism explaining why those who studied abroad earn more.

Researchers in economics and other disciplines are often interested in the causal effect of a binary treatment on outcomes. Econometric methods used to estimate such effects are divided into one of two strands depending on whether they require unconfoundedness (i.e., independence of potential outcomes and treatment assignment conditional on a set of observable covariates). When this assumption holds, researchers now have a wide array of estimation techniques from which to choose. However, very little is known about their performance – both in absolute and relative terms – when measurement error is present. In this study, the performance of several estimators that require unconfoundedness, as well as some that do not, are evaluated in a Monte Carlo study. In all cases, the data-generating process is such that unconfoundedness holds with the ‘real’ data. However, measurement error is then introduced. Specifically, three types of measurement error are considered: (i) errors in treatment assignment, (ii) errors in the outcome, and (iii) errors in the vector of covariates. Recommendations for researchers are provided.

In this chapter, we discuss whether early-childhood investments in low-income children could lead to a lasting impact on health outcomes. We note that such investments could improve adolescent and adult health by increasing child health, increasing educational attainment, or influencing parents' behaviors. Model preschool programs, such as the High/Scope Perry Preschool Program and the Carolina Abecedarian Program, have been successful in increasing the educational attainment and health behaviors of low-income children. The Head Start program, which is the largest public investment in low-income, preschool-aged children in the United States, has also improved child health and educational attainment.

Although there is extensive research on the impact of Head Start participation, there has been little research on the impact on risky behaviors in adolescence. Using data from the Panel Study of Income Dynamics (PSID) and its Child Development Supplements (CDS), we examine the impact of Head Start participation on smoking, alcohol use, and drug use throughout adolescence and the extent to which varying degrees of selection on unobservables influence this relationship.

In this paper, we study partial identification of the distribution of treatment effects of a binary treatment for ideal randomized experiments, ideal randomized experiments with a known value of a dependence measure, and for data satisfying the selection-on-observables assumption, respectively. For ideal randomized experiments, (i) we propose nonparametric estimators of the sharp bounds on the distribution of treatment effects and construct asymptotically valid confidence sets for the distribution of treatment effects; (ii) we propose bias-corrected estimators of the sharp bounds on the distribution of treatment effects; and (iii) we investigate finite sample performances of the proposed confidence sets and the bias-corrected estimators via simulation.