Elena Ragazzi (p), Greta Falavigna

Marco di Cataldo

This paper presents an organized system of indicators aimed at measuring investment readiness, applied experimentally in the context of the evaluation of the SEED2018 call.
This measure, launched by the Compagnia di San Paolo (a bank foundation), aims to strengthen the social cooperatives, triggering processes of organizational and managerial renewal through a two-phase mechanism. The first one is devoted to an analysis of needs supported by a specialist consultant. The output is a renovation plan that is implemented in the second phase. This provides us with three subgroups among the applying companies: excluded firms, firms participating only in phase 1, and firms participating in phase 1 and 2. The 3 groups may be exploited for evaluation purposes. The outcome of the project is identified by the policy-maker in the concept of Investment readiness, and has been measured with a set of metrics collected through ex-ante and ex-post surveys.
In this paper we will discuss the evaluation challenges connected to impact evaluation in the field of entrepreneurial coaching for operators of the third sector. We will propose the use of the concept of investment readiness to this aim and show how it can be operationalized through the calculation of a set of composite indicators. We will test the methodology, by applying it to the three subgroups of firms, used as non-experimental controls, with a dif-in-dif approach. Finally, we will regress the changes in investment readiness over a set of observable variables of the firm, including also balance sheet data.
Unfortunately, the implementation of the first edition of the SEED call occurred in the middle of the period affected by the Covid pandemic, which caused in Italy huge operational restrictions. This may perturbate the values of the observed indicators and reduce the readability of the impact, in the presence of a small number of participating firms in this pilot edition. Nevertheless, we think that this analysis will carry fundamental insights on the possibility to apply the methodology in such a particular field.

Eva Dettmann (p)

Elena Ragazzi

The aim of the intended study is the estimation of establishment-level employment effects of investment grants in Germany in terms of quantity and quality. As a starting point I estimate the average treatment effect for the treated establishment on the quantity of employed persons over the periods of one to seven years after the treatment is finished. Subsequently, I analyze potential changes in the quality of employment with the help of different proxies. The shares of high-skilled employees and at least medium-skilled employees are proxies for high quality employment in terms of employee qualification; the share of low-skilled employees represents the counterpart. The share of so-called ’normal contracts’ (full-time employment subject to
social insurance contributions) is regarded as high-quality employment in terms of security and
duration. Additionally, the median wage of full-time employees serves as a rough approximation of the labor productivity. For the estimation I apply a modification of Heckman’s matching and difference-in-differences approach suitable for a staggered adoption design. So I am able to consider the flexibility of investment grants in terms of treatment timing and duration.
I base the analysis on a rich data set that combines treatment-related, establishment-specific and regional information from different sources. The sample consists of establishments working in sectors eligible for investment grants in Germany, thereof are 10,215 treated establishments located in eligible regions. Non-treated establishments regarded as potential controls are found exclusively in non-eligible regions. This decision is made to circumvent potential selection problems due to unobservable characteristics, since in general all establishments in eligible regions (in the eligible sectors) have access to the GRW program. And I cannot observe why some establishments apply for investment grants and others do not. Resulting from the definition of the eligibility of regions with the help of a composite structural weakness score, the regions eligible for GRW investment grants and the non-eligible regions are remarkably different in terms of e. g. infrastructure, tax revenues, unemployment rate and other factors that describe the economic environment and influence the success/development of establishments and thus, the employment effect of investment grants.
This fact rises a methodological question I would like to discuss at the conference: Is it possible to control for such regional differences between the region types? Is there a (non-parametric) equivalent to the tripple DID model that is compatible to the staggered treatment adoption framework?

Marco di Cataldo (p), Giulia Romani

Eva Dettmann

The availability of local public goods can influence residential choices. Schools are especially relevant in this respect, since households with children have a daily need for school services. Hence, rationalisation policies aiming to increase efficiency by cutting on undersized nodes of the school network can induce population decline. This paper investigates the demographic and income effects of primary school closures by focusing on the Italian context (2010-2019), exploiting a 2008 education reform that produced a significant contraction of the school network. We assess whether school closures have an impact on citizens' residential choices, on top and beyond preexisting negative population trends which motivate school closures. We address endogeneity by combining a two-way-fixed-effects estimation with an instrumental variable approach, constructing the IV on the basis of institutional thresholds for school sizing adopted by some Italian Regions. Our findings suggest that municipalities affected by school closures experience significant reduction in population and
income. The effect is driven by municipalities far away from economic centres, and distant to further schools. This evidence indicates that schooling rationalisation policies, by inducing depopulation of peripheral areas, has an influence on the spatial distribution of the labour force and of income, thus affecting territorial disparities.