Developments in the evaluation of capital subsidy policies

Essay 1: A critical survey on capital subsidy policies. Despite the long history of capital subsidies in most developed countries and the numerous evaluations of their effectiveness, there is no comprehensive survey in the literature. This essay aims to provide a complete review of the most relevant research works in such literature highlighting their main findings. Besides, the core threats to internal validity and the main issues that a researcher has to face in order to deliver a robust evaluation work are stressed. Essay 2: The causal impact of capital subsidies: a multiple regression discontinuity design approach. This essay analyses the impact of a policy instrument - Law 488/92 (L488), the main Italian regional policy - that allocates subsidies to private firms by a multiple ranking system. Thanks to the peculiar L488 selection process that creates the conditions for a local random experiment, we are able to assess the effectiveness of these types of incentives for a relevant subgroup of firms. We propose a nonparametric multiple rankings regression discontinuity design that exploits the sharp discontinuities in the L488 rankings and extends the regression discontinuity design (RDD) approach to a context where the treatment is assigned by multiple rankings with different cut-off points. We find that the impact of the subsidies on employment, investment, and turnover is positive and statistically significant, while the effect on productivity is mostly negligible. The new subsidised capital is additional but non-complementary with the owner-financed investment. The results are robust to different specifications and not due to intertemporal substitution. Essay 3: Beyond the SUTVA: how policy evaluations change when we allow for interactions among firms. The shortage of studies on spatial spillovers of industrial policies is rather surprising considering that such policies are usually designed for generating spatial externalities. In Essay 3 we try to fill this gap proposing a new framework that partially relaxes the SUTVA assuming that a firm might interact only with firms having a limited economic distance from it (e.g. firms that belong to the same sector of activity) and that the intensity of these interactions is diminishing in distance and it does not extend over a certain threshold. This allows us to contrast the positive agglomeration effects with the negative cross-sectional substitution and the crowding-out effect. The global evaluation of the ATT and the spillover parameters shifts the spotlight from the policy effect on subsidised firms to the global effect of the industrial policy on the targeted territory making possible to determine if the subsidies have had a welfare-enhancing role in the underdeveloped regions. Analysing the effectiveness of the Italian L488 policy on firms located in peripheral areas, we find - in line with most of the literature - a positive and large effect of the policy on subsidised firms in terms of investment, turnover, and employment; however, the employment growth is in part determined to the detriment of affected untreated firms located in the very proximity of one or more treated firms that belong to the same sector of activity. This finding suggests that the ATT on itself is not a sufficient parameter to evaluate the effectiveness of an industrial policy and that we cannot rule out the possibility that the substitution effect (firms substitute labour with capital) might be in place

Quantitative Evaluation Techniques for Regional Policies

In recent years, the vision of what the essential factors for growth are and therefore the role of local policies has drastically changed. The importance of aspects such as human capital, innovation, agglomeration and institutions coupled with the diversified impacts of globalization, have drawn attention to the often-neglected role of space for growth and growth policies (Barca et al. 2012). Moreover, the presence of a wide and persistent inequality in income and joblessness among local areas, regions and countries, exacerbated by the Great Recession, has suggested a more important role for spatially targeted policies. Austin et al. (2018) indicate that place-based policies should be considered in this framework, because “social problems are increasingly linked to a lack of jobs rather than a lack of income” and “subsidizing job creation may be easier at the place level than at the person level”. Barca et al. (2012) argue that “space matters and shapes the potential for development not only of territories, but, through externalities, of the individuals who live in them.” Therefore, the place-based approach is more appropriate than a space-neutral sectoral approach if the geographical context matters, in terms of social, cultural, and institutional characteristics. These considerations have led to a new spread of place-based policies, often accompanied by skepticism with respect to their results from a significant group of economists and politicians (see, for instance, Glaeser and Gottlieb 2008). Indeed, “a fundamental concern is that spatially targeted policies may simply shift economic activity from one locality to another, with little impact on the aggregate level of output” (Kline and Moretti 2014). It is therefore not surprising that in recent years there has been a particular effort in the development of techniques capable of evaluating the effectiveness of territorial policies. In this survey of place-based policy evaluation techniques, we have chosen to consider only methodologies and studies based on the counterfactual approach. The reason is that we are convinced that to identify the effects of a policy we need a causal model, and the counterfactual approach is the most widely used and convincing approach in this field. The counterfactual approach, typical of program evaluation literature, attempts to compare what actually happened with what would have happened in the absence of the treatment. As each unit can be exposed or not exposed to the treatment (see Holland 1986), the researcher is bound to compare treated units with distinct untreated units. This approach derives from the potential outcomes framework (see Rubin 1974) where pairs of outcomes are defined for the same unit given different levels of exposure to the treatment, with the researcher only observing the potential outcome corresponding to the level of treatment received. Models are developed for the pair of potential outcomes rather than solely for the observed outcome. The potential outcomes framework has a number of advantages over a framework based directly on realized outcomes: i) it allows one to define causal effects before specifying the assignment mechanism, and without making functional form or distributional assumptions; ii) it forces the researcher to think about scenarios under which each outcome could be observed, that is, to consider the kinds of experiments that could reveal the causal effects; iii) it allows formulation of probabilistic assumptions in terms of potentially observable variables, rather than in terms of unobserved components; iv) it separates the modeling of the potential outcomes from that of the assignment mechanism. Of particular importance in Rubin’s approach is the relationship between treatment assignment and the potential outcomes (Imbens and Wooldridge 2009). The simplest case for analysis is random assignment of the treatment, which ensures that there are no systematic differences between the treatment and control groups before treatment assignment. This implies that any observed differences in outcomes following the treatment can then be attributed to the treatment itself, rather than to selection bias. Therefore, it is straightforward to obtain estimators for the average effect of the treatment. Randomized experiments have been used in some areas in economics but hardly ever in regional economics. This is why in this survey we will focus on observational studies

Evaluation of the Effectiveness of Firm Subsidies in Lagging-Behind Areas: The Italian Job

Since the late 1990s, Italian scholars have produced numerous studies in the field of regional policy evaluation, especially ones that have investigated the impact of financial incentives aimed at supporting the accumulation of private capital in underdeveloped areas. The number and innovativeness of these studies make it possible to define the presence of an Italian school for evaluating regional policies. This paper testifies to the importance and methodological advances of this school, putting it at the frontier of policy evaluation analyses. The presentation of the studies moves in two directions, historical and methodological, identifying the main themes and techniques addressed in recent years: the evaluation of Law 488 and negotiated programming policies, on the one hand, the advance in policy evaluation techniques in the presence of interactions and continuous treatment, on the other. The paper does not claim to be an exhaustive review; rather, it should be considered an overview of the historical path and the future prospects of what we call «the Italian school of regional policy evaluation»

Place-based amenities, well-being and territorial competitiveness: a new approach using tourists’ happiness

The well-being generated by each place is an unobservable characteristic affecting local competitiveness and territorial growth. In evaluating local well-being, the use of residents’ perceptions may generate biased evaluations. Alternatively, a revealed-preference analysis of tourists’ happiness might be exploited to assess the quality of life at the destination. Then, we develop a hedonic utility function to analyze a huge and original dataset of foreign tourists’ satisfaction, visiting Italy over 2005-2014, on a large number of place-based amenities. Results show a great diversity in the mix of features that affect tourist well-being at each destination, indicating strong heterogeneity in place-based amenities, correlated in space. The presence of spatially correlated common factors of competitiveness asks for coordinated action plans on the part of local and regional authorities

When did coronavirus arrive in Europe?

The first cluster of coronavirus cases in Europe was officially detected on 21st February 2020 in Northern Italy, even if recent evidence showed sporadic first cases in Europe since the end of 2019. In this study, we have tested the presence of coronavirus in Italy and, even more importantly, we have assessed whether the virus had already spread sooner than 21st February. We use a counterfactual approach and certified daily data on the number of deaths (deaths from any cause, not only related to coronavirus) at the municipality level. Our estimates confirm that coronavirus began spreading in Northern Italy in mid-January

Public subsidies, TFP and efficiency : a tale of complex relationships

This paper shows that a suitable decomposition of TFP can be applied to a large sample of subsidized firms for a relevant period of time, allowing an evaluation of the impact of subsidies on either the roles of technical progress and technical efficiency change or scale and allocative efficiency change as determinants of granted firms’ long-term growth. We measure and decompose TFP using a Stochastic Frontier Analysis (SFA). The impact of capital subsidies on the different components of TFP is captured by a quasi–experimental method (Multiple RDD), exploiting the conditions for a local random experiment created by Law 488/92 (L488), which has been an important policy instrument for reducing territorial disparities in Italy. The main findings from the case study are twofold. First, capital subsidies positively affect TFP growth in the medium-long term and not in the short term. The main reason is that allocative efficiency has a positive effect only after 2-3 years. Second, the positive impact comes especially through technical progress and not through scale impact change, as may have been expected

What happens when the income tax increases?

This paper exploits a sudden income tax rate increase in a large Italian region to examine whether this induced taxpayers to change their tax-related behavior. By using a spatial regression discontinuity design and a detailed dataset at the municipality level, we find a sizable and persistent decrease in declared income only for the self-employed and entrepreneurs