Research

"Valid frequentist causal inferences from an observational study can only be obtained if you embed the observational study within a hypothetical randomized experiment... otherwise you are just looking at computer output and implied associations, and making up, generally silly, although sometimes interesting, stories" (Don Rubin)

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(Selected) Journal Publications


Abstract: This paper provides a sound ex-post evaluation of the impact of the Eurasian integration on member countries’ bilateral trade after a decade of implementation. We overcome the main limitations of current empirical analyses on the effects of trade agreements, namely the aggregation of tariff and non-tariff barriers and the likely self-selection bias, by applying a non-parametric method specifically designed to fully exploit time-series cross-sectional data. We thus compare the trade flows of the member countries in the Eurasian agreement with the exporter-importer pairs located in the Eurasian continent, which are most similar in terms of pre-treatment trends and features. Our results confirm the previous literature about the lack of a significant impact of the Eurasian customs union but find more positive net effects of the more recent integration steps. Our results ask for additional efforts to complete the Eurasian integration and let its member countries fully benefit from its hoped-for long-term effects.

Abstract: This article investigates the long-term reaction of local labor markets (LLMs) to a mass layoff in a manufacturing plant. We adopt a non-parametric generalization of the difference-in-differences estimator expressly developed for time-series cross-sectional data and a new comprehensive dataset. Our results suggest that, on average, a mass layoff abruptly decreases industry employment by 22%; this negative impact is persistent even 9 years later. The shock has a negative and statistically significant effect only on the same industry of the affected LLM, while the rest of the local economy is, at most, mildly negatively affected. These findings depend on the initial level of development and call for the policymakers’ intervention to design efficient employment policies aimed at reducing the long-lasting social costs of a mass layoff at least for the less developed and less dynamic local economies.

Abstract: A growing literature has highlighted the role of economic grievances, global transformations, cultural cleavages and long-term trends of isolation and decline in engendering political discontent. However, this literature is silent on the potential role of unanticipated local shocks in fuelling support for authoritarian parties. We fill this gap by using comprehensive data at a fine spatial scale and a comparative natural experiment approach. Our study documents that the occurrence of two destructive earthquakes in Italy resulted in sharply diverging electoral outcomes: while the 2012 Emilia quake did not alter voting behaviour, the 2009 L’Aquila earthquake paved the way for an impressive and persistent authoritarian backlash in the most affected areas. Such heterogeneous patterns originate from a stark contrast in post-disaster reconstruction processes and shifts in institutional trust. These findings suggest that valence issues generated from local shocks can turn “places that don’t recover” into authoritarian hotbeds.

Abstract: What is the economic impact of joining a currency union? Is this impact heterogeneous across regions? And how does it change in case of a recession? We answer these questions by investigating the economic impact of joining the euro area for the latecomers, i.e., the eastern European countries that adopted the euro after 2002. Differently from previous literature, we use NUTS-2 regions as units of analysis. This novelty allows us to investigate the theoretical predictions of a currency union impact at a more appropriate geographical level. Using a recently developed counterfactual approach, we estimate the overall as well as the disaggregated impact of joining the euro area. We find that the adoption of the euro brought about a small positive effect, which was, however, dampened by the Great Recession. Individual regional estimates suggest heterogeneous returns with benefits accruing mostly to core regions.

Abstract: We investigate the influence of anti-immigrant parties on foreigners' location choices. Considering Italian municipal elections from 2000 to 2018, we create a comprehensive database that includes a classification of the anti-/pro-immigration axis of leading political parties based on specialists' assessments. Adopting a bias-corrected regression discontinuity design, we find that the election of a mayor supported by an anti-immigrant coalition significantly affects immigrants' location choices only when considering the most recent years. This finding is not driven by the enactment of policies against immigrants but by an ‘inhospitality effect’, which has become stronger over time due to the exacerbation of political propaganda. Therefore, foreigners' flows are influenced by the local political environment only when immigration is central to the political debate.

Abstract: Are place-based policies capable of taking lagging areas to a higher growth trajectory permanently? We answer this crucial question by investigating what happens when strongly subsidised regions experience a substantial reduction in funding. By analysing an extensive database via the mean balancing approach, we estimate the causal impact of exiting the convergence region status of the EU regional policy. We find that only regions which experienced a considerable reduction in funding during a recession suffered a negative impact on economic growth. However, the impact varies with the features of the regions and the local economic context.

Abstract: Our empirical analysis focuses on the effect of regional policies on migration attraction factors in Europe. We employ a regression discontinuity design to assess the causal relationship between the reception of large amounts of public funds and migration flows in the EU-15 regions. In highly-subsidized regions, we find a large increase in the share of foreign citizens from less-developed countries when compared to low-subsidized regions with similar pre-treatment characteristics. The analysis shows that such an increase is due to the positive impact of the European regional policy on job market opportunities as well as the improvement of public goods supply.


Abstract: This paper assesses the pandemic’s impact on Italian local economies with the newly developed machine learning control method for counterfactual building. Our results document that the economic effects of the COVID-19 shock vary dramatically across the Italian territory and are spatially uncorrelated with the epidemiological pattern of the first wave. The largest employment losses occurred in areas characterized by high exposure to social aggregation risks and pre-existing labor market fragilities. Lastly, we show that the hotspots of the COVID-19 crisis do not overlap with those of the Great Recession. These findings call for a place-based policy response to address the uneven economic geography of the pandemic.

Abstract: Most governments tackle the economic issues of underdeveloped areas by offering subsidies aimed at fostering economic activities and local employment. Localized policies put constraints on where businesses may locate to receive subsidies, but they generally place few restrictions on whom subsidized businesses must hire. Using administrative data on firms and workers in Italy, we adopt a multi-cutoff regression discontinuity design to empirically assess and decompose the employment effect of substantial incentives for the replacement or establishment of new capital. Our empirical strategy allows identifying the geographical origin and labor market status of new hires. The results show how the majority of recruits come from new entrants to the labor market, in particular, young people and students, while displacement effects are limited. It appears that subsidized companies tend to keep their most valuable staff and hire more qualified young people. Overall, we find only a modest spatial dispersion of the effects or a possible crowding-out of the local labor market.

Abstract: We evaluate the effectiveness of the most extensive experiment of income redistribution, i.e., the EU regional policy, at a time of economic crisis. By exploiting geographic discontinuities in fund eligibility, we analyze comprehensive data on all publicly funded Italian projects at the municipality level. We find a positive impact of localized support to firms with a sizable increase in employment and the number of plants in intensively treated areas. The result is an important policy lesson concerning the effects of place-based policies at a time of a long-lasting recession, such as that engendered by the COVID-19 crisis.

Abstract: We assess the impact of the EU Regional Policy on regional economic growth by applying a new evaluation strategy, which integrates mediation analysis with a quasi-experimental framework. Using the R&D expenditure as an indicator of innovation capability, we evaluate how much of the total effect of the EU Regional Policy is due to R&D in the poorest EU regions. Consistently with the previous literature, we found a positive impact of the overall policy on economic growth, but, among the convergence regions, those investing a higher proportion of funds in R&D have the same convergence rate as regions investing more in other priorities. These findings confirm that the EU Regional Policy played an important role in the economic recovery of the poorest regions in the aftermath of the Great Recession. However, focusing resources on R&D does not seem to provide additional economic benefits, at least in the short run.

Abstract: Estimates of the real death toll of the COVID-19 pandemic have proven to be problematic in many countries, Italy being no exception. Mortality estimates at the local level are even more uncertain as they require stringent conditions, such as granularity and accuracy of the data at hand, which are rarely met. The ‘official’ approach adopted by public institutions to estimate the ‘excess mortality’ during the pandemic draws on a comparison between observed all-cause mortality data for 2020 and averages of mortality figures in the past years for the same period. In this paper, we apply the recently developed machine learning control method to build a more realistic counterfactual scenario of mortality in the absence of COVID-19. We demonstrate that supervised machine learning techniques outperform the official method by substantially improving the prediction accuracy of local mortality in ‘ordinary’ years, especially in small- and medium-sized municipalities. We then apply the best-performing algorithms to derive estimates of local excess mortality for the period between February and September 2020. Such estimates allow us to provide insights about the demographic evolution of the first wave of the pandemic throughout the country. To help improve diagnostic and monitoring efforts, our dataset is freely available to the research community. 

Abstract: 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.

Abstract: This study utilises an exceptionally rich English administrative dataset, to estimate employment impacts from training voluntarily initiated by unemployed individuals. A Coarsened Exact Matching approach is adopted, in a dynamic evaluation framework, to estimate impacts up to 5 years from training start. We identify economically and statistically significant impacts, estimated separately for (i) all training starters, (ii) the partially, and (iii) fully treated. Investigation of possible endogenous selection into partial/full treatment, using distance to training provider as an instrumental variable, suggests inclusion of extensive employment and learning histories in a matching framework, justifies invocation of the conditional independence assumption for comparisons of full/partial treatment. The partially treated secure a return that is, on average, 2 percentage points lower than full treatment. Thus, an ‘intention to treat’ approach would not alter conclusions on the efficacy of training; but using the partially treated to estimate counterfactual outcomes risks understating returns. 


Abstract: We propose a novel evaluation strategy to estimate local multipliers in Italy during 1996-2006. We find the presence of positive multipliers: 0.26-0.33 for the tradable sector (manufacturing) and 0.88-1.13 for the non-tradable sector (construction and services). They are lower than what was previously found for the US but much higher than those identified for European and Asian countries. The reasons for this finding lie in the higher accuracy of the data, in the relevance of the instrument used, and in the widespread underutilization of production factors.


Abstract: A key strategy for supporting destination competitiveness is to enhance endogenous amenities, and tourists are the best candidate to evaluate them at the destination. The analysis in this paper uses a comprehensive data set on foreign travellers to investigate their happiness at Italian destinations between 2005 and 2014. Using a theory-dependent approach to model happiness at the destination with respect to endogenous and exogenous amenities, personal characteristics and trip features, a great diversity in the mix of amenities affecting tourist happiness is shown. However, some clear spatial patterns emerge. The findings call for place-based policies targeted at the specific needs of each area. 


Abstract: We evaluate whether the adoption of a well-known transition management instrument in the tourism industry can support simultaneously economic growth as well as sustainability. We create a detailed dataset at the municipality level and use a recently developed policy evaluation technique to investigate the causal impact of the Blue Flag programme on the local economies. Estimates show that this eco-label is not effective at enhancing the local economy; findings are homogeneous across destinations. This empirical result is in line with the recent theoretical literature arguing that a single policy does not suffice for transiting towards a sustainable economy.


Abstract: We evaluate whether the impact of EU Structural and Cohesion Funds (EUF) on Member States’ regional economic growth depends on the intensity of treatment, measured by the normalized amount of funds distributed in each region. We use an original data set that covers all the main sources of EUF and extend the regression discontinuity design to the case of continuous treatment. The results suggest an average positive effect on regional growth. The estimated conditional intensity-growth function is concave and presents a maximum value. Therefore, the exceeding funds could have been allocated to other lagging regions without reducing the effect on growth.

Abstract: The shortage of studies on spatial spillovers of capital subsidy policies is rather surprising, considering that such policies are usually designed to generate spatial externalities. We propose a new framework that allows positive agglomeration effects to be contrasted 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 capital subsidy policies on the targeted territory. The empirical evaluation of a policy in Italy mainly directed towards small- and medium-sized firms shows that the impact on investments, turnover and employment is positive and large, but is negative on TFP. However, the employment growth is partially determined to the detriment of the untreated firms.


Abstract: This paper evaluates the impact of subsidies on the different components of TFP for granted firms’ longterm growth. The impact of capital subsidies is captured by a quasi–experimental method (Multiple RDD), exploiting the conditions for a local random experiment created by an Italian industrial policy. Results show that capital subsidies negatively affect TFP growth in the short term, and signals of positive effects appear only after 3–4 years. This positive medium-long term impact comes especially through technological change and not through scale impact change, as may have been expected.



Abstract: There is still little consensus among economists on the effectiveness of business support policies. The evaluation of such policies requires a reliable identification procedure that is hardly achieved in empirical studies. We analyse 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.

(Other) Journal Publications



Abstract: Although widespread, the recent populist wave in Western countries is a heterogeneous phenomenon in terms of individual features of populist voters — the stereotype is “older, working-class, white, poorly educated, who live on low incomes” — as well as geographical characteristics of populist hotspots — “lagging-behind, stagnating and low-productivity regions”. This study leverages nonlinear statistical learning techniques to detect recurrent individual and geographical patterns of populist voting across Italy. Using the Chapel Hill expert survey classification, we analyse the most prominent voting patterns during the 2019 European elections in all Italian local labour markets. We map the Italian geography of discontent, highlighting how it seems to be shaped by the interaction between individual- and territorial-level predictors. Our study promotes the adoption of flexible and nonparametric predictive algorithms to ‘diagnose’ the main factors linked to the spatial distribution and evolution of populist hotspots.

Abstract: 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’.


Abstract: We consider from a theoretical and empirical viewpoint how network preferences of consumers, which differ in their willingness to pay (WTP) for green goods, affect the equilibrium configuration of a vertically differentiated duopoly when a cleaner firm competes against a dirtier rival. We find that a trade-off can emerge between emissions abatement and the catching-up process of the dirtier firm can emerge. In particular, emissions decrease only when consumers with low WTP have network preferences. Still, in this case, only the cleaner firm has an incentive to improve its environmental quality along the quality ladder, while the laggard firm is tied to its backward profile. These theoretical predictions are empirically tested by exploiting the duality of Italy's economy, with high-income citizens mainly concentrated in Northern regions, while low-income citizens are largely located in the South. We adopt a fixed-effects spatial error model at the provincial level to relate variables on firms' environmental management system with citizens' environmental behaviour, proxied by the recycling rate. Overall, the empirical estimates are in line with the theoretical predictions. From the empirical analysis, it emerges that consumers' environmental behaviour positively affects enterprises' future environmental choices. Moreover, firms have a stronger incentive to raise their environmental quality when low-income consumers, namely those buying dirtier variants, internalise the network effect.

Abstract: In recent years, the use of counterfactual techniques for the evaluation of regional policies has greatly expanded, mainly due to the availability of ever better data from the point of view of geographical location, the characteristics of the subjects involved, the temporal and spatial coherence. This process has posed new challenges to the econometric techniques developed to estimate regional policy impacts. There are specific characteristics of place-based policies that necessarily require a particular specification or even a specific adaptation of counterfactual techniques. The greatest difficulty is in the inherent endogeneity of place-based policies: the lower the development of a region, the greater the public intervention. In addition, the presence of interferences between treated subjects, between untreated subjects and between both, leads to the need to adapt the Rubin causal model, as it is based on the Stable Unit Treatment Value Assumption, which postulates that there is no interference between units. Furthermore, the presence of spillovers due to interference creates the need to define various measures of policy impact, considering direct, indirect, and total effects. This survey gives an account of the evaluation techniues most used in such literature, and of some recent or still evolving methodological developments. 


Abstract: As the demand for environmentally sustainable tourism grows, eco-labels are becoming increasingly popular as a signal of environmental quality. However, the existence of a causal link between awarding a seaside eco-label and the increase in tourism flows is still under discussion in the literature. In this article, we gauge the signalling impact of a specific eco-label, the Blue Flag award, using detailed data on tourism flows to seaside Italian destinations during the period 2008–2012. We adopt a recent econometric modelling strategy – the synthetic control method – in shaping estimation results and testing the sensitivity and robustness of our results. We find that being awarded the Blue Flag increases the flow of domestic tourists for up to three seasons after assignment. However, we find no effect for the flow of international tourists. Investigating the mechanisms driving the results, we find that the award of a Blue Flag only positively affects the flow of domestic tourists when it is used as a driver of organisation, coordination and integrated management of the tourism supply. 

Abstract: Although there are several studies looking at the effect of natural disasters on economic growth, less attention has been dedicated to their impact on educational outcomes, especially in more developed countries. We use the synthetic control method to examine how the L’Aquila earthquake affected subsequent enrolment at the local university. This issue has wide economic implications as the University of L’Aquila made a large contribution to the local economy before the earthquake. Our results indicate that the earthquake had no statistically significant effect on first-year enrolment at the University of L’Aquila in the three academic years after the disaster. This natural disaster, however, caused a compositional change in the first-year student population, with a substantial increase in the number of students aged 21 or above. This is likely to have been driven by post-disaster measures adopted in order to mitigate the expected negative effects on enrolment triggered by the earthquake. 



Abstract: This paper addresses an important question on the consequences of relegation from some of Europe’s top football leagues: What is the team’s performance following relegation, compared to the situation without relegation? We compare the performance of relegated and non-relegated teams that battled until the last match to escape relegation in four large European leagues. We find that, on average, up to six seasons are necessary to completely reabsorb the negative relegation shock in sports outcomes. Additionally, we exploit current information on future TV rights revenues to forecast the extra cost of an ‘unlucky’ relegation in the 2013-14 season. The results show that, on average, relegation will cause an extra cost of about €135m to ‘combative’ teams relegated from the English Premier League. Smaller extra losses apply to the Italian Serie A (€60m), the Spanish La Liga (€38m), and the French Ligue 1 (€32m).

Working Papers


Abstract: Assessing institutional quality at the municipal level is a complex task and available indices are usually dispersed across different years and offer limited geographical coverage. To bridge this gap, we have introduced the Municipal Administration Quality Index (MAQI), the first composite index designed to measure the quality of administrations at the most granular administrative level over a broad time span. Focusing on Italian municipalities, MAQI evaluates the quality of municipal administrations by examining objective dimensions concerning bureaucratic quality and capacity, local politicians’ valence attributes, and local governments’ economic and fiscal performance. Spanning from 2001 to 2021 and covering nearly all Italian municipalities, MAQI will enable researchers to assess the administrative quality of local governments across multiple dimensions and over time, a task that was previously impracticable.

Abstract: Without a credible control group, the most widespread methodologies for estimating causal effects cannot be applied. To fill this gap, we propose the Machine Learning Control Method (MLCM), a new approach for causal panel analysis based on counterfactual forecasting with machine learning. The MLCM estimates policy-relevant causal parameters in short- and long-panel settings without relying on untreated units. We formalize identification in the potential outcomes framework and then provide estimation based on supervised machine learning algorithms. To illustrate the advantages of our estimator, we present simulation evidence and an empirical application on the impact of the COVID-19 crisis on educational inequality in Italy. We implement the proposed method in the companion R package MachineControl.

Abstract: We evaluate the impact of a recent reform that sharply increased the salaries of Italian local politicians on electoral competition and the valence attributes of the candidates elected. Exploiting misaligned election dates across Italian cities, we propose a novel methodology, the shifted difference-in differences design (Sh-DiD), to estimate the reform’s impact on municipalities up to 30,000 inhabitants, representative of almost the entire universe of Italy’s local administrative units. We find a boost in the entry of new political candidates after the first post-reform electoral round, with no significant enhancement in the overall quality of the political class. These outcomes possibly stem from the varying distribution of compliers whose candidacy decision is influenced by the reform—across diverse political and economic contexts. Thus, we find that in less affluent areas or those with fewer entry barriers, the pay rise drew a larger number of mayoral candidates, encouraging individuals from outside the political sphere to enter the competition. In the poorest contexts, we also observe a shift in the profile of councilors and members of the mayor’s executive committee, where the pay rise attracted individuals with lower educational levels but with experience in white-collar positions.

Abstract: We explore whether mayors supported by pro-environmental parties enhance local environmental outcomes compared to their non-environmental counterparts. We study close elections within a regression discontinuity design and find a notable rise in recycling rates in Italian municipalities governed by pro-environmental coalitions. This uptick becomes far less pronounced when adopting broader criteria to define green mayoral candidates. Crucially, the enhanced recycling rates are not realized through augmented budgets for environmental initiatives or waste collection, but rather are primarily attributed to the implementation of local policies, such as on-call waste collection and the establishment of waste collection centers.

Abstract: Territorial reforms of administrative boundaries are primarily aimed at pursuing cost and administrative efficiency objectives, but their impact on local communities’ political engagement remains unclear. Moreover, while amalgamations have been widely studied, little is known about the effects of territorial fragmentation. To address this gap, we examine a regional reform in Italy’s Apulia region, where five municipalities split voluntarily in the mid Seventies. We analyze the long-term effects on political engagement using a synthetic difference-in-difference approach. Our findings reveal that newly founded municipalities experienced a substantial increase in voter turnout, particularly at the local level. This positive impact grew over time, enduring for almost half a century post-fragmentation. Interestingly, the ‘old’ municipalities remained unaffected.

Abstract: This paper exploits a sudden increase in the regional surcharge on the income tax rate in Lazio, one of the most populated regions of Italy, to compare taxpayers’ reported income in Lazio’s municipalities with those in the municipalities located in six neighboring regions. To this end, we have built a new yearly dataset (2012-2018) at municipal level containing the reported income of different categories of taxpayers and employ a spatial regression discontinuity design to estimate the response to an increase of the marginal tax rate in terms of reported taxable income by different types of taxpayers. We find a sizable and persistent decrease in reported income only for the self-employed and entrepreneurs, while the employees respond by slowly reducing their declared incomes. As expected, the retirees do not exhibit any response. 

Work in Progress

Going Local: Public Spending, Bureaucratic Efficiency and Decentralization (with C. Giannantoni)

The Clustered Dose-Response-Function Estimator for Continuous Treatment and Heterogenous Effects (with R. Di Stefano, R. Mattera)

Labor mobility in times of turmoil: A comparative analysis of the effects of different economic crises on displaced workers (with V. Celli, G. Pellegrini)


Other articles (Technical reports and non-peer reviewed publications)

Cerqua, A., 2023. Guidance note for the impact evaluation of State aid for R&D in Slovenia, Crivellaro, E., Ferrara, A. and Granato, S. editor(s), Publications Office of the European Union, Luxembourg, JRC133939.

Was there a Covid-19 Harvesting Effect in Northern Italy? 2021. In: Bernini, C., Emili, S., “Regions Between Challenges and Unexpected Opportunities” (with Di Stefano, R., Letta, M., Miccoli, S.)

Assessing Factors that Affect the Labour Market Decisions of Young People aged 16 to 24: Research Informing LPC Review of Youth Rates. Project Report. Low Pay Commission, UK. (with Bowyer, A., Di Pietro, G., Gorman, E., Urwin, P)

The Effects of EU Regional Policy on the Growth of European Regions. Chapter of the "The Impact of Cohesion Policies in Europe and Italy" dossier published by the Impact Assessment Office of the Senato della Repubblica Italiana.

Identifying Variation in Learner Outcomes by Further Education Provider. Project Report. Department for Education, London, 2017. (with Urwin, P.)

Measuring the impact of Structural and Cohesion Funds using the regression discontinuity design in the period 1994-2011 (part 2). Directorate-General for Regional and Urban Policy, European Commission, Luxembourg, 2016. (with Pellegrini, G.)

Returns to Maths and English Learning in Further Education. Project Report. Department for Business, Innovation and Skills, London, 2016. (with Urwin, P.).

Further Education: Social Mobility, Skills and Second Chances. Project Report (with Bibby, D., Thomson, D., Urwin, P.) Press coverage: TES_1; TES_2; TES_3

Impact of skills and training interventions on the unemployed. Project Report. Department for Business, Innovation and Skills, London, 2015. (with Bibby, D., Thomson, D., Urwin, P.).                                            Press coverage: FE_Week

Further disaggregation - employment and earnings returns by sector group. Project Report. Department for Business, Innovation and Skills, London, 2015. (with Thomson, D., Urwin, P.).

La dimensione spaziale nella valutazione degli incentivi alle imprese: cosa cambia se si tiene conto degli spill-over? In: Antonietti, R., Corò, G., Gambarotto, F., “Uscire dalla crisi. Città, comunità, specializzazione intelligenti”, 2015. (with Guido Pellegrini)

Further development in the estimation of labour market returns to qualifications gained in English Further Education using ILR-WPLS Administrative Data. Project Report. Department for Business, Innovation and Skills, London, 2014. (with Bibby, D., Buscha, F., Thomson, D., Urwin, P.).

Spillovers and Policy Evaluation. In: Mazzola, F., Musolino, D., Provenzano, V., “Reti, nuovi settori e sostenibilità. Prospettive per l'analisi e le politiche regionali”, 2014. (with Guido Pellegrini)