Academic literature on the topic 'Policy evaluation'

AbstractPolicy evaluations can be set up for multiple purposes including accountability, policy learning and policy planning. The question is, however, how these purposes square with politics itself. To date, there is little knowledge on how government ministers present the rationale of evaluations. This article is the first to provide a diachronic study of discourse about evaluation purposes and encompass a wide range of policy fields. We present an analysis of evaluation announcements in so-called ministerial policy notes issued between 1999 and 2019 by the Flemish government in Belgium. The research fine-tunes available evidence on catalysts for conducting evaluations. The Flemish public sector turns out to be a strong case where New Public Management brought policy evaluation onto the agenda, but this has not resulted in a prominent focus on accountability-oriented evaluations. We further show that policy fields display different evaluation cultures, albeit more in terms of the volume of evaluation demand than in terms of preferences for particular evaluation purposes.

This literature review offers a comprehensive overview of the use of evaluation criteria across five policy fields: social services, land-use planning, teaching in higher education, vocational education, and the environment. Though it is a key part of the evaluation process, the question of how criteria are defined, chosen, and applied generates surprisingly little debate among the evaluation community. In evaluation practice, criteria are often taken for granted – and occasionally even used in ways that are neither explicit nor transparent. This cross-field literature review shows a strong presence of routinized evaluation criteria (relating to the specifics of each policy field), while some new sets of higher-degree criteria also emerge in the face of social challenges relating to sustainability, public acceptance, or social justice. Criteria development draws on both inductive bottom-up processes (which can include policy stakeholders) and top-down deductive processes (which derive criteria from the literature, as well as from national and international standards). A more profound reflection on evaluation criteria (that is, the dimensions used by societies to assess the success of policy interventions) might be required in the future of evaluation research and planning; a deeper cross-field dialogue could support this endeavor.

Background All federal agencies are required to support appropriation requests with evidence and evaluation (US Public Law 115-435; the Evidence Act). The StrAtegic PoLicy EvIdence-Based Evaluation CeNTer (SALIENT) is 1 of 6 centers that help the Department of Veterans Affairs (VA) meet this requirement. Objective Working with the existing VA evaluation structure, SALIENT evaluations will contribute to (1) optimize policies and programs for veteran populations; (2) improve outcomes regarding health, equity, cost, and provider well-being; (3) advance the science of dissemination and knowledge translation; and (4) expand the implementation and dissemination science workforce. Methods We leverage the Lean Sprint methodology (iterative, incremental, rule-governed approach to clearly defined, and time-boxed work) and 3 cores to develop our evaluation plans collaboratively with operational partners and key stakeholders including veterans, policy experts, and clinicians. The Operations Core will work with evaluation teams to develop timelines, facilitate work, monitor progress, and guide quality improvement within SALIENT. The Methods Core will work with evaluation teams to identify the most appropriate qualitative, quantitative, and mixed methods approaches to address each evaluation, ensure that the analyses are conducted appropriately, and troubleshoot when problems with data acquisition and analysis arise. The Knowledge Translation (KT) Core will target key partners and decision makers using a needs-based market segmentation approach to ensure that needs are incorporated in the dissemination of knowledge. The KT Core will create communications briefs, playbooks, and other materials targeted at these market segments to facilitate implementation of evidence-based practices and maximize the impact of evaluation results. Results The SALIENT team has developed a center infrastructure to support high-priority evaluations, often to be responsive to shifting operational needs and priorities. Our team has engaged in our core missions and operations to rapidly evaluate a high-priority areas, develop a comprehensive Lean Sprint systems redesign approach to training, and accelerate rapid knowledge translation. Conclusions With an array of interdisciplinary expertise, operational partnerships, and integrated resources, SALIENT has an established and evolving infrastructure to rapidly develop and implement high-impact evaluations. Projects are developed with sustained efficiency approaches that can pivot to new priorities as needed and effectively translate knowledge for key stakeholders and policy makers, while creating a learning health system infrastructure to foster the next generation of evaluation and implementation scientists. International Registered Report Identifier (IRRID) PRR1-10.2196/59830

This dissertation consists of three empirical studies that aim at providing new evidence in the field of public policy evaluation. In particular, the first two chapters focus on the effects of the European cohesion policy, while the third chapter assesses the effectiveness of Italian labour market incentives in reducing long-term unemployment. The first study analyses the effect of EU funds on life satisfaction across European regions , under the assumption that projects financed by structural funds in the fields of employment, education, health and environment may affect the overall quality of life in recipient regions. Using regional data from the European Social Survey in 2002-2006, it resorts to a regression discontinuity design, where the discontinuity is provided by the institutional framework of the policy. The second study aims at estimating the impact of large transfers from a centralized authority to a local administration on the incidence of white collar crimes. It merges a unique dataset on crimes committed in Italian municipalities between 2007 and 2011 with information on the disbursement of EU structural funds in 2007-2013 programming period, employing an instrumental variable estimation strategy that exploits the variation in the electoral cycle at local level. The third study analyses the impact of an Italian labour market policy that allowed firms to cut their labour costs on open-ended job contracts when hiring long-term unemployed workers. It takes advantage of a unique dataset that draws information from the unemployment lists in Veneto region and it resorts to a regression discontinuity approach to estimate the effect of the policy on the job finding rate of long-term unemployed workers.

This dissertation consists of three empirical studies that aim at providing new evidence in the field of public policy evaluation. In particular, the first two chapters focus on the effects of the European cohesion policy, while the third chapter assesses the effectiveness of Italian labour market incentives in reducing long-term unemployment. The first study analyses the effect of EU funds on life satisfaction across European regions , under the assumption that projects financed by structural funds in the fields of employment, education, health and environment may affect the overall quality of life in recipient regions. Using regional data from the European Social Survey in 2002-2006, it resorts to a regression discontinuity design, where the discontinuity is provided by the institutional framework of the policy. The second study aims at estimating the impact of large transfers from a centralized authority to a local administration on the incidence of white collar crimes. It merges a unique dataset on crimes committed in Italian municipalities between 2007 and 2011 with information on the disbursement of EU structural funds in 2007-2013 programming period, employing an instrumental variable estimation strategy that exploits the variation in the electoral cycle at local level. The third study analyses the impact of an Italian labour market policy that allowed firms to cut their labour costs on open-ended job contracts when hiring long-term unemployed workers. It takes advantage of a unique dataset that draws information from the unemployment lists in Veneto region and it resorts to a regression discontinuity approach to estimate the effect of the policy on the job finding rate of long-term unemployed workers.

This document is a collection of three articles developed during the course of my PhD, which I submit as requirement for the final exam. The three papers focus to some extent on policy evaluation, applying two main microeconometric techniques: regression discontinuity design and difference-in-differences. Each paper is briefly described as follows. Daylight Saving Lives - In this paper I investigate the effect of Daylight Saving Time (DST) on homicides. Educated Candidates and Efficient Bureaucrats - I test whether more educated candidates make into less corrupt public managers Accountability Shock and Market for Oversight - In this paper I tests whether a top-down shock in oversight and political accountability can strengthen the market for transparency in public management.

This thesis comprises two rather different chapters. The first chapter explores the impact of increasing the exit costs of cohabitation on the stability of relationships. The second chapter explores the impact that an established environmental beach award has on the tourism sector and the balance sheet of a municipality. Notwithstanding these thematic differences, the two chapters are connected by the way in which the research therein was conducted. This particular approach to research is known as the credibility revolution". It was championed by Angrist and Pischke in Angrist and Pischke (2008) and Angrist and Pischke (2010). The approach is concerned with causality above all other issues and aims at minimising the assumptions made when estimating an object of interest; be it theoretical or technical. In order to construct well-founded economic models of behaviour based on the credibility revolution", this sort of humble policy evaluation work needs to be abundant. Without gathering sufficient evidence about the causal mechanisms that inform the behaviour of individuals; there can be no strong foundations upon which to build sound economic models. This is only likely to lead to misleading analyses and policy failures.

This thesis presents a number of examples where macroeconometric models are employed as useful tools for evaluation of contemporary policy problems. A range of approaches is proposed to shed light on how macromodels can actually contribute to the policy debate. In particular, the thesis emphasises how different models maybe augmented or modified and stresses the need for care in the experimental design of policy simulations. Small stylised models of the UK economy are estimated in the first part of this thesis. They are used to assess the performance of simple monetary policy rules under the current inflation targeting monetary regime. In a monetary policy regime of inflation targeting, the appropriate target band-width can be assessed by calculating the variance of inflation in a macroeconomic model under alternative policy rules. A recent Bank of England study concludes from stochastic simulation of a small semi-structural model that a 'fairly substantial lump of inflation uncertainty' exists in the United Kingdom. In chapter 2 an extended and improved version of that model is developed while their estimates of inflation variability are revised downwards by deploying analytic techniques. In chapter 3 a new small 'semi structural' dynamic model of the UK economy is estimated, with particular attention to the modelling of wages and prices. It is used to assess the performance of simple monetary policy rules, including 'inflation forecast targeting' and 'Taylor' rules, while taking into account different degrees of forward-lookingness in both inflation targeting horizon and wage bargaining. Computation of asymptotic inflation-output standard-error trade-offs is provided under various specifications and parametrisations of the model. Large-scale country models have the convenience to make explicit a complete range of relationships among macroeconomic variables most of which, for obvious reasons, are neglected in smaller dynamic models. As a consequence, such quantitative framework offers an unique opportunity to evaluate not only the aggregate impact of exogenous shocks on the variables of interest, but also to identify the underlying economic mechanisms enabling the transmission of such shocks. In the second part of the thesis, I undertake simulations of the National Institute's Domestic Econometric Model (NIDEM) to analyse the characteristics of the UK monetary transmission mechanism. Chapter 4 emphasises that the impact of interest rate movements on real variables is strictly determined by both the monetary regime at work and the underlying assumptions regarding consumption behaviour. Certainly, the steady integration of the members of the EMU and increasing awareness of the need for closer co-operation in monetary and fiscal policy have stimulated greater interest in modelling interdependencies between European countries and the impact and feedbacks from the rest of the world economy. Many of the key issues have now an international aspect, so it becomes more and more difficult to rely on single-country models to provide necessary analysis. International transmission mechanisms can therefore be better tackled with a multi-country model. The third and last part of this thesis focuses on cross-country asymmetric transmissions in response to a common monetary shock within EMU. In particular, in chapter 5 an empirical analysis of the links between monetary and fiscal policy within EMU is presented. This is done through simulation of a neo-classical highly non-Ricardian multi-country model: the IMF's MULTIMOD Mark III (MM3). Chapter 6 provides further evidence about the effects of embracing a Monetary Union when underlying macroeconomist structures still differ across countries. By use of the same model-based quantitative framework, this chapter examines the role of nominal and real rigidities in European labour markets for the assessment of asymmetries in monetary transmission under various monetary regimes.

2014 - 2015<br>Over the last two decades there has been a proliferation of literature on program evaluation. Many researches in economics look at the causal effect of exposure of units to programs on some outcomes through econometric and statistical analysis. The units are typically economic agents such as individuals, households, markets, firms, counties, states or countries. The programs can be job search assistance programs, educational programs, vouchers, laws or regulations, drug therapies, environmental exposure or technology shocks. Rubin potential outcomes framework seems to be the dominant framework in which the aim is to compare the two potential outcomes for the same unit when he or she is exposed and not exposed to the program (or treatment)1. However, each unit can be only exposed to one levels of program: an individual may enrol or not in a training program or he (or she) may be subjected or not to policy. We can refer to this as the fundamental problem of causal inference (Holland, 1986; Imbens andWooldridge, 2008). The impossibility to compare the same individual at different treatment status induces to resolve the issue thinking in term of counterfactual. We need to compare distinct units at different levels of treatment. This means to compare different physical units or the same physical unit observed at different times. But each individual or unit who chooses to enrol in a program is (by definition) different from that who chooses not to enrol. These differences may invalidate causal comparison of outcomes by treatment status. Indeed, the fear in this econometrics literature is traditionally related to endogeneity, or self-selection, issues2. The simplest case for analysis is when assignment to treatment is randomized, and thus independent from the covariates as well as the potential outcomes. It is straightforward to obtain attractive estimators for the average effect of treatment in randomized experiments (e.g. the difference in means by treatment status). Although there have been some example 1Starting from the seventies, Rubin (1974, 1977, 1978) proposed to interpret the causal effect as comparison of so-called potential outcomes, namely pairs of outcomes define for the same unit given different levels of exposure to the treatment. This represent the dominant approach to the analysis of causal relationship in observational studies known with the label of Rubin Causal Model. 2Many of the initial theoretical studies focused on the use of traditional methods for dealing with endogeneity, such as fixed effect methods from panel data analyses and instrumental variables methods. Subsequently, the econometrics literatures has developed new approaches, requiring fewer functional form and homogeneity assumptions (Imbens and Wooldridge, 2008). 3/ 12 of experimental evaluations, they remain relatively rare in economics. More common is the case where economists analyse data from observational studies. Observational data generally create challenges in estimating causal effects referred to unconfoundedness, exogeneity, conditional independence, or selection on observable characteristics3. Estimation and inference of causal effect under unconfoundedness assumption requires that conditional on observed covariates there are no unobserved factors that are associated both with the assignment and with the potential outcomes4. Without unconfoundedness assumption there is no general approach to estimating treatment effects and various methods have been proposed (for a review, see Imbens and Wooldridge 2008). Where additional data are present in the form of samples of treated and control units before and after the treatment comparisons can be made through a difference-in-difference approach. The simplest setting is one where outcomes are observed for units observed in one of two groups (i.e. treated and control) and in one of two time periods (i.e. pre-treatment and post-treatment). Only units in one of the two groups, in the second time period, are exposed to a treatment. There are no units exposed to the treatment in the first period, and units from control group are never observed to be exposed to the treatment. To estimate the causal effect, the average change over time in the outcomes of control group is subtracted from the change over time in the outcomes of treated group. This double differencing removes biases in second period comparisons between the treatment and control group, that could be the result from permanent differences between those groups, as well as biases from comparisons over time in the treatment group, that could be the result of time trends unrelated to the treatment. Where the assignment of treatment is a deterministic function of covariates, comparisons can be made exploring continuity of average outcomes as a function of covariates. This setting, known as the regression discontinuity design, has a long tradition in statistics though only recently it has attracted much attention in the economics literature5. The basic idea is that assignment to the treatment is determined, either completely or partly, by the value of a predictor (i.e. an individual’s observable characteristic) being on either side of a common threshold. This generates a discontinuity in the conditional probability of receiving the treatment as a function of this particular predictor. Any other characteristic, between elected and unelected individual, is assumed to be smooth. As a result, any discontinuity of the conditional distribution of the outcome, as a function of this covariate at the threshold, is interpreted as evidence of a causal effect of the treatment6. 3For a review on this literature, see Imbens and Wooldridge (2008). 4Unconfoundedness implies that we have a sufficiently rich set of predictors for the treatment indicator, such that adjusting for differences in these covariates leads to valid estimates of causal effect. 5For recent review in the economics literature, see Van der Klaauw (2008), Imbens andWooldridge (2008) and Lee and Lemieux (2010). 6It may be useful to distinguish between two general setting, the sharp and the fuzzy regression discontinuity design. In the sharp regression discontinuity design, the assignment to treatment is a deterministic function of one of the observable covariates. In the fuzzy regression discontinuity design the probability of receiving the treatment 4/ 12 This thesis presents three essays of policy evaluation using the above quasi-experimental approaches. The research covers two different type of policies. On the one hand, we assess the effects on crime induced by a marijuana decriminalization policy exploiting the reforms still ongoing in the United States, on the other hand, we evaluate the impacts of the labour market reforms on labour market outcomes by using the recent changes in Italy occurred after the law 92/2012 (the so-called Fornero reform) like identification tool. Depending on the specific subject, the analysis is carried out from a specific empirical point of view. The first essay sheds light on the relationship between Medical Marijuana Laws and crimes in United States using counties level data. The set of judicial rules on the therapeutic consumption, production and distribution of cannabis at State level—started since 1996 in the United States—is known as Medical Marijuana Law (MML). It recognises the medical value of marijuana and provides a legal defence for patients who used and possessed marijuana under recommendation of a physician. The purpose of policy was the pain reduction for which the States allow doctors to prescribe marijuana as a pain killer also for general complaints related to pain, such as migraines, back pain and other pathologies. But, since the list of illness is quite broad, de facto, MML allows wide possibility for recreational use of marijuana masked like therapeutic consumptions (Chu, 2012). Hence, the assessment of policy on crime seems suitable. The research closely examining the importance of policy dimensions and the timing of the core elements of MMLs. In the U.S. States there have been three main actions that have involved the cannabis use for medical purpose: the mere decriminalization of marijuana, the permission of home cultivation for patients and caregivers, the licence for selling marijuana in authorized dispensaries. We interpret dimensions as design choices of policy maker on legal marijuana market by distinguishing between demand side approach, aimed to merely decriminalize cannabis, and supply side approach, directed to provide legal sources of supply for marijuana. This permits to explain the possible transmission channel trough which Medical Marijuana State Laws can affect crime. We test three possible links between drugs liberalization reforms and crime (i.e. pharmacological, economic, and systemic channels) finding evidence for only one of them (i.e. systemic channel). The analysis uses the Uniform Crime Reporting Program Data (UCR, 2013) which reports the number of arrests by type of offence from 1994 to 2014 at the U.S. county level. Since we have data of treated and control counties before and after the implementation of MML, we employ difference-in-difference approach by considering several types of crime such as violent and property crimes, and also felonies for narcotic possession (i.e. cocaine, heroine need not change from zero to one at the threshold. The design only requires a sufficiently large discontinuity in the probability of assignment to the treatment at the threshold. 5/ 12 etc.). We exploit the assessment of Medical Marijuana Law to highlight an important question in program evaluation concerning the heterogeneity of treatment effect. Even if the average treatment effect is zero, it may be important to establish whether a targeted implementation of intervention or different levels of treatment across the population could affect average outcome. We find that a simple dichotomous indicator of Medical Marijuana Law (i.e. the average treatment effect on all the U.S. States that passed the policy) may mask crucial dynamics underlying the relationship between policy and crime. Assuming a homogeneous impact of policy on crime, regardless the action implemented, the dichotomous indicator of MML captures only the net effect of the regulatory tools put in place by the legislator. On the contrary, the policy decomposition in key dimensions allows to discover different results which suggests a heterogeneous effects on crime according to the specific regulatory actions put in place by the legislator. In detail, for burglaries, larcenies, and cocaine drug possession, the mere application of demand side approach increases the crime in counties that passed the policy compared to counties without MML. While, the joint application of demand and supply approach— which establish legal sources for supply marijuana — may be able to realize a crowding-out effect on these offences. The findings support the idea that the licit competition on the marijuana market, triggered by the policy, could push out the illegal trade decreasing the crime. Finally, we find a net reduction in murders and a net increase in synthetic drug possession for the U.S. counties subject to the Medical Marijuana Law relatively to counties never passed the policy. The second and the third essays assess the impact of law 92/2012, implemented in Italy in 2012 (the so-called Fornero reform), on different labour market outcomes. The law 92/2012 introduced numerous changes regarding employment relationships amending past discipline. First. It substantially changed the discipline concerning the dismissals in firms above 15 employees. The reform established that in case of unfair dismissal, the dismissed worker has no longer the right to be reinstated as in the pre-reform period and receives a monetary compensation that ranges between 12 and 24 months pay. Thus the reform significantly reduces the firing cost borne by large firms. Second. Starting from January 2013, the Fornero reform also changed the discipline on apprenticeships concerning to the minimum duration of contract (no less than six months), the maximum number of apprentices that an employer can hire per each skilled worker (passed from 1:1 to 3:2), and the minimum number of apprentices that an employer must stabilize into permanent contracts for hiring a new apprentice (at least the 30% of apprentices hired in the last 12 months). Third. The Fornero reform implemented a new incentive program in favour of employers that recruit (on fixed-term or open-ended contracts) or stabilize into permanent agreements a worker aged 50 or more years. 6/ 12 The second essay (carried out with Giovanni Pica) estimates the effect of employment protection legislation on the flow of monthly hirings on open ended contracts using the aforesaid labour market reform passed in Italy in 2012. Much empirical research has focused on the effects of dismissal costs on labour market outcomes. The evidence suggests that EPL decreases employment inflows and outflows with little effect on employment and unemployment stocks. The reason is that firing costs act, in expected discounted value, as hiring cost reducing the willingness of the firms to both fire and hire workers (Bentolila and Bertola, 1990; Blanchard and Portugal, 2001). The most recent studies identify the causal impact of employment protection on labour market outcome exploiting within-county variation in EPL either across firms (e.g. of different size) or workers (e.g. of different age and/or tenure). The essay presented is in the line with within-county approach which allows to better control for time-varying unobserved characteristics that may affect labour market outcomes (act as confounding factors) compared to cross-country analyses. The presence of both treated and control firms observed before and after the policy — where the assignment of treatment depends in deterministic way from the number of workers employed — allows to implement a difference-in-difference approach jointly to a regression discontinuity design. We thus exploit the differential law change between firms with more and less than 15 workers comparing hirings in firms just above and below the 15 employee threshold before and after the reform (July 2012). The analysis is based on monthly data drawn from Italian Social Security (INPS) record for the period 2012 and 2014. The data provide information on the number of newly hired workers by firms size, province, sector, contract type, age and gender at a monthly frequency. The findings suggest that the reform raises monthly hirings on open-ended contracts by about 5.1 percentage points. The quantification of results reveals that the reduction of dismissal costs after the reform have induced about 4000 hirings per month in firms with more than 15 workers relative to firms with less than 15 workers. The effect of the reduction in EPL is not homogeneous across workers’ types. The increase seems to be more pronounced for full-time, young, and blue-collar workers. Conversely, we find no significant effect on the number of conversions of temporary contracts into permanent ones. The third essay evaluates the impact of labour policies aimed to improve the job possibilities for workers categorized as vulnerable (particularly in labour markets with stringent employment protection)7. Given the increasingly complicated transition from school to works, the youth appear a group more vulnerable compared to the past. Here the apprenticeship contract performs a crucial role by improving the job possibility and the stability of young workers (Berton et al., 2007; Casale et al., 2014). At the same time, the low employment rates for older workers pushed most OECD countries 7Evidences suggest that labour market prospects for youth and other marginal groups seem to worsen as a consequence of stringent EPL (Allard and Lindert, 2007; Bertola et al., 2007; Skedinger, 2010). 7/ 12 to experiment specific employment protections with the purpose to protect them from unemployment or/and to improve their job finding rates (Chéron et al., 2011). The Fornero reform intervenes by changing the discipline of apprenticeship in Italy and implementing a new incentive program for workers aged 50 or more years. The reform asymmetrically acted on the apprenticeships by changing the discipline in firms with more than 10 employees leaving the rules for firms below 10 unchanged. Likewise, the new incentive program for workers aged 50 or more years, passed with the Fornero reform, cut the hiring costs in firms that recruit workers over-50, leaving unaffected the costs for hiring workers under-50. These discontinuities in the regulation as well as the simultaneous presence of treated and control groups observed before and after the policy allow to implement a difference-in-deference method jointly to a regression discontinuity design. This quasi-experimental method permits to evaluate the causal effect of reform on the monthly hirings of apprentices and workers over-50. We thus exploit the differential law change in apprenticeships between firms with more and less than 10 employees, comparing the hirings and the conversions into open-ended contracts of apprentices in firms just below and above the 10 employees threshold before and after the reform (January 2013). Similarly, we compare the recruitments and the conversions into permanent contracts of workers with more and less 50 years before and after the reform. Also this analysis uses monthly data draw from Italian Social Security (INPS) record for the period 2012 and 2014. The findings suggest that the change in apprenticeships increase the stabilization of apprentices into open-ended contracts by about 3.9 percentage points in firms with more than 10 employees relative to firms with less than 10. We also find a positive association between law 92/2012 and the new recruitments of apprentices by about 7.1 percentage points in firms with more than 10 employees relative to firms with less than 10 employees. The employer incentives for hiring and stabilizing the workers aged 50 or more years positively affect the recruitments into open-ended contracts of workers over-50 relative to workers under-50 by about 1.6 percentage point. We also find a positive association between the incentive program and the hirings into fixed-term contracts of workers over-50 relative to workers under-50. Conversely, we don’t find effects for the conversions into open-ended contracts of workers aged 50 or more years. [edited by author]<br>Proposito della tesi di dottorato, dal titolo “Three Essays on Policy Evaluation”, è quello di sottolineare come l’impatto di una politica (economica e non) possa essere valutato secondo un approccio rigoroso, quasi-sperimentale, quando architettata adeguatamente a tale scopo. A tal proposito, sono mostrati tre esempi di valutazione delle politiche, nel corso dei quali si espongono ed affrontano le principali problematiche legate a questo tipo di esercizio. L'interesse dell'approccio adoperato nella presente tesi è dato dall'ampia utilizzazione del metodo difference-in-difference che consente di stimare, in vari contesti, gli impatti che politiche di differente natura possono avere sulle variabili socio-economiche. Ciascuno degli esercizi di valutazione costituisce un capitolo della tesi. Ogni uno di essi ha comportato una rassegna della letteratura in materia (allo scopo di inquadrare il tema trattato), la ricerca dei dati e l’elaborazione di uno specifico modello econometrico finalizzato all’identificazione del nesso causale. Il primo capitolo valuta l’impatto che le politiche di decriminalizzazione della cannabis per scopi terapeutici (Medical Marijuana Laws), adottate nei singoli Stati degli Stati Uniti, hanno avuto sulla criminalità a livello di contea. L’impatto della riforma è valutato rispetto a differenti tipologie di crimini, tratti dal UCR del FBI, classificabili in reati legati alla persona (i.e. omicidi), alla proprietà (i.e. furti) e all’uso di altre sostanza stupefacenti (i.e. cocaina). Dal lavoro emerge come ciascuno Stato americano si differenzi dagli altri sia per le tempistiche che per le modalità attuative della decriminalizzazione. L’originalità del lavoro sta nello sfruttare questa eterogeneità. Esso, infatti, propone una scomposizione della politica di decriminalizzazione della cannabis in interventi chiave, legati alle specifiche azioni adottate in tema di approvvigionamento e di distribuzione della marijuana. Tale scomposizione permette di identificare come l’impatto sui crimini commessi vari a seconda del timing e delle modalità di approvazione della decriminalizzazione. La scomposizione consente, inoltre, di ipotizzare un possibile canale di trasmissione attraverso il quale la Medical Marijuana Law impatterebbe sui crimini. I risultati empirici suggeriscono che la semplice decriminalizzazione della marijuana avrebbe un impatto positivo sulla criminalità se non accompagnata da (contestuali) interventi finalizzati ad istituire fonti legali di approvvigionamento della sostanza. Il secondo capitolo studia il ruolo che i meccanismi di protezione dell’occupazione (employment protection legislation) esercitano sui flussi in entrata del mercato del lavoro. A tale scopo, il lavoro stima l’impatto sulle assunzioni (e conversioni) in contratti a tempo indeterminato indotto dalla riforma del mercato del lavoro in Italia – legge n. 92 del 2012 (cd. riforma Fornero) – che ha ridotto i costi di licenziamento in carico alle imprese con più di 15 dipendenti, lasciando inalterata la situazione per le imprese con meno di 15 dipendenti. Il lavoro, oltre ad inquadrare la tematica con una rassegna della letteratura, sfrutta l’asimmetrico impatto della riforma (per le imprese appena sopra e appena sotto i 15 dipendenti) per stimare un modello difference-in-difference in un contesto di regression discontinuity design, utilizzando dati mensili INPS. I risultati empirici suggeriscono che la riduzione delle protezioni del lavoro incrementi le assunzioni in contratti a tempo indeterminato. Tale effetto risulta non omogeneo tra i diversi gruppi di lavoratori, mostrandosi più pronunciato per gli assunti full-time, più giovani ed operai. Al contrario, non emerge un chiaro effetto rispetto alle conversioni in contratti a tempo indeterminato. Infine, il terzo capitolo esamina le politiche del lavoro aventi l’obiettivo di aumentare le possibilità occupazionali di categorie ritenute più vulnerabili, quali i giovani lavoratori e gli over-50. A questo scopo, si utilizza la riforma dell’apprendistato e l’introduzione di un nuovo schema di incentivi per i lavoratori over-50, in forza in Italia a partire da gennaio 2013 (legge 92/2012), per stimare l’impatto che tali tipologia di interventi hanno sulle nuove assunzioni (sia a tempo determinato che indeterminato) e sulle conversioni in contratti a tempo indeterminato. Nello specifico, la riforma dell’apprendistato ha introdotto, per le imprese con più di 9 dipendenti, nuovi obblighi di stabilizzazione degli apprendisti assunti ed ha innalzato il rapporto tra gli apprendisti e i lavoratori qualificati presenti in azienda. Al contrario, la riforma lascia inalterata la situazione per le imprese sotto i 10 dipendenti. Lo schema di incentivi per l’assunzione e la stabilizzazione dei lavoratori over-50 consta, invece, in un significativo abbattimento (50 per cento) dei contributi a carico impresa per i lavoratori con più di 50 anni, lasciando inalterata la situazione per i soggetti più giovani. Le suddette circostanze hanno reso possibile l’implementazione di un modello difference-in-difference in un contesto di regression discontinuity design, utilizzando dati mensili INPS. I risultati empirici dimostrano che la riforma dell’apprendistato ha effettivamente favorito la stabilizzazione degli apprendisti in contratti a tempo indeterminato. Lo schema di incentivi per gli over-50 sembrerebbe indurre nuove assunzioni tanto in contratti a tempo indeterminato quanto a tempo determinato. L’effetto sulle conversioni, invece, sembrerebbe trascurabile. [a cura dell'autore]<br>XIV n.s.

The aim of my thesis is to evaluate the impacts of several public policies in Australia. I apply tools common in the policy evaluation literature to identify the causal effect of these policies on outcomes that policymakers care about, such as student test scores, employment rates and wages. Although the tools I use are common, the identification strategies and datasets I use are novel. These identification strategies are developed by carefully studying Australia's institutional details. My first chapter examines whether an increase in capital spending in schools (e.g. to build a new library or classroom) affects student test scores. Exploiting a large-scale natural experiment and school-level administrative data, I find no evidence that an increase in capital spending improves student test scores. The achievement effects that I find are close to zero and precisely estimated. My second chapter assesses how changes in minimum wages affect the labour market outcomes of employees paid the minimum wage. I exploit Australia's detailed system of ‘award’ wages to implement a control strategy. I find that increases to minimum wages are almost fully passed on to employee wages (implying that firms largely comply with their legal obligations). Importantly, however, there is no evidence that these minimum wage changes affect hours worked or job loss. My third chapter explores whether the decline in union membership rates in Australia has contributed to low wages growth in recent years. My co-author and I argue that trends in unionisation rates are unlikely to account for much of the recent low wages growth. This reflects our finding that the ‘union wage growth premium’ has remained stable over recent decades and that the share of the workforce who receive that premium has also remained steady, contrary to conventional wisdom.

Stochastic variance-reduced gradient (SVRG) is an optimization method originally designed for tackling machine learning problems with a finite sum structure. SVRG was later shown to work for policy evaluation, a problem in reinforcement learning in which one aims to estimate the value function of a given policy. SVRG makes use of gradient estimates at two scales. At the slower scale, SVRG computes a full gradient over the whole dataset, which could lead to prohibitive computation costs. In this work, we show that two variants of SVRG for policy evaluation could significantly diminish the number of gradient calculations while preserving a linear convergence speed. More importantly, our theoretical result implies that one does not need to use the entire dataset in every epoch of SVRG when it is applied to policy evaluation with linear function approximation. Our experiments demonstrate large computational savings provided by the proposed methods.