This dissertation addresses issues that arise in the classic linear instrumental variables (IV) model when some of the underlying assumptions are violated. / Economics

This thesis makes contributions to the statistical research field of causal inference in observational studies. The results obtained are directly applicable in many scientific fields where effects of treatments are investigated and yet controlled experiments are difficult or impossible to implement. In the first paper we define a partially specified directed acyclic graph (DAG) describing the independence structure of the variables under study. Using the DAG we show that given that unconfoundedness holds we can use the observed data to select minimal sets of covariates to control for. General covariate selection algorithms are proposed to target the defined minimal subsets. The results of the first paper are generalized in Paper II to include the presence of unobserved covariates. Morevoer, the identification assumptions from the first paper are relaxed. To implement the covariate selection without parametric assumptions we propose in the third paper the use of a model-free variable selection method from the framework of sufficient dimension reduction. By simulation the performance of the proposed selection methods are investigated. Additionally, we study finite sample properties of treatment effect estimators based on the selected covariate sets. In paper IV we investigate misspecifications of parametric models of a scalar summary of the covariates, the propensity score. Motivated by common model specification strategies we describe misspecifications of parametric models for which unbiased estimators of the treatment effect are available. Consequences of the misspecification for the efficiency of treatment effect estimators are also studied.

<p>Diss. (sammanfattning) Umeå : Umeå universitet, 2002, Härtill 5 uppsatser.</p> / digitalisering@umu

The primary aim of this thesis was to make an initial evaluation of the cognitive-oriented treatment programs “A New Direction” for young people and ”New Challenges” for adult men. The treatment programs were examined in two studies mainly aimed at measuring treatment effects on criminal thought patterns and sense of coherence. In the study of the Youth Program (Paper I), pre- and post-measurements were made with the Psychological Inventory of Criminal Thinking Styles (PICTS) and the shortened version of Sense of Coherence (SOC-13). In addition, recidivism over a two-year period was analysed. The results show that the criminal thinking clearly decreases for participants in individual treatment for 9-30 weeks and that the rate of recidivism is lower compared with the control group. In the Adult Program (Paper II) study, pre- and post-measurements were made with PICTS, SOC-13, Positive and Negative Affect Schedule (PANAS) and Quality of Program Delivery (QPD). The result shows that criminal thinking is clearly reduced, and positive affect is increased for participants in cognitive treatment that included one-week group treatment, four weeks individual treatment and finally one-week further group treatment. The individual treatment for four weeks was combined with 12-step treatment. No significant results were shown for either control participants who received 12-step treatment or no treatment.  There is also a positive correlation between QPD and sense of coherence and between QPD and positive affect. The main conclusions are that the programs can reduce criminal thinking and improve salutogenic resources, which can help reduce criminal behaviour. / Licentiatuppsatsen representerar ett pilotprojekt som förväntas ge en första bild av effekterna av behandling med kriminalitetsprogrammen ”Ett nytt vägval” för ungdomar och ”Nya utmaningar” för vuxna män. Det övergripande syftet har varit att bidra till evidensforskningen av kriminalitetsprogram som kombinerar både ett risk- och skyddsfokus och som utvärderats inom missbruksvården. I studie I (ungdomsstudien) visade resultatet att flerveckors individuell behandling minskar det kriminella tänkandet, ökar känslan av sammanhang och minskar brottsåterfallsfrekvensen. Studiens resultat är valida för individuell behandling under 9 till 30 veckor för målgruppen svenska pojkar med en medelålder på 17 år i förkriminell och tidig fas av kriminalitet. I Studie II (vuxenstudien) undersöktes den behandlingsform som kallas Valbo modellen som kombinerar ”Nya utmaningar” med tolvstegsbehandling. Efter att tolvstegsbehandlingens inverkan på resultatet analyserats antas den största direkta förändringsfaktorn vara behandlingen med ”Nya utmaningar”. Tolvstegsbehandlingen antas ha en mer indirekt och långsiktig verkan och vara av betydelse för den känslomässiga förankringen och hållbarheten i ett förändrat normsystem och ny livsstil. Studiens resultat är valida för svenska män i 30 års-åldern i avancerad fas av kriminalitet. Studierna utgör ett första steg mot att programmen ”Ett nytt vägval” och ”Nya utmaningar” kan sägas motsvara dagens begrepp för evidens.

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Labor intensive sectors such as the specialty crop sector have historically had strong reliance on foreign labor, constituting roughly oneifth of all U.S. farms while incurring roughly two-thirds of direct-hire expenses. It is estimated that more than half unauthorized of the foreign-born labor force in the specialty crop sector are unauthorized for US employment. Using data from the National Agricultural Workers Survey for 1989-2014, this study uses a treatment effects approach (via propensity score matching and minimum-biased estimation) to evaluate the farm wage implications of legalization of foreign-born specialty crop farm workers nationally, as well as specifically in California. Positive wage effects are estimated in nationally and in California, with higher magnitude effects observed in California.

This dissertation consists of three chapters that generally focus on the design of welfare-maximizing treatment assignment rules in heterogeneous populations with interactions. In the first two chapters, I focus on an important pre-step in the design of treatment assignment rules: inference for heterogeneous treatment effects in populations with interactions. In the final chapter, I and my co-authors study treatment assignment rules in the presence of social interaction in heterogeneous populations. In chapter one, I argue that statistical inference of heterogeneous treatment effects (HTEs) across predefined subgroups is complicated when economic units interact because treatment effects may vary by pretreatment variables, post-treatment exposure variables (that measure the exposure to other units’ treatment statuses), or both. It invalidates the standard hypothesis testing technique used to infer HTEs. To address the problem, I develop statistical methods (asymptotic and bootstrap) to infer HTEs and disentangle the drivers of treatment effects heterogeneity in populations where units interact. Specifically, I incorporate clustered interference into the potential outcomes model and propose kernel-based test statistics for the null hypotheses of (a) no HTEs by treatment assignment (or post-treatment exposure variables) for all pretreatment variables values; and (b) no HTEs by pretreatment variables for all treatment assignment vectors. To disentangle the source of heterogeneity in treatment effects, I recommend a multiple-testing algorithm. In addition, I prove the asymptotic properties of the proposed test statistics via a modern poissonization technique. As a robust alternative to the inferential methods I propose in chapter one, in chapter two, I design randomization tests of heterogeneous treatment effects (HTEs) when units interact on a single network. My modeling strategy allows network interference into the potential outcomes framework using the concept of network exposure mapping. I consider three null hypotheses that represent different notions of homogeneous treatment effects, but due to nuisance parameters and the multiplicity of potential outcomes, the hypotheses are not sharp. To address the issue of multiple potential outcomes, I propose a conditional randomization inference method that expands on existing methods. Additionally, I consider two techniques that overcome the nuisance parameter issue. I show that my conditional randomization inference method, combined with either of the proposed techniques for handling nuisance parameters, produces asymptotically valid p-values. Chapter three is based on a joint paper with Young Ki Shin and Seungjin Han. We study treatment assignment rules in the presence of social interaction in heterogeneous populations. We construct an analytical framework under the anonymous interaction assumption, where the decision problem becomes choosing a treatment fraction. We propose a multinomial empirical success (MES) rule that includes the empirical success rule of Manski (2004) as a special case. We investigate the non-asymptotic bounds of the expected utility based on the MES rule. / Dissertation / Doctor of Philosophy (PhD)

This study investigates the heterogeneity of European NUTS-2 regions with regard to their ability to take advantage of European Union (EU) structural funds aimed at convergence. It considers a concept of absorptive capacity based on regional policy design, and additionally accounts for the programming period 2007-2013 in the empirical analysis. A fuzzy regression discontinuity design allowing for heterogeneous treatment effects is applied to evaluate convergence funds in 250 NUTS-2 regions from 2000 (and 1989) to 2013. The main results suggest a positive conditional impact of funds payments on regional GDP per capita growth. However, based on a time-varying treatment effects model, we are able to identify a deterioration in the effectiveness of convergence funds during the programming period 2007-2013. Furthermore, the analysis reveals an inverted U-shaped relationship between the share of committed funds paid out and GDP per capita growth. The latter finding indicates that the marginal benefits from EU convergence funds might be decreasing. (author's abstract) / Series: Department of Economics Working Paper Series

This thesis explores the use of observational microdata in cost-effectiveness analysis. The application of econometric methods adjusting for selection bias is first reviewed and critically appraised in the economic evaluation literature using a structured template. Limitations of identified studies include lack of good quality evidence regarding the performance of different analytical approaches; inadequate assessment of the sensitivity of their results to violations of fundamental assumptions or variations to crucial estimator parameters; failure to combine the cost and effectiveness outcomes in a summary measure; and no consideration of stochastic uncertainty for the purpose of evaluating cost-effectiveness. Data from the Birthplace national cohort study are used in an attempt to address these limitations in the context of an empirical comparison of estimators relying on regression, matching, as well as the propensity score. It is argued that although these methods cannot address the potential impact of unobservable confounding, a novel approach to bias-corrected matching, combining entropy balancing with seemingly unrelated regression, still has the potential to offer important advantages in terms of analytical robustness. The net economic benefit is proposed as a straightforward way to exploit the strengths of rigorous econometric methodology in the development of reliable and informative cost-effectiveness analyses.

The purpose of the study was to find out if the influential arrangements that is given to convicted delinquents between 15-17 years old is practised because they have evidence or if it is based on other grounds. The research questions were answered with the help of a questionnaire and interviews. The questionnaire was sent to all 290 local authorities whereof 52 answered the questions. The result indicated difficulties to get information regarding which arrangements that is being used, the local authorities have various ways of working and the programs and/or routines they use make it hard to access statistics. The most common influential arrangements were programs made by the local authorities themselves, which brings difficulties with the evidence of treatment effects. Interviews were carried out with three persons from social services who work with delinquents. The results showed that the choices were made on the basis of guidelines if there were any available, otherwise out of a feeling or experience. The conclusion was that there often seems to be a consideration regarding the evidence of treatment effects when arrangements are chosen, but that the choice many times still occur based on other premisses. / Studiens syfte var att utröna om de påverkande insatser som erläggs dömda ungdomsbrottslingar 15-17 år används för att de har evidens eller om valet vilar på andra grunder. Forskningsfrågorna besvarades med hjälp av enkät och intervjuer. Enkäten skickades till samtliga Sveriges 290 kommuner varav 52 svarade på frågorna. Resultatet visade på svårigheter att få tillförlitlig information om vilka insatser som används, kommunerna arbetar olika och de program och/eller rutiner som används gör det svårt att ta fram statistik. De vanligast förekommande påverkansinsaterna var egenkomponerade program, vilket medför svårigheter med kontroll av evidensen. Intervjuer utfördes med tre personer från socialtjänsten som arbetar med unga lagöverträdare. Resultatet visade att valet baseras på riktlinjer där sådana finns, annars tas egna beslut utifrån känsla och erfarenhet. Slutsatsen blev att det många gånger finns en tanke kring evidens när insatser ska väljas, men att valet ändå ofta sker på andra premisser.