As an economically as well as politically sensitive topic, labor market interventions stir up discussions among professionals as well as general public. Most economists take negative stance against minimum wage policies providing arguments backed by theoretical reasoning rather then sound empirical evidence. Knowledge of labor market outcomes and their transmission channel to other segments of the economy are till nowadays limited and inconsistent. Neither empirical research in the field contributes to a uniform consent on the impact of minimum wage hikes on the price level. Moreover, the reported estimates display large heterogeneity and after a brief inspection reveal that the field is infested with publication selectivity. A uniquely constructed dataset consisting of 469 estimates of the price effect of minimum wage changes and their associated characteristics is analyzed using a set of statistical tools generally known as meta-analysis. The method is a powerful tool nowadays widely used in empirical research to synthesize and systematically evaluate sometimes inconsistent research results. While the study finds no consistent evidence of an actual link between minimum wage hikes and inflationary pressures, the empirical results show strong presence of publication selectivity. Powered by TCPDF (www.tcpdf.org)

abstract: Consumers can purchase local food through intermediated marketing channels, such as grocery stores, or through direct-to-consumer marketing channels, for instance, farmers markets. While the number of farms that utilize direct-to-consumer outlets keeps increasing, the direct-to-consumer sales remain lower than intermediated sales. If consumers prefer to purchase local food through intermediated channels, then policies designed to support direct channels may be misguided. Using a variety of experiments, this dissertation investigates consumer preferences for local food and their demand differentiated by marketing channel. In the first essay, I examine the existing literature on consumer preferences for local food by applying meta-regression analysis to a set of eligible research papers. My analysis provides evidence of statistically significant willingness to pay for local food products. Moreover, I find that a methodological approach and study-specific characteristics have a significant influence on the reported estimates for local attribute. By separating the demand for local from the demand for a particular channel, the second essay attempts to disentangle consumers’ preferences for marketing channels and the local-attribute in their food purchases. Using an online choice experiment, I find that consumers are willing to pay a premium for local food. However, they are not willing to pay premiums for local food that is sold at farmers markets relative to supermarkets. Therefore, in the third essay I seek to explain the rise in intermediated local by investigating local food shopping behavior. I develop a model of channel-selection in a nested context and apply it to the primary data gathered through an online food diary. I find that, while some consumers enjoy shopping at farmers markets to meet their objectives, such as socialization with farmers, the majority of consumers buy local food from supermarkets because they offer convenient settings where a variety of products can be bought as one basket. My overall results suggest that, if the goal is to increase the sales of local food, regardless of the channel, then existing supply-chain relationships in the local food channel appear to be performing well. / Dissertation/Thesis / Doctoral Dissertation Agribusiness 2018

When estimating the influence income per capita exerts on health care expenditure, the research in the field offers mixed results. Studies employ different data, estimation techniques and models, which brings about the question whether these differences in research design play any part in explaining the heterogeneity of reported outcomes. By employing meta-regression analysis, the present paper analyzes 220 estimates of health spending income elasticity collected from 54 studies and finds that publication bias is of marginal concern for the literature. The model specification choices, more exactly whether a study accounts for institutional factors and advancements in medical technology, have a negative effect on reported outcomes. Moreover, the "economic research cycle hypothesis" finds support in our analysis. Lastly, the research finds that the true income elasticity of health spending is situated around unity level, which makes health care neither a luxury, nor a necessity. Keywords: meta-regression analysis, aggregate health expenditure, income elasticity 1

The thesis consists of three papers, summarized as follows.        "The Determinants of Labour Market Institutions: A Panel Data Study"    This paper analyses the argument that labour market institutions can be thought of as devices for social insurance. It investigates the hypotheses that a country's exposure to external risk and ethnic fractionalisation are correlated with labor market institutions. Extreme bounds analysis with panel data of fourty years indicates that countries that are more open to international trade have stricter employment protection, strong unions, and a more coordinated wage bargaining process. Moreover, there is evidence that union density is negatively associated with the degree of ethnic fracationalisation.  "Why do Some Studies Show that Generous Unemployment Benefits Increase Unemployment Rates? A Meta-Analysis of Cross-Country Studies"    This paper investigates the hypothesis that generous unemployment benefits give rise to high levels of unemployment by systematically reviewing 34 cross-country studies. In contrast to conventional literature surveys, I perform a meta-analysis which applies regression techniques to a set of results taken from the existing literature. The main finding is that the choice of the primary data and estimation method matter for the final outcome. The control variables in the primary studies also affect the results. "The Effects of Trade on Unemployment: Evidence from 20 OECD countries"    This study empirically investigates if international trade has an impact on aggregate unemployment in the presence of labour market institutions. Using data for twenty OECD countries for the years 1961-2008, this study finds that an increase in trade leads to higher aggregate unemployment as it interacts with rigid labour market institutions, whereas it may reduce aggregate unemployment if the labour market is characterised by flexibility. In a country with the average degree of the labour market rigidities, an increase in trade has no significant effect on unemployment rates.

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Healthcare decision-makers need high quality evidence to inform policy and practice decisions. Systematic reviews of randomized controlled trials (RCTs), including meta- analyses of study effects, are considered one of the highest forms of evidence to inform such decisions. Most applications of systematic reviews and meta-analyses are based on a standardized cannon of methods that seek to collect, abstract, assess, and synthesize evidence from primary studies to produce a comprehensive and unbiased summary of the evidence. While useful, standard synthesis methods tend to assume simple data structures (e.g., two-arm comparison of a single intervention vs. a similar control evaluated in a parallel individual randomized design) and some practices (e.g., author contact) may not always be supported by empirical evidence. Complex interventions are of increasing focus in healthcare and public health and pose challenges to the standard methods of systematic review and meta-analysis. While different definitions of complex interventions have been proposed, most definitions assume: i) multiple intervention ‘components’ that may or may not interact with each other to increase or decrease observed intervention effects and ii) effect modification by study-specific characteristics (e.g., healthcare setting, patient population). At least three challenges may result from this complexity. First, reviewers will likely have to contact authors for additional information about intervention components and contextual factors that may operate as effect modifiers. Unfortunately, evidence supporting optimal strategies for achieving response from author contact is lacking. Second, complex interventions are often evaluated using a cluster randomized trial (CRT) design that randomize units of patients to different healthcare/health policy interventions. Analyses from CRTs that are not adjusted for the clustering effect are said to have unit of analysis errors, which if incorporated in meta-analyses could lead to biased summary estimates and overly precise confidence intervals (CIs). Methods for reviewers to appropriately appraise abstract evidence from CRTs are limited. Thirdly, standard meta-analyses estimate an overall effect of a singular ‘complex intervention’. Such analyses answer the question “Do complex interventions as a whole lead to a difference in observed outcomes?” and tend to exhibit high statistical heterogeneity since variation in intervention components and effect modifiers are not accounted for. Hierarchical multivariate meta-regression models have been proposed as an alternative synthesis approach for complex interventions to better account for observed heterogeneity and answer the question decision-makers are really interested in; that is “What component(s) (or combination of components) work and under what conditions?”. Hierarchical multivariate meta-regression models however have yet to be applied in the review of complex healthcare interventions. The overall aim of my doctoral research was to explore the utility of three methodological approaches to address these challenges and optimize the synthesis of complex interventions using a large systematic review of diabetes quality improvement interventions as a case study. The first objective of this thesis was to do an RCT evaluation of the effect of telephone call versus repeated email contact of non-responding authors for additional study information on response rates and research costs. We found authors contacted by telephone call were more likely to complete requests for additional information (response rate 36.7% vs. 20.2%; adjusted odds ratio 2.26 [95% CI 1.10-4.76]) but the intervention took more time to deliver in total (20 vs. 10 hours over several months vs. one month) and was more expensive overall (approximately $505 vs. $253). The second objective of this thesis was to better account for evidence from CRTs and involved a descriptive study and a methodological study. The descriptive study described the proportion of studies with unit of analysis errors and the nature of the error (inappropriate analysis versus unclear or incomplete reporting). The methodological study investigated the utility of building a database of intracluster correlation coefficients (ICCs) and use of an ICC posterior predictive distribution model to correct unit of analysis errors identified in the descriptive study. We found that although trials often adjusted for the cluster effect (67% across outcomes; range 25%-81%), most did not report enough information to extract adjusted effect estimates required for meta-analysis (an average of 77% of studies with remaining unit of analysis errors across outcomes; range 42%-100%). We were able to construct a posterior predictive distribution of the ICC for most outcomes in our review using estimates of the ICC obtained from the descriptive study combined with external estimates and use these distributions to impute missing ICCs to correct unit of analysis errors. Finally, the third objective of this thesis was to illustrate the use of hierarchical multivariate meta-regression for quantitative synthesis when estimating the effects of complex interventions and exploring effect heterogeneity. Using an arm-based analysis of post-treatment means of one continuous outcome, we demonstrated that hierarchical multivariate meta-regression models can be used to estimate a ‘response surface’ that accounts for complex intervention multiple components and study characteristics, and these models can be used to infer estimates of component effects, interactions among components, and effect modification by study covariates. Collectively the results from this thesis suggest three methodological approaches (contacting authors by telephone, imputing missing ICCs using a predictive distribution, estimating complex intervention effects using a hierarchical multivariate meta-regression) can be used to optimize the processes of synthesizing complex interventions. Further work is needed to evaluate the impact of additional study-covariates on explaining residual heterogeneity and testing these methods in other reviews of complex interventions.

The main part of this thesis is composed of three separate chapters, each using an innovative approach to analysing externalities from economic activity. The general introduction and overall conclusion sections complete the structure of the thesis. Chapter one examines the value of statistical life, an essential parameter used in ascribing monetary values to the mortality costs of air pollution in health risk analyses. This willingness to pay estimate is virtually non-existent for most developing countries. In the absence of local estimates, two major benefit transfer approaches lend themselves to the estimation of the value of statistical life: the value transfer method and the meta-regression analysis. Using Nigeria as a sample country, we find that the latter method is better tailored than the former for incorporating many characteristics that vary between study sites and policy sites into its benefit transfer application. It is therefore likely to provide more accurate value of statistical life predictions for very low-income countries. Employing the meta-regression method, we find Nigeria’s value of statistical life estimate to be $489,000. Combining this estimate with dose response functions from the epidemiological literature, it follows that if Nigeria had mitigated its 2006 particulate air pollution to the World Health Organisation standards, it could have avoided at least 58,000 premature deaths and recorded an avoided mortality related welfare loss of about $28 billion or 19 percent of the nation’s GDP for that year. The second chapter applies the quantile fixed effects technique in exploring the CO2 environmental Kuznets curve within two groups of economic development (OECD and Non-OECD countries) and six geographical regions – West, East Europe, Latin America, East Asia, West Asia and Africa. A comparison of the findings with those of the conventional fixed effects method reveals that the latter may depict a flawed summary of the prevailing income-emissions nexus depending on the conditional quantile examined. We also extend the Machado and Mata decomposition method to the Kuznets curve framework to explore the most important explanations for the carbon emissions gap between OECD and Non-OECD countries. We find a statistically significant OECD-Non-OECD emissions gap and this contracts as we ascend the emissions distribution. Also, had the Non-OECD group the incomes of the OECD group, the former would pollute 26 to 40 percent more than the latter ceteris paribus. The decomposition further reveals that there are non-income related factors working against the Non-OECD group’s greening. We tentatively conclude that deliberate and systematic mitigation of current CO2 emissions in the Non-OECD group is required. The final chapter employs the Arellano-Bond difference GMM method in investigating the oil curse in OECD and Non-OECD oil exporting countries. Empirical studies investigating the natural resource curse theory mostly employ cross-country and panel regression techniques subject to endogeneity bias. Also, most of these studies employ GDP in its aggregate or per-capita terms as the outcome variable in their analyses. However, the use of GDP measures of income for resource curse investigations does not portray the true incomes of resource intensive economies. Standard national accounts treat natural resource rents as a positive contribution to income without making a corresponding adjustment for the value of depleted natural resource stock. This treatment, inconsistent with green national accounting, leads to a positive bias in the national income computations of resource rich economies. Our paper deviates from most empirical studies in the literature by using the Arellano-Bond difference GMM method. We test the robustness of the curse in the predominantly used measures of national income, GDP, by investigating the theme in genuine income measures of economic output as well. We employ two alternative measures of resource intensity in our explorations: the share of oil rents in GDP and per-capita oil reserves. Our results provide evidence of the curse in Non-OECD countries employing aggregate and per-capita measures of genuine income. On the other hand, we find oil abundance to be a blessing rather than a curse to the OECD countries in our sample.

Cette thèse s’intéresse à l’impact des instabilités macroéconomiques sur les institutions dans les pays endéveloppement et au rôle joué par l’aide. Le rôle de l’histoire dans l’explication de ces impacts est aussiexaminé. La thèse se structure en quatre essais qui analysent l’impact des instabilités macroéconomiques, del’aide et de l’histoire sur les institutions essentiellement mesurées par des indices de démocratie et de corruption.Le premier chapitre résume la littérature sur les impacts de l’aide sur la qualité des institutions etanalyse les résultats controversés qui en ressortent. Le deuxième chapitre étudie l’impact de l’instabilitédes termes de l’échange sur la démocratie et le rôle que l’aide peut jouer dans ce contexte. Nous confirmonsl’hypothèse que l’aide peut bien avoir un impact positif sur la démocratie dans le long terme en atténuant leseffets néfastes de l’instabilité des termes de l’échange sur l’instabilité sur la croissance et ce, en rendant cettedernière plus stable. Le troisième chapitre s’intéresse à l’instabilité même de l’aide et aborde la questionde savoir si l’imprévisibilité des flux d’aide peuvent susciter ou aggraver la corruption et ainsi affaiblir lesinstitutions. Les résultats empiriques confirment cette hypothèse et montrent en plus que cet impact est plusimportant pour les pays ayant une faible qualité initiale des institutions. Le quatrième chapitre revienssur l’importance de ces conditions institutionnelles pré-Existantes pour expliquer les impacts institutionnelsde l’aide en introduisant le rôle de l’histoire et plus particulièrement le rôle des transferts institutionnels.Le chapitre conclut que la crise institutionnelle provoquée par l’échec de ces transferts explique en grandepartie les effets pervers perçus de l’aide sur la qualité des institutions. / This thesis examines the impact of macroeconomic instabilities on institutions in developing countries andthe role played by aid. The thesis further invetigates the role of history in explaining those impacts. Thethesis consists of four essays analyzing the impacts of macroinstabilities, aid and history on institutions. Thefirst chapter provides a comprehensive literature survey on the institutional impacts of aid and sheds lighton the controversial findings evidenced. The second chapter focuses on the impact of trade instability oninstitutions and the role that aid can play in this context. We provide evidence that aid can have a positiverole in democracy building in the long term by dampening the adverse effects of terms-Of-Trade instabilityon growth and thereby by making it more stable. The third chapter examines the instability of aid flowand addresses the question of whether unpredictable aid flows can create or aggravate corruption among theelites, and thereby weaken institutions. The findings from the empirical analysis provide evidence that higheraid unpredictability is associated with more rent-Seeking and corruption, this impact being more severe forthe countries having weak initial institutions. The fourth chapter investigates the extent to which thosepre-Existing institutional conditions matters for explaining the impacts of aid on institutions, by introducingthe role of history and more particularly the role of institutional transplantations. The chapter provides supportivefindings to the hypothesis that the institutional crisis caused by the unreceptive transplants largelyaccounts for aid’s impacts on the quality of institutions.

Understanding of chronic sequelae development after infection with foodborne pathogens is limited and an increased understanding could assist with the development of more accurate burden of disease estimates. The purpose of this thesis was to determine via systematic review and meta-analysis of the published international literature, the proportion of cases of Salmonella, Campylobacter and E. coli O157 that will develop the chronic sequelae of reactive arthritis, haemolytic uraemic syndrome, irritable bowel syndrome, inflammatory bowel disease or Guillain Barré syndrome. This information can be used to increase our understanding of the relationship between infection and the development of long term health complications while providing a key piece of information for the development of accurate burden of disease estimates. / Canadian Institutes of Health Research Institute of Population and Public Health/Public Health Agency of Canada, Applied Public Health Research Chair (awarded to Jan M. Sargeant)

The study is intended to identify relevant channels and possibly biasing factors with respect to fiscal multipliers, and thus to contribute to improving the precision of multiplier forecasts. This is done by, first, defining the concept of the multiplier used in the present study, presenting the main theoretical channels of influence as discussed in the literature and the problems of empirical identification. Second, by conducting a meta-regression analysis on the reported multipliers from a unique data set of 1069 multiplier observations and the respective study characteristics in order to derive quantitative stylzed facts. Third, by developing a simple multiplier model that explicitly takes into account the time elapse of the multiplier process as an explanatory factor that has been largely overlooked by the relevant theoretical literature. Fourth, by identifying, for US macroeconomic time series data, the extent to which fiscal multiplier estimates could be biased in the presence of financial cycles that have not been taken into account by the relevant empirical literature.