ItemThree Essays on Procurement AuctionsEconomics; Clark, RobertThis thesis is an empirical study of procurement auctions. First, I explore how varying the timing of a sequence of auctions affects both bidder behaviour and the welfare of procurers and bidders. We develop a structural auction model with endogenous participation in which bidding may be simultaneous or sequential. Bidders perceive auctioned objects as either complements or substitutes. We apply this model to auctions for roof-maintenance projects in Montreal. We show that complementarities account for as much as 17\% of the total size of contract combinations. We develop an algorithm to search a schedule of auctions and show that the total cost of projects can be reduced by over 8\%. I also study the effect of corruption on outcomes of procurement auctions. I define corruption as any illegal behaviour used by firms to lower their costs. In Quebec, firms that are found to be involved in corruption are not allowed to bid in procurement auctions for a period of five years and added to a list. I consider the outcome of auctions in markets where firms on that list were active. Bids by corrupt firms are lower than bids by clean firms and corrupt firms are more likely to win auctions in which they participate. The behaviour of clean firms adjust as they interact with corrupt firms. Costs of corrupt firms recovered through structural estimation are shifted down by around 4.1\% relative to clean firms. Only half of this advantage is reflected in their bids. Finally, I run a case study of corruption in procurement auctions. The English Montreal School Board (EMSB) was placed under trusteeship by the government of Quebec in November 2019, following underreporting of contracts that the EMSB was legally required to report. Using public data, I confirm underreporting in the period that precedes the trusteeship and I find that the value of contracts reported by the EMSB after the trusteeship is in line with that of other school boards. Using a Difference-in-difference approach, I confirm that the underreporting disappears as the trusteeship begins. Simulations show damages of around \$16 millions between 2009 and 2015. ItemEssays on International Trade and Financial EconomicsNoel, Antoine; Economics; Sun, Amy HongfeiThis dissertation examines two important aspects of economics: international trade and financial economics. In the part of the thesis which focuses on international trade, I analyze the impact of preferential trade agreements in boosting global trade liberalization. I find that permitting countries to sign preferential trade agreements fails to reduce global tariffs when countries only differ in their levels of production structure. Regarding financial economics, we provide an exact algorithm for efficient computation of models that have an ARCH(?) representation, a technique often used to estimate the volatility of exchange rates. Finally, we develop a model for analysis of information transparency of optimal financial contracts. In Chapter 2, I examine the effects of differences in production structure across countries on the liberalization of global tariffs in the coalition-proof Nash equilibrium sense. Using a static tariff-setting game with endogenous trade agreements, I develop a competing exporters model with three countries and consider three settings that are differentiated by the type of trade agreements that countries can sign: free trade agreements, customs unions, and trade agreements that comply with the most-favour-nation (MFN) clause, i.e. MFN trade agreements. Using two analytical exercises involving symmetric and asymmetric changes in production structure, I find that preferential trade agreements incentivize countries to have higher global tariffs than if they could not sign such agreements, for sufficiently large differences in production structure. Chapter 3 provides an exact algorithm for efficient computation of the time series of conditional variances of models that have an ARCH(?) representation. The efficiency of the algorithm allows estimation of ARCH(?) models, even with very large data sets and without the truncation of the filter commonly applied in the literature. This reduces the bias of the quasi-maximum-likelihood estimators and improves out-of-sample forecasting. Chapter 4 proposes a theory on information transparency of optimal financial contracts. Our model nests adverse selection and agency costs. We demonstrate that there exists a unique perfect Bayesian equilibrium with novel features. First, three types of optimal contracts can arise endogenously: equity, transparent debt, and opaque debt. The former two require firms to take on a costly verification technology while opaque debt does not. Second, the unique equilibrium is either pooling on opaque debt, or mixing with transparent and opaque financing. Third, firms with sufficiently high quality and intermediate levels of internal funds find it optimal to use a transparent contract. ItemLong-Range Dependence in Stationary Gaussian Time Series: An Application to Stock Trading Volume and Realized VolatilityArango Castillo, Lenin; Economics; Takahara, Glen K.In this thesis, we examine pure and mixed-spectra Gaussian long-range dependent time series. In chapter 2, we introduce background material that is used in subsequent chapters. In chapter 3, we propose a method to robustly estimate the variance of the sample mean for two Gaussian processes exhibiting long-range dependence (LRD): fractional Gaussian noise, fGn(H), and fractional integrated noise with Gaussian innovations, GFI(H). An important feature of the proposed method is a test statistic to differentiate between fGn(H) and GFI(H), which, under a correct decision, allows us to estimate the Hurst parameter H using the correct model specification. Theoretical properties of the test statistic are derived and numerical comparisons against existing estimators are presented. In chapter 4, we study time series characterized by hidden periodic components buried in stationary noise. We propose an approach to the problem of estimating H in processes with mixed spectra in the context of two Gaussian LRD processes: fGn(H) and GFI(H). We apply the method to synthetic periodic time series, and we show numerical results. We also examine a real data case on air quality indices based on particulate matter data from the United States and we show the effect of hidden periodic components on the estimation of H using the method. Lastly, in chapter 5, we use stock trading volume and stock realized volatility time series to illustrate the methods in chapters 3 and 4. We show the presence of hidden periodic components and, using the test statistic in chapter 3, we propose a modelling approach. ItemWealth Concentration, Entrepreneurial Activity and Firms' Market Power: Theory, Evidence and MethodsBrien, Samuel; Economics; Abbott, Brant; Orregaard Nielsen, MortenThis dissertation examines the effect of household wealth concentration on entrepreneurial activity and firms’ market power and presents methods developed to support the empirical investigation. Both theoretical and empirical evidence suggest that an increase in wealth concentration is associated with a future rise in firms’ market power and that entrepreneurial firm creation may play a significant role in the relationship between household wealth distribution and firms’ market power. A step-by-step model of endogenous innovation and growth is developed in Chapter 2, in which firm entry is driven by entrepreneurial activity conducted by ex-ante identical households who differ only in their wealth. This general equilibrium model generates an endogenous wealth distribution and an endogenous measure of firms’ markups. Under the calibrated benchmark, an increase in wealth concentration yields a decrease in firm entry and an increase in firms’ market power. It is found that a small redistributive wealth tax is slightly growth-enhancing as it reduces firms’ market power by stimulating firm entry and business competitiveness. In Chapter 3, the relationship between wealth concentration, firm entry, and firms’ markups is investigated empirically using panel data for three OECD countries. A panel VAR is estimated by applying an iterated bootstrap bias-correction method to the least square dummy variable estimator. It is found that positive shocks in wealth concentration are significantly associated with future increases in aggregate markup via firm entry. A new impulse response decomposition method is used to quantify the contribution of the firm entry channel in the relationship between wealth concentration and markup. Chapter 4 features a new unit root test based on the unconditional likelihood ratio for autoregressive processes of arbitrary order. The test is nearly efficient in the sense that its asymptotic local power function is indistinguishable from the Gaussian envelope and that its power and size properties compare advantageously to other nearly efficient tests. The challenge posed by nuisance parameters in the higher-order autoregressive model is only now being tackled successfully to offer a proof for the distribution of the test statistic based on the fully maximized likelihood ratio where previous work relied on a plug-in approach instead. ItemEvaluating Education: An Economic Analysis of Education in Rural ZimbabweNordstrom, Ardyn; Economics; Cotton, ChristopherThis thesis uses a combination of innovative and existing evaluation techniques to understand the barriers to education in rural Zimbabwe, and to determine the impact of interventions that targeted some of these barriers. Chapter 2 uses a randomized controlled trial combined with text mining analysis of qualitative interviews to demonstrate the impact of a large-scale community mobilization campaign. After three and a half years of exposure to the community mobilization campaigns, community attitudes towards girls' education improved by 0.56 SD, and struggling students performed 0.28 SD better on learning assessments. Using mediation analysis, I show that the increased support likely partially mediated the program's impact on education. Chapter 3 exploits variation from a natural experiment to determine the impact of a severe drought on girls' education outcomes. I show that the drought decreased the opportunity cost of education, leading to an increase in enrolment. However, this did not correspond with an increase in learning, with students from particularly vulnerable households performing worse on learning assessments after the drought. Chapter 4 provides a descriptive analysis of the most important factors associated with education outcomes. By using multiple machine learning methods, I show that lack of support and pregnancy are the biggest barriers to student advancement. These are also barriers to student learning, however, other factors such as self-confidence were relatively more important for learning outcomes. These findings describe the programmatic contributions of this thesis, which provides important insights into the types of barriers students experience, as well the effectiveness of specific education interventions. The second contribution is more methodological, where I show how natural language processing and machine learning methods can be used in future evaluation research.