Climate change legislation is financially and politically costly. Financial markets have the capacity to encourage companies to do more than what is required by law (i.e. overcomply), and this could lead to socially optimal outcomes without the costs. First, I examine how the responses of Canadian companies to a voluntary survey regarding carbon emission levels affect those companies' valuations. I employ a signaling framework where companies choose between two signals - disclosure and nondisclosure - and where investors are uncertain about the likelihood of legislation in addition to company type. I test the prediction of the model that disclosure increases company value only when investors believe legislation is likely. I find that withholding emissions information resulted in average daily abnormal returns of 3 basis points, and that disclosure resulted in average daily abnormal returns of -11 basis points in the days surrounding the submission of survey responses. The level of emissions disclosed is found to be irrelevant. Second, I examine the credibility of green legislative threat. The economic climate impacts the government's ability to credibly threaten new environmental law, and so I model a company's pollution decision as a function of the economic climate. In times of recession, companies may choose to pollute heavily since they believe that the likelihood of legislation is low. As a first step in evaluating the model empirically, I use differences-in-differences regressions to estimate the effect of legislative threat during recession on company value. Although the value of carbon-intensive companies decreased initially in reaction to legislative threat, the relative value of these companies increased as the depth of the recession becomes more apparent. I find that on average the legislative threat of an emission trading scheme reduced Tobin's Q by 18% in the initial stages of the recession, but as the recession deepened the legislative threat effect was eliminated. My results suggest that financial markets combined with a credible threat of legislation could provide encouragement to companies to overcomply with current regulations, possibly to the extent that is socially optimal. More research on factors affecting company carbon emissions levels and intensity is required.

This thesis collects three papers that study applied problems in economics dealing with dynamic strategic behavior and imperfect information. In the first chapter I study the relationship between participation in United Nations Human Rights Treaties (HRT), foreign aid receipts and domestic human rights institutions. I provide empirical evidence that countries with relatively high HRT participation rates receive more foreign aid. Further, countries with high quality institutions are more likely to participate in HRTs, but that high levels of HRT participation leads to a decline in the quality of domestic human rights institutions. Based on these findings, I propose and estimate a dynamic game of HRT ratification. The estimates show that economic factors play an important role in HRT ratification and that the ratification costs countries incur vary significantly across treaties and country regime types. I use the estimated model to evaluate the effects of counterfactual policies on HRT ratification decisions, human rights behavior, and the distribution of foreign aid. The second chapter considers environmental regulation under imperfect information and political constraints. We compare the value of two types of information to a regulator: the cost of pollution and the profitability of firms in the economy. We find that in environments where small increases in the losses to regulated firms greatly affect the regulator's ability to implement the policy, it is most valuable to learn the types of firms, while it is most valuable to learn the cost of pollution when small increases in losses are relatively ineffectual. The third chapter deals with the identification and estimation of dynamic games when players maximize expected payoffs given beliefs about other players' actions, but their beliefs may not be in equilibrium. First, we derive conditions for point-identification of structural parameters and players' beliefs, and propose a simple two-step estimation method and sequential generalization of the method that improves its asymptotic and finite sample properties. We also present a procedure for testing the null hypothesis of equilibrium beliefs. Finally, we illustrate our model and methods with an application of a dynamic game of store location by retail chains.

Climate change legislation is financially and politically costly. Financial markets have the capacity to encourage companies to do more than what is required by law (i.e. overcomply), and this could lead to socially optimal outcomes without the costs. First, I examine how the responses of Canadian companies to a voluntary survey regarding carbon emission levels affect those companies' valuations. I employ a signaling framework where companies choose between two signals - disclosure and nondisclosure - and where investors are uncertain about the likelihood of legislation in addition to company type. I test the prediction of the model that disclosure increases company value only when investors believe legislation is likely. I find that withholding emissions information resulted in average daily abnormal returns of 3 basis points, and that disclosure resulted in average daily abnormal returns of -11 basis points in the days surrounding the submission of survey responses. The level of emissions disclosed is found to be irrelevant. Second, I examine the credibility of green legislative threat. The economic climate impacts the government's ability to credibly threaten new environmental law, and so I model a company's pollution decision as a function of the economic climate. In times of recession, companies may choose to pollute heavily since they believe that the likelihood of legislation is low. As a first step in evaluating the model empirically, I use differences-in-differences regressions to estimate the effect of legislative threat during recession on company value. Although the value of carbon-intensive companies decreased initially in reaction to legislative threat, the relative value of these companies increased as the depth of the recession becomes more apparent. I find that on average the legislative threat of an emission trading scheme reduced Tobin's Q by 18% in the initial stages of the recession, but as the recession deepened the legislative threat effect was eliminated. My results suggest that financial markets combined with a credible threat of legislation could provide encouragement to companies to overcomply with current regulations, possibly to the extent that is socially optimal. More research on factors affecting company carbon emissions levels and intensity is required.

This thesis collects three papers that study applied problems in economics dealing with dynamic strategic behavior and imperfect information. In the first chapter I study the relationship between participation in United Nations Human Rights Treaties (HRT), foreign aid receipts and domestic human rights institutions. I provide empirical evidence that countries with relatively high HRT participation rates receive more foreign aid. Further, countries with high quality institutions are more likely to participate in HRTs, but that high levels of HRT participation leads to a decline in the quality of domestic human rights institutions. Based on these findings, I propose and estimate a dynamic game of HRT ratification. The estimates show that economic factors play an important role in HRT ratification and that the ratification costs countries incur vary significantly across treaties and country regime types. I use the estimated model to evaluate the effects of counterfactual policies on HRT ratification decisions, human rights behavior, and the distribution of foreign aid. The second chapter considers environmental regulation under imperfect information and political constraints. We compare the value of two types of information to a regulator: the cost of pollution and the profitability of firms in the economy. We find that in environments where small increases in the losses to regulated firms greatly affect the regulator's ability to implement the policy, it is most valuable to learn the types of firms, while it is most valuable to learn the cost of pollution when small increases in losses are relatively ineffectual. The third chapter deals with the identification and estimation of dynamic games when players maximize expected payoffs given beliefs about other players' actions, but their beliefs may not be in equilibrium. First, we derive conditions for point-identification of structural parameters and players' beliefs, and propose a simple two-step estimation method and sequential generalization of the method that improves its asymptotic and finite sample properties. We also present a procedure for testing the null hypothesis of equilibrium beliefs. Finally, we illustrate our model and methods with an application of a dynamic game of store location by retail chains.

Doctor of Philosophy / Department of Economics / Lance Bachmeier / Steven Cassou / This dissertation consists of three essays in macroeconomic econometrics. The first essay investigates industry level production functions. Part of the interest in doing this is to contribute to the ongoing improvements in dynamic macroeconomic models which are increasingly disaggregating economies into industrial sectors. This paper provides useful production function parameter values for this endeavour. In addition, the paper shows that there are differences across industry level production functions, so model disaggregation cannot rely on a generic scaled down aggregate production function. Futhermore, evidence of these differences is provided in several ways. First, it is shown that some, but not all, industry level production functions exhibit constant returns to scale. Second, conducted pairwise tests show whether government capital production elasticities are the same for different pairs of industries. In the majority of these tests, the null hypothesis was rejected. In the second essay, the relevance of wage rigidities for understanding the effect of oil price shocks on output and inflation is examined. The theoretical framework of Blanchard and Gali (2007) is adopted and modified in two important ways. First, an empirically estimated wage adjustment cost function is incorporated following work by Kim and Ruge-Murcia (2009). Second, a realistic monetary policy function is incorporated into the model to be consistent with the current macroeconomic literature. The paper provides evidence that the degree of wage stickiness has little effect on the oil price-macroeconomy relationship. We find that the only way to generate large changes in the variances of output and inflation is to increase the wage adjustment cost by an extreme amount. The third essay assesses the statistical adequacy of the Cobb-Douglas aggregate production function with public capital as an input. The paper tests the statistical adequacy of the models proposed by Aschauer (1989a) and Tatom (1991) and finds that both models are misspecified. Furthermore, the paper finds that Tatom's model suffers from the same criticism he levels against Aschauer's model, non-stationarity in the data series used to estimate the model. Using Aschauer's framework, a properly specified model is found that models both deterministic heterogeneity and serial autocoreelation. Model results find that public capital is positive and significant. The results are in contrast to a large body of literature that discredits Aschauer's findings claiming his model is incorrect. Finally, an additional specification of the model using the student's t linear regression model is explored to capture potential heteroskedasticity.

Doctor of Philosophy / Department of Economics / Lance Bachmeier / Yang-Ming Chang / This dissertation comprises of three essays in international macroeconomics. The first essay investigates the competition between two city states, both of which will stand in place of countries in the global scheme. Under the framework of the three-stages-game, we assume that there are two cities competing for dominance over two sectors: the manufacturing sector and the financial sector. In addition, the government of each city state can build infrastructure to increase the competitiveness of the financial and distributive firms of its city. Under this framework, we are able to show that the amount of resources, the start-up costs of providing services, and the relative effectiveness of their infrastructures determine the optimal amounts of infrastructures the cities decide to build, and thus also decide the equilibrium outcome of this game. In my second essay, we examine the relationship between income distribution and import patterns. The Linder hypothesis states that countries with similar economic characteristics should trade more often. However, although the total volumes of trade between these countries are similar, the traded goods may be different. This paper investigates the trading patterns of countries with similar characteristics. Specifically, we analyze the relationship between the import patterns and income distributions of importers. We develop an import similarity index to portray the composition of imports and utilize the idea of a "market overlap," a theoretical concept proposed by Bohman and Nilsson (2007), to represent the similarity of income distributions across different importing countries. We provide empirical evidence to support the notion that countries with similar income distributions display similar import patterns. We also separate countries by income level and find that income distribution exerts a positive impact on the similarity of import patterns for all but low income countries. Finally, we incorporate the characteristics of goods into our analysis and show that the positive relationship between income distributions and import patterns holds for differentiated and reference-priced goods, but not for homogeneous goods. In my final essay, we look into another aspect of international literature: the exchange rate. In the literature, we find that vector autoregressive (VAR) models and impulse response analyses are common tools to study the relationship between monetary policy and exchange rate movements. Therefore, it is important to investigate the accuracy of the VAR model. In the first part of this essay, we assume that the true, underlying, data-generating process is hump-shaped, which is the shape of the impulse response of exchange rate to a monetary policy shock. We show that results estimated from any VAR models applying AIC as their lags selection are biased. We also introduce two possible solutions to remedy this bias: the use of more lags in the VAR models or the use of the proposed loss functions estimations. These results suggest we should be cautious when interpreting empirical evidences on international literature. In the second part of the same essay, we investigate another issue that is closely related to the exchange rate and the VAR model. Under the estimation of the VAR model, the researcher implicitly assumes that the objective loss function is quadratic. However, it is a well accepted fact that monetary authority adjusts the interest rate according to policy. One of the objectives of the monetary authority is to influence the exchange rate in their favor. They estimate the size of the loss caused by deviations from the current exchange rate to the rate they desire, and then they adjust the amount of money in the international market. We propose an asymmetric loss function that monetary authorities may use to estimate the impulse response of the exchange rate to a contractionary monetary policy shock. We then compare these estimated impulse response functions to those estimated by the VAR. We find that while both of these estimated impulse response functions share the same sign, the magnitude and the duration of the shock are quite different. These results suggest that the VAR model may not be appropriate in estimating the exchange rate movement.

This thesis consists of three essays in empirical finance and macroeconomics. The first essay proposes a new structural-break vector autoregressive model for predicting real output growth by the nominal yield curve. The model allows for the possibility of both in-sample and out-of-sample breaks in parameter values and uses information in historical regimes to make inference on out-of-sample breaks. A Bayesian estimation and forecasting procedure is developed which accounts for the uncertainty of both structural breaks and model parameters. I discuss dynamic consistency when forecasting recursively and provide a solution. Applied to monthly US data, I find strong evidence of breaks in the predictive relation between the yield curve and output growth. Incorporating the possibility of structural breaks improves out-of-sample forecasts of output growth. The second essay proposes a sequential Monte Carlo method for estimating GARCH models subject to an unknown number of structural breaks. We use particle filtering techniques that allow for fast and efficient updates of posterior quantities and forecasts in real-time. The method conveniently deals with the path dependence problem that arises in these type of models. The performance of the method is shown to work well using simulated data. Applied to daily NASDAQ returns, we find strong evidence of structural breaks in the long-run variance of returns. Models with flexible return distributions such as t-innovations or with jumps indicate fewer breaks than models with normal return innovations and are favored by the data. The third essay proposes a new tilt stochastic volatility model which extends the existing volatility models by modeling the asymmetric correlation between return and volatility innovations in a unified and flexible framework. The Efficient Importance Sampling (EIS) procedure is adapted to estimate the model. Simulation studies show that the Maximum Likelihood (ML)-EIS estimation of the model is accurate. The new model is applied to the CRSP daily returns. I find the extensions are significant and incorporating them improves the accuracy of volatility estimates.

This thesis develops new hidden Markov models and applies them to financial market and macroeconomic time series. Chapter 1 proposes a probabilistic model of the return distribution with rich and heterogeneous intra-regime dynamics. It focuses on the characteristics and dynamics of bear market rallies and bull market corrections, including, for example, the probability of transition from a bear market rally into a bull market versus back to the primary bear state. A Bayesian estimation approach accounts for parameter and regime uncertainty and provides probability statements regarding future regimes and returns. A Value-at-Risk example illustrates the economic value of our approach. Chapter 2 develops a new efficient approach to model and forecast time series data with an unknown number of change-points. The key is assuming a conjugate prior for the time-varying parameters which characterize each regime and treating the regime duration as a state variable. Conditional on this prior and the time-invariant parameters, the predictive density and the posterior of the change-points have closed forms. The conjugate prior is further modeled as hierarchical to exploit the information across regimes. This framework allows breaks in the variance, the regression coefficients or both. In addition to the time-invariant structural change probability, one extension assumes the regime duration has a Poisson distribution. A new Markov Chain Monte Carlo sampler draws the parameters from the posterior distribution efficiently. The model is applied to Canadian inflation time series. Chapter 3 proposes an infinite dimension Markov switching model to accommodate regime switching and structural break dynamics or a combination of both in a Bayesian framework. Two parallel hierarchical structures, one governing the transition probabilities and another governing the parameters of the conditional data density, keep the model parsimonious and improve forecasts. This nonparametric approach allows for regime persistence and estimates the number of states automatically. A global identification algorithm for structural changes versus regime switching is presented. Applications to U.S. real interest rates and inflation compare the new model to existing parametric alternatives. Besides identifying episodes of regime switching and structural breaks, the hierarchical distribution governing the parameters of the conditional data density provides significant gains to forecasting precision.

This dissertation studies three important questions in international political economy: The long run consequences of social divisions created by historical colonialism, the importance of trade shocks in shifting political power balances and shaping institutional development and the influence that major political powers have over the decisions of smaller nations. I study these three questions empirically in four papers that span three distinct regions and time periods. The first paper asks whether the large differences in economic development across Native American reservations today can be explained by social divisions that were created more than 150 years ago when the US government forcibly integrated distinct Native American bands into shared reservations, condemning them to a system of shared governance that was not consistent with their political traditions and tribal identities. The second and third papers study the effect of the first globalization on the political and economic equilibrium in seventeen 19th century British Caribbean plantation colonies. I use this set of highly comparable but in precise ways distinct islands as a laboratory to study the effect of globalization on the long run development of representative institutions and on the coerciveness of labour markets at the time. The first of two papers provides insights into the working of colonial institutions and traces the mechanisms through which the planter elite managed to maintain a monopoly over policy making and retard long run development. The second paper highlights the importance that exogenous output price changes had for the willingness of planter elites to engage in costly coercion that distorted labour markets in their favour. In the final paper I test whether major aid donors use foreign aid to buy the votes of developing countries. Taking advantage of a unique long-running dispute between major donors in the International Whaling Commission, I am able to address the three major empirical challenges in answering this question: that aid moves much slower than voting behaviour, that alliances constantly change with issues and that most international organizations vote frequently and on a range of issues while data on aid disbursals is available only in yearly aggregates.

This thesis consists of three chapters in Bayesian financial econometrics. The first chapter proposes new dynamic component models of returns and realized covariance (RCOV) matrices based on timevarying Wishart distributions. Bayesian estimation and model comparison is conducted with a range of multivariate GARCH models and existing RCOV models from the literature. The main method of model comparison consists of a term-structure of density forecasts of returns for multiple forecast horizons. The new joint return-RCOV models provide superior density forecasts for returns from forecast horizons of 1 day to 3 months ahead as well as improved point forecasts for realized covariances. Global minimum variance portfolio selection is improved for forecast horizons up to 3 weeks out. The second chapter proposes a full Bayesian nonparametric procedure to investigate the predictive power of exchange rates on commodity prices for 3 commodity-exporting countries: Canada, Australia and New Zealand. I examine the predictive effect of exchange rates on the entire distribution of commodity prices and how this effect changes over time. A time-dependent infinite mixture of normal linear regression model is proposed for the conditional distribution of the commodity price index. The mixing weights of the mixture follow a Probit stick-breaking prior and are hence time-varying. As a result, I allow the conditional distribution of the commodity price index given exchange rates to change over time nonparametrically. The empirical study shows some new results on the predictive power of exchange rates on commodity prices. The third chapter proposes a flexible way of modeling heterogeneous breakdowns in the volatility dynamics of multivariate financial time series within the framework of MGARCH models. During periods of normal market activities, volatility dynamics are modeled by a MGARCH specification. I refer to any significant temporary deviation of the conditional covariance matrix from its implied GARCH dynamics as a covariance breakdown, which is captured through a stochastic component that allows for changes in the whole conditional covariance matrix. Bayesian inference is used and I propose an efficient posterior sampling procedure. Empirical studies show the model can capture complex and erratic temporary structural change in the volatility dynamics.