Economics

Permanent URI for this collection

https://hdl.handle.net/10315/28604

Browse

Now showing 1 - 20 of 33

Open Access
Canadian Gender Wage Gap
(2023-12-08) Zhu, Shengyi; Sand, Benjamin M.
This dissertation provides a comprehensive analysis of the Canadian gender wage gap over the past two decades, employing modern methodologies and tools. In the first chapter, selection bias and its impact on the entire earning distribution are examined. A selection-corrected quantile regression is utilized to provide a more accurate depiction of the gender wage gap distribution. The simulation of potential government child care benefits as an instrument helps address the selection bias issue. Findings reveal the persistent but inconsistent effects of selection bias across wage quantiles and time. The presence of negative selection for women entering the workforce is identified, and the absence of this bias would result in an even higher unexplained portion of the gender wage gap. Moving to the second chapter, a thorough investigation of the heterogeneity of the gender wage gap is conducted. High-dimensional models are employed to explore the diverse factors contributing to the wage gap. Advanced machine learning algorithms are utilized as robustness checks to address possible multicollinearity problems. The analysis reveals significant reductions in the gender wage gap attributed to age and several occupations, while penalties related to family structure persist. Finally, the third chapter explores the under-researched area of job-education mismatch and its impact on the gender wage gap. The study focuses on the differences in vertical and horizontal matching between women and men. Self-reported measurements of both vertical and horizontal mismatch, as well as an objective index of horizontal mismatch, are utilized. Results indicate that, unlike other countries, vertical mismatch does not contribute significantly to the gender wage gap. Furthermore, the role of horizontal mismatch is economically insignificant in relation to the overall gap. This dissertation enhances our understanding of the Canadian gender wage gap by addressing important aspects such as selection bias, heterogeneity, and job-education mismatch. The findings contribute to the existing literature on gender inequality, offering valuable insights for policy interventions and future research in this field.
Open Access
An Analysis of the Impact of Governments Policies on Economic Activities
(2023-12-08) Bi, Zifan; Stoyanov, Andrey
This PhD dissertation explores the intersection of international trade, empirical microeconomics, and public economics. In each chapter of the dissertation, I investigate the impact of free trade agreements (FTAs), preferential tariffs under the Generalized System of Preferences (GSP), and government regulations on local labor markets, respectively. In the first chapter, the study examines the effects of FTAs on members’ incentives to participate in multilateral trade liberalization. By addressing endogeneity issues and considering the parallel existence of multiple FTAs, the research provides robust evidence that FTA formation leads to a reduction in external tariffs towards nonmembers, shedding light on the role of FTAs in accelerating global free trade. The second chapter focuses on understanding the factors underlying countries’ choices of preferential tariffs towards developing countries under the GSP. A theoretical model is constructed to capture the donor countries’ consideration of the economic interests of recipient countries. The findings demonstrate that donors partially internalize the effect of GSP tariffs on profits of firms from developing countries, indicating their concern for the welfare of recipient countries. However, evidence for such considerations among the least developed countries is limited. In the third chapter, the study analyzes the impact of government regulations on local labor markets, with a specific focus on the United States. Using innovative quantification methods, the research confirms the cost of regulations and their adverse effects on local employment and income equality. Furthermore, the analysis highlights the influence of political party affiliation, showing that regulations under Republican governments tend to attenuate the negative impacts on employment and income equity compared to regulations under Democratic governments.
Open Access
To Sin or Not to Sin: Studying Socio-Economic Impacts of Religious Agents Choices
(2023-08-04) Neleptchenko, Yulia; Smith, J Barry
This thesis investigates behavioral aspects of religious agents decision making when they believe to be punished for wrongdoing in the afterlife. In the thesis, a novel theoretical framework explaining the choices of sinning/non-sinning to be introduced, alongside with an empirical examination of a major religious event's impacts on observed behaviors of the faithful. The theoretical framework targets to identify the circumstances under which agents optimally choose to sin. It aims to discover how the limitations of alternative resources can bound their choices and help rationalize sinning behaviors. A formal model of such preferences would explain the abundance of vice practices observed. The theory proposed belongs to the dual-self models of principal-agent class and offers a new approach to solving problems arising in a complex personality. In my model, the tool kit of the religious planner is expanded to include an alternative consumption of goods and leisure as self-control resources. This resources are limited by the initial endowments. The solutions of the model are first-best, fully parametrized and corner, while all choices, of sinning and non-sinning, are rationalized as a function of the parameters. The empirical part of the thesis focuses on a major Catholic event that grants full remission of sins to Catholics. The research question in this part is: How does the forgiveness obtained change the sinning patterns of Catholics? In other words, the question is whether more, less or equal amount of crimes will be committed in the time-proximity to the event occurrence. The study to be conducted via two channels. The first path is to examine historical Italian time series data on crimes for a period during which a few events were held. The second route is to perform a conditional analysis on a longitudinal data set on European countries criminal activities count, recorded around the Great Jubilee of 2000 event celebration. The results of the empirical study on the event's impacts on crimes levels show that Catholics committed less crimes during the event celebration. In Italy, where a number of Jubilees were celebrated, a particularly interesting pattern of crimes behavior around the event occurred.
Open Access
Modelling Comovements of Selected Large Cap Cryptocurrencies: A Semi-Parametric Noncausal VAR Approach
(2023-08-04) Hall, Mauri Kemersley Rutten; Jasiak, Joann
This dissertation focuses on multivariate mixed causal noncausal models and their application to cryptocurrencies. The empirical application considered in the dissertation focuses on detecting comovements in the US dollar exchange rates of four prominent cryptocurrencies as well as on forecasting for multivariate mixed causal noncausal models. The dissertation explores forecasting methods which can be used when modelling data as mixed causal noncausal multivariate processes. The dissertation is divided into three chapters. Chapter one is dedicated to the detection of comovements in four prominent cryptocurrency US dollar exchange rates by modelling the exchange rates as mixed causal noncausal processes. The cryptocurrency pairs Bitcoin/Ethereum and Ripple/Stellar are modelled as bivariate mixed causal noncausal processes and then estimated as a single mixed causal noncausal multivariate time series model of dimension four. Chapter two contains forecasting methods and applications to the cryptocurrencies estimated in chapter one. Nonparametric predictive densities are calculated and a new linear approximation method is introduced and used to calculate one step ahead out of sample forecasts using a mixed causal noncausal vector autoregressive model estimated via the GCov estimator. Chapter three extends theory for forecasting multivariate mixed causal noncausal processes. Theory pertaining to the calculation of predictive densities for mixed causal noncausal vector autoregressive models with three lags using the latent causal and noncausal components of the process is discussed. Theory pertaining to the calculation of predictive densities for causal noncausal vector autoregressive models with high dimensional data is also discussed. Two experiments are conducted via simulation study. Firstly the coverage of the predictive density forecasting method is investigated. Secondly the predictive density forecasting method is compared with the linear approximation forecasting method in terms of their respective Mean Squared Errors.
Open Access
Essays on Human Capital Development, International Trade and Robotization
(2022-12-14) Chowdhury, Mahin Farjana; Stoyanov, Andrey
This dissertation consists of three related essays on trade, industrial robots and human capital. In Chapter 1, we investigate the importance of a country’s exports and imports for human capital development. In order to analyze this relationship, measures of the educational intensity of exports and imports are developed for a sample of 137 countries from 1962 to 2010. We find that the educational intensity of exports has a positive and statistically significant impact on human capital development while the educational intensity of imports has a negative and statistically significant impact on educational attainment. In Chapter 2, we investigate the importance of regional exports and imports of the U.S. for human capital development. In order to analyze this relationship, measures of the educational intensity of exports and imports are developed for a sample of commuting zones (CZs) from a single country (U.S.) for a study period from 1980 to 2010. We find that the educational intensity of exports has a positive and statistically significant impact on human capital development. On the other hand, the educational intensity of imports, as a whole, has a positive but insignificant effect on educational attainment but educationally-intensive imported intermediate inputs, when separated out, have a positive and significant effect on human capital development. In Chapter 3, we study the effect of robot adoption exposure in the labor market to identify the effect of technological-induced changes on educational attainment in the U.S. from 1993 to 2007. A closer look is taken by looking at educational attainment for the overall sample (ages 15 to 65), age group, educational share, and gender. We document exposure to robots having a positive impact on the educational attainment of middle-age groups across U.S. commuting zones, providing indication that the opportunity cost of schooling is less for middle-aged groups. We find a significant and positive relationship between robot adoption and an increase in educational level of those with a high school education but not a college degree. We did not find any significant relationship for the overall sample (ages 15 to 65) and gender with robot adoption.
Open Access
Climate Change, Structural Change and Innovation
(2022-12-14) Kim, HyungJu; Adamopoulos, Anastasios T.
In this dissertation, I study the sources of economic growth and structural transformation by combining a quantitative framework with micro data. As the main theme of the dissertation, I focus on the impact of climate change on the agricultural sector of developing countries and spatially analyze its impact on the agricultural productivity and long-run distribution of farming activity. Then, I move onto the non-agricultural sector of a developed country by analyzing the source of economic growth through product innovation. In chapter 1, I study the impact of climate change on farm size and agricultural productivity in developing countries. I combine pixel-level climate data from the Global Agro-Ecological Zones (GAEZ) project with rich household-level data on agricultural production from the World Bank’s LSMS for Uganda. I assess the implications of anticipated climate change on aggregate productivity through the lens of a two-sector model with endogenous farm size and crop choice, featuring heterogeneity in both land quality and farmer ability. In chapter 2, I study the interaction of climate change with transport frictions to determine the long-run distribution of farming activity in Ethiopia. I assess the implications of anticipated climate change through the lens of a spatial model featuring locational heterogeneity in land quality, transportation costs, and agricultural production, by incorporating a quantitative spatial framework to rich micro-data combined from different sources. I calibrate the model to the benchmark economy with baseline (1961-1990) geographical conditions, then change geographical conditions alone to the future level (year 2050). Where does the product innovation come from? From entering plants or incumbents? From existing products or brand new products? In chapter 3, I answer these questions by quantifying the sources of innovation in South Korea over the years 2001-2011. To account for the sources of innovation, I combine unique Korean data on the universe of non-farm private sector establishments and the growth framework of Garcia-Macia, Hsieh, and Klenow, which infers the sources of innovation from job creation and job reallocation flows among incumbent and entrant firms.
Open Access
The Predictive Power of Behavioral Economics in the Foreign Exchange Market
(2022-08-08) Mahdiyan Amirabadi, Vajiheh; Smith, J Barry
This dissertation explores the out-of-sample forecastability of changes in exchange rates using behavioral economics and combination methods and contributes to the literature by introducing three approaches presented in three essays. The first essay explores a new approach through behavioral heuristics to forecast changes in exchange rates. One key aspect of behavioral economics is that people do not use the realized distribution of historical data to predict variables. Instead, agents assign subjective probabilities which depend on heuristics in decision-making. These subjective probabilities are used as weights for the ten years of observations prior to time t in linear models of changes in exchange rates to estimate coefficients and form forecasts. This essay develops forecasting models for exchange rates using monthly data for the US dollar versus 37 (advanced and emerging/developing) currencies. The second essay incorporates behavioral economics by adding investor sentiment variables to macroeconomic models to form forecasts for exchange rates. In addition, I examine the predictive ability of a terms of trade index (in changes) both as a single predictor and as an added predictor in the uncovered interest rate parity model. Finally, I examine changes in commodity and oil prices (nominal and real) as predictors of changes in exchange rates. Some models provide promising results for some currencies using Pesaran-Timmermann (PT) statistics in both essays. In the first essay, models under the assumptions of anchoring-toward and optimism perform well. In the second essay, macroeconomic models augmented by behavioral factors outperform the White Noise (WN) model for several countries. The third essay of the dissertation addresses model uncertainty. It focuses on combining forecasts from various individual models introduced in the second essay. I use standard (e.g., equal weights) and new forecast combination approaches to form combined forecasts. Using a regularization technique (Ridge regression), I apply linear and convex combination estimates to combine forecasts. I propose Directional Prediction as a new weighting approach. The results indicate that for several countries, the linear combination (Ridge regression) weighting approach has proportions of correct direction of changes in exchange rates greater than 0.5, which means it performs better than the WN model.
Open Access
Investor Behavior and Stock Returns
(2022-03-03) Rahman, Oriana; Semenov, Andrei
Theoretical and empirical studies usually assume that agents are all rational thinkers in making decisions. Experimental evidence is, however, that human judgments are not always rational, and people make systematic mental mistakes by using some intuitive simplifying rules and shortcuts, rather than strict logic to make choices. Judgment errors can lead to decisions that differ from those that would be made by rational agents. These shortcuts are also known as "behavioural heuristics". This thesis contributes to the existing literature by exploring the influence of behavioural heuristics on the first four moments of the stock return distribution. It is comprised of three research papers. In the first two research papers, behavioural heuristics are accounted for through the subjective probabilities that an investor assigns to future stock returns. The third paper uses a different approach to recognize the investor's irrationality. It incorporates different behavioural heuristics through various behavioural factors that describe investors' biased investment decisions during extreme market conditions. The first paper "Investor Behaviour and the Predictability of Stock Returns" (coauthored with A. Semenov) examines the implications of behavioural heuristics for the ability of past returns to predict future returns on individual stocks. We find empirical evidence that assuming investor's rationality, one may substantially understate (overstate) the predictability of the next period stock return when the next period volatility of returns is higher (lower) than the historical volatility. The second paper "Behavioural Value-at-Risk" explores whether behavioural heuristics have the power to explain the volatility of stock returns. We find strong evidence that availability heuristic together with either optimism or overconfidence provides a more accurate forecast of the portfolio VaR compared with the conventional historical simulation and weighted historical simulation approaches. Finally, the third paper "Higher-Order Return Moments under Irrational Behaviour" (coauthored with A. Semenov) explores whether investors' irrational behaviour through various behavioural factors influences the third (skewness) and fourth (kurtosis) moments of the stock return distribution. Empirical evidence demonstrates that the asymmetric distribution of stock returns due to the existence of negative skewness and excess kurtosis can be explained by the investors' overreaction to price signal, herding intensity, and momentum return.
Open Access
Essays in determinants of comparative advantage and welfare implications of trade wars
(2022-03-03) Gu, Ke; Stoyanov, Andrey
My main research areas are international trade and empirical microeconomics. In the first and second chapter of my PhD dissertation, I use similar empirical methodology clearly identify and analyzing comparative advantage among aging and female labor supply unbalanced countries. The third chapter focus on the effect of US China trade war on the country welfare with intermediate and non-tradable goods. In the first chapter, we investigate a particular mechanism through which differences in demographic composition across countries affect international trade flows. Some cognitive functions are known to vary across the adult life span, and in particular the ability to update skills and adapt to changes in working conditions. As a country's population is getting older, it becomes increasingly difficult for firms to find workers with up-to-date skills. As a result, countries with aging populations will start losing comparative advantage in industries that rely heavily on workers' ability to adapt to frequent changes in working conditions. We test this hypothesis and find robust empirical evidence for a significant negative effect of population aging on comparative advantage of a country in industries which are intensive in skill adaptability of the labor force, in both the cross-sectional and the dynamic panel data sets. In the second chapter, we study the effect of female labor supply change on China's international trade. In 1979, the one-child policy (OCP) was introduced in China, many more boys than girls have been born, changing the relative female labor supply. Differences in sex ratios across cities, caused by differences in OCP enforcement, affect availability of gender-dependent skills. These regional differences interact with sector-specific differences in intensities in gender-dependent skills. Other things equal, cities with higher female population share specialize in industries which use female labor intensively. We empirically confirm this insight for the sample of 283 Chinese prefecture cities, using spatial variation in OCP stringency as an exogenous female labor supply shifter. We interpret our results as highlighting the importance of labor force gender composition for industry's productivity. Our results imply that the effect of gender imbalances in labor supply on labor market outcomes, observed in many parts of the world, can be mitigated through international trade by utilizing relatively abundant type of labor in export-oriented industries. In the third chapter, we use a quantitative general equilibrium trade model to analyze the effect of the US China trade war on welfare of the main countries affected by it. In 2018, the US introduced a 25% import tariff on certain imports from China in an attempt to reduce US China trade deficits and to nudge the Chinese government to abandon its unfair trade practices. Quantitative results suggest that after three rounds of import tariff increase both China and US suffered welfare reductions, by 0.3 and 0.0075 percentage points respectively. At the same time, some other economies benefited from the trade war, especially the ones that are close trade partners to either US or China. We use this model to simulate the effect of the same additional import tariff imposed on randomly selected industries, and find similar reduction in welfare.
Open Access
Corporate Hedging, Executive Compensation and Commodity Price Prediction
(2021-07-06) Tong, Michelle Jacqueline; Tian, YiSong; Jasiak, Joann
This thesis examines the agency problem surrounding the corporate hedging decision. It gives insight on how managerial incentives impact corporate hedging decisions and on how executive compensation can be used to minimize the agency problem and factors determining the optimal compensation. The model predictions are then tested against empirical data. One of the factors aecting optimal executive compensation is volatility of commodity prices. To explore this, the last chapter develops an empirical model to forecast commodity prices. Past theoretical and empirical studies found that risk-averse managers tend to overhedge, without analyzing how to align shareholders and managers hedging strategies. In this dissertation I develop a model aligning hedging strategies using executive compensation, incorporating a risk-averse managers utility into the hedging decision. Consistent with standard theories, the model show managers hedge more of the expected production than shareholders. The model shows there is a decrease in corporate hedging with the presence of managerial equity-based incentive pay. It also shows managerial incentives can be used to impact corporate hedging to minimize agency problem. To align and optimize managerial hedging decisions, the optimal managerial incentive should comprise more of the equity-based portion when there is a low risk tolerance, or low price volatility, or a low variable cost. In contrast, when there is high coecient of absolute risk aversion, or low price volatility, or high variable cost, it is best to compensate the manager with a lower equity-based portion in order to optimally align hedging decisions. In other words, by determining and examining the primary factors aecting compensation scheme includes risk aversion, price volatility, and prot margin we can determine the optimal compensation scheme. When there is a low (high) coecient of absolute risk aversion, low (high) price volatility, or low (high) variable cost, then optimal compensation should comprise more (less) equity-based incentives. Next, using empirical data I test the model predictions from the theoretical framework; (i) when incentive pay increases, the optimal hedge ratio decreases, (ii) when price volatility increases, the optimal hedge ratio decreases, while price volatility have a negative relation with equity-based incentive, (iii) when risk aversion increases, the optimal hedge ratio decreases, while risk aversion have a negative relation with equity-based incentive, and (iv) when variable cost increases, the optimal hedge ratio decreases, while variable cost have a negative relation with equity-based incentive. The predictions are tested against data obtained from oil and gas rms using a standard regression approach. I nd that the model predictions are further supported by empirical evidence from the oil and gas industry showing (i) a negative relationship between incentive pay and hedge ratio, (ii) a negative relationship between price volatility and hedge ratio/incentive pay, (iii) a negative relationship between risk aversion and hedge ratio/incentive pay, and (iv) a negative relationship between price volatility and hedge ratio/incentive pay. Overall, the rst two chapters claries the optimal compensation scheme under varying economic environments in order to mitigate the agency problem associated with hedging decisions. Last, a new model for the series of West Texas Intermediate (WTI) crude oil prices process is introduced, which accommodates spikes and local trends in its trajectory, as well as the multimodality of its sample distribution. The model relies on the convolution of two stationary processes, causal and noncausal processes, which allows for the estimation of the monthly WTI crude oil prices series. As an alternative specication, the mixed causal-noncausal autoregressive (MAR) models are estimated and used for oil price prediction. Two forecasting methods developed in the literature on MAR processes are applied to the data and compared. In addition, this chapter examines the long-term relationships between the WTI crude oil price, the Ontario Energy Price Index (OEP) and the Ontario Consumer Price Index (OCPI). These relationships are established using the cointegration analysis. The vector error correction (VEC) model allows us to predict the Ontario price indexes and the WTI crude oil prices. This chapter shows an alternative simple method of forecasting Ontario price indexes from stationary combinations of WTI crude oil price forecasts obtained from the mixed causal-noncausal autoregressive (MAR) models. This chapter shows that both method of prediction yields forecasts that are close approximation of the out of sample value.
Open Access
The Effects of Skill-Biased Technical Change on Income Distributions
(2020-11-13) Aziz, Imran; Cortes, Matias
This thesis broadly investigates the impacts of skill-biased technical change (SBTC) on income distributions. In Chapter 1, I develop a SBTC model with an intergenerational framework, where heterogeneously-skilled households make intergenerational transfers that determine the skill outcome of the next generation. By increasing the skill-premium, an SBTC shock increases these transfers, thus improving the probability that children from both high and low-skilled households will become skilled. With diminishing returns on investments, the relative improvement in skill outcomes is larger for children from low-skilled households compared to children from high-skilled households, implying that relative skill mobility also improves. I test the model's predictions in Chapter 2, using data from Chetty et al. (2014) which show how college attendance rates of children in U.S. commuting zones (CZs) are linked to the rank of their families in the national income distribution. A technology measure is constructed for each CZ using its share of STEM (Science, Technology, Engineering, and Mathematics) workers, which I instrument using a Bartik-type IV to deal with endogeneity concerns. From 2SLS estimations, I find that college attendance rates of children from households in the same income rank improve if households are located in higher technology CZs, with the improvement being larger among lower-ranked households. The findings from Chapters 1 and 2 thus suggest that SBTC can improve both absolute and relative skill mobility. Chapter 3 examines how the skill-premium from the SBTC model can impact between-group inequality among skilled and unskilled workers. I construct a Gini measure for the SBTC model, and find that if the proportion of skilled workers is more than half, a rising skill-premium can actually reduce between-group inequality if the skill-share is also growing. For empirical validation, I observe trends in the skill-portion, skill-premium and two inequality indices (Gini & Theil) for full-time, full-year workers in the U.S from 1980-2018. With the proportion of college-equivalent workers continually increasing, I find that the relationship between the skill-premium and between-group inequality has changed: from 1980-2005, the relationship was strongly positive, while from 2005 onward, it has become negative. Thus, the skill-premium's impact on between-group inequality is not unidirectional
Open Access
A Study of Immigration Performance in Terms of Task Specialization in the Canadian Labor Market
(2020-11-13) Jiang, Shiyu; Salisbury, Laura
In this dissertation, I study the impact of immigration on the Canadian economy as well as the economic outcomes of immigrants to Canada. I focus on two key economic outcomes, which differ from most of the previous literature: task usage and labor market segmentation. My first chapter examines the effect of immigration on natives' task usage. My second chapter studies differences in the outcomes of immigrants who work in and out of ethnic enclaves. My third chapter explores differences in the outcomes of first, second and third-generation immigrants. In Chapter 1, I use Canadian confidential census data to undertake research on the effects of immigration on employees' performance in the Canadian labor market. This chapter concentrates on changes in task supplies in the labor market resulting from changes in immigration to Canada. I also find the increase in the foreign-born share will lead both the relative supply of communication versus manual tasks and the relative compensations to go up in the highly-educated workers' group. In Chapter 2, I study performance differences between immigrants working in the regular Canadian labor market and those in the ethnic enclave sector. I find that the returns to education are greater and being a visible minority carries less of a wage penalty for immigrants working in the regular sector. Moreover, I document different effects of education and race on both earnings and job segments for these two types of immigrants and propose an explanation. Finally, I have a view of the differences in performance between immigrants working in the regular and enclave sectors. In Chapter 3, I estimate differences in task supply and earnings between natives and two generations of immigrants in 1970 and 2015. Furthermore, using a three-fold Blinder-Oaxaca decomposition, I link the average weekly wage of workers to their task productivity and try to find the effects of the returns to tasks as well as different task supplies on the average wage gap between natives and immigrants. Finally, I demonstrate and measure the significant effects of immigrant status on an employee's labor market segment
Open Access
Likelihood-Based Estimation Methods for Credit Rating Stochastic Factor Model
(2020-11-13) Bandehali, Maygol; Jasiak, Joann
This thesis is an empirical investigation of various estimation methods for the analysis of the dynamics of credit rating matrices. More specifically, the thesis presents three maximum likelihood estimation methods of the latent factor ordered-Probit model, which is also known as the stochastic credit migration model, a homogeneous nonlinear dynamic panel model with a common unobserved factor, to determine the dynamics of credit ratings transition probabilities. The first two methods rely on analytical approximation of the true log-likelihood function of the latent factor ordered-Probit model based on the granularity theory. The third method is maximum composite likelihood estimation of the latent factor ordered-Probit model which is the new. Chapter 1 provides the literature review on the dynamics, estimation and modelling the credit rating transition matrix. The notation and general assumptions of a latent factor ordered-Probit model are introduced, and the statistical inference of the latent factor ordered-Probit model is discussed. Chapter 2 reviews two maximum likelihood estimation methods of the latent factor ordered-Probit model which rely on analytical approximations of the log-likelihood function based on the granularity theory. The effect of the underlying state of the economy on corporate credit ratings is inferred from the common factor path. The estimated model allows us to examine the effects of shocks to the economy, i.e. the stress testing at the overall portfolio level, which is also a required element of the execution of Basel II. The stress scenarios are selected to evaluate the stressed migration probabilities and relate them with the state of the economy. The empirical results are obtained from the series of transition probabilities matrices provided by the internal rating system of a French bank over the period 2007 to 2015. Chapter 3 introduces the maximum composite likelihood estimation method for the latent factor ordered-Probit model. The computational complexity of the full information maximum likelihood in application to the stochastic migration model is the main motivation to introduce a new method, which is computationally easier and provides consistent estimators. The new method is illustrated in a simulation study that confirms good performance of the maximum composite likelihood estimation.
Open Access
Essays in Incomplete Information and Trade Policy
(2020-08-11) Ning, Haokai; Lo, Kin Chung
Strategic trade policy has been one of the most intensively researched areas in theory of industrial organization and international trade over the last three decades. The fundamental motivation is that governments adopt trade polices to confer strategic advantage to their respective domestic firms when firms are imperfectly competing with each other. However, most of existing literature focuses on markets with certainty and complete information among firms. This dissertation introduces incomplete information at industrial level into uncertainty markets in various trade models, and it also integrates the concept of option value from financial economics into equilibrium analysis. In Chapter 1, incomplete information at industrial level is introduced into an importing country model in which the domestic market demand is uncertain, and the policy is chosen before the uncertainty is resolved. Unlike the classical findings on the issue of equivalence of tariffs and quotas under certainty and complete information, it is shown that a tariff is superior to a quota regardless of the degree of uncertainty. Moreover, a prohibitive quota that results in autarky is always preferred to a quota at the free-trade level as long as quota is concerned. Chapter 2 studies the design of trade policies in an uncertain third market with incomplete information. It is shown that the country with firm having information disadvantage tends to choose the direct quantity control, while the country with well-informed firm would use export subsidy (export quota) when the degree of uncertainty is sufficiently high (low). Finally, Chapter 3 extends the conventional literature on strategic trade policy in reciprocal dumping model to the context that involves market demand uncertainty and incomplete information. Incomplete information at industrial level redistributes the option value associated with better information to the country with well-informed firm. As a result, both governments tend to choose tariffs over export subsidies in the Nash equilibrium of the simultaneous strategic trade policy games under complete and incomplete information. This yields a second best outcome. Moreover, Nash equilibrium outcome is shown to be inferior to free-trade outcome.
Open Access
Positional Momentum and Liquidity Portfolio Management
(2020-08-11) Panahidargahloo, Akram; Jasiak, Joann
This thesis introduces a new positional momentum management strategy based on the expected future ranks of asset returns and trade volume changes predicted by a bivariate Vector Autoregressive (VAR) model. Chapter one provides some facts about the relationship between return and trade volume changes and the way they have been computed in general. It begins by investigating the simple VAR model to see if we can use the past values of return and trade volume changes to predict their current values. Then recent developments in portfolio management research on momentum portfolios are discussed. Chapter two introduces a new method to build a positional momentum and liquidity portfolios based on the expected future ranks of asset returns and their trade volume changes. This method is applied to a data set of 1330 stocks traded on the NASDAQ between 2008 and 2016. It is shown that return ranks are correlated with their own past values, and the current and past ranks of trade volume changes. This result leads to a new expected positional momentum strategy providing portfolios of predicted winners, conditional on past ranks of returns and volume changes. This approach further extends to a new expected positional liquid strategy providing portfolios of predicted liquid stocks. The expected liquid positional strategy selects portfolios of stocks with the strongest realized or predicted increase in trading volume. These new positional management strategies outperform the standard momentum strategies and the equally weighted portfolio in terms of average returns and Sharpe ratio. Chapter three introduces new positional investment strategies that maximize investors positional utility from holding assets with high expected future return and liquidity ranks. The optimal allocation vectors provide new investment strategies, such as the optimal positional momentum portfolio, the optimal liquid portfolio and the optimal mixed portfolio that combines high return and liquidity ranks. The future ranks are predicted from a bivariate panel VAR model with time varying autoregressive parameters. We show that there exists a simple linear relationship between the time varying autoregressive parameters of the VAR model and the autoand cross-correlations at lag one of the return and volume change series of the SPDR. Therefore the autoregressive VAR parameters can be easily updated at each time, which simplifies the implementation of the proposed strategies. The new optimal allocation portfolios are shown to perform well in practice, both in terms of returns and liquidity.
Open Access
Measuring the Effect of Low-Skilled Workers on Innovation
(2020-08-11) Harris, Rachel Ann; Salisbury, Laura
While the effects of high-skilled immigration and labour on an economy have been well studied, the effects of low-skilled immigrants have not. In particu- lar, this effect is presumed to be negative. This Dissertation seeks to examine the relationship between low-skilled immigration and innovation and in par- ticular, patenting behaviour. In the first study, I provide novel empirical evidence to show how the Mariel Boatlift, an exogenous influx of low-skilled labour to south Florida, had an economically and statistically significant im- pact on individual patenting behaviour. I argue that this is because following the influx of low-skilled immigration, high-skilled inventors are now able to hire these low-skilled immigrants to help them with domestic work. This allows the individual inventors to free up their time and spend more time inventing, and thus we see an increase in individual patenting. My second study aims to see if these results hold in difference circumstances. I chose to look to the share of low-skilled immigrants in a city and whether this share affects individual patenting levels across time. However, I do not find that there is an effect. Finally, my third study provides a theoretical backing for the mechanism I argue in my first study.
Open Access
Time Series Analysis of Bitcoin
(2019-11-22) Hencic, Andrew; Jasiak, Joann
This thesis addresses the prediction problems associated with noncausal processes in cryptocurrency markets. Chapter one provides background on Bitcoin and cryptocurrencies in general. It begins by introducing four major cryptocurrencies. Then recent developments in economic research on Bitcoin are discussed. Chapter two introduces a noncausal autoregressive process with Cauchy errors in application to the exchange rates of the Bitcoin electronic currency against the US Dollar. The dynamics of the daily Bitcoin/USD exchange rate series display episodes of local trends, which are modelled and interpreted as speculative bubbles. The structure of the Bitcoin market is described to give context for the presence of multiple bubbles in the exchange rate. The bubbles may result from the speculative component in the on-line trading. The Bitcoin/USD exchange rates are modelled and predicted. The mixed causal-noncausal autoregressive model is shown to better fit the data than the traditional purely causal model. A forecasting exercise using the noncausal model is then presented. Chapter three examines the performance of nonlinear forecasts of noncausal processes from closed-form functional predictive density estimators. To examine the performance, time series are simulated with different conditional means and non-Gaussian distributions. The processes considered have the mixed causal-noncausal MAR(1,1)dynamics and both finite and infinite variance. The forecasts are assessed based on the forecast error behaviour and the goodness of fit of the estimated predictive density. The persistence in the noncausal component directly relates to the magnitude of the bubble effects in the time series and is found to have a meaningful impact on how forecastable the process is. To better predict bubbles the joint density of the forecast at horizon two is shown to be an effective graphical method to detect the outset of a bubble.
Open Access
Health, Labour, and the Environment: A Social Economic Analysis
(2019-03-05) Tumpane, Sara Kathleen; Buckley, Neil J.
In this dissertation, I explore several social economic topics, including health, labour, and the environment. Although the chapters of this dissertation explore diverse subjects, the overall theme is to analyze important social issues and their policy implications. I made use of a variety of rich datasets, as well as employing various econometric analyses, often supported by a theoretical model, to examine the research topics identified in each chapter. In Chapter 1, I explore a 1997 policy change, which altered eligibility requirements for Disability Insurance (DI). While DI in Canada provides income support to millions, it has also been criticized for creating a disincentive for labour force participation. The 1997 change affected some Canadians, but not others, creating a natural experiment setting in which to explore this policy. I found that, following the tightening of eligibility requirements, relative labour force participation for women did increase, but their level of employment did not. There was little effect for men. This distinction between labour force participation and employment is a crucial one in this context: it indicates that what may appear to be individuals returning to work after not being eligible for DI may instead be individuals returning to the labour force, but unable to find suitable employment. In Chapter 2, I examine whether searching for health information on the internet acts as a complement or substitute for the demand for information from physicians (proxied by physician visits). I found that the effect on physician-based information hinged on an individuals prior trust in the formal medical sector: those with high prior trust tended to use health information searching on the internet as a complement for physician visits, whereas, those with low prior trust substituted away from physician visits in favour of information found online. The results were very similar when a telehealth program was examined instead of internet-based information. Further, those who were online health information searchers also tended to be more likely to use a telehealth program. This is a reassuring result, as it may mean that those who substituted out of the formal medical sector, in favour of health online information, may also be using the more quality-controlled telehealth programs. In Chapter 3, I explore how attitudes towards the environment affect behaviours in five key areas of environmental-related household consumption: waste generation and recycling, energy use, organic food consumption, personal transport, and water use. Prior studies have not examined these areas together, often due to data restrictions, and not in the context of environmental attitudes. Using a modelling procedure that allows for the errors in these five areas to be correlated, I found that attitudes were often a more significant predictor of ones behaviour than the financially driven policy implemented in the area.
Open Access
Essays in Immigration and Migration
(2019-03-05) Monteiro, Stein; Bucovetsky, Sam
This research explores the socio-structural features of the migration and assimilation decision. The socio-structural features explored are the impact of extended family members on the migration decision of individuals within a household, and productivity differences on the assimilation rate of new immigrants. Extended families are a common feature of developing country households. I generalize the Mincer (1978) model of husband-wife migration by including decision makers from the extended family. The model with extended families predicts that migration decisions may become freer than in the husband-wife model because spouses are not more likely to be tied to their partners than members of the extended family. That is, marital status is a smaller deterrent to migration in extended family settings relative to nuclear families. I provide justification for the implications of the model using data from Nepal. Immigrants from poorer source countries have lower assimilation rates compared to immigrants from richer countries. Theory suggests that new immigrants from poor countries are exposed to co-ethnics more often than comparable immigrants from richer countries, which lead to lower assimilation rates. However, many new immigrants come with pre-immigration experience with the local culture which decreases learning costs. I insert investment into the matching model of Konya (2007). All immigrants face a cost to assimilating by investing in a process of cultural assimilation, but some new immigrants with large pre-immigration experience have significantly lower costs to investing. I provide evidence from the Longitudinal Survey of Immigrants in Canada: Waves 1-3. Source country richness has a significant positive effect on assimilation rates. But conditional on pre-immigration experience with the local culture, the exposure channel through which source country richness affects assimilation rates becomes insignificant. However, exposure to co-ethnics is not random, new immigrants face location choices among neighbourhoods in the host country. These location choices determine the level of exposure to other immigrants and the costs of learning the local native-born culture. I expand the model to include neighbourhood choice. Among neighbourhoods with fewer co-ethnics, immigrants from richer source country groups will sort into assimilating neighbourhoods. And neighbourhoods with a relatively large number of co-ethnics will receive some non-assimilating types. Using data from the Longitudinal Survey of Immigrants in Canada: Waves 1-3, I show that sorting is an important component of the exposure channel through which productivity differences affect assimilation rates. However, controlling for sorting, source country richness still has a significant positive effect on assimilation rates. There appears to be an alternate channel through which productivity differences affect assimilation rates.
Open Access
Essays on Private Contributions for Public Goods
(2018-11-21) Zhang, Yi; Bucovetsky, Sam
In many circumstances, public goods are funded by both government revenue and private contributions. Private contributions to public goods could achieve the same social goals as the government-funded public goods. Certain financial aid from the voluntary sectors reduces the heavy fiscal burdens of the public sector by sharing the responsibilities of providing public goods and services. As an alternative to the public provision of public goods, social planners encourage private contributions by providing fiscal subsidies as part of the income tax policy. My dissertation addresses the questions of whether the private provision of public goods is welfare improving in various aspects of theory and how effective it is applied to the Canadian tax schedule in an empirical model. In the second chapter of this dissertation, I focus on a particular case of the consumer's utility to investigate the effect of a government transfer to the private donation of a public good. Unlike the classic conclusion, the influence of income redistribution is not always neutral when I take consideration of the substitute relationship between the private contributed public good and the public provision of a public good. Then in chapter 3, I build on the traditional income tax model in Part I and improve it to a two-stage non-cooperative game in which it encompasses both governments funded public goods and private contributions in the optimal income tax problem in Part II. Finally, in chapter 4, I apply my theoretical model in an empirical setting using Canadian family expenditure data. I exploit this rich data on charitable contribution in Canada to assess the effectiveness of Canadian tax incentive towards charitable giving from the private sector. The empirical analysis illustrates that individuals in Canada are quite responsive to the change of tax incentive for charitable donation since price elasticity, in general, exceeds 1 in absolute value.