Economics
http://hdl.handle.net/10012/9874
2024-03-28T16:58:37ZMonetary Policy Analysis and its Contemporary Challenges
http://hdl.handle.net/10012/20298
Monetary Policy Analysis and its Contemporary Challenges
Baker, John
This thesis contains three essays on the empirical analysis of monetary policy. While the subjects are diverse, they all share the goal of providing for a thorough, data-driven analysis of critical policy developments related to communications from North American central banks. The first chapter examines the effectiveness of central bank communications as a policy tool. To evaluate this otherwise qualitatively-oriented policy channel, a new dictionary of central banking sentiment is developed using natural language processing. This dictionary aims to capture the relative prevalence of positive (contractionary) versus negative (expansionary) words used in discussions of the monetary policy landscape. It is then applied to a large sample of news articles, where sentiment scores are computed and adopted in two forms of empirical analysis. The first form of analysis utilizes these sentiment scores in a high-frequency event study, which indicate that positive communication surprises lead to increased interest rates across various horizons on the yield curve, along with an appreciation of the Canadian dollar relative to other major currencies. The sentiment measure is also employed in a lower-frequency analysis, where the average score across all articles is computed on a monthly basis. VAR estimates support the findings from the high-frequency event analysis and allow exploration of other outcomes available only at a monthly frequency. The analysis suggests limited direct evidence of links between communication shocks, prices, and real measures of economic activity, except for the real estate market. In the second chapter, we profile an essential case study that emerged during COVID-related monetary stimulus, where central banks sought to dismiss concerns about rising inflation as "transitory." This chapter focuses on the United States and develops a separate tailored dictionary that is used to quantify the degree of belief (or disbelief) in the transitory inflation signal. It analyzes news articles and tracks changes in sentiment-derived signal credibility over time, revealing that overall levels of credibility declined as positive inflation surprises persisted throughout 2021. This measure is then adopted within the framework of a daily VAR model, showing that the signal credibility measure declines significantly to positive inflation surprises and that market-based inflation expectations rise even at extended horizons in response to negative shocks from the credibility measure. The final chapter explores the potential intersection between economic inequality and monetary policy in Canada. In the first exercise, a macro panel exercise reveals a "U-shaped" effect on income sourced from labour, meaning that expansionary policy benefits the bottom and upper ends of the income distribution most significantly in percentage terms. A similar pattern is observed for non-labour income, which tend to favour the wealthiest Canadians, and particularly since the 2008-2009 Financial Crisis. Time series evidence highlights a growing connection between policy surprises and real asset prices, with a more modest impact on unemployment. Altogether, these essays address crucial issues related to monetary policy, emphasizing the importance of evidence-based analysis and objective quantitative research in evaluating the effectiveness and consequences of central bank communications and policies.
2024-01-26T00:00:00ZConspicuous Consumption and Inequality
http://hdl.handle.net/10012/20118
Conspicuous Consumption and Inequality
Nesterova, Iuliia
My research is centered around understanding consumption behavior and its relationship
with inequality.
In Chapter 1, I study how consumption inequality in the United States has evolved over
time, with a particular focus on distinguishing two major expenditure components: services
and goods. I argue that such distinction is important to understand inequality between
high and low income groups. I show that increases in consumption inequality over the
period 1984-2018 were driven mostly by rising inequality in expenditure on services rather
than goods. I further show that most of it was driven by increased inequality in young
households expenditure in services, whereas older households have experienced no change
in inequality of either good or service expenditures. As modern societies undergo the
transformation into service societies, this research contributes to our understanding of the
diverse effects of inequality and informs policy decisions to ensure that this transformation
benefits all.
Chapter 2 proposes a canonical model of intertemporal choice in which both current
and future conspicuous consumption can distort household consumption behavior. What
makes our model tractable is that we assume that each consumer cares about the expected
comparison of relative consumption, which provides a parsimonious characterization of
positional concerns. We show that equilibrium consumption behavior is a function of
the distribution of conspicuous consumption in an individual’s reference group as well as
her own permanent income. In turn, the distribution of conspicuous consumption is a
function of the distribution of permanent income. The relevant empirical implication is
that an individual’s consumption, by itself, is no longer a valid proxy for the individual’s
permanent income if relative consumption matters.
In Chapter 3, we document a robust effect of visible inequality on household expenditures in the United States over the period 2010–2018. To that end, we exploit variation in
the cross-sectional distribution of visible consumption — expenditures in clothing, personal
care, food away from home and vehicles — for younger and older households across regions
of the United States and over time. We find that rising inequality in expenditure on visible
goods within the different groups is associated with an increase in average spending on
those same goods as well as an increase in total expenditures by the average household in
the group. Our main findings are not likely to be a symptom of correlated differences in
preferences across generations, selection effects across geographical locations, alternative
sources of state-level variation over time, or measurement error. Rather, they most likely
reflect actual distortions associated with consumption externalities. We conjecture that
historically low interest rates and the rise of social media underlie our findings.
2023-11-27T00:00:00ZEssays on Portfolio Selection, Continuous-time Analysis, and Market Incompleteness
http://hdl.handle.net/10012/19251
Essays on Portfolio Selection, Continuous-time Analysis, and Market Incompleteness
Li, Yixuan
This thesis consists of three self-contained essays evaluating topics in portfolio selection, continuous-time analysis, and market incompleteness.
The two opposing investment strategies, diversification and concentration, have often been directly compared. Despite the less debate regarding Markowitz's approach as the benchmark for diversification, the precise meaning of concentration in portfolio selection remains unclear. Chapter 1, coauthored with Jiawen Xu, Kai Liu, and Tao Chen, offers a novel definition of concentration, along with an extreme value theory-based estimator for its implementation. When overlaying the performances derived from diversification (in Markowitz's sense) and concentration (in our definition), we find an implied risk threshold, at which the two polar investment strategies reconcile -- diversification has a higher expected return in situations where risk is below the threshold, while concentration becomes the preferred strategy when the risk exceeds the threshold. Different from the conventional concave shape, the estimated frontier resembles the shape of a seagull, which is piecewise concave. Further, taking the equity premium puzzle as an example, we demonstrate how the family of frontiers nested inbetween the estimated curves can provide new perspectives for research involving market portfolios.
Parametric continuous-time analysis for stochastic processes often entails the generalization of a predefined discrete formulation to a continuous-time limit. However, unknown convergence rates of the frequency-dependent parameters can destabilize the continuous-time generalization and cause modelling discrepancy, which in turn leads to unreliable estimation and forecast. To circumvent this discrepancy, Chapter 2, coauthored with Tao Chen and Renfang Tian, proposes a simple solution based on functional data analysis and truncated Taylor series expansions. It is demonstrated through a simulation that our proposed method is superior in both fitting and forecasting continuous-time stochastic processes compared with parametric methods that encounter troubles uncovering the true underlying processes.
When the markets are incomplete, perfect risk sharing is impossible and the law of one price no longer guarantees the uniqueness of the stochastic discount factor (SDF), resulting in a set of admissible SDFs, which complicates the study of financial market equilibrium, portfolio optimization, and derivative securities. Chapter 3, coauthored with Tao Chen, proposes a discrete-time econometric framework for estimating this set of SDFs, where the market is incomplete in that there are extra states relative to the existing assets. We show that the estimated incomplete market SDF set has a unique boundary point, and shrinks to this point only when the market completes. This property allows us to develop a novel measure for market incompleteness based upon the Wasserstein metric, which estimates the least distance between the probability distributions of the complete and incomplete market SDFs. To facilitate the parametrization of market incompleteness for implementation, we then consider in detail a continuous-time framework, in which the incompleteness specifically arises from stochastic jumps in asset prices, and we demonstrate that the theoretical results developed under the discrete-time setting still hold true. Furthermore, we study the evolution of market incompleteness in four of the world's major stock markets, namely those in China, Japan, the United Kingdom, and the United States. Our findings indicate that an increase in market incompleteness is usually caused by financial crises or policy changes that raise the likelihood of unanticipated risks.
2023-04-05T00:00:00ZAn Analysis of Optimal Agricultural Fertilizer Application Decisions in the Presence of Market and Weather Uncertainties and Nutrient Pollution
http://hdl.handle.net/10012/19054
An Analysis of Optimal Agricultural Fertilizer Application Decisions in the Presence of Market and Weather Uncertainties and Nutrient Pollution
Yang, Xinyuan
This thesis addresses the questions of how uncertain corn market and weather factors affect optimal fertilizer application decisions of the farmer and the social planner, and what factors drive the divergence between the two. Nutrient runoff from agricultural activities has become a primary source of surface water quality deterioration worldwide. Over-application of fertilizer in agricultural production represents a non-point source pollution which is causing extensive nutrient loading in water bodies and has a severe impact on the global environment. There is evidence that farmers apply more fertilizer than is socially optimal and more than is recommended by government agencies. This thesis first investigates the farmer’s optimal fertilizer application under crop price uncertainty by constructing an inter-temporal farmer’s decision model under two alternative stochastic price processes. Closed form results are derived, which indicate that an increase in price uncertainty implies a reduction in the quantity of fertilizer applied in the farmer’s optimal decision problem. Numerous factors that could impact the optimal fertilization decision are examined as well. The farmer’s decision model is then enhanced by allowing for two possible fertilizer application times in the growing season and the inclusion of additional stochastic state variables such as rainfall and temperature, in the corn yield model. The model is parameterized for average conditions in Iowa corn growing regions. Employing a Monte Carlo approach, numerical results conclude that for a wide range of parameter assumptions the farmer’s optimal strategy is to apply fertilizer at planting rather than later as a side dressing. This thesis analyzes the impacts of price uncertainty, fertilizer cost and other economic parameters on the farmer’s optimal fertilizer application strategy. The thesis also analyzes the optimal decisions of a social planner whose objective function includes an estimate of the damages caused by nitrogen leakage and denitrification. Numerical results show that including the damages from pollution affect both the quantity and timing of fertilizer application. Assumptions about the frequency and quantity of rainfall have an important impact on the optimal decision. This is an important consideration for public policy as climate change affects weather patterns over the next decade and beyond.
2023-01-12T00:00:00Z