Learning Optimal Behavior Through Reasoning and Experiences

We develop a novel framework of bounded rationality under cognitive frictions that studies learning over optimal behavior through both deliberative reasoning and accumulated experiences. Using both types of information, agents engage in Bayesian non-parametric estimation of the unknown action value function. Reasoning signals are produced internally through mental deliberation, subject to a cognitive cost. Experience signals are the observed utility outcomes at previous actions. Agents' subjective estimation uncertainty, which evolves through information accumulation, modulates the two modes of learning in a state- and history-dependent way. We discuss how the model draws on and bridges conceptual, methodological and empirical insights from both economics and the cognitive sciences literature on reinforcement learning

Transparency, Performance, and Agency Budgets: A Rational Expectations Modeling Approach

Existing research suggests that bureaucrats’ optimal behavior is to maximize their agency’s budgets, but does not account for information imperfections nor explore the tactics bureaucrats employ in maximizing their budgets. Drawing on the rational expectations literature, we propose a new theoretical model that describes the behaviors of politicians who, using imperfect information, judge an agency’s performance, and bureaucrats who, by varying the agency’s transparency, alter the degree of information imperfection and so influence the politicians’ abilities to judge the agency’s performance. We then fit data from the government’s Performance Accountability Reports and the Scorecard data set to our model and obtain empirical results that are consistent with what our theoretical model predicts.bureaucracy; agency; budget; budget maximization; transparency; performance; imperfect information; Government Performance Reports Act; Scorecard

Essays in International Finance

<p>This dissertation addresses three key issues in international finance and economics: the uncovered interest rate parity puzzle in exchange rates, the home bias puzzle in portfolio allocations, and the surprising lack of correlation between terms of trade shocks and output in small open economies. </p><p>The first chapter shows that the much-studied Uncovered Interest Rate Parity (UIP) puzzle, the observation that exchange rates do not adjust sufficiently to offset interest rate differentials, is more complicated than commonly understood. I show that the puzzle changes nature with the horizon. I confirm existing short-run evidence that high interest rate currencies depreciate less than predicted by the interest rate differential. But, building on Engel (2012), at longer horizons (4 to 7 years) I find a reverse puzzle: high interest rate currencies depreciate too much. Interestingly, the long-horizon excess depreciation leads exchange rates to converge to the UIP benchmark over the long-run. To address the changing nature of the puzzle, I propose a novel model, based on the mechanism of bond convenience yields, that can explain both the short and the long horizon UIP violations. I also provide direct empirical evidence that supports the mechanism. </p><p>In chapter 2, I address the puzzling observation that portfolios are concentrated in asset classes which comove strongly with the non-financial income of investors. As an explanation, I propose a framework of endogenously generated information asymmetry, where rational agents optimally choose to focus their limited attention on risk factors that drive both their non-financial income and some of the risky asset payoffs. In turn, the agents concentrate their portfolios in assets driven by those endogenously familiar factors. I explore an uncertainty structure that implies decreasing returns to information, whereas the previous literature has focused on a setup with increasing returns. I show that the two frameworks have differing implications, which I test in the data and find support for decreasing returns to information. </p><p>In chapter 3, I address the puzzling lack of correlation between Terms of Trade (ToT) and the Small Open Economy (SOE) GDP. A SOE model typically relies on three sources of exogenous disturbances: world real interest rate, Terms of Trade (ToT) and technology. However, the empirical literature has failed to reach a consensus on the relative importance of the terms of trade as a driver of business cycles, with some papers claiming they are hugely important while others find no evidence of a relationship at all. Kehoe and Ruhl (2008) have recently shown that the weak empirical link between ToT and the GDP might be due to measurement limitations with the output series in an open economy framework. This paper merges data on national accounts with data on global trade flows for a panel of 31 countries and finds that Terms of Trade have a negligible effect on GDP but a strong effect on aggregate consumption. The evidence supports the hypothesis that ToT are important drivers of business cycles, but measurement issues with GDP obscure their relationship with real output. This further suggests that researchers should be careful when equating model output with measured GDP in an open economy setup.</p>Dissertatio

Beyond home bias: international portfolio holdings and information heterogeneity

We show that international portfolios reflect the underlying heterogeneity in investors' beliefs. Using data on foreign sovereign debt holdings of European banks matched with their forecasts on future bond yields, we find that expecting higher returns and having more accurate forecasts are associated with larger bond holdings. Crucially, the elasticity of portfolio holdings to expected returns is increasing in the precision of the forecast, implying that investors optimally exploit comparative advantages in information production. We rationalize the results in a model where partial information specialization arises endogenously by introducing some degree of unlearnable uncertainty about asset payoffs