This dissertation combines micro-level empirical analyses and general equilibrium structural models to study shock propagation mechanisms and business cycles dynamics, with a particular emphasis on the role played by firms. In the first chapter, we study how regional shocks spill over across U.S. local markets through intra-firm market networks and explore how such spillovers reshape household welfare across regions. We link data on barcode-region-level prices and quantities with producer-level information to exploit variation in firms' initial exposure to differential drops in local house prices in the 2007-09 recession. We show that a firm's local sales decrease in response to not only direct negative local demand shock but also indirect negative local demand shocks originating in its other markets. Intra-firm cross-market spillover effects arise mainly from product creation and destruction, whereas direct local shock operates through the sales of continuing products. Spillover effects occur because (i) firms replace products that have higher value---sales per product, unit price, and organic sales share---with lower-value ones in response to negative demand shocks, and (ii) such product replacements are synchronized across many markets within each firm. Counterfactual analysis using an estimated multi-region model with endogenous quality adjustments shows that our channel works as a novel inter-regional shock transmission mechanism and generates an implicit regional redistribution effect. Such effect is economically sizable and is comparable to the size of transfer policies implemented during the Great Recession. In the second chapter, we investigate a role of supply chain network in transmitting housing market disruptions during the Great Recession. We build up a unique micro-level data that combines local housing market condition, firms' sales in each local market, and firm-level supply chain network information. Exploiting firm-specific demand shock stemming from cross-market variation in house price changes and an initial difference in firms' local sales, we find that such shock not only affects downstream firms but also transmits to their suppliers. The estimated supplier-level elasticity is quantitatively large, reflecting larger role of downstream firms with higher elasticity in the network structure. To quantify such propagation at the aggregate level, we build up a parsimonious network model calibrated to match the micro-level data. Our counterfactual analysis shows that approximately 18\% of the observed drop in the aggregate output can be attributed to the propagating role of the supply chain network. In the third chapter, we study the business cycle with a Translog production function. We empirically identify a complementarity between labor and energy that leads to procyclical returns to scale, which is not compatible with the tightly parameterized production function commonly used in the literature (Cobb-Douglas and CES). Therefore, we propose a flexible Translog production function that not only features complementarity-induced procyclical returns to scale but is also consistent with a balanced growth path. A simple calibrated business cycle model with the proposed production function generates strikingly data-consistent dynamics following demand shocks without relying on either nominal rigidities or countercyclical markups.

The first chapter studies the effects of government capital accumulation on sovereign debt default risk and debt restructuring renegotiation outcomes when a government has limited ability to extract revenues from households. To do so, this chapter develops a quantitative dynamic stochastic general equilibrium model of sovereign default, debt renegotiation, and fiscal policies, where the government chooses between the fiscal expenditures of government consumption and government investment. Government capital provides an additional means of adjustment in the face of a bad productivity shock. It also affects the government's incentive to re-access the international credit market when the government chooses to default. The model delivers three key predictions: (1) a higher level of government capital implies less risky sovereign debt and higher recovery rates when the government chooses to default; (2) a high debt to output ratio is sustainable with a sufficient level of government capital; (3) fiscal adjustment that reduces public investment may be self-defeating. The second chapter investigates the empirical facts that government expenditures and taxes are procyclical in developing countries but countercyclical or acyclical in developed economies. This chapter provides a possible explanation for this stylized fact by introducing news about future total factor productivity and endogenous fiscal policy in an otherwise-standard small open economy model of sovereign default risk, as in Arellano (2008). News tends to be more precise in developed countries, which relaxes credit constraints on foreign borrowing and makes developed countries less reliant on tax revenues. This dampens and potentially reverses the high correlation between output and government expenditures/taxes observed in developed countries. The third chapter studies the impact of creditors' income process on the outcomes of sovereign debt restructurings. This chapter compiles a new dataset on foreign creditors' income process during negotiation. This chapter shows that when foreign creditors are facing high income, restructurings are protracted and result in smaller haircuts. To explain these stylized facts, this chapter develops a dynamic stochastic general equilibrium model of defaultable debt that embeds multi-rounds negotiations between a risk-averse sovereign and risk-averse creditors. The quantitative analysis shows that high creditors' income results in a longer duration of restructuring and higher haircuts.

This dissertation finds significant differences in the micro-level household consumption behavior between emerging and developed economies, disentangles multiple possible explanations for these differences, and evaluates their macroeconomic implication on business cycles. The first chapter estimates the marginal propensity to consume (MPC) out of transitory income shocks using micro data for an emerging economy. To this end, I employ a nationally representative Peruvian household survey. Two striking differences emerge when the Peruvian MPC estimates are compared with U.S. MPC estimates obtained by the same method. First, the mean MPC of Peruvian income deciles is much higher than that of U.S. deciles. Second, within-country MPC heterogeneity over the deciles is substantially stronger in Peru than in the U.S. The second chapter studies the driving factor for the MPC differences between Peru and the U.S. I begin by exploring three possible explanations for the stronger MPC heterogeneity in Peru through the lens of a standard precautionary saving model: liquidity constraints, consumption front-loading behavior, and heterogeneous interest rates. Then, I disentangle these possible explanations by examining relevant data patterns appearing in the micro data. Specifically, participation rates in borrowing activities and consumption growth rate patterns of the income deciles suggest that liquidity constraints drive the stronger MPC heterogeneity in Peru. Then, I decompose the cross-country MPC gap into the component driven by liquidity constraints and the component caused by factors unrelated to liquidity constraints. To this end, I delineate a top income group unaffected by liquidity constraints in each country by conducting an MPC homogeneity test and evaluate its MPC. I find that liquidity constraints are also important for explaining the higher mean MPC in Peru. The third chapter makes a first attempt to study emerging market business cycles in a heterogeneous-agent open economy model. A central question in open economy macroeconomics is how to explain excess consumption volatility in emerging economies. This chapter argues that to understand this phenomenon, it is important to take into account households' idiosyncratic income risk, precautionary saving, and MPCs. Financial frictions determining asset liquidity in the model are calibrated such that MPCs are as high as empirical estimates from Peruvian micro data, which are substantially greater than the U.S. MPC estimates. I then estimate the model using macro data and Bayesian methods. The model captures the observed excess consumption volatility well. To highlight the importance of high-MPC households in driving this result, I show that excess consumption volatility disappears when households are counterfactually replaced with those exhibiting U.S. MPCs. High-MPC households contribute to consumption volatility through i) their strong consumption response to resource fluctuations and ii) large consumption reduction when assets become more illiquid. The transmission mechanisms of trend shocks and interest rate variations that previous studies use to explain excess consumption volatility are dampened because households significantly deviate from the permanent income hypothesis, on which these mechanisms crucially depend.

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This thesis attempts to answer three important questions: 1) Why did India's relative price of investment rise in 80s and fall in 1990s and afterwards? 2) Why is agricultural productivity very low in India? and 3) Did the pro-natalist policy in Quebec accomplish its goal of increasing fertility? Specifically, this thesis comprises of three essays. Chapter 1 builds a simple dynamic general equilibrium model calibrated to Indian data, in order to explore the impact of capital import substitution policies and their reform post-1991. The model delivers a 23% rise before reform and a 28% fall thereafter. Chapter 2 develops a tractable quantitative framework by incorporating one potential explanation - if residing in a village provides access to a network that effectively insures against income fluctuations, then households are less willing to live in cities where labor income risk is uninsured. This chapter shows that implementation of a social insurance system in the urban area could have raised the labor productivity agricultural sector. Chapter 3 studies the effects of a pro-natalist policy in Quebec and finds Quebec’s baby bonus accomplished its goal of increasing fertility. It finds a large response for third and higher-order births for which the bonus was more generous. Interestingly, it also finds a stronger response if there were two previous sons or a previous son and daughter rather than two previous daughters. / Thesis / Doctor of Philosophy (PhD)

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Thesis advisor: Peter N. Ireland / This dissertation examines three topics in computational macroeconomics and finance. The first two chapters are closely linked; and the third chapter covers a separate topic in finance. Throughout the dissertation, I place a strong emphasis on constructing computational tools and modeling devices; and using them in appropriate applications. The first chapter examines how a central banks choice of interest rate rule impacts the rate of mortgage default and welfare. In this chapter, a quantitative equilibrium (QE) model is constructed that incorporates incomplete markets, aggregate uncertainty, overlapping generations, and realistic mortgage structure. Through a series of counterfactual simulations, five things are demonstrated: 1) nominal interest rate rules that exhibit cyclical behavior increase the average default rate and lower average welfare; 2) welfare can be substantially improved by adopting a modified Taylor rule that stabilizes house prices; 3) a decrease in the length of the interest rate cycle will tend to increase the average default rate; 4) if the business and housing cycles are not aligned, then aggressive inflation targeting will tend to increase the mortgage default rate; and 5) placing a legal cap on loan-to-value ratios will lower the average default rate and lessen the intensity of extreme events. In addition to these findings, this paper also incorporates an important mechanism for default, which had not pre- viously been included in the QE literature: default spikes happen when income falls and home equity is degraded at the same time. The paper concludes with a policy recommendation for central banks: if they wish to crises where many households default simultaneously, they should either adopt a rule that generates interest rates with slow-moving cycles or use a modified Taylor rule that also targets house price growth. The second chapter generalizes the solution method used in the first and compares it to more common techniques used in the computational macroeconomics literature, including the parameterized expectations approach (PEA), projection methods, and value function iteration. In particular, this chapter compares the speed and accuracy of the aforementioned modifications to an alternative method that was introduced separately by Judd (1998), Sutton and Barto (1998), and Van Roy et al. (1997), but was not developed into a general solution method until Powell (2007) introduced it to the Operations Research literature. This approach involves rewriting the Bellman equation in terms of the post-decision state variables, rather than the pre-decision state variables, as is done in standard dynamic programming applications in economics. I show that this approach yields considerable performance benefits over common global solution methods when the state space is large; and has the added benefit of not forcing modelers to assume a data generating process for shocks. In addition to this, I construct two new algorithms that take advantage of this approach to solve heterogenous agent models. Finally, the third chapter imports the SIR model from mathematical epidemiol- ogy; and uses it to construct a model of financial epidemics. In particular, the paper demonstrates how the SIR model can be microfounded in an economic context to make predictions about financial epidemics, such as the spread of asset-backed securities (ABS) and exchange-traded funds (ETFs), the proliferation of zombie financial institutions, and the expansion of financial bubbles and mean-reverting fads. The paper proceeds by developing the 1-host SIR model for economic and financial contexts; and then moves on to demonstrate how to work with the multi-host version of the model. In addition to showing how the SIR framework can be used to model economic interactions, it will also: 1) show how it can be simulated; 2) use it to develop and estimate a sufficient statistic for the spread of a financial epidemic; and 3) show how policymakers can impose the financial analog of herd immunity-that is, prevent the spread of a financial epidemic without completely banning the asset or behavior associated with the epidemic. Importantly, the paper will focus on developing a neutral framework to describe financial epidemics that can be either bad or good. That is, the general framework can be applied to epidemics that constitute a mean-reverting fad or an informational bubble, but ultimately yield little value and shrink in importance; or epidemics that are long-lasting and yield a new financial in- strument that generates permanent efficiency gains or previously unrealized hedging opportunities. / Thesis (PhD) — Boston College, 2013. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

Thesis (Ph. D.)--University of Texas at Austin, 1997. / Includes bibliographical references (p. 349-356).

This thesis is concerned with macroeconomic dynamics under various forms of uncertainty. Chapter 2 recognizes that the information flow from the interest rate is impeded when the nominal interest rate hits the zero lower bound. This impediment can (a) increase the duration of zero lower bound episodes and (b) bring about more persistent deflationary pressure. Moreover, it can make the exit from the zero lower bound disorderly. Chapters 3 and 4 are concerned with dynamics of aggregate variables under Knightian Uncertainty. To overcome difficulties with expectations formation under Knightian Uncertainty, the agents follow Interactive Trial and Error Learning (ITEL) (Young, 2009; Pradelski and Young, 2012) to choose investment portfolios. This involves learning by occasionally experimenting with new actions even when the current action proves to be good. Two applications of ITEL are presented. Chapter 3 deals with the growth of aggregate variables. The growth model can match several business cycle features of the US real aggregate wealth data. Chapter 4 considers a portfolio choice problem. The portfolio choice model can match the first two moments of the US real excess return of equity over bonds almost perfectly. Chapter 5 explores “This Time Is Different Syndrome” of Reinhart and Rogoff (2009) in a setting where the agents are learning under Knightian Uncertainty. The agents are grouped into different generations and their models compete in terms of forecasting power. The predecessor’s model is discarded together with the data set when its forecasting power is worse than the current generation’s model. This loss of relevant data is rooted in focusing only on forecasting well in the short-run. By shifting the weight towards finding the true model of the economy, this problem can be substantially reduced.

Using survey-based measures of future interest rate expectations from the Blue Chip Economic Indicators and the Survey of Professional Forecasters, we examine the relationship between monetary policy uncertainty, captured as the dispersion of interest rate forecasts, and fluctuations in real economic activity and core inflation. We use a flexible time-varying parameter vector autoregression (TVP-VAR) model to clearly isolate the dynamic effects of shocks to monetary policy uncertainty. To further study possible a possible nonlinear relationship between monetary policy uncertainty and the macroeconomic aggregates, we extract the impulse-response functions (IRF’s) estimated at each quarter in the time series, and use a multi-variate regression with various measures of the shape of the IRF’s and the level of monetary policy uncertainty at that quarter in the TVP-VAR model to gauge the relationship between the effectiveness of traditional monetary policy (shocks to the Federal Funds rate), forward guidance (shocks to expected interest rates) and uncertainty. The results show that monetary policy uncertainty can have a quantitatively significant impact on output, with a one standard deviation shock to uncertainty associated with a 0.6% rise in unemployment. The indirect effects are more substantial, with a one standard deviation increase in monetary policy uncertainty associated with a 23% decrease in the maximum response of unemployment to a forward guidance episode (interest rate expectations shock). This evidence points to the importance of managing monetary policy uncertainty (clear and direct forward guidance) as a key policy tool in both stimulating economic activity as well as propagating other monetary policy through the macroeconomy.