Essays in Macroeconomics

My dissertation consists of three self-contained essays on macroeconomics. Chapter 2 "Churning, firm inter-connectivity, and labor market fluctuations'' studies the implications of firm inter-connectivity and irreversibility of inter-firm cooperation relationships on the business cycle. Chapter 3 "Inter-sector matching efficiency and sectoral comovement'' examines the comovement of sectoral labor markets when there is search friction in the inter-firm matching market. Chapter 4 "Lumpy investment and endogenous investment price'' (Joint work with Linxi Chen) studies the endogenous fluctuation of investment price induced by search friction in the investment goods market and partial irreversibility of capital adjustment. Each of the essays investigates the implication of market frictions, such as search friction and partial irreversibility, to the business cycle from a different perspective.

Bayesian Emulation for Sequential Modeling, Inference and Decision Analysis

The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.