Three Essays in Econometrics
Creators: Tuzcuoglu, Kerem
Publisher: name: Columbia University
Year: 2017
Subjects: subject: Macroeconomics
subject: Finance
subject: Econometrics
subject: FOS: Economics and business

description: This dissertation contains both theoretical and applied econometric work. The applications are on finance and macroeconomics. Each chapter utilizes time series techniques to analyze dynamic characteristics of data. The first chapter is on composite likelihood (CL) estimation, which has gained a lot of attention in the statistics field but is a relatively new technique to the economics literature. I study its asymptotic properties in a complex dynamic nonlinear model and use it to analyze corporate bond ratings. The second chapter explores the importance of global food price fluctuations. In particular, I measure the effects of global food shocks on domestic macroeconomic variables for a large number of countries. The third chapter proposes a method to interpret latent factors in a data-rich environment. In the application, I find five meaningful factor driving the US economy. 
      Chapter 1, persistent discrete data are modeled by Autoregressive Probit model and estimated by CL estimation. Autocorrelation in the latent variable results in an intractable likelihood function containing high dimensional integrals. CL approach offers a fast and reliable estimation compared to computationally demanding simulation methods. I provide consistency and asymptotic normality results of the CL estimator and use it to study the credit ratings. The ratings are modeled as imperfect measures of the latent and autocorrelated creditworthiness of firms explained by the balance sheet ratios and business cycle variables. The empirical results show evidence for rating assignment according to Through-the-cycle methodology, that is, the ratings do not respond to the short-term fluctuations in the financial situation of the firms. Moreover, I show that the ratings become more volatile over time, in particular after the crisis, as a reaction to the regulations and critics on credit rating agencies. 
      Chapter 2, which is a joint work with Bilge Erten, explores the sources and effects of global shocks that drive global food prices. We examine this question using a sign-restricted SVAR model and rich data on domestic output and its components for 82 countries from 1980 to 2011. After identifying the relevant demand and supply shocks that explain fluctuations in real food prices, we quantify their dynamic effects on net food-importing and food-exporting economies. We find that global food shocks have contractionary effects on the domestic output of net food importers, and they are transmitted through deteriorating trade balances and declining household consumption. We document expansionary and shorter-lived effects for net food exporters. By contrast, positive global demand shocks that also increase real food prices stimulate the domestic output of both groups of countries. Our results indicate that identifying the source of a shock that affects global food prices is crucial to evaluate its domestic effects. The adverse effects of global food shocks on household consumption are larger for net food importers with relatively high shares of food expenditures in household budgets and those with relatively high food trade deficits as a share of total food trade. Finally, we find that global food and energy shocks jointly explain 8 to 14 percent of the variation in domestic output.
      Chapter 3, which is a joint work with Sinem Hacioglu, exploits a data rich environment to propose a method to interpret factors which are otherwise difficult to assign economic meaning to by utilizing a threshold factor-augmented vector autoregression (FAVAR) model. We observe the frequency of the factor loadings being induced to zero when they fall below the estimated threshold to infer the economic relevance that the factors carry. The results indicate that we can link the factors to particular economic activities, such as real activity, unemployment, without any prior specification on the data set. By exploiting the flexibility of FAVAR models in structural analysis, we examine impulse response functions of the factors and individual variables to a monetary policy shock. The results suggest that the proposed method provides a useful framework for the interpretation of factors and associated shock transmission.