Two Essays on Estimation and Inference of Affine Term Structure Models

Two Essays on Estimation and Inference of Affine Term Structure Models
Author: Qian Wang
Publisher:
Total Pages: 147
Release: 2015
Genre:
ISBN:

Affine term structure models (ATSMs) are one set of popular models for yield curve modeling. Given that the models forecast yields based on the speed of mean reversion, under what circumstances can we distinguish one ATSM from another? The objective of my dissertation is to quantify the benefit of knowing the “true” model as well as the cost of being wrong when choosing between ATSMs. In particular, I detail the power of out-of-sample forecasts to statistically distinguish one ATSM from another given that we only know the data are generated from an ATSM and are observed without errors. My study analyzes the power and size of affine term structure models (ATSMs) by evaluating their relative out-of-sample performance. Essay one focuses on the study of the one-factor ATSMs. I find that the model’s predictive ability is closely related to the bias of mean reversion estimates no matter what the true model is. The smaller the bias of the estimate of the mean reversion speed, the better the out-of-sample forecasts. In addition, my finding shows that the models' forecasting accuracy can be improved, in contrast, the power to distinguish between. different ATSMs will be reduced if the data are simulated from a high mean reversion process with a large sample size and with a high sampling frequency. In the second essay, I extend the question of interest to the multi-factor ATSMs. My finding shows that adding more factors in the ATSMs does not improve models' predictive ability. But it increases the models' power to distinguish between each other. The multi-factor ATSMs with larger sample size and longer time span will have more predictive ability and stronger power to differentiate between models.

Two Essays on Maximum Likelihood Estimations of Dynamic Stochastic General Equilibrium Models

Two Essays on Maximum Likelihood Estimations of Dynamic Stochastic General Equilibrium Models
Author: Gulnur Kozak
Publisher:
Total Pages: 155
Release: 2008
Genre:
ISBN:

This dissertation consists of two essays on maximum likelihood estimation of Dynamic Stochastic General Equilibrium (DSGE) models. The first essay focuses on a monetary DSGE model of term structure, while the second essay explores and compares three different versions of New Keynesian DSGE models. In Chapter 1, a general background is given for the DSGE models, and their estimation techniques along with a review of the term structure models and New Keynesian models. The first essay, which is a joint work with Hwagyun Kim, empirically evaluates the relationships between money, inflation, output growth, and the interest rates of different maturities using a monetary DSGE model of term structure, featuring inflation targeting behavior, asset market segmentation, and external habit extended for nominal economy. This model can generate liquidity effect, average upward sloping yield curve, and time-varying bond risk premia for bearing inflation and real shocks. By exploiting the term structure equations derived from the model, the deep parameters of the model describing risk preference, inflation targeting behavior, and market segmentation between bond traders and non-traders are estimated. The model is estimated under alternative specifications: latent factors; macroeconomic factors; and both latent and macroeconomic factors. The empirical findings show that all the methods give consistent estimates of the parameters, and conclude that asset market segmentation, inflation targeting, and time-varying risk aversion are significant to account for the term structure dynamics. They also suggest that monetary factors and monetary policy are important to understand both short-run and long-run behaviors of bond prices. In the second essay, three different versions of New Keynesian DSGE models are developed, and their structural parameters are estimated by maximum likelihood estimation. Specifically, the role of velocity of money on the dynamics of real variables is empirically examined by constructing a money in the utility model and two special cases of transactions cost model. Wealth effects, previously ignored in many transactions cost models, are taken into consideration in one of the cases examined here, and comparisons are made between the transactions cost model that includes the wealth effects and the transactions cost model that ignores the wealth effects entirely. The equivalence of money in the utility model and transactions cost model with wealth effects is also quantitatively examined. The results show that there is no evidence of quantitative equivalence between these two models. Although the magnitude of impulse responses are different among the models studied here, all three models give consistent estimates for the structural parameters. The empirical findings from the maximum likelihood estimates of all three models' parameters also suggest that the velocity of money is a very important part of the IS and Phillips curves of all three models developed here, and should be included in IS and Phillips curves when examining the inflation and output dynamics.