Economics, Department ofhttp://hdl.handle.net/1974/7722017-06-27T01:53:51Z2017-06-27T01:53:51ZReturns to scale and fire-sales in the Canadian Banking SystemMcKeown, Roberthttp://hdl.handle.net/1974/159032017-06-16T07:13:38ZReturns to scale and fire-sales in the Canadian Banking System
McKeown, Robert
My dissertation is divided into four parts. Chapter one summarizes and analyzes data on the Canadian banking system using data from CANSIM and a little used dataset from OSFI. I describe how the Canadian banks earn revenue, fund business activities, and pay expenses and a broad overview of the data, accounting rules, and trends in Canadian banking. Chapter two is an in-depth study on cost efficiency and returns to scale (RTS) in Canadian banking, and I estimate a transcendental log cost function for the six largest Canadian commercial banks. To my knowledge, this is the first work to find evidence of constant RTS among the Canadian banks and it is robust to a number of different asset and price specifications. In Chapter three, I compare the U.S. and Canadian banks from 1996 to 2015 and estimate both a trans-log cost function and, for robustness, an input-oriented distance function. Among the ten largest U.S. commercial banks, I find that constant returns to scale best describes the average bank in this period. However, the smaller banks in the sample exhibited increasing RTS but this became exhausted as bank size increased. In Chapter four, I apply a stress test model based on the work of Duarte and Eisenbach (2015) to estimate potential fire-sale losses in the Canadian banking system from 1996 to 2015. I find that the major banks are resilient to all but the most extreme event. This is because (i) Canada has strong macroprudential regulation that improves the quality of assets, (ii) if given a scenario of severe losses, banks retain a sufficient quantity of liquid assets that these could be used to meet short-term liabilities, and (iii) sufficient equity is available to absorb significant losses. However there remain some areas of concern. Using aggregate vulnerability (AV), I find that the Canadian banking system has become more vulnerable to a fire-sale episode since 2011 which could suggest a rising probability of future losses. The concentration of loans-to-households, including residential mortgages and consumer loans, should be of some concern to regulators.
Essays on Regional Recessions, Spatial Interactions and ForecastingShibaev, Sergeihttp://hdl.handle.net/1974/156852017-05-03T18:14:59ZEssays on Regional Recessions, Spatial Interactions and Forecasting
Shibaev, Sergei
This thesis contains three essays spanning the fields of econometrics and empirical
macroeconomics. The first essay develops an econometric procedure that enables
applied researchers to quantify spatial interactions from panel data where variables
exhibit recurrent abrupt shifts in behavior. In empirical macroeconomics, omitting
spatial effects is restrictive in many contexts because the units of analysis are regions,
the characteristics of which are rarely independent. The second essay employs
this methodology to investigate how recessions propagated through small regional
economies in the United States from 1990 to 2015. The empirical results identify
regions that are potentially at risk of collective economic distress, which is useful
for national and regional policy makers. The analysis shows the importance of the
spatial (or geographical) dimension in explaining how regional shocks amplify in the
economy. The third essay, co-authored with Morten Ø. Nielsen, investigates a unique
data set of daily political opinion polls in the United Kingdom from 2010 to 2015.
This work explores the forecasting capabilities of the recently developed fractionally
cointegrated vector auto-regressive (FCVAR) model. The results show that the
FCVAR model delivers superior forecast accuracy relative to a portfolio of existing
alternatives. Furthermore, the forecasts generated by the FCVAR model leading into
the UK 2015 general election provide a more informative assessment of the current
state of public opinion than that suggested by opinion polls.
An Empirical Investigation of the Transmission and Effects of Monetary and Fiscal PoliciesPopiel, Michalhttp://hdl.handle.net/1974/156362017-04-12T07:17:59ZAn Empirical Investigation of the Transmission and Effects of Monetary and Fiscal Policies
Popiel, Michal
Using statistical models, this dissertation investigates the transmission and effects of monetary and fiscal policies in the context of new challenges and environments that emerged following the 2008 global financial crisis. Chapter 2 analyzes an important step in the transmission of monetary policy---the interest rate pass-through from money market rates to consumer retail loan and deposit rates---in Canada from 1983 to 2015 using a nonlinear vector error-correction model. I find that pass-through was complete for all rates before the financial crisis but since the end of the 2008--09 recession, it has significantly declined for deposit rates. Chapter 3, co-authored with Margaux MacDonald, investigates the effects of unconventional monetary policy in Canada. We use recently proposed methods to construct a shadow interest rate that captures monetary policy at the zero lower bound and estimate a small open economy Bayesian structural vector autoregressive model. Controlling for the US macroeconomic and monetary policy variables, we find that Canadian unconventional monetary policy had expansionary effects on the Canadian economy. Chapter 4 shifts focus to fiscal policy. The rise in US partisan conflict following the Great Recession led to a popular belief that uncertainty about fiscal policy was impeding output growth. I explore this hypothesis by nesting it in a standard structural vector autoregression model traditionally used for estimating fiscal multipliers. I augment the model with stochastic volatility (a measure of uncertainty) and allow that to interact with the endogenous variables. I consider various trend assumptions, subsamples, information sets and estimation methods and find that the evidence does not support this hypothesis. The results reveal that there is no systematic relationship between fiscal policy uncertainty and output. Moreover, a time-varying parameter version of the model shows that the lack of consistency across specifications is not driven by changes in the transmission of uncertainty shocks over time.
Keeping Variables within Bounds: Using Information between ObservationsMorin, Lealandhttp://hdl.handle.net/1974/153132017-03-30T14:03:48ZKeeping Variables within Bounds: Using Information between Observations
Morin, Lealand
This research develops an econometric framework to analyze time series processes with bounds. The framework is general enough that it can incorporate several different kinds of bounding information that constrain continuous-time stochastic processes between discretely-sampled observations. It applies to situations in which the process is known to remain within an interval between observations, by way of either a known constraint or through the observation of extreme realizations of the process. The main statistical technique employs the theory of maximum likelihood estimation. This approach leads to the development of the asymptotic distribution theory for the estimation of the parameters in bounded diffusion models.
The results of this analysis present several implications for empirical research. The advantages are realized in the form of efficiency gains, bias reduction and in the flexibility of model specification. A bias arises in the presence of bounding information that is ignored, while it is mitigated within this framework. An efficiency gain arises, in the sense that the statistical methods make use of conditioning information, as revealed by the bounds. Further, the specification of an econometric model can be uncoupled from the restriction to the bounds, leaving the researcher free to model the process near the bound in a way that avoids bias from misspecification.
One byproduct of the improvements in model specification is that the more precise model estimation exposes other sources of misspecification. Some processes reveal themselves to be unlikely candidates for a given diffusion model, once the observations are analyzed in combination with the bounding information. A closer inspection of the theoretical foundation behind diffusion models leads to a more general specification of the model. This approach is used to produce a set of algorithms to make the model computationally feasible and more widely applicable.
Finally, the modeling framework is applied to a series of interest rates, which, for several years, have been constrained by the lower bound of zero. The estimates from a series of diffusion models suggest a substantial difference in estimation results between models that ignore bounds and the framework that takes bounding information into consideration.