C51 - Model Construction and Estimation
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Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models
This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models. -
Sectoral Uncertainty
We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a disaggregated industrial production series for the US economy. We identify unexpected changes in durable goods uncertainty as drivers of downturns, while unexpected hikes in non-durable goods uncertainty are expansionary. -
Comparison of Bayesian and Sample Theory Parametric and Semiparametric Binary Response Models
We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models. -
Equilibrium in Two-Sided Markets for Payments: Consumer Awareness and the Welfare Cost of the Interchange Fee
We construct and estimate a structural two-stage model of equilibrium in a market for payments in order to quantify the network externalities and identify the main determinants of consumer and merchant decisions. -
Demand for Payment Services and Consumer Welfare: The Introduction of a Central Bank Digital Currency
Using a two-stage model, we study the determinants of Canadian consumers’ choices of payment method at the point of sale. We estimate consumer preferences and adoption costs for various combinations of payment methods. We analyze how introducing a central bank digital currency would affect the market equilibrium. -
The Simple Economics of Global Fuel Consumption
This paper presents a structural framework of the global oil market that relies on information on global fuel consumption to identify flow demand for oil. We show that under mild identifying assumptions, data on global fuel consumption help to provide comparatively sharp insights on elasticities and other key structural parameters of the global oil market. -
Explaining the Interplay Between Merchant Acceptance and Consumer Adoption in Two-Sided Markets for Payment Methods
Recent consumer and merchant surveys show a decrease in the use of cash at the point of sale. Increasingly, consumers and merchants have access to a growing array of payment innovations as substitutes for cash. -
Characterizing the Canadian Financial Cycle with Frequency Filtering Approaches
In this note, I use two multivariate frequency filtering approaches to characterize the Canadian financial cycle by capturing fluctuations in the underlying variables with respect to a long-term trend. The first approach is a dynamically weighted composite, and the second is a stochastic cycle model. -
State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models
Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood.