Dalibor Stevanović
Biographic Data
| ID | 4414630 |
|---|---|
| NAME | Dalibor Stevanović |
| GIVEN NAMES | Dalibor |
| FAMILY NAME | Stevanović |
| SIGNATURE | STEVANOVIC D |
| AFFILIATIONS | Université du Québec à Montréal |
| ORCID | 0000-0002-0084-4831 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Risk Scenarios and Macroeconomic Impacts: Insights for Canadian Policy
This article analyzes the macroeconomic implications of risk scenarios for the Canadian economy using a vector autoregressive model. We focus on three scenarios: an aggressive monetary policy easing, an unexpected rise in oil prices, and a sudden slowdown in US economic activity. By illustrating how these scenarios would cause the economy to deviate from baseline macroeconomic forecasts, we demonstrate the value for policy-makers of assessing the…
How is machine learning useful for macroeconomic forecasting
We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by adding the how . The current forecasting literature has focused on matching specific variables and horizons with a particularly successful algorithm. To the contrary, we study the usefulness of the underlying features driving ML gains over standard macroeconometric methods. We distinguish four so‐called features (nonlinearities, regularization, cross‐validation, and alter…
Dynamic Effects of Credit Shocks in a Data-Rich Environment
We examine the dynamic effects of credit shocks using a large dataset of U.S. economic and financial indicators in a structural factor model. An identified credit shock resulting in an unanticipated increase in credit spreads causes a large and persistent downturn in indicators of real economic activity, labor market conditions, expectations of future economic conditions, a gradual decline in aggregate price indices, and a decrease in short- and …
Factor-Augmented Varma Models With Macroeconomic Applications
We study the relationship between vector autoregressive moving-average (VARMA) and factor representations of a vector stochastic process. We observe that, in general, vector time series and factors cannot both follow finite-order VAR models. Instead, a VAR factor dynamics induces a VARMA process, while a VAR process entails VARMA factors. We propose to combine factor and VARMA modeling by using factor-augmented VARMA (FAVARMA) models. This approa…
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Factor-Augmented Varma Models With Macroeconomic Applications
We study the relationship between vector autoregressive moving-average (VARMA) and factor representations of a vector stochastic process. We observe that, in general, vector time series and factors cannot both follow finite-order VAR models. Instead, a VAR factor dynamics induces a VARMA process, while a VAR process entails VARMA factors. We propose to combine factor and VARMA modeling by using factor-augmented VARMA (FAVARMA) models. This approa…
Dynamic Effects of Credit Shocks in a Data-Rich Environment
We examine the dynamic effects of credit shocks using a large dataset of U.S. economic and financial indicators in a structural factor model. An identified credit shock resulting in an unanticipated increase in credit spreads causes a large and persistent downturn in indicators of real economic activity, labor market conditions, expectations of future economic conditions, a gradual decline in aggregate price indices, and a decrease in short- and …
How is machine learning useful for macroeconomic forecasting
We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by adding the how . The current forecasting literature has focused on matching specific variables and horizons with a particularly successful algorithm. To the contrary, we study the usefulness of the underlying features driving ML gains over standard macroeconometric methods. We distinguish four so‐called features (nonlinearities, regularization, cross‐validation, and alter…
Risk Scenarios and Macroeconomic Impacts: Insights for Canadian Policy
This article analyzes the macroeconomic implications of risk scenarios for the Canadian economy using a vector autoregressive model. We focus on three scenarios: an aggressive monetary policy easing, an unexpected rise in oil prices, and a sudden slowdown in US economic activity. By illustrating how these scenarios would cause the economy to deviate from baseline macroeconomic forecasts, we demonstrate the value for policy-makers of assessing the…
Monetary Policy and Economic Impact (4 works) · Econometrics (3 works) · Market Dynamics and Volatility (3 works) · Computer Science (2 works) · Economics (2 works) · Mathematics (2 works) · Statistics (2 works) · Applied Mathematics (1 works) · Artificial Intelligence (1 works) · Autoregressive model (1 works)