DRE 7011 Lecture series on Oil Markets and the Macro Economy
DRE 7011 Lecture series on Oil Markets and the Macro Economy
This is an old course description. Please note that this course will be revised before it is offered again.
After taking this course the students should have a solid knowledge of advanced research in oil market models and the link between oil prices, the macroeconomy and monetary policy.
To model and forecast the oil market, the students should master and be able to produce sophisticated research using a variety of linear and non-linear time series methods.
To analyse the link between the oil market, the macroeconomy and monetary policy, the students will be familiar with, among others, structural vector autoregression (VAR) models and Dynamic stochastic general equilibrium (DSGE) models
Lecture 1:
Alternative Specifications of the Price of Oil
- Key Oil Price Series
- One Price?
- No Oil Price Series is Perfect for all Purposes
- A Statistically Significant Break in 1973
Traditional Interpretations of Oil Price Shocks
- What is an Oil Price Shock?
- Oil Price Shocks Driven by Oil Supply Shocks
- The Crude Oil Market Becomes a Global Market
- What about the Post-1973 Oil Market?
Hypothesis 1: Wars Cause Oil Price Shocks
Hypothesis 2: The Case for Endogenous Oil Prices
Hypothesis 3: The OPEC Cartel Controls Oil Prices
Synthesis
A Structural Model of the Global Market for Crude Oil
- Competing Views of the Global Market for Crude Oil
- Limitations of Traditional Oil Market Models
- Examples of Forward-Looking Elements in Expectations of Oil Demand and Oil Supply
- Key Insights
- A Structural Model of the Oil Market
- Why Do We Not Include the Oil Futures Spread?
- Historical Decompositions for 1978.6-2010.6
- What Explains the 2003-08 Oil Price Surge
- Three Policy Conclusions
- Speculation without a Change in Oil Inventories?
- Digression: The Short-Run Price Elasticity of Oil Demand
Financial Speculation
- The Masters Hypothesis
- Why Do Policymakers Pay So Much Attention?
- What is the Evidence on this Hypothesis?
- What is Speculation?
- The Role of Speculation in Oil Markets
- Speculation versus Excessive Speculation
- What is Excessive Speculation?
Conclusion
- Increased Financialization of Oil Futures Markets
- Do Index Funds Cause Oil Price Increases?
- Do Oil Futures Prices Predict Oil Spot Prices
- Is there a Theoretical Link from Inflows into Index Funds to Higher Spot Prices?
- Did Index Funds Cause the Oil Price-Inventory Relationship to Collapse?
- What Do Structural Oil Markets Tell Us?
- The Role of Time-Varying Risk Premia
- Index Funds and Oil Price Volatility
- What is the Consensus?
Lecture 2:
Forecasting the Real Price of Oil and Quantifying Oil Price Risks
- Background
- Why Real-Time Data Matter
- The Baumeister-Kilian Real-Time Data Set
- Key Parameters for the Forecasting Horserace
- Candidate Models
- Results
- Limitations of Standard Oil Price Forecasts
- Forecast Scenarios
- Examples of Scenarios
- Probability Weighted Real-Time Density Forecasts
- Real-Time Risk Analysis
- Case Study: December 2010.
Lecture 3:
A Review of the Channels of Transmission of Exogenous Oil Price Shocks
Production Channels
Direct Effects
Indirect Effects
Consumption Channels
Direct Effects
Indirect Effects
Summary of the Demand-Side Channels of Transmission
Summary of the Supply-Side Channels of Transmission
Are Macroeconomic Responses Asymmetric in Oil Price Increases and Decreases?
- The Literature on Oil Prices and the Economy
- Asymmetric Models of the Transmission of Oil Price Shocks
- Two Types of Studies in the Literature
- Censored Oil Price VAR Models
- Problems with Estimates of Asymmetric Responses from Censored VAR Models
- A Stylized Static Model
- What if the DGP is a Linear Symmetric VAR?
- What if the DGP Is an Asymmetric Dynamic Model?
- A General Model of the Oil Price-Economy Link
- Computing Asymmetric Responses Properly
- The Standard Approach to Constructing Asymmetric Responses
- How Different is the Traditional Response from the Correctly Computed Response?
Summary
- Testing for Symmetry in the Responses
- Testing Models of Net Energy Price Increases
- Testing Symmetry in Models of Net Energy Price Increases
- Implications for the Literature on the Transmission of Oil Price Shocks
Evidence from (Pseudo) Linear VAR Models
- Two Seeming Puzzles
Summary
- Why Structural Oil Market Models Are Important
Do Oil Prices Forecast Real GDP?
- Using Oil Prices to Forecast Real GDP Growth
- Possible Explanations of the Limited Success of Linear Forecasting Models
- Nonlinear Forecasting Models
Lecture 4:
Monetary Policy Responses to Oil Price Fluctuations
- The Central Message
- This Insight is Not New
- Policy Makers Have Been Slow to Accept This Point
Oil Prices and Monetary Policy: A Review
- The Monetary Policy Regime Shifts Hypothesis
- The Monetary Policy Reaction Hypothesis
The Bernanke, Gertler, and Watson (1997) Model
Towards a New Class of Structural Models
An Open Economy DSGE Analysis of Policy Responses with Endogenous Oil Prices
Empirical Results
Welfare Analysis
Conclusions
Extensions
A course of 3 ECTS credits corresponds to a workload of 80-90 hours.
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class that is not included on the course homepage/It's learning or text book.
Enrollment in a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or conformation letters will not be issued for sitting in on courses.
| Assessments |
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Exam category: Submission Form of assessment: Written submission Weight: 100 Grouping: Individual Duration: 1 Semester(s) Exam code: DRE70111 Grading scale: Pass/fail Resit: All components must, as a main rule, be retaken during next scheduled course |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 3 ECTS credit corresponds to a workload of at least 80 hours.