1. David Givens Sreekanth Venkataraman
Factors determining U.S. natural gas prices post 2008: a Structural VAR analysis delivered to the 36th North American conference of USAEE/IAEE Washington, D.C. September 24, 2018
David Givens
Sreekanth Venkataraman

2. Structural VAR: a framework to sort drivers

3. Overview and summary
Decoupling of crude oil and natural gas followed by shale gale
Structural vector autoregressive model analyzed determinants
Economic reasoning imposed restrictions on model
Study period
Lag criteria test: 1
Impulse response functions on natural gas prices by determinants was consistent with economic reasoning
Only three determinants really count

4. Methodology
Structural vector autoregression model allows for endogeneity of fundamental variables
Monthly data was necessary to include all variables
Matrix for instantaneous interaction among the variables
With the number of lags at one, future values can be predicted among variables
most approaches treat gas inventories exogenous with respect to the natural gas prices.

5. Variables/data Crude oil price Industrial consumption
Natural gas exports
Rig count
Natural gas imports
Storage
Natural gas futures price
BTU price spread
Temperature
Natural gas price
We started by thinking that storage and rig count most significant, futures prices less than in past

6. Economic reasoning for restrictions
Crude Oil Price
Natural Gas Exports
Natural Gas Imports
Natural Gas Futures Price
Temperature
Natural Gas Industrial Consumption
Rig Count
Storage
BTU Price Spread
Natural Gas Price
Crude Oil Price *
Natural Gas Exports
Natural Gas Imports
Natural Gas Futures Price  *
Rig Count
BTU Price Spread
Natural Gas Price
Rows: equations
Columns: Impact of variable in equation
Should there not be a diagonal of zeroes? Perhaps not include. And some are blank. Do highlights?

7. Economic restrictions in contemporaneous matrix
Crude oil price: impact on rig count and BTU price spread, not natural gas price
Natural gas exports: impact on natural gas price
Natural gas futures price: impact on all except the rig count
Natural gas industrial consumption: impact on all variables
Temperature is likely to have a lagged impact on rig count and industrial consumption
Natural gas exports, rig count also likely to have lagged impact on industrial consumption
Do limitations in the matrix affect limitations in the impulse response

8. Results expressed in impulse response
Based on one standard deviation of respective structural shock
The percentage change in the natural gas price over 12 months as a reaction to the standardized shock of the respective variable
Meaningful impact:
Natural gas futures price
Heating degree days
Cooling degree days
Imports

9. HDD impulse response sustained for year
X axis: Percent change in natural gas price as a reaction to the shock
Y axis: Months

10. Gas futures have major impact on gas prices
X axis: Percent change in natural gas price as a reaction to the shock
Y axis: Months

11. CDDs: Reduce price when not cold enough
X axis: Percent change in natural gas price as a reaction to the shock
Y axis: Months

12. When imports rise, prices get a bump
X axis: Percent change in natural gas price as a reaction to the shock
Y axis: Months

13. Forecast Error Variance Decomposition Analysis
Analyzes relative contribution of variables; uses SVAR results
Result is the fraction of gas price variance that can be explained by other variables over 12 month period
Confirmatory
HDDs (negligible month 1, 20% month 12)
Gas futures prices (72% month 1, 35% month 12)
High impact
Rig count (9% month 1, 4% month 12)
Crude oil prices (1% month 1, 21% month 12)

14. Conclusions
Structural VAR finds that cold weather, gas futures and imports have the greatest impact on natural gas prices
Decomposition analysis confirms prominence of HDDs, futures
Natural gas production associated with crude oil should spur reconsideration
Different restrictions on the model should prompt multivariate study including crude oil prices, rig count
Decoupling from oil prices that began a generation ago is critical for policy makers to understand. Here are the other factors.

15. Author contact information
David Givens, head of Natural Gas and Power Services, Argus Media
Telephone: (240)
Sreekanth Venkataraman, consulting economist
Telephone: (518)