1. Relevance of global oil market: shocks with significant influence in the economic growth and inflation worldwide.

2. Relevance of Elasticities of supply an demand: they are crucial to determine the magnitude and duration of the shocks in the global oil market.

3. Relevance of inventories oil inventories:

   • Act as a buffer against uncertainties
   • Serve as an assets in the financial markets

4. Inventories have been treated as speculative component of the demand but

   • … do they have the same features and cause the same effects in the whole market?
   • … are they traded by the same agents with the same motives?
   • … do they have also effects in the global oil supply?
   • … what would be the consequences for the equilibrium?

1. Propose a theoretical model for the global oil market where there are two types of inventories: strategics and speculatives.

2. This new theoretical framework helps in the identification of a SVAR.

3. New evidence from inventories reported in financial accounts by 820 companies in the oil industry, 70% of which are commercial traders and 30% are financial investors.

4. Exploit different features of the agents accumulating inventories in an attempt to improve estimation of the elasticities of oil supply and oil demand.

1. Discrimination by strategic and speculative inventories has significant effects on impulse response function.

2. Impulse responses show a more persistent increase in the price of oil after oil supply shock than implied by previous estimates.

3. Impulse responses show a more persistent increase in the price of oil after oil supply shock than implied by previous estimates.

4. By contrast, demand shocks cause more transitory changes in the price of oil.

5. Moreover, only supply and global demand shocks cause persistent changes in the oil production.

1. Kilian, L. (2009). Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market. American Economic Review, 99(3), 1053–1069. 1666 citations.

2. Kilian, L., & Murphy, D. P. (2012). Why agnostic sign restrictions are not enough: Understanding the dynamics of oil market var models. Journal of the European Economic Association, 10(5), 1166–1188. 183 citations.

3. Baumeister, C., & Peersman, G. (2013a). The role of time-varying price elasticities in accounting for volatiltity changes in the crude oil market. Journal of Applied Econometrics, 28, 1087–1109. https://doi.org/10.1002/jae. 166 citations.

4. Baumeister, C., & Peersman, G. (2013b). Time-Varying Effects of Oil Supply Shocks on the US Economy. American Economic Journal: Macroeconomics, 5(4), 1–28. Retrieved from http://www.aeaweb.org/articles.php?doi=10.1257/mac.5.4.1

5. Kilian, L., & Murphy, D. P. (2014). The role of inventories and speculative trading in the global market for crude oil. Journal of Applied Econometrics, 29, 454–478. https://doi.org/10.1002/jae. 473 citations.

6. Baumeister, C., & Hamilton, J. D. (2015). Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information. Econometrica, 83(5), 1963–1999. https://doi.org/10.3982/ECTA12356. 99 citations.

7. Baumeister, C., & Hamilton, J. D. (2019). Structural interpretation of vector autoregressions with incomplete identifcation: Revisiting the role of oil supply and demand shocks. American Economic Review, 109(5), 1873–1910. https://doi.org/10.1257/aer.20151569. 154 citations.

8. Caldara, D., Cavallo, M., & Iacoviello, M. (2019). Oil price elasticities and oil price fluctuations. Journal of Monetary Economics, 103, 1–20. https://doi.org/10.1016/j.jmoneco.2018.08.004. 69 citations.

9. Herrera, A. M., & Rangaraju, S. K. (2020). The effect of oil supply shocks on US economic activity: What have we learned? Journal of Applied Econometrics, 35(2), 141–159. https://doi.org/10.1002/jae.2735. 23 citations.

10. Kilian, L. (2022). Understanding the estimation of oil demand and oil supply elasticities. Energy Economics, 107, 105844. https://doi.org/10.1016/J.ENECO.2022.105844

• \(\Delta i_t:\) log-change in inventories.
  

• \(\Delta i_t^{ct}:\) log-change in inventories of commerical traders.
  

• \(\Delta i_t^{fi}:\) log-change in inventories of financial investors.
  
  

  • Commercial traders: Big oil integrated companies or companies operating in the upstream segment of the oil industry.
    
  • Financial investors: Midstream or downstream segment of the oil industry diversify their portfolio by accumulating oil inventories.

\(\mathbf{y}_t = (\Delta q_t, y_t, p_t, \Delta i_t^{ct}, \Delta i_t^{fi})'\)

\(y_t = \alpha_{yq}\Delta q_t + \alpha_{yp}p_t + \alpha_{yc}\Delta i_t^{ct} + \alpha_{yf}\Delta i_t^{fi} + \mathbf{b_2^{'}y_{t-1}} + u_{2t}\)

\(p_t = \alpha_{pq}\Delta q_t + \alpha_{py}y_t + \alpha_{pc}\Delta i_t^{ct} + \alpha_{pf}\Delta i_t^{fi} + \mathbf{b_3^{'}y_{t-1}} + u_{3t}\)

\(\Delta i_t^{ct} = \alpha_{cq}\Delta q_t + \alpha_{cy}y_t + \alpha_{cp}p_t + \alpha_{cf}\Delta i_t^{fi} + \mathbf{b_4^{'}y_{t-1}} + u_{4t}\)

1. Including more disaggregated data on inventories could explain the inverse relationship in the estimation of elasticities in the global oil market.

2. It seems to be important to consider two different agents accumulating inventories for different motives.

3. This approach could explain more accurately the narrative evidence of the adjustment in the oil market via mainly prices.

4. This approach is compatible with the storage theory and could help to explain the seemingly conflicting findings in the recent literature of oil shocks.

5. This mechanism could also help to explain the conflict in some literature between the buffering and speculating role of oil inventories.