Asymmetries in the oil priceindustrial production relationship? Evidence from 18 OECD countries

Transcription

1 Asmmeries in he oil priceindusrial producion relaionship? Evidence from 8 OECD counries Ana María Herrera Laika Lagalo Tasuma Wada Wane Sae Universi

2 Moivaion Is he relaionship beween economic acivi and oil prices linear? Do oil price increases lead o recessions bu decreases do no resul in booms? A large volume of lieraure argues he relaionship is asmmeric: Mork (989): oil price increases lead o recession while oil price decreases don lead o expansions. Hamilon (996, 2003) and Li, Ni and Rai (995): oher nonlinear ransformaions of oil prices do a beer job a capuring he nonlineari of he relaion: Wh is his asmmer imporan? Amplificaion of oil price shocks

3 Moivaion The imporance of accouning for asmmeries in he relaionship beween changes in energ price and macroeconomic aggregaes seemed o be widel agreed on b he earl 2000s. I has been common in he lieraure o esimae VAR models of he form x # = = A A 2 # ( L) x + A2( L) + ε, # ( L) x + A ( L) + ε 22 2, Censored variables have been commonl used in he lieraure o sud he effec of oil price shocks.

4 Daa Censoring Oil Prices Le o be he Refiners' Acquisiion Cos measured in he local currenc. Mork's (989) oil price increase x { 0,ln( o ) ln( o )} = max 2. Hamilon (996) ne oil price increase over he previous 2-monh maximum x 2 { 0,ln( o ) max( ln( o ),,ln( o ))} = max 2 3. Hamilon (2003) ne oil price increase over he previous 36-monh maximum x 36 { 0,ln( o ) max( ln( o ),,ln( o ))} = max 36

5 Censored Oil Prices

6 Moivaion Killian and Vigfusson (QE, 20) show ha: Using a censored variable biases he esimaes IRF esimaes exaggerae he macroeconomic responses o oil price shocks. If a rue linear model is misakenl esimaed as a nonlinear model asmmer in responses of macroeconomic aggregaes is arificiall creaed. If he rue relaionship is non-linear, bu one esimaes a linear specificaion, hen he esimaed parameers are asmpoicall biased.

7 Moivaion Ye: Evidence of asmmer is dependen on: Oil measure (Hamilon 20) Sample period (Kilian and Vigfusson 20, Herrera, Lagalo and Wada 20) I is imporan o consider large shocks Moreover

8 Conribuion The discussion regarding nonlineariies has focused on US daa. GDP growh (Kilian and Vigfusson 200, Hamilon 200) Growh of he IP index (Herrera, Lagalo and Wada, 20) No work has been done addressing he quesion of asmmer in he IRF using inernaional daa.

9 Conribuion II Propose a measure of asmmer mean squared disance We compue daa mining robus criical values Our mehodolog can be applied o a varie of cases.

10 Daa: IP indices for OECD Samples for some counries sar in he 960s. Ye, we use pos-973 Counr Sample period Ausria 96:-200:7 Belgium 96:-200:7 Canada 96:-200:7 Finland 96:-200:7 France 96:-200:7 German 96:-200:7 Ial 96:-200:7 Japan 96:-200:7 Luxemburg 96:-200:7 Neherlands 96:-200:7 Norwa 96:-200:7 Porugal 96:-200:7 Sweden 96:-200:7 UK 96:-200:7 US 96:-200:7 G7 96:-200:7 OECD-Europe 96:-200:7 Greece 962:-200:7 Spain 965:-200:7 Denmark 974:-200:7 OECD-Toal 975:-200:7

11 Wh he shif owards inernaional daa? Three reasons wh his daa se is a good esing ground for he issue of smmer.

12 . Imporance of oil producion in GDP

13 2. Oil Imporers vs. Oil Exporers

14 3. Energ inensi in consumpion

15 3. Energ inensi Oil exporers

16 3. Energ inensi G7

17 Ouline of his alk Moivaion Relaed Lieraure Theoreical Background Tess of Asmmer or Nonlineari Slope based ess of non lineari Impulse-response funcion based es The Magniude of he Asmmer The Effec of Daa Mining Conclusions

18 Relaed Lieraure Oil imporer/exporer: In a sample of 7 OECD counries, all bu Norwa show negaive correlaions beween oil prices and he macro aggregae (Mork, Olsen and Msen 994). Manufacuring oupu responds o oil price shocks differenl across counries in France, Ial, Spain and German bu similarl in he U.K. and he U.S. (Jiménez-Rodríguez, 2009).

19 Theoreical Background The ransmission of oil price shocks:. Suppl-side effecs Direc effec of an increase in oil prices on energ use and oupu Indirec effec of capial and labor reallocaion 2. Demand-side effecs Direc effec of income ransfer and consequen effec on purchasing power Indirec effec of heighened uncerain

20 . Suppl-side effecs The Direc Effec Consider a represenaive firm ha uses capial, labor and energ in producion hen, i can be shown ha Moreover, if K and L are fixed hen ( ) E L K F,, P P p Y E E Y = Y E p E E E Y E = = where, ε E p p E Y p p Y E E E Y E E =, ε

21 . Suppl-side effecs The Direc Effec Effec is smmeric and bounded b he share of energ in oupu

22 . Suppl-side effecs Indirec Effecs: reallocaion of capial and labor Akeson and Kehoe (999)P: pu-cla capial Finn (2000): capial uilizaion ha changes wih energ Leduc and Sill (2004): adding wage rigidiies These models generae amplificaion bu NO asmmer.

23 . Suppl-side effecs Indirec Effecs: reallocaion disurbances Secoral Reallocaion (Davis 987a, Davis 987b, Bresnahan and Rame 993, and Davis and Haliwanger, 200) Slow relocaion of workers (Hamilon 988) These models generae amplificaion AND asmmer.

24 2. Demand-side effecs The Direc Effec: income ransfer from oil imporing o oil exporing counries This effec is smmeric and bounded. Indirec effecs: Heighened uncerain (Bernanke 983, Pindck 99) Change in he composiion of demand (Rame and Vine 200) Change in purchasing power and precauionar saving (Edelsein and Kilian, 2009) These effecs generae amplificaion AND asmmer.

25 2. Oil Imporers vs. Oil Exporers Direcion and magniude of he asmmer?

26 Sources of asmmeries and heir effec on oupu growh Oil Imporers Oil Exporers Sign of oil price shock +δ -δ +δ -δ. Suppl-side effecs Direc effec - +?? Indirec effecs Reallocaion of K and L Reallocaion disurbances Demand-side effecs Direc effec Indirec effecs Heighened uncerain Changes in he composiion of demand Precauionar demand

27 VAR Model Kilian and Vigfusson's (200) srucural VAR (nesing linear and non-linear models): x i, where x x ε i, #, = = a 0 a 20 + :is he log growh in he IP index rfor counr i :is he log growh in he real oil price :is one of and ε 2, 2 + j= 2 a j= 0, j a x 2, j j x j j= 2 j= he non - linear measures of are orhogonal 2, j 22, j i, j i, j price change Oil price shocks have conemporaneous effec on IP Oil prices are assumed o be predeermined. a a + ε +, 2 j= 0 g oil 2, j x # j + ε 2,

28 . Slope based es Problem: We don' know he link beween a rejecion of H₀ and he degree of asmmer in he response o a shock. Therefore, we do no use he slope es o evaluae asmmer in he response.

29 2. KV Impulse-response-based es Do impulse-responses exhibi asmmer? Due o he censored variables, impulse responses depend on: The magniude of he shock The hisor of he observaions compuing impulse responses requires Mone Carlo inegraion (Koop e al 996).

30 2. KV Impulse-response-based es x i, where x x ε i, #, = = a 0 a 20 + :is he log growh in he IP index rfor counr i :is he log growh in he real oil price :is one of he non - linear measures of oil price change and ε 2, 2 + j= 2 a j= 0, j a x 2, j j x j j= 2 j= are orhogonal a 2, j a 22, j i, j i, j + ε +, 2 j= 0 g 2, j x # j + ε 2,

31 2. KV Impulse-response-based es Seps: (i) For a given horizon, h, condiional on he hisor Ω, and he size of he shock δ, he condiional IRFs, I (h,δ,ω ) can be compued: a),r ¹ is he pah of afer he shock δ,r ² is he pah of afer ɛ b) Afer R replicaions, ( ) ( ) [ ] [ ] Ω Ω Ω = = Ω + + = = R as E E h I where H h for R R h I h h p R r r R r r,,,., 0,,,, 2,, δ δ δ

32 2. KV Impulse-response-based es (ii) The uncondiional IRF is generaed b repeaing () for all possible Ω, =,,T and hen aking he mean over all he hisories: I T T ( ) ( h, δ = I Ω ) h, δ, = (iii) The es of smmer is ( h, δ ) = I ( h, δ ) for h = 0,,2,,. H 0 : I H

33 2. KV Impulse-response-based es The es saisic is given b ( ) ( ) ( ) ( ) ( ) ( ) ( ) [ ] ( ) ( ) ( )( ) = Ξ = = Ξ ' H - ˆ ˆ ;, 0,, 0, ˆ ~ (R ˆ) ) W = (R ˆ)'(R ˆ R' β β β β δ δ δ δ β χ β β E I I R H I I H I I where H H H H H H H

34 2. KV Impulse-response-based es Small Shock Large Shock -monh 2-monh 36-monh -monh 2-monh 36-monh Ne Exporers Canada Denmark Norwa UK Ne Imporers Ausria Belgium Finland France German Greece Ial Japan Luxembourg Neherlands Porugal Spain Sweden US Aggregaes G7 OECD-Europe OECD-Toal or more 6 or more

35 2. Impulse-response-based es Small shocks: Resuls for x and x 2 sugges asmmeries mainl for: Large oil exporing: Canada and Norwa Large oil imporing: US and Japan Large shocks: Resuls for x (more grounded on heor han on behavioral model) sugges asmmeries for Large oil exporing: Canada and Norwa Large oil imporing: US and Japan Plus some oher counries (Finland, German, and Greece)

36 The Magniude of he Asmmer How big is he difference beween he response of indusrial producion o posiive and negaive shocks? 2 Exporers: Afer a ear, a posiive shock of s.d. leads o a conracion of indusrial producion of 0.6% in Canada and.3% in Norwa. A negaive shock of he same magniude would resul in a 0.7% conracion in Canada, bu no change in Norwa. For he larges oil imporer:

37

38 The Magniude of he Asmmer We define he mean squared disance beween he response o a posiive shock and ha of a negaive shock as d = H H ( h, δ ) I ( h, δ ) [ I ( )] h= 0 2

39 The Magniude of he Asmmer Small Shock Large Shock -monh 2-monh 36-monh -monh 2-monh 36-monh Ne Exporers Canada Denmark Norwa UK Ne Imporers Ausria Belgium Finland France German Greece Ial Japan Luxembourg Neherlands Porugal Spain Sweden US Aggregaes G OECD-Europe OECD-Toal

40 The Effec of Daa Mining Our purpose: o es for smmer in a counr-b-counr basis We use 2 Wald ess for each h and each oil price measure, hus he resuls are subjec o daa mining

41 The Effec of Daa Mining Daa Mining: Insead of rolling he forecas, we add counries

42 The Effec of Daa Mining Using he OLS residuals ε and ε 2, ogeher wih he esimaed parameers, we generae 00 ses of pseudo-daa: {(x i, i )} i=:2 For each daa se {(x i, i )} i=:2 we conduc he IRF based-es and ake he supremum of he Wald saisic across all counries. Compue he disribuion of Sup-Wald and he 5% criical values.

43 The Effec of Daa Mining We see ver few rejecions. No clear wheher his resul is due o: True effec of daa mining Low power of he es (small sample) Small number of replicaions

44 Conclusions We find some evidence of asmmer for abou half of he counries In general, he linear model is suiable for gauging he impac of small oil price shocks. Care mus be aken when considering large oil price shocks. Especiall for counries: Oil exporers where oil represens a large percenage of GDP Large oil imporers

45 Conclusions The fac ha evidence of asmmer is more prevalen for he oil price increase han he ne increase sugges ransmission mechanisms a pla are: Reallocaion disurbances Heighened uncerain Changes in he composiion of demand Ye

46 Conclusions Afer using he daa mining robus criical values, however, almos no rejecions are found. Quesion sill o be answered: Power of he es