catalysts and inhibitors of the trade collapse mattia di ubaldo university of sussex, phd conference...
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Catalysts and Inhibitors of the Trade Collapse
Mattia Di Ubaldo
University of Sussex, PhD Conference5th of December 2014
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Mattia Di Ubaldo, University of Sussex
Motivation & Context - 1
29/10/2014 2
The Slovenian ExperienceGrowth of GDP Growth of trade
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Mattia Di Ubaldo, University of Sussex 3
Motivation & Context - 2
• Causes of trade collapse:
• Supply side • Credit crunch – working capital (Bricongne et al., JIE 2012; Chor &
Manova, JIE 2012; Behrens et al., RES 2013).• Trade finance – bank or firm intermediated (Korinek et al., 2010;
Malouche, 2011; Antràs & Foley, JPE 2014).
• Demand side• Decrease in expenditure – composition (Engel & Wang, JIE 2009; Eaton
et al., 2011; Petropoulou & Soo, 2011).• Vertical linkages (Levchenko et al., IMF review 2010, Bems et al., AER
2011).• Inventory adjustments (Alessandria et al., AER 2010).29/10/2014
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Mattia Di Ubaldo, University of Sussex 4
ContributionMy analysis: factors that amplified or dampened the reaction of trade.
• Most of the action was in GVCs! Intermediates:• 2/3 of total trade (Bems et al., 2011).• 11/15 most affected sectors (Bricongne et al. 2012).
1. Analyse the reaction of different inputs, depending on the cost-share in firms’ sales.
2. Explore the reaction of inputs along Intra-Firm vs Arm’s Length trade dimension: one WP so far (Altomonte et al. 2012), but I add:• Cost-share of inputs.
• Intensive and Extensive margins.
• Firm fixed effects and additional firm controls.
3. Detailed intensive/extensive (firm, destination, product) margins decomposition.• New across Intra-firm vs Arm’s Length trade.
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Mattia Di Ubaldo, University of Sussex 5
Preview of findings
1. Cost-share of imported inputs in sales:• Higher cost share, larger reaction (but Intra-Firm dampens).
2. Firm affiliation – Intra-firm (RP) versus arm’s length (AL) trade.• No different performance.
3. Intensive vs Extensive margin
• 70% Intensive margin; larger intensive margin share for RP.
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Mattia Di Ubaldo, University of Sussex 6
Outline
•Data and sample.
•Hypotheses.
•Methodology.
•Results.
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Mattia Di Ubaldo, University of Sussex 7
Data and Sample
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Mattia Di Ubaldo, University of Sussex 8
Data• Slovenia: why?
• small, open economy. • strongly integrated with both eastern and western European
countries: intermediates 72% of imports.
• Transaction-level trade data (SURS): monthly exports/imports at the
CN-8 digits product level (xickt); 2000-2011.
• Firm Balance Sheet data (AJPES): balance sheet and income statements of all Slovenian firms; 2000-2011.
• Ownership data (Bureau Van Dijk): ORBIS allows to track all the proprietary network, on a world scale, up to the 10th level of subsidiarity.
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Mattia Di Ubaldo, University of Sussex 9
Intra-firm (RP) trade proxy• I need to infer whether shipments are RP or AL: • I assume that transactions are RP when there is an affiliate in the
destination they are directed to. 88% of trade by affiliates to a certain destination is either pure RP or pure AL (Bas & Carluccio 2009),
• This inflates RP trade proxy when firms adopt a mixed strategy; but it’s a classification mistake working against me.
• 49% exports are RP in Slovenia in 2007: • 47% in US (US Census Bureau data)
• 52.6% exports to US are RP – Slovenian data; 51.3% – Census Bureau data (Lanz & Miroudot, 2011).29/10/2014
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Mattia Di Ubaldo, University of Sussex 10
Timing and Sample
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Timing
October 2008 – May 2010; trough in November 2009.
Final sample
Exporters 9,238
NACE-4dig sectors
462
Products 7,350
median 58; mean 136
Destinations 199 median 10; mean 16
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Mattia Di Ubaldo, University of Sussex 11
Hypotheses
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Mattia Di Ubaldo, University of Sussex 12
• Inventory adjustments were observed to have amplified the reaction of trade (Alessandria et al. 2010). GVC ideal locus!
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2nd Hypothesis : RP trade of intermediates is more resilient than AL trade .Why? For RP trade:• Lower uncertainty• Shorter delivery lags Lower buffer of inventories
Lower adjustments!• Better communication
.
Hypotheses – 1 and 2
Why? Inventories of higher cost share inputs get adjusted more promptly, if inventories management costs are proportional to the cost share of inputs.
Larger adjustments!
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Mattia Di Ubaldo, University of Sussex 13
Hypotheses – 3 and 4.
3rd Hypothesis: intermediates’ inventories adjustment generate a Bullwhip Effect: this is exacerbated by the cost share in sales.
• The reaction of RP and AL trade can differ across trade margins:In a crisis, different sunk costs, market rigidities and hold-up problem would cause:
4th Hypothesis: intensive margin adjustments are more pronounced for RP trade than for AL trade; vice-versa for extensive margin adjustments.
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Why? Inventories accelerator mechanism!
Why? Firms might more easily reduce the size of shipments to affiliates rather than to non-affiliates. Extensive margin changes could happen more
at AL.
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Mattia Di Ubaldo, University of Sussex 14
Methodology
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Mattia Di Ubaldo, University of Sussex 15
Methodology
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ickti210ickt εγrecoveryΩ*αΩααg
ickt5iy4iktkicktikticktkickt
k3ikt2ickt1
ExYugβXβRP*CS*IntRP*IntCS*Int
CSβRPβIntβΩ
321 δδδ
)x0.5(x
xxg
12)ick(tickt
12)ick(ticktickt
2007
2000y
N
1i iy
12
1t icktk Y
im
NY1
CS
Dep. var.:
Hypothesis 1
Hypothesis 2
Hypothesis 3
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Mattia Di Ubaldo, University of Sussex 16
Results
Estimations
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RP trade and Cost Share (Hyp. 1 and 2):(1) (2) (3) (4) (5) (6) (7)
Int. 0.0389*** 0.0389*** 0.0559*** 0.0588*** 0.0612***
(3.04) (3.79) (4.62) (4.78) (4.97)
RP -0.0448 -0.0465 -0.0482 -0.0480 -0.0616*
(-1.39) (-1.25) (-1.26) (-1.26) (-1.64)
CS -0.00391 -0.00156 -0.000922 -0.0104
(-0.70) (-0.29) (-0.17) (-0.27)
Int. * RP 0.00166 0.000918 -0.00934 -0.0104
(0.05) (0.02) (-0.24) (-0.27)
Int. * CS -0.178 -0.287* -0.306**
(-1.26) (-1.95) (-2.10)
Int. * CS * RP
0.380* 0.356
(1.62) (1.54)
Ex Yug. -0.106***
(-4.05)
Firm FE yes yes yes yes yes yes yes
Firm Controls
yes yes yes yes yes yes yes
N 1,636,936 1,636,936 1,636,936 1,636,936 1,636,936 1,636,936 1,636,936Note: t statistics arising from robust standard errors clustered at the firm level in parentheses; * p < 0.10, ** p < 0.05, *** p < 0.01.
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Mattia Di Ubaldo, University of Sussex 18
Results: sector-product CS variable
• Sectoral disaggregation of the product level CS variable:
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(1) (2) (3)
Int. 0.0607*** 0.0633***
(5.31) (5.48)
RP -0.0468 -0.0612
(-1.16) (-1.55)
CS-SECT 0.000588 0.000871 0.000858
(0.74) (1.12) (1.09)
Int. * RP -0.00944 -0.0108
(-0.23) (-0.26)
Int. * CS-SECT -0.125** -0.143**
(-2.20) (-2.27)
Int. * CS-SECT * RP
0.000236
(0.00)
Firm FE yes yes yes
Firm Controls yes yes yes
N 1,554,771 1,554,771 1,554,771
2007
2000y
N
1i ijy
12
1t ijcktk Y
im
NY1
CSj
Note: t statistics arising from robust standard errors clustered at the firm level in parentheses; * p < 0.10, ** p < 0.05, *** p <
0.01.
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Hypothesis 3: Bullwhip(1) (2) (3)
Int. 0.0113 0.0234
(0.72) (1.44)
CS -0.00855 -0.00636
(-1.20) (-0.90)
Int. * CS -0.294**
(-2.05)
Int. * Rec 0.0958*** 0.0864***
(3.59) (3.24)
CS * Rec. 0.0157 0.0167
(1.09) (1.16)
Int. * CS * Rec.
0.401**
(2.31)
Firm FE yes yes yes
Firm Controls yes yes yes
N 1,636,936 1,636,936 1,636,936Note: t statistics arising from robust standard errors clustered at the firm level in parentheses; * p < 0.10, ** p < 0.05, *** p <
0.01.
Downturn
Recovery
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Mattia Di Ubaldo, University of Sussex 20
Results
Margin decomposition
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Mattia Di Ubaldo, University of Sussex 21
Margin decomposition -2
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Decomposition of growth of exports: net intensive and net extensive margin contributions
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Mattia Di Ubaldo, University of Sussex 2229/10/2014
Intensive/Extensive margin decomposition (in %):RP vs AL trade
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Mattia Di Ubaldo, University of Sussex 23
Conclusion
• This work adds to the study of the trade collapse by finding:
• RP trade reacted more at the intensive margin, compared to AL trade; but no significant difference overall.
• A higher cost-share of inputs induced a larger reaction of trade.
• Especially larger fall in downturn.
• CS heterogeneity allows to discover:
• Dampening impact of RP trade, relative to AL trade.
• Bullwhip effect.29/10/2014
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Mattia Di Ubaldo, University of Sussex 24
THANK YOU!
29/10/2014
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Mattia Di Ubaldo, University of Sussex 25
RP trade and Cost Share (Hyp. 1 and 2):
• Impact of Cost Share of inputs and RP trade on growth rate of export of intermediates.
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Mattia Di Ubaldo, University of Sussex 26
Exports over the crisis
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Growth of Exports, with “contributions” of RP and AL trade to overall variation.
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Mattia Di Ubaldo, University of Sussex 27
Hypotheses – 5 and 6. Trade finance.
• Trade finance (bank intermediated) became more expensive in the
crisis:5th Hypothesis: greater reliance on firm intermediated trade finance
induced a better trade performance.
6th Hypothesis: greater reliance on firm intermediated trade finance induced a better trade performance for RP trade, relative to AL trade.
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Why? Firm intermediated trade credit should be easier between related parties.
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Mattia Di Ubaldo, University of Sussex 28
Methodology
29/10/2014
ickti10ickt εγΩααg
ickt5iy4icktiyiy
ickt2ickt1
ExYugβXβRP*TCTC
RPβIntβΩ
6δδ5
)x0.5(x
xxg
12)ick(tickt
12)ick(ticktickt
Dep. var.:
Hypothesis 5
Hypothesis 6
1y
1yiy sales
sreceivableTC
ijy
ijyN
1n
2007
2000yj sales
sreceivable
NY1
TC
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Mattia Di Ubaldo, University of Sussex 29
Results – hypothesis 4 and 5: trade finance
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(1) (2) (3) (4) (5)
TC-SECT 0 0 TC-FIRM 0.0461* 0.0347 0.0350
- - (1.62) (1.38) (1.36)
RP -0.0670** RP -0.0843* -0.0618
(-2.37) (-1.78) (-0.77)
TC-SECT * RP 0.00312*** 0.00318*** TC-FIRM * RP 0.162 0.0827
(7.41) (9.65) (1.40) (0.36)
Int. * TC-SECT * RP
-0.000752 Int. * TC-FIRM* RP
0.119
(-1.11) (0.56)
Firm FE yes yes Firm FE yes yes yes
Firm Controls yes yes Firm Controls yes yes yes
N 1,661,136 1,661,136 N 1,661,075 1,661,075 1,661,075
Note: t statistics arising from robust standard errors clustered at the firm level in parentheses; * p < 0.10, ** p < 0.05, *** p < 0.01.
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Results – hypothesis 4 and 5: trade finance
• Impact of Receivables and RP trade on growth rate of exports.
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Larger reliance on trade
credit was associated to a
better trade
performance, with an
additional premium
detected to RP trade.
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Results – all hypotheses together(1) (3) (4)
Int. 0.0575*** Int. 0.0620***
(4.62) (3.94)
RP -0.0786*** RP -0.0465
(-2.61) (-1.25)
CS -0.00106 CS -0.000265
(-0.20) (-0.05)
TC-SECT 0 TC-FIRM 0.0321
(.) (1.18)
Int. * CS -0.287** Int. * CS -0.287**
(-1.95) (-1.96)
Int. * CS * RP 0.381* Int. * CS * RP 0.386*
(1.63) (1.65)
TC-SECT * RP 0.00330*** TC-FIRM * RP 0.0145
(9.31) (0.06)
Int.*TC-SECT*RP
-0.000947 Int.*TC-FIRM*RP
0.192
(-1.38) (0.81)
Firm FE yes Firm FE yes
Firm Controls yes Firm Controls yes
N 1,636,936 N 1,636,875
Note: t statistics arising from robust standard errors clustered at the firm level in parentheses; * p < 0.10, ** p < 0.05, *** p < 0.01.
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Margin decomposition -1
• Methodology (Bricongne et al., 2012).I decompose mid-point growth rates:
Extensive margin: created (gickt =2) and destroyed flows (gickt =-2)Intensive margin: increased (0< gickt <2) and decreased flows (-2< gickt <0)
Weight each flow by its share in total Slovenian exports:
Aggregate subsets of the weighted mid-point growth rates to obtain the margins, since the aggregate year on year total growth rate can be correctly approximated by:
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)x0.5(x
xxg
12)ick(tickt
12)ick(ticktickt
i c i c k 12)ick(tk ickt
12)ick(ticktickt xx
xxs
c i k ickticktt s*gG
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Mattia Di Ubaldo, University of Sussex 33
Margin decomposition -3
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Decomposition of growth of exports: detailed extensive margin contributions
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Mattia Di Ubaldo, University of Sussex 34
Margin decomposition -5
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Mattia Di Ubaldo, University of Sussex 35
Margin decomposition -4
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