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Motivation
Method
Conclusions
Productivity Spillovers in the GVC
The Case of Poland and the New EU Member States
Jan Hagemejer
Narodowy Bank Polski
University of Warsaw
September 10, 2016
The views presented here are those of the author and not necessarily of the National Bank of Poland. I greatly
acknowledge the nancing by the National Science Centre, grant no: UMO- 2013/09/D/HS4/01519.
Hagemejer Productivity  GVC
Motivation
Method
Conclusions
Outline
1 Motivation
Introduction
Literature
2 Method
Outline
GVC measures
Foreign ownership premium
Spillovers and GVC
3 Conclusions
Hagemejer Productivity  GVC
Motivation
Method
Conclusions
Introduction
Literature
Why?
Ongoing internationalization of New Member States economies due
to:
transition
EU integration
involvement in the GVC
Internationalization is believed to have important direct and indirect
eects on rm productivity
through selection eects (export related)
through FDI hosting
through FDI productivity spillovers
FDI  exports are already well established in the literature - but to
what extent participation in GVC and the position in the production
chain matters for productivity?
Hagemejer Productivity  GVC
Motivation
Method
Conclusions
Introduction
Literature
Why GVC?
Emerging economies compete for a good placement in the GVCs.
This motivates rms to restructure and reorganize.
Inclusion in GVC may involve:
adoption of high quality standards
adoption of modern technology
adoption of modern management techniques
The smile curve debate? Ye, Meng, and Wei (2015), Kowalski et al.
(2015) or Cheng et al. (2015). Is the distribution of gains uniform
along the GVC? Is it good to be close to the nal demand?
Hagemejer Productivity  GVC
Motivation
Method
Conclusions
Introduction
Literature
Literature
FDI spillover literature is already abundant.
Most studies follow the Sma»y«ska-Javorcik (2004) method based
on rm-level data and input output tables. Other notable works
Haddad and Harrison (1993), Aitken and Harrison (1999), Djankov
and Hoekman (2000) or Konings (2001).
Own sector eects, backward and forward eects.
Review can be found in Crespo, Fontoura, and Proenca (2009)
Irsova and Havranek (2013) analyse more than a 1000 of FDI
spillovers in a large-scale meta-analysis showing that, NMS: the
overall evidence of FDI spillovers is heterogeneous.
Hagemejer and Kolasa (2011) show large spillovers from sectoral
internationalization (FDI, exporting, imports of intermediates).
Spillovers are either horizontal of backward.
Hagemejer Productivity  GVC
Motivation
Method
Conclusions
Outline
GVC measures
Foreign ownership premium
Spillovers and GVC
What we do?
Use Amadeus database for the economies of the New Member States
Combine multiple waves of Amadeus to maximize the span of the
sample: 1997-2011 for most countries
Merge rm-level Amadeus database with the sector-level GVC and
spillover measures computed using the WIOD database.
Augment the foreign productivity premia/spillover equations with
GVC measures
Hagemejer Productivity  GVC
Motivation
Method
Conclusions
Outline
GVC measures
Foreign ownership premium
Spillovers and GVC
GVC measures
We measure upstreamness according to the denition provided by
Antras et al. (2012).
Ui = 1 ·
Xi
Yi
+2 ·
∑N
ij zij Xj
Yi
+3 ·
∑N
k=1∑N
ij zij zjk
Yi
+... (1)
U is the distance from nal demand measured in stages of
production computed for the WIOD database for a paper by
Hagemejer  Ghodsi (2015).
We measure foreign content of exports using Wang, Wei, and Zhu
(2013) backward-based decomposition that is valid on the sectoral
level
FVA (foreign value added of exports) - from intermediate and nal
goods
VS (vertical specialization) - overall foreign content of exports
Hagemejer Productivity  GVC
GVC measures
Motivation
Method
Conclusions
Outline
GVC measures
Foreign ownership premium
Spillovers and GVC
Premia from foreign ownership
Is GVC participation associated with a lower productivity GAP
between foreign and domestic rms?
Similar to Bernard and Jensen (1997) exporter premia regressions
The following equation is estimated:
TFPit = β1foreignit +β2foreignit ·GVCit +β3GVCit +εit (2)
TFP: using Levinsohn and Petrin (2003) method using materials as
a proxy for unobservables
Country-sector-clustered SE
Individual countries and full sample regressions
Hagemejer Productivity  GVC
Baseline results: high foreign productivity premia
(1) (2) (3) (4) (5) (6) (7) (8)
BGR CZE EST HUN POL ROU SVK SVN
Foreign 0.418*** 0.614*** 0.648*** 0.651*** 0.374*** 0.385*** 0.530*** 0.394***
(0.0226) (0.0213) (0.0261) (0.0492) (0.0130) (0.0146) (0.0252) (0.0260)
Obs. 66,761 95,901 17,385 13,761 57,173 350,733 33,855 17,650
R2 0.626 0.546 0.306 0.383 0.459 0.292 0.494 0.431
Poland: foreign ownership premium drops with the foreign
content of intermediate goods
(1) (2) (3) (4) (5) (6)
VARIABLES All Mnfc All Mnfc Mnfc Mnfc
Foreign 0.721*** 0.497*** 0.612*** 0.531*** 0.455*** 0.420***
(0.0399) (0.0629) (0.0571) (0.0639) (0.0539) (0.0232)
Foreign * Upstreamness 0.0145 -0.0815 0.173** -0.148
(0.0483) (0.0602) (0.0752) (0.0987)
Upstreamness 0.301 0.230 0.366** 0.260
(0.184) (0.325) (0.172) (0.351)
Foreign * VS -1.277*** -0.228
(0.128) (0.202)
VS 3.130*** 2.544***
(0.355) (0.587)
Foreign * VS (final goods) -0.782*** -0.314 -0.210
(0.214) (0.213) (0.222)
VS (final goods) 4.051*** 2.681*** 2.459*** 2.395***
(0.514) (0.857) (0.744) (0.685)
Foreign * VS (intermediate
goods)
-1.929*** 0.00648 -0.427* -0.365**
(0.233) (0.405) (0.244) (0.139)
VS (intermediate goods) 2.062*** 2.373*** 2.527*** 2.504***
(0.532) (0.622) (0.638) (0.545)
Observations 138,117 57,173 138,117 57,173 57,173 57,173
R-squared 0.425 0.502 0.426 0.502 0.501 0.501
Full NMS sample: point to heterogeneity of NMS
(1) (2) (3) (4) (5) (6)
VARIABLES All Mnfc All Mnfc Mnfc Mnfc
Foreign 0.280*** 0.294*** 0.236*** 0.288*** 0.352*** 0.360***
(0.0213) (0.0321) (0.0231) (0.0372) (0.0299) (0.0179)
Foreign * Upstreamness 0.218*** 0.135*** 0.307*** 0.150***
(0.0244) (0.0297) (0.0326) (0.0566)
Upstreamness 0.168 0.485*** -0.442*** 0.489***
(0.174) (0.119) (0.155) (0.141)
Foreign * VS 0.0814 0.161
(0.0628) (0.0987)
VS 0.615 1.678***
(0.424) (0.260)
Foreign * VS (final goods) 0.268*** 0.182 0.0434
(0.0917) (0.118) (0.113)
VS (final goods) 0.173 1.697*** 1.125*** 1.134***
(0.166) (0.376) (0.326) (0.326)
Foreign * VS (intermediate
goods)
-0.326** 0.102 0.577*** 0.560***
(0.133) (0.201) (0.113) (0.104)
VS (intermediate goods) 3.670*** 1.668*** 1.548*** 1.552***
(0.445) (0.301) (0.311) (0.312)
Observations 2,172,952 654,105 2,172,952 654,105 654,105 654,105
R-squared 0.818 0.854 0.819 0.854 0.854 0.854
NMS: foreign ownership premium - VS in nal goods
Table: Foreign rms productivity premia in individual countries
(NMS)-interaction with VS in nal goods, manufacturing
(1) (2) (3) (4) (5) (6) (7) (8)
VARIABLES BGR CZE EST HUN POL ROU SVK SVN
Foreign 0.709*** 0.601*** 0.686*** 1.036*** 0.382*** 0.434*** 0.389*** 0.287***
(0.0605) (0.0483) (0.0517) (0.125) (0.0279) (0.024) (0.037) (0.0584)
Foreign -1.786*** 0.0443 -0.208 -1.952*** -0.0684 -0.365*** 0.832*** 0.649**
* VS (final goods) (0.317) (0.213) (0.234) (0.456) (0.197) (0.115) (0.208) (0.322)
VS (final goods) 0.398 4.517*** 0.726** 1.252** 1.730** -0.0175 -0.417 0.313
(0.855) (0.43) (0.349) (0.545) (0.726) (0.416) (0.647) (1.184)
Observations 66,761 95,901 17,385 13,761 57,173 350,731 33,855 17,651
R-squared 0.549 0.53 0.371 0.545 0.501 0.251 0.497 0.591
Motivation
Method
Conclusions
Outline
GVC measures
Foreign ownership premium
Spillovers and GVC
NMS: foreign ownership premium - VS in intermediate goods
Table: Foreign rms productivity premia in individual countries (NMS) -
interaction with VS in intermediate goods
(1) (2) (3) (4) (5) (6) (7) (8)
VARIABLES BGR CZE EST HUN POL ROU SVK SVN
Foreign 0.295*** 0.749*** 0.616*** 0.987*** 0.421*** 0.350*** 0.555*** 0.455***
(0.0312) (0.0523) (0.0574) (0.0913) (0.0368) (0.0237) (0.0584) (0.0761)
Foreign * VS 0.885*** -0.741*** 0.162 -1.693*** -0.359** 0.369** -0.164 -0.366
(int. goods) (0.195) (0.239) (0.272) (0.4) (0.134) (0.168) (0.353) (0.414)
VS (int. goods) 0.603 3.745*** 0.881** -0.127 1.739*** 0.834* 3.960*** -0.309
(0.541) (0.679) (0.379) (0.637) (0.651) (0.466) (0.607) (1.036)
Observations 66,761 95,901 17,385 13,761 57,173 350,731 33,855 17,651
R-squared 0.549 0.528 0.371 0.544 0.501 0.251 0.498 0.591
Hagemejer Productivity  GVC
Motivation
Method
Conclusions
Outline
GVC measures
Foreign ownership premium
Spillovers and GVC
Spillovers from GVC
Is GVC participation associated with a lower productivity GAP
between foreign and domestic rms?
The following equation is estimated for domestic rms:
∆TFPijt = α0 +α1∆HZjt +α2∆BWjt +α3∆FWjt
+α4∆GVCjt +α5∆EXPjt +εit (3)
∆TFPijt is a change of TFP in rm i in sector j and time t. HZjt,
BWjt,FWjt are the measures of horizontal, backward and forward
linkages as dened originally by Smazynska-Javorcik (2004).
∆EXPjt is a change in export share of output at sectoral level to
account for productivity eects related to exporting
(learning-by-exporting or self selection).
Country-sector level eects, time dummies, sector-clustered SE
Individual countries and full sample regressions
Hagemejer Productivity  GVC
Baseline results: not much FDI spillovers
(1) (2) (3) (4) (6) (7) (8) (9)
BGR CZE EST HUN POL ROU SVK SVN
Horizontal -0.825** 0.104 -0.1 0.00311 0.143 -0.106 0.162* 0.138
(0.385) (0.113) (0.0878) (0.0784) (0.103) (0.0786) (0.0904) (0.0971)
Forward 0.341 -0.867*** -0.0875 -0.721 -0.155 -0.12 -0.436* 0.245
(0.468) (0.303) (0.145) (0.462) (0.366) (0.199) (0.237) (0.775)
Backward 1.717 1.972*** 0.0563 -0.322 1.323*** 0.228 0.405* -0.908*
(1.174) (0.337) (0.19) (0.331) (0.39) (0.144) (0.238) (0.525)
Obs. 35,840 63,348 10,114 7,029 30,041 218,561 21,834 9,966
R2 0.108 0.083 0.036 0.046 0.1 0.082 0.051 0.093
Spillovers: Poland
(1) (2) (3) (4) (5) (6) (7)
VARIABLES All Mnfc Mnfc Mnfc Mnfc Mnfc Mnfc
Horizontal FDI -0.0894 -0.00942
(0.0799) (0.0900)
Forward FDI -0.903** -0.390
(0.351) (0.359)
Backward FDI 1.584*** 1.180*** 0.993*** 1.046*** 1.004*** 1.050*** 1.040***
(0.370) (0.350) (0.206) (0.218) (0.206) (0.218) (0.228)
Export share 0.710*** 0.834*** 0.861*** 1.184*** 1.233*** 1.071*** 0.995***
(0.160) (0.132) (0.142) (0.170) (0.168) (0.0993) (0.196)
VS 0.676 1.071*** 0.939***
(0.519) (0.327) (0.350)
Upstreamness -0.731*** -0.252* -0.233* -0.413** -0.408** -0.294** -0.409**
(0.170) (0.133) (0.135) (0.184) (0.191) (0.135) (0.165)
Foreign VA -0.790 -1.059
(final goods) (0.751) (0.737)
Foreign VA 0.769 1.078*
(intermediate goods) (0.577) (0.558)
VS 0.0652
(final goods) (0.718)
VS (intermediate 1.311***
goods) (0.354)
Observations 71,336 30,041 30,041 30,041 30,041 30,041 30,041
R-squared 0.113 0.122 0.122 0.121 0.121 0.121 0.122
Spillovers: NMS
(1) (2) (3) (4) (5) (6) ()
VARIABLES All Mnfc Mnfc Mnfc Mnfc Mnfc Mnfc
Horizontal FDI -0.185** -0.121
(0.0786) (0.0793)
Forward FDI -0.0592 -0.0226
(0.131) (0.164)
Backward FDI 0.345*** 0.466** 0.365** 0.337** 0.343** 0.346*** 0.334**
(0.132) (0.182) (0.142) (0.135) (0.139) (0.131) (0.139)
Export share 0.663*** 0.650*** 0.643*** 0.557*** 0.504*** 0.649*** 0.568***
(0.106) (0.159) (0.159) (0.154) (0.124) (0.0876) (0.167)
VS -0.335*** -0.116 -0.129
(0.117) (0.417) (0.417)
Upstreamness -0.204** -0.183 -0.189 0.0115 0.00729 -0.106 0.0613
(0.0891) (0.125) (0.127) (0.0882) (0.0879) (0.130) (0.0866)
Foreign VA 0.740 1.006*
(final goods) (0.686) (0.546)
Foreign VA -0.805 -1.148***
(intermediate goods) (0.606) (0.402)
VS (final goods) 0.805
(0.575)
VS (intermediate -0.885**
goods) (0.409)
Observations 1,295,481 397,210 397,210 397,210 397,210 397,210 397,210
R-squared 0.090 0.102 0.101 0.103 0.102 0.102 0.103
Spillovers - individual countries, manufacturing
(1) (2) (3) (4) (5) (6) (7) (8)
VARIABLES BGR CZE EST HUN POL ROU SVK SVN
Horizontal FDI -0.820** 0.180* -0.116 0.00571 0.0122 -0.111 0.0862 0.127
(0.338) (0.105) (0.0831) (0.0701) (0.0852) (0.0747) (0.0803) (0.0921)
Forward FDI 0.123 -0.695** -0.0122 -1.420*** -0.393 -0.121 -0.518** -0.127
(0.414) (0.284) (0.15) (0.289) (0.357) (0.199) (0.23) (0.597)
Backward FDI 1.333** 0.907*** -0.0893 0.0704 1.204*** 0.212 0.11 -0.585
(0.61) (0.287) (0.132) (0.243) (0.364) (0.131) (0.218) (0.383)
Export share 1.673*** 0.441*** -0.0413 -1.152*** 0.965*** 0.282** 0.376** -0.141
(0.522) (0.13) (0.0627) (0.34) (0.183) (0.122) (0.189) (0.315)
VS (final -0.149 2.424*** 0.648** 1.484* 0.202 0.241 2.463*** 1.628
goods) (1.404) (0.441) (0.319) (0.789) (0.664) (0.426) (0.59) (1.159)
VS (int. -3.243*** -1.490*** -0.219 3.265*** 1.439*** -0.583** 1.464** 0.608
goods) (1.109) (0.541) (0.194) (0.547) (0.347) (0.249) (0.592) (0.609)
Upstreamness -0.0374 0.705*** 0.419*** -0.0785 -0.426** 0.0437 0.0132 -0.00488
(0.402) (0.16) (0.103) (0.214) (0.17) (0.0623) (0.233) (0.19)
Observations 35,840 63,348 10,114 7,029 30,041 218,561 21,834 9,966
R-squared 0.151 0.108 0.038 0.064 0.122 0.083 0.073 0.11
Conclusions
Poland: most of the GVC related productivity gains are in
intermediate goods
this is where foreign content of exports is associated with lower
productivity dierences between domestic and foreign enterprises. At
the same time productive rms are, other things equal, located close
to the nal demand.
it pays of to be on close to the nal consumer unless being further
away involves a high content of imported foreign value added in
exported goods.
In most of the other countries (except Hungary where results are
similar to that of Poland) where positive spillovers in the GVC exist,
they tend to stem from production of nal goods.
In Romania and Bulgaria the GVCs do not seem to bring to much of
productivity improvement to domestic rms
Results are similar when labour productivity is used instead of TFP.

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Productivity Spillovers in the GVC. The Case of Poland and the New EU Member States

  • 1. Motivation Method Conclusions Productivity Spillovers in the GVC The Case of Poland and the New EU Member States Jan Hagemejer Narodowy Bank Polski University of Warsaw September 10, 2016 The views presented here are those of the author and not necessarily of the National Bank of Poland. I greatly acknowledge the nancing by the National Science Centre, grant no: UMO- 2013/09/D/HS4/01519. Hagemejer Productivity GVC
  • 2. Motivation Method Conclusions Outline 1 Motivation Introduction Literature 2 Method Outline GVC measures Foreign ownership premium Spillovers and GVC 3 Conclusions Hagemejer Productivity GVC
  • 3. Motivation Method Conclusions Introduction Literature Why? Ongoing internationalization of New Member States economies due to: transition EU integration involvement in the GVC Internationalization is believed to have important direct and indirect eects on rm productivity through selection eects (export related) through FDI hosting through FDI productivity spillovers FDI exports are already well established in the literature - but to what extent participation in GVC and the position in the production chain matters for productivity? Hagemejer Productivity GVC
  • 4. Motivation Method Conclusions Introduction Literature Why GVC? Emerging economies compete for a good placement in the GVCs. This motivates rms to restructure and reorganize. Inclusion in GVC may involve: adoption of high quality standards adoption of modern technology adoption of modern management techniques The smile curve debate? Ye, Meng, and Wei (2015), Kowalski et al. (2015) or Cheng et al. (2015). Is the distribution of gains uniform along the GVC? Is it good to be close to the nal demand? Hagemejer Productivity GVC
  • 5. Motivation Method Conclusions Introduction Literature Literature FDI spillover literature is already abundant. Most studies follow the Sma»y«ska-Javorcik (2004) method based on rm-level data and input output tables. Other notable works Haddad and Harrison (1993), Aitken and Harrison (1999), Djankov and Hoekman (2000) or Konings (2001). Own sector eects, backward and forward eects. Review can be found in Crespo, Fontoura, and Proenca (2009) Irsova and Havranek (2013) analyse more than a 1000 of FDI spillovers in a large-scale meta-analysis showing that, NMS: the overall evidence of FDI spillovers is heterogeneous. Hagemejer and Kolasa (2011) show large spillovers from sectoral internationalization (FDI, exporting, imports of intermediates). Spillovers are either horizontal of backward. Hagemejer Productivity GVC
  • 6. Motivation Method Conclusions Outline GVC measures Foreign ownership premium Spillovers and GVC What we do? Use Amadeus database for the economies of the New Member States Combine multiple waves of Amadeus to maximize the span of the sample: 1997-2011 for most countries Merge rm-level Amadeus database with the sector-level GVC and spillover measures computed using the WIOD database. Augment the foreign productivity premia/spillover equations with GVC measures Hagemejer Productivity GVC
  • 7. Motivation Method Conclusions Outline GVC measures Foreign ownership premium Spillovers and GVC GVC measures We measure upstreamness according to the denition provided by Antras et al. (2012). Ui = 1 · Xi Yi +2 · ∑N ij zij Xj Yi +3 · ∑N k=1∑N ij zij zjk Yi +... (1) U is the distance from nal demand measured in stages of production computed for the WIOD database for a paper by Hagemejer Ghodsi (2015). We measure foreign content of exports using Wang, Wei, and Zhu (2013) backward-based decomposition that is valid on the sectoral level FVA (foreign value added of exports) - from intermediate and nal goods VS (vertical specialization) - overall foreign content of exports Hagemejer Productivity GVC
  • 9. Motivation Method Conclusions Outline GVC measures Foreign ownership premium Spillovers and GVC Premia from foreign ownership Is GVC participation associated with a lower productivity GAP between foreign and domestic rms? Similar to Bernard and Jensen (1997) exporter premia regressions The following equation is estimated: TFPit = β1foreignit +β2foreignit ·GVCit +β3GVCit +εit (2) TFP: using Levinsohn and Petrin (2003) method using materials as a proxy for unobservables Country-sector-clustered SE Individual countries and full sample regressions Hagemejer Productivity GVC
  • 10. Baseline results: high foreign productivity premia (1) (2) (3) (4) (5) (6) (7) (8) BGR CZE EST HUN POL ROU SVK SVN Foreign 0.418*** 0.614*** 0.648*** 0.651*** 0.374*** 0.385*** 0.530*** 0.394*** (0.0226) (0.0213) (0.0261) (0.0492) (0.0130) (0.0146) (0.0252) (0.0260) Obs. 66,761 95,901 17,385 13,761 57,173 350,733 33,855 17,650 R2 0.626 0.546 0.306 0.383 0.459 0.292 0.494 0.431
  • 11. Poland: foreign ownership premium drops with the foreign content of intermediate goods (1) (2) (3) (4) (5) (6) VARIABLES All Mnfc All Mnfc Mnfc Mnfc Foreign 0.721*** 0.497*** 0.612*** 0.531*** 0.455*** 0.420*** (0.0399) (0.0629) (0.0571) (0.0639) (0.0539) (0.0232) Foreign * Upstreamness 0.0145 -0.0815 0.173** -0.148 (0.0483) (0.0602) (0.0752) (0.0987) Upstreamness 0.301 0.230 0.366** 0.260 (0.184) (0.325) (0.172) (0.351) Foreign * VS -1.277*** -0.228 (0.128) (0.202) VS 3.130*** 2.544*** (0.355) (0.587) Foreign * VS (final goods) -0.782*** -0.314 -0.210 (0.214) (0.213) (0.222) VS (final goods) 4.051*** 2.681*** 2.459*** 2.395*** (0.514) (0.857) (0.744) (0.685) Foreign * VS (intermediate goods) -1.929*** 0.00648 -0.427* -0.365** (0.233) (0.405) (0.244) (0.139) VS (intermediate goods) 2.062*** 2.373*** 2.527*** 2.504*** (0.532) (0.622) (0.638) (0.545) Observations 138,117 57,173 138,117 57,173 57,173 57,173 R-squared 0.425 0.502 0.426 0.502 0.501 0.501
  • 12. Full NMS sample: point to heterogeneity of NMS (1) (2) (3) (4) (5) (6) VARIABLES All Mnfc All Mnfc Mnfc Mnfc Foreign 0.280*** 0.294*** 0.236*** 0.288*** 0.352*** 0.360*** (0.0213) (0.0321) (0.0231) (0.0372) (0.0299) (0.0179) Foreign * Upstreamness 0.218*** 0.135*** 0.307*** 0.150*** (0.0244) (0.0297) (0.0326) (0.0566) Upstreamness 0.168 0.485*** -0.442*** 0.489*** (0.174) (0.119) (0.155) (0.141) Foreign * VS 0.0814 0.161 (0.0628) (0.0987) VS 0.615 1.678*** (0.424) (0.260) Foreign * VS (final goods) 0.268*** 0.182 0.0434 (0.0917) (0.118) (0.113) VS (final goods) 0.173 1.697*** 1.125*** 1.134*** (0.166) (0.376) (0.326) (0.326) Foreign * VS (intermediate goods) -0.326** 0.102 0.577*** 0.560*** (0.133) (0.201) (0.113) (0.104) VS (intermediate goods) 3.670*** 1.668*** 1.548*** 1.552*** (0.445) (0.301) (0.311) (0.312) Observations 2,172,952 654,105 2,172,952 654,105 654,105 654,105 R-squared 0.818 0.854 0.819 0.854 0.854 0.854
  • 13. NMS: foreign ownership premium - VS in nal goods Table: Foreign rms productivity premia in individual countries (NMS)-interaction with VS in nal goods, manufacturing (1) (2) (3) (4) (5) (6) (7) (8) VARIABLES BGR CZE EST HUN POL ROU SVK SVN Foreign 0.709*** 0.601*** 0.686*** 1.036*** 0.382*** 0.434*** 0.389*** 0.287*** (0.0605) (0.0483) (0.0517) (0.125) (0.0279) (0.024) (0.037) (0.0584) Foreign -1.786*** 0.0443 -0.208 -1.952*** -0.0684 -0.365*** 0.832*** 0.649** * VS (final goods) (0.317) (0.213) (0.234) (0.456) (0.197) (0.115) (0.208) (0.322) VS (final goods) 0.398 4.517*** 0.726** 1.252** 1.730** -0.0175 -0.417 0.313 (0.855) (0.43) (0.349) (0.545) (0.726) (0.416) (0.647) (1.184) Observations 66,761 95,901 17,385 13,761 57,173 350,731 33,855 17,651 R-squared 0.549 0.53 0.371 0.545 0.501 0.251 0.497 0.591
  • 14. Motivation Method Conclusions Outline GVC measures Foreign ownership premium Spillovers and GVC NMS: foreign ownership premium - VS in intermediate goods Table: Foreign rms productivity premia in individual countries (NMS) - interaction with VS in intermediate goods (1) (2) (3) (4) (5) (6) (7) (8) VARIABLES BGR CZE EST HUN POL ROU SVK SVN Foreign 0.295*** 0.749*** 0.616*** 0.987*** 0.421*** 0.350*** 0.555*** 0.455*** (0.0312) (0.0523) (0.0574) (0.0913) (0.0368) (0.0237) (0.0584) (0.0761) Foreign * VS 0.885*** -0.741*** 0.162 -1.693*** -0.359** 0.369** -0.164 -0.366 (int. goods) (0.195) (0.239) (0.272) (0.4) (0.134) (0.168) (0.353) (0.414) VS (int. goods) 0.603 3.745*** 0.881** -0.127 1.739*** 0.834* 3.960*** -0.309 (0.541) (0.679) (0.379) (0.637) (0.651) (0.466) (0.607) (1.036) Observations 66,761 95,901 17,385 13,761 57,173 350,731 33,855 17,651 R-squared 0.549 0.528 0.371 0.544 0.501 0.251 0.498 0.591 Hagemejer Productivity GVC
  • 15. Motivation Method Conclusions Outline GVC measures Foreign ownership premium Spillovers and GVC Spillovers from GVC Is GVC participation associated with a lower productivity GAP between foreign and domestic rms? The following equation is estimated for domestic rms: ∆TFPijt = α0 +α1∆HZjt +α2∆BWjt +α3∆FWjt +α4∆GVCjt +α5∆EXPjt +εit (3) ∆TFPijt is a change of TFP in rm i in sector j and time t. HZjt, BWjt,FWjt are the measures of horizontal, backward and forward linkages as dened originally by Smazynska-Javorcik (2004). ∆EXPjt is a change in export share of output at sectoral level to account for productivity eects related to exporting (learning-by-exporting or self selection). Country-sector level eects, time dummies, sector-clustered SE Individual countries and full sample regressions Hagemejer Productivity GVC
  • 16. Baseline results: not much FDI spillovers (1) (2) (3) (4) (6) (7) (8) (9) BGR CZE EST HUN POL ROU SVK SVN Horizontal -0.825** 0.104 -0.1 0.00311 0.143 -0.106 0.162* 0.138 (0.385) (0.113) (0.0878) (0.0784) (0.103) (0.0786) (0.0904) (0.0971) Forward 0.341 -0.867*** -0.0875 -0.721 -0.155 -0.12 -0.436* 0.245 (0.468) (0.303) (0.145) (0.462) (0.366) (0.199) (0.237) (0.775) Backward 1.717 1.972*** 0.0563 -0.322 1.323*** 0.228 0.405* -0.908* (1.174) (0.337) (0.19) (0.331) (0.39) (0.144) (0.238) (0.525) Obs. 35,840 63,348 10,114 7,029 30,041 218,561 21,834 9,966 R2 0.108 0.083 0.036 0.046 0.1 0.082 0.051 0.093
  • 17. Spillovers: Poland (1) (2) (3) (4) (5) (6) (7) VARIABLES All Mnfc Mnfc Mnfc Mnfc Mnfc Mnfc Horizontal FDI -0.0894 -0.00942 (0.0799) (0.0900) Forward FDI -0.903** -0.390 (0.351) (0.359) Backward FDI 1.584*** 1.180*** 0.993*** 1.046*** 1.004*** 1.050*** 1.040*** (0.370) (0.350) (0.206) (0.218) (0.206) (0.218) (0.228) Export share 0.710*** 0.834*** 0.861*** 1.184*** 1.233*** 1.071*** 0.995*** (0.160) (0.132) (0.142) (0.170) (0.168) (0.0993) (0.196) VS 0.676 1.071*** 0.939*** (0.519) (0.327) (0.350) Upstreamness -0.731*** -0.252* -0.233* -0.413** -0.408** -0.294** -0.409** (0.170) (0.133) (0.135) (0.184) (0.191) (0.135) (0.165) Foreign VA -0.790 -1.059 (final goods) (0.751) (0.737) Foreign VA 0.769 1.078* (intermediate goods) (0.577) (0.558) VS 0.0652 (final goods) (0.718) VS (intermediate 1.311*** goods) (0.354) Observations 71,336 30,041 30,041 30,041 30,041 30,041 30,041 R-squared 0.113 0.122 0.122 0.121 0.121 0.121 0.122
  • 18. Spillovers: NMS (1) (2) (3) (4) (5) (6) () VARIABLES All Mnfc Mnfc Mnfc Mnfc Mnfc Mnfc Horizontal FDI -0.185** -0.121 (0.0786) (0.0793) Forward FDI -0.0592 -0.0226 (0.131) (0.164) Backward FDI 0.345*** 0.466** 0.365** 0.337** 0.343** 0.346*** 0.334** (0.132) (0.182) (0.142) (0.135) (0.139) (0.131) (0.139) Export share 0.663*** 0.650*** 0.643*** 0.557*** 0.504*** 0.649*** 0.568*** (0.106) (0.159) (0.159) (0.154) (0.124) (0.0876) (0.167) VS -0.335*** -0.116 -0.129 (0.117) (0.417) (0.417) Upstreamness -0.204** -0.183 -0.189 0.0115 0.00729 -0.106 0.0613 (0.0891) (0.125) (0.127) (0.0882) (0.0879) (0.130) (0.0866) Foreign VA 0.740 1.006* (final goods) (0.686) (0.546) Foreign VA -0.805 -1.148*** (intermediate goods) (0.606) (0.402) VS (final goods) 0.805 (0.575) VS (intermediate -0.885** goods) (0.409) Observations 1,295,481 397,210 397,210 397,210 397,210 397,210 397,210 R-squared 0.090 0.102 0.101 0.103 0.102 0.102 0.103
  • 19. Spillovers - individual countries, manufacturing (1) (2) (3) (4) (5) (6) (7) (8) VARIABLES BGR CZE EST HUN POL ROU SVK SVN Horizontal FDI -0.820** 0.180* -0.116 0.00571 0.0122 -0.111 0.0862 0.127 (0.338) (0.105) (0.0831) (0.0701) (0.0852) (0.0747) (0.0803) (0.0921) Forward FDI 0.123 -0.695** -0.0122 -1.420*** -0.393 -0.121 -0.518** -0.127 (0.414) (0.284) (0.15) (0.289) (0.357) (0.199) (0.23) (0.597) Backward FDI 1.333** 0.907*** -0.0893 0.0704 1.204*** 0.212 0.11 -0.585 (0.61) (0.287) (0.132) (0.243) (0.364) (0.131) (0.218) (0.383) Export share 1.673*** 0.441*** -0.0413 -1.152*** 0.965*** 0.282** 0.376** -0.141 (0.522) (0.13) (0.0627) (0.34) (0.183) (0.122) (0.189) (0.315) VS (final -0.149 2.424*** 0.648** 1.484* 0.202 0.241 2.463*** 1.628 goods) (1.404) (0.441) (0.319) (0.789) (0.664) (0.426) (0.59) (1.159) VS (int. -3.243*** -1.490*** -0.219 3.265*** 1.439*** -0.583** 1.464** 0.608 goods) (1.109) (0.541) (0.194) (0.547) (0.347) (0.249) (0.592) (0.609) Upstreamness -0.0374 0.705*** 0.419*** -0.0785 -0.426** 0.0437 0.0132 -0.00488 (0.402) (0.16) (0.103) (0.214) (0.17) (0.0623) (0.233) (0.19) Observations 35,840 63,348 10,114 7,029 30,041 218,561 21,834 9,966 R-squared 0.151 0.108 0.038 0.064 0.122 0.083 0.073 0.11
  • 20. Conclusions Poland: most of the GVC related productivity gains are in intermediate goods this is where foreign content of exports is associated with lower productivity dierences between domestic and foreign enterprises. At the same time productive rms are, other things equal, located close to the nal demand. it pays of to be on close to the nal consumer unless being further away involves a high content of imported foreign value added in exported goods. In most of the other countries (except Hungary where results are similar to that of Poland) where positive spillovers in the GVC exist, they tend to stem from production of nal goods. In Romania and Bulgaria the GVCs do not seem to bring to much of productivity improvement to domestic rms Results are similar when labour productivity is used instead of TFP.