Multinational Production and Comparative Advantage

Transcription

1 Multinational Production and Comparative Advantage Vanessa Alviarez Sauder Business School University of British Columbia May, 2015

2 Multinational Production (MP) and Sectoral Productivity What is the relationship between MP and dierences in relative productivity across sectors? Observations: MP represents a large fraction of output, employment and trade The fraction of MP on output is signicantly heterogeneous across sectors Signicant cross-country dierences in the sectoral heterogeneity of MP MP and sectoral productivity are negatively correlated

3 Relevance of Multinational Production

4 Multinational Production (MP) and Sectoral Productivity What is the relationship between MP and dierences in relative productivity across sectors? Observations: MP represents a large fraction of output, employment and trade The fraction of MP on output is signicantly heterogeneous across sectors Signicant cross-country dierences in the sectoral heterogeneity of MP MP and sectoral productivity are negatively correlated

5 Sectoral Heterogeneity of MP shares

6 Multinational Production (MP) and Sectoral Productivity What is the relationship between MP and dierences in relative productivity across sectors? Observations: MP represents a large fraction of output, employment and trade The fraction of MP on output is signicantly heterogeneous across sectors Signicant cross-country dierences in the sectoral heterogeneity of MP MP and sectoral productivity are negatively correlated

7 Cross-country dierences in MP heterogeneity

8 Cross-country dierences in MP heterogeneity index

9 Multinational Production (MP) and Sectoral Productivity What is the relationship between MP and dierences in relative productivity across sectors? Observations: MP represents a large fraction of output, employment and trade The fraction of MP on output is signicantly heterogeneous across sectors Signicant cross-country dierences in the sectoral heterogeneity of MP MP and sectoral productivity are negatively correlated

10 MP is correlated with sectoral productivity Negative Correlation Between (MP j hs /outputj h ) and Relative TFP Foreign aliate sales are higher in sectors where the host economy is relatively less productive.

11 MP is correlated with sectoral productivity Negative Correlation Between (#sources j hs /outputj h ) and Relative TFP More source countries invest in sectors where the host economy is relatively less productive.

12 Bilateral MP and Productivity Dierences

13 Interaction between Multinational Production (MP) and Comparative Advantage Are the observed uneven allocation of MP across sectors related to dierences in sectoral productivity? Does multinational production aect the average productivity of each industry dierently? What are the welfare implications of the interaction between MP and relative dierences in sectoral productivity?

14 Can MP aect relative productivity dierences across sectors? Multinationals bring knowhow, innovative knowledge, and managerial skills. MP induces larger transfer of technology in sectors where the host country is relatively less productive Reducing dierences in relative productivity across sectors

15 CA MP Eect of Comparative Advantage on MP allocation

16 MP CA Eect of MP on Comparative Advantage

17 This paper 1. Assembles an industry-level dataset of bilateral foreign aliates' sales to document some empirical regularities 2. Incorporates a sectoral dimension into a multi-country model of trade and MP: Estimates productivities at the sectoral level for domestic and all producers in the economy Derives analytical implications for welfare Conducts counterfactual exercises to evaluate the eects of MP Unisectoral models of Trade and MP are silent with respect to the interaction between MP and comparative advantage

18 Preview of Results The increase in real income following an opening to multinational activity is 15 percentage points higher compared to the case where MP is homogeneous across sectors (27% compared to 12%) The increase in real income following a trade liberalization is about half of what it would be if MP does not aect comparative advantage (10% compared to 19.4%)

19 Preview of Results The increase in real income following an opening to multinational activity is 15 percentage points higher compared to the case where MP is homogeneous across sectors (27% compared to 12%) The increase in real income following a trade liberalization is about half of what it would be if MP does not aect comparative advantage (10% compared to 19.4%)

20 Contribution to Related Literature Uni-sector MP-trade models: Ramondo and Rodriguez-Clare (2011); Shikher (2011) Arkolakis, Ramondo, Rodriguez-Clare and Yeaple (2012) Alfaro and Chen (2012, 2011) Multi-sector trade-only models: Costinot, Donalson and Komunjer (2012), Caliendo and Parro (2013), Levchenko and Zhang (2012) Horizontal MP and technology transfer: Guadalupe, Kuzmina and Thomas (2012), Fons-Rosen et al (2013), Chen and Alfaro (2011), Békeé, Kleinert and Toubal (2009), Blyde et al. (2004) Brainard (2009, 2011), Ramondo et al. (2012), Neary (2007)

21 Roadmap Presents a GE model of trade and MP that incorporates the sectoral dimension. Estimates productivity parameters of local producers and overall economy for each country-sector pair. Evaluates the welfare implications of the eect of MP on comparative advantage.

22 A Multi-Sector Trade-MP Model Environment N countries: source (s), host (h) and destination market (m) J tradable sectors and one (J + 1) non-tradable sector Each sector has a continuum of varieties ω = [0, 1] MP by source country s in host country h occurs when a technology from s is used in h to produce variety ω. Trade: Country produces from their own market to sell to a foreign market s = h. MP: Country produces at the destination market h = m. Export Platforms: Country s produces in h to sell from there to destination market m. preferences

23 A Multi-Sector Trade-MP Model Environment N countries: source (s), host (h) and destination market (m) J tradable sectors and one (J + 1) non-tradable sector Each sector has a continuum of varieties ω = [0, 1] MP by source country s in host country h occurs when a technology from s is used in h to produce variety ω. Trade: Country produces from their own market to sell to a foreign market s = h. MP: Country produces at the destination market h = m. Export Platforms: Country s produces in h to sell from there to destination market m. preferences

24 A Multi-Sector Trade-MP Model Environment N countries: source (s), host (h) and destination market (m) J tradable sectors and one (J + 1) non-tradable sector Each sector has a continuum of varieties ω = [0, 1] MP by source country s in host country h occurs when a technology from s is used in h to produce variety ω. Trade: Country produces from their own market to sell to a foreign market s = h. MP: Country produces at the destination market h = m. Export Platforms: Country s produces in h to sell from there to destination market m. preferences

25 A Multi-Sector Trade-MP Model Environment N countries: source (s), host (h) and destination market (m) J tradable sectors and one (J + 1) non-tradable sector Each sector has a continuum of varieties ω = [0, 1] MP by source country s in host country h occurs when a technology from s is used in h to produce variety ω. Trade: Country produces from their own market to sell to a foreign market s = h. MP: Country produces at the destination market h = m. Export Platforms: Country s produces in h to sell from there to destination market m. preferences

26 A Multi-Sector Trade-MP Model Environment Using technology to produce in a foreign country entails a cost: Iceberg MP costs: g j hs > 1, and gj ss = 1 Trade across countries is costly: Iceberg trade costs: d j nh > 1, and dj hh = 1 Factors of Production: capital (K), labor (L) Productivity of each country-sector pair is described by: z j s (ω) { z j 1s (ω), z j 2s (ω),..., z j Ns (ω)} i, j = 1 : N technology

27 Production Structure Production function: [ [ (L Q j mhs (ω) = ) j αj ( ) h K j 1 αj ] J+1 ] 1 βj ) βj ( ) h Q k γkj (z j hs (ω) s where: p j mhs (ω) = ( k=1 c j h gj hs z j hs (ω) ) d j mh [ [ (w c j h = ) j αj ( ) h r j 1 αj ] J+1 ] 1 βj βj ( ) h p k γkj h. k=1 g j hs

28 Production Structure Seller s will choose the location h to reach country m with the lowest possible price p j ms (ω) = min { p j m1s (ω), p j m2s (ω),..., p j mns (ω)} Consumers in m will choose to buy from the source technology country s that oers the cheapest price p j m (ω) = min { p j m1 (ω), p j m2 (ω),..., p j mn (ω)}

29 Market Structure Hence, the probability that country (m) imports sector (j) goods from country (h) using country (s) technologies is described as: π j mhs = T ( ) s j ( j ms) θ j δ j θj mhs s T ( ) s j j θj ( ) ms h δ j θj. mhs }{{}}{{} Term 1 Term 2 where j ms = ( h ( ) δ j θj ) 1 θ j mhs and δ j mhs = dj mh cj h gj hs.

30 Trade Shares: π j mh Summing up π j mhs across source countries s π j mh = N s=1 π j mhs X j mh X j m ( ) j T = π j mh = h c j θ h dj mh N T ( j k c j k dj mk k=1 ) θ Where T j h is the eective technology: T j h = T j 1 g j θ h1 + T j 2 g j θ h T j N gj θ hn

31 MP Shares: y j hs MP sales: summing up π j mhs Xj m across destination countries m; where X j m = p j mq j m I j hs = N MP shares are given by: m=1 π j mhs Xj m I j hs = T ( ) s j g j θ hs cj h (X h ) 2 ( ) p j θ X hh h y j hs = Ij hs s Ij hs = Ij hs I j h = T j s ( ) g j θ hs T j h

32 Closing the Model } N { Given the set of prices w h, r h, P h, { } p j J+1 h, j=1 h=1 production is allocated across countries and sectors as follows: ( J+1 p j h Qj h = pj h Y j h + N (1 β k ) γ j,k k=1 m=1 s=1 ) N πmhsp k k mq k m The optimal sectoral factor allocations in country h and tradable sector j must thus satisfy: N N m=1 s=1 π j mhs pj mq j m = w hl j h α j β j = r h K j h (1 α j ) β j.

33 Analytical predictions Simplifying assumptions Cobb Douglas preferences and equal expenditure shares Preferences A mirror image of the fundamental productivity across sectors and countries: T a 1 = T b 2 and T b 1 = T a 2 Country 2 has comparative advantage in sector a: T a 2 > T b 2 Symmetry in trade and MP barriers The above assumptions ensure that wages are equal in both countries, w 1 = w 2 = 1

34 Welfare Analysis: Gains from Trade Welfare: an expression for real wage W s = w s (p a sp b s) 1 2 = Γ 1 ( T a s T b s ) 1 2θ ( π a ssπ b ss ) 1 2θ ( y a ssy b ss ) 1 2θ Gains from trade: ( πssπ a ss b GT s = W s d>0 W s d = j=a,b ) 1 2θ ) ) a ( T 1 /T1 ( T a b 1 /T1 b (1 + (dgj) θ ) + T j 1 T j 1 (g j θ + d θ ) 1/2θ

35 Welfare Analysis: Gains from MP Welfare: an expression for real wage W s = w s (p a sp b s) 1 2 = Γ 1 ( T a s T b s ) 1 2θ ( π a ssπ b ss ) 1 2θ ( y a ssy b ss ) 1 2θ Gains from MP: GMP s = W s g>0 W s g = j=a,b j=a,b ) (1 + T j 1 d θ T j 1 (1 + (dgj) θ ) + T j 1 T j 1 (g j θ + d θ ) 1 2θ

36 MP is disproportionately allocated in comparative disadvantage sectors Proposition 1 In a two-country, two-sector world economy, the lower the technology of country 1 in sector a (country 1's comparative disadvantage sector) relative to sector b, the higher the probability that rms from country 2 will produce in sector a relative to sector b in country 1. Proposition 1

37 The higher the heterogeneity of MP across sectors, the higher the gains from MP Proposition 2 The higher the heterogeneity of MP across sectors, the higher the gains from MP. When the share of domestically produced goods is the same across sectors (yhh a = yb hh ), the gains from MP attain a minimum. Therefore, uni-sectoral trade-mp models understate the actual gains from MP as long as yhh a yb hh

38 Gains from trade are lower the more heterogeneous the technology upgrade across sectors Proposition 3 The more heterogeneous the technology upgrade across sectors toward comparative disadvantage sectors, the lower the dispersion of eective technologies and the lower the gains from trade

39 Figure: Proportional Technology Transfer

40 Bilateral MP Data: Sectoral Dimension Coverage: 34 declaring countries 9 manufacturing and 4 non-manufacturing sectors Variables: Sales, and employment Unit of Analysis: Each observation is a (source-host-sector) triplet, averaged over the period Sources: OECD (Statistics on Measuring Globalization and IDIS) Eurostat (Foreign Aliates Statistics (FATS)) UNCTAD (FDI Country Proles) ORBIS dataset

41 Bilateral MP Data: Sectoral Dimension Coverage: 34 declaring countries 9 manufacturing and 4 non-manufacturing sectors Variables: Sales, and employment Unit of Analysis: Each observation is a (source-host-sector) triplet, averaged over the period Sources: OECD (Statistics on Measuring Globalization and IDIS) Eurostat (Foreign Aliates Statistics (FATS)) UNCTAD (FDI Country Proles) ORBIS dataset

42 Bilateral MP Data: Sectoral Dimension Coverage: 34 declaring countries 9 manufacturing and 4 non-manufacturing sectors Variables: Sales, and employment Unit of Analysis: Each observation is a (source-host-sector) triplet, averaged over the period Sources: OECD (Statistics on Measuring Globalization and IDIS) Eurostat (Foreign Aliates Statistics (FATS)) UNCTAD (FDI Country Proles) ORBIS dataset

43 Bilateral MP Data: Sectoral Dimension Coverage: 34 declaring countries 9 manufacturing and 4 non-manufacturing sectors Variables: Sales, and employment Unit of Analysis: Each observation is a (source-host-sector) triplet, averaged over the period Sources: OECD (Statistics on Measuring Globalization and IDIS) Eurostat (Foreign Aliates Statistics (FATS)) UNCTAD (FDI Country Proles) ORBIS dataset

44 Estimating Model's Parameters Trade and MP Gravity Equations ln Trade Gravity Equation ( ) X j mh Xmm j j = ln ( T h ( ) c j θ ) h }{{} exporter xed eect Trade barriers are dened as: ( j ln ( T m c j m ) ) θ }{{} importer xed eect θln ( ) d j mh }{{} bilateral observables ln ( ) d j mh = d j k + bj mh + CU j mh + RT Aj mh + exporterj h + vj mh Two Step Procedure

45 Estimating Model's Parameters Trade and MP Gravity Equations MP Gravity Equation ( ) I j hs ln I j = ln ( ) Ts j ln ( ) T j h θln ( ) g j hs }{{}}{{}}{{} hh source xed eect host xed eect bilateral observables MP barriers are dened as: ln ( g j hs ) = d j k + bs hs + CU j hs + RT Aj hs + sourcej s + µ j hs

46 Estimating Model's Parameters Recovering the T j h Recall that eective technology parameters are given by T j 1 g j T j 11 g j g j 1N T j 2 g j 21 g j g j 1 2N.. = T j T j g j N N1 g j N2.... g j NN T j N Given T s j and h j si we can solve for the fundamental productivity T j i using the above system of equations for each sector j Other methods

47 Table: Change in Absolute and Comparative Advantage Variable Mean Group 1 (10 countries) CV T 0.09 Group 2 (24 countries) CV T 0.17 All sample (34 countries) CV T 0.14 per country

48 MP Technology Transfer

49 MP technology transfer ln ( ) 1/θ ( T j h ln T j 1/θ h) = β0 + β 1 ln ( Th) j 1/θ + γh + δ j + ɛ hj

50 The Fit of the Baseline Model with the Data Wages Imports/GDP Inward MP/Production Model Data Mean Median corr(model,data) Mean Median corr(model,data) Mean Median corr(model,data) 0.758

51 Proportional Technology Transfer Counterfactual 1: Gains from Trade Figure: Counterfactual 2: Proportional Technology Transfer

52 Gains from MP: in a multisector framework Counterfactual 1: Gains from MP Table: Gains From MP Median Mean Std.Dev Min Max MP Gains (Multisector) (%) Counterfactual Vs Baseline MP Gains (Uni-sector) (%) Counterfactual Vs Baseline

53 Proportional Technology Transfer Counterfactual 2: Gains from Trade Table: Proportional Technology Transfer Mean Median Std.Dev Min Max Gains from Trade (%) Actual Gains Counterfactual

54 Innity barriers to MP in non-tradable sectors Counterfactual 3: welfare eect Table: MP in non-tradables Median Mean Std.Dev Min Max Welfare Change (%) Counterfactual Vs Baseline Tradable Price Index (%) Counterfactual Vs Baseline

55 Conclusion This paper documents a new empirical regularity: A negative relationship between MP and comparative advantage It shows that MP weakens countries comparative advantage It shows that uni-sectoral models systematically overstate the gains from trade and understate the gains from MP

56 Appendix

57 Cross-country dierences in MP heterogeneity cross-country dierences

58 Preferences Consumers in country m maximize utility subject to the budget constraint: ( J ) η η 1 ( ) ξm η 1 ( ) U m = Y j η m Y J+1 1 ξm m, j=1 ω 1 η j s.t. J+1 p j mym j = w m L m + r m K m j=1 P m - price level in country m is given by: P m = B m ( J j=1 ) 1 1 η ( ) ξm ω j p j 1 η ( ) m p J+1 1 ξm, m back

59 Technology Productivity vectors are drawn independently across varieties ω in sector j and origin country i from a multivariate Frechet distribution [ ( N )] ( ) Fs j (z) = exp Ts j z j θj hs. h=1 Productivity dierences are characterized by : technology 1. Inter-industry heterogeneity or relative technology dierences( in fundamental ) productivity across industries T j=a s /T j=b s 2. Intra-industry heterogeneity, governed by θ j

60 MP and sectoral productivity Employment Sales Value Added Added BEA Rel. Productivity -3.71*** -1.98** -2.12** Obs. 1,089 1,089 1,353 OECD Rel. Productivity -1.39*** -1.05*** -1.08*** Obs. 1,260 1,366 1,100 Note: Standard errors are cluster at the country level. All regressions have country and year xed eects MP and Productivity

61 MP and Comparative Advantage MP sales j n = α + β T F P j n + δ n + γ j + ɛ j n - MP sales are normalized by output in country n and sector j - Total Factor Productivity (T F P j n) is measured relative to the frontier in sector j - δ n and γ n denotes country and sector xed eects - robust to T F P correction by selection in open economies, and alternative measures of MP Robustness

62 MP and Comparative Advantage

63 MP and Comparative Advantage

64 MP in comparative disadvantage sectors Proof: Lets dene the ratio of probabilities πa 112 π112 b country 2 produce in country 1 as: π a 112 π b 112 Proposition 1 = T a 2 T b 2 T2 b T1 a T a 1 T b 1 that [ 1 + (hd) θ] 1 θ ( h θ + d θ) 1 θ + T 1 b T1 a [ (h θ + d θ ) 1 θ (hd) θ] 1 θ ( ) π a 112 / T1 a < 0 π b 112 ( ) π a 112 / T2 a > 0 π b 112

65 Estimating Model's Parameters Recovering the T j s Given Ts j (obtained from the gravity equation xed eects) and h j si we can calculate the eective productivity T j i for each sector j T j 1 = T j 1 h j 11 θ + T j 2 h j θ 12 T j 2 = T j 1 h j 21 θ + T j 2 h j θ 22

66 Estimating Model's Parameters Generalize Method of Moments Given h j si and dj si, T j i min T j s are chosen to minimize: [ (1 R T ) + (1 R MP ) ] where R T and R MP are given by: preferred method R T 1 R MP 1 [ Xj,data i,n;n i ni i,n;n i ( Xj,data ni [Ĩj,data i,n;n i ni i,n;n i ] 2 j,model X ni ) 2 Ĩj,model ni ) 2 (Ĩj,data ni ] 2

67 Eective technology: two step procedure The importer xed eect Sn j = T ( ) n j c j θ n T us j c j us The share of spending going to home-produced goods X j nn X j us = T j n ( c j n p j n ) θ Dividing it by US, we have: X j nn/x j n X j us,us/x j us = T ( ) n j c j θ ( ) n p j θ n T us j c j us p j = Sn j us ( p j us p j n ) θ

68 Eective technology: two step procedure The ratio of price levels in sector j relative to US becomes ( ) p j n X j = nn /Xn j 1 θ 1 p j us Xus,us/X j us j Sn j The cost of the input bundles relative to the U.S can be written as: c j n c j us ( ) w j αj β j ( ) = n r j (1 αj ( )β j J+1 ( ) n p k γk,j ) 1 βj n w j us r j us k=1 p k us Trade Gravity Equation

69 Technology Productivity vectors are drawn independently across sector varieties ω in sector j and origin country i from univariate Frechet marginals combined by a copula { [ (z F j i (z) = exp T j j i 1i (ω)) θ j 1 ρ j θ ( + z j 2i (ω)) j ] } 1 ρj 1 ρ j There are three levels of heterogeneity in this model: technology 1. Inter-industry heterogeneity or relative technology dierences in fundamental productivity across industries Ti 1/T i 2 2. Intra-industry heterogeneity, governed by θ 3. Correlation between draws from dierent locations ρ.

70 Preferences Two-tier preferences: First tier: Cobb-Douglas (ξn ) on aggregate tradable sectors Yn j Y n = (Y a n ) ξn (Y b n ) 1 ξn Second tier: CES (εn ) on varieties Y j n (ω) ( 1 Yn j = 0 ε j 1 ) ε j Yn j ε j 1 ε (ω) j dω And the actual price in sector j, country n is given by: P j n = B n (p n1 ) ξn (p n2 ) 1 ξn Assumptions

71 MP and trade barriers Table: Estimated trade d j nh and gj hs back Sector Trade MP Food Textiles Wood Chemicals Non-metallic Metals Machinery Transport Furniture

72 Average Change Relative Change Top 10: Largest Change Top 10: Largest Change Countries Countries Czech Rep Poland Poland 0.35 Czech Rep Lithuania 0.30 Spain Hungary 0.29 Portugal Austria 0.24 Canada Netherlands 0.22 Austria Slovakia 0.22 Italy Portugal 0.22 Turkey Sweden 0.20 Russia Canada 0.17 Sweden Turkey 0.14 Slovenia back

73 Average Change Relative Change Bottom 10: Smallest Bottom 10: Smallest Change Countries Change Countries Finland 0.09 Japan France 0.07 Belgium Switzerland 0.06 Denmark Denmark 0.04 Greece Norway 0.04 United Kingdom New Zealand 0.04 Norway Australia 0.03 Latvia 0.05 Belgium 0.02 Germany 0.08 Greece 0.01 France 0.14 Israel 0.01 Bulgaria 0.14 back

74 Model's correlation of MP sales and T j s