1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf...

37
1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMF Ashoka Mody, IMF Assaf Razin, Tel-Aviv University Assaf Razin, Tel-Aviv University and Cornell University and Cornell University Efraim Sadka, Tel-Aviv University Efraim Sadka, Tel-Aviv University
  • date post

    21-Dec-2015
  • Category

    Documents

  • view

    231
  • download

    0

Transcript of 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf...

Page 1: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

1

The Role of Information in Driving FDI:

Theory and Evidence

• Ashoka Mody, IMFAshoka Mody, IMF

• Assaf Razin, Tel-Aviv University and Assaf Razin, Tel-Aviv University and Cornell UniversityCornell University

• Efraim Sadka, Tel-Aviv UniversityEfraim Sadka, Tel-Aviv University

Page 2: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

2

• Foreign direct investment (FDI) has been Foreign direct investment (FDI) has been growing faster than world GDP, and is becoming growing faster than world GDP, and is becoming a major component of foreign investment.a major component of foreign investment.

• We identify from empirical data two main We identify from empirical data two main categories of variables that significantly explain categories of variables that significantly explain FDI inflows:FDI inflows:

1)1) Positive correlation between the industry Positive correlation between the industry specialization in the source countries and FDI flows specialization in the source countries and FDI flows into the host countries is shown to exist;into the host countries is shown to exist;

2)2) Countries with higher quality of corporate Countries with higher quality of corporate transparencies and stronger capital market transparencies and stronger capital market institutions attract less FDI flows.institutions attract less FDI flows.

Page 3: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

3

In this paper we develop a simple information-based In this paper we develop a simple information-based model, that is consistent with empirical findings. We model, that is consistent with empirical findings. We interpret the industry specialization in the source interpret the industry specialization in the source country as providing a comparative advantage to the country as providing a comparative advantage to the potential foreign direct investors, in eliciting good potential foreign direct investors, in eliciting good investment opportunities in the host country, relative investment opportunities in the host country, relative to domestic investors in the latter country:to domestic investors in the latter country:

A lower cost of cream-skimming (of high-productivity A lower cost of cream-skimming (of high-productivity firms) on the part of foreign direct investorsfirms) on the part of foreign direct investors . This . This advantage of FDI investors in their cream-skimming advantage of FDI investors in their cream-skimming skills is less pronounced when corporate skills is less pronounced when corporate transparencies and capital market institutions are of transparencies and capital market institutions are of high quality in which case FDI inflows are less high quality in which case FDI inflows are less abundant.abundant.

Page 4: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

4

• Our model suggests that the gains from FDI are Our model suggests that the gains from FDI are reflected in a more efficient size of the stock of reflected in a more efficient size of the stock of domestic capital and its allocation across firms. domestic capital and its allocation across firms. Domestic firms that are controlled by FDI investors Domestic firms that are controlled by FDI investors are typically the “cream” (high-productivity firms). are typically the “cream” (high-productivity firms). The magnitude of the non-traditional gains from The magnitude of the non-traditional gains from trade that arise in our model depends crucially (and trade that arise in our model depends crucially (and inversely) on the degree of competition among inversely) on the degree of competition among potential FDI investors over the domestic firms. potential FDI investors over the domestic firms. These gains can shrink to zero if there is no such These gains can shrink to zero if there is no such competition altogether. Also, FDI inflows enlarge competition altogether. Also, FDI inflows enlarge the size of the aggregate stock of domestic capital the size of the aggregate stock of domestic capital (under plausible assumptions). (under plausible assumptions).

Page 5: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

5

NN – Large number of ex-ante identical domestic – Large number of ex-ante identical domestic firms.firms.

KK – Capital stock (in the first period). – Capital stock (in the first period).

- Rate of depreciation.- Rate of depreciation.

- Output (in the second period).- Output (in the second period).

- - Productivity factorProductivity factor..

GG – Cumulative distribution function of . – Cumulative distribution function of .

- A common knowledge signal aboutA common knowledge signal about ..

)((KF

'

Page 6: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

6

Cumulative distribution function of , conditional Cumulative distribution function of , conditional

onon :

'

)'()'(

)'()()'()1(

GG

GG

max expected market value of the firm, max expected market value of the firm, conditional on : conditional on :

KK00 – Initial stock of capital – Initial stock of capital

r – world rate of interest. r – world rate of interest.

)'(K'

)'(])1()'([1

)'()1()1)]('([)'()2(

'

'

0

dKKr

KKFV

Page 7: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

7

Therefore:Therefore:

where:where:

rEKF )]'(1)]['([')3(

)'()'()4('

'

dE

Page 8: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

8

Suppose that after an FDI investor acquires and Suppose that after an FDI investor acquires and gains control of the firm, she can apply at a cost gains control of the firm, she can apply at a cost CCFF (lower than for domestic investors) a (lower than for domestic investors) a

screening technique that elicit the true of the screening technique that elicit the true of the firm. Therefore, the bid price of an FDI investor firm. Therefore, the bid price of an FDI investor for a firm with a signal is: for a firm with a signal is:

'

Where:Where:

'11

11][)'()5(

'

'

0*

**

dKKr

KKFCP F

rKF 1')6( *

Page 9: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

9

The ask price of the domestic owners is .The ask price of the domestic owners is .

Therefore, there is a cutoff level of the signal, Therefore, there is a cutoff level of the signal, denoted by , and defined bydenoted by , and defined by

)'(V

F0'

)'()'()7( 00 FFF VCP

such thatsuch that

FF

FF

allforVCP

and

allforVCP

0

0

'')'()'(

'')'()'(

Page 10: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

10

That is: all firms with signals above are That is: all firms with signals above are purchased by FDI investors; all other firms (with purchased by FDI investors; all other firms (with

) are purchased by domestic or foreign ) are purchased by domestic or foreign portfolio investors. portfolio investors.

F0'

F0''

In the absence of FDI, the cutoff signal, denoted In the absence of FDI, the cutoff signal, denoted by , is defined by:by , is defined by:

where Cwhere CDD is the screening cost of domestic is the screening cost of domestic

investors (Cinvestors (CDD>C>CFF).).

We then haveWe then have

D0'

DDD VCP 00 '')8(

DF 00 '')9(

Page 11: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

11

Stock of CapitalStock of Capital

-1 1F0' D0'

'K '* KE

In the absence of FDI

with FDI

'K

'* KE

Note: '''

'

**

dKKE

Page 12: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

12

Results:Results:

(1) Stock of capital is higher with FDI than in its (1) Stock of capital is higher with FDI than in its absence.absence.

(2) Gains from FDI:(2) Gains from FDI:

(a) Efficiency gain –(a) Efficiency gain –

(b) Cost gain –(b) Cost gain –

''')10(0

0

'

'

dGVCPD

F

F

DFD GCC 0'1)11(

Page 13: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

13

Page 14: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

14

Page 15: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

15

Page 16: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

16

Page 17: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

17

Page 18: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

18

Brief Description of Each RoundBrief Description of Each Round

   Round 1Round 1: The three original tables from the : The three original tables from the paper. Gravity Equations for Trade, FDI, and paper. Gravity Equations for Trade, FDI, and Equity with trade residual not including host Equity with trade residual not including host country creditor rights.country creditor rights.

   Round 2Round 2: Regressed trade including host country : Regressed trade including host country creditor rights. The trade residual from this creditor rights. The trade residual from this regression is then used in the regression from regression is then used in the regression from round 1.round 1.

   Round 3Round 3: Replaced Trade Residuals with the : Replaced Trade Residuals with the actual value of Trade. Then ran the same actual value of Trade. Then ran the same regression as in round 1.regression as in round 1.

Page 19: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

19

Round 4Round 4: Replaced the dependent variable to : Replaced the dependent variable to FDI/Trade and Equity/Trade. Then ran the same FDI/Trade and Equity/Trade. Then ran the same regression as Round 3. regression as Round 3.

   Round 5Round 5: Regressed the gravity equation for : Regressed the gravity equation for trade and using the fitted values of trade, then ran trade and using the fitted values of trade, then ran the same regression as in round 4.the same regression as in round 4.

   Round 6Round 6: The same regression as Round 4 : The same regression as Round 4 including time dummy variables.including time dummy variables.

   Round 7Round 7: Replaced the dependent variable to : Replaced the dependent variable to FDI/Equity and ran the same regression as FDI/Equity and ran the same regression as

round 2. round 2.

Page 20: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

20

Round 8Round 8: Replaced the dependent variable with the : Replaced the dependent variable with the volatility of FDI and ran the same regression as volatility of FDI and ran the same regression as round 2.round 2.

   Round 9Round 9: Instrumented the host country Debt-: Instrumented the host country Debt-Equity ratio with Host country GDP per capita, Equity ratio with Host country GDP per capita, host country creditor rights, and host country host country creditor rights, and host country dummies. Then ran the same regression as round 4.dummies. Then ran the same regression as round 4.

Page 21: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

21

Round 1. Gravity Equations for Imports of Goods Round 1. Gravity Equations for Inward FDI Flows

( 1 ) ( 2 )Host Population 0.742 0.883

(3.98)** (5.29)**Source Population 0.976 0.976

(13.25)** (13.24)**Host GDP Per Capita 0.643 0.725

(2.05)* (2.38)*Source GDP Per Capita 0.914 0.889

(3.99)** (3.89)**Distance -0.742 -0.747

(11.89)** (11.99)**Instrumented Telephone Traffic 0.544 0.526

(1.88) (1.82)Source Export Concentration 4.192 4.092

(0.77) (0.75)(Source GDP) X (Source Export Concentration)-0.163 -0.137

(0.2) (0.17)Host Debt-Equity Ratio 0 0.002

(0.05) (0.73)Host Creditor Rights 0.581

(3.62)**Constant 1.558 -0.48

(0.75) (0.22)Number of Observations 324 324R2 Within 0.8843 0.8842R2 Between 0.4131 0.5873R2 Overall 0.5826 0.6968

Page 22: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

22

Round 1. Gravity Equations for Inward FDI Flows Round 1. Gravity Equations for Equity Flows

( 1 ) ( 2 )Host Population 1.185 1.108

(5.04)** (4.56)**Source Population 1.812 1.816

(6.46)** (6.50)**Host GDP Per Capita -0.058 -0.308

(0.09) (0.45)Source GDP Per Capita 6.215 6.218

(7.35)** (7.40)**Distance -0.271 -0.289

(1.19) (1.29)Instrumented Telephone Traffic 2.929 2.835

(2.73)** (2.68)**Source Export Concentration 60.389 61.191

(2.92)** (2.97)**(Source GDP) X (Source Export Concentration)-10.202 -10.316

(3.28)** (3.32)**Trade Residual 0.395 0.509

(2.53)* (3.06)**Host Debt-Equity Ratio -0.013 -0.017

(2.10)* (2.74)**Host Creditor Rights -0.362

(1.54)Constant -28.334 -25.777

(3.78)** (3.39)**Number of Observations 324 324Log Likelihood -630.5 -629.15

Page 23: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

23

Round 1. Gravity Equations for Equity Flows

( 1 ) ( 2 )Host Population 1.82 1.788

(8.35)** (7.19)**Source Population 2 2.005

(7.44)** (7.49)**Host GDP Per Capita 3.163 3.021

(6.25)** (4.67)**Source GDP Per Capita 2.4 2.356

(2.96)** (2.90)**Distance 0.419 0.395

(2.48)* (2.27)*Instrumented Telephone Traffic 7.733 7.612

(5.85)** (5.68)**Source Export Concentration 8.32 9.005

(0.41) (0.45)(Source GDP) X (Source Export Concentration)-2.601 -2.671

(0.87) (0.89)Trade Residual 0.201 0.237

(2.05)* (1.8)Host Debt-Equity Ratio -0.01 -0.01

(2.49)* (1.65)Host Creditor Rights -0.024

(0.12)Constant -52.767 -51.597

(6.56)** (6.20)**Number of Observations 207 207R2 Within 0.603 0.6044R2 Between 0.8952 0.8795R2 Overall 0.684 0.6808

Page 24: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

24

Round 2. Gravity Equations for Inward FDI Flows with new Trade Residual

Round 2. Gravity Equations for Equity Flows with new Trade Residual

( 1 ) ( 2 )Host Population 1.182 1.161

(5.07)** (4.79)**Source Population 1.815 1.817

(6.49)** (6.50)**Host GDP Per Capita -0.23 -0.278

-0.35 -0.41Source GDP Per Capita 6.212 6.21

(7.38)** (7.39)**Distance -0.286 -0.292

-1.27 -1.3Instrumented Telephone Traffic 2.858 2.826

(2.70)** (2.67)**Source Export Concentration 60.931 61.222

(2.96)** (2.97)**(Source GDP) X (Source Export Concentration)-10.275 -10.316

(3.31)** (3.32)**Trade Residual 0.5 0.509

(3.09)** (3.06)**Host Debt-Equity Ratio -0.015 -0.016

(2.69)** (2.62)**Host Creditor Rights -0.069

-0.35Constant -27.234 -26.674

(3.68)** (3.53)**Number of Observations 324 324Log Likelihood -629.209 -629.147

Page 25: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

25

Round 2. Gravity Equations for Equity Flows with new Trade Residual

( 1 ) ( 2 )Host Population 1.811 1.823

(8.06)** (7.35)**Source Population 2.003 2.005

(7.46)** (7.49)**Host GDP Per Capita 3.083 3.037

(5.70)** (4.70)**Source GDP Per Capita 2.361 2.352

(2.91)** (2.89)**Distance 0.399 0.394

(2.34)* (2.27)*Instrumented Telephone Traffic 7.614 7.603

(5.74)** (5.68)**Source Export Concentration 9.049 9.024

(0.45) (0.45)(Source GDP) X (Source Export Concentration)-2.682 -2.671

(0.89) (0.89)Trade Residual 0.22 0.237

(1.86) (1.8)Host Debt-Equity Ratio -0.012 -0.009

(2.58)** (1.59)Host Creditor Rights 0.114

(0.64)Constant -51.782 -52.05

(6.39)** (6.26)**Number of Observations 207 207R2 Within 0.6033 0.6044R2 Between 0.8809 0.8795R2 Overall 0.6802 0.6808

Page 26: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

26

Round 3. Gravity Equations for Inward FDI Flows (with Actual Trade instead of Trade Residual)

Round 3. Gravity Equations for EquityFlows (with Actual Trade instead of Trade Residual)

( 1 ) ( 2 )Host Population 0.862 0.692

(3.16)** (2.41)*Source Population 1.432 1.326

(4.53)** (4.16)**Host GDP Per Capita -0.293 -0.611

(0.43) (0.84)Source GDP Per Capita 5.864 5.765

(6.83)** (6.77)**Distance 0.02 0.086

(0.08) (0.34)Instrumented Telephone Traffic 2.707 2.548

(2.51)* (2.39)*Source Export Concentration 59.175 59.624

(2.86)** (2.89)**(Source GDP) X (Source Export Concentration)-10.202 -10.316

(3.28)** (3.32)**Trade 0.395 0.509

(2.53)* (3.06)**Host Debt-Equity Ratio -0.013 -0.017

(2.11)* (2.75)**Host Creditor Rights -0.362

(1.54)Constant -28.908 -26.519

(3.87)** (3.50)**Number of Observations 324 324

Log Likelihood -630.502 -629.147

Page 27: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

27

Round 3. Gravity Equations for EquityFlows (with Actual Trade instead of Trade Residual)

( 1 ) ( 2 )Host Population 1.659 1.598

(7.19)** (5.78)**Source Population 1.796 1.756

(6.23)** (5.87)**Host GDP Per Capita 2.934 2.751

(5.68)** (4.10)**Source GDP Per Capita 2.17 2.085

(2.65)** (2.52)*Distance 0.555 0.555

(3.01)** (2.83)**Instrumented Telephone Traffic 7.46 7.29

(5.62)** (5.39)**Source Export Concentration 7.856 8.458

(0.39) (0.42)(Source GDP) X (Source Export Concentration)-2.601 -2.671

(0.87) (0.89)Trade 0.201 0.237

(2.05)* (1.80)Host Debt-Equity Ratio -0.01 -0.01

(2.49)* (1.65)Host Creditor Rights -0.024

(0.12)Constant -52.001 -50.694

(6.46)** (6.06)**Number of Observations 207 207

R2 Within 0.603 0.6044R2 Between 0.8952 0.8795R2 Overall 0.684 0.6808

Page 28: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

28

Round 4. Gravity Equations for Inward FDI Flows / Trade Round 4. Gravity Equations for Equity Flows / Trade

( 1 ) ( 2 )Host Population 0.417 0.279

(1.52) (1.14)Source Population 0.793 0.791

(3.04)** (3.02)**Host GDP Per Capita -0.881 -1.105

(1.17) (1.63)Source GDP Per Capita 5.15 5.163

(6.47)** (6.51)**Distance 0.513 0.503

(2.40)* (2.37)*Instrumented Telephone Traffic 2.468 2.407

(2.46)* (2.42)*Source Export Concentration 55.032 55.387

(2.86)** (2.88)**(Source GDP) X (Source Export Concentration)-9.778 -9.831

(3.38)** (3.39)**Host Debt-Equity Ratio -0.01 -0.019

(1.47) (2.84)**Host Creditor Rights -0.676

(3.27)**Constant -29.332 -25.71

(4.18)** (3.63)**Number of Observations 324 324R2 Within 0.1547 0.1542R2 Between 0.2447 0.4904R2 Overall 0.1871 0.2966

Page 29: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

29

Round 4. Gravity Equations for Equity Flows / Trade

( 1 ) ( 2 )Host Population 0.995 0.857

(3.09)** (2.32)*Source Population 0.983 0.988

(3.49)** (3.56)**Host GDP Per Capita 1.63 1.215

(1.72) (1.12)Source GDP Per Capita 1.230 1.222

(1.43) (1.44)Distance 1.088 1.074

(5.81)** (5.78)**Instrumented Telephone Traffic 6.355 6.294

(4.46)** (4.46)**Source Export Concentration 5.285 6.072

(0.25) (0.29)(Source GDP) X (Source Export Concentration)-2.539 -2.636

(0.81) (0.85)Host Debt-Equity Ratio -0.007 -0.011

(0.86) (1.15)Host Creditor Rights -0.505

(1.54)Constant -47.756 -44.241

(5.38)** (4.87)**Number of Observations 207 207R2 Within 0.2853 0.2858R2 Between 0.3746 0.5074R2 Overall 0.3152 0.3919

Page 30: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

30

Round 5. Gravity Equations for Inward FDI Flows / Trade (with fitted value of Trade)

Round 5 Gravity Equations for Equity Flows / Trade (with fitted value of Trade)

( 1 ) ( 2 )Host Population 0.039 0.034

(0.2) (0.18)Source Population 0.801 0.804

(2.65)** (2.66)**Host GDP Per Capita 0.289 0.196

(0.74) (0.49)Source GDP Per Capita 5.459 5.391

(6.07)** (5.98)**Distance 0.696 0.639

(3.23)** (2.85)**Instrumented Telephone Traffic 3.348 3.163

(3.17)** (2.93)**Source Export Concentration 51.092 51.884

(2.32)* (2.35)*(Source GDP) X (Source Export Concentration)-9.562 -9.59

(2.87)** (2.88)**Host Debt-Equity Ratio -0.013 -0.014

(3.81)** (3.90)**Host Creditor Rights -0.105

(0.91)Constant -35.697 -34.011

(4.76)** (4.40)**Number of Observations 270 270R2 Within 0.1569 0.1578R2 Between 0.6243 0.6297R2 Overall 0.2739 0.2762

Page 31: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

31

Round 5 Gravity Equations for Equity Flows / Trade (with fitted value of Trade)

( 1 ) ( 2 )Host Population 0.483 0.482

(2.36)* (2.34)*Source Population 1.163 1.164

(3.92)** (3.91)**Host GDP Per Capita 2.186 2.181

(6.61)** (6.44)**Source GDP Per Capita 1.496 1.492

(1.77) (1.76)Distance 1.09 1.087

(6.58)** (6.31)**Instrumented Telephone Traffic 5.896 5.879

(4.30)** (4.22)**Source Export Concentration 22.013 22.17

(1) (1)(Source GDP) X (Source Export Concentration)-5.339 -5.356

(1.61) (1.61)Host Debt-Equity Ratio -0.01 -0.011

(3.83)** (3.64)**Host Creditor Rights -0.007

(0.08)Constant -47.097 -46.981

(5.77)** (5.64)**Number of Observations 175 175R2 Within 0.2858 0.2859R2 Between 0.8874 0.8872R2 Overall 0.468 0.468

Page 32: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

32

Round 6. Gravity Equations for Inward FDI Flows/Trade with Time Dummy Variables

Round 6. Gravity Equations for Equity Flows/Trade with Time Dummy Variables

( 1 ) ( 2 )Host Population 0.533 0.382

(1.91) (1.52)Source Population 0.809 0.805

(3.11)** (3.08)**Host GDP Per Capita -0.019 -0.498

(0.02) (0.66)Source GDP Per Capita 5.775 5.711

(6.81)** (6.72)**Distance 0.645 0.619

(2.90)** (2.80)**Instrumented Telephone Traffic 3.073 2.941

(2.96)** (2.84)**Source Export Concentration 57.161 57.175

(2.98)** (2.97)**(Source GDP) X (Source Export Concentration)-10.329 -10.306

(3.57)** (3.55)**Host Debt-Equity Ratio -0.012 -0.019

(1.65) (2.89)**Host Creditor Rights -0.639

(3.07)**Dummy for 1990-1992 -36.593 0.462

(4.67)** (1.74)Dummy for 1993-1995 -36.991 0.103

(4.68)** (0.45)Dummy for 1996-1998 -37.143 0

(4.67)** (.)Constant 0 -32.231

(.) (4.04)**

Number of Observations 324 324R2 Within 0.1666 0.1643R2 Between 0.2667 0.4947R2 Overall 0.2021 0.3038

Page 33: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

33

Round 6. Gravity Equations for Equity Flows/Trade with Time Dummy Variables

( 1 ) ( 2 )Host Population 1.066 0.922

(3.12)** (2.18)*Source Population 1.005 1.008

(3.58)** (3.65)**Host GDP Per Capita 2.026 1.643

(1.87) (1.19)Source GDP Per Capita 1.46 1.433

(1.65) (1.64)Distance 1.135 1.118

(5.90)** (5.85)**Instrumented Telephone Traffic 6.72 6.637

(4.60)** (4.60)**Source Export Concentration 5.849 6.542

(0.28) (0.32)(Source GDP) X (Source Export Concentration)-2.727 -2.798

(0.87) (0.91)Host Debt-Equity Ratio -0.009 -0.012

(1.02) (1.13)Host Creditor Rights -0.497

(1.31)Dummy for 1991-1993 0 0

(.) (.)Dummy for 1994-1996 -0.203 -0.185

(1.08) (0.95)Dummy for 1997-1999 0 0

(.) (.)Constant -51.08 -47.585

(5.39)** (4.78)**

Number of Observations 207 207R2 Within 0.2882 0.2882R2 Between 0.3743 0.5296R2 Overall 0.3252 0.4071

Page 34: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

34

Round 7. Gravity Equations for Inward FDI Flows / Equity Flows

( 1 ) ( 2 )Host Population -0.316 -0.534

(0.98) (1.46)Source Population -0.258 -0.432

(0.61) (0.99)Host GDP Per Capita -3.16 -3.53

(4.69)** (4.44)**Source GDP Per Capita 4.374 4.19

(3.59)** (3.44)**Distance -0.189 -0.064

(0.71) (0.23)Instrumented Telephone Traffic -0.634 -0.975

(0.32) (0.49)Source Export Concentration 29.727 30.343

(0.99) (1.02)(Source GDP) X (Source Export Concentration)-4.661 -4.89

(1.03) (1.1)Trade 0.117 0.291

(0.9) (1.74)Host Debt-Equity Ratio -0.002 -0.006

(0.34) (0.9)Host Creditor Rights -0.343

(1.48)Constant 5.545 8.39

(0.47) (0.69)Number of Observations 207 207R2 Within 0.2326 0.2431R2 Between 0.7046 0.7R2 Overall 0.3806 0.3868

Page 35: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

35

Round 8. Gravity Equations for Volatility of Inward FDI Flows

( 1 ) ( 2 )Host Population 0.911 0.683

(2.94)** (1.92)Source Population 0.747 0.579

(3.60)** (2.56)*Host GDP Per Capita 0.2 -0.18

(0.23) (0.19)Source GDP Per Capita 3.565 3.327

(4.99)** (4.61)**Distance 0.14 0.222

(0.55) (0.87)Instrumented Telephone Traffic 3.567 3.3

(3.09)** (2.85)**Trade 0.416 0.592

(2.56)* (3.13)**Host Debt-Equity Ratio -0.014 -0.023

(1.76) (2.20)*Host Creditor Rights -0.5

(1.55)Constant -24.776 -21.009

(3.01)** (2.46)*Number of Observations 216 216R2 Within 0.507 0.5147R2 Between 0.5527 0.5386R2 Overall 0.5047 0.5043

Page 36: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

36

Round 9. Gravity Equations for Inward FDI Flows / Trade (with Fitted Value of Host Debt-Equity Ratio)

Round 9. Gravity Equations for Equity Flows / Trade (with Fitted Value of Host Debt-Equity Ratio)

( 1 ) ( 2 )Host Population 0.341 0.193

(1.36) (0.74)Source Population 0.777 0.775

(2.94)** (2.95)**Host GDP Per Capita -1.079 -1.415

(1.56) (2.00)*Source GDP Per Capita 5.215 5.257

(6.50)** (6.59)**Distance 0.571 0.575

(2.68)** (2.71)**Instrumented Telephone Traffic 2.67 2.675

(2.66)** (2.68)**Source Export Concentration 53.308 53.633

(2.74)** (2.78)**(Source GDP) X (Source Export Concentration)-9.602 -9.667

(3.28)** (3.32)**Host Debt-Equity Ratio -0.01 -0.01

(0.74) (0.74)Host Creditor Rights -0.448

(2.15)*Constant -30.561 -28.214

(4.34)** (3.98)**Number of Observations 324 324R2 Within 0.1544 0.1551R2 Between 0.1965 0.3133R2 Overall 0.1678 0.221

Page 37: 1 The Role of Information in Driving FDI: Theory and Evidence Ashoka Mody, IMFAshoka Mody, IMF Assaf Razin, Tel-Aviv University and Cornell UniversityAssaf.

37

Round 9. Gravity Equations for Equity Flows / Trade (with Fitted Value of Host Debt-Equity Ratio)

( 1 ) ( 2 )Host Population 0.946 0.82

(2.70)** (2.08)*Source Population 0.996 1.002

(3.56)** (3.61)**Host GDP Per Capita 1.318 0.947

(1.28) (0.83)Source GDP Per Capita 1.313 1.334

(1.53) (1.56)Distance 1.104 1.102

(5.93)** (5.93)**Instrumented Telephone Traffic 6.499 6.509

(4.58)** (4.61)**Source Export Concentration 5.789 6.286

(0.28) (0.3)(Source GDP) X (Source Export Concentration)-2.633 -2.707

(0.84) (0.87)Host Debt-Equity Ratio 0.001 0.001

(0.09) (0.07)Host Creditor Rights -0.375

(1.13)Constant -48.058 -45.772

(5.37)** (5.01)**Number of Observations 207 207R2 Within 0.2874 0.2888R2 Between 0.3557 0.3708R2 Overall 0.289 0.32