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Nita Rudra, University of Pittsburgh Siddharth Joshi, Indian Institute of Management, Bangalore Good for the Goose, Bad for the Flock? FDI in Developing.

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Presentation on theme: "Nita Rudra, University of Pittsburgh Siddharth Joshi, Indian Institute of Management, Bangalore Good for the Goose, Bad for the Flock? FDI in Developing."— Presentation transcript:

1 Nita Rudra, University of Pittsburgh Siddharth Joshi, Indian Institute of Management, Bangalore Good for the Goose, Bad for the Flock? FDI in Developing Countries (with special focus on India)

2 2 Puzzle: Limited research on how FDI affects the poor?  Political economy has yet to uncover the many complexities of FDI  Existing literature: FDI affects growth, inequality, labor rights, wages, and employment.  But these can improve without impacting quality of life of majority of population in developing countries (Sen 1987, 2003)  Point: we have limited understanding of how FDI impacts the well- being of host populations

3 3 Research focus: The links between FDI, water, and the poor  Study of FDI impacts on poor should focus on water because:  It is the poor who lack access in developing countries  It provides a more complete picture of well-being of the poor  Existing research on water access has neglected the role of international economic factors  It is a precise way to unravel (some of) the complexities of FDI and its effects on host populations

4 4 Argument in Brief: FDI contributes to water crises  FDI helps improve the well-being of the poor only under certain circumstances: low socioeconomic diversity  Much of the rapidly expanding sectors attracting FDI in developing countries are highly water intensive or water-polluting, or both  FDI= key mechanism for tech transfer and best practices  BUT foreign investors have limited incentive to treat water as a valuable resource  AND governments have limited incentives in diverse countries to regulate MNC activities or implement comprehensive water policies

5 5 3. Theoretical foundation: FDI as a factor in water access  OLI framework: host countries must offer locational advantages to firms (Dunning 2001, 1998, 1973)  The Pollution Haven Hypothesis: developing countries have a comparative advantage in ‘dirty’ products  Findings: Free trade is good for the environment (Bhagwati 2004, Frankel 2003, de Soysa and Neumayer2005, Birdsall and Wheeler 1993, Grossman and Krueger 1994, Amtweiler, Copeland and Taylor 2001) Issues...  Focus on atmospheric pollution  Neglect extent of water consumption  Most focus on trade effects

6 6 3. FDI could help…but limited incentives  Much of the expanding sectors for FDI in developing countries are water-intensive and/or water-polluting (electric and electronic products, machinery, automotive products, metals, food and beverages)  Spread of best practice is unlikely:  South-South FDI on the rise  Most FDI in developing countries is market-oriented  Lower consumer awareness in internationally and domestically

7 7 3. Weak government regulations As multinational firms demand greater access to water and increase water pollution, potable water declines  Weakly enforced water regulations (supply and usage)  Low tariffs=> prevents cost recovery to provide access to gen pop  Corruption: Rent seeking occurs as governments underreport water use, accepting bribes to cover wastewater discharge and pollution ( Global Corruption Report 2004) H1: FDI will have an adverse impact on access to potable water

8 8 3. But FDI does not hurt water access in all countries Government preferences are related to level of inequality and ethnic diversity :  Richer groups in unequal countries prefer the status quo, and hold more political sway relative to larger group of disadvantaged poor (logic based on Alesina, Baqir, and Easterly 1999)  Rich already have access to potable water in developing countries; they benefit the most from water subsidies (Human Development Report 2006, World Bank 2005).  Reforms would result in higher costs for themselves and multinationals  This group of elites favor multinationals (Pandya 2010)  Ethnic diversity increases chasm between elites and masses  In more equal countries, larger middle classes shares an economic interest in regulating MNCs and comprehensive water policies.

9 9 3. FDI impacts will be conditioned by government preferences  High inequality is associated with weak conflict mediating institutions (World Development Report 2005, Acemoglu, Johnson and Robinson 2001, Engerman et al 2002, Easterly, Rizen and Woolcock 2006)  Reasons: historical  inequality lends itself to a power structure that is crystallized in institutions  Political elites systematically neglect subordinate groups in unequal societies H2: FDI will slow access to potable water in countries with high socioeconomic diversity

10 10 3. Case study: India  Increases confidence that a link between FDI and India’s water crisis  Additional causal mechanisms:  FDI does have environmentally friendly technologies, but insufficient  FDI boosts productivity and output of local firms (Haskel, Pereira and Slaughter 2002).

11 3. Theoretical Predictions : Impact of FDI on Poor

12 12 4. Impact of FDI on Water Consumption and Water Pollution Models Industrial water withdrawal (% total water withdrawal) Organic water pollutant (BOD) emissions (kg per day) (1)(2)(3) FDI inflow 0.209* (0.119) 1.500** (0.593) 0.0465*** (0.0123) Population 3.836*** (1.331) 0.337 (1.568) 1.082*** (0.0598) Urban population (%) 0.0239** (0.0112) -0.0973 (0.126) 0.00674** (0.00296) GDP per capita 8.015** (3.364) 0.458*** (0.0641) GDP growth -1.138 (1.141) -0.666** (0.272) Constant -59.93*** (20.81) -50.57 (37.86) -10.96*** (1.466) N18789119 R-squared0.2360.1540.680

13 4. FDI and potable water access in developing countries Models Access to water (% change) (1)(2)(3)(4)(5) FDI inflow (t-1) -0.0181** (0.00782) 0.0569 (0.0546) 0.118* (0.0654) 0.100* (0.0498) 0.0112*** (0.00153) Socio-economic diversity 0.0999 (0.0591) Estimated Household Income Inequality (EHII) 0.00587 (0.00543) Gini index 0.0102*** (0.00279) 0.00544*** (0.000609) FDI flow (t-1) *Socio-economic diversity -0.0443* (0.0235) FDI flow (t-1) * EHII -0.00323* (0.00168) FDI flow (t-1) *Gini index -0.00275*** (0.000942) -0.000256*** (5.51e-05) Non-military gov spending (t-1) -5.39e-05 (4.00e-05) -3.59e-05 (2.25e-05) 3.45e-06 (5.31e-05) 0.00374*** (0.000693) Economic growth 0.00405 (0.0147) 0.00381 (0.00872) 0.00907 (0.0131) -0.0175** (0.00708) Climate change 0.0230 (0.0213) -0.00102 (0.0140) 0.0165 (0.0171) 0.0126 (0.0188) GDP per capita -0.0112 (0.0587) -0.0249 (0.0399) -0.0217 (0.0393) -0.0219*** (0.00717) Urban population -0.00211 (0.00139) -0.000844 (0.000914) -0.0217 (0.0393) Population 0.477 (0.375) 0.533 (0.361) 0.516* (0.268) 0.0201*** (0.00239) Polity 0.00592 (0.00468) 0.00594 (0.00412) 0.00110 (0.00490) 0.00474*** (0.00145) Fixed EffectsNo Yes Year EffectsYes No Region EffectsNo Yes N77395040 108 R-squared0.2520.5980.4730.703 0.98

14 14 4. India : Impact of FDI on Water Supplies Models ADD CasesAccess to water (%age change) (1)(2)(3)(4)(5) a (6) a FDI inflow (t-2) 0.0967* (0.0502) 0.101* (0.0591) 0.111* (0.0595) -0.00345*** (0.00122) -0.00283** (0.00118) -0.00270** (0.00120) Population growth 1.354 (0.974) 1.079 (1.026) 2.96 (0.0319) 4.70 (0.0405) Economic growth -0.131 (0.712) 0.0262 (1.209) 0.0548* (0.0321) 0.0778** (0.0393) Urban pop -0.124 (0.354) GSDP per cap 0.517 (0.815) -0.00847 (0.0247) Water exp per cap -0.161 (0.202) -0.000406 (0.00586) Health exp per cap 0.656 (0.489) State fixed effectsNoYes NoYes Year fixed effectsNoYes NoYes a N247231217262243224 R-squared0.9660.9740.9730.0650.3100.308

15 4. Impact of FDI on HHLD Access to Piped Water in India Models Access to water (% change) MV: Socioeconomic inequality MV: Weaker section population MV: Conviction rate (1)(2)(3)(4) FDI inflow (t-2) -0.00282** (0.00118) 4.326*** (1.129) 0.0112 (0.00691) -0.00537 (0.00334) Socio-economic diversity -0.0145* (0.00822) 0.110 (0.0811) SC/ST (% population) 0.00389** (0.00152) Conviction rate -0.0153* (0.00857) FDI flow (t-2) *Socio-economic diversity -2.165*** (0.564) FDI flow (t-2) *% SC/ST -0.000660* (0.000341) FDI flow (t-2) *Conviction rate 0.0608* (0.0356) Population growth 0.0332 (0.0327) 0.0404 (0.0331) -0.0522 (0.0511) -0.138*** (0.0376) State econ growth 0.0574* (0.0325) 0.0496 (0.0402) 0.0736*** (0.0284) 0.0946*** (0.0328) Urban pop -0.0263 (0.103) 0.130 (0.376) 1.184 (0.740) GSDP -0.0171 (0.0185) 0.0149 (0.0338) -0.129** (0.0546) Water expenditure per capita -0.00153 (0.00334) -0.00288 (0.00546) 0.00267 (0.00732) Access to water (% change) (t-1) 0.0621 (0.184) 0.457** (0.228) 0.390 (0.294) State fixed effectsYes Year fixed effectsYes a Yes N243224 165 R-squared0.3100.8420.6440.668

16 16 4. Impact of FDI on HHLD Access to Piped Water

17 17 4. Impact of FDI on HHLD Access to Piped Water Dependent Variable: Access to water (%age change) Manufact FDI Services FDI Manufacturing Subsector FDI Textile FDI Chemicals FDI Food and Beverages FDI Electrical Machinery FDI Transport Equipment FDI FDI (Disaggregated) -0.00347** (0.00170) 0.00747 (0.00480) -0.00938** (0.00456) -0.00195 (0.00452) 0.0262 (0.0578) -0.0467 (0.0634) 0.000133 (0.00252) Population growth 0.0256 (0.0330) -0.0720 (0.206) -2.407*** (0.835) 0.0556 (0.0487) -0.365 (0.342) -1.315 (0.925) -3.033** (1.545) State Economic growth 0.0533 (0.0342) 0.100** (0.0504) 0.0655* (0.0389) 0.105** (0.0510) 0.0889 (0.0568) 0.161 (0.100) 0.129** (0.0513) Year Fixed Effects Yes State Fixed Effects Yes N222171451551477799 R-squared0.2920.3110.7810.3370.5310.5980.630

18 18 5. Conclusions and Contributions  FDI can adversely affect water access in countries with skewed distributions of income  Potential contributions to debates in CPE, IPE and IE:  Do multinationals flock to developing countries because of weak regulations (PHH)?  Likely  Contribution: Need to consider water pollution and water consumption  Does global market integration undermine government control?  FDI pressures can reinforce government inaction  Contribution: different mechanisms at play  Does FDI help the poor?  In homogenous developing countries; some political responses to globalization can be predicted on the basis of inequality and ethnic heterogeneity  Contribution: impacts of openness may be conditioned by class cleavages


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