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Robert J.R. Elliott (University of Birmingham, UK)Puyang Sun (Nankai University, China)Siyang Chen (National University of Singapore, Singapore)FDI, Energy Intensity and Growth:Evidence from Chinese Cities1MotivationChina now has become the largest recipient of foreign investment in the developing world with inflows of $95.25 billion in 2010 (World Development Indicators 2010)

China currently accounts for 17.7% of global energy consumption to produce approximately 8% of global output

In 2008 Chinas emissions of sulphur dioxide (SO2) and carbon dioxide (CO2) were the highest and second highest in the world at 23.32 million and 2.7 billion tons respectively

In this paper we investigate the relationship between economic development, FDI and the efficiency of energy consumption in China

2Energy Intensity (ENTI)is ameasureof the energy efficiency of aneconomy, which is calculated as units ofenergyper unit ofGDP

Industrial Energy Intensity (ENDD)

Energy intensity is negatively correlated with energy efficiency Measurement of Energy Efficiency

3Improving the energy efficiency of Chinese firms is essential to the sustainable developmentof the country.

Energy efficiency is not only important from a pollution perspective but also from the perspective of being able to use less oil, gas and coal in production (and hence less imports) and hence cheaper products.

One possible channel to enhance energy efficiency is energy-saving technology transfer from developed to developing countries

FDI is considered a critical channel for technology transfer (Keller 2004)

4 cities with the highest & lowest aggregate energy efficiency cities with the highest & lowest industrial energy efficiency CityENTICityENTICityENDDCityENDDNingde0.545 Panzhihua**3.581 Haikou 0.241 Qitaihe* 6.589 Shanwei0.567 Baise**3.677 Zhongshan 0.451 Hegang* 6.606 Shenzhen0.568 Lvliang*3.723 Xiamen 0.500 Yuncheng* 6.898 Taizhou0.595 Linfen*4.068 Shenzhen 0.564 Xinzhou* 7.103 Xiamen0.625 Zhongwei**4.300 Yanan** 0.671 Weinan** 7.174 Zhuhai0.632 Laiwu4.385 Putian 0.695 Shuangyashan* 7.316 Shantou0.658 Wuhai*5.671 Wenzhou 0.710 Laibin** 7.578 Zhanjiang0.698 Wuzhong**5.952 Foshan 0.764 Dazhou** 7.973 Zhangzhou0.703 Shizuishan**7.651 Heyuan 0.797 Heihe* 8.150 Wenzhou0.705 Liupanshui**8.691 Zhoushan 0.810 Jixi* 10.391 Source: China City Statistical Yearbook, 2006-2009*Indicates cities in central region**Indicates cities in western regionTop 10 and Bottom 10 Cities of Energy Efficiency in China, 2005-2008Nearly all the cities with highest level of energy efficiency are in eastern coastal provinces The majority of cities at the bottom belong to the central or western areas5Cities with the highest FDI inflow in actual useCities with the highest agglomeration in finance sectorFigure 1 The Geographic Distribution of Agglomeration and FDI (2003-2008)LiteratureFDI & Energy ConsumptionAuthorsEvidenceLimitationEskeland & Harrison (2003) Foreign ownership is associated with more energy-efficient production in an analysis of manufacturing plants in Cote dIvoire, Mexico and Venezuela. These studies are based on cross-country panel data in which heterogeneity may result in misspecification

Cole et al. (2011)

Multinational firms are less pollution intensive than domestic firms since the latter may utilize more advanced technologies, cleaner production methods, and possess more developed environmental management systemsChichilnisky (1994) Motta & Thisse (1994)Pollution Havens Hypothesis: FDI may be attracted to economies by less stringent environment regulationsHbler & Keller (2009) Aggregate FDI inflows do not help to reduce energy intensity in a developing country context6ContributionWe employ an extensive city-level data set that covers 206 of Chinas largest cities for the period 2005-2008 to investigate more closely the relationship between economic growth, FDI and the efficiency of energy consumption in China

We believe that a city-level study is a better able to represent regional differences compared with the more usual province level studies

We examine the relationship between the output of domestically-owned, foreign-owned and by Hong Kong, Taiwan and Macao (HTM) owned firms to better understand the relationship between FDI and local energy intensity

7Mechanism Total energy consumption can be decomposed into three channels: (Hbler and Keller, 2009) Scale effect is left out when energy intensity is used (Keller, 2009)

One of indirect effects from FDI to energy savings in our estimationThe main dimension in our study8Technique effects of FDI on Energy Savings9Core question:Does FDI envourage energy saving (i.e. reduce energy intensity) in China through the technique effect?

Sub-questions: How do technique effects of FDI differ across Chinese cities? If the effect of FDI differs by region, what are the mechanisms that drive these differences ?

10Regional facts of Energy Intensity

Lighter dots: Cities with lower energy intensity (i.e., higher energy efficiency)11Regional distribution of FDI

Darker dots: Cities with higher FDI inflows12

Regional facts of income Darker dots: Cities with higher income level

13These maps suggest:

Cities with the highest income are also those that receive the greatest volume of FDI, and

Cities with the highest income have higher energy efficiency (lower value of energy Intensity)

We now identify if these relationships hold econometrically and whether these relationships are consistent across Chinese cities and which if not which mechanisms drive any regional differences14

Estimation equation& Empirical resultsVariableDefinition of VariableFunction of variableExpectedsignExplained VariablesENTIAggregate energy intensityENDDIndustrial energy intensityExplaining VariablesYPC2quadratic term of income per capitato capture the inverted-U shaped relationship between YPC and EI-FDIForeign direct investment normalized by GDP (%)to capture the energy-saving technology transfer of FDI-GIPfIndustrial product normalized by GDP for foreign countries invested firmsto capture the energy-saving technology transfer of foreign investment alternatively-GIPhIndustrial product of the firms from HTM, normalized by GDPto compare the effects of foreign firms and firms from HTM+/-GIPdGross industrial product normalized by GDPto compare the effects of foreign and domestic investment+15VariableDefinitionSourceEIEnergy Intensity, energy consumption per unit of GDP (ton per 10,000 yuan)Government Report (2006-2010) by Chinese Provincial Bureau of Statistics YPCIncome per capita (2005 price).China City Statistical Yearbook (2010)

FDIShare of foreign direct investment in GDP (100 yuan per yuan) (%)GIPd,h,fIndustrial product normalized by GDP for domestic/HTM/foreign firms (100 yuan per yuan)Data (From 2005 to 2008, across 206 Chinese municipal-cities )16ENTIENDD123456123456YPC-0.2527***1.1633**-0.2693***1.5326***-0.6432**-0.1533-0.3772***2.8992**-0.4552***2.3817*-1.1829*0.6106YPC2-0.0785***-0.0970***-0.0185-0.1877***-0.1584**-0.0676FDI-0.0197***-0.0267***-0.0309**-0.0339**GIPd0.1228 ***0.0958 ***0.2553**0.1189GIPf-0.0018-0.00190.0183-0.0116GIPh-0.0028-0.0030-0.0287*-0.0537*Hausman for RE1.47(0.225)1.79(0.408)2.85(0.242)3.44(0.329)8.21(0.084)26.52(0.000)1.33(0.250)2.58(0.276)2.82(0.244)0.37(0.947)16.15(0.024)1.12(0.952)Hausman for IV 17.67(0.000)5.53(0.063)9.82(0.007)7.04(0.071)15.13(0.004)23.55(0.000)13.92(0.000)10.02(0.007)9.58(0.008)7.02(0.071)12.58(0.014)25.29(0.000)Turning point(RMB)1651.72697.32259.61840.9Results (National Level)17YPC & EI (national regression)

Column 2, 4 :

Inverted-U relationship between income per capita and energy intensity is confirmed at the national levelTurning point of the inverted-U curve is estimated at between RMB 1,651 and RMB 2,697 for ENTI, and RMB 1,840 and RMB 2,259 for ENDDThe majority of Chinese cities belong to the downward sloping part of the inverted-U curve, which means the rising income per capita contributes to energy savings in these citiesA significant income-induced technique effect is expected to be found in the cities with higher income levels

18 income-induced effect

We propose that there is an inverted-U-shaped relationship between income per capita and energy intensity. The nonlinear relationship is expected to exist at the national level

At the regional level, we pay more attention to the linear relationship between income and energy intensity, which reflects the income-induced technique effect

The income-induced effect intensifies with the income level and is expected to be prominent in the region with higher income Indirect technique effects:19FDI & EI (national regression)

Column 3, 4 inflows of FDI facilitate energy savings in ChinaA 1% of FDI inflows will generate a 0.02%-0.027% reduction in aggregate energy intensityA 1% of FDI inflows will generate a around 0.03% reduction in industrial energy intensity

20Columns 5, 6

Production of domestic firms can lead to a reduction of energy efficiency in China

Production of firms from HTM is helpful to enhance energy efficiency in China

It is further confirmed that foreign firms help to enhance energy efficiency in China

Industrial Production(GIPd, GIPf,GIPh) & EI(national regression)21Eastern Areas (A)Central Areas (B)Western Areas (C)A(1)A(2)A(3)A(4)B(1)B(2)B(3)B(4)C(1)C(2)C(3)C(4)YPC-0.3770***0.6841*-0.5340***-0.30640.1978***3.9294***-0.14490.42580.15820.86870.0528-0.0559YPC2-0.0554***-0.0081-0.2189***-0.0457-0.03860.6606FDI-0.0014-0.0043-0.0884***-0.0523***-0.0458***-0.0517***GIPd0.1938***0.1599**0.1475*0.1933**0.2386***0.0032*GIPf0.0063-0.0017-0.0250-0.0034-0.0360*-0.0070GIPh0.0176*0.0095-0.0343**-0.0184*-0.0322**-0.0091Test RE4.32(0.116)4.05(0.256)7.73(0.357)8.28(0.407)0.05(0.976)5.98(0426)2.46(0.652)1.29(0.936)3.99(0.136)2.93(0.403)8.51(0.290)26.08(0.000)Test IV87.33(0.000)157.28(0.000)10.41(0.034)50.45(0.000)112.91(0.000)16.6(0.010)37.68(0.000)1188.68(0.000)6.6(0.037)16.09(0.001)13.37(0.010)6.81(0.236)Results (Regional Level)22Eastern Areas (A)Central Areas (B)Western Areas (C)A(1)A(2)A(3)A(4)B(1)B(2)B(3)B(4)C(1)C(2)C(3)C(4)YPC-0.4178***6.4257*0.02360.3819-0.02883.5690*-0.3560*1.0862-0.3236*-6.1219-0.3604*-12.963**YPC2-0.3714**-0.056-0.2106*-0.09260.35320.7370**FDI-0.0426-0.0443-0.0548***-0.0484***-0.0204-0.0295*GIPd0.3154***0.2528**-0.0765-0.0552-0.00910.1729GIPf-0.1307**0.0026-0.0206-0.0030-0.0226-0.0315GIPh-0.1419***-0.1002***-0.0206-0.0258-0.0369**-0.0032TestRE5.54(0.354)1.63(0.652)2.57(0.632)6.37(0.272)0.76(0.685)1.19(0.978)1.65(0.977)0.68(0.984)1.66(0.437)0.25(0.968)4.16(0.385)4.12(0.532)TestIV13.82(0.001)34.94(0.000)9.70(0.046)10.07(0.073)22.35(0.000)15.01(0.002)26.00(0.000)15.82(0.007)6.02(0.049)8.05(0.045)27.19(0.000)188.91(0.000)Results (Regional Level)23YPC & EI (regional results)EAST (Group A)A significant negative linear relationship is confirmed The income-induced technique effect is significant in the East China: in this area energy efficiency will ascend in accordance with income per capita CENTER (Group B)For both ENTI and ENDD, an inverted-U relationship between YPC and EI is confirmed with negative and positiveFor ENTI, there is a significantly positive linear relationship between income and energy intensity in this region, while for ENDD, this relationship becomes negativeThe income-induced technique effect is ONLY significant for aggregate energy intensity in Central China.WEST (Group C)For ENTI, NO significant relationship between income and energy intensity is found ( linear or nonlinear) For ENDD, a negative linear relationship exists Similarly, the income-induced technique effect is also ONLY significant for aggregate energy intensity in Central China

24FDI & EI (regional results)A direct technique effect from FDI is insignificant for the east and exhibits a magnified in the central and western regions in terms of both significance and absolute value

The value of is slightly larger in the central rather than the western areas of China

The elasticity of ENTI on foreign investment is higher than that estimated for ENDD

In western cities, there is highly possible to exist a relatively higher technical difference between firm with FDI and domestic firms, compared with lower difference gap in eastern cities. This provide a reasonable reason to explain why the technical effects in western cities are more significant than in eastern cities.

25Demonstration effect:

We denote demonstration effects in East, Center and West China by D1, D2 respectively so that:

EastCenter & WestTechnological gap between domestic and foreign firmssmalllargeDemonstration effectLess SignificantMore SignificantMathematical expression D1 < D2Direct Technique Effect of FDI - regional analysis26Vertical linkage effect

We denote the vertical linkage effect in the east, center and west of China by V1, V2 respectively so that we have:

EastCenter & Westexport and import-oriented HighLowForeign ownershipIntegration of business chainVertical spilloverLess SignificantMore significantMathematical expression V1