國際貿易視角下外商直接投資對制造業部門的影響中國和印度的比較研究

來源: www.tcwpwd.live 作者:vicky 發布時間:2019-10-20 論文字數:33625字
論文編號: sb2019092009201427898 論文語言:English 論文類型:碩士畢業論文
本文是一篇國際貿易論文,本文通過建立自回歸分布滯后模型(ARDL)考察中印兩個國家 FDI 與制造業部門之間的實證關系,并進行協整以估計模型。E-views 和 Stata 軟件已用于數據分析。
本文是一篇國際貿易論文,本結果表明,中國制造業對外商直接投資對制造業增長的影響具有統計顯著性,然而,國內投資對制造業增長的影響微不足道甚至產生了負面影響。同樣,研究結果表明外國直接投資對印度制造業產生了重大而積極的影響。但是,兩個重要的解釋變量即人力資本和國內投資的影響微不足道。結果證實,與印度相比,中國外國直接投資對制造業增長產生了顯著的積極影響,雖然印度利用外商直接投資也顯示出積極的影響,但它遠遠落后于中國市場。

CHAPTER 1: INTRODUCTION

1.1  Introduction and Background
Over the past few decades, FDI has remarkably  increased throughout the world, exceeding  the  growth  of   international  trade  and  world  production  (Herzer  and  Klasen 2008,  Simionca  2013).  It  has  experienced  a  continuous  increase  exceeding  other international  trade  transactions,  which  ultimately  makes  it  the  prime  economic transaction across the globe (Graham and Krugman 1993). Most importantly, the increase is  noteworthy  for  the  developing  countries,  where  it  has  become  the  most  stable  and largest  component  of  capital  flows  (Alfaro,  Chanda  et  al.  2004).  Its  importance  has enforced  the  countries  to  adopt  favorable  policies  in  order  to  attract  more  FDI  and  to access  modern  technologies.  In  this  context,  developing  countries  created  a  history  in 2012 for the very first time and received more FDI than developed countries. A total of nine  development  countries  secure  their  position  in  the  list  of  twenty  largest  FDI recipients  in  the  world  (UNCTAD  2013).  The  importance  of  FDI  has  revitalized  the debate about its costs and benefits and several developing countries are taking measures to attract higher FDI flows based on this supposition that it is an important stimulus for economic growth (Aykut and Sayek 2007).
Manufacturing  has  traditionally  played  a  key  role  in  the  economic  growth  of developing  as  well  as  the  developed  countries.  Development  of  any  country  is  largely reliant  on  its  manufacturing  sector  of  the  economy  (Szirmai  2012).  Historically,  it  has been  proved  to  be  the  driver  of  economic  growth  and  it  is  no  more  considered  as  the corner stone (Naudé and Szirmai 2012, Herman 2016). In general, manufacturing sectors, difficult  and  sluggish  recovery  into  an  economic  revival  (Adugna  2014).  A  study conducted  by  Kuznets  et  al.  (Kuznets  and  Murphy  1966)  described  that  an  increased share  of  manufacturing  in  GDP  is  a  key  factor  of  modern  economic  growth  and  it  is regarded as the main engine of fast growth. It is also noteworthy from the recent studies pertaining to China and India that even in the manufacturing sector, a larger proportion of total FDI inflow is invested in the high-tech industries (Caves and Caves 1996). Over the years,  the  high-tech  industries  making  it  approximately  70%  of  the  total  FDI  into  the manufacture  sectors  (He  Feng,  Yuan  Xiaoan,  2010).  However,  generally  an  increasing trend of FDI has been observed in both the countries in the overall manufacturing sector. In  this  context,  impact  of  FDI  on  manufacturing  sectors  is  vital  importance  for  any country. Most of the countries attempt to attract FDI in the manufacturing sector due to its acknowledged advantages as an economic development tool (Akinlo 2004).  Role of FDI  in  manufacturing  is  often  regarded  to  be  positive  and  is  equally  important  to stimulate the growth in the manufacturing sector as well as the other vital sectors of the economy (Sokunle, Chase et al.).
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1.2  An Overview of the FDI in Different Sectors of the Economy of China and India
Table 1.1 provides an overview of the FDI inflow in different sectors of Chinese economy. That are presented in 10000 million US$ and covers the statistics from 1997 to 2017. Each section will be described very briefly as the focus of the thesis work is on the manufacturing sector.  It  can  be seen from the Table 1 that  agriculture, forestry, animal husbandry and fishery have seen no significant increase and in fact it firstly reduced from 1997 to 2007 which again slightly increased during the period from 2007-2017. However, mining  has  seen  tremendous  increase  and  the  figures  have  almost  doubled  in  20  years despite  of  the  fact  that  during  first  ten  years  it  severely  dropped.  The  details  of  the remaining segments of the economy can be found in Table 1.1. 
It  can  be  seen  from  the  highlighted  text  that  from  the  1997  to  2007,  Chinese manufacturing sectors has seen tremendous growth and the FDI had almost doubled in 10 years from 1997 to 2007. However, it again decreased significantly but overall there is an increasing trend of FDI in the manufacturing sector for the entire period of two decades (1997-2017).
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CHAPTER 2: LITERATURE REVIEW

2.1  Impact of FDI on Manufacturing Sector
This section seeks to explore the contemporary evidences around key themes that have  been  found  in  recent  literature  to  have  an  insight  into  the  FDI  impact  on  the manufacturing sector. Organization for Economic and Development (OECD) defines FDI as follows 
“An investment that reflects the objectives of obtaining a lasting interest by a resident entity  in  one  economy  (“direct  investor”)  in  an  entity  resident  in  an  economy  other than that of the investor (“direct investment enterprise”). The lasting interest implies the existence of a long-term relationship between the direct investor and the enterprise and a significant degree of influence on the management of the enterprise” (OECD, 1996, pp7, 8)
It  is  noteworthy  that  empirical  evidences  of  FDI  on  economic  growth  are  rather inconclusive,  however,  Kolstadet  al.  (Kolstad  and  Wiig  2011)  and  Gudlaet  al.(Madem, Gudla et al. 2012) stated that FDI is one of the drivers of economic growth and poverty alleviation in the developing countries. L.C. Arango Vieira (Arango Vieira 2009) argues that the economy grows due to capital accumulation and generation of positive long-term spillovers  to  various  stakeholder  groups  due  to  an  interaction  between  the  FDI  and  the host  country.  On  the  contrary,  some  authors  rather  emphasis  on  the  negative  effects  of FDI. In this context, Adam (Adams 2009) and Moyo (Moyo 2009) stated that developing countries can probably have negative impact of foreign investment on the economy due to the negative spillovers brought by the foreign companies into the host country. 
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2.2  Spillover of FDI in the High-Tech Manufacturing Industry of China and India
It has been discussed above that a large proportion of the manufacturing sector is actually  covered  by  the  High-Tech  Manufacturing  Industries.  In  addition,  international technology  spillovers,  are  the  key  to  understand  how  an  FDI  and  trade  impact  the  host countries. Therefore, both of these will be briefly discussed in this section. 
Knowledge  emerging  from  one  country  or  a  nation  go  beyond  the  geographical boundaries  and  significantly  contributes  the  technological  development  of  other countries,  particularly  the  developing  countries  (Fan  2002).  The  spillover  effect  is significantly important for the domestic firms to benefit from FDI. It is widely researched topic and several studies have been conducted on positive  as well as insignificant or even negative  spillover  effect  on  the  local  industry  (Liu  and  Wang  2003,  Marin  and  Bell 2006).  However,  the  research  results  may  vary  due  to  several  factors  such  as;  different empirical methods, varied levels of used data and also the different levels of absorptive capacity  in  the  host  countries.  It  is  noteworthy  that  getting  access  to  the  technology spillover of FDI is the desired mean for manufacture industry, particularly, the high-tech industry in the developing countries (Caves and Caves 1996). This is due to the fact that multinational  companies  often  prefer  to  transfer  their  technology  to  a  wholly  owned subsidiary rather than joint ventures or third parties.   
The existing literature that focuses the FDI technology spillover clearly indicates the  positive  spillovers  based  on  vigorous  research  focusing  several  countries  across  the globe  (Javorcik  and  Spatareanu  2008,  Suyanto  and  Salim  2011,  Jude  2016).  In  the context  of  China,  most  of  the  research  that  is  focusing  China,  also  indicates  the  FDI positive  technology  spillovers  in  China  (Wang,  Liu  et  al.  2016).  Even  the  government strongly  encourages  the  research  and  innovation  in  this  sector,  especially  the  high-tech sector. For instance, government provides tax-free incentives to the firms if they produce new developments. In China, high-tech industries are often referred as " pillar", however, all  receive  the  same  support  from  the  government  (Liu  and  Zou  2008).  In  China,  high tech  industry  is  regarded  as  a  leading  industry  not  only  in  national  economic development, but it is also a key carrier in absorbing and applying advanced technology. 
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CHAPTER 3: METHODOLOGY ............................ 17
3.1  Theoretical Background ..................................... 17
3.2  Materials and Methods ............................... 18
3.3 Description of Variables............................. 19
CHAPTER 4: RESULTS AND DISCUSSION ................................ 30
4.1  Results and Discussion of China ................................ 31
4.1.1  Empirical Findings ...................................... 31
4.1.2  ARDL Bounds Test for Co-integration .......................... 33
CHAPTER 5: CONCLUSIONS AND IMPLICATIONS .................... 47

CHAPTER 4: RESULTS AND DISCUSSION

4.1 Results and Discussion of China
4.1.1  Empirical Findings
The  first  step  is  to  determine  the  number  of  lags  for  the  Dickey-Fuller  unit  root test.  This  is  an  essential  and  delicate  procedure,  as  the  results  obtained  from  Dickey-Fuller  test  are  sensitive  to  the  selected  lag  numbers.  The  lags  are  obtained  through  the execution  of  vector  auto  regression  (ARDL).  The  five-lag  selection  criteria  consist  of Final  Prophecy  Error  (FPE),  Akaike’s  information  criterion  (AIC),  Schwarz’s information criterion (SC), Hannan-Quinn Criterion (HQ), and LR test. For our purpose, we  employed  Akaike’s  information  criterion  to  determine  the  optimal  lag.  Once  the optimal lag orders are determined, anan Augmented Dickey-Fuller unit root test (tables 1) is  organized  to  determine  the  ranking  of  the  variables.  Application  for  testing  the stationary variables of the variants is used to estimate the model of all Augmented Fuller (ADF) tests.
Table 4.1 is showing the ADF unit root test results. While, ***, **, * denotes the significance level at 1, 5 and  10% respectively.  The results of this study show that five variables  are  non-static  at  level.  On  the  other  hand,  in  all  its  first  differences,  all  the variables  are  stable.  These  results  show  that,  with  interference  and  tendency,  all  the variables  are  integrated  into  1  (1).  Such  results  of  a  stable  test  will  not  allow  us  to implement  the  Johannesburg  view  of  co-integration.  This  condition  of  variables  lead  to apply  auto-regressive  dependent  lags  (ARDL)  tests  to  check  long-lasting  relationships between variables. Time series data for all variables is used for the period from 1985 to 2017.

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CHAPTER 5: CONCLUSIONS AND IMPLICATIONS
The  current  presents  the  detailed  study  on  the  impact  of  FDI  on  manufacturing sectors  of  China  and  India  by  employing  ARDL  model  using  the  time  series  data.  It covers  the  structural  changes  in  the  economy  during  an  appropriate  time  period.  After covering  the  detailed  body  of  the  relevant  literature  in  Chapter  2,  a  modified  growth model  was  constructed  that  includes  several  factors  such  as  FDI,  MAC  (manufacturing growth  )  GDP,  Human  Capital,  and  Gross  Domestic  Capital  Formation  (DI),  among which MAC was dependent variable while rest were independent variables.
The  study  reveals  that  the  FDI  have  very  much  positive  impact  on  the manufacturing sectors of both the China and India (FDI was taken as long-run coefficient which is the mean contributor of manufacturing growth (MAC ).The central government of  China  had  put  tremendous  efforts  to  increase  the  potential  of  positive  spillovers  on domestic economy. In addition to the main variables, the control variables including the human  capital,  GDP,  trade  openness  (OP)  and  exchange  rate  had  significantly  affected the  Chinese  Economy.  The  results  also  signify  the  importance  of  FDI  for  the technological spillover and the enhancement of technical knowhow.  Also,  the negative impact  of  the  domestic  investment  on  the  manufacturing  sector  indicates  the corresponding  increase  in  the  FDI.  The  results  are  consistent  with  the  Ali  and  Wang (2018) describing the fact the outbound investment crowed out the domestic investment, that  ultimately  influences  the  manufacturing  growth  negatively  and  insignificantly. Whereas,  India  also  shows  the  positive  impact  of  FDI  on  the  manufacturing  sector.  In addition to the main variables; the trade openness, GDP and exchange rate  had positive impact  on  manufacturing  growth  of  India.  However,  Indian  unskilled  and  unhealthy human  capital  had  an  overall  negative  impact  that  is  needed  to  be  addressed.  It  is noteworthy  that  improvement  in  human  capital  (skilled  and  healthy  workers)  leads  to productivity enhancement that boosts output. 
reference(omitted)

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