Research Plan and Data Collection
By and large, research workers tend to utilize two chief method of analyzing informations which are quantitative and qualitative analysis ( Isadore, 2000 ) . The former, is a positive attack which assumes a hypotheses has been derived from a theory doing it deductive in nature. It is frequently referred to as theory testing and can be summarised in the undermentioned order:
Theory
General Hypotheses
Data Collection
Datas Analysis
Consequences
Decision
Theory Confirmation/Revision
Qualitative analysis, on the other manus, is inductive in nature. The usage of this analysis is non to prove a theory, but to develop and explicate it and can be summarised in the undermentioned order:
Data Collection
Datas Analysis
Decisions
Development of Hypotheses
Leading to Theory Development
Sing the nature of the current survey, a qualitative attack is needed as this research is non aimed at analysis an bing theory but at developing one. The chief strengths of this method is it helps when analyzing instances in dept, provides single informations and enable cross comparing and besides helps to explicate complex informations. Nevertheless, the chief restrictions to this method are data analysis involves a batch of clip and consequences can be influenced by the research worker ‘s personal prejudice.
The most first-class manner of grouping information required is to setup a research program which means roll uping primary and secondary informations ( Kotler, 1991 ) .
Primary Data
Primary informations comprises of initial facts and figures for an expressed map. This type of informations can be collected through: observation, interviews, questionnaires and transporting out trials ( Kotler, 1991 ) . Primary information will be gathered to accomplish the research ‘s demands. Interviews and questionnaires will assist derive more in dept informations and will ease comparing. However, the major restraint is the clip and costs involved. There is limited support and ability to travel to China and to 20 Sub-saharan African states to roll up first manus informations. Therefore, this survey will utilize secondary resources to roll up valuable and related information.
Secondary Datas
Data which already exists which have been gathered for a different ground is called secondary informations ( Kotler, 1991 ) . The benefits of utilizing secondary information are that garnering them is less expensive, more convenient and less clip devouring than garnering primary information.
Secondary information has been collected from assorted topographic points and assorted agencies as discussed below:
The University of Northampton library, UK, was a good beginning of information offering assorted business-related academic diaries and books. The literature reappraisal is based largely on the articles in these academic diaries. Books as good were a beginning of secondary informations assisting understanding the different theories and the analysis methods associated to this survey.
Secondary information was besides gathered from international administrations such as the World Trade Organisation ( WTO ) , Organisation for Economic Cooperation and Development ( OECD ) and United Nations Conference on Trade and Development ( UNCTAD ) , World Bank, Bank of Mauritius ( BOM ) , Board of Investment ( Mauritius ) , The State Investment Corporation Ltd ( Mauritius ) , The University of Mauritius ( UOM ) , Southern African Development Community ( SADC ) and The New Partnership for Africa ‘s Development ( NEPAD ) largely. Information of Chinese outward foreign direct investing ( FDI ) was available from China ‘s Ministry of Foreign Trade and Economic Cooperation ( MOFTEC ) .
Although there are many advantages associated with analyzing secondary informations, disadvantages besides occur in this survey as discussed below:
Published information is frequently one or two old ages old and recent informations, i.e. 2009, are merely for the first one-fourth of the twelvemonth but really seldom from the terminal of the terminal. Therefore some figures might be out of day of the month taking to a little deficiency for relevancy for the survey. Besides, since there were no surveies taking into consideration the South-South Cooperation as a determiner of FDI, this information will hold to be calculated.
Roll uping information sing influxs of FDI to Sub-Saharan Africa ( SSA ) is hard most surveies focus on Africa in general. Datas from each single state is non a available on the cyberspace from the several authoritiess.
Methodology and Models
Empirical and theoretical plants on the assorted determiners of FDI has already been discussed in the old chapter and the possible methodological analysis is explain below:
Asiedu ( 2002 ) used the ordinary least square analysis ( OLS ) which was discovered by Carl Friedrich Gauss in 1795. This method assumes that the dependent variables are a additive map of the independent variables and the equation as shown below:
Y = x1+x2…+xn
where x1, x2, xn are invariables
The purpose is to happen the best invariables to bring forth the most accurate consequences. The theoretical account is said to be additive because when the invariables are plotted on a graph, it forms a consecutive line ( Clockbackward, 2009 ) . When different types of invariables are plotted together, for illustration, four invariables, it forms a plane ( Appendix 1 ) . Its advantages are that it is easy to utilize, supply a ocular consequences which is easy to understand and can be generated on a computing machine easy. However, it can non be applied to this survey as it can non be used with excessively many variables which is why Asiedu ( 2002 ) used merely 4. Furthermore, in existent life, nil is additive which will do the survey theoretical and inordinate difference in big and little values of invariables make the survey inaccurate ( Clockbackward, 2009 ) .
Fixed and random effects theoretical account besides known as a assorted theoretical account was used by Onyeiwu and Shrestha ( 2004 ) . Fixed effects are defined as taking variables invariables variables from a standard ( e.g. revenue enhancement rate is less than 30 % ) whereas random effects are taking random variables ( e.g. general revenue enhancement rate ) . The expression for this method is a vector equation as shown in Appendix 2.
The biggest advantage of this theoretical account is that the mistake vector is related to the single effects of each factor. This method is no suited for this research as it have no control over other factors makes it confounding. Since it involves much calculation and the degree of south-south cooperation can non be computed easy, it makes it irrelevant.
Hausman specification trial was used by Sawkut et Al. ( 2007 ) in their research because it compares fixed ( assumes differences in informations ) and random ( explores differences in mistake discrepancies ) effects of informations collected under the void hypothesis, where each effects are uncorrelated in the theoretical account ( Hausman, 1978 ) . It is used to find the relationship between an efficient variable and an inefficient one and largely significantly which of the fixed or random consequence theoretical account should be used for the survey and the equation is shown in Appendix 3.
It is utile to find which theoretical account, either fixed or random to utilize, but however, the usage of big samples and high grade of freedom in variables which leaves the degree of difference undetermined and creates an mistake coefficient which can non be valued. Another restriction is that is does non alter over clip which is the chief point of the survey sing the clip period.
For this research, the empirical work for Cleeve ( 2008 ) and Billington ( 1999 ) is used to look into the determiners impacting Chinese FDI in SSA and Mauritius. There will be an betterment of these old by accounting for South-South Cooperation.
This survey will utilize the cross sectional multiple arrested development theoretical account to measure the relationship between FDI from China and the remainder of the universe to the variables in SSA and Mauritius to the period 2000-2009. It is based on the 10 most successful states in pulling FDI and the 10 worst successful states in pulling FDI in the SSA part.
Based on the theoretical account of bookmans such as Cleeve ( 2008 ) and Billington ( 1999 ) , the additive equation can be formulated as:
FDI = degree Fahrenheit ( X1, X2, X3, ….Xi )
Where: I = 1,2,3, … , N
FDI = FDI influx from China and the remainder of the universe to host states in SSA
Eleven = Different variable which influence FDI inflows to host states in SSA
Billington ( 1999 ) used this theoretical account to analyze the location of FDI in the UK ; Cleeve ( 2008 ) used the theoretical account to discourse how pecuniary policies by authoritiess in host states increases FDI and Ancharaz ( 2002 ) used cross-country arrested development analysis to compare the influxs of FDI in SSA to the remainder of the universe. To obtain successful consequences, the location and the different factors impacting the states in the survey needs to be considered and the equation does give a guideline for this.
Chen ( 1997 ) suggested that this equation needs to be altered to explicate the degree of influxs of FDI in a host state. Ordinary least square ( OLS ) is used to measure the power of location factors impacting FDI ( Zhao and Zhu, 2000 ) . Variables which are dependent and independent have changed to ordinary logarithm. This will well diminish the crook of information when plotted on normal graduated tables. This allows the use of the arrested development analysis and besides improves unity in the analysis. The acceptance of a log-linear signifier can be utile to alter non-linear bonds between FDI and economical factors impacting FDI into additive 1s. This will be the basic functional signifier associating FDI influxs and economical variables in host states in SSA ( Chen, 1997 ) . The equation will accordingly alter as follows:
InFDIit = ?0 + ?1InXit + ?
Where: i = cross-section unit or state
T = clip
? = the mistake term
The current research is based on the determiners impacting FDI from Chinese companies in SSA as compared to the universe and therefore this will be the simple equation used in this survey. The undermentioned subdivision will depict the determiners of FDI influxs and put up the independent factors.
Variable Set
The Dependent Variable
The Explanatory Variables
Combine Variables and the Model
( Word Count: 3,955 )
Referencing
Bibliography
Krogstrup, S. and Matar, L. ( 2005 ) . Foreign Direct Investment, Absorptive Capacity and Growth in the Arab World. Graduate Institute of International Studies: Geneva. Working Paper No. 02/2005.
The World Bank Group ( 2009 ) , Global Investment Promotion Benchmarking 2009: Drumhead Report. Washington D.C. : The World Bank Group.
United Nations Conference on Trade And Development. ( 2006 ) Measuring Restrictions on FDI in Services in Developing States and Transition Economies. New York and Geneva: United Nations.