PhD Research proposal:Analysis of Chinese Trade and Foreign Direct Investment on eight African countries Economic Development

PhD Research proposal:

Supervisor: Professor Lan Yisheng

Shanghai University of Finance and Economics

 

Analysis of Chinese Trade and Foreign Direct Investment on eight African countries Economic Development

  

I-Introduction

 

China’s newfound interest in trade and investment with African-home to 300 million of the globe’s poorest people and the world’s most formidable development challenge presents a significant opportunity for growth and integration of the Sub-Saharan continent into the global economy.

These emerging economic “giant” of Asia is at the center of the explosion of African-Asian trade and investment, a striking hallmark of the new trend in South-South commercial relations. Both nations have centuries-long histories of international commerce, dating back to at least the days of the Silk Road, where merchants plied goods traversing continents, reaching the most challenging and relatively untouched markets of the day.

Chinese trade and investment with Africa actually dates back several decades, with most of the early investments made in infrastructure sectors, such as railways, at the start of Africa’s post-colonial era.

China’s fast-growing economic ties with Africa are attracting considerable attention. The relationship came into the spotlight during the summit of the Forum on China-Africa

Cooperation (FOCAC) in Beijing in November 2006 and the Annual Meetings of the African

Development Bank (AfDB) in Shanghai in May 2007. While the expansion of trade and investment between Africa and China has been generally welcomed, concerns have been expressed about how China’s growing presence might affect African development (These concerns range from debt sustainability and governance reform to environmental impact; see news reports in Les Echos, October 24, 2006 (in French); Financial Times, November 28, 2006, and News Edge, May17, 2007).

Today’s scale and pace of China’s trade and investment flows with Africa, however, are wholly unprecedented. The volume of African exports to Asia is accelerating. It grew by 15% between 1990 and 1995; it has grown by 20% during the last five years (2000-2005) (Harry G. Broadman: “Africa’s silk road”; China and India new Economic Frontier).

Trade between Africa and China began to accelerate in about 2000. Between 2001 and 2006,

Africa’s exports to China increased at an annual rate of over 40 percent, rising from US$4.8 billion to reach US$28.8 billion in 2006 (Figure 1 and Table 1). During the same period,

Africa’s imports from China quadrupled to US$26.7 billion. In 2006 Sub-Saharan Africa

(SSA) accounted for the bulk of the Africa-China trade; the region’s exports to China amounted to US$25 billion, about 85 percent of all African exports to China that year.

According to statistics compiled by China, for 2004–06 Africa ran a small trade surplus, about US$2 billion each year (See IMF Working Paper (2007) “What Drives China’s Growing Role in Africa?” Jian-Ye Wang).

 

The acceleration of South-South trade and investment is one of the most significant features of recent developments in the global economy.

Trade between China and Africa is also expanding rapidly. Valued at only around $3 billion in 1995, total trade grew to an estimated $40 billion in 2005. Premier Wen Jiabao of China stated during the China-Africa Cooperation Forum summit that China hopes to increase that amount to $100 billion by 2010.

Table 1: China Imports and Exports from Africa (US$ millions)

  

Figure 1: China-Africa Trade Statistics 1995-2005

 

Source: World Atlas Trade Data, Tralac Analysis (Centre for Chinese Studies, Stellenbosch University (South Africa))

China started providing aids to Africa in 1956. By May 2006, it had contributed a total of 44.4 billion yuan (US$5.7 billion) for more than 800 aid projects, according to a researcher at the Chinese Academy of Social Science (He, 2006). The last officially reported flows were in 2002, when the Chinese government reported that it provided (US$1.8 billion) to support Africa.

China has also been providing debt relief to African countries on its own terms. At the first China-Africa Cooperation Forum in October 2000 in Beijing, the Chinese government pledged to write off in two years overdue obligations on 156 loans owed by African countries; these equaled to 10.5 billion yuan (US$1.3 billion). The pledge was fulfilled ahead of schedule (He, 2007).

Chinese capital flows to Africa in the form of foreign direct investment (FDI) are growing. While in the past many of these investments were limited to the raw materials sector, the current wave involves firms from many countries and sectors than ever before. This foreign investment also has many implications patterns and the development of the bilateral trade and integration. Many African exports are channeled through multinational enterprises, helping to integrate African countries both with one another and with the global economy.

 

Table 2: Chinese capital flows to Africa

 

Figure 2: China FDI flows to Africa

 

Source: Jonathan HOLSLAG “China’s FDI in SUB-SAHARA AFRICA” Brussels Institute of Contemporary China Studies.

So far, the nature of these flows has been quite similar to those between Africa and its traditional trading partners noted in the OECD studies (2005-2006) (OECD study, The Rise of China and India: What’s in it for Africa?). Against this backdrop, there is intense interest by policy makers and businesses in both Africa and Asia, as well as by international development partners, to better understand the evolution and the developmental, commercial, and policy implications of African-Asian trade and investment relations. This interest is reflected, perhaps most notably, in the South- South discussions held during the African-Asian summit in Jakarta in April 2005 celebrating the fiftieth anniversary of the Bandung Declaration, where the dramatic rise in international commerce between the two regions figured prominently, as well as at the July 2005 (G-8 summit in Gleneagles G8 Summit took place at Gleneagles Hotel, Perthshire, Scotland on 6-8 July 2005), where the leaders of the North underscored the growing importance of South-South trade and investment flows, especially as they pertain to the prospects for fostering growth and poverty reduction in Africa.

The importance of South-South trade has been recognized for some time; however, there has been no in-depth study conducted specifically on Africa-China trade relations to date.

The main objective of this study is to build a basic understanding of the potential of Africa-China trade and investment relations.

A literature review will be first conducted tracing the evolution of economic growth theories since Adam Smith to the present on the impact of commercial and technological aspects, resulting from international trade, on the physical accumulation and quality of productive factors.

Next, using historical data covering a sample of African countries, multiple regression analyses will be performed to determine the relationship between the specific determinants and real per capita economic (GDP) growth over a twelve year period. Using the results, conclusions will be drawn about the relationship among the determinants in their effects on long-term economic growth. Several additional trials will be carried out to determine more nuanced information and to test the reliability of the endogenous growth theory model.

The data will be collected according to the International Standard Industry Classification (ISIC).

 

II-Statement of the problem and motivation

II-1.Overview

China is not a new player in Africa. But its economic and political presence on the continent and its impact on Africa have grown exponentially in the last few years. This has huge consequences for Africa, but it also has significant implications for western policy towards the continent.

In thinking through how Africans and the wider international community should address the new challenges posed by China’s role on the continent, a critical starting point is to better understand the diverse impacts of China on Africa.

Like other parts of the world, Africa is being affected indirectly by the phenomenal growth of the Chinese economy.

It is clear that Africa must not loss its momentum and determination to tackle its development problems and attain the renewed vision of a prosperous vibrant region. In this regard the establishment of the China-Africa Forum came at a critical juncture, offering unconditional support for the AU (African Union) and its various instruments including NEPAD, which is being integrated into sub-regional and National development strategies.

Put another way the big question is how to kick start African poor countries out of a cycle of poverty throughout their trade relationship with China.

So, what is so important about economic growth? Economic growth leads to greater economic prosperity. Increasing overall prosperity improves the lives of those able to partake in the system. People are better able to provide for their needs and fulfill their wants, without the use of force. This rising prosperity is empirically linked to higher overall levels of human happiness and betterment.

Recent developments in growth theory have considered various sources of long-run growth, each of which involves an externality associated with some activity. Examples include human capital accumulation through either learning by doing or education and technological advance through R&D activities.

Additionally many policy makers and academics contend that foreign direct investment (FDI) can have important positive effects on a host country’s development effort, but that empirical evidence for FDI generating positive spillovers for host countries is ambiguous at both the micro and macro levels. In a recent survey of the literature, Hanson (2001) argues that evidence that FDI generates positive spillovers for host countries is weak. But Balasubramanayam et al. (1996) found that in developing countries pursuing outward-oriented trade policies, FDI flows were associated with faster growth than in those developing countries that pursued inward oriented trade policies (Laura Alfaro. “Foreign Direct Investment and Growth: Does the Sector matter?”).

A questions immediately arises relative our study and which we would like to answer is:

-What role does China-Africa trade relationship play in African countries economic growth?

 

-What is the contribution of Chinese outward FDI to host African countries economic growth?

 

II-2.The aim and Objectives

 

The need for base-line studies to assess the changing future impact of China on Africa and to the extent that trade links are an accurate reflection of the wider impact of China on Africa.

 

The main aim of this research is to understand the role of China in the economic growth process of African countries trough its trade relationship with those countries.

In order to achieve this, the key objectives are:

-See the Africa’s Position in International Trade.

-Present the statistics (data) on the Chinese net export with Africa.

-Measure and analyze volume and composition of trade between China and Africa.

-Measure the impact of the trade relationship on African countries trade balance.

-To examine the contribution of Chinese FDI on African countries economy.

-To determine whether FDI and ICT exerts different effects on African countries economic growth.

 

II-3.Expected finding

 

Since imports and FDI bring additional competition and variety to domestic markets, benefiting consumers, and exports enlarge markets for domestic production, benefiting businesses. Trade exposes domestic firms to the best practices of foreign firms and to the demands of discerning customers, encouraging greater efficiency. Trade gives firms access to improved capital inputs such as machine tools, boosting productivity and providing new opportunities for growth for developing countries.

We would expect to observe greater spillover effect through Chinese trade relationship with Africa on Africa economic growth. We also expect that Chinese FDI flows to Africa will tend to have a positive effect on African countries economic growth.

 

III-Literature context and issues:

China first became involved in Africa during the cold war, when it made friends and did business in parts of the world overlooked by the West and the Soviet Union. Its investment is paying off now in oil and raw material imports and markets for manufactured goods.

Since the 1960s, China has been rather consistent in offering assistance to African countries in agriculture, heavy industries, and infrastructure development. In recent years, Sino-African trade has enjoyed particularly rapid growth. As Paul Mooney reports, many African leaders, regarding China as a reliable friend who has suffered the similar imperialist aggression by Western powers, welcome investment and development teams from Beijing. Furthermore, the Chinese have not used their economic power to place political pressure on Africa. Skepticism, however, does exist. Some African scholars think that China is simply relaying the European colonial torch of purchasing raw materials from the continent and selling value-added products back, creating an unfavorable trade balance for Africa.

But “The Chinese are much more prone to do business in a way that today Europeans and Americans do not accept paying bribes and bonuses under the table. The researcher think that it will be much easier for some African countries to work with Chinese companies, rather than American and European companies, which are becoming more and more restricted by the publish what you pay initiative and others calling for better transparency” ( www.Catholicrelief.org).

While acknowledging such drawbacks, other Africans have welcomed the opportunity to diversify the continent’s external partnerships. They also appreciate the absence of explicit political or economic policy conditions on China’s part, in contrast to the sometimes heavy-handed approach of certain Western powers.

As to illustrate the landscape Macharia Gaitho, managing editor of the Kenyan daily Nation, commented  “As long as China is so willing to invest in Africa, we must not miss out on the bounty,” “But we must engage with our eyes wide open.” because : Charity and international aid will not solve Africa’s problems, but economic reform and growth can.(Allafrica.com)

 

China’s burgeoning relationship with Africa is alarming not only because it has facilitated Chinese energy and weapons dealings, but also because it is competing with U.S.–African trade. The China–Africa Cooperation Forum (CACF) was founded in 2000 to promote stronger trade and investment relations between China and African countries in both the government and private sectors.

 

In recent years, Beijing has identified the African continent as an area of significant economic and strategic interest. America and its allies and friends are finding that their vision of a prosperous Africa governed by democracies that respect human rights and the rule of law and that embrace free markets is being challenged by the escalating Chinese influence in Africa.

The love affair with China, however, may be sour as well as sweet. For countries that do not sit on oil or mineral deposits, higher commodity prices make life harder. Even for producers there are risks. A recent report by the World Bank argues that Africa’s new trade with China and India opens the way for it to become a processor of commodities and a competitive supplier of cheap goods and services to Chinese and Indian consumers. But another report, from the OECD (2005-2006), a club of industrialized countries, argues that China’s appetite for commodities may stifle producers’ efforts to diversify their economies. Oil rigs and mines create few jobs; it points out, and tends to suck in resources from other industries. And if Africa is to escape its vulnerability to the capricious movements of world commodity prices, it must start to export more manufactures. On this the World Bank adds its own warning: China and India must end their escalating tariffs on Africa’s main exports.

China is also bringing irresistible “some say unfair” competition to Africa. All over Africa Chinese traders can now be seen selling cheap products from the homeland, not just electronics but plastic goods and clothes.

The Chinese government has also actively promoted their own brand of economic development and reform model to African countries, encouraging government counterparts in several countries to visit China and learn from their experience. China’s efforts to encourage African governments to fashion their economic systems after their own is an important indication of the soft power that China hopes to ultimately project in Africa.

China’s soft power gambit can also be seen in its heavy investments in Africa’s educational systems, both by sending teachers to Africa and providing scholarships to African students from across the continent to study in Chinese universities. Between the start of the educational exchanges in the mid-1950s and 2000, 5,582 African students had enrolled in Chinese universities. These students typically spend two years learning Chinese, then study technical subjects, particularly engineering disciplines. Currently, about half of African students are pursuing advanced degrees. This support for education improves China’s image in many countries, builds grassroots support in local communities and a better understanding of China among the educated elite.

IV-Methodology and Hypothesis

 

The trade performance of individual countries tends to be a good indicator of economic performance since well performing countries tend to record higher rates of GDP growth. The majorities of developing countries has joined the World Trade Organization (WTO) and have taken initiatives aimed at opening their economies.

But the net effect of trade openness on economic growth has been and remains a subject of controversy.

Two issues are at the center of the debate: theoretical elaboration and empirical investigation.

On the theoretical side, since the time of Adam Smith through Ricardo and Solow, trade has been shown to allow a country to reach a higher level of income since it permits a better allocation of resources.

Imports bring additional competition and variety to domestic markets, benefiting consumers, and exports enlarge markets for domestic production, benefiting businesses.

But the benefits of international trade for economic growth and development are difficult to understate.

In models of endogenous growth, trade can impact upon growth by allowing access to the innovative products of other countries. Since most LDCs do little if any innovation it is primarily through trade with developed countries that they profit from higher levels of technological development. Also Foreign Direct Investment is viewed as a major stimulus to economic growth in

developing countries.

We will predict manufacturing imports of China to a sample of African countries over a 12-year period (1995-2007). To predict such imports we will use a variety of measures of trade, China FDI, the GDP and GDP per capita of the importer and exporter.

With computer programs such as SPSS, Eviews, Matlab and SAS the study will consist on quantitative analysis using secondary studies. The sample will consist on some African countries. This particular sample will be chose based on the availability of data for each of the variables need in the project for the countries in question

 

In order to analyze the China’s role in Africa economic growth the analysis will first applies numerical measures to evaluate the evolution the trade performance index of individual countries and the index of overall, after we will adopt the empirical studies on intra-industry trade (IIT); the level of IIT in an industry is usually quantified by the Grubel and Lloyd index (1975). We follow the same fashion in this study. The index of IIT in an industry is generally defined as:

  

In the equation, refers to unit value of exports, while  refers to unit value of imports at time t.

 

IV-1.Time-series data analysis

 

Hence there are several preliminary steps to using time-series data in econometric analyses.

In many cases, particularly with macroeconomic data, it is reasonable to conclude, on the basis of theoretical considerations and by looking at a plot of data against time that a variable is or is not growing. Such growth could occur via a deterministic time trend, or it could occur because the annual change in the variable is equal to a constant.

 

Initially it is essential to determine the form in which the data can be used for any subsequent estimation; in many instances using macroeconomic data in their levels leads to serious econometric problems. Time-series data typically contains a trend, which must be removed prior to undertaking any estimation. The traditional detrending procedure separates the trend from the cyclical component of the series. This procedure is appropriate for trend stationary (TS) time-series. However, many macroeconomic time-series are difference stationary (DS). DS type time-series are nonstationary and they contain unit roots. The DS type sequences must be differenced prior to any meaningful econometric estimation. If ordinary least squares (OLS) estimation techniques are applied to undifferenced DS type sequences, resulting error terms are serially correlated. This renders any subsequent hypothesis tests unreliable.

 

IV-2.Econometric Techniques:

 In order to examine the hypotheses, suitable econometric models are required.

Since the objective of this research is to test the Granger-causality of several variables, the test should be based on the appropriate multivariate times series models (could be VAR ?vector autoregression? or VECM ?vector error correction model?).

The examination procedures conducted in this paper is that, firstly, unit root test at the levels and first differences are conducted to determine whether each variable is stationary or non-stationary. Secondly, the Engle-Granger residual-based test tests the existence of cointegration among the variables for each country. Thirdly, if a cointegration relationship does not exist, VAR analysis in first difference is applied, however if the variables are cointegrated, the analysis continues in a cointegration framework. Finally, the Granger-causality test is conducted based on the chosen analytical framework.

 

Figure 3: depicts the methodology heuristics.

 

Therefore, the overall methodology is as follows:

- test if the system is stable, using the unit root tests

- if there are unit root tests on the series of variables, apply cointegration tests

- if cointegration is found, then obtain the VECM representation of the system and apply causality tests on this representation

- if there is no cointegration, simply differentiate the variables to obtain the VARD (vector autoregressive representation on differences) representation and apply causality tests of VARD representation

- if the systems is stable, the use of the simple, initial VAR representation for causality tests.

Some methodological problems still have to be solved. These regards how we should collect and represent the data, which should be the autoregressive order of the system, what variables the stochastic model should comprise.

 

IV-3.Aggregate Production Function

Observing from theory the possible growth promoting roles of both FDI and Trade, our data analysis is modelled in an aggregate production function (APF) framework. The standard APF model has been extensively used in econometric studies to estimate the impacts of FDI inflows and trade on growth in many developing countries. The APF assumes that, along with “conventional inputs” of labour and capital used in the neoclassical production function, “unconventional inputs” like FDI and trade may be included in the model to capture their contribution to economic growth. The APF model has been used by Feder (1983); Fosu (1990); Ukpolo (1994); Kohpaiboon (2004); Mansouri (2005); and Herzer et al (2006) among others.

Following Herzer et al (2006), the general APF model to be estimated is derived as:

                                             1

Where  denotes the aggregate production of the economy (real GDP per capita) at time t, and  are the total factor productivity (TFP), the capital stock, and the stock of labor, respectively. According to Lipsey (2001), the impact of FDI on economic growth possibly operates through TFP (A). Moreover, from the Bhagwati’s hypothesis (Bhagwati, 1985), any gains from FDI on TFP will surely be dependent on the volume of trade of a particular host country. Since we want to investigate the impacts of FDI inflows (FDI) and trade variables on economic growth through changes in TFP, we assume therefore that TFP is a function of FDI, M, X and, other exogenous factors. Thus:

                                              2

Combining equations (2) with (1), we get:

                                               3

 where  and are constant elasticity coefficients of output with respect to the  and From equation (3), an explicit estimable function is specified, after taking the natural logs of both sides, as follows:

                                               4

 where all coefficients and variables are as defined, c is a constant parameter, and  is the white noise error term. The sign of the constant elasticity coefficient  and ?are all expected to be positive. Equation (4) represents only the long-run equilibrium relationship and may form a cointegration set provided all the variables are integrated of order 1, i.e. I(1).

 

From equation (4) Y is defined as real GDP per capita; FDI is the value of foreign direct investment flows; X is the value of the current country export to China and M is the value of the current country import to China; L is measured as the volume of the total labor force; since a time-series on the capital stock is not directly available for African countries, K is proxied by the real value of gross fixed capital formation (GFCF). This proxy for capital stock has been used in many previous studies. See Balasubramanyam et al., (1996), Kohpaiboon (2004), Mansouri (2005) among others.

 

IV-4.ARDL Model Specification

 

In this Section, the Autoregressive Distributed Lag (ARDL) bounds testing approach proposed by Pesaran, et al. (2001) will be used to examine the dynamic relationship between FDI, import and export for the 8 African countries. As pointed out by Narayan and Narayan (2005), the bounds test which is based on the estimation of an unrestricted error correction model (UECM) has several advantages over the conventional type of cointegration techniques. First, the standard Wald or F-statistics used in the bounds test has a non-standard distribution under the null hypothesis of no-cointegration relationship between the examined variables, irrespective whether the underlying variables are I(0), I(1), or fractionally integrated. Therefore, the bounds test obviates the uncertainty associated with pre-testing for unit roots as it does not require the information for the order of integration of the variables. Otherwise, the ARDL approach can be applied whether the regressors are I(1) and/or I(0). This means that the ARDL approach avoids the pre-testing problems associated with standard cointegration, which requires that the variables be already classified into I(1) or I(0) (Pesaran et al, 2001). If we are not sure about the unit root properties of the data, then applying the ARDL procedure is the more appropriate model for empirical work. Second, it is more robust and is the more statistically significant approach to determine the cointegration relation when applied on a small sample study compare to Engle and Granger (1987) or Johansen type of cointegation methods that require large data samples for validity. Third, the short as well as long-run parameters of the model could be estimated simultaneously. Fourth, once the orders of the lags in the ARDL model have been appropriately selected, we can estimate the cointegration relationship using a simple ordinary least square (OLS) method. The UECM used in the present study has the following form as expressed in the below Equations.

 

On the basis, the conditional VECM of interest can be specified as:

                                                     5

 where ?are the long run multipliers,  is the drift, and  are white noise errors.

 

IV-5.Bounds Testing Procedure

 

The first step in the ARDL bounds testing approach is to estimate equation (5) by ordinary least squares (OLS) in order to test for the existence of a long-run relationship among the variables by conducting an F-test for the joint significance of the coefficients of the lagged levels of the variables, i.e., ?against the alternative

.We denote the test which normalize on Y by

. Two asymptotic critical values bounds provide a test for

cointegration when the independent variables are I(d) (where ): a lower value assuming the regressors are I(0), and an upper value assuming purely I(1) regressors. If the F-statistic is above the upper critical value, the null hypothesis of no long-run relationship can be rejected irrespective of the orders of integration for the time series. Conversely, if the test statistic falls below the lower critical value the null hypothesis cannot be rejected.

Finally, if the statistic falls between the lower and upper critical values, the result is inconclusive. The approximate critical values for the F-test were obtained from Pesaran and Pesaran, 1997, p.478).

In the second step, once cointegration is established the conditional  long-run model for  can be estimated as:

                                                6

 Where, all variables are as previously defined. This involves selecting the orders of the  model in the six variables using Akaike information criteria (AIC).

In the third and final step, we obtain the short-run dynamic parameters by estimating an error correction model associated with the long-run estimates. This is specified as follows:

                                                  7

 Here ??and  are the short-run dynamic coefficients of the model’s convergence to equilibrium, and ??is the speed of adjustment.

 

IV-6.Growth model

 

The purpose of the empirical analysis is to determine whether FDI exerts different effects on a country’s growth. Following Borensztein et al. (1998), Carkovic and Levine (2002), and Alfaro et al. (2003), we want to look at the direct effect of FDI on economic growth using cross-section regressions with 8 Sub-Saharan African countries for the time period 1995-2006.

Initially, as a benchmark, we calculated the impact of overall FDI inflows on economic growth based on the following equations:

                                                      8

 We pursue this analysis and test the direct impact of FDI had on the growth of two different countries sample divided as importers countries and exporter’s countries.

Growth here is the GDP growth.

 

Hypothesis:

1-  are positive.

2-The correlation between GDP and ICT is high.

3-The correlation between GDP and FDI is low.

4-there are no correlation between ICT and FDI.

  

Reference

 

1.Blomstram, Magnus, Steven Globerman and Ari Kokko.2000.The Determinants of Host Country Spillovers from Foreign Direct Investment,” CEPR Discussion paper No.2350

2. Branstetter, Lee G. 2001. “Are Knowledge Spillovers International or International in Scope? Micro econometric Evidence from the U.S. and Japan,” Journal of International Economics 53:53-79

3. Coe, D. and Helpman, E. (1995)”International R&D Spillovers”, European Economic Review, 39, 859-887.

4. Coe, David, Helpman and A. W. Hoffmaister.1997 “North-South R&D Spillovers,” Economic Journal 107: 134-149.

5. Xinhua He, Yongfu Cao: “Analysis and Forecast of World Economic Situation (2005-2006); Yellow Book of International Economy.

6. Xinhua He, Yongfu Cao: “Analysis and Forecast of the World Economy in 2006-2007”; Yellow Book of International Economy.

7. Grossman, G. M. and Helpman, E. (1991)“Innovation and Growth in the Global Economy”, MIT Press, Cambridge, MA.

8. Harry G. Broadman: “Africa’s silk road”; China and India new Economic Frontier.

9. Kao, C. (1999). “Spurious Regression and Residual-Based Tests for Cointegration in Panel Data”, Journal of Econometrics, 90, 1-44.

10. Kao, C. and Chiang, M.H. (1998) “On the Estimation and Inference of a Cointegrated Regression in Panel Data”, Working Paper, Center for Policy Research, Syracuse University.

11. Keller, W. (1998) “Are International Spillovers Trade-Related? Analyzing Spillovers among Randomly Matched Trade Partners”, European Economic Review, 42, 1469-1481.

12. Krishna, Pravin. 2003. “Are regional trading partners ‘natural’?” Journal of Political Economy

111: 202-226.

13. Liu, zhiqiang. 2002. “Foreign Direct Investment and Technology Spillover: Evidence from China” Journal of Comparative Economics 30:579-602.

14. SSB (State Statistical Bureau of China), Statistical Yearbook of China, Statistical Publishing House.

15. SSB (State Statistical Bureau of China), China National Science and Technology Committee, China Statistical Yearbook on Science and Technology, Statistical Publishing House.

16. OECD study, The Rise of China and India: What’s in it for Africa?

“Bottom of the barrel: Africa’s oil boom and the poor”, Catholicrelief.org.

17. Yuqing Xing. “Foreign direct investment and China’s bilateral intra-industry trade with Japan and the US” Bank of Finland, BOFIT, Institute for Economies in Transition. Discussion Papers 1.2007.

18. Laura Alfaro. “Foreign Direct Investment and Growth: Does the Sector matter?” Harvard Business School. April 2003.

19. Davidson, R. and MacKinnon, J.G. (1993) Estimation and Inference in Econometrics. New York: Oxford University Press, pp. 320, 323.

20. Gujarati, D. (2004). Basic Econometrics. 4th ed. New York: McGraw Hill, pp. 638- 640.

21. Stata (2003). Cross-Sectional Time Series. College Station, Texas: Stata Press, pp. 10, 62, 93, 224.

22. Testing Export-led Growth Hypothesis in Kenya: An ADRL Bounds Test Approach Mohan, Ramesh and Nandwa, Boaz. Bryant University, 03 November 2007.

 

 Links

-(Xinhua He, Yongfu Cao: “Analysis and Forecast of World Economic Situation (2005-2006))

-( Xinhua He, Yongfu Cao: “Analysis and Forecast of the World Economy in 2006-2007”)

-The main difference between these two types of time-series variables is the fact that TS type variables return to the deterministic trend function, whereas no such tendency exists with the DS type of time-series variables. Nelson and Plosser (1982) and McCallum (1993) provide a more detailed explanation of this point.

- A time-series variable is weakly stationary if its mean, variance, and covariance are finite, and if all of these are independent of time. If the variance increases over time, then the time-series becomes explosive. Given this fact, such time-series variables should not be used for hypothesis testing. For a further explanation of this point see Stock and Watson (1988), among others.

- Most of the variation in the data is across country, reflecting conditions that change slowly.