1. Globalization and Export Concentration
Chowdhury Nawsheen Farooqui

2. Outline of the Presentation
Introduction
Motivation and Research question
Literature Review
Methodology
Empirical Framework
Findings and discussion
Conclusion

3. Introduction
Joseph Stiglitz, a noble laureate economist defines Globalization as follows:
Globalization "is the closer integration of the countries and peoples of the world ...brought about by the enormous reduction of costs of transportation and communication, and the breaking down of artificial barriers to the flows of goods, services, capital, knowledge, and people across borders." (from Globalization and its Discontents)
Globalization covers a wide range of issues, economic, political, cultural, etc.
Globalization does not only mean opening of trade opportunities only in terms of goods and services but it also refers to transfer or free flow of capital, labor and so on.

4. Introduction
Export Concentration- Export concentration reflects the degree to which a country’s exports are concentrated on a small number of products or a small number of trading partners.
A country that exports one product to only one trading partner has a perfectly concentrated export portfolio. Conversely, a country whose exports are comprised of a larger number of products and that trades with a larger number of trading partners has a lower export concentration ratio (ECR), i.e., has more diversified exports.
Connecting the two in this paper .

5. Choosing Bangladesh to see the relationship between globalization and export concentration
Bangladesh being a developing country and is a small open economy in international trade. Early 1980s the major export concentration was jute and jute products, which was overshadowed by the RMG sector in the end of 1990s.
Bangladesh experienced vertical diversification of its exports (from primary to manufactures). By 2000, it became a unique LDC exporting predominantly manufactures (over 90%).The exports are largely dominated by readymade garments, whose share was 81.2 percent in FY2014. Around 96 percent of all exported goods are manufactured commodities. Bangladesh's export basket is heavily concentrated on one product that is the readymade garments and others include: jute goods, home textile, footwear and frozen shrimps and fish.

6. Motivation and Research question
Bangladesh being a developing country still has restrictions on the free flow of capital, movement of labor and so on. Bangladesh has not yet enrolled in the super highway of globalization but still it has globalized to some extent and therefore we can expect some sort of impact of globalization on export scenario in the context of Riacrdian specialization theory.
Research Question : Does globalization of Bangladesh leads to more export concentration or not ?

7. Literature Review
Ricardo (1817) referred to the framework of two countries and two commodities when studying the notions of comparative advantage and efficient specialization in production.
Studies by Simon Kuznets (1964) and A. 0. Hirschman (1945) suggest that country size and commodity export concentration are inversely related.
Michael Michaely [1958] found that it is the level of development rather than country size that exerts a significant influence on the degree of export concentration.
Johansson and Nilsson (2007) ,The results from the empirical analysis do not support the hypotheses of increasing trade globalization ,It is rather the case that export flows are becoming more internationally regionalized.

8. Methodology In this study I used the econometric methods such as
Unit root tests
 Johansen Cointegration test
Granger Causality test
Fully modified OLS
Canonical OLS
Dynamic OLS

9. Methodology
Unit root tests are carried out to find out if the data series is stationary or non- stationary. Non-stationary data give rise to spurious regression results for which it is important for us to make our data stationary.
We focus on the ADF and Phillips Perron unit test to check the stationarity of our data. In order to do so, we assume a hypothesis considering the data series to be non-stationary and integrated. If there is a clear proof of rejection, it is only then we reject the hypothesis.
Cointegration means that a linear combination of different order 1-integrated variables I(1) is stationary (I(0)), and it implies the existence of an empirical long- run relationship between those variables. Johansen's cointegration test was performed to find out existence of any possible relationship between variables. Next, Johansen cointegration test is applied to investigate the relationship between the variables

10. Methodology
It is pointed out by Granger (1986, 1988) and Engel (1987) that if two variables are cointegrated then a causal relationship must exist between them, at least in one direction. Therefore, once the cointegration is established, the next step is to investigate direction of causality existing between the variables.
However cointegration test does not give the direction of relationship among variables so we took help of cointegrating regressions namely Fully Modified Ordinary Least Square (FMOLS), Canonical Cointegration Regression (CCR), and Dynamic Ordinary Least Squares (DOLS). These are single equation regression based methods and are variations of OLS method to avoid some problems that are common among cointegrating relationship

11. Methodology
Fully modified ordinary least squares The FM-OLS regression is designed to provide efficient estimates of cointegrating regressions. The method modifies least squares to account for serial correlation effects and for the endogeneity in the regressor that results from the existence of a cointegrating relationship.
In the same vein, CCR and DOLS estimators deal with the problem of second-order asymptotic bias arising from serial correlation and endogeneity.

12. Empirical Framework
We used a linear regression model, where the HHI is the dependent variable (export concentration index measured by Herfrindal - Hirschman index) and the globalization index - the globalization index that covers the economic, social and political dimensions of globalization, is the independent variable.
The KOF Index of Globalization was introduced in 2002 (Dreher, published in 2006) and is updated and described in detail in Dreher, Gaston and Martens (2008). The overall index covers the economic, social and political dimensions of globalization.

13. Empirical Framework
Looked at the data between the periods 1985 to The final regression equation looks like (here the symbols have their usual meanings):
Ran the regression keeping the dependent variable HHI and changing the globalization index , first did the regression with HHI and KOF Overall globalization index . The overall index covers the economic , social and political dimensions of globalization.
Then ran the same tests using HHI and K0F political and HHI with KOF economic globalization index .

14. Deintions of variables
Economic Globalization – characterized as long distance flows of goods, capital and services as well as information and perceptions that accompany market exchanges;
Political Globalization – characterized by a diffusion of government policies.
Social globalization , expressed as the spread of ideas , information, images and people.

15. Definitons of the variables
Herfindahl Hirschman index is a flow-weighted concentration index which implies that it can be decomposed according to the shares of total flows of each group. Thus, the weight given to each group depends on the trade share of each group. The formula is as follows:
HHI is ‘Herfindahl Hirschman Index’ of country i. Xik is the export value of commodity k or export destination k for exporter i. Xi is the total export value of all commodities or export destinations for exporter i. Then, it is converted into export concentration index

16. Results Obtained Group unit root test: Summary Series: HHI, KOFOVERALL
Series: HHI, KOFOVERALL
Sample:
Cross-
Method
Statistic
Prob.**
sections
Obs
Null: Unit root (assumes common
unit root process) 
Levin, Lin & Chu t*
 0.0001  2  
Breitung t-stat
 0.0083  
Null: Unit root (assumes individual
Im, Pesaran and Shin W-stat 
ADF - Fisher Chi-square
 0.0146
  2    
 0.0228
  2 53
PP - Fisher Chi-square  
 0.0235

17. Cointegration Rank Test between HHI and kofoverall (Glob)
Sample (adjusted):
Hypothesized
Trace
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None      
 0.4206
At most 1      
 0.3978
 Trace test indicates no cointegration at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values

18. Results of Granger Causality test between HHI and kofoverall (glob)
Sample:
lag : 1 
Null Hypothesis:
Obs
F-Statistic
Prob. 
KOFOVERALL does not Granger Cause HHI
 25  
0.0023
 HHI does not Granger Cause KOFOVERALL  
0.4962

19. Results of Granger Causality test between HHl and kofoverall
Sample:
lags : 2 
 Null Hypothesis:
Obs
F-Statistic
Prob. 
 KOFOVERALL does not Granger Cause HHI
 23  
0.0909
 HHI does not Granger Cause KOFOVERALL  
0.6138

20. Results of Granger Causality test between HHI and Kofoverall (Glob)
Sample:
Lags:3
 Null Hypothesis:
Obs
F-Statistic
Prob. 
 KOFOVERALL does not Granger Cause HHI
 22  
0.4061
 HHI does not Granger Cause KOFOVERALL  
0.5977

21. Results showing the FMOLS between HHI and KOF0verall(Glob)
Dependent Variable: HHI
Mehod: Fully Modified Least Squares (FMOLS)
Included observations: 26 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.  
KOFOVERALL
0.0000 C
R-squared
    Mean dependent var
Adjusted R-squared
    S.D. dependent var
S.E. of regression
    Sum squared resid
Durbin-Watson stat
    Long-run variance

22. Results of the CCR Regression
Dependent Variable: HHI
Method: Canonical Cointegrating Regression (CCR)
Included observations: 26 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.  
KOFOVERALL
0.0000 C
R-squared
    Mean dependent var
Adjusted R-squared
    S.D. dependent var
S.E. of regression
    Sum squared resid
Durbin-Watson stat
    Long-run variance

23. Results of the DOLS Regression
Dependent Variable: HHI
Method: Dynamic Least Squares (DOLS)
Included observations: 21 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.  
KOFOVERALL
0.0000 C
0.7249
R-squared
    Mean dependent var
Adjusted R-squared
    S.D. dependent var
S.E. of regression
    Sum squared resid
Durbin-Watson stat
    Long-run variance

24. Group unit root test Group unit root test: Summary
Series: HHI, KOFECON
Sample:
Cross-
Method
Statistic
Prob.**
sections
Obs
Null: Unit root (assumes common
unit rootprocess) 
Levin, Lin & Chu t*
 0.0487  2
 53
Breitung t-stat
 0.4915
 51
Null: Unit root (assumes individual
unit root process) 
Im, Pesaran and Shin W-stat 
 0.0341
ADF - Fisher Chi-square
 0.0378
PP - Fisher Chi-square  
 0.0392

25. Cointegration Rank Test between HHI and KOFECON
Sample (adjusted):
Hypothesized
Trace
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None      
 0.4056
At most 1      
 0.4048
 Trace test indicates no cointegration at the 0.05 level
 * denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values

26. Group unit root test Group unit root test: Summary
Group unit root test: Summary 
Series: KOFPOLITICAL, HHI
Sample:
Cross-
Method
Statistic
Prob.**
sections
Obs
Null: Unit root (assumes common unit root process) 
Levin, Lin & Chu t*
 0.0001  2
 53
Breitung t-stat
 0.4382
 51
Null: Unit root (assumes individual unit root process) 
Im, Pesaran and Shin W-stat 
 0.0100
ADF - Fisher Chi-square  
 0.0179
PP - Fisher Chi-square  
 0.0004

27. Cointegration test between HHI and kofpolitical
Sample (adjusted):
Hypothesized
Trace
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None *      
 0.0023
At most 1      
 0.1309
 Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
 * denotes rejection of the hypothesis at the 0.05 level
 **MacKinnon-Haug-Michelis (1999) p-values

28. Results of Granger Causality test between HHI and Globalization (Glob)
Sample:
Lags: 1 
Null Hypothesis:
Obs
F-Statistic
Prob. 
 KOFPOLITICAL does not Granger Cause HHI
 25  
0.0085
 HHI does not Granger Cause KOFPOLITICAL  
0.2098

29. Results of Granger Causality test between HHI and Kof political
Sample:
Lags :2
Null Hypothesis:
Obs
F-Statistic
Prob. 
 KOFPOLITICAL does not Granger Cause HHI
 23  
0.0379
 HHI does not Granger Cause KOFPOLITICAL  
0.0631

30. Results of Granger Causality test between HHI and KOF political
Sample:
lags :3
Null Hypothesis:
Obs
F-Statistic
Prob. 
 KOFPOLITICAL does not Granger Cause HHI
 22  
0.2214
HHI does not Granger Cause KOFPOLITICAL  
0.8878

31. Results showing the FMOLS between HHI and kofpolitical (Glob)
Dependent Variable: HHI
Method: Fully Modified Least Squares (FMOLS)
Included observations: 26 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.  
KOFPOLITICAL
0.0000 C
0.1359
R-squared
    Mean dependent var
Adjusted R-squared
    S.D. dependent var
S.E. of regression
    Sum squared resid
Durbin-Watson stat
    Long-run variance

32. Results of the CCR Regression
Dependent Variable: HHI
Method: Canonical Cointegrating Regression (CCR)
Sample (adjusted):
Variable
Coefficient
Std. Error
t-Statistic
Prob.  
KOFPOLITICAL
0.0000 C
0.1384
R-squared
    Mean dependent var
Adjusted R-squared
    S.D. dependent var
S.E. of regression
    Sum squared resid
Durbin-Watson stat
    Long-run variance

33. Table 6.2: Results of the DOLS Regression
Method: Dynamic Least Squares (DOLS)
Sample (adjusted):
Included observations: 21 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.  
KOFPOLITICAL
0.0617 C
0.3050
R-squared
    Mean dependent var
Adjusted R-squared
    S.D. dependent var
S.E. of regression
    Sum squared resid
Durbin-Watson stat
    Long-run variance

34. Conculsion
From the regression analysis it can be concluded that globalization has positive association with increased export concentration .
However the interesting observation from this study has been that the export concentration increased more with political globalization then with economic globalization . This therefore indicate that more political friendly or globalized we are as a nation it has impact on attracting our exports more by other nations.