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Empirical Evidence on Indirect Spillover Effects BRICs AND THE LOW INCOME COUNTRIES: Aysu INSEL Istanbul Kemerburgaz University, Faculty of Economics and.

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Presentation on theme: "Empirical Evidence on Indirect Spillover Effects BRICs AND THE LOW INCOME COUNTRIES: Aysu INSEL Istanbul Kemerburgaz University, Faculty of Economics and."— Presentation transcript:

1 Empirical Evidence on Indirect Spillover Effects BRICs AND THE LOW INCOME COUNTRIES: Aysu INSEL Istanbul Kemerburgaz University, Faculty of Economics and Administrative Sciences Department of Economics aysu.insel@kemerburgaz.edu.tr Abdurrahman KORKMAZ Izmir Katip Çelebi University, Faculty of Economics and Administrative Sciences Department of Economics Argiro MOUDATSOU Technological Educational Institute of Crete, School of Accounting and Management, Department of Business Administration Second International Conference of the Society for Economic Measurement July 22-24, 2015 OECD Conference Center Paris, France

2 OUTLINE BACKGROUND BACKGROUND MOTIVATION MOTIVATION RESEARCH QUESTIONS RESEARCH QUESTIONS DATA AND METHODOLOGY DATA AND METHODOLOGY EMPIRICAL RESULTS EMPIRICAL RESULTS CONCLUSION AND IMPLICATIONS CONCLUSION AND IMPLICATIONS

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7 While industrial countries remain LICs’ dominant development partners, LIC-BRIC ties have increased so rapidly over the past decade that BRICs have become new growth drivers for LICs. (IMF, 2011) Source: IMF, 2011

8 Neither BRICs nor LICs are homogeneous and relations at a bilateral level vary considerably. For this reason, detailed analysis will be needed to inform policy formulation (IMF, 2011). Source: Samake and Yang (2011)

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10 engine of growth J. O’Neill (2001) stated: the BRIC Economies as the engine of growth driven by demand. BRICs stated as a bridge between DC and LDC. Our Discussion Our Discussion: trade If the growth is driven by demand, then trade is important. FDI If the architecture of international development is changing, then FDI is important. So; What will happen to the LIC economies as the BRIC Economies are slowing down? Past, Now, Future states...

11 New Growth Drivers for Low-Income Countries: The Role of BRICs Prepared by the Strategy, Policy, and Review Department, (In collaboration with the African Department), Approved by Reza Moghadam, IMF, January 12, 2011 Low-Income Countries' BRIC Linkage: Are There Growth Spillovers? SamakeYang Issouf Samake and Yongzheng Yang, IMF Working Paper, Western Hemisphere Department and Asia and Pacific Department, November 2011 The Role of BRICs in the Developing World. Morazán, Pedro, Knoke, Irene,, Knoblauch, Doris, Schäfer, Thobias, The European Parliament's Committee, Development Report, April 2012 RELATED!! LITERATURE

12 RESEARCH QUESTIONS Which one is the important direct spillover channels of transmission from BRICs to LICs: TRADE and/or FDI inflows? If there is strong direct spillover effect between the BRICs and LICs, what could happen to the LICs in the future?

13 Source: The EU Development Report

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17 Data and Variable Definitions Data source: Trade and Development Statistical Database. (UNCTADSTAT) Variable definitions: g = GDP growth (US Dollars at constant prices (2005) and constant exchange rates (2005) X = (Export to BRIC/ Total LIC’s export)*100 M = (Import from BRIC/ Total LIC’s import)*100 FDI = (FDI from BRIC/ Total FDI to LIC’s))*100 (as flow balanced panel 2006-2012 Dataset is balanced panel and covers the period of 2006-2012

18 balanced dynamic panel-data model The model is specified as a balanced dynamic panel-data model: Dynamic Panel Data Model ω i are the panel level effects (which may be correlated with the covariates)

19 Arellano and Bover (1995) and (2) Blundell and Bond (1998, 2000), the System GMM two-step estimator Roodman (2006). The model is estimated by (1) the Arellano and Bover (1995) and (2) Blundell and Bond (1998, 2000), the System GMM two-step estimator is obtained in STATA by using xtabond2 routine of Roodman (2006). Considering a possible correlation between the lagged dependent variable and the panel fixed effects and the “small T, large N” restriction, Windmeijer’s (2005) procedure robust Windmeijer’s (2005) procedure is implemented so that standard errors become robust after getting small sample size of the dataset under control. Estimation Method

20 possible weaknesses; For the possible weaknesses; such as unobserved heterogeneity, endogeneity, autocorrelation, weak instruments; Arellano-Bond AR test for autocorrelation the Arellano-Bond AR test for autocorrelation Hansen tests for over-identifying restrictions and thus the instrument exogeneity the Hansen tests for over-identifying restrictions and thus the instrument exogeneity F test the convetional F test are employed.Instruments: for first differences equation for first differences equation first differenced (lag) Standard first differenced (lag) variables for levels equation for levels equation level lag) variables Standard level (lag) variables Estimation Method

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22 TABLE.1: Dynamic Panel Estimation, Two Step System GMM Direct Spillover Effects from BRIC economies to Low Income Countries_with dummy ALL_SPECIFIC g LIC g LIC (-1)0.219 ** (0.041)0.178 *** (0.098)0.257 * (0.099)0.266 ** (0.105)0.238 ** (0.104) X bra -0.209 (0.288) X bra (-1)0.429 *** (0.262) 0.326 ** (0.159) M bra 0.154 (0.229) M bra (-1)-0.325 (0.174) -2.737 ** (0.141) FDI bra 0.0002 (0.024) FDI bra (-1)-0.018 (0.023) X rus 0.254 (0.253) X rus (-1) -0.331 (0.242) -0.137 ** (0.077) M rus -0.129 (0.217) M rus (-1) 0.209 (0.241) FDI rus 0.0281 (0.029) FDI rus (-1) -0.091 ** (0.509) X ind -0.126 (0.028) -0.149 * (0.203) X ind (-1) 0.113 (0.027) 0.136 * 0.017 M ind 0.008 (0.067) M ind (-1) -0.001 (0.051) FDI ind 0.198 (0.061) 0.144 ** (0.065) FDI ind (-1) 0.033 (0.101) X chi 0.689 (0.067) X chi (-1) -0.042 (0.070) M chi 0.128 (0.888) M chi (-1) -0.138 (0.919) FDI chi 0.0003 * (0.000)0.0003 * (0.0001) FDI chi (-1) -0.0002 * (0.000)-0.0003 * (0.0002) Dummy 2009 -2.379 * (0.757)-3.367 * (0.908)-2.557 * (0.770)-2.593 * (0.766)-3.257 * (0.804) Dummy africa 4.705 * (0.741)5.008 * (0.745)4.445 * (0.688)4.054 * (0.795)5.578 * (0.825) Dummy CIS 5.245 * (0.989)4.839 * (1.815)4.595 * (0.887)4.215 * (0.993)7.521 * (1.329) Dummy asia 3.935 * (0.681)4.487 * (0.859)3.986 * (0.923)3.462 * (0.971)4.886 * (1.074) Dummy america 2.415 * (0.576)3.056 * (0.726)2.716 * (0.668)2.606 * (0.636)2.582 * (0.548)

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26 Econometrics Results for specific form Diagnostics T=6 and Group=52N=312. Diagnostics with T=6 and Group=52, N=312. Arellano & Bond AR test no autocorrelation for AR(2) process Arellano & Bond AR test: AR(1) and AR(2) test for the existence of the first and second order autocorrelation in first-differenced errors under the null hypothesis reveal that there is no autocorrelation for AR(2) process. Hansen tests orthogonality conditions Hansen tests of over-identifying restrictions do not reject the orthogonality conditions for all of the estimations. Roodman uncorrelated System GMM two-step estimators are implemented in STATA by using xtabond2 routine of Roodman to ensure that first differenced instruments used in levels are uncorrelated with unobserved effects.

27 BRAZIL & LICs Direct Spilover channels of Brazil to LICs: Individual model:  Table.1: EXPORT(t-1)  Table.2: no effect Joint model:  Table.1: EXPORT (t-1), IMPORT(t-1)  Table.2: IMPORT(t)  No FDI effects  TRADE effects Economic Results for specific form

28 RUSSIA & LICs Direct Spilover channels of Russia to LICs: Individual model:  Table.1: FDI(t-1)  Table.2: no effect Joint model:  Table.1: EXPORT (t-1)  Table.2: no effect  No IMPORT effect  ??? EXPORT and FDI effects.

29 INDIA & LICs Direct Spilover channels of India to LICs: Individual model:  Table.1: no effect  Table.2: EXPORT(t-1), IMPORT(t) Joint model:  Table.1: EXPORT (t) & (t-1)  Table.2: IMPORT(t), FDI(t)  No FDI effect  TRADE effects

30 CHINA & LICs Direct Spilover channels of China to LICs: Individual model:  Table.1: FDI (t) & (t-1)  Table.2: X(t-1), FDI (t) & (t-1) Joint model:  Table.1: no effect  Table.2: M(t-1), FDI (t) & (t-1)  ??? TRADE effects  FDI effect

31 What have we found? Brazil and India strong TRADE weak FDI Brazil and India have relatively strong TRADE and weak FDI ties with the LICs. Chinastrong FDI weak TRADE China has relatively strong FDI and weak TRADE links which seem to be diversified in Asia and Africa. Russia weak TRADE FDI Russia has relatively weak TRADE and FDI links with LICs. China India FDI large scale land acquisitions demand for natural resources China and India FDI have the form of large scale land acquisitions; so their demand for natural resources are high.

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33 Conclusion: through either TRADE or FDI  Direct spillover channels of transmission from the BRIC economies to the LICs arise through either TRADE or FDI. complementary trade pattern  The results support the view that BRICs and LICs have a complementary trade pattern which have been explained by the comparative advantages (IMF view). BItrade ties are strong  BRIC trade ties are strong with Asian and African LICs. TradeFDI resource rich  Their Trade & FDI links are strong with resource rich LICs.

34 What could happen?  Which direction? Backward looking OR forward looking!!  BRIC  BRIC economies are experiencing slowing down…  China  China has almost 60% share of BRIC economies and a high level of capital acquisition…  China  China has almost 30% share of world’s economic growth… cyclical structuralChina.  There is not only cyclical, but also a structural slow down in China.

35 Overall E Examining the transmission effects of BRICs on the LICs during the globalization process and considering the implications of the research results with current state of global economies;  It is true that the BRICs imposed positive effects on the LICs growth patterns; However;  It is difficult to conclude that the BRICs will be the persistent growth drivers for the LIC economies in the future.

36 Thank you..


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