Causal Relationship between Agriculture, Industry and Services Sector for GDP Growth in Bangladesh: An Econometric Investigation

Transcription

1 Causal Relaionship beween Agriculure, Indusry and Services Secor for GDP Growh in Bangladesh: An Economeric Invesigaion Mirza Md. Moyen Uddin Assisan Professor (Economics), Bangladesh Civil Service General Educaion Cadre, Under Naional Universiy, Direcorae of Secondary and Higher Educaion, Minisry of Educaion, Bangladesh, Dhaka Absrac This sudy examines he conribuion of agriculure, indusry and services secors o economic growh in Bangladesh by using ime series daa from 1980 o Augmened Dickey-Fuller (ADF) and Phillips-Perron (PP) uni roo ess show ha he ime series daa saionary a firs difference. Then, he coinegraion analysis indicaes ha each economic secor has srong, posiive and significan linear relaionship wih economic growh. Granger causaliy es found bi-direcional causaliy beween agriculure and GDP and also indusry and agriculure. This empirical sudy also found he unidirecional granger causaliy from services secor o agriculure and indusry secor o services secor. Finally, he Vecor Error Correcion Model (VECM) also used o examine he shor and long run equilibrium relaionships among he variables. This sudy gives he guideline o he invesors and policy makers. Keywords: economic growh, economic secors, economeric analysis, Bangladesh 1. Inroducion Agriculure is he core secor for he economy of Bangladesh since is independence (1971) and sill conribuing around 18 percen o GDP. Besides providing employmen o 48.1 percen labor force, his secor provides accommodaion 62 percen manpower of he naion, and 84 percen of he populaion of Bangladesh living in rural areas, direcly or indirecly depends upon agriculure for heir livelihood. I is he primary source of employmen, livelihood, and food securiy for he majoriy of rural people. I also provides raw maerial o indusry and conribues o counry s expors. So any sraegy change for agriculure secor will affec he economy and a large secion of populaion in he counry (Alam, 2008a). However, due o rapid developmen and reformaion of a counry, he agriculure secor has been gradually negleced. Neverheless, undersanding he role of agriculure and is linkages o economic growh is imporan. The indusry secor includes manufacuring, consrucion, public uiliies and mining, growing gradually wih increase in employmen in Bangladesh. According o Kaldor (1967), manufacuring is an engine of economic growh as indusrial goods have a higher-income elasiciy of demand. In Bangladesh, indusries could no develop much due o hinder by poliical insabiliy and naural disasers. Despie hese negaive facors, he expor secor has acceleraed wih he average growh of 30% and economic growh has been surprisingly sable, averaging 6.3% in he pas 5 years (Rahman, 2011). The services secor is increasingly seen as a means o promoe economic developmen and reduce povery. I is fas becoming he larges secor, in erms of is share of GDP and employmen, in mos developing counries (Hussin and Yik, 2012). The services secor is highly diverse, ranging from infrasrucure services, financial services, business services and social services. Since his secor conribues significanly o GDP in Bangladesh, herefore i is also included as a variable in his sudy. Recenly, service is he larges secor in he percenage conribuion o 53.9 % of GDP. Wang, e al. (2010) shows ha here has always been a posiive relaion beween agriculure and economic growh and discuss how agriculure conribues o economic growh. They concludes ha alhough he share of agriculure in GDP has declined significanly over ime, he conribuion of agriculural growh has mainained an upward rend and i has made an imporan bazaar, foreign exchange and oupu conribuions o non-agriculural growh and remains an excepional driving force for economic growh. Andzio and Kamiewoko, (2004), analyze ha he influence of agriculure on GDP of China and hree Sub-Saharan African (SSA) counries by using muliple regression models and demonsrae ha agriculure remains as he cornersone of China and he SSA counries where i has a significan effec on GDP in hese counries. Subramaniam and Reed (2009) esimaed an economeric model ha incorporaes he linkage among agriculure, manufacuring, service and rade secors using a vecor error correcion model for Poland and Romania. Chang e al., (2006), menion ha he revenue generaion effec dominaes he comparaive advanage effec; higher agriculural produciviy enhances indusrializaion and increases long run economic growh in Japan, Taiwan and Korea. The resuls show ha higher agriculural produciviy will subsequenly increase indusrial secors employmen and hus will enhance economic growh. Sulan (2008) saes ha indusry value-added as a possible source of economic growh in addiion o expor and impor ha can conribue more han he growh rae of expor-impor owards 124

2 he growh rae of GDP in Bangladesh. He found ha he exisence of co-inegraion and a long run relaionship beween GDP and indusry value added using bivariae co-inegraion es. This paper aims o invesigae how hree differen secors namely, agriculure, Indusry and Service secor are affecing he GDP growh in Bangladesh. I also inends o measure he relaionship beween he concerned variables and heir overall impac on GDP. The res of he sudy is organized as follows. The daa and mehodology are explained in Secion 2. The empirical resuls are discussed in Secion 3. Findings and concluding remarks are discussed in he las secion. 2. Daa and Mehodology 2.1 Daa This paper uses annual ime series daa of Agriculure, Indusry and Service secor of heir value added conribuion in GDP covering he period from 1980 o 2013 of Bangladesh. Real per capia GDP is aken as US dollar ($). The daa obained from online version of World Developmen Indicaors (WDI), he World Bank. As his sudy examines he conribuion of agriculure, indusry and service secor o economic growh in Bangladesh, secondary daa is appropriae for he sudy. Mehodology Assessmen of Granger causaliy beween he variables and he direcion of heir causaliy in a vecor error correcion framework requires hree seps. The firs sep is o es he non-saionariy propery and deermine order of inegraion of he variables, he second sep is o deec he exisence of long run relaionship and he hird sep is check he direcion of causaliy beween he variables. 2.2 Model Specificaion This sudy invesigaes he conribuion of economic secors o economic growh in Bangladesh from 1980 o Correlaion analysis and muliple regression analysis are used o examine he relaionship beween he dependen variable and he independen variables in he sudy. The following model represens he relaionship beween per capia real Gross Domesic Produc (GDP) and he hree economic secors, namely agriculure, indusry and services secors for Bangladesh. The equaion for he muliple regression analysis is: GDP = β 0 + β1agr + β2ind + β3serv + µ (1) Where, GDP = Real Gross Domesic Produc per capia, Agr = Share of value added in agriculure secor o real GDP per capia, Ind = Share of value added in indusry secor o real GDP per capia, Serv = Share of value added in services secor o real GDP per capia, β0 = Inercep, β β = Co-efficien and µ = Error Term 1, 2, β3 2.3 Saionariy Tes The annual ime series daa cover a period of 34 years from 1980 o 2013 is used o deermine he relaionship beween economic secors and economic growh in Bangladesh. In he firs sep of he esimaion process, his sudy examines he saionariy properies of he daa series. According o Nelson and Plooser (1982), mos of he ime series ha appear in he economy will have o be differenced in order o become saionary. In fac, mos economic variables show a rend and herefore in mos cases are non-saionary. Thus, before moving furher analysis of he variables, i needed o ensure saionary properies of he variables. This sudy uses Augmened Dickey Fuller (ADF) es (Dickey and Fuller, 1979, 1981) o perform he uni roo ess. The ADF es includes exra lagged erms of he dependen and independen variables, which are real GDP per capia, agriculure secor, indusry secor and services secor in order o eliminae auocorrelaion. This sudy uses a regression model ha includes an inercep and a ime rend: Y = β + β + β Y + α Y + µ k i i (2) i= 1 The ADF regression ess for he exisence of uni roos ofy, namely all model variables a ime. The variable Y i represens he firs differences wih k lags while µ is a variable ha adjuss he errors of auocorrelaion. β 0, β1 and α i are he coefficiens values. The Augmened Dickey-Fuller (ADF) and Phillips-Perron (PP) uni roo ess use inercep and rend and es for variables saionariy a levels and firs differences. 125

3 Table 1: Augmened Dickey-Fuller and Phillips-Perron uni roo es resuls for boh Trend and Wihou Trend of four variables in Level and Firs Difference Resuls of Augmened Dickey-Fuller (ADF) Uni Roo Tes Variables Saisics Criical value Saisics Criical value Wih inercep 1% 5% 10% Wih rend and inercep Level Form GDP (3) * * - Agr (3) Ind (3) Serv (3) * * - Difference Form GDP % 5% 10% (3) (3) (3) (3) (3) * * (3) Agr * * (3) * * (3) * Ind (3) * * (3) Serv (3) * * (3) Resuls of Phillips-Perron (P.P.) Uni Roo Tes Variables Saisics Criical value Saisics Criical value Wih 1% 5% 10% inercep 1% 5% 10% Wih rend and inercep Level Form GDP (3) * * - Agr (3) Ind (3) * * - Serv (3) * * - Difference Form GDP (3) (3) (3) (3) (3) * * (3) Agr * * (3) * * (3) * Ind (3) * * (3) Serv (3) * * (3) Noe: The es is conduced using Eviews Table 1 repors he resuls of he ADF and PP uni roo es for four variables in he levels and differences. Ineresingly, all he variables are no saionary in heir levels bu become saionary afer firs differencing. On he base of criical value, * denoes ha he rejecion of null hypohesis of uni roo a 1%, 5% and 10% levels of significance. Here we consider he variables wih inercep only, and wih rend and inercep, boh in level and firs difference form. Number in he bracke denoes lag lengh. 3. Empirical Resuls 3.1 Resuls of Coinegraion Afer examining he saionariy of hese series we used Johansen s and Juselius (1990) mehod o es for 126

4 coinegraion beween he series of Agriculure, Indusry, Service secor and GDP growh. Coinegraion means ha despie being individually non-saionary, a linear combinaion of wo or more ime series daa can be saionary (Gujarai, 2011). When a linear combinaion of non saionary variables is saionary, he variables are said o be coinegraed and he vecor ha is quie possible for a linear combinaion of inegraed variables o be saionary. In his case he variables are said o be coinegraed. The coinegraion echnique uses wo ess-he maximum Eigen value saisics and race saisics in esimaing he number of coinegraion vecors. The race saisic evaluaes he null hypohesis ha here are a mos r coinegraing vecors whereas he maximal Eigen value es evaluaes he null hypohesis ha here are exacly r coinegraing vecors. Table 2: Johansen Tes for Co-inegraion Noe: The es is conduced using Eviews From Table 2, we found ha Maximum Eigen value es and Trace es, he esimaed es saisics is no less han he criical value for r=0 for boh wih and wihou rend a 5 % level of significance. This indicaes ha here is one coinegraion equaion and he variables- share of value added of Agriculure in GDP, share of value added of Indusry in GDP and share of value added of Service secors in GDP and oal GDP have he long run relaionships. So, i is clear ha here is one linear coinegraion equaion, long run relaionship and liner deerminisic rend among he variables. 3.2 Resuls of Granger Causaliy Tes Granger Causaliy (1969) analyzed ha if he variables are coinegraed hen here should be a leas one direcion of causaliy beween he wo variables and his causaliy has been esed by F-saisics. Table 3 shows he resuls of secor wise Granger causaliy beween he variables. Resul shows ha GDP and Agriculure secor Granger causes each oher bi-direcionally. Indusry secor Granger causes GDP very srongly bu GDP does no cause Indusry secor. Service secor and GDP do no cause each oher. Indusry and Agriculure secor Granger cause each oher i.e. hese secors are dependen on each oher srongly for heir conribuion o GDP. On he oher hand Service secor Granger causes Agriculure secor bu Agriculure secor does no granger cause Service secor. Finally, Service secor does no cause Indusry secor bu Indusry secor Granger causes Service secor in he sudy. 127

5 Table 3: Granger Causaliy beween he Variables (Agr, Ind, Serv and GDP) Null Hypohesis Lag Obs. F-Saisics Probabiliy Decision Agr does no Granger Cause GDP Rejeced* GDP does no Granger Cause Agr Rejeced* Ind does no Granger Cause GDP GDP does no Granger Cause Ind Rejeced* Acceped Serv does no Granger Cause GDP GDP does no Granger Cause Serv Acceped Acceped Ind does no Granger Cause Agr Agr does no Granger Cause Ind Rejeced* Rejeced* Serv does no Granger Cause Agr Agr does no Granger Cause Serv Rejeced* Acceped Serv does no Granger Cause Ind Ind does no Granger Cause Serv Acceped Rejeced* Noe: The es are performed using he sofware Eviews Here, GDP = Real Gross Domesic Produc per capia, Agr = Share of value added in agriculure secor o real GDP per capia, Ind = Share of value added in indusry secor o real GDP per capia, Serv. = Share of value added in services secor o real GDP per capia. * denoes significance of he resuls and rejecion of hypohesis. From hese resuls i can be said ha Agriculure and Indusry secor closely relaed o GDP bu Service secor and GDP do no cause each oher in he process. 3.3 Error Correcion Modeling (ECM) Granger and Engle (1983) analyzed ha if he variables are inegraed of order one and coinegraed, hen here exiss he Error Correcion Term (ECT) and hese variables bears he seady sae siuaion or in equilibrium siuaion. Considering he following equaion which exis each oher relaionship as: Y k = β + β + β Y + α Y + α ECT + ε i i i i (3) i= 1 Where Y denoes he variables, ECT i is he error correcion erm which is he lagged residual series of he coinegraing vecor, denoes he firs difference and ε denoes he whie noise erm. Here he error correcion erm capuring he disequilibrium siuaion. The negaive and significan coefficien of error erm suggess ha here is a shor run adjusmen process working behind he long run equilibrium relaionship among he variables. Coefficien parameers of error correcion erm are he speed of adjusmen for he shor run imbalances. In fac, in he vecor error correcion model all he variables are endogenously deermined wihin he model. When he variables are coinegraed, here is a sysemaic and general endency of he series o reurn o heir equilibrium siuaion. This means ha he dynamics of adjusmen is inrinsically embodied in he heory of coinegraion. Moreover, Granger Represenaion Theorem indicaes how o model a coinegraed series in a Vecor Auo Regressive (VAR) forma. VAR can be consruced eiher in erms of level daa or in erms of heir firs differences wih he addiion of an error correcion o capure he shor run dynamics. Table 4: Resuls of Vecor Error Correcion Tes Coefficien F Coefficien F [ ]* [ ]* GDP = ( Agr) Arg = (GDP) GDP = (Ind) GDP = (Serv) Ind = ( Agr) Ind = (Serv) Agr = (Serv) [ ]* [ ]* [ ]* [ ]* [ ]* Ind = (GDP) Serv = (GDP) Agr = (Ind) Serv = (Ind) Serv = ( Agr) [ ]* [ ]* [ ]* [ ]* [ ]* Noe: The es are performed using he sofware Eviews Noe: * denoes he rejecion of he hypohesis a 5% level of significance. The (*) values are saisically significan and shows he esimaed coefficien of lagged variables. Values in he hird brackes are -saisics. Table 4 shows ha he vecor error correcion resuls are significan for agriculure and GDP growh, indusry and GDP growh, service secors and GDP growh and service secors and agriculural developmen, indicaing 128

6 he long run and shor run causal effecs on each oher. The significan lagged ECT coefficien indicaes ha he curren oucomes are affec by he pas equilibrium errors. If he wo variables are coinegraed, here mus i exiss an error correcion mechanism. This implies ha error correcion model is associaed wih he coinegraion es. The long erm effecs of he variables can be represened by he esimaed coinegraion vecor. The adjused coefficien of error correcion erm (ECT) shows he long erm effec and he esimaed coefficien of lagged variables shows he shor erm effec. Causaliy es among he variables are based on Error Correcion Model wih firs difference. 4. Findings and Concluding Remarks This paper examined he causal relaionship among GDP per capia, agriculure, indusry and services secors for Bangladesh for he year The sudy found he exisence of he long run causal relaionship among hese variables. To search for he naure of he relaionship beween he variables, we have implemened he granger causaliy ess and found bi direcional relaionship beween GDP and agriculural which indicae ha he agriculural and GDP influence on each oher o grow in case of Bangladesh. And also bi direcional causaliy is obained in case of agriculure and indusry. So, he resuls showed ha indusry and agriculure secor influence on each oher for he growh of our GDP. We also found unidirecional granger causaliy from indusrial secor o GDP growh and service secors o indusrial growh. So, i is clear ha if agriculure and indusry secor will boos, hen is influence o increase he GDP of Bangladesh where as service secors do no influence he GDP of Bangladesh individually. Bu, services secor is a more significan conribuor (53.9%) o economic growh in Bangladesh and day by day is involvemen is increasing. Therefore his secor should be given prioriy in he planning of naional developmen policies. In addiion, he counry should devise sraegies o arac more foreign invesmens ino is indusry and agriculure secors o conribue in GDP growh. Thus, he hree secors are closely conneced wih each oher and any changes of sraegy in any secor will affec he economy and he livelihoods of he people ha is why governmen and policy makers should ake he decision wih updaed and significan resul of research. References Alam, G.M. (2008a), The Role of Technical and Vocaional Educaion in Naional Developmen of Bangladesh, Asia Pac. J. Coop. Educ., 9(1), Chang, J. J., Chen, B.L., and Hsu, M. (2006), Agriculural produciviy and economic growh: Role of ax revenues and infrasrucures, Souhern Economic Journal, 72, ,hp://dx.doi.org/ / Dickey, D.A., and Fuller, W.A. (1981), Disribuion of he esimaors for he auoregressive ime series wih a uni roo, Economerica, 49, Granger, C. W. J. (1969), Invesigaing causal relaion by economeric and cross secional mehod. Economerica, 37, Gujarai, D. N. (2011), Basic Economerics, Eighh reprin, McGraw-Hill Publicaions, New York. Hussin, F. and Yik, S. Y. (2012), The Conribuion of Economic Secors o Economic Growh: The Cases of China and India, Research in Applied Economics, 4(4), 38-53, ISSN Johansen, S., and Juselius, K. (1990), Maximum likelihood esimaion and inference on coinegraion wih applicaions o he demand for money, Oxford Bull, Eco, Sa., 52, Kaldor, N. (1967), Sraegic facor in economic developmen, New York: New York Sae School of Indusrial and Labor Relaions Nelson, C., and Plosser, C. I. (1982), Trend and random walks in macroeconomic ime series:some evidence and implicaion, Journal of Moneary Economics, 10, ,hp://dx.doi.org/ / (82) Rahman, M.M., Rahman, M.S. and Hai-bing, W.U. (2011), Time Series Analysis of Causal Relaionship Among GDP, Agriculural, Indusrial and Service Secor Growh in Bangladesh, David Publishing, 10(1), 9-15, China USA Business Review, ISSN Subramaniam, V. and Reed, M. (2009), Agriculural iner-secoral linkages and is conribuion o economic growh in he ransiion counries, Conribued Paper Prepared for Presenaion a he Inernaional Associaion of Agriculural Economiss Conference, Beijing, China Sulan, P. (2008), Trade, indusry and economic growh in Bangladesh, Journal of Economic Cooperaion, 29(4), Wang, X. Z., Wu, S. L., and Gao, F. (2010), The relaionship beween economic growh and agriculural growh: The case of China. Paper presened a Inernaional Conference on E-Business and E-Governmen (ICEE), Guanghou, China 129

7 The IISTE is a pioneer in he Open-Access hosing service and academic even managemen. The aim of he firm is Acceleraing Global Knowledge Sharing. More informaion abou he firm can be found on he homepage: hp:// CALL FOR JOURNAL PAPERS There are more han 30 peer-reviewed academic journals hosed under he hosing plaform. Prospecive auhors of journals can find he submission insrucion on he following page: hp:// All he journals aricles are available online o he readers all over he world wihou financial, legal, or echnical barriers oher han hose inseparable from gaining access o he inerne iself. Paper version of he journals is also available upon reques of readers and auhors. MORE RESOURCES Book publicaion informaion: hp:// Academic conference: hp:// IISTE Knowledge Sharing Parners EBSCO, Index Copernicus, Ulrich's Periodicals Direcory, JournalTOCS, PKP Open Archives Harveser, Bielefeld Academic Search Engine, Elekronische Zeischrifenbibliohek EZB, Open J-Gae, OCLC WorldCa, Universe Digial Library, NewJour, Google Scholar