AVRUPA’DA KAMU HARCAMALARI VE EKONOMİK BÜYÜME ARASINDAKİ İLİŞKİNİN MEKÂNSAL PANEL VERİ ANALİZİ İLE İNCELENMESİ

Devletin ekonomiye müdahale etmesi gerektiğini savunan Keynesyen yaklaşımda etkili müdahale kalemlerinden biri kamu harcamalarıdır. Bazı iktisatçılar, kamu harcamalarının politikacıların oy toplama amaçlarına hizmet ettiği için verimsiz harcamalar olduğunu, bu harcamaların ileriki dönemlerde vergi olarak geri döneceğini söylemekteyken bazı iktisatçılar da ekonomik durgunluk durumunda yapılacak olan kamu harcamalarının ekonomiyi tekrar canlandıracağı için gerekli ve yararlı olduğu görüşündedirler. Bu çalışmada 1997-2017 yılları arasında Avrupa‟da hükümet harcamalarının kişi başı Gayri Safi Yurt İçi Hâsıla büyümesini nasıl etkilediği mekânsal bağımlılığı dikkate alan modeller kullanılarak araştırılmıştır. Birbirine komşuluk ilişkisi bulunan yatay-kesitler (ülkeler), mekânsal ekonometrik yöntemlerin kullanılmasını gerekli kılmıştır. Bunun için mekânsal gecikme modeli, mekânsal hata modeli, mekânsal Durbin model, genel mekânsal model ile bunların rassal ve sabit etkili versiyonları ve genelleştirilmiş rassal etkili mekânsal hata modeli incelenmiştir. Kurulan modellerden elde edilen bulgulara göre, tüm modellerde hükümet harcamaları yıllık büyümesinde meydana gelen artışlar kişi başı GSYİH büyümesini artırmaktadır. Avrupa‟da tam istihdam seviyesini yakalamak isteyen politikacılar, hükümet cari harcamalarını artırma yoluna gidebilir. Bunun yanında, komşu ülkelerdeki durumu da dikkate almak zorundadırlar. Çünkü mekânsal otokorelasyonu gösteren katsayılar istatistiksel olarak anlamlı bulunmuştur, yani mekânlar birbirine yaklaştıkça birbirini daha çok etkilemektedirler. Bu mekânsal bağımlılık, hem mekânsal hata hem de mekânsal gecikme modellerinde görülmüştür. Yani hem komşu hataları hem de komşu bağımlı değişken olan kişi başı GSYİH büyümesi değerleri komşularını etkilemektedir.

ANALYSIS OF THE RELATIONSHIP BETWEEN PUBLIC EXPENDITURE AND ECONOMIC GROWTH IN EUROPE WITH SPATIAL PANEL DATA ANALYSIS

In the Keynesian approach which advocates government interference to the economy, one of the efficient interference items is government expenditures. While some economists allege the public expenditures are inefficient, because of they serve the vote collection goal of the politicians and thus, they will turn back as higher taxes in the future; some of them assert that public expenditures made at the recession period are essential and beneficial, because they will revive the economy. In this study, it is investigated that how the effects of government spending on per capita GDP growth in Europe between 1997-2017 using by models considering spatial dependence. The cross-sections (countries) with neighboring relations, have required to use spatial econometric methods. Therefore, spatial lag model, spatial error model, spatial Durbin model, general spatial model and also fixed and random effects versions of these and lastly generalized random effects spatial error model have been examined. Our results reveal that increases in the annual growth of government spending in all models enhance the GDP per capita growth. Politicians who want to achieve the full level of employment in Europe could increase government spending. They must also consider the situation in neighboring countries. Because the coefficients of spatial autocorrelation are statistically significant mean that they interact with each other much more as the spaces approach each other. This spatial dependency, not only have been seen in the spatial lag models, but also seen in the spatial error models. Namely, either the values of neighbor errors and neighbor depended variable called GDP per capita growth, effects neighbors.

PDF

___

AFONSO, A., ve Furceri, D. (2010). Government size, composition, volatility and economic growth. European Journal of Political Economy, 517-532. https://doi.org/10.1016/j.ejpoleco.2010.02.002
ANSELİN, L. (1988). Spatial Econometrics: Methods and Models. Netherlands: Kluwer Academic Publishers.
ANSELİN, L., Gallo, J. L., ve Jayet, H. (2008). Spatial panel econometrics. L. Matyas, ve P. Sevestre içinde, The Econometrics of Panel Data (s. 625-657). Berlin: Springer. https://doi.org/10.1007/978-3-540-75892-1_19
ARBİA, G. (2006). Spatial Econometrics. Springer. https://doi.org/10.1007/3-540- 32305-8
ARPAİA, A., ve Turrini, A. (2007). Government expenditure and economic growth in the EU: Long-run tendencies and short term adjustment. Economic Papers 300. https://doi.org/10.2139/ssrn.2004461
BALTAGİ, B. H. (2005). Econometric Analysis of Panel Data. John Wiley ve Sons, Ltd. https://doi.org/10.1017/s0266466600006150
BALTAGİ, B. H., Egger, P., ve Pfaffermayr, M. (2013). A Generalized spatial panel data model with random effects. Econometric Reviews, 650-685. https://doi.org/10.1080/07474938.2012.742342
BALTAGİ, B. H., Song, S. H., ve Koh, W. (2003). Testing panel data regression models with spatial error correlation. Journal of Econometrics, 123-150. https://doi.org/10.1016/s0304-4076(03)00120-9
BARRO, R. J. (1990). Government spending in a simple model of endogenous growth. Journal of Political Economy, 103-125. https://doi.org/10.1086/261726
BASİLE, R. (2008). Regional economic growth in europe: a semiparametric spatial dependence approach. Papers in Regional Science 87(4), 527-544. https://doi.org/10.1111/j.1435-5957.2008.00175.x
BELL, K. P., ve Bockstael, N. E. (2000). Applying the generalized-moments estimation approach to spatial problems involving microlevel data. The Review of Economics and Statistics, Cilt: 82, Sayı: 1, 72-82. https://doi.org/10.1162/003465300558641
BİVAND, R., ve Brunstad, R. (2006). Regional growth in Western Europe: Detecting spatial misspecification using the R environment. Papers in Regional Science 85(2), 277 - 297. https://doi.org/10.1111/j.1435-5957.2006.00086.x
BLOMMESTEİN, H. J., ve Koper, N. A. (1997). The influence of sample size on the degree of redundancy in spatial lag operators. Journal of Econometrics 82, 317 333. https://doi.org/10.1016/s0304-4076(97)00060-2
BOCUTOĞLU, E. (2011). Makro İktisat:Teoriler ve Politikalar. Trabzon: Murathan Yayınevi.
BODSON, P., ve Peeters , D. (1975). Estimation of the coefficients of a linear regression in the presence of spatial autocorrelation. An application to a Belgian labour-demand function. Environment and Planning A, 455-472. https://doi.org/10.1068/a070455
CLİFF, A. D., ve Ord, J. K. (1975). Model building and the analysis of spatial pattern in human geography. Journal of the Royal Statistical Society. Series B (Methodological), Cilt 37, Sayı 3, 297-348. https://doi.org/10.1111/j.2517- 6161.1975.tb01548.x
CLİFF, A., ve Ord, J. (1973). Spatial Autocorrelation. London: Pion. https://doi.org/10.1177/030913259501900205
CUARESMA, J. C., ve Feldkircher, M. (2013). Spatial filtering, model uncertainty and the speed of income convergence in Europa. Journal of Applied Econometrics, 28, 720-741. https://doi.org/10.1002/jae.2277
DEVARAJAN, S., Swaroop, V., ve Zou, H.-f. (1996). The composition of public expenditure and economic growth. Journal of Monetary Economics, 313-344. https://doi.org/10.1016/s0304-3932(96)90039-2
ELHORST, J. P. (2003). Specification and estimation of spatial panel data models. International Regional Science Review, 244-268. https://doi.org/10.1177/0160017603253791
ELHORST, J. P. (2014). Spatial Panel Data Models. Berlin: Springer.
ERTUR, C., Gallo, J. L., ve LeSage, J. (2005). Local versus global convergence in Europe: A Bayesian spatial econometric approach. The Review of Regional Studies, Vol. 37, No. 1, 82 – 108. https://doi.org/10.2139/ssrn.924626
FİSCHER, M. M., ve Wang, J. ( 2011). Spatial Data Analysis-Models, Methods and Techniques. Springer. https://doi.org/10.1007/978-3-642-21720-3
FÖLSTER, S., ve Henrekson, M. (2001). Growth effects of government expenditure and taxation in rich countries. European Economic Review, 1501-1520. https://doi.org/10.1016/s0014-2921(00)00083-0
GEARY, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, Cilt 5, Sayı 3, 115-146. https://doi.org/10.2307/2986645
HAİNİNG, R. (2003). Spatial Data Analysis - Theory and Practice. Cambridge University Press. https://doi.org/10.1017/cbo9780511754944
HASSAN, M. K., Sanchezb, B., ve Yuc, J.-S. (2011). Financial development and economic growth: new evidence from panel data. The Quarterly Review of Economics and Finance, 88-104. https://doi.org/10.1016/j.qref.2010.09.001
HAUSMAN, J. A. (1978). Specification tests in econometrics. Econometrica, 1251- 1271. https://doi.org/10.2307/1913827
HSİAO, C. (1986, 2014). Analysis of Panel Data. Cambridge University Press. https://doi.org/10.1017/cbo9781139839327
KAPOOR, M., Kelejian, H. H., ve Prucha, I. R. (2007). Panel data models with spatially correlated error components. Journal of Econometrics, 97-130. https://doi.org/10.1016/j.jeconom.2006.09.004
KEYNES, J. (1936). The General Theory of Employment, Interest and Money. Palgrave Macmillan. https://doi.org/10.1007/978-1-349-81807-5_4
KOLLURİ, B. R., Panik, M. J., ve Wahab, M. S. (2000). Government expenditure and economic growth: evidence from G7 countries. Applied Economics, 1059-1068. https://doi.org/10.1080/000368400322110
LANDAU, D. (1986). Government and economic growth in the less developed countries: an empirical study for 1960-1980. Economic Development and Cultural Change, 33-75. https://doi.org/10.1086/451572
LANDAU, D. L. (1985). Government expenditure and economic growth in the developed countries: 1952-76. Public Choice, 459-477. https://doi.org/10.1007/bf00182148
LEE, L.-F. (2002). Consistency and efficiency of least squares estimation for mixed regressive, spatial autoregressive models. Econometric Theory, Cilt 18, Sayı: 2, 252- 277. https://doi.org/10.1017/s0266466602182028
LESAGE, J. P. (1999). The Theory and Practice of Spatial Econometrics. Ohio: University of Toledo.
LOİZİDES, J., ve Vamvoukas, G. (2005). Goverment expenditure and economic growth: evidence from trivariate causality testing. Journal of Applied Economics, 125-152. https://doi.org/10.1080/15140326.2005.12040621
MORAN, P. (1948). The interpretation of statistical maps. Journal of the Royal Statistical Society. Series B (Methodological), Cilt 10, Sayı 2, 243-251. https://doi.org/10.1111/j.2517-6161.1948.tb00012.x
NİEBUHR, A. (2003). Spatial interaction and regional unemployment in Europe. European Journal of Spatial Development, 1-26.
PİNKSE, J., ve Slade, M. E. (1998). Contracting in space: An application of spatial statistics to discrete-choice models. Journal of Econometrics 85 , 125-154. https://doi.org/10.1016/s0304-4076(97)00097-3
ROMERO-ÁVİLA, D., ve Strauch, R. (2008). Public finances and long-term growth in Europe: Evidence from a panel data analysis. European Journal of Political Economy, 172-191. https://doi.org/10.1016/j.ejpoleco.2007.06.008
The World Bank. (2018, 04 27). http://databank.worldbank.org adresinden alınmıştır
TOBLER, W. R. (1970). A computer movie simulating urban growth in the Detroit Region. Economic Geography, 46, 234-340. https://doi.org/10.2307/143141
UZAY, N. (2002). Kamu büyüklüğü ve ekonomik büyüme üzerindeki etkileri: Türkiye örneği (1970-1999). Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 151-172.
WAGNER, A. (1886). Finanzwissenschaft. CF Winter. https://doi.org/10.2307/2139073
WOOLDRİDGE, J. M. (2001). Econometric Analysis of Cross Section and Panel Data. The MIT Press.
YILMAZ, Ö., ve Kaya, V. (2005). Kamu harcama çeşitleri ve ekonomik büyüme ilişkisi. SÜ İİBF Sosyal ve Ekonomik Araştırmalar Dergisi, 257-271.