Measuring the Macroeconomic Impact Of Economic Diplomacy Using VARFIMA Model for Croatia 1990-2018

• Autorzy: Marinko Škare , Dubravko Radošević , Sanja Radolović
• Języki publikacji: EN

Abstrakty

EN

Solving economic issues in international relations has historically become an inseparable part of diplomatic theory and practice. The consequence of the latest speed-up in trade globalization and liberalization is the increased competition on both domestic and foreign markets. Thus, the states which do not have a built-up concept of economic diplomacy cannot have a proactive role in their relationship with other countries, but become the object of other countries' economic diplomacies. Given the importance of economic diplomacy's action in solving economic issues in international relations, we empirically measure its impact on the most important macroeconomic indicators in the Republic of Croatia by means of applying the MLE (maximum likelihood estimation) method. As the primary macroeconomic aggregates are by their nature fractionally integrated, this assumption was the threshold for applying the empirical VARFIMA model based on fractionally integrated data. The primary dependent variables in the VARFIMA model were different macroeconomic indicators - industrial production, unemployment, inflation, export. We find a positive link between economic diplomacy and macroeconomic performance of Croatia during 1990-2018. (original abstract)

Słowa kluczowe

PL

Dyplomacja; Modelowanie makroekonomiczne gospodarki; Międzynarodowe stosunki gospodarcze

EN

Diplomacy; Macroeconomic modelling of economy; International economic relations

• Czasopismo: Economics & Sociology
• Rocznik: 2020
• Tom: 13
• Numer: nr 3
• Strony: 230-243

Twórcy

autor

Marinko Škare

• University of Pula, Pula, Croatia

autor

Dubravko Radošević

• Economic Institute, Zagreb Zagreb, Croatia

autor

Sanja Radolović

• University of Pula, Pula, Croatia

Bibliografia

• Awad, A. (2020). Foreign direct investment inflows to Malaysia: Do macroeconomic policies matter? Journal of International Studies, 13(1), 196-211. doi:10.14254/2071-8330.2020/13-1/13
• Bergeijk, P.A.G. van, & Kloosterhuis, E.J. (2005). Modelling European Mergers: Theory, Competition Policy and Case Studies. Cheltenham: Edward Elgar.
• Bergeijk, P.A.G. van (2009). Economic Diplomacy and the Geography of International Trade. Cheltenham: Edward Elgar.
• Bilan Y., Mishchuk, H., Roshchyk, I., & Kmecova I. (2020). Analysis of Intellectual Potential and its Impact on the Social and Economic Development of European Countries. Journal of Competitiveness, 1, 22-38. https://doi.org/10.7441/joc.2020.01.02
• Box, G. E. P., and D. A. Pierce (1970). The distribution of residual causations in autoregressiveintegrated moving average time series models, Journal of the American Statistical Association, 65, 1509-26.
• Box-Steffensmeier, Janet M., and A R. Tomlinson (2000). Fractional Integration Methods in Political Science. Electoral Studies, (19), 63-76.
• Buturac, G., Mikulić, D. & Palić, P. (2019). Sources of export growth and development of manufacturing industry: empirical evidence from Croatia, Economic ResearchEkonomska Istraživanja, 32(1), 101-127, https://doi.org/10.1080/1331677X.2018.1550003
• Chi-Wei, S., Song, Y., Tao, R., & Hao L.H. (2019). Does political conflict affect bilateral trade or vice versa? Evidence from Sino-U.S. relations, Economic Research-Ekonomska Istraživanja, https://doi.org/10.1080/1331677X.2019.1694559
• Clarke, H.D., Lebo, M. (2003), Fractional (co)integration and government party support in Britain. British Journal of Political Science 33, 283- 301
• Croatian statistical office. (2019). Accessed in January 2019. www.dzs.hr
• Croatian national parliament. (2019). accessed in January 2019, https://www.sabor.hr/en/home
• Dickey, D.A., and W.A. Fuller (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root, Journal of the American Statistical Association 74, 427-431
• Dueker, M., and Startz, R. (1997). Maximum-likelihood estimation of fractional cointegration with application to the short end of the yield curve, Working Papers 1994-027, Federal Reserve Bank of St. Louis.
• Dueker, M., and Startz, R. (1998). Maximum-Likelihood Estimation of Fractional Cointegration with an Application to U.S. and Canadian Bond Rates. The Review of Economics and Statistics 420-26.
• Durr, R.H., Gilmour, J.B., & Wolbrecht, C. (1997). Explaining congressional approval. Electoral Studies 19, 63-76.
• Elliott, G., T. J. Rothenberg, and J. H. Stock (1996). Efficient tests for an autoregressive unit root. Econometrica 64(4), 813-836.
• Eurostat. (2019). Accessed in January 2019, https://ec.europa.eu/eurostat/home.
• Geweke, J., and S. Porter-Hudak (1983). The estimation and application of long-memory time series models. Journal of Time Series Analysis 4, 221-237.
• Giraitis, L, Kokoszka, P., Leipus, R., and Teyssière, G. (2003). Rescaled variance and related tests for long memory in volatility and levels, Journal of Econometrics 112, 265-294.
• Grossman, Gene M. i E. Helpman (1991). Innovation and Growth in the Global Economy. Cambridge, Mass.: The M.I.T. Press
• Hadri, K. (2000). Testing for stationarity in heterogeneous panel data, The Econometrics Journal 3(2), 148-161.
• Hair Jr., J., Black W. , Barry J. Babin, R. E. Anderson (2009). Multivariate Data Analysis (7th Edition), Prentice-Hall.
• Harris, D, B. McCabe and S. Leybourne (2008). Testing for long memory. Econometric Theory 24(1), 143-175.
• Harold, D. Clarke, and Lebo, M. (2003). Fractional (Co)integration and Governing Party Support in Britain. British Journal of Political Science 33(2), 283-301.
• Havrylyshyn, O., and van Rooden, R. (2003). Institutions Matter in Transition, but so do Policies. Comparative Economic Studies, 55, 2-24.
• Im, Pesaran i Shin (2003). Testing for Unit Roots in Heterogeneous Panels, Journal of Econometrics, 115, 53-74.
• Jaworski, J., & Czerwonka, L. (2019). Meta-study on the relationship between macroeconomic and institutional environment and internal determinants of enterprises' capital structure, Economic Research-Ekonomska Istraživanja, 32(1), 2614-2637, https://doi.org/10.1080/1331677X.2019.1650653
• Levin, A., C. F. Lin, and C. Chu (2002). Unit Root Tests in Panel Data: Asymptotic and FiniteSample Properties, Journal of Econometrics, 108, 1-24
• Lo, Andrew W. (1991). Long-term memory in stock market prices, Econometrica 59(5), 1279-1313.
• Maddala, G.S., and Wu, S. (1999). A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test, Oxford Bulletin of Economics and Statistics, vol.61, 631-652.
• Moulines, E., and P. Soulier (1999). Broadband log-periodogram estimation of time series with long-range dependence. Annals of Statistics 27, 1415-1439
• Moons, S.J.V., & van Bergeijk, P.A.G. (2013). A meta-analysis of economic diplomacy and its effect on international economic flows, I.S.S. Working Papers - General Series 50074, International Institute of Social Studies of Erasmus University Rotterdam (I.S.S.), The Hague.
• Okuneviciute Neverauskiene, L., & Rakauskiene, O. G. (2018). Identification of employment increasing possibilities in the context of the EU socioeconomic environment evaluation: The case of Lithuania. Economics and Sociology, 11(4), 51- 68. doi:10.14254/2071-789X.2018/11-4/3
• Peres, M., Ameer, W., & Xu, H. (2018). The impact of institutional quality on foreign direct investment inflows: evidence for developed and developing countries, Economic Research-Ekonomska Istraživanja, 31(1), 626-644, https://doi.org/10.1080/1331677X.2018.1438906
• Phillips, P. C. B., and P. Perron (1988). Testing for a unit root in time series regression, Biometrika 75, 335-346
• Rana, K. S. (2002),.Bilateral Diplomacy, DiploProjects, Mediterranean Academy of Diplomatic Studies, Malta
• Rana, K. S. (2000), Inside Diplomacy, Chapter 4, Manas, New Delhi
• Robinson, P. M. (1994). Semiparametric analysis of long memory time series, Annals of Statistics 22(1), 515-539.
• Robinson, P. M. (1995). Log-periodogram regression of time series with long-range dependence, Annals of Statistics 23, 1048-1072.
• Robinson, P. M. (1995b). Gaussian semiparametric estimation of long-range dependence, Annals of Statistics 23, 1630-1661.
• Robinson, P. M., and I. N. Lobato (1998). A nonparametric test for I(0), Review of Economic Studies 65(3), 475-495.
• Rose, A.K. (2007). The foreign service and foreign trade: embassies as export promotion, World Economy 30, 22-38,
• Ruëll, H., and Zuidema, L. (2012). The Effectiveness of Commercial Diplomacy. A Survey Among Dutch Embassies and Consulates. Discussion Paper in Diplomacy. Netherlands Institute for International Relations Clingendael.
• Said, E. S., and D. A. Dickey (1984). Testing for unit roots in autoregressive-moving average models of unknown order, Biometrika 71, 599-607.
• Schlotzhauer, S. (2007). Elementary Statistics Using JMP, International Statistical Review 75(3), 409-438.
• Sowell, E. (1989). Effects of manipulative materials in mathematics instruction, Journal for Research in Mathematics Education, 20, 498-505.
• Sowell, F. (1992). Maximum likelihood estimation of stationary univariate fractionally integrated time series models, Journal of Econometrics 53, 165-188.
• Tsay, W.J. (2010a). Maximum likelihood estimation of stationary multivariate ARFIMA processes, Journal of Statistical Computation and Simulation 80, 729-745.
• Tsay, W.J. (2010b). The long memory autoregressive distributed lag model and its application on congressional approval, Electoral Studies 29, 128-143.
• Tsay, W. J. (2012). Maximum likelihood estimation of structural VARFIMA models, Electoral Studies, 31(4), 852-860.
• Yakop, M., and Bergeijk, P. (2009). The weight of economic and commercial diplomacy, Working Paper International Institute of Social Studies, No. 478, The Hague: International Institute of Social Studies.

Identyfikatory

DOI

10.14254/2071-789X.2020/13-3/14