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Sanayi Üretim Endeksi ve İlişkili Faktörlerin Vektör Otoregresyon Model Etki-Tepki Analizi Bağlamında Değerlendirilmesi

Year 2024, Volume: 58 Issue: 4, 681 - 690, 31.10.2024
https://doi.org/10.51551/verimlilik.1562851

Abstract

Amaç: Sanayi üretim endeksi ile ilgili literatür incelendiğinde sanayi üretim endeksini etkileyen faktörlerin birbirinden farklılaştığı görülmektedir. Çalışmanın amacı, makroekonomik göstergelerin ve borsa performansının Türkiye'nin sanayi üretim endeksi üzerindeki etkisini ampirik olarak analiz etmektir.
Yöntem: Çalışma, 2016:01 ile 2023:12 arasındaki dönemi kapsamaktadır. İncelenen makroekonomik değişkenler enflasyon, mevduat faiz oranı ve reel efektif döviz kuru ve ek olarak Borsa İstanbul 100 endeksidir. Değişkenlerin durağanlığını araştırmak için ADF testi kullanılmış ve vektör otoregresyon (VAR) metodolojisinin Etki-Tepki Analizi, makroekonomik değişkenler ile sanayi üretim endeksi üzerindeki borsa getirisi arasındaki ilişkiye uygulanmıştır. Amaçlanan, değişkenlerden birinde oluşan bir birimlik şokun diğer değişken üzerindeki etkisini ölçmektir.
Bulgular: Çalışma bulguları sanayi üretim endeksinin kendisinde ve diğer değişkenlerdeki birim şokluk değişimlerin etkisinin ortalama 2-4 dönem sonrasında sıfıra yakınsadığını göstermektedir. Sanayi üretim endeksinin reel efektif döviz kuru ve enflasyon oranına tepkisi farklı büyüklüklerde olsa da aynı patikayı izlemekte ancak mevduat faiz oranına tepkisi ise tam zıt yönlü olmaktadır.
Özgünlük: Elde edilen bulgulara göre, ilgili değişkenlerde oluşan değişimler 2-4 aylık dönemde etkisini yitirip sistem dengeye gelmektedir. Buna göre büyümenin öncü göstergesi olan sanayi üretim endeksine ilişkin oluşturulacak politikalarda takip edilecek ve etkilerinin yönüne göre dikkate alınacak değişkenler belirlenmiş olmakta ve uzun dönemli etkiler için diğer makroekonomik değişkenlerin araştırılması gerekliliği ortaya konmaktadır.

References

  • Amarasinghe, A. (2016). “A Study on the Impact of Industrial Production Index (IPI) to Beverage, Food and Tobacco Sector Index with Special Reference to Colombo Stock Exchange”, Procedia Food Science, 6, 275-278. DOI: 10.1016/J.PROFOO.2016.02.054
  • Banda, K., Hall, J. ve Pradhan, R. (2019). “The Impact of Macroeconomic Variables on Industrial Shares Listed on the Johannesburg Stock Exchange”, Macroeconomics and Finance in Emerging Market Economies, 12, 270-292.
  • Barışık, S. ve Yayar, R. (2012). “Sanayi Üretim Endeksini Etkileyen Faktörlerin Ekonometrik Analizi”, İktisat İşletme ve Finans, 27(316), 53-70. DOI: 10.3848/iif.2012.316.3342
  • Bodo, G., Golinelli, R. ve Parigi, G. (2000). “Forecasting Industrial Production in the Euro Area”, Empirical Economics, 25, 541-561. DOI: 10.1007/s001810000032.
  • Brunhes-Lesage, V. ve Darné, O. (2012). “Nowcasting the French Index of Industrial Production: A Comparison from Bridge and Factor Models”, Economic Modelling, 29, 2174-2182. DOI: 10.1016/J.ECONMOD.2012.04.011
  • Bruno, G. ve Lupi, C. (2003). “Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data”, ISAE Istituto di Studi e Analisi Economica. 1-22.
  • Chiang, T.C. ve Chen, X. (2017). “Stock Market Activities and Industrial Production Growth: Evidence from 20 International Markets”, Advances in Pasific Basin Business, Economics and Finance, 39-75. DOI: 10.1108/S2514- 465020170000001003
  • Chi-Kung, M. ve Shih, T. (1977). Lecture 5: Industrial Production Planning. Chinese Economy, 10, 15-26. DOI: 10.2753/CES1097-1475100315.
  • Ciubotariu, M. ve Avdei, S. (2018). “Production Activity - Important Rank of the State Economy”, European Journal of Accounting, Finance & Business, 104-114. DOI: 10.4316/ejafb.2018.629
  • Dickey, D.A. ve Fuller, W.A. (1979). "Distribution of the Estimators for Autoregressive Time Series with a Unit Root", Journal of the American Statistical Association, 74 (366), 427–431. DOI:10.1080/01621459.1979.1048253
  • Ejaz, M. ve Iqbal, J. (2021). “Estimation and Forecasting of Industrial Production Index”, The Lahore Journal Of Economics, 26(1), 1-30. DOI: 10.35536/lje.2021.v26.i1.a1
  • Enders, W. 2009. “Applied Econometric Time Series”, Wiley, New York. Frey, C. ve Mokinski, F. (2016). “Forecasting with Bayesian Vector Autoregressions Estimated Using Professional Forecasts”, Journal of Applied Econometrics, 31, 1083-1099. DOI: 10.1002/JAE.2483
  • Gerlach, H. (1988). “World Business Cycles under Fixed and Flexible Exchange Rates. Journal of Money”, Credit and Banking, 20, 621-632. DOI: 10.2307/1992288
  • Gholipour, H., Tajaddini, R., Farzanegan, M. ve Yam, S. (2021). “Responses of REITs Index and Commercial Property Prices to Economic Uncertainties: A VAR Analysis”, Research in International Business and Finance, 58, 101457. DOI: 10.1016/J.RIBAF.2021.101457
  • Gültekin H. ve Taştan B. (2022) “The Impact of Covid-19 and Inflation on the Industrial Production Index”, Journal of Economics and Administrative Sciences, 23(3), 790-799.
  • Giannone, D., Lenza, M. ve Primiceri, G. (2012). “Prior Selection for Vector Autoregressions”, Review of Economics and Statistics, 97, 436-451. DOI: 10.1162/REST_a_00483
  • Habibi, A. (2019). “Non-Linear Impact of Exchange Rate Changes on U.S. Industrial Production”, Journal of Economic Structures, 8, 1-17. DOI: 10.1186/s40008-019-0172-0
  • Karunadhika, S., Munasinghe, R. ve Dharmarathne, G. (2022). “A Dynamic Factor Approach to Forecasting the Index of Industrial Production of Sri Lanka”, 22nd International Conference on Advances in ICT for Emerging Regions (ICTer), 142-147. DOI: 10.1109/ICTer58063.2022.10024075
  • Kennedy, P. (2006). “Ekonometri Kılavuzu”, Gazi Kitabevi, Ankara.
  • Lippi, M. ve Reichlin, L. (1994). “VAR Analysis, Nonfundamental Representations, Blaschke Matrices”, Journal of Econometrics, 63, 307-325. DOI: 10.1016/0304-4076(93)01570-C
  • Pekçaglayan, B. (2021). “Türkiye’de Sanayi Üretim Endeksinin Belirleyenleri: ARDL Modeli”, İstanbul İktisat Dergisi - Istanbul Journal of Economics, 71(2), 435-456. DOI: 10.26650/ISTJECON2021-972114
  • Robertson, J. ve Tallman, E. (1999). “Vector Autoregressions: Forecasting and Reality”, Econometric Reviews, 84, 4-18.
  • T.C. Merkez Bankası Elektronik Veri Dağıtım Sistemi (2024). https://evds2.tcmb.gov.tr/, (Erişim Tarihi: 30.06.2024)
  • TÜİK. (2024). “Sanayi Üretim Endeksi, Haziran 2024”, https://data.tuik.gov.tr/Bulten/Index?p=Sanayi-%C3%9Cretim-Endeksi-Haziran-2024-53775&dil=1, (Erişim Tarihi: 30.06.2024).

Evaluation of Industrial Production Index and Related Factors in the Context of Vector Autoregression Model Impulse-Response Analysis

Year 2024, Volume: 58 Issue: 4, 681 - 690, 31.10.2024
https://doi.org/10.51551/verimlilik.1562851

Abstract

Purpose: When the literature on the industrial production index is examined, it is seen that the factors affecting the industrial production index differ from each other. The aim of the study is to empirically analyze the effect of macroeconomic indicators and stock market performance on Turkey's industrial production index.
Methodology: The study covers the period between 2016:01 and 2023:12. The macroeconomic variables examined are inflation, deposit interest rate and real effective exchange rate, and additionally Borsa Istanbul 100 index. ADF test was used to investigate the stationarity of the variables and the Impulse-Response Analysis of the vector otoregressions (VAR) methodology was applied to the relationship between macroeconomic variables and stock market returns on the industrial production index. The aim is to measure the impact of a unit shock in one of the variables on the other variable.
Findings: The findings of the study show that the impact of unit shock changes in the industrial production index itself and other variables does not converge to zero after 2-4 periods on average. The response of the industrial production index to the real effective exchange rate and inflation rate, although in different magnitudes, follows the same path, but its response to the deposit interest rate is in the exact opposite direction.
Originality: Changes in the relevant variables disappear in the 2-4-month interval and the system balance is formed. Accordingly, the variables to be followed in the policies to be formed regarding the regulation of industrial production, which is an indicator of growth, and the variables to be monitored according to the perspective of their effects are determined and the certainty of other macroeconomic variables for long-term effects is revealed.

References

  • Amarasinghe, A. (2016). “A Study on the Impact of Industrial Production Index (IPI) to Beverage, Food and Tobacco Sector Index with Special Reference to Colombo Stock Exchange”, Procedia Food Science, 6, 275-278. DOI: 10.1016/J.PROFOO.2016.02.054
  • Banda, K., Hall, J. ve Pradhan, R. (2019). “The Impact of Macroeconomic Variables on Industrial Shares Listed on the Johannesburg Stock Exchange”, Macroeconomics and Finance in Emerging Market Economies, 12, 270-292.
  • Barışık, S. ve Yayar, R. (2012). “Sanayi Üretim Endeksini Etkileyen Faktörlerin Ekonometrik Analizi”, İktisat İşletme ve Finans, 27(316), 53-70. DOI: 10.3848/iif.2012.316.3342
  • Bodo, G., Golinelli, R. ve Parigi, G. (2000). “Forecasting Industrial Production in the Euro Area”, Empirical Economics, 25, 541-561. DOI: 10.1007/s001810000032.
  • Brunhes-Lesage, V. ve Darné, O. (2012). “Nowcasting the French Index of Industrial Production: A Comparison from Bridge and Factor Models”, Economic Modelling, 29, 2174-2182. DOI: 10.1016/J.ECONMOD.2012.04.011
  • Bruno, G. ve Lupi, C. (2003). “Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data”, ISAE Istituto di Studi e Analisi Economica. 1-22.
  • Chiang, T.C. ve Chen, X. (2017). “Stock Market Activities and Industrial Production Growth: Evidence from 20 International Markets”, Advances in Pasific Basin Business, Economics and Finance, 39-75. DOI: 10.1108/S2514- 465020170000001003
  • Chi-Kung, M. ve Shih, T. (1977). Lecture 5: Industrial Production Planning. Chinese Economy, 10, 15-26. DOI: 10.2753/CES1097-1475100315.
  • Ciubotariu, M. ve Avdei, S. (2018). “Production Activity - Important Rank of the State Economy”, European Journal of Accounting, Finance & Business, 104-114. DOI: 10.4316/ejafb.2018.629
  • Dickey, D.A. ve Fuller, W.A. (1979). "Distribution of the Estimators for Autoregressive Time Series with a Unit Root", Journal of the American Statistical Association, 74 (366), 427–431. DOI:10.1080/01621459.1979.1048253
  • Ejaz, M. ve Iqbal, J. (2021). “Estimation and Forecasting of Industrial Production Index”, The Lahore Journal Of Economics, 26(1), 1-30. DOI: 10.35536/lje.2021.v26.i1.a1
  • Enders, W. 2009. “Applied Econometric Time Series”, Wiley, New York. Frey, C. ve Mokinski, F. (2016). “Forecasting with Bayesian Vector Autoregressions Estimated Using Professional Forecasts”, Journal of Applied Econometrics, 31, 1083-1099. DOI: 10.1002/JAE.2483
  • Gerlach, H. (1988). “World Business Cycles under Fixed and Flexible Exchange Rates. Journal of Money”, Credit and Banking, 20, 621-632. DOI: 10.2307/1992288
  • Gholipour, H., Tajaddini, R., Farzanegan, M. ve Yam, S. (2021). “Responses of REITs Index and Commercial Property Prices to Economic Uncertainties: A VAR Analysis”, Research in International Business and Finance, 58, 101457. DOI: 10.1016/J.RIBAF.2021.101457
  • Gültekin H. ve Taştan B. (2022) “The Impact of Covid-19 and Inflation on the Industrial Production Index”, Journal of Economics and Administrative Sciences, 23(3), 790-799.
  • Giannone, D., Lenza, M. ve Primiceri, G. (2012). “Prior Selection for Vector Autoregressions”, Review of Economics and Statistics, 97, 436-451. DOI: 10.1162/REST_a_00483
  • Habibi, A. (2019). “Non-Linear Impact of Exchange Rate Changes on U.S. Industrial Production”, Journal of Economic Structures, 8, 1-17. DOI: 10.1186/s40008-019-0172-0
  • Karunadhika, S., Munasinghe, R. ve Dharmarathne, G. (2022). “A Dynamic Factor Approach to Forecasting the Index of Industrial Production of Sri Lanka”, 22nd International Conference on Advances in ICT for Emerging Regions (ICTer), 142-147. DOI: 10.1109/ICTer58063.2022.10024075
  • Kennedy, P. (2006). “Ekonometri Kılavuzu”, Gazi Kitabevi, Ankara.
  • Lippi, M. ve Reichlin, L. (1994). “VAR Analysis, Nonfundamental Representations, Blaschke Matrices”, Journal of Econometrics, 63, 307-325. DOI: 10.1016/0304-4076(93)01570-C
  • Pekçaglayan, B. (2021). “Türkiye’de Sanayi Üretim Endeksinin Belirleyenleri: ARDL Modeli”, İstanbul İktisat Dergisi - Istanbul Journal of Economics, 71(2), 435-456. DOI: 10.26650/ISTJECON2021-972114
  • Robertson, J. ve Tallman, E. (1999). “Vector Autoregressions: Forecasting and Reality”, Econometric Reviews, 84, 4-18.
  • T.C. Merkez Bankası Elektronik Veri Dağıtım Sistemi (2024). https://evds2.tcmb.gov.tr/, (Erişim Tarihi: 30.06.2024)
  • TÜİK. (2024). “Sanayi Üretim Endeksi, Haziran 2024”, https://data.tuik.gov.tr/Bulten/Index?p=Sanayi-%C3%9Cretim-Endeksi-Haziran-2024-53775&dil=1, (Erişim Tarihi: 30.06.2024).
There are 24 citations in total.

Details

Primary Language Turkish
Subjects Public Economy, Applied Economics (Other)
Journal Section Araştırma Makalesi
Authors

Ayşegül Ak 0000-0003-1434-3103

Publication Date October 31, 2024
Submission Date October 7, 2024
Acceptance Date October 28, 2024
Published in Issue Year 2024 Volume: 58 Issue: 4

Cite

APA Ak, A. (2024). Sanayi Üretim Endeksi ve İlişkili Faktörlerin Vektör Otoregresyon Model Etki-Tepki Analizi Bağlamında Değerlendirilmesi. Verimlilik Dergisi, 58(4), 681-690. https://doi.org/10.51551/verimlilik.1562851

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