Housing Loans and Domestic Credit in the Baltic States and Poland: Structural Breaks and Macroeconomic Determinants

• Autorzy: Scott W. Hegerty
• Języki publikacji: EN

Abstrakty

EN

Aim/purpose - This study examines the time-series properties of home loans and domestic credit in Poland and the three Baltic countries, first in the univariate sense by identifying structural breaks in the series, and then using a multivariate model to identify the key drivers of loan growth. Design/methodology/approach - Structural break tests are conducted using the method of Bai & Perron (1998), while orthgonalised VARs are used for the macroeconomic model. Findings - The Estonian and Lithuanian home lending growth series have structural breaks in 2007, preceding the onset of the 2008 Global Financial Crisis. Estonian home lending has two additional structural breaks in 2009 and 2013. Neither of the two Polish lending series has any break after the sample begins in 2009, indicating more stability in the country's markets. In the macroeconomic model, consumer price inflation and real effective exchange-rate appreciations have the largest influence on lending and credit growth, and Poland more affected than the Baltic countries. Research implications/limitations - This study opens the door to future research be-hind the specific causes of structural breaks in these series. While there is some evidence of an 'early warning' before the 2008 crisis, longer data series are needed for Poland and especially in the case of Latvia. Originality/value/contribution - This study offers insight into the lending markets in an area of the world that was significantly impacted by the 2008 crisis. Understanding the behaviour and causes of lending growth will help avoid future problems. (original abstract)

Słowa kluczowe

EN

Housing loan; Bank credit; Domestic banks; Time-series

PL

Kredyt mieszkaniowy; Kredyt bankowy; Banki krajowe; Szeregi czasowe

• Czasopismo: Journal of Economics & Management / University of Economics in Katowice
• Rocznik: 2020
• Numer: nr 42
• Strony: 48--69

Twórcy

autor

Scott W. Hegerty

• Northeastern Illinois University, Chicago, USA

Bibliografia

• Apostoaie, C.-M., Percic, S., Cocris. S., & Chirlesan. D. (2014). Research on the credit cycle and business cycle with a focus on ten states from Central, Eastern, and Southeastern Europe. Emerging Markets Finance & Trade, 50(4), 63-77. https:// doi.org/10.2753/REE1540-496X5004S404
• Aus, V., Kolbre, E., & Kahre, K. (2015). Drivers of Estonian housing market cycles. Research in Economics and Business: Central and Eastern Europe, 7(2). Retrieved from http://rebcee.eu/index.php/REB/article/view/79
• Bai, J. & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78. https://doi.org/10.2307/2998540
• Bank for International Settlements. (n.d.). Real and Nominal Broad Effective Exchange Rates, retrieved from FRED, Federal Reserve Bank of St. Louis. Retrieved from fred.stlouisfed.org
• Bank of Latvia Statistical Database. (n.d.). Retrieved from https://statdb.bank.lv/lb/
• Bank of Lithuania Statistical Database. (n.d.). Retrieved from https://www.lb.lt/lt/ statistikos-duomenu-baze-2
• Eesti Pank Statistics. (n.d.). Retrieved from https://www.eestipank.ee/en/statistics
• Hegerty, S. W. (2020). Do capital flows drive credit growth and consumption in Central and Eastern Europe? Post-Communist Economies, 31(1), 36-51. https://doi.org/ 10.1080/14631377.2018.1461516
• Henilane, I. (2016). Review of housing mortgage lending policy practices in Latvia. Journal of Business Management, 10, 59-69.
• Hoffmann, A. (2010). An overinvestment cycle in Central and Eastern Europe. Metroeconomica, 61(4), 711-734. https://doi.org/10.1111/j.1467-999X.2010.04103.x
• International Financial Statistics [IFS]. (n.d.). Country Tables [Data File]. Washington, D.C.: International Monetary Fund. Retrieved from data.imf.org
• Ivanauskas, F., Eidukevicius, R., Marcinskas, A. & Galiniene, B. (2008). Analysis of the housing market in Lithuania. International Journal of Strategic Property Management, 12(4), 271-280. https://10.3846/1648-715X.2008.12.271-280
• Korzeniowska, A. M. (2019). Sources of financing of household debt in Poland. Folia Oeconomica Stetinensia, 19(2), 56-67. https://doi.org/10.2478/foli-2019-0013
• Krusinskas, R. (2012). Research on housing bubbles in the capitals of the Baltic and Central Europe. Economics and Management, 17(2), 480-485. https://doi.org/ 10.5755/j01.em.17.2.2169
• Kulikauskas, D. (2016). Fundamental housing prices in the Baltic States: Empirical approach. Baltic Journal of Economics, 16(2), 53-80. https://doi.org/10.1080/ 1406099X.2016.1173446
• Lane, P. R., & Milesi-Ferretti, G. M. (2011). The cross-country incidence of the global crisis. IMF Economic Review, 59, 77-110. https://doi.org/10.1057/imfer.2010.12
• National Bank of Poland [NBP]. (n.d.). Statistics and indicators. Retrieved from https:// www.nbp.pl/home.aspx?f=/statystyka/statystyka.html
• Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. https://doi.org/10.2307/2336182
• Posedel, P. & Vizek, M. (2009). House price determinants in transition and EU-15 coun- tries. Post-Communist Economies, 21(3), 327-343. https://doi.org/10.1080/146313 70903090640
• Poskart, R. (2012). Changes in Poland's housing loan market in 2004-2010. Nauki o Finansach. Financial Sciences, 1(10), 97-115.
• Reichenbachas, T. (2017). Credit-related shocks in VAR models: The case of Lithuania. Ekonomika/Economics, 96(3), 7-19.
• Sax, C., & Eddelbuettel, D. (2018). Seasonal adjustment by X-13ARIMA-SEATS in R. Journal of Statistical Software, 87(11), 1-17. https://doi.org/10.18637/jss.v087.i11
• Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48, 1-48. https://doi.org/ 10.2307/1912017
• Skare, M., Sinković, D., & Porada-Rochoń, M. (2019). Measuring credit structure impact on economic growth in Croatia Using (VECM) 1990-2018. Journal of Business Economics and Management, 20(2), 294-310. https://doi.org/10.3846/JBEM. 2019.8344
• Zeileis, A., Leisch, F., Hornik, K., & Kleiber, C. (2002). strucchange: An R package for testing for structural change in linear regression models. Journal of Statistical Software, 7(2), 1-38. https://doi.org/10.18637/jss.v007.i02
• Zeileis, C., Kleiber, W. & Hornik, K. (2003). Testing and dating of structural changes in practice. Computational Statistics & Data Analysis, 44, 109-123. https:// doi.org/10.1016/S0167-9473(03)00030-6

Identyfikatory

DOI

doi.org/10.22367/jem.2020.42.03