Lozano Navarro, Francisco-Javier (2018): Efecto de las condiciones financieras sobre el desempeño del sector Construcción. Published in: Working Papers No. 102 (1 November 2018)
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Abstract
The credit channel mechanism of monetary policy describes how a central bank’s policy changes affect the credit strategies of private banks. This has a direct effect on the amount of credit that banks issue to firms and consumers, which in turn affects the aggregated demand, employment and inflation. This paper tests the hypothesis that financial conditions relative to the construction sector, according to the Senior Loan Officers Survey, are capable of foreseeing changes in sectoral activity. Indeed, as shown in several international studies, supply and demand standards for mortgages, real-estate and construction credits have predictive power over credit changes, sectoral activity and housing supply and demand.
Item Type: | MPRA Paper |
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Original Title: | Efecto de las condiciones financieras sobre el desempeño del sector Construcción |
English Title: | Effect of financial conditions on the performance of the Construction sector |
Language: | Spanish |
Keywords: | credit, bank lending survey, housing, real estate, construction |
Subjects: | G - Financial Economics > G0 - General R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R0 - General |
Item ID: | 118261 |
Depositing User: | Francisco-Javier Lozano Navarro |
Date Deposited: | 18 Sep 2023 07:37 |
Last Modified: | 18 Sep 2023 07:37 |
References: | Alfaro, R.; Pacheco, D.; Sagner, A. (2013). Dinámica de la frecuencia de impago de los créditos de consumo en cuotas. El Trimestre Económico, Vol. LXXX (2), Núm. 318, abril-junio de 2013, pp. 329-343. Andrews, B. H.; Dean, M. D.; Swain, R.; Cole, C. (2013). Building ARIMA and ARIMAX models for predicting long-term disability benefit application rates in the public/private sectors. Society of Actuaries. Bánbura, M.; Giannone, D.; Reichlin, L. (2010). Large Bayesian Vector Auto Regressions. Journal of Applied Econometrics, Vol. 25, No. 1, pp. 71–92. Barajas, A.; Luna, L.; Restrepo, J. E. (2006). Fluctuaciones macroeconómicas y comportamiento de los bancos en Chile. Informe de Estabilidad Financiera Segundo Semestre 2016, Banco Central de Chile. Beer, C.; Waschiczek, W. (2012). Analyzing Corporate Loan Growth in Austria Using Bank Lending Survey Data. Monetary Policy & the Economy, (2), 61-80. Bell, V.; Pugh, A. (2014). The Bank of England Credit Conditions Survey (No. 515). Bank of England. Blaes, B. (2011). Bank-related loan supply factors during the crisis: An analysis based on the German bank lending survey (No. 2011, 31). Discussion Paper Series 1: Economic Studies. Box, G.; Jenkins, G. (1970). Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco. Box, G. E.; Tiao, G. C. (1975). Intervention analysis with applications to economic and environmental problems. Journal of the American Statistical association, 70(349), 70-79. Canova, F. (2007). Methods for Applied Macroeconomic Research. Princeton University Press. Cappiello, L.; Kadareja, A.; Kok, C.; Protopapa, M. (2010). Do bank loans and credit standards have an effect on output? A panel approach for the euro area (No. 1150). ECB Working Paper. Chava, S.; Park, H.; Gallmeyer, M. F. (2010). Credit conditions and expected stock returns. Working paper, Georgia Institute of Technology. Ciccarelli, M.; Rebucci, A. (2003). Bayesian VARs: A Survey of the Recent Literature with an Application to the European Monetary System. Working Paper WP/03/102, International Monetary Fund. Cools, M.; Moons, E.; Wets, G. (2009). Investigating the Variability in Daily Traffic Counts Using ARIMAX and SARIMA (X) Models: Assessing the Impact of Holidays on Two Divergent Site Locations. In TRB 88th Annual Meeting Compendium of Papers DVD. Cunningham, T. J. (2006). The predictive power of the Senior Loan Officer Survey: do lending officers know anything special? (No. 2006-24). Federal Reserve Bank of Atlanta. Dagum, E. B.; Bianconcini, S. (2016). Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation. Springer International Publishing. de Bondt, G.; Maddaloni, A.; Peydro, J. L.; Scopel, S. (2010). The euro area Bank Lending Survey matters: empirical evidence for credit and output growth (No. 1160). European Central Bank. De Gregorio, J. (2009). La política monetaria y su traspaso a las tasas de interés. Presentación en la Cámara de Diputados, 16 de marzo de 2009. Del Giovane, P. D.; Eramo, G.; Nobili, A. (2010). Disentangling demand and supply in credit developments: a survey-based analysis for Italy (No. 764). Bank of Italy, Economic Research and International Relations Area. Durka, P.; Pastorekova, S. (2012). ARIMA vs. ARIMAX – which approach is better to analyze and forecast macroeconomic time series? Proceedings of 30th International Conference Mathematical Methods in Economics. EViews (2018). EViews 10 Help Topics: Bayesian VAR. Recuperado de http://www.eviews.com/help/helpintro.html#page/content/VAR-Bayesian_VAR.html. Fondo Monetario Internacional (2018). Quarterly National Accounts Manual, 2017 Edition. Departamento de Estadísticas, Fondo Monetario Internacional, Washington D.C. Gallardo, M.; Rubio, H. (2009). Diagnósticos de estacionalidad con X-12-ARIMA. Estudios Económicos Estadísticos Nº 76, Banco Central de Chile. García, C. J.; Sagner, A. (2013). Ciclo económico, riesgo y costo del crédito en Chile desde una perspectiva de modelos VAR estructurales. Economía Chilena, Volumen 16, Nº 1, abril 2013, pp. 64-99. García, P. (2014). A quince años de las metas de inflación en Chile. Documentos de Política Económica, Nº 48, Mayo 2014. Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, Vol. 37, No. 3 (Aug. 1969), pp 424-438. Guichard, S.; Haugh, D.; Turner, D. (2009). Quantifying the Effect of Financial Conditions in the Euro Area, Japan, United Kingdom and United States (No. 677). OECD Publishing. Hempell, H. S.; Kok, C. (2010). The impact of supply constraints on bank lending in the euro area-crisis induced crunching? (No. 1262). European Central Bank. Hill, R. C.; Griffiths, W. E.; Lim, G. C. (2008). Principles of Econometrics. Third Edition. John Wiley & Sons Inc. Jara, A.; Martínez, J. F.; Oda, D. (2017). Bank’s Lending Growth in Chile: The Role of the Senior Loan Officers Survey (No. 802). Central Bank of Chile. Jara, A.; Silva, C. G. (2007). Metodología de la Encuesta sobre Condiciones Generales y Estándares en el Mercado de Crédito Bancario. Estudios Económicos Estadísticos Nº 57, Banco Central de Chile. Jaramillo, P.; Ormazábal, F.; Villatoro, F. (2009). Traspaso de Tasas de Interés en la Banca Chilena: Evidencia a Nivel Micro. Nota Técnica, Departamento de Estudios, Superintendencia de Bancos e Instituciones Financieras. Kaufmann, S.; Scharler, J. (2013). Bank-lending standards, loan growth and the business cycle in the Euro area (No. 2013-34). Working Papers in Economics and Statistics. Keller, E. (2007). Classical and Bayesian Methods for the VAR Analysis: International Comparisons. Rivista di Politica Economica, Vol. 97, No. 6, pp. 149–202. Kongcharoen, C.; Kruangpradit, T. (2013). Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) Model for Thailand Export. Conference: the 33rd International Symposium on Forecasting, Seoul. Lacroix, R.; Montornès, J. (2009). Analysis of the scope of the results of the bank lending survey in relation to credit data. Quarterly selection of articles-Bulletin de la Banque de France, (16), 33-51. Litterman, R. B. (1979). Techniques of Forecasting Using Vector Autoregressions. Working Paper 115, Federal Reserve Bank of Minneapolis. Lown, C.; Morgan, D. P. (2006). The credit cycle and the business cycle: new findings using the loan officer opinion survey. Journal of Money, Credit and Banking, 1575-1597. Lozano, F. J. (2014). La importancia de la competencia financiera y los estándares de aprobación de créditos hipotecarios para la vivienda. Revista En Concreto, Volumen 12, Núm. 135, junio 2014, p. 96. Lozano, F. J. (2015). Elasticidad precio de la oferta inmobiliaria en el Gran Santiago. Documento de Trabajo Nº 80, Cámara Chilena de la Construcción. Lozano, F. J. (2018). Estimación del equilibrio del mercado inmobiliario. Documento de Trabajo Nº 91, Cámara Chilena de la Construcción. Piguillem, J. F. (2004). Un indicador mensual de la actividad de la construcción. Documento de Trabajo Nº 20, Cámara Chilena de la Construcción. Pintaric, M. (2016). What is the Effect of Credit Standards and Credit Demand on Loan Growth? Evidence from the Croatian Bank Lending Survey. Comparative Economic Studies, 58, Issue 3, pp. 335-358. Schreft, S. L.; Owens, R. E. (1991). Survey evidence of tighter credit conditions: what does it mean? Federal Reserve Bank of Richmond Working Paper Nº 91-5. Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, Vol. 48, No. 1, pp. 1-47. Stock, J. H.; Watson, M. W. (2003). Introduction to Econometrics. Addison Wesley. Todd, R. M. (1988). Implementing Bayesian Vector Autoregressions. Working Paper 384, Federal Reserve Bank of Minneapolis. Walsh, G. (2016). BVAR Hyper-parameter Selection using EViews (Part 1). Artículo Linkedin, recuperado de https://www.linkedin.com/pulse/bvar-hyper-parameter-selection-using-eviews-graeme-walsh/. Wosko, Z. (2016). Determinants of credit in the Polish banking sector before and after the GFC according to information from the NBP Senior Loan Officer Survey. Does supply or demand matter? IFC Bulletin 603. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/118261 |