Auswahl der wissenschaftlichen Literatur zum Thema „Foreign exchange rates – Ethiopia“

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Zeitschriftenartikel zum Thema "Foreign exchange rates – Ethiopia"

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Rao, Nandeeswara, und TassewDufera Tolcha. „DETERMINANTS OF REAL EXCHANGE RATE IN ETHIOPIA“. International Journal of Research -GRANTHAALAYAH 4, Nr. 6 (30.06.2016): 183–210. http://dx.doi.org/10.29121/granthaalayah.v4.i6.2016.2652.

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Real exchange rate has direct effects on trade particularly on international trade and has indirect effects on productions and employments, so it is crucial to understand the factors which determine its variations. This study analyses the main determinants of the real exchange rate and the dynamic adjustment of the real exchange rate following shocks to those determinants using yearly Ethiopian time series data covering the period 1971 to 2010. It begins with a review of literatures on Exchange rate, real exchange rate, determinants of the real exchange rate and provides an updated background on the exchange rate system in Ethiopia. An empirical model linking the real exchange rate to its theoretical determinants is then specified. This study had employed the cointegration and vector autoregression (VAR) analysis with impulse response and variance decomposition analyses to provide robust long run effects and short run dynamic effects on the real exchange rate. Share of investment, foreign exchange reserve, capital inflow and government consumption of non-tradable goods were the variable that have been found to have a long run relationship with the real exchange rate. The estimate of the speed of adjustment coefficient found in this study indicates that about a third of the variation in the real exchange rate from its equilibrium level is corrected within a year. The regression result of VECM reveals that terms of trade, nominal exchange rate, and one period lag of capital flow were the variables significantly affects the real exchange rate in the short run. However, the impulse response and variance decomposition analysis shows a better picture of the short run dynamics. The their analysis provided evidence that the Shocks to terms of trade, nominal exchange rate, capital inflow and share of investment have persistent effects on the real exchange rate in the short run. In general the regression results of both long run and short run models mostly suggest that the fluctuations of real exchange rates are predominantly responses to monetary policies shocks rather than fiscal policy shocks.
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Dube, Ahmed, Burhan Ozkan und Ramu Govindasamy. „Analyzing the Export Performance of the Horticultural Sub-Sector in Ethiopia: ARDL Bound Test Cointegration Analysis“. Horticulturae 4, Nr. 4 (16.10.2018): 34. http://dx.doi.org/10.3390/horticulturae4040034.

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High dependency on traditional primary agricultural commodities and recurrent world market price fluctuations had exposed Ethiopia to foreign earnings instability. To reduce the high dependence on primary agricultural commodities and the associated vulnerability of negative price declines, diversification of trade from primary agricultural commodities into high-value horticultural commodities has attracted the attention of policy makers. The developments made in this area have brought the sector to the position of fifth largest foreign revenue generator for the country. However, given the comparative advantage in marketing and the potential to achieve trade gains that the country possesses, the benefit from the horticultural sub-sector is far below its potential. In this regard, knowledge of the determinants of the industry’s development is very important. So far, no attempt was made to examine factors influencing the export performance of the sector, taking the long period performance of the sector into consideration. Consequently, this study was proposed to examine the factors that have influenced the horticultural export performance of Ethiopia for the period from 1985–2016. Secondary data collected from National Bank of Ethiopia, Ethiopia Horticulture Producer Exporter Association, Ministry of Agriculture of Ethiopia, FAOSTAT, UNCTAD, and the World Bank were used in this study. The short-run and long-run relationships among the series were investigated using the autoregressive-distributed lag (ARDL) bound test cointegration approach. The model result of the Error Correction Model (ECM (-1)) was revealed as negative and significant, whereby it confirmed the existence of cointegration among the series. Its coefficient value was 0.472, which showed 47% of the adjustment will be made in the first year and it will return to its long-run equilibrium after 2.12 years. The model results also showed that the real effective exchange rate, the real GDP of Ethiopia, foreign direct investment (FDI), prices, and the structural break had significantly influenced the horticultural export performance both in the short-run and the long-run. Foreign GDP and real interest rates were revealed significant only in the long-run. Finally, important policy measures deemed to improve the horticultural export performance of Ethiopia were recommended.
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Havenner, Arthur, und Bagher Modjtahedi. „Foreign exchange rates“. Journal of Econometrics 37, Nr. 2 (Februar 1988): 251–64. http://dx.doi.org/10.1016/0304-4076(88)90005-x.

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Nathani, Navita, Jaspreet Kaur und Pooja Shrivas. „Dynamics of Foreign Exchange Rates“. Prestige International Journal of Management & IT - Sanchayan 04, Nr. 02 (15.12.2015): 35–58. http://dx.doi.org/10.37922/pijmit.2015.v04i02.002.

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van de Gucht, Linda M., Marnik G. Dekimpe und Chuck C. Y. Kwok. „Persistence in foreign exchange rates“. Journal of International Money and Finance 15, Nr. 2 (April 1996): 191–220. http://dx.doi.org/10.1016/0261-5606(96)00001-0.

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JÜTTNER, D. JOHANNES, und BERND P. LUEDECKE. „Interest Rates, Exchange Rates and Foreign Debt“. Economic Record 67, Nr. 2 (Juni 1991): 139–46. http://dx.doi.org/10.1111/j.1475-4932.1991.tb02537.x.

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Sideris, Dimitrios A. „Foreign exchange intervention and equilibrium real exchange rates“. Journal of International Financial Markets, Institutions and Money 18, Nr. 4 (Oktober 2008): 344–57. http://dx.doi.org/10.1016/j.intfin.2007.04.001.

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LOWE, PHILIP, und ALISON TARDITI. „Interest Rates, Exchange Rates and Foreign Debt: Comment*“. Economic Record 69, Nr. 1 (März 1993): 77–79. http://dx.doi.org/10.1111/j.1475-4932.1993.tb01800.x.

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JÜTTNER, D. JOHANNES. „Interest Rates, Exchange Rates and Foreign Debt: Rejoinder“. Economic Record 69, Nr. 1 (März 1993): 80–81. http://dx.doi.org/10.1111/j.1475-4932.1993.tb01801.x.

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Cheung, Yin-Wong. „Long Memory in Foreign-Exchange Rates“. Journal of Business & Economic Statistics 11, Nr. 1 (Januar 1993): 93. http://dx.doi.org/10.2307/1391309.

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Dissertationen zum Thema "Foreign exchange rates – Ethiopia"

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Chen, Ruo. „Essays on exchange rates“. Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1481668671&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Liu, Kit-ying Ida. „Empirical exchange rate models : out-of-sample forecasts for the HK$/Yen exchange rate /“. Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20666895.

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Gau, Yin-Feng. „Heteroskedastic volatility of foreign exchange rates /“. Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1997. http://wwwlib.umi.com/cr/ucsd/fullcit?p9804526.

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Kim, Chung-Han. „Empirical studies of real exchange rates : heteroskedasticity, cross exchange rate correlation, forecasting /“. Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/7396.

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Chan, Man Ching Stella. „Essays on real exchange rate adjustments in a fixed exchange rate system“. Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1666128101&sid=5&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Liu, Kit-ying Ida, und 廖潔瑩. „Empirical exchange rate models: out-of-sampleforecasts for the HK$/Yen exchange rate“. Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B3195456X.

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Kristensen, Scott Dennis 1958. „A new monetary model of foreign exchange rates“. Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/288762.

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An attempt is made to create a model of exchange rates that explains the short term, daily levels of the foreign exchange spot market. The model is a monetary type that focuses on the eurocurrency markets and the current account. It has a liquidity preference form and employs daily data. The futures rate, the euro interest rate, the eurocurrency money stocks and a current account variable are the individual variables of the model. The futures rate and the euro interest rates are from the assumed Fisher's 'Covered Interest Rate Paradigm'. The eurocurrency money stock variable's justification is based on the real world structure of the spot market where the foreign exchange desks of the major world commercial banks are the dominant players. The current account variable, which is motivated by a desire to improve on the short run performance of the Purchasing Power Parity variable of other monetary models, is justified by trade theory. The liquidity preference form of the model is in keeping with current monetary models. The econometric results show that the model is better than the random walk model. However the results of the individual variables are mixed. The futures rate accounts for the vast majority of the model's success. Although the eurocurrency variable is as statistically significant as the interest rate differentials from the widely accepted Fisher's Covered Interest Rate Parity paradigm, neither was as significant as the futures rate. The current account variable results are not statistically significant. Thus, the current account variable may be discarded while the eurocurrency interest rates and euromoney variables warrant further study. As a result of the dominance of the futures rate variable, models that cry to capture rational expectations such as the News or Chaos Models are appealing. This rational expectations characteristic of the market combined with the dominance of speculation over economic fundamentals also points toward game theory as a good candidate for further study.
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Packirisamy, Someshini. „Empirical modelling of high-frequency foreign exchange rates“. Master's thesis, University of Cape Town, 2004. http://hdl.handle.net/11427/5963.

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Includes bibliographical references (leaves 213-219).
There is a wealth of information available on modelling foreign exchange time series data, however, research studies on modelling and predicting high frequency foreign exchange data is less prominent. Furthermore, there does not appear to be much evidence supporting work on the modelling and prediction of high frequency South African Rand/United States Dollar (ZAR/USD) exchange rates. A fair amount of noise is embedded in high frequency time series data, especially the ZAR/USD exchange rates, and the modelling of these time series requires the use of specialized models. In addition, lengthy high frequency foreign exchange data is largely unavailable for the South African market. This dissertation undertakes empirical explorations to model high frequency foreign exchange time series (primarily the ZAR/USD time series), through the use of multi-agent neural networks, linear Kalman filters and fuzzy Markov chain theory.
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Wan, Chung-kum. „Cross hedging of foreign exchange risk“. Click to view the E-thesis via HKUTO, 2000. http://sunzi.lib.hku.hk/hkuto/record/B31954741.

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Wan, Chung-kum, und 尹頌琴. „Cross hedging of foreign exchange risk“. Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31954741.

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Bücher zum Thema "Foreign exchange rates – Ethiopia"

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Kidane, Asmerom. Indices of effective exchange rates: A comparative study of Ethiopia, Kenya, and the Sudan. Nairobi: African Economic Research Consortium, 1994.

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Kidane, Asmerom. Real exchange rate price and agricultural supply response in Ethiopia: The case of perennial crops. Nairobi: African Economic Research Consortium, 1999.

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Söylemez, Arif Orçun. Foreign Exchange Rates. Abingdon, Oxon ; New York, NY : Routledge, 2021. | Series: Routledge focus on economics and finance: Routledge, 2020. http://dx.doi.org/10.4324/9781003102809.

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Bourne, Compton. Foreign exchange rates: Again? St. Augustine, Trinidad and Tobago: Caribbean Center for Monetary Studies, the University of the West Indies, 2003.

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Managing exchange rates. New York: Published in North America for the Royal Institute of International Affairs [by] Council on Foreign Relations Press, 1988.

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On exchange rates. Cambridge, Mass: MIT Press, 1993.

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Fosler, Gail D. Do exchange rates matter? New York, NY: Conference Board, 2004.

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Engel, Charles. Exchange rates and fundamentals. Cambridge, MA: National Bureau of Economic Research, 2004.

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Engel, Charles. Exchange rates and fundamentals. Cambridge, Mass: National Bureau of Economic Research, 2004.

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Sarno, Lucio, Jessica James und Ian W. Marsh. Handbook of exchange rates. Hoboken, New Jersey: John Wiley & Sons, Inc., 2012.

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Buchteile zum Thema "Foreign exchange rates – Ethiopia"

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Anthony, Steve. „Exchange Rates“. In Foreign Exchange in Practice, 1–11. London: Palgrave Macmillan UK, 2003. http://dx.doi.org/10.1057/9781403914552_1.

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Harvey, Jack. „Foreign Exchange Rates“. In Economics Revision Guide, 159–60. London: Macmillan Education UK, 1994. http://dx.doi.org/10.1007/978-1-349-13313-0_39.

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Bhogal, Tarsem Singh, und Arun Kumar Trivedi. „Foreign Exchange Rates“. In International Trade Finance, 11–19. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/9780230594326_4.

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Bhogal, Tarsem, und Arun Trivedi. „Foreign Exchange Rates“. In International Trade Finance, 15–24. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24540-5_4.

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Harvey, J., und M. K. Johnson. „Foreign Exchange Rates“. In Modern Economics, 131–33. London: Macmillan Education UK, 1994. http://dx.doi.org/10.1007/978-1-349-23360-1_39.

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Harvey, Jack, und Ernie Jowsey. „Foreign Exchange Rates“. In Modern Economics, 495–500. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-1-137-08602-0_39.

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Harvey, J. „Foreign Exchange Rates“. In Modern Economics Student’s Notebook, 94. London: Macmillan Education UK, 1985. http://dx.doi.org/10.1007/978-1-349-81181-6_32.

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Anthony, Steve. „Forward Exchange Rates“. In Foreign Exchange in Practice, 78–100. London: Palgrave Macmillan UK, 2003. http://dx.doi.org/10.1057/9781403914552_6.

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Söylemez, Arif Orçun. „A brief introduction of the global foreign exchange market“. In Foreign Exchange Rates, 1–5. Abingdon, Oxon ; New York, NY : Routledge, 2021. | Series: Routledge focus on economics and finance: Routledge, 2020. http://dx.doi.org/10.4324/9781003102809-1.

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Söylemez, Arif Orçun. „Prominent structural models for exchange rate determination“. In Foreign Exchange Rates, 6–12. Abingdon, Oxon ; New York, NY : Routledge, 2021. | Series: Routledge focus on economics and finance: Routledge, 2020. http://dx.doi.org/10.4324/9781003102809-2.

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Konferenzberichte zum Thema "Foreign exchange rates – Ethiopia"

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Cross, D. W., C. J. Hinde und M. D. Sykora. „Predicting fluctuations in foreign exchange rates“. In 2013 13th UK Workshop on Computational Intelligence (UKCI). IEEE, 2013. http://dx.doi.org/10.1109/ukci.2013.6651318.

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„Contradiction Resolution for Foreign Exchange Rates Estimation“. In International Conference on Neural Computation Theory and Applications. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0004152905290535.

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Bahramy, Farhad, und Sven F. Crone. „Forecasting foreign exchange rates using Support Vector Regression“. In 2013 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE, 2013. http://dx.doi.org/10.1109/cifer.2013.6611694.

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He, Haibo, und Xiaoping Shen. „Bootstrap Methods for Foreign Currency Exchange Rates Prediction“. In 2007 International Joint Conference on Neural Networks. IEEE, 2007. http://dx.doi.org/10.1109/ijcnn.2007.4371141.

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Samarawickrama, A. J. P., und T. G. I. Fernando. „Multi-Step-Ahead Prediction of Exchange Rates Using Artificial Neural Networks: A Study on Selected Sri Lankan Foreign Exchange Rates“. In 2019 IEEE 14th Conference on Industrial and Information Systems (ICIIS). IEEE, 2019. http://dx.doi.org/10.1109/iciis47346.2019.9063310.

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AmirAskari, Mercedeh, und Mohammad Bagher Menhaj. „A modified fuzzy relational model approach to prediction of Foreign Exchange rates“. In 2016 4th International Conference on Control, Instrumentation, and Automation (ICCIA). IEEE, 2016. http://dx.doi.org/10.1109/icciautom.2016.7483206.

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Huang, Wei, Kin Keung Lai, Jinlong Zhang und Yukun Bao. „Foreign Exchange Rates Forecasting with Multilayer Perceptrons Neural Network by Bayesian Learning“. In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.661.

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Cakar, O., O. O. Aybar, A. S. Hacinliyan und I. Kusbeyzi. „Chaoticity in the time evolution of foreign currency exchange rates in Turkey“. In Selected Papers from the 3rd Chaotic Modeling and Simulation International Conference (CHAOS2010). WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814350341_0014.

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Sekmen, Fuat, und Galip Afsin Ravanoglu. „The Effects of the Interest Rate and Foreign Exchange Rates on Kyrgyzstan Export“. In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c09.02012.

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In the Keynesian models, such as Mundell-Fleming model, it is accepted that there is a significant relationship between interest rates and the value of national currency. When interest rate increases, demand for assets in terms of national currency rises and the value of national currency ascends, but in this case because of diminishing exports, the balance of trade deteriorates. In this study, it is stressed that the value of national currency is determined by productivity and output increasing. This study analysis export, interest rate, exchange rate and inflation relationship for Kyrgyzstan economy for the period of 2002:1-2017:4 The VAR granger causality method is used to get the relationship among the variables used in this study. The result of VAR granger causality test shows that there is causality from exchange rate to inflation. Also, it has been found that there has been causality running from inflation to interest rate.
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Cheong, France. „A hierarchical fuzzy system with high input dimensions for forecasting foreign exchange rates“. In 2007 IEEE Congress on Evolutionary Computation. IEEE, 2007. http://dx.doi.org/10.1109/cec.2007.4424670.

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Berichte der Organisationen zum Thema "Foreign exchange rates – Ethiopia"

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Guo, Hui, und Robert Savickas. Idiosyncratic Volatility, Economic Fundamentals, and Foreign Exchange Rates. Federal Reserve Bank of St. Louis, 2005. http://dx.doi.org/10.20955/wp.2005.025.

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Lewis, Karen. Occasional Interventions to Target Rates with a Foreign Exchange Application. Cambridge, MA: National Bureau of Economic Research, Juli 1990. http://dx.doi.org/10.3386/w3398.

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Giovannini, Alberto. Currency Substitution and the Fluctuations of Foreign-Exchange Reserves with Credibly Fixed Exchange Rates. Cambridge, MA: National Bureau of Economic Research, Februar 1991. http://dx.doi.org/10.3386/w3636.

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Tamru, Seneshaw, Bart Minten und Johan F. M. Swinnen. Trade, value chains, and rent distribution with foreign exchange controls: Coffee exports in Ethiopia. Washington, DC: International Food Policy Research Institute, 2019. http://dx.doi.org/10.2499/p15738coll2.133414.

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Froot, Kenneth, und Jeremy Stein. Exchange Rates and Foreign Direct Investment: An Imperfect Capital Markets Approach. Cambridge, MA: National Bureau of Economic Research, März 1989. http://dx.doi.org/10.3386/w2914.

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Dominguez, Kathryn. Does Central Bank Intervention Increase the Volatility of Foreign Exchange Rates? Cambridge, MA: National Bureau of Economic Research, November 1993. http://dx.doi.org/10.3386/w4532.

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Goldberg, Linda. Moscow Black Markets and Official Markets for Foreign Exchange: How Much Flexiblity in Flexible Rates? Cambridge, MA: National Bureau of Economic Research, März 1992. http://dx.doi.org/10.3386/w4040.

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Giovanni, Julian di, und Jay Shambaugh. The Impact of Foreign Interest Rates on the Economy: The Role of the Exchange Rate Regime. Cambridge, MA: National Bureau of Economic Research, Oktober 2007. http://dx.doi.org/10.3386/w13467.

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Fabiani, Andrea, Martha López, José-Luis Peydró, Paul E. Soto und Margaret Guerrero. Capital Controls, Domestic Macroprudential Policy and the Bank Lending Channel of Monetary Policy. Banco de la República, Juni 2021. http://dx.doi.org/10.32468/be.1162.

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We study how capital controls and domestic macroprudential policy tame credit supply booms, respectively targeting foreign and domestic bank debt. For identification, we exploit the simultaneous introduction of capital controls on foreign exchange (FX) debt inflows and an increase of reserve requirements on domestic bank deposits in Colombia during a strong credit boom, as well as credit registry and bank balance sheet data. Our results suggest that first, an increase in the local monetary policy rate, raising the interest rate spread with the United States, allows more FX-indebted banks to carry trade cheap FX funds with more expensive peso lending, especially toward riskier, opaque firms. Capital controls tax FX debt and break the carry trade. Second, the increase in reserve requirements on domestic deposits directly reduces credit supply, and more so for riskier, opaque firms, rather than enhances the transmission of monetary rates on credit supply. Importantly, different banks finance credit in the boom with either domestic or foreign (FX) financing. Hence, capital controls and domestic macroprudential policy complementarily mitigate the boom and the associated risk-taking through two distinct channels
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Vargas-Herrera, Hernando, Juan Jose Ospina-Tejeiro, Carlos Alfonso Huertas-Campos, Adolfo León Cobo-Serna, Edgar Caicedo-García, Juan Pablo Cote-Barón, Nicolás Martínez-Cortés et al. Monetary Policy Report - April de 2021. Banco de la República de Colombia, Juli 2021. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr2-2021.

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1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.
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