ALTERNATIVE METHODOLOGIES FOR ESTIMATING POTENTIAL OUTPUT AND THE OUTPUT GAP
Abstract
The paper aims to present alternative methodologies for estimating potential output and output gap. The goal is to make a brief overview and comparison between the most commonly used methodologies for estimating potential GDP. A better knowledge of the different methodologies and their specificities will contribute to obtaining more reliable and adequate estimates of potential output and the output gap. Regardless of the method chosen, it is necessary to use it critically and non-mechanically. Most methods provide estimates with a similar overall profile of potential output and to some extent the output gap, but there are large differences in estimating the scale of the output gap.
Keywords
Full Text:
PDFReferences
Ganev, K. (2004). Statisticheski otsenki na otkloneniyata ot makroikonomicheskiya potentsial. Prilozhenie za ikonomikata na Balgariya. Agentsiya za ikonomicheski analizi i prognozi.
Ganev, K. (2015). Biznes tsikli: Teorii i modeli. Sofiyski universitet „Sv. Kliment Ohridski”. Sofiya.
Gladnishki A. (2004). Agregirana proizvodstvena funktsiya na Balgariya v usloviya na prehod. Agentsiya za ikonomicheski analizi i prognozi.
Gladnishki, A. (2005). Izmervane na potentsialnoto proizvodstvo: izpolzvane na instrumentariuma na proizvodstvenite funktsii. Agentsiya na ikonomicheski analizi i prognozi.
Minasyan, G. (2008). Finansovo programirane. Sofiya: Klasika i stil.
Raleva, S. (2013). Inflatsiya i ikonomicheski rastezh: teoriya, metodologiya, empirika. Sofiya: Izdatelski kompleks UNSS.
Todorov, I. (2015). Dva podhoda za otsenka na agregiranata proizvodstvena funktsiya na Balgariya. Ikonomicheski izsledvaniya, 4/2015.
Todorov, I. (2017). Rastezhat i tsiklichnostta na balgarskata ikonomika v usloviyata na parichen savet. Sofiya: Avangard Prima.
Todorov, I. i Aleksandrov, A. (2018). Dva kombinirani podhoda za otsenka na tsiklichnata pozitsiya i fazata na biznes tsikala na Balgariya. Spisanie „Dialog“ 3/2018. Stopanska Akademiya „D.A. Tsenov“, Svishtov.
Tsalinski, Ts. (2006). Dva podhoda za empirichna otsenka na potentsialnoto proizvodstvo na Balgariya. BNB, Diskusionni mateirali, DP/57/2006.
Adams, C., Coe, D. (1990). A system approach to estimating the national rate of unemployment and potential output for the United States. IMF Staff Papers, Vol 37, № 2.
Alichi, A. (2015). A New Methodology for Estimating the Output Gap in the United States. IMF Working Paper, WP/15/144.
Anderton, R., Aranki, T., Dieppe, A., Elding, C., Haroutunian, S., Jacquinot, P., Jarvis, V., Labhard, V., Rusinova, D., Szörfi, B. (2014). Potential Output from Euro Area Perspective. ECB. Occasional Paper Series. No. 156.
Apel M., Jansson, P. (1997). System Estimates of Potential Output and the NAIRU. Economics Department, Sveriges Riksbank.
Balakrishnan, R., López-Salido, J. (2002). Understanding UK Inflation: the Role of Openness. Bank of England Working paper No. 164.
Bank of Japan Research and Statistics Department. (1989). A Study on Potential Supply and Market Conditions: A Production Function Approach Including the Stabilizing Effect of Imports. Bank of Japan Special Paper, No 175.
Baxter, M., King, R. (1995). Measuring business cycles: Approximate band-pass filters for economic series. NBER Working Paper No. 5022.
Baxter, M., King, R. (1999). Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series. Review of Economics and Statistics (81)4, 573-593.
Benes, J., Clinton, K., Garcia-Saltos, R., Johnson, M., Laxton, D., Manchev, P., Matheson, T. (2010). Estimating Potential Output with a Multivariate Filter. IMF WP, № 285.
Beveridge, S., Nelson, C. (1981). A New Approach to the Decomposition of Economic Time Series into Permanent and Transitory Components with Particular Attention to Measurement of the Business Cycle. Journal of Monetary Economics 7: 151-74.
Blagrave, P., Garcia-Saltos, R., Laxton, D., Zhang, F. (1979). A Simple Multivariate Filter for Estimating Potential Output. IMF WP/15/79.
Blanchard, O., Quah, D. (1989). The Dynamic Effects of Aggregate Demand and Aggregate Supply. The American Economic Review, 79(4), pp. 655-673.
Bokan, N., Ravnik, R. (2012). Estimating potential output in the Republic of Croatia using a multivariate filter. Croatian National Bank, Working Paper W35.
Borio, C., Disyatat, P., Juselius, M. (2013). Rethinking potential output: embedding information about the financial cycle. BIS WP, No 404.
Camba-Mendez, G., Rodriguez-Palenzuela, D. (2001). Assessment criteria for output gap estimates. ECB WP 54.
Christiano, L., Fitzgerald, T. (1999). The band-pass filter. NBER WP 7257.
Clarida, R., Gali, J. (1994). Sources of Real Exchange Rate Fluctuations: How Important Are Nominal Shocks? Carnegie-Rochester CS on Public Policy, 41, pp 1-56.
Cochrane, J. (1994). Permanent and Transitory Components of GNP and Stock Prices. Quarterly Journal of Economics 61: 241-65.
Cogley, T., Nason, J. (1995). Effects of the Hodrick-Prescott Filter on Trend and Difference Stationary Time Series: Implications for Business Cycle Research. Journal of Economic Dynamics and Control 19: 253-78.
De Massi, P. (1997). Estimates of Potential Output: Theory and Practice. IMF
Denis, C., McMorrow, K., Roger, W. (2002). Production function approach to calculating potential growth and output gaps–estimates for the EU Member States and the US. European Commission, Economic Papers 176.
DeSerres, A., Guay, A. (1995). The Selection of the Truncation Lag in Structural VARs (or VECMs) with Long-Run Restrictions. Working Paper 95-9. Bank of Canada, Ottawa.
Dobrescu, E. (2006). Double-conditioned potential output. Romanian Journal of Economic Forecasting, Vol. 3, pp. 32-50.
Durova, K. (2018). Long-term Impact of the European Funds on Bulgaria’s Economy. Economic Alternatives 2018(2).
Economic Research Institute at the Bulgarian Academy of Sciences. (2012). Economic Development and Policy in Bulgaria: Evaluations and Expectations. Special Focus: Competitiveness of Bulgarian Economy.
Epstein, N., Machiarelli, C. (2010). Estimating Poland’s Potential Output – A Production Function Approach. IMF Working Paper, No 15.
European Commission. (2014). The Production Function Methodology for Calculating Potential Growth Rates & Output Gaps. Economic Papers 535.
European Commission. (2015). Bulgaria: Report papered in accordance with Article 126(3) of the Treaty. Brussels.
Gagales, A. (2006). Growth in Greece: Can Better Performance be Sustained? Selected Issues and Statistical Appendix, IMF Country Report No. 06/5.
Gali, J., López-Salido, J. (2001). A New Phillips Curve for Spain. BIS WP No. 3.
Ganev, K. (2005). Measuring Total Factor Productivity: Growth Accounting for Bulgaria. Discussion Paper, Agency for Economic Analysis and Forecasting, Bulgaria.
Ganev, K. (2015). A Small Model for Output Gap and Potential Growth Estimation: An Application to Bulgaria. Center for Economic Theories and Policies, BEP 04/2015.
Grech, A. (2013). Adapting the Hodrick-Prescott filter for very small open economies. International Journal for Economics and Finance, 5(8).
Guay, A., St-Amant, P. (1996). Do Mechanical Filters Provide a Good Approximation of Business Cycles? Technical Report No. 78. Ottawa: Bank of Canada
Harvey, A., Jaeger, A. (1993). Detrending, Stylized Facts and the Business Cycle. Journal of Applied Econometrics 8: 231-47.
Hodrick, R., Prescott, E. (1997). Post-war U.S. business cycles: An empirical investigation. Journal of Money, Credit and Banking, 29(1).
IMF. (1991). Potential Output in Major Industrial Countries. World Economic Outlook.
IMF. (2014). Bulgaria’s EU Funds Absorption: Maximizing the Potential. WP/14/21.
Kalman, R. (1960). A New Approach to Linear Filtering and Prediction Problems. Journal of Basic Engineering, Vol. 82, pp. 35-45.
Kasabov, D., Kotseva, P., Vassilev, A., Yanchev, M. (2017). Relationship between Inflation, Potential Output and Structural Unemployment in Bulgaria. BNB, DP 104/2017.
Kuttner, K. (1994). Estimating potential output as a latent variable. Journal of Business and Economic Statistics 12, pp. 361-68.
Lippi, M., Reichlin, L. (1994). Diffusion of Technical change and the decomposition of output into trend and cycle. Review of Economic Studies 61(1), pp. 19-30.
Mankiw, G. (2003). Macroeconomics. Worth Publishers, 5th edition.
Maybeck, P. (1979). Stochastic Models, Estimation, and Control. Academic Press.
Micallef, B. (2016). A Multivariate Filter to Estimate Potential Output and NAIRU for the Maltese Economy. International Journal of Economics and Finance; Vol. 8, No. 5.
Micolet, P. (1999). Eléments pour une analyse appliquée des cycles. Mimeo, Paris.
Ministry of Finance of the Republic of Bulgaria. (2014). Bulgaria’s economy 2013: an annual survey.
Mishkin, F. (2007). Estimating Potential Output. Address at the Conference on Price Measurement for Monetary Policy, Federal Reserve Bank of Dallas.
Morley, J. (2011). The Two Interpretations of the Beveridge-Nelson Decomposition. Macroeconomic Dynamics, 6/2011.
Morley, J., Nelson, C., Zivot, E. (2003). Why are Beveridge-Nelson and Unobserved components decompositions of GDP so different? Review of Economics and Statistics, Vol. 85, №2.
Okun, A. (1962). Potential GDP: Its measurement and significance. Proceedings of the American Statistical Association.
Orphanides, A., van Norden, S. (1999). The reliability of output gap estimates in real time. Board of Governor of the Federal Reserve System, Finance and Economics DS 99/38.
Proietti, T. (2006). Trend-cycle decompositions with correlated components, Econometric Reviews 25, 61-84.
Quah, D. (1992). The Relative Importance of Permanent and Transitory Components: Identification and Some Theoretical Bounds. Econometrica 60: 107-18.
Ravn, M., Uhlig, H. (2002). On adjusting the Hodrick-Prescott filter for the frequency of observations. Review of Economics and Statistics (84)2, 371-380.
Razzak, W. (1997). The Hodrick-Prescott Technique: A Smoother Versus a Filter: An Application to New Zealands GDP. In: Economics Letters, 57, 163–168.
Schumacher, C. (1999). Measuring EMU Potential Output Using a Multivariate Beveridge-Nelson-Decomposition. Institute for Economic Research Halle DP 98.
Solow, R. (1957). Technical Change and the Aggregate Production Function. Review of Economics and Statistics, 39(3), 312–320.
Sramkova, L., Kobilicova, M., Krajcir, A. (2010). Output gap and NAIRU estimates within state-space framework: An application to Slovakia. Financial Policy Institute. The Ministry of Finance of the Slovak Republic, Economic Analysis 16.
St-Amant, P., van Norden, S. (1997). Measurement of the output gap: A discussion of recent research at the Bank of Canada. Bank of Canada Technical Report No. 79.
Svensson, L. (1999). Inflation Targeting as a Monetary Policy Rule. Journal of Monetary Economics, 43: 607-54.
Swagel, P., Scacciavillani, F. (2002). Measures of Potential Output: An Application to Israel. Applied Economics, 34: 945-957.
Taylor, J. (1993). Discretion versus Policy Rules in Practice. Carnegie-Rochester Series on Public Policy, 39: 195-214.
Toth, M. (2014). Measuring the Cyclical Position of the Hungarian Economy: a Multivariate Unobserved Components Model. Magyar Nemzeti Bank Working Paper.
Van Norden, S. (1995). Why Is It So Hard to Measure the Current Output Gap? Bank of Canada.
Zarnowitz, V. (1999). Theory and History Behind Business Cycles: Are the 1990’s the Onset of a Golden Age? In: The Journal of Economic Perspectives, 13 (2), 69–90.
Refbacks
- There are currently no refbacks.
New knowledge Journal of science is financed by the National Science Fund of the Republic of Bulgaria - contract № КП-06-НП1/5 of 17.12.2019 in the competition of Bulgarian scientific periodicals – 2019
New knowledge Journal of science is financed by the National Science Fund of the Republic of Bulgaria – contract № ДНП 05/52 от 22.12.2016 in the competition of Bulgarian scientific periodicals – 2016
The contents of this publication do not necessarily reflect the position or opinion of the National Science Fund of the Republic of Bulgaria. The opinions expressed are those of the author(s) only and should not be considered as representative of the National Science Fund’s official position.