Back Matter

Back Matter

Author(s):
Nir Klein
Published Date:
August 2011
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    References

      Akinboade, O. A.,2005, “Some Estimates of Potential Output and the Output Gap for South Africa,” Journal Studies in Economics and Econometrics, Vol. 29 (1), pp. 1528.

      Arora, V., and A.Bhundia,2003, “Potential Output and Total Factor Productivity Growth in Post-Apartheid South Africa,” IMF Working Paper No. 03/178 (Washington: International Monetary Fund).

      Baxter, M., and R. G.King,1995, “Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series,” NBER Working Paper No. 5022 (Cambridge, Massachusetts: National Bureau of Economic Research).

      Blanchard, O., and D.Quah,1989, “The Dynamic Effects of Aggregate Supply and Demand Disturbances,” American Economic Review, Vol. 79, pp. 65573.

      Cerra, V., and S.Saxena,2000, “Alternative Methods of Estimating Potential Output and the Output Gap: An Application to Sweden,” IMF Working Paper 00/59 (Washington: International Monetary Fund).

      Clarida, R., and J.Galí,1994, “Sources of Real Exchange Rate Fluctuations: How Important are nominal Shocks?Carnegie-Rochester Conference Series on Public Policy, Vol. 41, pp. 156.

      De Masi, P.,1997, “IMF Estimates of Potential Output: Theory and Practice,” Staff Studies for the World Economic Outlook (Washington: International Monetary Fund).

      Du Plessis, S., B.Smit, and F.Sturzenegger,2007, “Identifying Aggregate Supply and Demand Shocks in South Africa,” CID Working Paper No. 164 (Cambridge, Massachusetts: Center for International Development at Harvard University).

      Du Toit, C. B., and E.Moolman,2003, “Estimating Potential Output and Capacity Utilization for the South African Economy,” South African Journal of Economics, Vol. 71 (1), pp. 96118.

      Fuentes, R., F.Gredig., and M.Larrain. 2007. “Estimating the Output Gap for Chile.” Central Bank of Chile Working Paper No. 455.

      Magud, N., and L.Medina,2011, “The Chilean Output Gap,” IMF Working Paper 11/02 (Washington: International Monetary Fund).

      Menashe, Y., and Y.Yakhin,2004, “Mind the Gap: Structural and Nonstructural Approaches to Estimating Israel’s Output Gap,” Israel Economic Review, Vol. 2 (2), pp. 79106.

      Obsfeld, M.,1985, “Floating Exchange Rates: Experience and Prospects,” Brookings Papers on Economic Activity, Vol. 2, pp. 369450.

      Okun, A.,1962, “Potential GNP: Its Measurement and Significance,” 1962 Proceedings of the Business and Economic Statistics Section of the American Statistical Association, pp. 17.

    Appendix 1. Unobserved Component Models using Kalman Filter

    Model 1

    The state space form of the univariate filter can be presented as follows:

    The variables ytc and gt represent the cyclical component of yt (the output gap) and the trend growth, respectively. and ϵtc and ϵtg are residual terms of mean 0 and variances σc2 and σg2, respectively. The cyclical component of output follows an autoregressive process, and θ is lower than 1 to ensure a stationary process. The smoothness of the trend component is controlled by constraining the relative variance (σc2/σg2) to be equal to 1,600, as in the HP filter. The system can be estimated by Kalman filter, using equation (2) as a signal equation and equations (3) to (5) as the transitional equations.

    Model 2

    In this model, we add a backward-looking Phillips curve as a second signal equation in the system presented previously, which implies that inflation path is affected by past inflation rates as well as current and past output gaps, as follows:

    Where πt is the inflation rate and is a white noise process of mean 0 and variance σπ2. The parameters p and q refer to the lags of inflation and output gap, respectively.

    Model 3

    In this third model, we add the following standard backward-looking IS curve to the second model, such that the system includes three signal equations:

    Where rt is the real short-term rate and ϵty is the white process of mean 0 and variance σy2. The parameter r^t reflects the unobserved natural real rate, which is affected by the trend growth, as follows:

    The smoothness of r^t is controlled by constraining the relative variance of ϵty and ϵtr(σy2/σr2) to λ.

    Figure A1.The estimated total factor productivity (in natural logarithm), 1985-2009

    Figure A2.The cyclical components of energy production and employment, 1985-2010

    Figure A3.South Africa’s output gap by main sectors

    Figure A4.South Africa: Participation rate and discouraged work-seekers

    Source: Quarterly Labor Force Survey, SASTAT.

    Figure A5.REER change in selected EMs, 2008Q2-2010Q4

    Source: INS database.

    Figure A6.The share of South Africa’s exports of goods by regions

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