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Who benefits from being self-employed in urban Ghana?

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Abstract

The income gap between the self-employed and wage earners is of interest particular in developing countries. This is because this gap can explain to some extent the observed inequality in income. Literature suggests that in developing countries formal sector workers tend to be wage earners while the self-employed mostly work in the informal sector.Â

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  • Adeola Oyenubi, 2019. "Who benefits from being self-employed in urban Ghana?," Working Papers 189, Economic Research Southern Africa.
  • Handle: RePEc:rza:wpaper:189
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    1. Clements, Michael P. & Smith, Jeremy, 1997. "The performance of alternative forecasting methods for SETAR models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 463-475, December.
    2. Mishkin, F S., 2008. "How should we respond to asset price bubbles?," Financial Stability Review, Banque de France, issue 12, pages 65-74, October.
    3. Naraidoo, Ruthira & Paya, Ivan, 2012. "Forecasting monetary policy rules in South Africa," International Journal of Forecasting, Elsevier, vol. 28(2), pages 446-455.
    4. Ben S. Bernanke & Mark Gertler, 2001. "Should Central Banks Respond to Movements in Asset Prices?," American Economic Review, American Economic Association, vol. 91(2), pages 253-257, May.
    5. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    6. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    7. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    8. Ruthira Naraidoo & Rangan Gupta, 2009. "Modelling monetary policy in South Africa: Focus on inflation targeting era using a simple learning rule," Working Papers 200904, University of Pretoria, Department of Economics.
    9. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    10. repec:bla:econom:v:71:y:2004:i:281:p:209-221 is not listed on IDEAS
    11. Geoffrey Woglom, 2003. "How Has Inflation Targeting Affected Monetary Policy in South Africa?," South African Journal of Economics, Economic Society of South Africa, vol. 71(2), pages 198-210, June.
    12. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.
    13. Bec Frédérique & Ben Salem Mélika & Collard Fabrice, 2002. "Asymmetries in Monetary Policy Reaction Function: Evidence for U.S. French and German Central Banks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-22, July.
    14. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    15. Virginie Boinet & Christopher Martin, 2008. "Targets, zones, and asymmetries: a flexible nonlinear model of recent UK monetary policy," Oxford Economic Papers, Oxford University Press, vol. 60(3), pages 423-439, July.
    16. Castro, Vitor, 2008. "Are Central Banks following a linear or nonlinear (augmented) Taylor rule?," Economic Research Papers 269883, University of Warwick - Department of Economics.
    17. Clarida, Richard & Gali, Jordi & Gertler, Mark, 1998. "Monetary policy rules in practice Some international evidence," European Economic Review, Elsevier, vol. 42(6), pages 1033-1067, June.
    18. Aksoy, Yunus & Orphanides, Athanasios & Small, David & Wieland, Volker & Wilcox, David, 2006. "A quantitative exploration of the opportunistic approach to disinflation," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1877-1893, November.
    19. Antonello D'Agostino & Paolo Surico, 2009. "Does Global Liquidity Help to Forecast U.S. Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 479-489, March.
    20. A. Robert Nobay & David A. Peel, 2003. "Optimal Discretionary Monetary Policy in a Model of Asymmetric Central Bank Preferences," Economic Journal, Royal Economic Society, vol. 113(489), pages 657-665, July.
    21. Carl E. Walsh, 2009. "Using monetary policy to stabilize economic activity," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 245-296.
    22. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    23. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    24. Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
    25. Hayat, Aziz & Mishra, Sagarika, 2010. "Federal reserve monetary policy and the non-linearity of the Taylor rule," Economic Modelling, Elsevier, vol. 27(5), pages 1292-1301, September.
    26. Demertzis Maria & Viegi Nicola, 2009. "Inflation Targeting: A Framework for Communication," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-32, December.
    27. Rudebusch, Glenn D., 2002. "Term structure evidence on interest rate smoothing and monetary policy inertia," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1161-1187, September.
    28. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    29. Janine Aron & John Muellbauer, 2002. "Estimating Monetary Policy Rules for South Africa," Central Banking, Analysis, and Economic Policies Book Series, in: Norman Loayza & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.),Monetary Policy: Rules and Transmission Mechanisms, edition 1, volume 4, chapter 15, pages 427-476, Central Bank of Chile.
    30. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
    31. Bomfim, Antulio N & Rudebusch, Glenn D, 2000. "Opportunistic and Deliberate Disinflation under Imperfect Credibility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(4), pages 707-721, November.
    32. Christopher Martin & Costas Milas, 2010. "Testing The Opportunistic Approach To Monetary Policy," Manchester School, University of Manchester, vol. 78(2), pages 110-125, March.
    33. Gerlach-Kristen Petra, 2004. "Interest-Rate Smoothing: Monetary Policy Inertia or Unobserved Variables?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 4(1), pages 1-19, March.
    34. Moura, Marcelo L. & de Carvalho, Alexandre, 2010. "What can Taylor rules say about monetary policy in Latin America?," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 392-404, March.
    35. By Gunnar Jonsson, 2001. "Inflation, Money Demand, and Purchasing Power Parity in South Africa," IMF Staff Papers, Palgrave Macmillan, vol. 48(2), pages 1-2.
    36. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    37. Qin, Ting & Enders, Walter, 2008. "In-sample and out-of-sample properties of linear and nonlinear Taylor rules," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 428-443, March.
    38. Cukierman Alex & Muscatelli Anton, 2008. "Nonlinear Taylor Rules and Asymmetric Preferences in Central Banking: Evidence from the United Kingdom and the United States," The B.E. Journal of Macroeconomics, De Gruyter, vol. 8(1), pages 1-31, February.
    39. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    40. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    41. Tobias Knedlik, 2006. "Estimating Monetary Policy Rules For South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 74(4), pages 629-641, December.
    42. Surico, Paolo, 2007. "The Fed's monetary policy rule and U.S. inflation: The case of asymmetric preferences," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 305-324, January.
    43. Clifford M. Hurvich & Jeffrey S. Simonoff & Chih‐Ling Tsai, 1998. "Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 271-293.
    44. Martin, Christopher & Costas Milas, 2002. "Modelling Monetary Policy: Inflation Targeting in Practice," Royal Economic Society Annual Conference 2002 137, Royal Economic Society.
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    Cited by:

    1. Naraidoo, Ruthira & Paya, Ivan, 2012. "Forecasting monetary policy rules in South Africa," International Journal of Forecasting, Elsevier, vol. 28(2), pages 446-455.
    2. Luchelle Soobyah & Mulalo Mamburu & Nicola Viegi, 2023. "IsSouthAfricafallingintoafiscaldominantregime," Working Papers 11041, South African Reserve Bank.
    3. Leroi RAPUTSOANE, 2016. "Financial Stress Indicator Variables and Monetary Policy in South Africa," Journal of Economics Bibliography, KSP Journals, vol. 3(2), pages 203-214, June.
    4. Ellyne, Mark & Veller, Carl, 2011. "What is the SARB's inflation targeting policy, and is it appropriate?," MPRA Paper 42134, University Library of Munich, Germany.
    5. Tumisang Loate & Ekaterina Pirozhkova & Nicola Viegi, 2021. "Sailing into the Wind evaluating the near future of Monetary Policy in South Africa," Working Papers 11006, South African Reserve Bank.
    6. Leroi RAPUTSOANE, 2015. "The lean versus clean debate and monetary policy in South Africa," Journal of Economics and Political Economy, KSP Journals, vol. 2(4), pages 467-480, December.
    7. Mehmet Balcilar & Rangan Gupta & Kevin Kotzé, 2017. "Forecasting South African macroeconomic variables with a Markov-switching small open-economy dynamic stochastic general equilibrium model," Empirical Economics, Springer, vol. 53(1), pages 117-135, August.
    8. Georgiadis, Georgios & Jančoková, Martina, 2020. "Financial globalisation, monetary policy spillovers and macro-modelling: Tales from 1001 shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    9. Chesang, Laban K. & Naraidoo, Ruthira, 2016. "Parameter uncertainty and inflation dynamics in a model with asymmetric central bank preferences," Economic Modelling, Elsevier, vol. 56(C), pages 1-10.
    10. Raputsoane, Leroi, 2018. "Targeting financial stress as opposed to the exchange rate," MPRA Paper 84865, University Library of Munich, Germany.
    11. Davide Debortoli & Ricardo Nunes, 2014. "Monetary Regime Switches and Central Bank Preferences," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(8), pages 1591-1626, December.
    12. Alessandro Piergallini, 2019. "Nonlinear policy behavior, multiple equilibria and debt-deflation attractors," Journal of Evolutionary Economics, Springer, vol. 29(2), pages 563-580, April.
    13. Ruch,Franz Ulrich, 2021. "Neutral Real Interest Rates in Inflation Targeting Emerging and Developing Economies," Policy Research Working Paper Series 9711, The World Bank.
    14. Baaziz, Yosra & Labidi, Moez & Lahiani, Amine, 2013. "Does the South African Reserve Bank follow a nonlinear interest rate reaction function?," Economic Modelling, Elsevier, vol. 35(C), pages 272-282.
    15. Ruthira Naraidoo & Leroi Raputsoane, 2015. "Financial markets and the response of monetary policy to uncertainty in South Africa," Empirical Economics, Springer, vol. 49(1), pages 255-278, August.
    16. Njindan Iyke, Bernard, 2017. "Asymmetries in Yield Curves: Some Empirical Evidence from Ghana," MPRA Paper 79155, University Library of Munich, Germany.
    17. Kasai, Ndahiriwe & Naraidoo, Ruthira, 2011. "Evaluating the forecasting performance of linear and nonlinear monetary policy rules for South Africa," MPRA Paper 40699, University Library of Munich, Germany.
    18. Ma, Yong, 2016. "Nonlinear monetary policy and macroeconomic stabilization in emerging market economies: Evidence from China," Economic Systems, Elsevier, vol. 40(3), pages 461-480.
    19. Philippe Burger, 2014. "Inflation and Market Uncertainty in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 82(4), pages 583-602, December.

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    More about this item

    Keywords

    Africa; Development Economics; Labour Market; Panel data; Quantitative Methods; Social welfare;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand

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