Estimating a Time-Varying Phillips Curve for South Africa

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1 Esimaing a Time-Varying Phillips Curve for Souh Africa Alain Kabundi* 1 Eric Schaling** Modese Some*** *Souh African Reserve Bank ** Wis Business School and VU Universiy Amserdam *** World Bank 27 Ocober The views in his paper are hose of he auhors (s) and do no necessarily represen hose of he Souh African Reserve Bank or Souh African Reserve Bank policy.

2 1. Inroducion Esimaing a Phillips Curve for Souh Africa 27/10/16 Relaion beween economic aciviy and inflaion dubbed he Phillips curve by Samuelson and Solow (1960) one of he corner sones of macroeconomics. Popular in models used by cenral banks, feauring he New Keynesian Phillips curve. See e.g. Gali (2015a), Gali e al. (2012). Blanchard e al. (2015). Oupu, unemploymen and inflaion 50 years 23 advanced economies (prior o Grea Financial Crisis) 2

3 Esimaing a Phillips Curve for Souh Africa 27/10/16 Findings: shif o inflaion argeing and sable inflaion privae agens have pu less weigh on pas inflaion and more on CB s inflaion arge. Slope of he curve has flaened over ime (demand facors have be become less prominen as inflaion drivers). This paper: Phillips curve model in unemploymen inflaion space along he lines of Chan, Koop and Poer (2015). We allow he slope of he Phillips curve, he cenral bank s perceived inflaion arge, he naural rae of unemploymen and inflaion persisence o be ime-varying. 3

4 Esimaing a Phillips Curve for Souh Africa 27/10/16 Souh African conex: Kabundi and Schaling (2013): economic agens inflaion expecaions largely depend on pas inflaion SARB has no been no enirely successful in anchoring expecaions since he adopion of he IT regime in Implici inflaion arge (consisen wih privae secor expecaions) slighly lies above he upper bound of he official IT band. 2 Resuls (his paper): In SA inflaion persisence and he slope of he Philips curve are ime-varying. 2 In addiion he SARB appears o have been focusing on he business cycle raher han inflaion sabilizaion. 4

5 Esimaing a Phillips Curve for Souh Africa 27/10/16 Inflaion persisence has decreased since he Grea Recession in 2008 in his framework his can be inerpreed as beer anchoring of inflaion expecaions since Slope parameer sligh decrease since Thus, inflaion has become less responsive o demand facors. In line wih Maheson and Savrev (2013) and Blanchard e al. (2015). 5

6 Esimaing a Phillips Curve for Souh Africa 27/10/16 2. The Unobserved Componens Model Phillips curve: n ( u u ) e = π α ε (1) π + n Variable u unobserved. ε is an inflaion (supply) shock, such as a change in oil or impor prices. Pos 2008, benign inflaion environmen ( ε < 0 ), more on ha below. Wha abou inflaion expecaions? π e = ρ ( ) * π ρ π (2) 6

7 Esimaing a Phillips Curve for Souh Africa 27/10/16 * Here π is a proxy for he SARB s inflaion arge poin, which is assumed o be ime-varying. ρ = 0 : inflaion expecaions compleely anchored o he CB s inflaion arge. CB policy fully credible. ρ = 1 : lacks credibiliy The inflaion arge is unobserved (follows so-called bounded random walk). The reduced form of he inflaion process can be wrien as: * * n ( π π ) α ( u u ) π π = ρ + ν 1 1 (4) 7

8 Esimaing a Phillips Curve for Souh Africa 27/10/16 where ν = ρ ε + * ε 3 Equaion (4) is a Phillips curve in erms of he cyclical componen of inflaion. 4 This formulaion has been adoped in previous work including Chan, Koop and Poer (2015), Sock and Wason (2007) and Sella and Sock (2013). We assume ha he parameers ρ and α, and he naural rae of unemploymen also follow (bounded) random walk processes. 3 2 We model his disurbance erm as N ( 0, h ) h ν where ( h ) log( ) + ε ~ log = h 1. 4 We assume ha he cenral bank s inflaion arge is a good proxy for rend inflaion. 8

9 Esimaing a Phillips Curve for Souh Africa 27/10/16 Our framework can be viewed as a bivariae unobserved componens model of rend inflaion and srucural unemploymen where inflaion persisence and he slope of he Phillips curve are ime-varying. Model esimaed via CKP (2015) algorihm which is a Bayesian esimaion mehod using a Markov Chain Mone Carlo drawing procedure. 9

10 Esimaing a Phillips Curve for Souh Africa 27/10/16 3. Daa Unemploymen: Quarerly unemploymen daa obained from he SARB covering 1994Q1-2014Q1. Inflaion: Year-on-year headline inflaion daa obained from he SARB. 10

11 Esimaing a Phillips Curve for Souh Africa 27/10/16 11

12 Esimaing a Phillips Curve for Souh Africa 27/10/ Empirical Resuls: Trends Esimaed inflaion arge ( π * ) relaively consan wih a mean of 5.12%. Imporan: higher han he midpoin and closer o he upper bound of 6% han o he lower bound of 3%. Esimaed band: 3.25% See Figure 2 below. π * 6.47% 12

13 Esimaing a Phillips Curve for Souh Africa 27/10/16 13

14 Esimaing a Phillips Curve for Souh Africa 27/10/16 The esimaed unemploymen rend or NAIRU is relaively fla hroughou he enire sample period, around 24.5%. 14

15 Esimaing a Phillips Curve for Souh Africa 27/10/16 15

16 Esimaing a Phillips Curve for Souh Africa 27/10/ Empirical Resuls: Parameer Esimaes Slope of he Phillips Curve n ( u u ) π + e = π α ε (1) The slope α capures he degree of he response of inflaion o excess demand facors and he exen of he shor-run rade-off faced by policy makers. Alhough a low levels he slope parameer has increased from 1994 o he mid 2000s and hen exhibis a sligh downward rend. 16

17 Esimaing a Phillips Curve for Souh Africa 27/10/16 17

18 Esimaing a Phillips Curve for Souh Africa 27/10/16 The decline in he slope parameer means ha inflaion has become less responsive o demand side facors. In he conex of our model his means ha he imporance of unemploymen as a driver of he inflaion process has decreased. Noe ha his paern of he slope parameer is in line wih he finding in mos advanced economies whereby he slope of he Phillips curve has significanly flaened paricularly afer he Grea Recession. 18

19 Esimaing a Phillips Curve for Souh Africa 27/10/16 Anchoring of Inflaion Expecaions/Inflaion Persisence π e = ρ ( ) * π ρ π (2) The parameer ρ measures he impac of pas inflaion on inflaion expecaions. The more inflaion expecaions are * anchored o he cenral bank inflaion arge levelπ, he beer he anchoring of inflaion expecaions (he lower ρ ). 19

20 Esimaing a Phillips Curve for Souh Africa 27/10/16 20

21 Esimaing a Phillips Curve for Souh Africa 27/10/16 The esimaes sugges ha he persisence parameer ρ has increased from 1994 o 2001, remained consan from 2001 ill 2008, and evenually decreased afer around This indicaes ha inflaion expecaions in Souh Africa have been relaively more anchored and sable since

22 Esimaing a Phillips Curve for Souh Africa 27/10/ Anchoring and Inflaion Persisence In our empirical specificaion inflaion persisence is idenical o he anchoring of inflaion expecaions. However, inflaion persisence is no invarian o he moneary policy regime (Lucas criique). In order o address his consider he following opimal moneary policy exercise: The cenral bank minimizes 22

23 Esimaing a Phillips Curve for Souh Africa 27/10/16 L 1 2 a = u + π, subjec o he Phillips curve and he process driving inflaion expecaions. We hen find ha lower inflaion persisence is consisen wih (1) Beer anchoring of inflaion expecaions and (2) More aggressive inflaion sabilizaion, which would lower inflaion persisence even furher. 23

24 Esimaing a Phillips Curve for Souh Africa 27/10/ Sabiliy of Inflaion: Good Policy or Good Luck? The financial crisis of 2008 followed by he recession in 2009 in Souh Africa opens he quesion of wheher improved inflaion sabiliy is he resul of good policy or good luck. This is because he global recession was marked by low levels of inflaion around he world. In our opimal moneary policy exercise more sable inflaion is associaed wih (1) A seeper slope of he Phillips curve (counerfacual o he daa) 24

25 Esimaing a Phillips Curve for Souh Africa 27/10/16 (2) Beer anchoring of inflaion expecaions (consisen wih he daa) (3) More hawkish moneary policy (consisen wih he daa) (4) Lower inflaion residual ( shocks ) or good news (consisen wih he daa). See Figure 7. 25

26 Esimaing a Phillips Curve for Souh Africa 27/10/16 26

27 Esimaing a Phillips Curve for Souh Africa 27/10/16 Boh beer anchoring and good news are consisen wih more sable inflaion. Which one is more imporan? Furher research needed. 27

28 Esimaing a Phillips Curve for Souh Africa 27/10/16 6. Conclusions and Suggesions for Furher Research We have esimaed a Phillips curve for Souh Africa using a bounded random walk model. Anchoring of expecaions, he slope of he Phillips curve, he cenral bank s inflaion arge and he naural rae of unemploymen are ime-varying. We find ha he slope of he Phillips curve has flaened since he mid 2000s paricularly afer he Grea Recession which is in line wih he findings in mos advanced counries. 28

29 Esimaing a Phillips Curve for Souh Africa 27/10/16 Furher, our esimaes indicae ha inflaion persisence has decreased from 1994 o 2001, remained consan from 2001 o 2008, and evenually decreased around However, he quesion is wheher he improvemen in inflaion sabiliy afer 2008 which coincides wih he Grea Financial crisis is a resul of beer policy or good luck. Here more work needs o be done. In his paper we have worked wih a Phillips curve in inflaion unemploymen space. However, labor marke daa in Souh Africa are somewha unreliable. Therefore in fuure work we wan o pursue our approach based on (several) 29

30 Esimaing a Phillips Curve for Souh Africa 27/10/16 measures of he oupu gap. There we will also look a a longer sample. 30

31 Esimaing a Phillips Curve for Souh Africa 27/10/16 Thank you 31

32 References Esimaing a Phillips Curve for Souh Africa 27/10/16 Chan, J, Koop, G. and Poer, S. (2015), A Bounded Model of Time Variaion in Trend Inflaion, NAIRU and he Phillips Curve, Forhcoming in Journal of Applied Economerics. Furher references in he paper 32

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