Assessing Nonlinear Dynamics of Central Bank ...

Journal of Business Management and Economics 3: 9 September (2015).

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JOURNAL OF BUSINESS MANAGEMENT AND ECONOMICS Homepage: http://innovativejournal.in/jbme/index.php/jbme

Assessing Nonlinear Dynamics of Central Bank Reaction Function: The Case of MENA Countries Yosra Baaziz E-Mail: [email protected]

DOI: http://dx.doi.org/10.15520/jbme.2015.vol3.iss9.145.pp13-21 Abstract: Empirical evidence suggests that the Taylor rule describing the interest rate setting behavior of four keyMENA central banks (Tunisia, Egypt, Jordon and Morocco) is non-linear. This is achieved using an empirical framework that allows for regime change over time or more specifically the time variance in the model parameters. Using quarterly data from 2000:Q2 to 2014:Q3 to analyze the movement of nominal short-term interest rate of MENA central banks, we find strong evidence that the real decision-making process followed by these central banks varies from one central bank to another and that it exhibits nonlinearity. In particular, considerations about economic growth (for Morocco), inflation (for Jordon), stability of REER rate (in Egypt) and concerns about hitting the zero lower bound of the nominal interest rate (in the cases of Tunisia) seem to be the major drivers of such nonlinear pattern of monetary policy. Keywords: monetary policy, MENA central banks, nonlinear Taylor rule.

more complex price-setting behavior than those subsumed a linear specification.

INTRODUCTION The conventional framework for analyzing monetary policy rule is mainly established under the assumption that Central Bank handle in a linear manner interest rate setting. The theoretical underpinning of this linear policy rule is the linear-quadratic (L.Q) framework, stemming from the combination of a linear economic structure and a symmetric objective preferences of the policymaker. This combination leads to a linear reaction function. The Taylor rule is probably the most recognized features of this literature.

There is a growing literature that relax the quadratic preference assumption of the central bank and adopt instead asymmetric preference specification [Nobayand Peel (2003), Ruge-Murcia (2003), Dolado, Maria-Dolores andRugeMurcia (2005), Karagedik and Lees (2004), Surico (2007), Cukierman and Muscatelli (2008)…]. The not quadratic (asymmetric) preferences imply that the Central Bank is assigning different weight to upwards and downwards deviations of aggregates from their expected values in its loss function. In contrast, what is important in a quadratic loss function is especially magnitude of deviation and not its sign. Which means that the Central Bankers put equal weights on positive and negative deviations of key macroeconomic variables such as inflation and output from their target values.

After Taylor’s 1993 seminal work, a variants of Taylor-type regressions have been applied extensively in order to understand and model the behavior of monetary policy for many countries. Some Taylor Rule–type equations include a lagged value of interest rate as an additional explanatory variable. This process called “inertia” or “gradualism” tend to move policy rate in a series of small a moderate steps. [Clarida et al, 1998]. Others augmented version of the linear Taylor rule enclose other indicators in the conduction mechanism of monetary policy. In this vein, Svensson (2003) proposes an extension of the Taylor rule by incorporating the exchange rate in a rule designed for small open economies. His conclusion is in line with that of Batini et al (2001) who show that the descriptive power of the Taylor rule augmented by the exchange rate variable is higher than the standard Taylor rule for small open economies (i.e. UK).

It is also possible that the Phillips Curve can assume many forms apart from linearity. Such nonlinearity of the Phillips Curve (PC) implies that the cost of decreasing inflation would not be the same in a recession and in an expansion. Often the Phillips Curve seems to be convex, when the economy is in a recession, further decrease of the economic activity do not produce much disinflation (the costs associated with ﬁghting inﬂation is high). Schalin g (1999), Nobay and Peel (2000), Dolado et al (2004-2005) among others provide some evidence for the relevance of nonlinearity in the Phillips Curve.

A common feature of the above specifications of the Taylor rule is that they are linear specifications. However, as cited above the cogency of such rulesisthat policymakerstend to treat, symmetrically and with the same magnitude, deviations (either positive or negative) of the objective variables from their pre-determined target valuesand that the aggregate supply or Phillips curve is linear. But, in reality, it might not be the case; monetary authorities mayhave asymmetric preferences, and the Phillips curve may reflect

To be effective, allowing for nonlinear dynamics can offer a more realistic specification of the Taylor reaction function and improves the explanatory power of a dynamic pattern of central bank reaction functions during macroeconomic turbulence.While the unawareness of such possible nonlinearity response may bias the results and lead to fallacious policy implications. 13

Yosra Baaziz al, Journal of Business Management and Economics, 3 (9), September, 2015,

Consequently, this gives Central Bank impetus to reconsider their monetary policy frameworkin view of specific circumstances, such as shocks.In addition, most recent studies focused on nonlinear Taylor rules are limited to industrialized countries, especially the US (Conrad and Eife, 2012; Lee and Son, 2013; Olsen et al., 2012), the UK, ECB, Japan and Canada (KempaandWilde, 2011; Kolman, 2013).

the need to build consensus to support a policy change. We also augment the conventional Taylor rule by the real exchange rate (REER). Similarly, Svensson (2003) proposes an extension of the Taylor rule by incorporating the exchange rate in a rule designed for small open economies. His conclusion is in line with that of Batini et al (2001) who shows that the descriptive power of the Taylor rule augmented by the exchange rate is higher than the standard Taylor rule for small open economies (i.e: UK).

In this respect, the aim of this paper is to investigate more in-depth the possible presences of nonlinear dynamics using the Smooth Transition Regression (STR) methodology advocated by Granger and Terasvirta (1993).We established to that purpose a list offour MENA countries presenting a great similarity in terms of economic structure, who are, Tunisia, Egypt, Jordan and Morocco.

There are several reasons to include the REER in the MENA reaction function. The constant real effective exchange rate rule provides a buffer against shocks and helps to reduce volatility in interest rate. This policy is partly out of concerns for the international competitiveness of MENA manufacturing exports and in particular for a rise in the index implies a fall in competitiveness and vice versa.

The road map of the paper is as follow. Section 2 describes the econometric methodology. In section 3, we present our dataset and we review the empirical result. The final section concludes.

When dealing with capital flows the authorities confront a trade-off between currency appreciation and depreciation. The former has a negative impact of the competitiveness of exports while depreciation induces losses to MENA central banksby increasing the country massive debt burden, which is reflected in a higher debt service. Thus, the concept of REER goes beyond the weighted average of currencies to greater significance forMENA policymakers where sectors are expected to contribute more to the growth of the economy. Indeed, many researchers argue that real effective exchange rate has important effects not only on the general economic performance of a country and its international competitiveness but also on the different sectors of the economy.

ECONOMETRIC METHODOLOGY A Taylor Rule-type equation have shown to be a useful formulation of monetary policy to understand, in simple terms, the interest rate setting behavior of Central Bank across the world. Its original form can be specified as follows: 𝑖𝑖𝑡𝑡 = 𝑟𝑟̅𝑡𝑡 + 𝜋𝜋 ∗ + 𝑏𝑏𝜋𝜋 (𝜋𝜋𝑡𝑡 − 𝜋𝜋 ∗ ) + 𝑏𝑏𝑦𝑦 (𝑦𝑦𝑡𝑡 − 𝑦𝑦𝑡𝑡∗ ) (1) 𝑖𝑖 𝑡𝑡 represents the nominal short term interest rate, and 𝑟𝑟̅𝑡𝑡 represents the equilibrium real interest rate. 𝜋𝜋𝑡𝑡 is the inflation rate at time t calculated from the consumer price index (CPI), reflecting cost of acquiring a fixed basket of goods and services by an average consumer. (𝑦𝑦𝑡𝑡 − 𝑦𝑦𝑡𝑡∗ )refers to the output gap, defined as the difference between actual output and potential output, which is measured using the Hodrick–Prescott (1997)'s filter. 𝑏𝑏𝜋𝜋 indicates the sensitivity of the interest rate policy to deviations of inflation from its target. 𝑏𝑏𝑦𝑦 represents the coefficient of the reaction of the central bank to the output gap.

Given the importance of exchange rate especially in the context of a small open economy, it is widely agreed to introduce it as an explanatory variable in the Taylor rule. To sum up, the inclusion of the REER is consistent with the objectives of MENA central banksin terms of maintaining price stability. The model thus becomes: 𝑖𝑖𝑡𝑡 = 𝑟𝑟̅𝑡𝑡 + 𝜋𝜋 ∗ + 𝜌𝜌𝑖𝑖𝑡𝑡−1 + 𝑏𝑏𝜋𝜋 (𝜋𝜋𝑡𝑡 − 𝜋𝜋 ∗ ) + 𝑏𝑏𝑦𝑦 (𝑦𝑦𝑡𝑡 − 𝑦𝑦𝑡𝑡∗ ) + (2) 𝑏𝑏𝑞𝑞 𝑞𝑞𝑡𝑡 + 𝑢𝑢2.𝑡𝑡

The rule recommends that short-term interest rate should rise if inflation 𝜋𝜋𝑡𝑡 rise above its predetermined target or if output 𝑦𝑦𝑡𝑡 increase above its potential level 𝑦𝑦𝑡𝑡∗ .

qt refers to the REER. bq is the coefficient of reaction of the Central Bank to change in REER and ρ measures the degree of interest rate smoothing.

In equilibrium, the deviation of inflation and output from their target values is zero and, therefore, the nominal short term interest rate 𝑖𝑖𝑡𝑡 is the sum of the equilibrium real rate 𝑟𝑟̅𝑡𝑡 plus the target value of inflation.

Indeed, in a context dominated by uncertainty, the evolution of monetary policy setting over longer period is structurally unstable. The failure to take into account these changes may bias the results. This opens the way to seek alternative policy rules that can provide better results even through macroeconomic structural changes occur continuously and/or the central bank has imperfect knowledge of the dynamic of the economy. Therefore, the recent literature tries to take nonlinearity into account. To explain this nonlinear behavior, the common solutions used in the literature are the Markov-switching (MS) model and the smooth transition regression (STR) model.Moreover, the STR models have several advantages over the Markov-switching regime models by allowing gradual evolution of the model’s coefficients and do not impose restrictions on the way parameters vary over time. If

Some studies extend this linear rule by considering the effect of additional variables in the conduct of monetary policy. Following Clarida et al (1998) andRudebush (2002) among others, we augment the baseline specification by introducing the lagged interest rate that takes into account the inertia of monetary policy. Clarida et al (1998) find that the interest rate smoothing parameter enters significantly in the Taylor rule. In fact, the reason of doing so is mainly due to fear to disturbing capital markets which are too sensitive to policy changes and could create financial instability via investors herding behavior, or 14


a linear functional form were correct, the STR would exclude nonlinear effects and the linear specification outperforms the nonlinear one. Instead, if some nonlinearity exists, the STR technique allows one to choose both the appropriate switching variable and type of the transition function without entailing restrictions on the speed, the intensity and the persistence of the changes.Consequently, we follow the STR approach in the current paper.

shows that this identification problem can be circumvented by approximating the transition function with a third Taylor expansion around γ = 0 . After reparametrization and rearrangement the approximation yields the following regression:

~ ~ ~ ~ it = δ 0 + δ ' Z t + β 1' Z t S t + β 2' Z t S t2 + β 3' Z t S t3 + v t

(3)

Following the work of Teräsvirta(1998), the standard tworegime LSTRfor a nonlinear Taylor rule could be derived as follows: it = ϕZ t + θZ t G (γ , c, St ) + ut ,t=1,…, T(2)

Accordingly, the null hypothesis of linearity becomes:

β 1' = β 2' = β 3' = 0

and a LM-type test with Fdistribution is used to test this null hypothesis of linearity. Teräsvirta (1998) suggests a linearity test for each candidate transition variable. In terms of this approach, the variable with the lowest p-value (strongest rejection of linearity) is chosen as the transition variable. Once the linearity is rejected against LSTR-type nonlinearity we follow Teräsvirtaet al (2004) and consider the following three tests:

  γ k ( S − c ) )− 1 with γ > 0 . k ∏ t   σ S t k = 1

where G ( γ , c , St ) = ( 1 + exp−

Z t = ( w't , x't ) is a vector of regressors including the

xt = (1, x1t ,..., xkt ) dependent variable, wt = ( yt −1 ,..., yt − p ) .

exogenous

variables,

and

lagged

H 02 : β 3 = 0 , H 03 : β 2 =

0

β3

= 0 and H 04 : β 1 =

0

β2

ϕ = ( ϕ 0 ,ϕ 1 ,...,ϕ n ) , θ = ( θ 0 ,θ 1 ,...,θ m )

The above test statistics are labeled F2 , F3 and F4 ,

represent (( n + 1 ) * 1 ) and (( m + 1 ) * 1 ) parameter vectors in the linear and nonlinear parts of the model, respectively.

respectively and are used to determine the number of regime shifts among LSTR1 and LSTR2. The decision rule

The vectors

is that the LSTR1 is chosen if the p-value of H 04 or H 02 is the lowest. Conversely, the LSTR2 is selected if the pvalue of H 03 is the lowest.

The disturbance term is iid with zero mean and constant variance, ut → iidN (θ , σ ) . 2

G ( γ , c , S t ) is the transition function bounded by 0 and 1, and depends upon the transition variable S t , the slope parameter γ and the location parameter c .

The chosen model can then be estimated and evaluated as outlined in Eitreheim and Teräsvirta (1996). Several misspecification tests are used in the STR literature, such as test of no remaining nonlinearity, no residual autocorrelation and parameter constancy. These tests will be carried out in the empirical section.

In terms of the above equation, the transition variable increases in tandem with the logistic function. VanDijk et al. (2002)demonstrate that as St → 0 (or ∞) , the transition function becomes abrupt, such that the model becomes indistinguishable from the linear autoregressive model.

ESTIMATION RESULTS Data Description: As we detail in the introduction, our empirical analysis focuses on MENA countries: Tunisia, Egypt, Jordan and Morocco. Our data set includes quarterly observations, obtained from Datastream, available from the countries under examination for the interest rate, inflation, industrial production and the REER. The sample periods differ slightly across countriesand covers the period2000. Q2→2014.Q3. The table1 provides a detailed description of Sample size used in the analysis.

Teräsvirta (1994) proposes some procedures to build an STR model; these include linearity test, estimation and evaluation of the model. A linearity test is performed for the purpose of choosing the appropriate transition variable S t and the most suitable form of the transition function among LSTR1 (with a single transition variable), LSTR2 (with two transition variables) and ESTR. In fact, the null hypothesis of linearity can be formulated as follows: The null hypothesis of linearity consists in testing H 0 : θ = 0 in Equation (2) against the alternative hypothesis of nonlinearity:

Table 1 : Sample size

H1 : θ ≠ 0 .

Luukkonen et al. (1988) argue that testing for linearity is not a straightforward task, due to the fact that the model is only identified under the alternative of nonlinearity. In particular, the parameters c and θ are nuisance parameters and are not present under the null of linearity. Teräsvirta (1998) 15

Country

Obs

Sampleperiod

Tunisia

39

2004. Q4→2014.Q3

Jordan

57

2000. Q2→2014.Q3

Morocco

24

2008. Q4→2014.Q2

Egypt

44

2002. Q3→2013.Q2

= β3 =


stationarity for inflation, REER and interest rate series for Tunisia, Jordan and Morocco respectively. That means these series have an unit root problem. Except for output gap,which was found to be stationary in level in all counties. There is no need to difference them when estimating.

Unit-root test: In order to examine the time-series properties of our data we conduct panel unit root tests. Then, on the basis of the results reported in table 2, it appears Augmented DickeyFuller test cannot reject the null hypothesis of non

Table 2: Unit Root Test Statistics Test

Statistic Tunisia

Output-gap

Inflation REER Interest rate

Jordan

Morocco

Egypt

ADF

-4.5908***

-4.1225***

-3.423***

-3.5878***

KPSS

0.0712***

0.0332***

0.0676***

0.046***

ADF KPSS ADF KPSS ADF

-0.4352 1.2257 -2.4265*** 0.5108* -1.6906*

-9.8435*** 0.1232*** 0.4556 0.4932* -1.9445*

-2.5039*** 0.2638*** -0.5666 0.6411 -0.8577

-0.7317 0.8652 -1.7799*** 0. 312*** -1.8692*

KPSS

0.727*

0.1779*

0.7906

0.288***

Note:This table reports the results of ADF and KPSSstationarity tests. it, πt, yt and qtstand for interest rate, inflation rate, output gap and exchange rate, respectively. 1% , 5% and 10% Critical values for the ADF test are -2.56 , -1.94 and -1.62whereas those of the KPSS test are 0.347,0.463 and 0.739, respectively. ***,** and * indicate significance at the 1%, 5% and 10% significance levels respectively.

REER seems to be the major determinant of the change in the conduct of Egyptianmonetary policy.Finally, for Morocco, the threshold variable is the output-gap. In all cases, the selected transition variable provides the lowest p-value of the computed F-statistics for the rejection of the null hypothesis of linearity. Thus, the parameter set changes whenever theseselected transition variables drop below or rise above some threshold value.Our results confirm once again our suggestions regarding the heterogeneity associated with theseMENA countries.

After examining time properties of different series, we now turn to the methodology. Empirical Results: The evidence from the estimation of the nonlinear monetary rules is presented in Table 3. The results for Tunisia, Egypt, Jordan and Morocco are reported in Columns 1 to 4, respectively, while Figure 1 plots the estimated transition functions and provides evidence that it is possible to characterize the behavior of MENA central banks as a two-state Taylor rule.

The test for the choice of the transition function is also presented in the table3; it indicates that an LSTR1 model fits better the monetary policy conduct for MENA central banks. This model is often used to capture the asymmetric behavior of the business cycle in the sensethat booms and busts are characterized by different dynamics [Teräsvirta and Anderson, 1992].

In general, results are robust in challenging the assumption of linearity that prevailed the previous studies of these economies and indicate that the monetary policy followed by theseMENA Central Banks can best be modelled in a non-linear fashion.

By looking at the estimated transition functions, a stronger response regime takes place when the output gap is positive, in the cases of Morocco, when the inflation rate is above the threshold level, for Jordan, when there is a large rise in the REER rate forEgypt and when the past interest rate increases beyond the threshold value for Tunisia.

In practice, linearity was tested for several transition variables for each country under consideration. Our findings show that there is strong evidence against the linear specification of the Taylor rule and that the past interest rate is likely to be responsible for nonlinear behavior of BCT.While for Jordan,the threshold variable is inflation.The

Table 3 confirms our conjectures; the estimates clearly reveal the existence of two regimes. It clearly shows the ex²istence of a special regime that applies only to unusual economic conditions, in response to which central banks change their usual policy conduct.

16


Figure 1: Transition Functions for Tunisia, Egypt, Morocco and Jordan

The empirical evidence strongly corroborate the idea of a nonlinear formulation of the monetary policy rule as both the transition speed (𝜆𝜆) and the threshold parameter (c) are statistically significant for all MENA countries included in our sample.

This is consistent with Bruggemann and Riedel (2011) and Alcidi et al (2011) identification of transition variable. They identify and use the lagged interest rate as a threshold variable. Thus the switching between regimes is controlled by concerns about hitting the zero lower bound of the nominal interest rate where policy instrument does not respond in the usual way to its determinants.

For Tunisia,The empirical work that is presented in Table 3 clearly shows that the monetary policy followed by the BCT can be described by a nonlinear Taylor ruleand concerns about hitting the zero lower bound of the nominal interest rate seem to be the major determinant of the change in the conduct of monetary policy across regimes. In particular, when the lagged interest rateis above the target level of 4.4028%, monetary policy enters the liquidity trap regime where the policy instrument does not respond in the usual way to its determinants.These special regimes require disconnection from the automatic pilot rule of the Central Bank and policymakers should extensively use their judgments to make decision.

Tunisia is not excluded as its economy was also mired in a slump especially after the revolution of 2011. The first post revolution days were characterized by simultaneous sharp drops in demand and supply, accompanied by serious disturbances in the production system (sit-in, social unrest with strikes). Similarly, this period was marked by a sharp decline in foreign currency assets, down under the combined effect of the fall in the number of tourists visiting the country and exports of phosphates.

17

Yosra Baaziz al, Journal of Business Management and Economics, 3 (9), September, 2015, Table 3: Nonlinear monetary policy rules: Evidence for the MENA central banks (Tunisia, Jordan, Morocco and Egypt) Tunisia

Jordan

Morocco

Egypt

Constant

4.59095*** [1.8673]

0.366 [0.3612]

4.9418*** [0.000]

5.75043** [3.5105]

Inflation

0.5332** [0.1572]

0.037 [0.066]

0.1033 [0.0687]

0.775*** [0.234]

Output-gap

0.02381** [0.0168]

0.0164*** [0.008]

-0.10424*** [0.2186]

0.0721*** [0.0369]

REER

-0.0746*** [0.03]

-0.0139 [0.0349]

0.0985* [2.062]

-0.1276** [0.024]

Interest rate (t-1)

1.552*** [0.4473]

0.873*** [0.0645]

0.395* [0.4021]

0.6662*** [0.2143]

Constant

-5.0472*** [1.8968]

0.0438 [0.61]

5.354* [3.4078]

-4.6947 [3.6625]

Inflation

0.53201 [72.4067]

0.325** [0.0358]

0.508 [0.2509]

0.608*** [0.249]

Output-gap

-0.0108 [0.0177]

0.0185*** [0.0215]

0.72449** [0.2071]

0.07506*** [0.0196]

REER

0.08502*** [0.0306]

-0.01952*** [0.0251]

-0.3828** [0.0549]

0.1784*** [0.044]

Interest rate (t-1)

0.839*** [0.4549]

0.10204 [0.61]

0.588*** [0.000]

0.3725* [0.2218]

c

4.4028*** [0.0686]

3.7997*** [0.00]

-3.4317*** [0.00]

110.7319*** [0.022]

𝜸𝜸

8.133* [45.77]

10.00** [1.0395]

0.5*** [0.1079]

10.00* [0.326]

𝑆𝑆𝑡𝑡

Interest rate (t1)

Inflation

Output-gap

REER

𝑨𝑨𝑨𝑨𝑨𝑨

-3.305

-1.93

-6.5168

-1.663

𝑅𝑅2

94.68

94.98

87.71

82.74

16.3528 (0.0376)

5.3506 (0.7195)

8.6587 (0.3719)

3.136 (0.9255)

33.4632 (0.00)

0.7312 (0.6938)

0.6795 (0.712)

25.414 (0.00)

Linear part

Nonlinear part

𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴(8) 𝐽𝐽𝐽𝐽𝐽𝐽𝐽𝐽𝐽𝐽𝐽𝐽 − 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵

Note: This table reports the estimates of the nonlinear Taylor rule. Standard errors are between [ ] and p-values are between(). ***, ** and * indicate significance at the respective significance levels 1%, 5% and 10%.

All these factors have led to a major shock reflected through the exceptional decline in real GDP growth. This brings the Tunisian economy to move into a situation of liquidity trap when cuts in policy rate seem to have little or no impact of

hick-starting demand and output [reduce twice its interest rate to 50 basis points each in June and September 2011]. This decline in interest rates failed to encourage the economic actors to lend money. These actors continue to be 18


deaf to calls for consumption and investment as a result of growing anxiety about the future.

regime (recession), which clearly shows the existence of a special regime that applies only to unusual economic conditions, in response to which central bankers change their usual policy conduct.

The empirical findings suggest that the monetary policy followed by Egyptian central bank exhibits nonlinearity and the dynamics of REER seems to be the main driver of monetary policy. We attribute this finding to the sequence of adverse, supply shocks that hit the Egyptian economy. During, the time spamthat we consider in this paper, Egypt underwent several shocks: the global financial crisis in 2008 and the effect of political instability with the onset of the revolution.

Finally, in the case of Jordan, the empirical evidence provides support of a nonlinear specification and it provides evidence that the Jordanian policy-makers pay close attention to the inflation rate when establishing interestrate.These features are in line with the main goal of the Bank of Jordan. Building on this view, it is possible to characterize the behavior of the Jordanian Central Bank as two-state Taylor rule with different coefficients depending on whether the inflation rateis below or above the estimated threshold value of 3.7997%.Our results are consistentwith those ofPeterson (2007).This later in his paper lays out a framework for how the Fed handle interest rate setting during the 1985–2005 period using the logisticsmooth transition regression (LSTR)model that was developed earlier by Teräsvirta (1998). The study notes the presence of nonlinearity and, more importantly, argues that once inflation approaches a certain threshold, the Fed begins to react aggressively to inflation.

When the world financial crisis began, central bankers had expectations regarding its extent. Unfortunately, a series ofconsequential shocks to the world economy, such as the Lehman Brothers bankruptcy, the AIG flop and the crush of the Reserve Primary Fund (a large money market mutual fund in the US), spoiled these expectations, leading to the demolition of the financial system and the economy (Mishkin, 2011). Indeed, after the revolution the political instability in the country had increased uncertainty and led to a systematic capital outflow the tourism sector, which prior the revolution had represented 11% of the country’s GDP has been severely affected as tourism income plunged by 9 percent after January, 25 revolution which took their toll on the Egyptian foreign exchange reserve.

Summing up,the nonlinear Taylor rule appears to be the appropriate framework to characterize the MENA Central Banks behavior and the real decision-making process can be approximated by a two-state Taylor rule, with different coefficients depending on whether the selected transition variableis below or above an estimated threshold value.In particular, while the dynamics of inflation seem to be the major development driving the behavior of the monetary authority in Jordan, considerations about economic growth are crucial for Morocco, concerns about hitting the zero lower bound of the nominal interest rateare key in Tunisia and vigilance towards the real effective exchange rate misalignment would be determinant in monetary authorities’ mindset shifting for Egypt.

Our results are consistent with those of Mora and Carvalho (2010), whose findings support evidence of nonlinear Taylor rule for Mexico. The authors consider several specifications of the Taylor rule to examine how monetary policy is conducted in the sevenlargest economies in Latin America. They show that the exchange rate is relevant variable for the interest rate in Mexico,establishing the monetary policy rate in Chile, Columbia and Venezuela. In the case of Morocco, The output gap is chosen to be the threshold variable because of theimportant weight that the central bank places on this variable.The reaction of the Morocco's central banktoshocks on these variables changes depending on whether the level of the output gap is above or below the threshold value of -3.4317.

In order to check the robustness of our findings, we have finally applied several misspecification tests (Table 3).The results of diagnostic tests indicate the absence of an ARCH effect in the residuals for all countries under consideration (except for Tunisia). Moreover, testing for omitted nonlinearity in the estimation results shows that some of the nonlinearity was absorbed by an LSTR model with two regimes. So, we come to find evidence for the validity of our empirical nonlinear model. In addition, the parameter constancy test shows that the parameters do not vary over time. All in all, the findings reflect thatthe monetary policy followed by the MENA Central Banks exhibits some nonlinearity.

Our results are consistentwith those of Castro (2011), whose findings support evidence of a nonlinear Taylor rule for the European Central Bank and for the Bank of England.He also shows that the Fed's monetary policy is better described by a linear Taylor rule. Based on these estimates,we can affirm the existence of two regimes of monetary policy that depend on the values of the output gap: an initial regime that is close to the linear specification and a second region, calledthe low output gap

19

Yosra Baaziz al, Journal of Business Management and Economics, 3 (9), September, 2015, Table 4: Robustness Tests Tunisia

Jordan

Morocco

Egypt

No Remaining Nonlinearity Transition Variable F

1.121*10-2

4.3364*10-1

4.8988*10-2

9.7272*10-3

F2

1.6753*10-1

8.478*10-1

6.2157*10-4

2.0861*10-2

F3

2.555*10-3

4.678*10-1

1.23*10-4

5.0462*10-1

F4

3.899*10-1

1.5625*10-1

8.5827*10-1

2.1592*10-2

Parameter Constancy Test H1

8.7929 (0.001)

2.358 (0.001)

4.0586 (0.0148)

1.7544 (0.144)

H2

7.305 (0.0024)

3.6827 (0.0024)

3.3618 (0.0206)

7.3009 (0.0004)

1.7673 (0.5408)

4.1534 (0.0012)

3.992 (0.0101)

9.3841 (0.0102)

H3

Note: This table reports the diagnostic tests of no remaining linearity and parameter constancy.p-values are between ().

CONCLUDING REMARKS This paper investigates nonlinear dynamics of Central Bank reaction function for four keyMENA countries: Tunisia, Egypt, Jordan and Morocco. More specifically, we extend the linear Taylor rule to a regime-switching framework, where the transition from one regimeto another occurs in a smoothway, using a logistic smooth transition regression (LSTR) approach. Using quarterly data from 2000:Q2 to 2014:Q3, we confirm the occurrence of nonlinearity in the Taylor rulefor all countries included in our sample.In particular, considerations about economic growth (for Morocco), inflation (for Jordan), stability of REER rate (in Egypt) andconcerns about hitting the zero lower bound of the nominal interest rate(in the cases of Tunisia) seem to be the major drivers of such nonlinear pattern of monetary policy. So far, this paper has provided evidence that it is possible to characterize the behavior of MENA central banks as a twostate Taylor rule, with different coefficients depending on whether the transition variable is below or above an estimated threshold value. Overall, the evolution of coefficients portraits a richer picture of MENA conduct andconfirm once again our suggestions regarding the heterogeneity associated with thesecountries.

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