2. MARCO TEÓRICO
2.3. GESTIÓN PEDAGÓGICA
2.3.2. Elementos que la caracterizan
Earlier attempts to determine the net-benefit of monetary union focused on the measurement of shocks symmetries among countries (Bayoumi and Eichengreen, 1992; Bini-Smaghi and Vori, 1994; Bergman, 1999; Ferrari-Filho, 2001; Ogunkola, 2001 and 2005 and Ogunkola and Jerome, 2005). These authors utilize different related models including aggregate demand and supply disturbance model (Bayoumi and Eichengreen, 1992; Bouyomi and Ostry, 1997Z), cluster analysis (see Debrun, Masson and Pattillo, 2010) and real exchange rate variance models (Vaubel, 1978; Ogunkola, 2005 and Ogunkola and Jerome, 2005). Cluster analysis involves purely determining whether group of countries in a cluster converges using the OCA properties. The limitation of this approach is instructive since it focuses only on the OCA criteria and not the direct costs of monetary union. Perhaps, the focus of this study is on costs of monetary union.
Real exchange rate variance model involves the determination of the variation in real exchange rate as a measure of asymmetric shocks. Ogunkola (2005) drawing on Von Hagen and Neumann (1994) develop a model to compare real exchange rate variation between the non-CFA countries (group A) and the CFA zone (group B) in ECOWAS. He specified a generic Real Exchange Rate (RER) model as;
, , , ,
aib t ai t abi t b t
Q P S P 3.23 Where, Qaib t, is the logarithm of the real exchange rate between country i in group A and any country in group B at time t. Pai t, is the consumer price index (CPI) of country i in group A, at time t expressed in logarithm. Sabi t, is the logarithm of the nominal exchange rate between country i‟s currency (i belonging to group A countries) and the currency of group B countries at
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time t. Pb t, is the logarithm of the CPI of country j in group B at time t. Further innovation was to obtain the variances as the observed changes in RER by estimating the model below for country
i in group A DQaib t, and any other country in group B at time t as;
, ,
aib t m m aib t
DQ
B D e 3.24 Where, Bm are the parameters to be estimated, Dmare the quarterly dummies of exchange ratesand eaib t, are the regression residuals interpreted as the seasonally adjusted RER changes. The
variances of real exchange rate between country j and k of the CFA zone is modeled as;
, ,
bjbk t m m bjbk t
DQ
B D e 3.25 Where, ebjbk t, of equation 3.25 is the residual of the regression interpreted as the seasonally adjusted RER changes. In order to eliminate the unexpected components of the seasonally adjusted RER changes, RER changes were regressed against their lags to obtain estimates using vector autoregressive method. The residuals from the autoregressive models were referred to as RER shocks and the variances as the conditional RER variances.Despite the link between the OCA properties and exchange rate, there are two caveats peculiar to this approach. First, the determination of acceptable benchmark of real exchange rate variation for comparison is a major issue. Second, the use of observe real exchange rate variance within an existing union and the comparison of RER among countries with different economic structures is defective. The thrust of this method of analysis clearly indicates that real exchange rate variation model is the same as other models determining the optimality of the OCA criteria rather than costs of monetary union.
The output demand and supply disturbance model is the most popular approach of measuring shock symmetry in the literature (Bayoumi and Eichengreen, 1992; Bayoumi and Ostry, 1997 and Bergmann, 1999). This approach suggests that asymmetric shocks arise due to output and productivity changes among members of the union. This involves determining the shocks to output and prices following the Blanchard and Quah (1989) shocks decomposition approach. Bayoumi and Eichengreen (1992) develop structural variance decomposition model on aggregate demand and supply disturbances in 11 European communities. Their central focus is
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the determination of demand and supply disturbances using price and output variation as a measure of the nature and degree of shocks symmetry in the (then) proposed European monetary union. They specified a shock model with a vector of price and output in a transformed matrix form as;
1 1 2 2 ...
t t t n t n t
X B X B X B X e
(1 B L( )1et 3.26 (1 B L( )B L( )2...)et
et D e D e1 t1 2 t2D e3 t3...
Where; et represents the residuals from the equations in the vector auto-regression and the vector B represents the estimated coefficients of the equation. It implies thatet, is composed of the residuals of a lagged values of yt and pt (output and prices) on current values of each in turn and labeled eyt and ept respectively. The residual et is then transformed into the demand and supply shockst. The outcome and nature of these shocks were then utilized to determine the movement of shocks within the region. This method, however, has its short-comings. The essential drawbacks of the Bayoumi and Eichengreen (1992) model are numerous. First, the model does not predict the dynamics of change in the historical data after monetary union has been formed. Second, the factors that account for the variances in output and prices were not taken into consideration. For instance, output is composed of imports from other regions through which business cycles from a given region may complement the variances in output and prices in the domestic country (Bergmann, 1999). The variation in output may be exemplified by productivity shocks that impact on the terms of trade.
Masson and Pattillo (2001) added that asymmetric shock in real output of WAMZ results from terms of trade shocks and fiscal policy distortion. They noted that shocks to the terms of trade are typically not well correlated, due to large differences in commodity exports and the fact that world prices of the various commodities do not move together which could make the costs of monetary union relatively high. They calculated the standard deviation of the terms of trade
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among member countries of WAMZ as shocks. This method is also fraught with the same limitation given that the focus is not to capture direct costs of monetary union.
WAMI (2005) in their influential study derived standard deviations of the terms of trade to determine the size of shocks as well as the correlation of the shocks to establish the nature of shocks among WAMZ nations. WAMI further developed a Generalized Purchasing Power Parity (G-PPP) type model based on VAR to determine whether exchange rate could actually respond to asymmetric shock given that asymmetric shocks make exchange rate a costly instrument to lose in monetary union. The structure of the model is based on determining whether a co-integration among variables exists. The G-PPP model is specified as;
1it 0 11 11t 12 12t ... 1m1mt t
r B B r B r B r 3.27 where, r1it is the real exchange rate of the countries in period t, B0is an intercept, B1itis the parameter of the co-integrating vector and t is a stationary stochastic disturbance error term.
The first procedure was the computation of real exchange rates for the countries in the form of
*
1 1
it
it it
it
r S P
P 3.28 Equation 3.28 indicates that real exchange rate is nominal exchange rate multiplied by the ratio of domestic price to foreign price over time as in the standard international finance literature.
Further innovation was to analyze the role of nominal exchange rate as a shock–absorber in the WAMZ countries by examining the response of the exchange rate to real and nominal shocks.
Drawing on the various sources of shocks, three variable VAR model associated with output, consumer price index and exchange rate were utilized and specified as;
, ,
t t t t
X Y P e 3.29 Where,Xt is the vector of the various components of shocks in a log form. Transforming these in VAR form helps to establish the effect of individual variable to aggregate idiosyncratic shocks.
0 t ( ) t 1 t
A x A L x with,t iidN(0,
) 3.30UNIVERSITY OF IBADAN LIBRARY
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Where, A, a 3 x 3 matrix of contemporaneous coefficients is a polynomial of order p in the lag operator L. The vector of t [txr trgd tcpi] represents the idiosyncratic shocks associated with each endogenous variable that drive aggregate fluctuation. The above VAR model is then used to determine how much exchange rate responds to output and price shocks in nominal and real terms as basis for evaluating the impact of losing exchange rate to asymmetric shocks. If nominal shock predominates, it is taken that nominal exchange rate may not be a potent instrument in response to macroeconomic imbalances. The idea is that if asymmetric shock prevails, then it will be costly to lose exchange rate for domestic adjustment.
Holistically, this modeling approach appears as a better approximation of the response of exchange rate to idiosyncratic shocks in monetary union as a measure of the cost of losing monetary autonomy. The model, however, did not capture the sources of the shocks itself. The link between output shocks correlation between two countries is influenced significantly by their terms of trade which also depend on the variability of exchange rate as an instrument of adjustment to domestic and foreign shocks (Mongelli, 2010 and Ricci, 2008). It is suggested that terms of trade shock is influenced by the changes in exchange rate (Obstfeld and Rogoff, 1995).
The insight provided by these models indicates that major improvement of the gaps would be to draw the link between source of shock and exchange rate.