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Inflation analysis in the Central American Monetary Council

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Abstract

Though not working toward an imminent transition to a monetary or currency union, the Central American Monetary Council (or CMCA, from Spanish Consejo Monetario Centroamericano) serves as an institution promoting economic and financial stability among five Central American countries (Costa Rica, El Salvador, Guatemala, Honduras and Nicaragua) and the Dominican Republic. Econometric studies conducted by researchers from CMCA have mostly focused on studying inflation levels of these countries, making use of econometric tools such as VECM and cointegration. We expand the study of inflation stability in the member countries of the CMCA by adopting a long memory and fractionally integrated approach and implementing cointegration methods that have not yet been used in the study of the Central American Monetary Council. Our results first show that all the series of prices are nonstationary, with orders of integration equal to or higher than 1 in all cases. Looking at long-run equilibrium relationships among the countries, we only found strong evidence of a cointegration relationship in the case of Honduras with El Salvador. All the other vis-a-vis relationships seem to diverge in the long run. Policy implications of the results obtained are also derived in the paper.

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Notes

  1. The issue of structural breaks in the context of fractional integration has been widely developed in recent years (see, e.g., Gil-Alana 2008; Ohanissian et al. 2008). However, no theoretical works have been developed so far for fractional cointegration under the possibility of structural breaks.

  2. Some authors argue that “mean reversion” is not a proper concept in the context of nonstationary series, i.e., if the fractional differencing parameter d belongs to the interval [0.5, 1). In this case, rather than “mean reversion” we can use the concept of “finite impulse responses” or “responses disappearing in the long run”.

  3. The main advantage of the LM approach of Robinson (1994a) is that it remains valid even in nonstationary contexts (e.g., \(d=0.5\)). Moreover, it is the most efficient method in the Pitman sense against local departures from the null.

  4. Classical cointegration as widely employed in the literature occurs then if \(d=1\) and \(b=1\).

  5. Other more general definitions of fractional cointegration allow for different degrees of integration for each series (see, e.g., Marinucci and Robinson 2001). However, in a bivariate context, as is the case in the present paper, the two parent series must display the same degree of integration.

  6. \(m=(n)^{0.5}\) is the bandwidth number usually employed in most empirical applications. Always, there is a trade-off between bias and variance: The asymptotic variance is decreasing with m, while the bias is growing with m.

  7. This method requires covariance stationarity prior to the estimation. Thus, the values were estimated on the first differenced data, adding then 1 to the estimated values of d. We also performed the Abadir et al. (2007) approach that remains valid in the context of nonstationary series, and the results were completely in line with those reported with the tests of Robinson (1995a).

  8. Alternative methods for the estimation of \(\beta _{0}\) and \(\beta _{1}\) in (6) were also employed including a Narrow Band Least Squared (NBLS) estimator as proposed in Robinson (1994b) and a Fully Modified NBLS as in Nielsen and Frederiksen (2011).

  9. Non-fractional cointegration analysis was carried out by means of Engle–Granger (1987) cointegration tests. The results are displayed in Appendix 2, indicating that cointegration only takes places in three of the possible cases (Costa Rica with Nicaragua, Dominican Republic with Guatemala and Honduras with Guatemala).

  10. We only display in Table 14 the values for \(m=15\) and 16. However, qualitatively the same results were obtained for other bandwidth numbers (m = 10, ..., 20) in terms of the unit root cases.

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Author information

Authors and Affiliations

  1. ICS, NavarraCenter for International Development, Faculty of Economics, University of Navarra, Edificio Amigos, 31080, Pamplona, Spain

    Hector Carcel & Luis A. Gil-Alana

Authors
  1. Hector Carcel
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  2. Luis A. Gil-Alana
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Corresponding author

Correspondence to Luis A. Gil-Alana.

Additional information

Luis A. Gil-Alana acknowledges financial support from the Ministry of Education of Spain (ECO2014-55236). Comments from the Editor and two anonymous referees are gratefully acknowledged. This work was presented at the \(9\mathrm{th}\) Forum of Researchers from the CMCA at the Dominican Republic Central Bank on July 2015.

Appendices

Appendix 1: Unit root tests

ADF

Costa Rica

Dominican Republic

El Salvador

Guatemala

Honduras

Nicaragua

No regressors

2.7257

2.6582

5.5378

7.0306

1.8294

5.4877

Intercept

1.1572

0.43892

\(-\)1.4980

1.3702

1.1991

2.7358

Intercept and Linear Trend

\(-\)1.9927

\(-\)2.2145

2.1242

\(-\)1.5862

\(-\)1.1472

\(-\)0.97942

PP

Costa Rica

Dominican Republic

El Salvador

Guatemala

Honduras

Nicaragua

No regressors

11.9356

4.8872

5.9038

11.068

13.092

10.05

Intercept

2.8245

1.1301

\(-\)1.3870

1.6321

1.715

3.3581

Intercept and Linear Trend

\(-\)2.2658

\(-\)2.0284

\(-\)2.070

\(-\)1.5785

\(-\)1.960

\(-\)0.7391

  1. Statistic values of the corresponding unit root tests. None of them reveals evidence of rejecting the null hypothesis of a unit root

Appendix 2: Engle and Granger’s (1987) cointegration results

 

Dom. Rep.

Hond.

EL Salv.

Guatemala

Nicaragua

COSTA RICA

\(-\)2.83

\(-\)2.025

\(-\)1.633

\(-\)2.560

\(-\) 3.362

DOM. REP.

XXXXX

\(-\)2.667

\(-\)3.201

\(-\) 3.933

\(-\)2.478

HONDURAS

XXXXX

XXXXX

\(-\)2.159

\(-\) 3.610

\(-\)1.942

EL SALV.

XXXXX

XXXXX

XXXXX

\(-\)1.970

\(-\)2.397

GUATEMALA

XXXXX

XXXXX

XXXXX

XXXXX

\(-\)3.227

  1. The first two values refer to the test statistics resulting from the hypothesis that each of the series is nonstationary. The third value refers to the test statistic related to the hypothesis that the residuals of the cointegrating relationship are nonstationary
  2. In bold the cases where we can reject the null hypothesis that the residuals have a unit root, i.e., that there is no cointegration at the 5% level

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Carcel, H., Gil-Alana, L.A. Inflation analysis in the Central American Monetary Council. Empir Econ 54, 547–565 (2018). https://doi.org/10.1007/s00181-016-1223-0

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