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This paper originated in work with Marcello Estevão. I am grateful for useful discussions and comments received from him. I have also benefitted from comments by Issouf Samake, Alfred Schipke, Jesus Gonzalez and Sebastian Sosa, and seminar participants at WHD. Camila Henao and Alexander Herman provided excellent research assistance.
Nicaragua is one of the three economies classified under this exchange rate arrangement. The other two are Botswana and Uzbekistan (IMF, 2011).
Our definition of sustainable growth will define the pattern for potential growth and output gap.
The growth accounting exercise could benefit from adjusting the labor force by human capital (see, for instance, Sosa, Tsounta, and Kim, 2013). Otherwise, changes in the quality of the labor force are automatically imputed to the estimated TFP measure. A caveat on the measure of TFP: changes in the use of land (not considered here) would contaminate our TFP measure.
Guatemala was not considered in the production function approach as employment data was not available. Data source: WEO. Some methodologies (HP Filter) use data up to 2017 to avoid end-of-sample bias.
To avoid end-of-sample bias data included projections up to 2017.
Exploratory analysis done using the method of optimal filtering (Pedersen, 2001, 2002) didn’t make any significance difference. For instance, for Nicaragua the optimal lambda was 181, however the loss function of the method is very flat between lambdas 100 and 300, implying very similar potential output dynamic for lambdas belonging to this interval. See Appendix B for details.
A cointegration approach was explored to generate estimates for labor and capital-output elasticities. Initial estimations show that all the series are integrated of order 1 (analysis with panel and individual unit root tests), while the Johansen Cointegration test indicates one cointegrating equation. However results from the VECM (DOLS) were not reliable in terms of the value of the estimated coefficients. This extension is left for future research.
By overheating we mean growing above potential or trend, implying a positive output gap and consequently inflationary pressures. The usual pass-through to inflation is invoked but not tested here.
This hypothesis, causality tests and the inclusion of the US growth into the model were left for future research.
Stationarity means a stable variance-covariance matrix.
Mizrach and Watkins (1999) mentioned that the EM algorithm is very robust contrasting the traditional hill climbing gradient techniques. However it is highly computer intensive, which decreased its attractiveness. For a complete evaluation of alternative univariate non linear optimization routines, see Potter (1999).
Bayes’ theorem or Bayes’ rule establish that: P[yt,st = j | Ψt–1; Г] = f(yt | st = j | Ψt–1; Г) · f(st = j | Ψt–1; Г).
Johnson (2000) evaluates alternative optimization methods, considering the traditional hill-climbing techniques and the most advanced genetic algorithms optimization methods. It is shown that genetic algorithm methods are very efficient in finding the optimal parameter vector, although computer-intensive.
Could be the case that the maximum likelihood function is infinite if some scenario’s distribution mean is equal to any observation, where the variance of this state equals to zero. Hamilton (1991) uses a “pseudo-Bayesian” procedure to solve this problem, modifying the numerator and the denominator by some constant, to avoid this indeterminacy problem in the iterative system of equations. It was not necessary to implement this modification in our algorithm as indeterminacy was not an issue.
It seems natural in our application set the number of states equals to three. In our model, each state can be easily identifiable with a specific macroeconomic policy stance: for overheating (recession), macroeconomic policy should be contractionary (expansive). Finally, under sustainable growth patterns, macroeconomic policy should aim to be neutral and under this scenario the economy is growing at its potential.
In the GAUSS code (see appendix) the iterations are indexed with the letter m. It was considered a maximum of k=10000 iterations, however convergence was achieved earlier.
Given the mixture approach, the envolvent function for these three distributions is called mixture distribution (not reported) and should integrate 1 (100 percent). Each one of the distributions reported across the country charts do not integrate 1 because there were weighted using the unconditional probability reported in the third segment of Table 2. However the envolvent function it does.
This indicator would be useful to assess monetary policies during the cycles.
Stationarity condition requires that all the roots of the AR (2) differential equation must be outside the unit circle, which implies that: |ρ2| < 1, ρ1 + ρ2 < 1, ρ1 – ρ2 < 1, simultaneously. This stationarity condition must be imposed in the Kalman procedure.
The GAUSS codes used in this section are available upon request. Convergence issues compelled us to exclude El Salvador from the sample.
The CAPDR average β is about -0.04.
These are simple averages, not reported in the table.