El Salvador: Selected Issues

Abstract

El Salvador: Selected Issues

El Salvador: Potential Growth1

This paper constructs estimates of potential output growth and the output gap for El Salvador, and compares it to other Central American countries. It examines potential growth before and in the aftermath of the global financial crisis its likely trajectory in the medium-term. Findings are that pre-crisis potential growth was the lowest in the region, and it declined after the crisis mostly due to lower capital accumulation and persistent negative TFP growth, which have not recovered to pre-crisis rates. Looking forward, potential growth is expected to reach 1.9 percent in the medium-term due to constraints to capital and employment growth, and low TFP growth. There are no indications of significant economic slack in 2015.

1. Pre-crisis potential growth in El Salvador was well below that of other Central American economies. Potential growth was 2.6 percent during 2001–07, significantly lower than other Central American economies where potential growth was at least 3.4 percent (and as high as 5.8 percent in Panama). Lower potential growth in El Salvador reflected lower capital and employment growth, and negative TFP growth. Notably, strong TFP growth explained high potential growth in Costa Rica, the Dominican Republic, and Panama, as well as high capital stock growth in the first two counties, and high employment growth in Costa Rica. Robust potential growth in Honduras was explained by rapid capital accumulation and strong employment growth.

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Determinants of Potential Output Growth

(% and contributions to potential output growth, average for the period)

Citation: IMF Staff Country Reports 2016, 209; 10.5089/9781498342346.002.A002

Source: IMF staff estimates.

2. TFP growth was persistently negative in El Salvador in the years before the crisis. This was the case in Guatemala also, and productivity growth in Honduras and Nicaragua was not high either compared to Costa Rica, the Dominican Republic and Panama, which saw significant improvements in TFP growth. Productivity shortfalls in El Salvador may reflect, among other factors, lags in investment in R&D and adoption and development of new technologies. Lower human capital growth (El Salvador saw a significant decline in human capital growth from 2001 to 2007) and migration of high-skilled workers seem to have hampered TFP growth. Productivity gains were also hindered by a lack of competition and high market concentration. Weak business environment, including political and economic uncertainty, poor security, high red tape and corruption, lack of legal/judicial stability, high costs of infrastructure and poor quality are additional factors.

3. Along with negative productivity, capital stock growth was among the lowest in the region during 2001–07. The growth of the capital stock was on average 4.9 percent, compared to over 5.2 percent in Costa Rica, the Dominican Republic, Guatemala, and Honduras. Capital goods imports were booming in these economies in the mid-2000s and as a consequence there was an overhauling of physical capital (this was not the case in El Salvador and Nicaragua).

4. Pre-crisis employment growth lagged behind neighboring countries. It was about 2 percent during 2001–07, likely due to a decline in the labor force participation given continuous outward migration. Employment growth in Costa Rica, Guatemala, and Honduras was at least 3.3 percent, while the Dominican Republic, Nicaragua and Panama saw lower rates below 3 percent, but higher than in El Salvador.

5. The global financial crisis had a substantial negative impact on growth in Central America, including in El Salvador. Potential growth declined from 2.6 percent to 1 percent in El Salvador in the aftermath of the crisis (i.e. from 2001–07 to 2008–10). Most other Central American economies experienced significant declines as well. Notably, potential growth declined by over 1 percentage point in Costa Rica, Honduras, and Nicaragua, and less than 1 percentage point in the Dominican Republic and Guatemala. Only Panama saw an increase in potential growth by 2.5 percentage points. While some countries (Costa Rica, the Dominican Republic, Honduras, and El Salvador) saw a recovery in potential growth in 2011–14, the rates remain lower compared to their pre-crisis rates. Only Nicaragua saw a significant boost in potential growth in 2011–14 that surpasses pre-crisis rates.

6. Large declines in capital stock growth accounted for most of the decline in potential growth in the region after the crisis. In El Salvador, capital growth dropped by 2 percentage points from 2001–07 to 2008–10, the largest drop in Central America (with Guatemala being the only country experiencing a similar drop). Honduras and Nicaragua experienced falls in capital growth in the magnitude of 1 percentage point, while the other countries’ capital growth was not affected by the crisis, or in the case of Panama, the expansion of the canal brought about an expansion in capital growth (of almost 5 percentage points). In several Central American economies, capital growth continued its downward trend in 2011–14 (i.e. El Salvador, Guatemala, and Honduras). The Dominican Republic saw a significant fall in capital growth in 2011–14 after the increase it experienced from 2001–07 to 2008–10. Only Nicaragua saw a significant boost in capital growth in 2011–14 that surpassed pre-crisis rates.

7. TFP growth declined after the crisis, but has since recovered in some countries. TFP growth declined in many Central American economies by up to 1.4 percentage points from 2001–07 to 2008–10, but has recovered and surpassed pre-crisis rates in the Dominican Republic and Nicaragua (and in Guatemala where it turned slightly positive from negative pre-crisis rates) in 2011–14. Its contribution to potential growth is 2 percent in the Dominican Republic and 3.5 percent in Panama. These two latter countries have the highest TFP growth in the region. In El Salvador, however, TFP growth continued at similar negative rates following the crisis, which worsened thereafter in 2011–14 (reaching negative 1 percent). In Costa Rica and Honduras, TFP growth has also not recovered to pre-crisis rates.

8. Employment growth declined significantly in some Central American economies after the crisis. It declined by about 1.4 percentage points in El Salvador, likely due to a lower labor force participation rate due to continued migration. However, it has recovered and surpassed pre-crisis rates, reaching 2.5 percent in 2011–14. Within the Central American region, Guatemala experienced a continued increase throughout the 2001–14 period, while other economies went through important declines in employment growth after the crisis (e.g. in Costa Rica, the Dominican Republic, and Panama). El Salvador’s employment growth is still lagging behind Guatemala, Honduras, and Nicaragua.

9. From a cyclical perspective, El Salvador’s economy is assessed to be operating slightly below potential in 2014–15. Core inflation has fallen since 2012 and has been negative more recently, and labor market conditions appear to be improving. The output gap is negative at 0.5 percent of potential output (having shrunk from negative 1 percent in 2013), while the unemployment gap is negative at 0.4 percent of the NAIRU in 2015, both having shrunk since the crisis when the output and unemployment gaps turned substantially negative. There was significant slack immediately after the crisis (the output gap turned from 1 percent to −2.5 percent).

A02ufig2

Output gap

(% of potential output)

Citation: IMF Staff Country Reports 2016, 209; 10.5089/9781498342346.002.A002

Source: IMF staff estimates.
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SLV: Output gap

(% of potential output)

Citation: IMF Staff Country Reports 2016, 209; 10.5089/9781498342346.002.A002

Source: IMF staff estimates.

10. Potential growth in El Salvador is likely to remain below pre-crisis rates in the medium term. Prospects for the components of potential growth—labor, capital, and TFP—are considered over the period from 2015 to 2020. The scenario analysis builds on the analysis of potential growth until 2014 and extends it, based on projected demographic patterns, prospects for capital growth, and improvements in TFP growth. These scenarios are subject to significant uncertainty, as a number of country-specific factors could influence potential growth, and the evolution of TFP growth in the medium term. Finally, these scenarios do not assume policy changes that could boost potential growth in the medium term.

11. These scenarios for the components imply that potential growth in El Salvador is likely to reach 1.8 percent in the medium term. The working-age population growth is expected to decline, while labor force participation is expected to increase by less, resulting in slightly lower employment growth. Investment-to-capital ratios have not changed much since 2011 and are likely to continue at the same rates. This is because of less favorable external financing conditions, and weaknesses in the institutional, regulatory, and legal environment. TFP growth is expected to remain below pre-crisis rates over the next six years, and is projected at the 2002-2014 average growth rates, also consistent with more sluggish potential growth in advanced economies, and thus no positive spillovers from them.

A02ufig4

SLV: Components of Potential Output Growth (%)

Citation: IMF Staff Country Reports 2016, 209; 10.5089/9781498342346.002.A002

Source: IMF staff estimates.

12. If, on the other hand, TFP performance improves significantly, the impact on potential growth could be substantial. Relative to the region and emerging markets, El Salvador performs poorly in various facets of innovation such as spending on R&D, tertiary enrollment rates, number of patent applications, FDI inflows, ease of protecting investors, knowledge-intensive employment, and creative services exports. Enhancing R&D/technological diffusion will require strengthening institutions, human capital and research, achieving higher business and market sophistication, and competition in product and labor markets. Important improvements in the quality of schooling are needed to enhance human capital.

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Global Innovation Index, 2015

Citation: IMF Staff Country Reports 2016, 209; 10.5089/9781498342346.002.A002

Source: Global Innovation Index.

13. Policies should also prioritize mobilizing domestic savings to invest and build a higher capital stock. Investment-to-capital ratios are lowest in El Salvador compared to the region, and much lower compared to emerging markets. Attracting private domestic and foreign investment will require reducing policy uncertainties, strengthening institutions to secure property rights and reduce red tape and corruption, ensuring legal and judicial stability, and improving security. Higher and more efficient public investment is critical to address infrastructure deficiencies.

14. Removing labor market rigidities and reducing informality will improve labor productivity. World Economic Forum-based surveys suggest certain labor market rigidities in El Salvador, including inefficiencies in wage determination, alignment of pay with productivity, capacity to retain talent, mismatches between skills and jobs. Facilitating access to social security systems, reducing tax distortions, simplifying tax filing and business licensing procedures are reforms that would help reduce informality.

Annex I. Methodology

The multivariate filter approach specified in this selected issues paper requires data on three observable variables: real GDP growth, CPI inflation, and the unemployment rate. Annual data is used for these variables for the 7 countries considered. In this section, we present the equations which relate these three observable variables to the latent variables in the model. Parameter values and the variances of shock terms for these equations are estimated using Bayesian estimation techniques.

In the model, the output gap is defined as the deviation of real GDP, in log terms (Y), from its potential level (Y¯):

(1)y=YY¯

The stochastic process for output (real GDP) is comprised of three equations, and subject to three types of shocks:

(2)Y¯t=Y¯t1+Gt|+ɛtY¯
(3)Gt=θGSS+(1θ)Gt1+ɛtG
(4)yt=φyt1+ɛty

The level of potential output (Y¯t) evolves according to potential growth (Gt) and a level-shock term (ɛtY¯). Potential growth is also subject to shocks (ɛtG), with their impact fading gradually according to the parameter θ (with lower values entailing a slower adjustment back to the steady-state growth rate following a shock). Finally, the output-gap is also subject to shocks (ɛty), which are effectively demand shocks.

All else equal, output would be expected to follow its steady-state path, which is shown above by the solid blue line (which has a slope of Gss). However, shocks to: the level of potential (ɛtY¯); the growth rate of potential (ɛtG); or the output gap (ɛty), can cause output to deviate from this initial steady-state path over time. As shown by the dashed blue line, a shock to the level of potential output in any given period will cause output to be permanently higher (or lower) than its initial steady-state path. Similarly, shocks to the growth rate of potential, illustrated by the dashed red line, can cause the growth rate of output to be higher temporarily, before ultimately slowing back to the steady-state growth rate (note that this would still entail a higher level of output). And, finally, shocks to the output gap would cause only a temporary deviation of output from potential, as shown by the dashed green line.

In order to help identify the three aforementioned output shock terms, a Phillips Curve equation for inflation is added, which links the evolution of the output gap (an unobservable variable) to observable data on inflation according to the process:

(5)πt=λπt+1+(1λ)πt1+βyt+ɛtπ

Finally, equations describing the evolution of unemployment are included to provide further identifying information for the estimation of the output gap:

(6)U¯t=(τ4U¯ss+(1τ4)U¯t1)+gU¯t+ɛtU¯
(7)gU¯t=(1τ3)gU¯t1+ɛtgU¯
(8)ut=τ2ut1+τ1yt+ɛtu
(9)ut=U¯tUt

Here, U¯t is the equilibrium value of the unemployment rate (the NAIRU), which is time varying, and subject to shocks (ɛtU¯) and also variation in the trend (gU¯t), which is itself also subject to shocks (ɛtgU¯)—this specification allows for persistent deviations of the NAIRU from its steady-state value. Most importantly, we specify an Okun’s law relationship wherein the gap between actual unemployment (Ut) and its equilibrium process (given by ut) is a function of the amount of slack in the economy (yt).

Equations 1-9 comprise the core of the model for potential output. In addition, data on growth and inflation expectations are added, in part to help identify shocks, but mostly to improve the accuracy of estimates at the end of the sample period:

(10)πt+jc+πt+j+ɛt+jπc ,j=0,1
(11)GROWTHt+jc=GROWTHt+j+ɛt+jGROWTHc,j=0,…,5

For real GDP growth (GROWTH) the model is augmented with forecasts from the WEO for the five years following the end of the sample period. For inflation, expectations data are added for one year following the end of the sample period. These equations relate the model-consistent forward expectation for growth and inflation (πt+j and GROWTHt+j) to observable data on how WEO forecasters expect these variables to evolve over various horizons (one to five years ahead) at any given time (GROWTHt+jc). The ‘strength’ of the relationship between the data on the WEO forecasts and the model’s forward expectation is determined by the standard deviation of the error terms ((ɛt+jπc) and (ɛt+jGROWTHc)). In practice, the estimated variance of these terms allows WEO data to influence, but not completely override, the model’s expectations, particularly at the end of the sample period. In a way, the incorporation of WEO forecasts can be thought as an heuristic approach to blend forecasts from different sources and methods.

The methodology requires taking a stance on prior beliefs regarding a number of variables. A key assumption fed into the model’s estimation is that supply shocks are the primary source of real fluctuations in Central America. The prior belief that supply is more volatile than demand leads the model to assign much of observed volatility of real GDP to potential GDP fluctuations. In addition to the prior distributions of parameters, values for the steady-state (long-run) unemployment rate and potential GDP growth rates are provided.

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After obtaining estimates of potential output and NAIRU from the multivariate Kalman filter, potential TFP is calculated as a residual in the Cobb-Douglas function:

At=Yt/KtαLt1α

where Yt is potential output, Kt and Lt are capital and labor inputs, while At is the contribution of technology or TFP. Output elasticities (α is the capital share in the production function and is set at 0.35) sum up to one.

The capital stock series is constructed using a perpetual inventory method where the level of initial capital stock for a given year, 1990 in our case, is calculated assuming a constant level of depreciation rate of 5 percent per annum and a constant investment share of GDP.

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Prepared by Iulia Teodoru.

El Salvador: Selected Issues
Author: International Monetary Fund. Western Hemisphere Dept.