Guatemala: Selected Issues and Analytical Notes

International Monetary Fund. Western Hemisphere Dept.

doi:10.5089/9781475531534.002.A002

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Guatemala: Selected Issues and Analytical Notes

Author: International Monetary Fund. Western Hemisphere Dept.

Publication Date:: 01 Sep 2016

eISBN:: 9781475531534

Language:: English

Keywords:: ISCR; CR; GDP; yield; Guatemala; debt ratio; poverty incidence; cash transfer; transfer program; revenue yield; Income inequality; Consumption; Value-added tax

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Guatemala: Selected Issues and Analytical Notes

Abstract

Guatemala: Selected Issues and Analytical Notes

Fiscal Policy: Sustainability and Social Objectives

A. Fiscal Sustainability Assessment¹

This section presents an assessment of Guatemala’s medium and long term debt sustainability. The results suggest that under the current policies, central government debt is sustainable at 24 percent of GDP and even a short-term relaxation of the fiscal deficit by ½ percent of GDP would only slightly increase the debt-to-GDP ratio in the longer term. Other alternative scenarios based on a permanent relaxation by ½ percent of GDP, historical averages and a large contingent liability shock also indicate debt stabilization in the longer term at levels between 25 and 30 percent of GDP, respectively. The debt path is quite resilient to macro shocks. While not an immediate concern, rising demographic pressures, if left unaddressed, would pose challenges for the budget in the medium and long term.

Introduction

1. Guatemala has a solid track record of a prudent fiscal policy. Guatemala’s average overall fiscal balance at 2 percent of GDP and public debt at 21 percent of GDP, over the past 20 years, reflect both prudent fiscal management and stable macroeconomic environment. Fiscal performance deteriorated in the aftermath of the global financial crisis of 2007-08 as the deficit increased from 1½ percent of GDP to over 3 percent of GDP by 2010, but quickly declined to around 2½ percent of GDP by 2012. The deficit fell further to 1½ percent of GDP in 2015 during the political crisis, as revenue shortfalls were offset by even larger expenditure cuts. The improvement in the fiscal position over the past 5 years has been largely driven by the sharp decline in social spending, transfers and capital spending.²

2. Guatemala’s debt is low as a share of GDP though it is moderately high in relation to fiscal revenues. Public debt currently stands at 24½ percent of GDP. It has been virtually unchanged over the last four years. This level compares favorably to other countries in the region and to emerging market peers. Moreover, it is well below an indicative benchmark of 60 percent of GDP for countries with market access.³ However, Guatemala’s position looks less favorable when debt is compared to revenues since revenues are low by international standards.⁴

3. Additional efforts to raise tax collections will be needed to ensure adequate provision of basic public goods. Guatemala’s low revenue capacity constrains the level of government spending, currently at 12 percent of GDP. However, literature finds that the optimal size of the government, in particular, with respect to human development, is at least 15 percent of GDP.⁵ Hence, it would be desirable raising fiscal revenues to 15 percent of GDP in the medium term to accommodate higher social and infrastructure spending as well as support efforts to durably reduce crime and corruption. Improving tax performance, however, will require strong and sustained political commitment at the highest levels. The 2012 tax reform provided additional tools for the government to enforce tax controls and supervision, as well as eliminate VAT exemptions and reduce rates of the corporate income tax while broadening its base. The additional revenue from the 2012 tax reform was envisaged at 1-1½ percent of GDP over the course of several years. However, the reform ended up plagued by multiple legal challenges and administrative problems. Most importantly, the customs agency faced significant administrative delays in implementing the reform, which were exacerbated by high staff turn-over. As a result, the revenue yield of the reform turned out to be much lower than envisaged with virtually unchanged tax-to-GDP ratio after the reform.

Assessing Debt Dynamics and Fiscal Sustainability

4. The sustainability of public finances was analyzed under 5 alternative scenarios. The first scenario (the baseline) assumes a relatively constant primary deficit of 0.1 percent of GDP (a corresponding overall fiscal deficit of 1.6 percent of GDP). The second scenario assumes a temporary relaxation (for 5 years) of the overall deficit to 2 percent of GDP—a historical average. The third scenario assumes a primary balance consistent with a permanent relaxation of the overall fiscal deficit to 2 percent of GDP. The fourth scenario assumes that real GDP growth rate, real interest rate and the primary balance remain at their historical averages over the past ten years.⁶ The fifth scenario assumes that a contingent liability shock of 10 percent of the size of commercial bank assets must be accommodated by the budget.⁷

5. Fiscal position is sustainable in the long-run under all five scenarios but the debt ratio is higher under the permanent relaxation, and contingent liability shock scenarios. In the baseline scenario the debt-to-GDP ratio stabilizes at the current level of 24 percent of GDP in the medium and long term; the debt-to-revenue ratio remains at around 210 percent. In the scenario of temporary relaxation, the debt-to-GDP ratio rises slightly in the short term and stabilizes at 26 percent of GDP in the long term while debt-to-revenue ratio increases to 230 percent. In the permanent relaxation scenario, the debt ratio continues rising over a long horizon but stabilizes at 28½ percent of GDP with the debt-to-revenue ratio reaching 250 percent. In the historical average scenario debt to GDP ratio rises only to 24¾ percent of GDP and debt-to-revenue increases to 220 percent. Finally, in the contingent liability shock scenario the debt reaches a 30 percent of GDP level faster than in the permanent relaxation scenario but remains stable thereafter, with the debt to revenue slightly exceeding 260 percent. Under all five scenarios the debt-to-GDP does not exceed an indicative benchmark for countries with market access at 60 percent.

6. Sensitivity analysis suggests that Guatemala’s public debt is fairly resilient to shocks. We consider 5 sensitivity tests, including a shock to the primary balance, a shock to the real GDP growth, a shock to the real interest rate, a shock to the real exchange rate as well as the shock combining all of the above. The size of the shocks was based on the historical standard deviations of the corresponding variables.⁸ In addition, a stochastic simulation of the public debt path has been constructed by producing frequency distributions of debt paths under these shocks. Simulations yield a very slight upward trend in public debt-to-GDP ratio, with the median debt forecast reaching about 25 percent of GDP, almost identical to the baseline projection. The 95 percent upper confidence interval reaches 27 percent of GDP. A restricted simulation in which upside shocks are disregarded yields an only slightly-higher 95 percent upper confidence interval of 28 percent of GDP. The narrowness of these ranges reflects the historical stability of Guatemala’s macro variables.

7. While not an immediate concern, rising demographic pressures, if left unaddressed, would pose challenges for the budget in the medium and long term. Pension spending in the central government budget has generated a deficit of 0.41 percent of GDP in 2015 and is predicted to rise slightly to 0.45 percent of GDP in 2016 under the baseline scenario. However, rising aging pressures would likely lead to a somewhat higher central government pension spending in the future (currently estimated at an additional ¼ percent of GDP). Given the history of deficit containment, the baseline scenario assumes that these additional expenditure pressures would be accommodated through budget cuts elsewhere, thereby likely reducing even further social and infrastructure spending. In addition, actuarial projections suggest that the social security institute (IGSS) will start running a deficit in 2017 and will deplete its reserves to cover the deficit by 2030. While this rising pension deficit does not directly affect the central government budget, it represents contingent liability for the government. Therefore, in the longer run a parametric reform (for example, an increase in the pension age and contributions) of the pension system will be needed to bring the pension system on a sustainable footing.

B. Poverty, Inequality and Fiscal Redistribution⁹

Guatemala has high levels of poverty and inequality, with distinct patterns in terms of rural-urban as well as ethnic divide. At the same time, low tax revenues constrain the size of the government and thus the scope to pursue social objectives. This section quantifies the poverty gap in Guatemala and estimates the effect on growth and redistribution of alternative tax/spending policy combinations. Results suggest that the extreme poverty gap amounts to about 1 percent of 2016 GDP, while lifting all poor out of total poverty would take at least 7 percent of GDP. Raising revenues through higher and more progressive PIT would be less detrimental to growth and poverty/inequality than the VAT. Redistributing 1 percent of GDP through the existing cash transfer program would reduce extreme poverty by 4 percentage points. Trade-offs on the spending side imply that both cash transfers and public investment need to increase in order to reduce poverty while simultaneously fostering growth.

Trends in Poverty and Inequality

8. Poverty and inequality in Guatemala are high compared to regional peers. Contrary to other countries in the region where poverty has decreased over time, both poverty and extreme poverty have increased in Guatemala over the last decade. Poverty incidence also displays a clear regional pattern and is significantly higher in rural compared to urban areas, which also translates in a clear ethnic divide as indigenous populations mostly reside in rural regions. High extreme poverty has dire consequences for basic nutrition outcomes, hence the higher incidence of malnutrition in Guatemala compared to regional peers and other countries in the world.

9. Persistently low tax revenue constrains the size of the budget and limit the government’s capacity to pursue social objectives. At 10.2 percent of GDP in 2016, tax revenues are among the lowest in the world, which limit the size of government and its spending capacity. As a result, social spending is also very low, even compared to countries with similar per capita income levels. Additionally, revenue to GDP ratios have been declining over the last few years, not least as a consequence of the political crisis in 2015. Given the government’s prudent fiscal policy, spending cuts have overcompensated for such declines and in particular public investment that has typically absorbed the brunt of the fiscal adjustment.

10. Hence, in 2014 more than 20 percent of the population lived in extreme poverty while almost 60 percent were generally poor. The cumulative distribution of household per capita consumption below, based on the released 2014 ENCOVI microdata, shows that the per capita consumption of more than 20 percent of the population remained below the extreme poverty line (first from the left) and was below the general poverty line (second from the left) for about 60 percent of the population. At the same time, the distribution of per capita consumption in the second panel shows how most of the 40 percent of population confined between the two poverty lines are clustered just above extreme poverty as showed by the mode of the distribution approaching the extreme poverty line from the right. The third panel below presents annual households per capita consumption in quetzales by consumption deciles: the consumption of the first two and six deciles is lower than the extreme and general poverty lines respectively, consistently with Guatemala’s extreme poverty rate of 23 and the general poverty rate of 59 percent.

11. Meeting the SDG target of eradicating extreme poverty would require at least one percent of 2016 GDP, while halving total poverty starting from the most severe would require at least five percent. To quantify the size of the problem we estimated the average and total poverty gaps, namely the difference between the poverty lines and annual per capita consumption. Results show that the extreme poverty gap amounts to 1 percent of 2016 GDP, and the total poverty gap sums to about 7 percent. This means that meeting the SDG targets of eradicating extreme poverty and halving the number of people living in poverty would require at least 1 and 5 percent of GDP respectively. With respect to the latter target, we are assuming a static scenario in which the most severe poverty is eliminated first, i.e., the bottom three deciles or (4.8 millions) are lifted out of poverty first. This would be the notional annual cost of a perfect cash transfer program perfectly targeted to the poor and perfectly calibrated to exactly fill the per capita consumption gap of each household. In practice, of course, there is no such program: the cost of administration, and imperfect targeting (both in terms of beneficiaries and benefit amount), which crucially depend on the government administrative capacity, will need to be added to these lower bounds.

Fiscal Policy and Redistribution: Evidence from the Past

12. Previous incidence analyses suggest that fiscal policy in Guatemala had little redistributive effect. Based on the 2009/10 National Survey of Family Income and Expenditures, Cabrera and others (2014)¹⁰ find that the Gini coefficient for disposable income (after direct taxes and transfers) declined by a mere 0.005 points compared to the Gini for market income. When the monetized value of education and health services are incorporated, the decline is still a very small 0.024. Although direct taxes were somewhat progressive, consumption taxes were outright regressive, and inequality of post-fiscal income (after direct and consumption taxes and direct transfers) was the same as market income inequality. At the same time, consumption taxes were regressive enough to more than offset the benefit to the poor of progressive cash transfers, leaving post-fiscal poverty at higher rate than market income poverty.

13. Direct transfers were progressive, although too low to make a material difference. According to the same study, the poverty rate based on disposable income was lower than for net market income (after direct taxation) suggesting that spending on direct transfers was targeted to the groups with the highest incidence of poverty. At the time, the most relevant program, with a budget of 0.4 percent of GDP, was Mi Familia Progresa (MIFAPRO). Introduced in 2008, MIFAPRO provided conditional cash transfers for health and education to poor households with children and pregnant or breast feeding women. Although the average transfer was very small and not adjusted for the number of children in the household, as of January 2011 the program covered about a third of Guatemala’s total population, and 33 percent of the poor (UNDP).

14. However, reforms and adjustments that occurred since 2010 have reduced the already mild progressivity of direct taxation and transfers. The MIFAPRO program has shrunk since then, and its budget has been gradually reduced to only 0.1 percent of GDP in 2013, with increasingly irregular payments. In 2015 the program, now renamed Mi Bono Seguro, only executed 0.06 percent of GDP in spending and, according to 2014 ENCOVI microdata, covered 27 percent of poor, of which 43 percent extremely poor, resulting in a 36 percent coverage of extreme poor. On the other hand, the tax reform that in 2012 lowered the tax rates applied to both PIT and CIT, and reduced the PIT brackets for wage earners to two, with rates of 5 and 7 percent respectively, is likely to have further reduced the already limited progressivity of direct taxation.

Looking Forward: Policy Options and Trade-Offs

15. This section simulates the redistributive and macroeconomic effect of alternative combinations of tax and spending policies. We use the general equilibrium model described in the Box below and Appendix 1 to simulate the growth and redistributive effect of a tax increase of 1 percent of GDP through higher Value Added Tax (VAT) and Personal Income Tax (PIT) with alternative spending options including: (i) untargeted public consumption, (ii) public investment; and (iii) cash transfers. While the calculations in ¶4, provided the minimum cost of eradicating extreme poverty through perfectly targeted transfers, this analysis looks at the effect on poverty of the same amount of money spent in a less perfectly targeted way.

16. Compared to PIT, VAT has a stronger negative impact on consumption and GDP, and is regressive, resulting in worse overall poverty and inequality outcomes. The model results indicate that revenue mobilization through VAT would have a stronger depressive effect on the output level: while GDP only decreases by less than 1 percent compared to the baseline in the PIT scenario, it would fall by almost 2 percent if the additional revenues were raised through VAT. The result on the GDP is unconventional. The VAT is usually considered less distortionary than the PIT, in particular, because of its neutral impact on investment. However, the conventional wisdom may not apply in the case of Guatemala due to the presence of a large informal sector. The informal sector may be able to escape taxation all together, including taxation of intermediate goods, in part, because VAT controls are weak and in part because many goods are unsophisticated and do not have multiple production stages. At the same time, many of the goods produced by the formal and informal sectors are close substitutes. Under these circumstances, the VAT penalizes consumption of goods produced in the formal sector, reduces the demand for these goods with the corresponding decline in their prices, and, thereby, reduces marginal returns of the formal sector firms. As the relative prices of goods shift in favor of a less productive informal sector, which performs only a small part of investment in the economy (the majority is done by the formal sector), the VAT becomes distortive both in terms of consumption allocations and in terms of investment decisions. Hence, while the PIT is always distortive with or without the informal sector, the VAT can become distortive in the presence of the informal sector. This, however, does not automatically guarantee that the VAT has to be more distortive than the PIT. It is the particular structure of the PIT in Guatemala with extremely low rates and little progressivity and a relatively high VAT rate that help explain the result.¹¹ At the same time, VAT is regressive, thus poverty and inequality increase more.

Box 1. General Structure of the Model

Small open economy with three consumption goods: agricultural, services, and manufacturing and modern services.¹
There are four types of households: two types in the urban area: skilled and unskilled urban; and two types in the rural area small-land holders, and large-land holders. Within each of the first three types, there is a continuum of households, equal ex ante, but facing idiosyncratic risk. Households solve dynamic optimization problems taking prices and government policies as given. Households receive remittances in a lump-sum fashion, their magnitude and distribution match the data.
Four goods are produced: (i) agricultural commodities for exports (and not domestically consumed), (ii) agricultural goods for domestic consumption (non-tradable), (iii) manufacturing (tradable), and (iv) services (non-tradable).
The only financial assets available are one-period capital share holdings. The total amount of capital shareholdings equals the capital stock of the manufacturing sector. These titles are traded among households to allow for risk sharing. The interest rate of these assets and the price of domestic food are determined by supply and demand forces in equilibrium.
The government collects tax revenue (on income, consumption, etc.). This revenue is used to fund government expenditures (including public sector wages, capital investment and other pro-poor spending).
The model is thus a dynamic general equilibrium including a continuum of households facing idiosyncratic risk (as in the income inequality literature) and also multiple sectors (as in the structural transformation literature).

¹ Manufacturing should be understood as the modern, high productivity sector of the economy (and thus include some services like banking, finance, etc.; while services refer to the informal non-taxable activities, such as personal services.

17. Spending in untargeted government consumption would result in a contraction of growth as the distortive effect of taxation would prevail. Given its superior growth and distributional outcomes, we focus on PIT increases for the analysis of spending scenarios. If the additional revenue was used to finance untargeted government consumption, GDP would shrink following the reduction in private consumption and investment. In addition, since government consumption is in part spent in tradable goods, some of the expenditure would leak away from the economy in the form of imports, thus exacerbating the distortionary effect of higher taxation.

18. Additional spending in cash transfers would significantly reduce extreme poverty and inequality but result in a more pronounced fall in GDP. The model proportionately expands cash transfers according to the distribution of the Mi Bono Seguro Program in the ENCOVI 2014 database, which covered 36 percent of extreme poor households, but leaked about 20 percent of its benefits to non-poor households. Given the limited amount of additional funds and imperfect targeting, the effect on poverty is trivial but extreme poverty would drop by almost 20 percent, from 23 to 19 percent of the population. Inequality, as measured by the Gini index, would decrease accordingly by about 2.5 percent to 0.52. Moreover, cash transfers support the consumption of poor households thus the reduction in private consumption is less than in the public consumption scenario. However, cash transfers shift resources away from the groups that save and invest, hence a bigger drop in private investment. In addition, cash transfers are not treated as government consumption in the model, resulting by construction in lower government expenditure—as the revenue becomes a transfer—which depresses private investment further. Thus, the reduction in poverty comes at the expense of lower growth.

19. Using the additional funds to finance infrastructure would result in a moderate economic expansion. The model assumes that public investment is efficient, resulting in a higher stock of public capital, which in turn improves the productivity of the private sector. Better infrastructure generates higher private sector productivity, and a lesser decrease in private investment which provides a boost to total output. Higher productivity also increases the demand for labor and its remuneration, which results in higher labor income for poor households. Higher productivity also makes food cheaper, further reducing extreme poverty. Therefore, both extreme poverty and inequality are reduced, although less than in the cash transfer scenario.

Programa Mi Bono Seguro

Poor households targeting, 2014

Conclusions and Policy Recommendations

20. Mobilizing tax revenues is crucial to achieve social objectives. The government of Guatemala needs tax revenues to improve social conditions and lift its people out of extreme poverty and malnutrition. While in the short term revenue administration measures to widen the tax base should be prioritized, in the medium to long term—once the taxpayers’ morale is restored—tax rates increases are likely to be needed. In this respect, improving the collection of VAT will be key, and so would be making the PIT regime more progressive. Our results show that eradicating extreme poverty would require at least 1 percent of GDP.

21. The way resources are mobilized and spent matters. Alternative taxes and spending strategies have different outcomes in terms of macroeconomic impact and redistribution, hence a careful analysis of growth and poverty effects is required when designing tax/spending policies. Our analysis suggests that, likely due to its current low rates and relatively neutral structure, PIT would generate a larger reducing effect on inequality and less distortionary impact on growth. Design, of course, matters too, and any identified policy measure can be designed to mitigate the negative effect on growth and the poor.

22. When it comes to spending, there are trade-offs between growth and redistribution objectives. While cash transfers are more efficient in reducing extreme poverty and inequality, (efficient) public investment generates better growth outcomes. Hence, both government transfers and public investment will need to rise to spur growth and reduce poverty and inequality. Our results suggest that expanding existing CCT programs by 1 percent of GDP to increase benefits would reduce the extreme poverty rate from 23 to 19 percent. However, growth and social objectives do not need to be incompatible if a virtuous cycle can be started where economic growth improves the living condition of people and a less poor, more productive labor force contributes to faster economic growth. In this respect, effective targeting and efficient public investment spending are key to maximize the social and growth returns of higher tax yields.

References

Davies, A. “Human Development and the Optimal Size of Government,” Journal of Socioeconomics, 2009, Vol. 35, No. 5, pp. 868–76.
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Gunalp, B. and Dincer, O., 2005, “The Optimal Government Size in Transition Countries,” Department of Economics, Hacettepe University Beytepe, Ankara and Department of Commerce, Massey University, Auckland
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Karras, G., 1997, “On the Optimal Government Size in Europe: Theory and Empirical Evidence,” The Manchester School of Economic & Social Studies
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Appendix. Model Details¹

We consider a small open economy populated by a continuum of heterogeneous households who live indefinitely and face idiosyncratic shocks. All types of households have the same preferences over the consumption of food, c^f, manufacturing c^m, and services, c^s. We assume that services are non-tradable, while manufacturing and food is tradable, and also the numeraire.

There are three fixed types of households in the model: large farmers, rural households, and urban households. Rural households own a small plot of land and have the occupational choice problem of choosing the amount time to devote to producing food (which requires labor and land), and the amount of time working for large farmers for a competitive wage w^r. Similarly, urban households have the occupational choice problem of choosing the optimal amount of time to produce services (which use only labor as an input), and how much time to work in manufacturing for a competitive wage w. We assume that households cannot move across rural and urban sectors.

Large farmers own a large plot of land where they can produce food for the domestic market or exports. They hire labor from small farmers and also accumulate capital, both of which are used to produce agricultural goods for export. Large farmers’ capital follows a standard law of motion of capital:

k_{+}^{f} = x^{f} + (1 - δ) k^{f}

Finally, there are competitive firms that produce manufacturing goods using capital and labor as an input. Manufacturing can also be used indistinctly for investment by large farmers or for consumption. Markets are incomplete, urban and rural households can save at a risk-free interest rate r. Entrepreneurs can borrow at a rate (1 + d)r, where d captures the risk premium in lending. We assume that the capital account is closed and trade balance is always zero.

The government collects value added taxes on food τ^a and manufacturing goods r^m, trade taxes r*, corporate taxes τ^f, and labor income taxes τ^w. The government spends part of its resources on manufacturing goods, and gives or collects lump-sum taxes that may be specific to each household type. In the next section we explain the urban households’ problem.

The framework considered here is a continuum of infinitely-lived agents with productivity risk. The model is small open economy with three different agents types: urban households u, farms f, and rural households r. The total mass of agents is normalized to equal 1. All agents maximize the present value of their consumption over three different types of goods: food c^a, manufactured goods c^m, and services c^s.

A. Urban Households’ Problem

Urban households are endowed with one unit of time. There are two types of households in urban areas: low-skilled and high-skilled households. μ^l share of urban households is low-skilled producing services y^s and (1 − μ^l) share of urban households is high-skilled working on manufacturing for a wage w^m. Households that live in urban areas maximize the expected present value of utility from stochastic consumption sequences. We will use the superscript l for low-skilled urban households, h for high-skilled urban households, and u for urban households. All urban households face idiosyncratic shocks to their productivity ϵ^l and ϵ^h and can save in risk-free bonds b^l and b^h, for low-skilled and high-skilled urban households. The problem of a low-skilled urban households is given by:

\begin{matrix} \max_{{c^{l, a}, c^{l, m}, c^{l, s}}} E \sum_{t = 0}^{\infty} β^{t} u (c^{l, a}, c^{l, s}, c^{l, m}) \\ s . t . \\ (1 + τ^{a}) p^{a} c^{l, a} + (1 + τ^{m}) p^{m} c^{l, m} + p^{s} c^{l, s} + b^{l} \\ = p^{s} y^{s} + (1 + r) b^{l} + T^{l} (p^{s} y^{s}) + \prod_{}^{l} (p^{s} y^{s}) \\ y^{s} = ε^{l} z^{s} \end{matrix}

The problem of a high-skilled urban household is given by:

\begin{matrix} \max_{{c^{h, a}, c^{h, m}, c^{h, s}}} E \sum_{t = 0}^{\infty} β^{t} u (c^{h, a}, c^{h, s}, c^{h, m}) \\ s . t . \\ (1 + τ^{a}) p^{a} c^{h, a} + (1 + τ^{m}) p^{m} c^{h, m} + p^{s} c^{h, s} + b_{+}^{h} \\ = (1 - τ^{w}) ε^{h} w h^{h} + (1 + r) b^{h} + T^{h} (ε^{h} w h^{h}) + Π^{h} (ε^{l} w h^{l}) \end{matrix}

We assume that households face idiosyncratic shocks to their productivities, ϵ^l and ϵ^h, which follow AR(1) processes. The calibration of these shocks will be such that, as in the data, low productivity households work more on their households’ enterprises, while high productivity households spend more time working on the market.

B. Rural Households’ Problem

Households that live in rural areas maximize the expected present value of utility from stochastic consumption sequences. The superscript r denotes rural households’ allocations. Rural households are endowed with one unit of labor and with a small plot of land d^r. They choose between working on their own plot or working for large farms for a wage w^r. They face idiosyncratic shocks to their productivity on their own plot and can save in a risk-free bond b^r. The maximization problem of a rural household is given by:

\begin{matrix} \begin{matrix} \max_{{c^{u, a}, c^{u, m}, c^{r, s}, h^{u}}} E \sum_{t = 0}^{\infty} β^{t} u (c^{r, a}, c^{r, s}, c^{r, m}) \\ s . t . \\ (1 + τ^{a}) p^{a} c^{r, a} + (1 + τ^{m}) p^{m} c^{r, m} + p^{s} c^{r, s} + b^{r} \\ = (1 - τ^{w}) ε^{r} w^{f} h^{r} + p^{a} y^{a} + (1 + r) b^{r} + T^{r} (ε^{h} w^{f} h^{f}) + \prod_{}^{r} (ε^{r} w^{f} h^{f}) \\ y^{a} = z^{a} ε^{r} (d^{r})^{α^{a}} (1 - h^{r})^{1 - α^{a}} \end{matrix} \\ h^{r} \in [0, 1] \end{matrix}

We assume that households face idiosyncratic shocks to their productivity, ϵ^r follows an AR(1) process. The calibration of these shocks will be such that as in the data, low productivity households devote the majority of their time working for big farms, while high productivity households spend more time working on their own farms.

C. Large Farm’s Problem

Farmers that own larger plots of land also maximize their present discounted utility. They do not face any idiosyncratic risk, and the economy is assumed to be in a stationary state so that prices are constant through time. Hence, they do no face any uncertainty. Large farmers produce two goods domestic food and exports. The production of exports requires land d*, capital k^f and labor h*, while the production of food only requires land d^a and labor h^a. We assume that there is no land market, and consequently the allocation of land between domestic and export goods is fixed. Large farmers choose how much labor to hire to produce for the domestic and the external markets, and how much capital to accumulate. The problem of a larger farmer is given by:

\begin{matrix} \begin{matrix} \begin{matrix} \max_{{c^{f, a}, c^{f, m}, c^{f, s}, k_{+}^{f}, h^{a}, h^{*}}} E \sum_{t = 0}^{\infty} β^{t} u (c^{f, a}, c^{f, s}, c^{f, m}) \\ s . t . \\ (1 + τ^{a}) p^{a} c^{f, a} + (1 + τ^{m}) p^{m} c^{f, m} + p^{s} c^{f, s} + p^{m} k^{f} \\ = Y^{*} + τ * δ p^{m} k^{f} + (1 - δ) p^{m} k^{f} + T^{f} (Y^{*}) + \prod_{}^{f} (Y^{*}) \\ π^{a} = p^{a} z^{a} (d)^{α_{1}^{a}} (h^{a})^{1 - α_{1}^{a}} - w^{f} h^{a} \end{matrix} \\ π^{*} = p^{*} z (d^{*})^{α_{1}^{*}} (h^{*})^{α_{2}^{*}} (k^{f})^{(1 - α_{1}^{*} - a_{2}^{*})} - w^{f} h^{a} \end{matrix} \\ Y^{*} = (1 - τ^{r}) π^{a} + (1 - τ *) π^{*} \\ h^{a}, h^{*} \geq 0 \end{matrix}

In addition to paying consumption taxes, large farmers also pay taxes on their land and capital incomes obtained in both, the domestic market, taxed at a rate τ^r, and on exports, taxed (after depreciation allowances) at a rate τ*.

D. Firm’s Problem

We assume that there is a competitive firm that rents capital k^m, hires effective hours of labor h^m, and buys intermediate goods q^m to maximize profit. The firm’s problem is given by:

\max_{{k^{m}, h^{m}, q^{m}}} E \sum_{t = 0}^{\infty} β^{t} (z^{m} (k^{m})^{α_{1}^{m}} (h^{m})^{α_{2}^{m}} (q^{m})^{1 - α_{1}^{m} - α_{2}^{m}} - w^{m} h^{m} - (1 + d) r k^{m} - (1 + τ^{m}) q^{m}

Where d is the risk premium paid by firms and τ^m is the consumption tax rate on intermediate goods.

E. Government Budget Constraints

The government collects taxes and spend its revenue on manufacturing G and lump-sum transfers to households {T^r(.),T^u(.),T^f(.)}. In equilibrium the government budget constraint must hold. The expression of the government budget constraint is given by:

\begin{matrix} \begin{matrix} τ^{a} P^{a} C^{a} + τ^{m} C^{m} + τ^{*} π^{*} + τ^{r} π^{r} + τ^{w} μ^{u} (\int ε^{1, u} h^{u} Γ (b^{u}, ε^{u}) + μ^{r} \int ε^{1, r} h^{r} Γ (b^{r}, ε^{r})) \\ = G + μ^{r} \int T^{r} (w^{f} ε^{r} h^{r}) Γ (b^{r}, ε^{r}) + μ^{u} \int T^{u} (w ε^{u} h^{u}) Γ (b^{u} +, ε^{u}) + μ^{f} T^{f} + τ^{*} δ k^{f} \end{matrix} \end{matrix}

where Γ(b^u, ϵ^u) = μ^lΓ(b^l, ϵ^l) + (1 − μ^l)Γ(b^h, ϵ^h). The government budget constraint implies that the revenue from consumption, corporate and labor income taxes must be equal to government spending on manufacturing, transfers to households, and subsidies for food.

F. Market Clearing

In this economy four markets clear in equilibrium. The market clearing conditions depend on the endogenous distribution of shocks and asset holdings Γ(·, ·) and on the share of each type of household: urban households μ^u, rural households μ^r, and large farms μ^f. Since labor markets are segmented between urban and rural workers, there are two labor market clearing conditions one for each sector.

i. Urban labor market
$\int ε^{u} h^{u} Γ (b^{u}, ε^{u}) = h^{m}$
ii. Rural labor market
$μ^{r} \int ε^{r} h^{r} Γ (b^{r}, ε^{r}) = μ^{f} (h^{a} + h^{*})$

Interest rates must clear the capital market so that households’ savings are equal to the capital demanded by manufacturing firms.

iii. Capital market
$k^{m} = μ^{u} \int b^{u} Γ (b^{u}, ε^{u}) + μ^{r} \int b^{r} Γ (b^{r}, ε^{r})$

Finally, the relative price of services and food must be such that the corresponding markets of such non-tradable goods clear.

iv. Services market
$μ^{u} \int c^{u, s} Γ (b^{u}, ε^{u}) + μ^{r} \int c^{r, s} Γ (b^{r}, ε^{r}) + μ^{f} c^{f, s} = μ^{u} \int ε^{u} z^{s} (1 - h^{u})^{α} Γ (b^{u}, ε^{u})$
v. Food market
$\begin{matrix} μ^{u} \int c^{u, a} Γ (b^{u}, ε^{u}) + μ^{r} \int c^{r, a} Γ (b^{r}, ε^{r}) + μ^{f} c^{f, a} \\ = μ^{u} \int ε^{u} z^{a} (1 - h^{r})^{1 - α^{α}} Γ (b^{u}, ε^{u}) + μ^{f} z^{α} (d^{α})^{α_{1}^{α}} (h^{α})^{1 - α_{1}^{α}} \end{matrix}$

G. Stationary Equilibrium

A competitive equilibrium for this economy is constituted by a stationary distribution of assets holdings and idiosyncratic shocks {Γ}, sequences of service and agricultural prices, manufacturing and rural wages, and interest rates {p^s, p^a, w^r, w^f, r}, together with allocations of consumption, investment, time use and bond holdings for each type of households, such that—given manufacturing prices and exported goods prices {p^m, p*}, sectoral productivity, idiosyncratic shocks, government spending, and predetermined taxes {τ^m, τ^a, τ^w, τ^f, τ*} and transfers {T^r, T^u, T^f}—the stochastic sequence of allocations solve their respective constrained optimization problem, clear markets, and satisfy the government budget constraint. Note that the market clearing conditions along with the fact that the government and individual budgets constraints hold at every period, imply that the external sector condition of a balanced current account is also satisfied (Walras’ law).

Prepared by Carlos Janada.

Primary spending fell from 13 percent of GDP in 2010 to 10.7 percent in 2015.

See Annex II of the IMF “Staff Guidance Note for Public Debt Sustainability Analysis in Market Access Countries,” 2013 at https://www.imf.org/external/np/pp/eng/2013/050913.pdf.

Guatemala has one of the lowest revenue-to-GDP ratios in the world (see, for example. “Tax Capacity and Growth: Is There a Tipping Point,” by Vitor Gaspar, Laura Jaramillo and Philippe Wingender; FAD Seminar Series, December 9, 2015.

Peden, E. (1991), Karras, G. (1997), Davies (2009), Gunalp and Dincer (2005), On the upper side, estimates vary but mainly fall below 30 percent of GDP.

The years of 2009 and 2010, when the effects of the global financial crisis affected Guatemala most deeply, were excluded. The historical sample was extended by two earlier years to compensate (i.e., the historical average is still based on a 10-year sample).

Commercial bank assets were roughly half of GDP at the end of 2015. Therefore, the contingent liability shock is equivalent to 5 percent of GDP. As a reference, the Troubled Asset Relief Program (TARP) in the U.S. was equivalent to about 5 percent of US GDP when it was announced during the financial crisis of 2008.

Real GDP Growth Shock: GDP growth rate is reduced by 1 standard deviation for 2 consecutive years; level of non-interest expenditures is the same as in the baseline; deterioration in primary balance lead to higher interest rate; decline in growth leads to lower inflation (0.25 percentage points per 1 percentage point decrease in GDP growth). Primary Surplus Shock: Minimum shock equivalent to 50% of planned adjustment (50% implemented), or baseline minus half of the 10-year historical standard deviation, whichever is larger. There is an increase in interest rates of 25bp for every percentage point of GDP worsening in the primary balance.

Interest Rate Shock: Interest rate increases by the difference between average real interest rate level over projection and maximum real historical level, or by 200bp, whichever is larger.

Real Exchange Rate Shock: Estimate of overvaluation or maximum historical movement of the exchange rate, whichever is higher; pass-through to inflation with default elasticity of 0.25 for EMs and 0.03 for AEs.

Preparad by Valentina Flamini, Marina Mendez Tavares, Adrian Peralta-Alva, and Xuan Tam.

Cabrera, M., N. Lustig, and H. Moran, 2014, “Fiscal Policy, Inequality, and the Ethnic Divide in Guatemala”, CEQ Working Paper No. 20.

An empirical study by Acosta-Ormaechea and Yoo (2012) also finds that in low income countries PIT does not significantly affect growth, likely due to the low level of PIT collection in such countries (1.5 percent of GDP on average). This result is relevant for Guatemala where PIT collection is only 0.4 percent of GDP.

This application is part of a research project on macroeconomic policy supported by the U.K.’s Department for International Development (DFID) but should not be reported as representing the views of DFID.

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Guatemala: Selected Issues and Analytical Notes

Author: International Monetary Fund. Western Hemisphere Dept.

Volume/Issue:: Volume 2016: Issue 282

Publisher:: International Monetary Fund

ISBN:: 9781475531534

ISSN:: 1934-7685

Pages:: 106

DOI:: https://doi.org/10.5089/9781475531534.002

Keywords
Fiscal Policy: Sustainability and Social Objectives
- A. Fiscal Sustainability Assessment1
  - Introduction
  - Assessing Debt Dynamics and Fiscal Sustainability
- B. Poverty, Inequality and Fiscal Redistribution9
References
- Appendix. Model Details1

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Fiscal Indicators

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General Government Debt Indicators^*

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Long-Term Sustainability

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Alternative Scenarios

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Public DSA – Stress Tests

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Evolution of Predictive Densities of Gross Nominal Public Debt

(in percent of GDP)

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Poverty and Inequality Indicators

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Revenue, Expenditure, and Social Spending

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Consumption Distribution

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Poverty Gap by Income Deciles

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Impact of VAT and PIT Increases on Economic Activity, Poverty, and Inequality

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Impact of Spending Alter natives on Economic Activity, Poverty, and Inequality

	Extreme Poor
Beneficiary	No	Yes	Total
No	8376	1213	9,589
Yes	1252	695	1,947
Total	9628	1908	11,536
	Poor
Beneficiary	No	Yes	Total
No	5,314	4,275	9,589
Yes	325	1622	1947
Total	5,639	5,897	11,536

	Extreme Poor
Beneficiary	No	Yes	Total
No	8376	1213	9,589
Yes	1252	695	1,947
Total	9628	1908	11,536
	Poor
Beneficiary	No	Yes	Total
No	5,314	4,275	9,589
Yes	325	1622	1947
Total	5,639	5,897	11,536

	Extreme Poor
Beneficiary	No	Yes	Total
No	8376	1213	9,589
Yes	1252	695	1,947
Total	9628	1908	11,536
	Poor
Beneficiary	No	Yes	Total
No	5,314	4,275	9,589
Yes	325	1622	1947
Total	5,639	5,897	11,536

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Abstract

Fiscal Policy: Sustainability and Social Objectives

A. Fiscal Sustainability Assessment1

Introduction

Assessing Debt Dynamics and Fiscal Sustainability

B. Poverty, Inequality and Fiscal Redistribution9

Trends in Poverty and Inequality

Fiscal Policy and Redistribution: Evidence from the Past

Looking Forward: Policy Options and Trade-Offs

References

Appendix. Model Details1

A. Urban Households’ Problem

B. Rural Households’ Problem

C. Large Farm’s Problem

D. Firm’s Problem

E. Government Budget Constraints

F. Market Clearing

G. Stationary Equilibrium

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A. Fiscal Sustainability Assessment¹

B. Poverty, Inequality and Fiscal Redistribution⁹

Appendix. Model Details¹