This Selected Issues paper assesses recent trends in Hungary’s potential growth and medium-term growth prospects. It analyzes to what extent the recent moderation of GDP growth reflects structural factors. The paper lays out some stylized facts about the Hungarian economy that could explain the growth slowdown observed in recent years. It provides estimates of potential growth using various methods, identifies the sources of the growth slowdown, and offers forecasts of potential growth over the medium-term under the baseline scenario. A model-based approach is also employed to estimate potential growth over the medium term under a reform scenario.

Abstract

This Selected Issues paper assesses recent trends in Hungary’s potential growth and medium-term growth prospects. It analyzes to what extent the recent moderation of GDP growth reflects structural factors. The paper lays out some stylized facts about the Hungarian economy that could explain the growth slowdown observed in recent years. It provides estimates of potential growth using various methods, identifies the sources of the growth slowdown, and offers forecasts of potential growth over the medium-term under the baseline scenario. A model-based approach is also employed to estimate potential growth over the medium term under a reform scenario.

Potential Output Growth In Hungary 1

A. Introduction

1. Hungary’s growth performance weakened considerably in recent years. Following a period of rapid growth that averaged 4 percent in the ten years prior to the global financial crisis—which resulted in part from Hungary’s increased integration into the German Central European Supply Chain (GCESC) and the related surge in investment and exports—the economy stagnated in 2007, and with the intensification of the global financial crisis, contracted substantially, by 6¾ percent in 2009. Since then, growth performance has been rather disappointing, and the economy slipped into a second recession in 2012. In 2013, the economy registered a modest recovery, but real GDP remained at about 5 percent below its pre-crisis level, lagging behind the performance of most regional peers, which are also heavily integrated into the GCESC.

A01ufig01

Hungary. Real GDP growth, 1997-2013

(Percent)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Source: Haver.1/ Peers include Czech Republic, Poland and Slovakia.

2. Against this background, this chapter aims to assess recent trends in Hungary’s potential growth and medium-term growth prospects. More specifically, the chapter addresses the following questions:

  • To what extent does the recent moderation of GDP growth reflect structural factors?

  • What would growth prospects over the medium-term be if recent trends were to continue?

  • What are key reforms necessary to raise Hungary’s potential growth, and what would be their impact on the real economy?

3. This chapter addresses these questions by: (i) estimating Hungary’s potential growth since the mid-1990s and identifying the contributing factors to the recent weak growth; (ii) forecasting potential output growth over the medium-term under current policies; and (iii) quantifying the impact of structural reforms on Hungary’s potential growth employing a model-based approach.

4. The rest of the chapter is organized as follows: Section B lays out some stylized facts about the Hungarian economy which could explain the growth slowdown observed in recent years. Section C provides estimates of potential growth using various methods, identifies the sources of the growth slowdown, and offers forecasts of potential growth over the medium-term under the baseline scenario. Section D employs a model-based approach to estimate potential growth over the medium-term under a reform scenario. Finally, section E concludes.

B. Why Has Output Growth been Disappointing in Hungary?

5. Following its collapse in the aftermath of the global crisis, investment has recovered somewhat, but remains low. In the ten years prior to the crisis, the investment-to-GDP ratio averaged 23 percent, but in recent years it declined significantly reaching a record-low of 17 percent of GDP in 2012. This largely reflected the deleveraging process of the corporate and household sectors, the deterioration in the external environment and increased macroeconomic uncertainty, and the weakened business climate and institutional framework. The difficult operating environment for banks, owing in part to the heavy tax burden and high NPLs, and the sharp cross-border bank deleveraging also played an important role in limiting credit and investment. In 2013, investment recovered slightly, reaching 18 percent of GDP, largely on account of increased public investment co-financed with EU funds, the relaxation of the monetary policy stance, and the positive impact of the “Funding for Growth” Scheme (FGS), which provides subsidized lending to SMEs. Despite the recent moderate uptick, the investment ratio in Hungary remains low by historical standards and continues to lag behind regional peers.

A01ufig02

Hungary: Investment and Credit to the Private sector

(Share of GDP)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Sources: Haver and IMF staff’s calculations.

6. Labor productivity lags behind regional peers and the gap has been widening since the crisis. The loss of output in Hungary since 2008 was among the sharpest in the region, while employment remained broadly the same. This pattern, which points to a further deterioration in labor productivity, is also consistent with the decline in investment, capital stock, and total factor productivity (TFP). As potential growth depends on both the quality and the quantity of labor, low productivity, and weak labor market conditions—particularly if resulting in prolonged periods of unemployment—adversely affect the productive capacity of the economy and undermine potential growth, including through hysteresis effects (Blanchard et al. 2013).

A01ufig03

Change in Real GDP and Employment in Hungary and Peers, 2008–12

(Percent)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Sources: World Economic Outlook and IMF staff calculations.

7. The still high levels of public and external debt continue to over burden the economy. Hungary’s public debt level is the highest in the region and, combined with the large financing needs, poses significant vulnerability. It could also impede growth through its potential adverse impact on capital accumulation and TFP. This can occur through a variety of channels, including higher long-term interest rates (Baldacci and Kumar, 2010), crowding-out of private investment, higher distortionary taxation (Dotsey, 1994), greater uncertainty about future policy decisions, and higher vulnerability to crises.2 High public debt is also likely to constrain the scope for countercyclical fiscal policies, which may result in higher output volatility and further lower growth (Aghion and Kharroubi, 2007; and Woo, 2009). The risks associated with high public debt are amplified by Hungary’s high external debt and reflected in Hungary’s risk premia, which—although moderating recently—remains substantially above the pre-crisis levels and has decoupled from those of its peers.

A01ufig04

5-Year CDS Spreads: Hungary and Peers

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Source: Bloomberg.

8. Moreover, difficult business climate, and weak policy and institutional frameworks are weighing on competitiveness and competition, undermining productivity, confidence, investment, and growth.

A01ufig05

Share in the World’s Exports

(2007q1=100)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Source: IMF Direction of Trade Statistics.
A01ufig06

Investment Volume by Sector, 2008–2013

(2008=100)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Sources: Haver Analytics and IMF staff calculations.

C. Potential Output Growth in a Baseline Scenario

9. A number of alternative estimation techniques are employed to assess the impact of the global financial crisis on Hungary’s current and medium term potential growth. The different approaches can be classified into some of the de-trending statistical methods, such as Hodrick-Prescott filter (HP), Baxter-King Band-Pass filter (BK), and the Unobserved Component method using Kalman filter (KF). The latter is also extended into a multivariate system that includes structural relationships between economic variables. A more structural approach for output gap estimation that is being used in this chapter is the Production Function method (PF). The main features of each methodology are described in Appendix I.

A01ufig07

Hungary. Potential Growth Estimates

(Percent)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Source: IMF staff’s calculations.

10. Estimation results point to a substantial deceleration of potential growth during the global financial crisis. In the early 2000s potential growth hovered around 3½ percent. However, starting in 2007, all estimates indicate a substantial deceleration, which, apart from the PF estimation, turned negative at a later stage. Specifically, the HP and BK estimations suggest a shift to negative growth rates in 2008, while the two specifications under the unobserved components method point to a shift to a negative territory in 2009 (KF2) and 2010 (KF1). The production function approach exhibits a smoother trajectory over time and, although decelerating sharply in 2006-09, potential growth rates remained positive. In 2013, the average potential growth was around zero, with three methodologies (PF, HP and BK), pointing to a positive rates (average ½ percent), while the two specifications under the unobserved components method still suggesting negative rates (-0.7 percent).

11. The production function approach suggests a deceleration of potential growth mainly due to TFP and capital stock. Although the contribution of both capital and TFP to potential growth continued to be positive, it declined significantly since 2007. More specifically, the contribution of TFP moderated to an average of ½ percent per annum in 2007–13 from an average of about 2 percent in 2000–06, while the contribution of capital declined to an average of 0.4 percent in 2007–13 from 0.9 percent in 2000–06. The contribution of labor turned negative during 2005–12, but remained modest.

A01ufig08

Contribution to Potential Output Growth

(Production Function Approach)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Source: IMF staff’s calculations.

12. Going forward, potential output growth is projected to somewhat recover but remain subdued. Using the IMF’s World Economic Outlook (WEO) real GDP growth and investment projections, as well as the 10-year average annual growth of employment and hours per employee, the estimated potential growth by the five methodologies gradually increases over the medium term from zero in 2013 to about 1.2 percent in 2019 (on average). That said, the uncertainty regarding these estimations remains high as they vary in a relatively wide range between 1.7 percent (HP filter) and 0.9 percent (KF1).

A01ufig09

Hungary. Potential Growth Estimates

(Average and range, Percent)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Source: IMF staff’s calculations.

13. Based on current policies, Hungary’s medium term potential growth is expected to lag behind that of its peers. Despite the modest economic recovery in 2013 and more favorable external conditions in 2014, Hungary’s medium term growth prospects are projected to remain weak mainly on account of continued low investment and modest TFP growth. A shift to a higher growth trajectory will necessitate the implementation of structural reforms to raise investment and productivity. As such, it would be important to change the policy direction with greater focus on removing structural impediments in the labor markets, boosting market confidence and investment by increasing policy predictability, and strengthening the business climate by reducing the regulatory and tax burdens.

A01ufig10

Potential Growth: Hungary and Peers over the Medium-term

(Range and average, 2013–2019)

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Source: IMF World Economic Outlook.

D. Potential Output Growth in a Reform Scenario

14. A model-based approach is employed to assess the impact of structural reforms on Hungary’s potential output over the medium-term. We employ the Emerging Europe module of the IMF’s Flexible System of Global Models (FSGM). The FSGM is a semi-structural, multi-region, general-equilibrium model. It contains some key elements, like private consumption and investment, which have solid micro-foundations, while other elements such as trade, labor supply and the Phillips curve have reduced-form representations. Aggregate supply in the model is based on an aggregate Cobb-Douglas production function. There is a full stock-flow consistency in the model, and agents use model-consistent expectations. Monetary and fiscal policies are endogenous and pinned down with simple rules.7 The reforms under consideration are: (i) labor market reforms to increase labor participation rate; (ii) budget-neutral fiscal reforms to improve the quality of fiscal policy; and (iii) structural reforms to enhance the business environment. The impact of the full implementation of the reform package on key variables is depicted as deviations from the baseline scenario in Figure 1. Specifically:

Figure 1:
Figure 1:
Figure 1:

Hungary Reform Scenario

Citation: IMF Staff Country Reports 2014, 156; 10.5089/9781498379861.002.A001

Source: IMF staff calculations.

15. On whole, these structural changes could boost Hungary’s potential output level and growth rate significantly, largely through the investment and consumption channels. Relative to the baseline scenario, investment, consumption, and potential output levels could be above the baseline trajectory by 12, 6, and 13 percent, respectively over the course of the next decade or so—supported by (i) the increase in human wealth on the back of higher labor participation rate; (ii) the increase in financial wealth, on the back of increased investment activity, owing to lower cost of capital, as sectoral taxes are eliminated, and the sovereign’s risk premium is reduced (Figure 1). Over the medium-term, potential output growth could reach its pre-crisis rates, and, as the economy catches up in the longer term, potential growth decelerates and converges to that of the advanced economies (Figure 1).

E. Summary and Conclusions

16. Hungary’s growth performance has been weak in recent years. Following robust growth in the decade that preceded the financial crisis, economic activity moderated considerably in 2007–08, and contracted sharply in 2009. The inventible external and domestic adjustment that took place since the onset of the crisis, alongside the deterioration in the operating environment for banks, the erosion of competitiveness, and weakened business climate, in part due to the government’s interventionist policies, have undermined investment and productivity, and contributed to a substantial moderation of potential growth.

17. Based on current policies, the medium term growth prospects—although somewhat improving—remain subdued and below that of Hungary’s peers. While the drag from the private sector’s deleveraging is projected to gradually diminish over the medium term, policy unpredictability and persistent interventionist government policies are likely to continue depress private investment. At the same time, labor market performance, while gradually improving, is held back by the low participation rate, weak labor productivity, and skill mismatches. Although estimations are subject to high uncertainty, they suggest that, under current policies, potential output growth is likely to accelerate modestly to 0.9–1.7 percent in 2019 from just above zero in 2013.

18. Lifting Hungary’s potential growth calls for an ambitious reform agenda. Key elements of such a reform package should include (i) labor market reforms to increase labor participation rate; (ii) budget-neutral fiscal reforms to enhance the quality of fiscal policy that focuses on eliminating distortionary taxes; and (iii) structural reforms to improve the business environment, including by strengthening policy predictability, reducing the regulatory burden, and enhancing competition in the product and services markets.

19. Results of simulations using a model-based approach suggest that there are large gains in potential output associated with the full implementation of the reform policy package. More specifically, and although estimates are inherently uncertain, model simulations suggest that under such a reform scenario, potential growth could return to its pre-crisis rates over the medium term.

Appendix I. Review of Estimation Methods

The Hodrick-Prescott (HP) filter Overview

The Hodrick-Prescott filter (1997) is a simple smoothing procedure and one of the most common methods to estimate the potential output. The main assumption is that the potential output varies smoothly over time, and, as such, this method minimizes the gap between actual output (y) and potential output subject to a penalty that constrains the second difference of potential output, as follow:

Mint=1T(yty^t)2+λt=2T1[(y^t+1y^t)(y^ty^t1)]2(1)

where λ determines the degree of smoothness of the trend. Following the standard practice for quarterly data, we adopt a smoothness parameter equal to 1,600. In addition, to avoid the endsample bias, we extended the sample to 2019 using the April 2014 WEO real GDP growth forecast.

Baxter-King Band-Pass filter

Another univariate approach to filter a time series was developed by Baxter-King (1995). The advantage of this approach (compared to the Hodrick-Prescott filter) is that it isolates the cyclical component of a time series by specifying a range for its duration. Thus, the business cycles, and the high frequency components that reflect irregularities or seasonal effects do not affect the trajectory of potential output. The business cycle duration is set to last between 2 to 32 quarters, though other specifications were tested as well, yet they did not produce results that differed significantly.

Unobserved Component methods using Kalman filter

This methodology is commonly used to estimate the two unobserved components of GDP: the trend component (potential output) and its cyclical component (the output gap). It allows identifying unobserved variables by their link to observed variables and by their underlying statistical process. We follow Fuentes et al. (2007) and Magud and Medina (2011) with some modifications, and present two alternative models: (i) a univariate model that includes one signal equation, which is close in its characteristic to a Hodrick-Prescott filter though it allows a stochastic variation of potential output, and (ii) a multivariate filter that includes a Phillips curve.

Model 1 (KF1)

The state space form of the univariate filter can be presented as follows:

yt=y^t+ytc(2)
y^t=y^t1+gt1(3)
gt=gt1+εtg(4)
ytc=θyt1c+εtcθ<1(5)

The variables ytc and gt represent the cyclical component of yt (the output gap) and the trend growth, respectively. εtc and εtg are residual terms of mean 0 and variances σc2 and σg2, respectively. The cyclical component of output follows an autoregressive process, and θ is lower than one to ensure a stationary process. The smoothness of the trend component is controlled by constraining the relative variance (σc2/σg2). The system can be estimated by Kalman filter, using eq. (2) as a signal equation and equations (3)-(5) as the transitional equations.

Model 2 (KF2)

In this model, we add a backward-looking Phillips curve as a second signal equation in the system presented above, which implies that inflation path is affected by past core inflation, as well as current and past output gaps, as follows:

πt=p=1Pαpππtp+q=1Qαqyytqc+εtπ(6)

Where πt is core inflation rate and εtπ is a white noise process of mean 0 and variance σπ2. The parameters p and q refer to the lags of inflation and output gap, respectively.

Production function

This approach assumes the output can be reflected by the following standard Cobb-Douglas production function:

Yt=AtKt(1α)(LtHt)α(7)

Where Yt represents domestic output in period t, Kt the physical capital stock, Lt the employed labor force, Ht the hours worked per worker, and At total factor productivity (TFP). The labor share of output, α, is set to 0.64, consistent with the long-term average.

We use annual data from different sources. The number of employees and hours per worker is taken from the OECD; and real GDP is taken from WEO. The capital stock series is constructed with investment data from the Penn World Tables using the perpetual inventory method until 2010, and investment real growth from WEO for 2011–19 to calculate the capital stock. In particular, we assume that the economy is on a balanced growth path at time zero and compute the initial capital stock, K0, according to the expression:

K0=I0(1+g)(1+n)(1δ)(8)

where I0 is the initial investment expenditure, g is the technological progress rate, n is the population growth rate, and δ is the rate of capital depreciation. Like Sosa et al. (2013), we assume that g is equal to 1.53 percent; δ is equal to 3.5 percent; and n is equal to the average annual growth of population (-0.08 percent).

Using Eq. (7) and Eq. (8), we can extract the TFP growth as follows (denoting X^ the growth rate of the variable X):

A^=Y^αL^αH^(1α)K^(9)

Appendix II. Description of the Flexible System of Global Models (FSGM)

Overview

IMF’s Flexible System of Global Models (FSGM) is a suite of several region-specific modules used for major IMF publications, such as the World Economic Outlook and the Spillover Report. Each of these modules features an identical economic structure, but differs in its coverage of countries in order to suit the needs of the IMF’s area departments. The Emerging Europe module (EEUmod) used for the policy-reforms scenario considered in this chapter is one such module.

Although a complete exposition of the model is beyond the scope of this chapter, we present the key elements of the model, which are most relevant for this scenario (potential output, and investment behavior) below.

Aggregate Demand

Aggregate demand follows the standard national expenditure accounts identity, where GDP is the sum of household consumption, private business investment, government absorption and exports of goods and services, less imports of goods and services.

Private Consumption

The consumption block uses a discrete-time representation of the Blanchard-Weil-Yaari overlapping generations model (OLG), based on a constant-elasticity-of-substitution utility function containing only consumption. Using OLG households rather than the typical infinitely-lived households results in important non-Ricardian properties whereby the path for government debt has significant economic implications. Essentially the OLG framework means that households treat government bonds as wealth since there is a chance that the associated tax liabilities will fall due beyond their expected lifetimes. The OLG formulation results in the endogenous determination of national savings given the level of government debt. The world real interest rate adjusts to equilibrate the global supply of and demand for savings. The use of an OLG framework necessitates the tracking of all the stocks and flows associated with wealth—human wealth (based on labor income) and financial wealth (based on government debt, the private business capital stock, and net foreign assets). It should be noted that financial markets are incomplete, so international financial flows are tracked as net positions (net foreign assets or net foreign liabilities) and denominated in U.S. dollars.

Consumption dynamics are driven not only by OLG households, but also by liquidity constrained (LIQ) households. LIQ households do not have access to financial markets, do not save, and thus consume all their income each period. This feature amplifies the non-Ricardian properties of the basic OLG framework.

Private Investment

Private business investment uses an updated version of the Tobin’s Q model, with quadratic real adjustment costs. Investment is negatively correlated with real interest rates. Investment cumulates to the private business capital stock, which is chosen by firms to maximize their profits. The capital-to-GDP ratio is inversely related to the cost of capital, which is a function of depreciation, the real interest rate, the corporate tax rate, and relative prices.

Public Absorption

Government absorption consists of spending on consumption and investment goods. Government consumption spending only affects the level of aggregate demand. It is an exogenous choice determined by the fiscal authority. The level of government investment is also chosen exogenously, but in addition to affecting aggregate demand directly, it also cumulates into a public capital stock, which can be thought of as public infrastructure (roads, buildings…etc.). A permanent increase in the public capital stock permanently raises the economy-wide level of productivity.

Net Exports

The level of net exports is determined in the long run by the real competitiveness index (RCI) that adjusts to achieve the current account balance required to support the desired net foreign asset position. Exports and imports, individually, are modeled as reduced-form equations. Exports increase with foreign activity, and are also an increasing function of the depreciation in the RCI. Imports increase with domestic activity, and are also an increasing function of the appreciation of the REER.

To keep the dimensionality of the model small enough to allow it to have a large number of individual country blocks, the model does not track all the bilateral trade flows among countries. The model has, however, been developed to have exchange rate and export volume properties that are similar to the IMF’s multiple-good, structural models. This is accomplished by having time-varying trade shares that are a function of the relative level of tradable and non-tradable productivity within each country. Consequently, the model is able reproduce the currency appreciation that results when a country’s tradable sector productivity growth exceeds that in the non-tradable sector (Balassa-Samuelson effect). Further, even though only the aggregate levels of exports and imports are tracked in each country, there are mechanisms in place that ensure global exports and imports sum to zero.

Importantly, the current account and implied net-foreign-asset positions are intimately linked to saving decision of the households. The model can be used to study both creditor and debtor nations as non-zero current accounts can be a feature of the well-defined steady-state in the OLG framework.

Aggregate Supply

Aggregate supply is captured by potential output, which is based on Cobb-Douglas production technology with trend total factor productivity, the steady-state labor force, the non accelerating inflation rate of unemployment (NAIRU), and the actual capital stock.

Steady-state population growth is taken as exogenous, although there are cyclical variations in both the participation rate and the unemployment rate. The behavior of the participation rate is based on properties of labor supply observed in other IMF structural models, such as the Global Integrated Monetary and Fiscal Model (GIMF) and Global Economy Model (GEM). The unemployment rate varies relative to the NAIRU according to an Okun’s law relationship based on the output gap.

Prices

The core price in all regions is the consumer price index excluding food and energy, CPIX, which is determined by an inflation Phillips curve. CPI inflation is sticky and reflects the expected paths of exchange rates and the economic cycle, as captured by the output gap. In addition, although the direct effects of movements in food and energy prices are excluded, there is a possibility that persistent changes in oil prices can leak into core inflation. The degree of forward-looking behavior in inflation is country specific.

The prices mimic the structure of production of consumption, investment, government, and exports of goods and services. The consumption deflator is the CPI (including the effects of oil and food prices). The investment deflator is a weighted average of the deflators for GDP and imports. The government deflator moves in tandem with the CPIX deflator. The deflator for exports is an estimated equation, with coefficients on the GDP deflator, and a competitiveness-weighted average of the relative price of foreign goods, accounting for real exchange rate movements. The import deflator is an import-weighted average of all other countries’ export price deflators. Finally, the GDP deflator itself is a real-component-weighted average of the consumption, investment, government, export and import deflators.

In addition, there is a Phillips curve for nominal wage growth. Wage inflation exhibits stickiness and allows the real wage to return to its equilibrium only gradually depending on the expected evolution of overall economic activity.

Monetary and Fiscal Policy

In the short run, the nominal side of the economy is linked to the real side through monetary policy. The behavior of monetary authorities is represented by an interest rate reaction function. The standard form is an inflation-forecast-based rule operating under a flexible exchange rate. However, the form of the interest rate reaction function is such that there is scope for a fixed exchange rate regime, monetary union, or a managed floating exchange rate regime.

The model also contains a 10-year interest rate that is based on the expectations theory of the term structure, plus a term premium. The interest rates on consumption, investment, government debt and net foreign assets are weighted averages of the short-term policy rate and the 10-year interest rate, reflecting their differing term structures, and allowing for a meaningful role for the term premium.

The government sector is much broader than government absorption. There is additional spending by the fiscal authority on lump-sum transfers to all households, or targeted exclusively to liquidity-constrained households. The fiscal authority chooses a long-run level of debt relative to GDP (or conversely, a long-run deficit target). In order to meet its debt or deficit targets, as well as spending obligations, it can tax, using consumption taxes (VAT), labor income taxes, corporate income taxes and lump-sum taxes. In the face of shocks to the economy under the default fiscal reaction function, all tax rates remain fixed and spending on general lump-sum transfers adjusts to ensure that the public debt-to-GDP ratio is maintained in the medium term. However, the fiscal reaction function can also be specified to use other instruments besides general transfers.

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1

Prepared by Asmaa El-Ganainy and Nir Klein (both EUR), and Patrick Blagrave (RES).

2

See Elmendorf and Mankiw (1999) for a comprehensive literature survey on the macroeconomic effects of public debt.

3

See Box 4 of the Staff Report for the 2014 Article IV Consultation.

4

See Staff Report for the 2014 Article IV Consultation.

5

For instance, in the energy sector, the effective CIT rate can reach up to 50 percent (OECD, 2014).

6

In 2010, the government imposed a temporary price freeze on energy prices. In 2013, regulated energy prices in electricity, gas, and district heating for households were cut by a total of 20 percent in two steps, and the cost has been borne by foreign energy providers. In 2014, another round of government-mandated reduction of energy prices for households was approved by the Parliament to take place in three steps (the price of natural gas was lowered by 6.5 percent as of April 1; whereas the price of electricity will drop by 5.7 percent as of September 1, and that of district heating by 3.3 percent as of October 1).

7

See Appendix II for more details about the FGSM.

8

See Chapter III for more details on Hungary’s recent labor market trends, reforms, and policies.

9

When considered in the context of recent history, this speed of adjustment seems reasonable, as the activity rate increased at roughly this pace during 2009–12.

10

Sectoral taxes are levied in Hungary on a number of sectors, particularly those with relatively large foreign ownership, including, financial, energy, telecommunication, and retail sectors. Such taxes adversely affect growth through their negative effect on the business climate, foreign investment, bank lending, competition, and inefficient allocation of resources. Sectoral taxes are proxied in the model using capital taxes.

Hungary: Selected Issues
Author: International Monetary Fund. European Dept.