Republic of Poland: Selected Issues
Author: International Monetary Fund. European Dept.
Publication Date:
17 Jul 2017
eISBN:
9781484310311
Language:
English
Keywords:
ISCR; CR; Poland; TFP growth; firm; investment; infrastructure gap; cyclical position; lack of progress; product market regulation; gaps vis-à-vis; Potential output; Infrastructure; Output gap; Structural reforms; Europe; Global
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Selected Issues

Abstract

Selected Issues

Long-Run Growth—Baseline and Reform Scenarios

Shrinking labor supply and slower TFP growth imply a much slower pace of income convergence to advanced Europe going forward. Addressing structural bottlenecks will be critical for improving allocative efficiency and lifting investment and TFP growth. An illustrative reform scenario shows that under realistic assumptions (calibrated based on the historical experiences of the OECD countries), specific improvements in the product market and labor market regulations, as well as higher infrastructure investment and R&D support could significantly increase the level of GDP in Poland by 2030, though more efforts would be needed to reach the goal set out in the government’s Responsible Development Strategy.

A. Baseline Scenario1

1. A fresh look at Poland’s potential output is needed to better understand the current cyclical position of the economy and the impact of recent policies on the long-term growth. The latest economic indicators point to a strong cyclical upswing. Following a temporary slowdown in 2016, GDP growth strengthened to 4 percent (y/y) in 2017:Q1 amid a record low unemployment and rising core inflation (Figure 1). However, the views on the strength of the cyclical recovery and the output gap estimates vary across different institutions (Figure 1). Furthermore, some recent policies, notably the decision to reverse the 2013 retirement age increase, are likely to have a significant impact on the labor supply over the medium to long term (as discussed in Chapter 1), which is yet another reason for taking a closer look at Poland’s potential growth.

Figure 1.
Figure 1.

Cyclical indicators and Output Gap Estimates

Citation: IMF Staff Country Reports 2017, 221; 10.5089/9781484310311.002.A004

Sources: National authorities and IMF staff calculations.Note: NBP’s estimate (March 2017) is based on a structural macro-model; European Comission’s (EC) estimate (February 2017) is based on a Production Function Approach; IMF’s estimate (January 2017) is based on a version of the HP filter.

2. This section presents estimates of potential output and output gap for Poland based on a range of methods. These include: (i) a univariate Hodrick-Prescott (HP) filter; (ii) a multivariate filter (MVF); and (iii) a production function approach (PF). While each method has its own merits and limitations, taken together they can provide a good gauge of Poland’s cyclical position:

  • The HP filter is a purely statistical method, which minimizes deviations from trend based on a statistical smoothing formula. While this method is easy to use, as it only requires information on the GDP time series, it suffers from the well-known end-of-sample bias and the results are sensitive to the assumption on the smoothing parameter. The end-of-sample problem is typically mitigated by using forecasts.

  • The MVF filter-based approach, developed by Blagrave, et al. (2015), exploits the economic relationships between inflation, unemployment and output gap, guided by standard economic theories—Phillips curve and Okun’s law. It improves the estimation of potential output and output gap by incorporating more information from different cyclical indicators. It also uses the medium-term growth and inflation forecasts to address the end-of-sample problem. But the accuracy of this method depends on whether the underlying economic relationships hold and the assumed values of certain smoothing parameters.2

  • The PF approach, following the framework in Podpiera, et al. (2017), decomposes potential growth into its key production factors-Capital, Labor and TFP, while it also captures the cycles in labor (AHW-average hours worked) and capital (CU-capacity utilization) aiming to improve the estimate of the residual item-TFP. This method provides insights into the key growth drivers from the supply side, but it also relies on the HP filter approach to decompose production factors into structural and cyclical components.3

3. All three methods point to a post-crisis slowdown in potential growth and a slightly positive output gap in 2016. The estimated potential growth has declined significantly from the pre-crisis peak of above 5 percent to 2.5–3 percent in 2016, suggesting that the post-crisis growth slowdown has been largely structural. The negative output gap experienced during the global financial crisis and European debt crisis was largely closed by 2015, with a slightly positive output gap opening in 2016. The differences between the estimates generated using the three different approaches are relatively small, especially in the most recent period (Figure 2).

Figure 2.
Figure 2.

Backward Looking—Potential Output and Output Gap Estimates

Citation: IMF Staff Country Reports 2017, 221; 10.5089/9781484310311.002.A004

Source: IMF staff calculations.Note: MVF results incorporate information from growth, headline inflation, unemployment, consensus forecasts of growth and inflation; alternative measures of inflation (core inflation, Unit labor cost, NBP calculated domestic inflation) yield similar results.

4. The decline in potential growth has been largely due to the TFP growth slowdown, followed by declining labor contribution. A decomposition of potential growth based on the PF approach suggests that the post-crisis potential growth was mainly dragged down by stagnant TFP growth and to a lesser extent, by shrinking labor contribution (Figure 3).

  • The adjusted TFP contribution (adjusted for AHW and CU) has dropped from the pre-crisis peak of 3 percent to negative in 2016. If we look at the standard TFP contribution (the sum of the adjusted TFP, AHW and CU), it has also declined significantly from 2.4 percent to around 0.7 percent in 2016.

  • The reduced labor contribution post-crisis largely reflects negative demographics, as the working age population has been on a declining trend since 2012. Although the trend employment growth has picked up moderately since 2012 following the drop during the crisis times, this is partially offset by the decline in average hours worked (AHW) after the crisis.

  • The post-crisis investment growth has been very volatile amid some temporary rebounds, with the average growth of capital stock fluctuating around 3 percent. However, the capacity utilization has been rising quickly and approaching the pre-crisis peak. Thus, capital accumulation has become the main growth driver, supported by rising capacity utilization.

Figure 3.
Figure 3.

The Production Function Approach

Citation: IMF Staff Country Reports 2017, 221; 10.5089/9781484310311.002.A004

Sources: National authorities and IMF staff calculations.

5. Over the medium term, on current policies, potential growth will likely remain below 3 percent. The impact of unfavorable demographics will become more pronounced (see Chapter 1). TFP growth is expected to recover somewhat reflecting an improvement in the external environment (see Chapter 3). As investment gradually picks up, the contribution from capital accumulation will also increase (see Chapter 2). However, on current policies, the baseline potential growth will likely stabilize around 2.7–3.0 percent (Figure 4), which is well below the pre-crisis average.

Figure 4.
Figure 4.

Forward Looking—Baseline Potential Growth

Citation: IMF Staff Country Reports 2017, 221; 10.5089/9781484310311.002.A004

Source: IMF staff calculations.

B. Reform Scenarios4

6. The key structural reform gaps are identified using both quantitative indicators and qualitative assessments. Quantitative indicators point to four main areas where structural reform gaps appear to be the largest: infrastructure, business regulation, labor market efficiency and R&D/innovation (see Chapter 3, Figure 8). Qualitative assessments by various international institutions have, in addition, consistently identified shortcomings in the labor market regulations, human capital development and government efficiency (Figure 5).

Figure 5.
Figure 5.

Poland: Structural Reform Priorities

Citation: IMF Staff Country Reports 2017, 221; 10.5089/9781484310311.002.A004

1/ based on findings for all emerging markets, not Poland-specific. See “Staff Note for the G20—A Guiding Framework for Structural Reforms”.2/ based on the comparisons of institutional indicators for Poland relative to other OECD and CESEE countries, see IMF REI (May 2016) for more details;3/ based on the IMF staff’s recommendations over the past four years, see 2016 Article IV, 2015 Article IV, 2014 Article IV, and 2013 Article IV for more details;4/ see “Economic Policy Reforms: Going for Growth” Country Note on Poland (2015) for more details.5/ includes areas, where progress falls short of targets, see EC Country Report (2017) for more details.6/ areas where most indicators for Poland are below the OECD average.7/ areas where most indicators for Poland are below the OECD average, but the gaps are relatively small compared to the most lagging reform areas.

7. To assess the potential long-run economic impact of structural reforms, we estimate the impact of fully or partially closing the structural reform gaps in four areas:

  • The product market regulation (PMR) reforms could include the deregulation of network industries (gas, airlines and road sectors), easing of administrative burdens for startups, and changes to the regulations of retail and professional services. These reforms could help boost TFP and increase private investment

  • Labor market reforms include active labor market policies (ALMP), increasing spending on childcare and early education, and relaxing employment protection. These reforms could help raise the labor force participation, increase labor mobility and reduce skills mismatches.

  • Increasing infrastructure investment could help boost TFP and increase private investment.

  • Increasing funding for R&D could help boost the R&D activity and innovation.

8. The reform efforts are assumed to vary across the three reform scenarios, with the first scenario aiming to be somewhat more realistic than the other two. In the first scenario, the reform efforts assumptions are calibrated by taking into account the past performance of Poland and other OECD countries, as well as the size of Poland’s reform gaps relative to the OECD average (Table 1). For example, in the areas where Poland has been significantly lagging behind the best performers, it may be unrealistic to expect rapid progress leading to the closing of the reform gaps by 50 percent or more over the projection period, especially where gaps relative to the OECD average are large. Hence, the assumptions on the reform efforts vary across different structural reform areas:

  • In terms of relaxing regulations of the network industries, professional services and retail distribution, Poland does not seem to have made tangible changes during 2008–13, while the best performers achieved substantial progress (Table 1). Given Poland’s lack of progress in the past, assumptions on future reform efforts are also less ambitious. If Poland were to close the gaps relative to the current OECD average by around 25 percent in the gas sector, by 40 percent in the airlines and road sectors, and by 45 percent in the professional services and retail distribution, then each of the relevant PMR sub-index would decline by 0.4 points (which is roughly similar to the average reform effort of other OECDE countries that carried out such reforms during 2008–2013).

  • In contrast, Poland has been the best performer among the OECD countries in reducing the administrative burdens on startups, and therefore, a faster closing of the gap might be feasible. A decline of 0.71 points in this PMR sub-index would allow Poland to fully close the gap relative to the current OECD average.

  • Similarly, on active labor market policies (ALMPs), Poland could aim to reach the OECD average by increasing public expenditures on the ALMPs from 10.5 percent to 14.8 percent of the GDP per capita.

  • Public expenditures on childcare and early education services in percent of GDP in Poland increased by only 0.02 percentage points during the 2008–13 period, whereas the best performing OECD country increased these expenditures by 0.73 percentage points. Given the relatively weak past performance, a realistic target for Poland might be to increase the public expenditures by 0.18 percentage points to close half of the gap relative to the OECD average.

  • The employment protection index in Poland is higher than the OECD average, though the gap is relatively small compared to other areas. Thus, Poland could aim to lower the employment protection index by 0.25 points, i.e., below the OECD average.

  • Poland has doubled its direct public funding of business R&D between 2008 and 2013. Given this, Poland could aim to maintain the same pace to reach the OECD average.

  • Boosting the infrastructure investment-to-GDP ratio by 0.36 percentage points (annual average during 2017–30, relative to the baseline) would allow Poland to close the infrastructure gap, measured using public capital stock-to-GDP as a proxy, relative to the EU average by around 27 percent (see below for details).

9. The second and third scenarios assume reform efforts that would close the gaps vis-à-vis the OECD average by half or fully in most reform areas. Specifically, the second scenario assumes that all reform gaps (except for infrastructure gaps) are closed by half relative to the current OECD average by 2030, whereas the third scenario assumes that all reform gaps (except for infrastructure gaps) are fully closed relative to the current OECD average by 2030 (Figure 6, Table 1). In all three scenarios, the additional infrastructure spending is calculated as a residual, based on the remaining fiscal space after accounting for the fiscal costs related to other reforms and allowing for some buffer relative to the EDP limit and the debt limits. Under this approach, infrastructure gaps in all three scenarios are closed by 26 to 28 percent relative to the EU average by 2030, depending on the fiscal costs of other reforms. Assuming higher infrastructure spending would entail larger fiscal outlays, which would not be feasible given the fiscal rules and debt sustainability considerations.

Figure 6.
Figure 6.

Potential Gains from Structural Reforms

Citation: IMF Staff Country Reports 2017, 221; 10.5089/9781484310311.002.A004

10. The impact of structural reforms is assessed using a semi-structural general equilibrium model calibrated for Poland.5 First, the effects of structural reforms are mapped into changes in the total factor productivity (TFP) and in the aggregate labor force participation (LFP) rate. The general equilibrium impact of each reform is then estimated using the FSGM model. Deregulating product markets and increasing funding for the business R&D are simulated as shocks to the TFP, whereas all labor market reforms are simulated as shocks to the LFP rate. Infrastructure investment is simulated as a shock to public investment. Private investment responds endogenously to higher TFP, and hence, higher expected return on investment.

11. The impact on the level of GDP is estimated using the elasticities from the literature. For the ALMPs, elasticities are from Barnes et al. (2013); for reforms of the childcare and early education services, elasticities are from Thevenon (2013) 6; for the impact of increased government spending on supporting business R&D, elasticities are from the April 2016 Fiscal Monitor, Chapter 2. All reforms except infrastructure investment are phased in over ten years, and economic agents are assumed to respond to specific reforms (as they are phased in) but not instantaneously to the entire reform package. Additional infrastructure spending (as a share of GDP) increases gradually over the entire period between 2017 and 2030, with the size determined by available fiscal space every year (as discussed above). The impact of the fiscally costly reforms on output also reflects the macroeconomic effects of the required increase in deficit financing.

12. Under the three reform scenarios, the level of GDP could be lifted by about 7–11 percent by 2030 (Table 1). The reform scenario of fully closing the gaps generates the largest output gains (around 11 percent above the baseline GDP level by 2030), with a sizable contribution coming from fully closing the gaps in the PMR. If Poland were to close half of all reform gaps relative to its OECD peers, then the potential output could increase by around 6.8 percent by 2030. The scenario of fully closing reform gaps could be considered too optimistic in some areas, such as regulations of the gas, airlines and road sectors, where previously Poland did not make much progress, whereas the scenarios of closing the gaps by half could be underestimating the reform potential in certain areas, such as reducing administrative burdens on startups, where Poland has made significant progress in the past. Given these considerations, the first scenario, based on past reform experiences of Poland and other countries, is the most realistic one, which suggests a total reform impact on potential output of about 7 percent (Figure 6 and Table 1). In this scenario, reducing the administrative burdens on startups would generate the largest output gains (around 1.4 percent), followed by increasing infrastructure spending (1.2 percent), reducing sectoral regulations on professional services and retail distribution, and relaxing employment protection (each around 0.8 percent). The estimated impact of other reforms on potential output is around 0.5–0.7 percent, except for the ALMP where the estimated impact is more modest (0.2 percent). The overall impact of the PMR reforms is larger than that of the fiscally costly reforms, given fiscal constraints.

13. The prioritization of reforms should be based on their potential impact on growth, available fiscal space and the cyclical position of the economy.7 The estimated impact on output is shown in Figure 6, Table 1. The PMR reforms—that do not entail any fiscal outlays—generate the highest impact on output over the long run, whereas direct public funding for business R&D is estimated to have the largest impact on potential output per percentage point increase in government deficit over GDP. The fiscal space is limited, given the fiscal rules and the need to address long-term aging costs. In each scenario, the package of fiscally costly reforms utilizes the entire available fiscal space. In Figure 6, the fiscal cost of each reform is shown as an annual increase in the fiscal deficit (in percent of GDP). In general, with limited fiscal space, the priority could be given to reforms that do not require additional public expenditures, while fiscally costly reforms could, in the first instance, be financed by the allocated EU funds. The current cyclical position of the economy is favorable, which bodes well for structural reforms, including those that might have a slight contractionary impact on domestic demand in the near term (e.g., relaxing employment protection), but could generate sizable gains over the long term.

14. The reforms discussed above would help achieve some of the goals set out in the Responsible Development Strategy (RDS). The overarching goal of the RDS is for Poland to achieve convergence with the EU average per capita income by 2030. The key policy areas in the RDS —re-industrialization, development of innovative firms, development of the SME sector, building Polish brand and promoting expansion of Polish companies abroad, mobilizing capital for development and promoting social and regional development—include some the reform areas discussed above (see text table in section D of the 2017 Article IV Staff Report). Staff’s estimates suggest that under a range of plausible reform scenarios focusing on the product market regulations, raising the labor force participation, upgrading infrastructure and increasing support for R&D, the level of output in Poland could be lifted by about 7–11 percent by 2030, allowing the authorities to cover about 1/3 of the distance to their convergence objectives (Figure 6). Reaching the convergence objectives by 2030 would likely require greater reform efforts in these as well as in other areas. Other areas not included in the simulations, but where there is also scope for improvement (relative to the OECD average), include human capital development and institutions/government efficiency.

Table 1.

Poland Structural Reform Scenarios: Assumptions, Costs, Results

article image
Sources: OECD and IMF staff calculations.Note: Past experiences for the R&D reforms are based on the difference between 2012–14 average and 2007–09 average. All other past experiences are based on the differences between 2008 and 2013 indicators.

For the PMR, 0.4 percentage points decline is assumed for Poland by using judgement based on Poland’s and OECD best performers’ experiences in reducing the regulations in these sectors during the 2008–13 period. With these assumptions, Poland closes gaps relative to the OECD average by 25 percent in gas sector, 40 percent in airlines and road sectors, and 45 percent in professional services and retail distribution.

The infrastructure gap is proxied by the difference between Poland’s public capital stock/GDP and the EU average. Infrastructure spending in three reform scenarios is calculated as a residual item by utilizing the available fiscal space after taking account into the fiscal costs of other reforms, while also leaving some “safety buffer” relative to the EDP debt and deficit limits. For all other reforms with fiscal costs, the spending target is reached gradually over the next 10 years. For instance, for the R&D the first-year spending in percent of GDP is higher by 0.04/10 pp, in the second-year it is higher by 0.08/10 pp… etc. Once the target spending level is reached, it is maintained for the 2027–2030 period. The impact on the government deficit/GDP for infrastructure spending refers to the average over the entire 2017–2030 period.

References

  • Andrle, M., P. Blagrave, P. Espaillat, K. Honjo, B. Hunt, M. Kortelainen, R. Lalonde, D. Laxton, E. Mavroeidi, D. Muir, S. Mursula, and S. Snudden, 2015, “The Flexible System of Global Models – FSGM,” IMF Working Paper, No. WP/15/64.

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  • Barnes, S., R. Bouis, P. Briard, S. Dougherty, and M. Eris, 2013, “The GDP Impact of Reform: A Simple Simulation Framework,” OECD Economics Department Working Papers, No. 834, OECD Publishing.

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  • Blagrave, et al., 2015, A Simple Multivariate Filter for Estimating Potential Output, IMF Working Paper No. 15/79.

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1

Prepared by Xin Cindy Xu.

2

For details on the MVF approach, see Blagrave, et al., 2015, A Simple Multivariate Filter for Estimating Potential Output, IMF Working Paper No. 15/79.

3

For details on the PF approach, see Podpiera, et al., 2017, A Fresh Look at Potential Output in Central, Eastern and Southeastern European Countries, IMF Working Paper No. 17/37.

4

Prepared by Ezgi O. Ozturk and Zoltan M. Jakab.

5

The model is a variant of the IMF’s Flexible System of Global Models (FSGM), see in Andrle and others (2015).

6

We used the estimates for childcare expenditures which control for labor market characteristics and other interaction variables (Thevenon (2013) Table 5, Column 3)). Thevenon (2013) estimated the impact of childcare and early education for children under 3 years. Since we focus on the total childcare and early education expenditures, we assumed that expenditures on children under 3 years are changed by the same proportion as total expenditures. Thus, the elasticity of Thevenon (2013) could be applied in our exercise.

7

This approach to prioritize structural reforms is discussed in the IMF’s Staff Note for the G20—A Guiding Framework for Structural Reforms.

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Cover IMF Staff Country Reports
Republic of Poland: Selected Issues
Author: International Monetary Fund. European Dept.
Volume/Issue:
Volume 2017: Issue 221
Publisher:
International Monetary Fund
ISBN:
9781484310311
ISSN:
1934-7685
Pages:
64
DOI:
https://doi.org/10.5089/9781484310311.002

Cyclical indicators and Output Gap Estimates

Backward Looking—Potential Output and Output Gap Estimates

The Production Function Approach

Forward Looking—Baseline Potential Growth

Poland: Structural Reform Priorities

Potential Gains from Structural Reforms