Tag: governance

For a Better Budget Management of Infrastructure Investments

Aerial photo of buildings and roads representing infrastructure investments

Many developing countries rely on investment-to-GDP metrics as a sign of progress towards their development goals. Unfortunately, too often the focus on investment pushes aside the issues of adequately maintaining existing infrastructure. The result could be disastrous to human lives, health, and well-being. Lack of maintenance of existing infrastructure is a well-known problem, not only in developing economies but also in some developed countries. However, how much the government should plan to spend on maintenance over the lifetime of infrastructure assets is neither a simple nor straightforward question. In this policy brief, we examine the cases of two transition economies – Georgia and Estonia – and provide a more general discussion of the challenges and possible solutions to infrastructure maintenance issues. We argue that relevant research along with properly aligned incentives could help the countries overcome these problems and optimize infrastructure spending.

Introduction

The efficiency of infrastructure investment has gotten quite some attention in the past years. A recent book by G. Schwartz et al. (2020) shows that countries waste about 1/3 (and some even more) of their infrastructure spending due to inefficiencies. With poor management, the major budgetary efforts undertaken to make room for infrastructure investments go to waste. The question of how much the country should plan to spend on maintenance over the lifetime of infrastructure assets is neither simple nor straightforward. In two recent ISET-PI blog posts, Y. Babych and L. Leruth (2020a, b) stress the importance of striking the right balance between new infrastructure investments and the rehabilitation and maintenance of existing infrastructure. Without this balance, the up-keep of public infrastructure could either be too expensive for the budget to handle, or, at the other extreme, would quickly deteriorate to the point where it is no longer operational and needs to be rebuilt from the ground up (which is the case in many developing countries, including Georgia, Armenia, Ukraine, and others). This policy brief focuses on the reasons why developing (and even some developed) countries tend to invest too little in public infrastructure maintenance and what can be done to solve this problem. We first examine the cases of Georgia and Estonia, two post-Soviet transition economies with different approaches to infrastructure maintenance financing. This analysis is then followed by a more general discussion about the infrastructure maintenance challenges and potential solutions.

Maintenance vs. Investment: the Cases of Georgia and Estonia

Developing countries tend to use investment (public or private) as a share of GDP to measure their economic progress and prospects. Georgia is one of the countries that has invested a lot in public infrastructure. Public investment grew sharply between 2003-2007 to 8% of GDP and settled at 6% of GDP after 2017 (PIMA GEO 2018).  The capital stock is about 90% of GDP. In comparison, in Estonia, another post-Soviet economy, public investment was about 4% of GPD, whereas the capital stock was 57% of GDP in 2015. Yet, the quality of Georgia’s public infrastructure is much lower than in Estonia (Georgia is in 69th place globally according to Global Competitiveness Index 2017-2018, while Estonia is in 32nd place).  The reason for this is quite simple:  management, especially the maintenance of public infrastructure. Both countries recently went through a Public Investment Management Assessment (PIMA), a comprehensive framework developed by the IMF to assess infrastructure governance. The results suggest that Georgia is much weaker than Estonia in planning, budgeting, and maintenance. (A complete summary of the assessment results can be found here).

Georgia’s case is far from unique. The country belongs to the vast majority of emerging economies that have not efficiently linked their medium- and long-term infrastructure plans within a sustainable fiscal framework. Moreover, infrastructure planning deficiencies spread way beyond the emerging markets: Allen et al. (2019) estimate that 56% of all world countries do not have a proper Public Investment Program.

Why is Infrastructure Maintenance a Challenge for Many Countries?

Even though maintenance, rehabilitation, and new investments are intrinsically linked, the practical process of integrating these three infrastructure components is complex. Blazey et al. (2019), for example, identify the following reasons:

  • Political economy reasons—governments will opt for a ribbon-cutting rather than maintaining existing assets;
  • Fiscal reasons—budget funding for operations and maintenance is prone to be cut when fiscal space is limited;
  • Institutional reasons—in many countries, separate agencies still prepare investment and current expenditure budgets;
  • Capacity reasons— up-to-date information on the state of assets may not be readily available.

A number of international studies (usually sectorial) point to the high cost of neglecting maintenance. A study on the upkeep of bridges and roads in the US shows that 1$ of deferred maintenance will cost over 4$ in future repairs. The same holds for airports. In Africa, the World Bank estimates that timely road expenditure of $12 billion spent in the 80s would have saved $45 billion in reconstruction costs during the next decade. It is not only rehabilitation costs that increase with poor maintenance: user costs can increase dramatically (Escobal and Ponce, 2003); health costs in terms of injuries or deaths; and ecological costs (the water lost daily because of leaks could satisfy the needs of 200 million people according to the World Bank, 2006).

Conceptually, however, the link between maintenance, rehabilitation, and new investments is simple to understand. Figure 1 below, adopted from Thi Hoai Le et al. (2019), clarifies this point. As discussed in Babych and Leruth (2020b), when planned maintenance activities (such as planned repair, upkeep, etc.) are insufficient, then the rate at which infrastructure is deteriorating will be high, and the unplanned maintenance costs will increase as well. This response would, in turn, result in a higher total cost. If the amount of planned maintenance activities is excessive, then the unplanned costs may be low, but the total cost is higher than optimal. In order to strike the optimal balance, there need to be just enough planned maintenance activities. 

Figure 1. Optimal zone of maintenance.

Source: Thi Hoai Le et al., (2019).

Conceptually simple maybe, but the devil(s) is (are) in the details. We have already listed above some of the reasons why integration is complex. Data availability is another issue raised by numerous Public Investment Management Assessments made by the IMF. The reporting standards are simply not built in a way that would allow for the compilation of maintenance and rehabilitation data (although aggregate estimates of investment data are available). In any case, the Government Finance Statistics Manual of the IMF (2014) does not separate maintenance expenditure, which is undoubtedly an area that requires further deepening.  More fundamentally perhaps, as pointed out long ago by Schick (1966), there is an additional issue relating to governance philosophy: “planning and budgeting have run separate tracks and have invited different perspectives, the one conservative and negativistic, the other innovative and expansionist …”. Finally, with governments looking for the ‘cheap’ route through public-private partnerships (PPPs) to finance infrastructure development, fiscal risks have increased in advanced and emerging economies in the early 2000s (IMF, 2008). To our knowledge, there have been no systematic assessments of PPP-related fiscal risks since IMF’s report in 2008, but as fiscal positions have deteriorated with the Covid-19 pandemic, PPP projects are likely even riskier today.

What Can Be Done to Improve Infrastructure Maintenance?

Leaving the data, PPPs, and inter-departmental culture issues aside, several considerations that emerge from a closer look at Figure 1 can feed the policy discussions. Let us first consider the notion of planned maintenance (the orange line). In principle, as a project is developed, the cost of maintenance is projected over its life cycle. If the infrastructure is maintained accordingly, its life span may even exceed the projections. At the time the project is conceived, a schedule of maintenance expenditure is also planned and integrated into the analysis. In the figure above, one would expect that these cost assumptions are located in the ‘optimal maintenance zone’ with a limited amount to be spent on unplanned maintenance later on. This level of planned maintenance should then be integrated as a ‘given’ in all subsequent budgets. Usually, as we have already mentioned, it is not.

If we now move to ‘unplanned’ maintenance (the line in blue), we are really referring to situations when infrastructure must be brought back to shape after months (or even years) of neglect. In some cases, this can no longer be labeled as maintenance, and it becomes rehabilitation. Reduce regular maintenance a bit more and the authorities must start over.

Finally, the continuity of the curves is misleading: it is wrong to say that things are necessarily smooth even in the optimal zone.

Let us look more closely at the leading causes and the ways to overcome the problems that arise when optimizing maintenance expenditure.

Setting benchmarks: One explanation for the shortage of maintenance planning outlined above is the lack of information on the practical implementation of such planning.  There are too few studies on maintenance expenditure for policymakers to set benchmarks and develop reliable estimates. The existing studies in this area tend to focus on OECD countries (where data availability is less of a constrain) and on the transportation sector (roads, rail, etc.) perhaps because the private sector is more often involved (see, for example, the American Society of Civil Engineers from 2017, that concluded that 9 percent of all bridges are structurally deficient). Some studies have looked at buildings (e.g., Batalovic et al., 2017 or the Ashrae database, 2021) and unsurprisingly concluded that the age of the construction and its height are significant variables to explain maintenance outlays. However, we are not aware of studies that would, for example, distinguish between different types of maintenance in order to limit overall costs. We are neither aware of studies investigating which organizational arrangements are the most efficient (as discussed by Allen et al., 2019). The bottom line is that there is not much to use as a benchmark, and an effort must be made to build reliable estimates.

Policy dialogue on maintenance is needed:  The abovementioned considerations of the consequences of delayed, unplanned, and sometimes unexpected maintenance bring us to our next point. Things break down when they are not maintained (and sometimes break down when they are maintained too), and such long-term aspects must be more present in the policy dialogue with developing countries. Clearly, delaying maintenance increases fiscal costs in the short- and longer-term (Blazey et al., 2019).

The smoothness of the curves in Figure 1 can be misleading because insufficient maintenance may suddenly trigger a major problem (a bridge or a dam can collapse, as it happened in Italy and in India recently,)  and this will entail high costs, even disasters involving in human lives. The major collapses of nuclear plants (as in Chornobyl, Ukraine, and more recently in Fukushima, Japan) are other examples of the same problem. In addition, studies estimate that poor maintenance of transmission lines could be one of the reasons for electricity blackouts (Yu and Pollitt, 2009). In fact, the lack of maintenance increases the speed at which the value of the existing capital of infrastructure is eroding. While politicians may well hope that this will not happen during their tenure, the probability of a failure increases as maintenance decreases.

On top of the above, inefficiency in maintenance expenditures can be aggravated by wrongly set incentives, both for domestic actors and foreign donors. Indeed, the latter play an important role in infrastructure investment in many developing countries. In Georgia, for example, 40% of infrastructural projects are funded by foreign donors. Setting the right incentives for both parties, as well as their interplay, are thus of immense importance.

Aligning the incentives: Incentives are against maintenance. As pointed out by Babych and Leruth (2020a), capital investment and rehabilitation look good on paper. Maintenance, on the other hand, is considered a current expenditure item in the Government Finance Statistics (GFS) (IMF, 2014). Spending more on maintenance will therefore not look good since 1) more maintenance will reduce government savings in the short term; 2) spending less on maintenance will increase the need for virtuous-looking investment expenditure in the medium and long term. Yet, in spite of the lack of clear benchmarks, donors can play an essential role by stressing the need to systematically integrate maintenance in the budget and in the Medium-Term Expenditure Framework (MTEF). To some extent, it is already the case. In Georgia, projects that are funded by donors tend to follow better appraisal procedures. However, ex-post audits are irregular – e.g., no individual projects audits were completed by State Audit Office during 2015-2017 (PIMA GEO, 2018). If donors could include these audits in their dialogue, it would clearly be helpful. Training subnational governments in proper maintenance management would be even more critical as capacities tend to be weaker than in the center.

Overcoming a potential moral hazard problem of donor involvement: Excessive donor involvement in new investments could also be counterproductive. Donors should carefully examine the need to build new infrastructure and first consider the possibility of performing some rehabilitation while holding the authorities accountable for the maintenance of existing ones. If the authorities are expecting a donor to eventually replace a piece of infrastructure that does not function, the incentives to maintain it are greatly reduced.

Conclusion

  • Developing economies, but also emerging ones like Georgia, as well as Armenia, Ukraine and others, would benefit from proper incentives and support from the international donors to integrate maintenance into the infrastructure planning framework;
  • This is especially important for local governments, who lack the financial and human capital resources to maintain local infrastructure properly, making regions outside of the capital city less attractive places to invest or live in;
  • Given the absence of transparent and comparable sources of information about the composition of maintenance expenditures – for example, the Government Finance Statistics (IMF), which does not distinguish between maintenance and rehabilitation expenditures, – donors could insist that governments compile these expenditures and report on them, at least for the major projects;
  • The culture of maintaining rather than rehabilitating or replacing is directly linked to the sustainable development goals and the circular economy concept. In light of their commitment to Agenda 2030, the international community and the national governments in countries like Georgia should consider prioritizing and implementing the set of reforms suggested in their respective PIMAs.

References

  • Allen, R., M. Betley, C. Renteria and A. Singh, “Integrating Infrastructure Planning and Budgeting,” in Schwartz et al. (2020), pp. 225-244 (2019).
  • American Society of Civil Engineers, Infrastructure Report Card, Reston, Va, (2017).
  • ASHRAE, Purpose of The Service Life and Maintenance Cost Database, available at., (2021).
  • Babych, Y., and L. Leruth, “Tbilisi: a Growing City with Growing Needs,” ISET-PI Blog available at, (2020a).
  • Babych, Y., and L. Leruth, “To Prevent, to Repair, or to Start Over: Should Georgia Put’ Maintenance’ Ahead of ‘Investment’ in Its Development Dictionary?,” ISET-PI Blog available at, (2020b).
  • Batalovic, M., K. SokolijaM. Hadzialic, and N. Batalovic, “Maintenance and Operation Costs Model for University Buildings,” Tehnicki Vjesnik, 23(2), pp. 589-598, (2017).
  • Blazey, A., F. Gonguet, and P. Stokoe, “Maintaining and Managing Public Infrastructure Assets,” in Schwartz et al. (2020), pp. 265-281 (2019).
  • Escobal, J. and C. Ponce, “The Benefits of Rural Roads: Enhancing Income Opportunities for the Rural Poor,” Working Paper 40, Grupo de Analysis Para el Desarrollo (GRADE), Lima, Peru, (2003).
  • IMF, “Fiscal Risks—Sources, Disclosure, and Management,” Fiscal Affairs Department, Washington DC,(2008).
  • IMF, GFS, Government Finance Statistics Manual, IMF, Washington DC, (2014).
  • PIMA EST, Republic of Estonia: Technical Assistance Report-Public Investment Management Assessment, IMF, Washington DC, (2019).
  • PIMA GEO, Republic of Georgia: Technical Assistance Report-Public Investment Management Assessment, IMF, Washington DC, (2018).
  • Rozenberg, J., and M. Fay, eds, “Beyond The Gap: How Countries Can Afford The Infrastructure They Need While Protecting The Planet,” Sustainable Infrastructure Series, The World Bank, Washington DC, (2019)
  • Schick, A., “The Road to PPB: The Stages of Budget Reform,” Public Administration Review, 26(4), pp. 243-258, (1966).
  • Schwartz, G., M. Fouad, T. Hansen, and G. Verdier, Well Spent : How Strong Infrastructure Governance Can End Waste in Public Investment, IMF, Washington DC, (2020).
  • Thi Hoai Le, A., N. Domingo, E. Rasheed, and K. Park, “Building Maintenance Cost Planning and Estimating: A Literature Review,” 34th Annual ARCOM Conference, Belfast, UK (2019).
  • World Bank, The Challenge of Reducing Non-Revenue Water in Developing Countries – How The Private Sector Can Help,” Water Supply and Sanitation Board Discussion Paper Series No 8, Washington DC, (2006).
  • Yu, W., and M. Pollitt, “Does Liberalization Cause More Electricity Blackouts?,” EPRG Working Paper 0827, Energy Policy Research Group, University of Cambridge, United Kingdom, (2009).

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Governance in the Times of Corona: Preliminary Policy Lessons from Scandinavia

Areal image of empty restaurant tables with only one table occupied by two people representing governance and Covid-19

This policy brief summarizes the key points discussed in the webinar entitled “How did we end up here? Governance lessons from the Covid-19 pandemic” which was organized by CEPR, LSE IGA, SPP and SITE on June 18, 2020. The main insights concern the relationship between science and expert authorities on the one hand and elected and democratically accountable political institutions on the other hand. The Covid-19 pandemic has illustrated the need to strike a balance between being prepared and having a plan, and at the same time being able to take in new information and learn as new challenges unfold. This requires drawing on expertise from multiple fields as well as keeping an open mind to reevaluate chosen strategies when necessary.

Introduction

Economists have long reflected upon the potential benefits from separating the short-run decision making and implementation of policies from the overarching long-run goals. Central bank independence is probably the most prominent example, but the general idea of elected politicians transferring decisions to technocrats is widespread and, in different forms and to a different extent, part of the governance structure of all countries.

In the context of the corona crisis, governance issues have also been discussed, and the pros and cons of different systems are under debate: China, with its authoritarian system, has found it easier to control its population’s movements than many hard-hit European countries. In the US, the duality between the federal government and strong states has caused a lot of tensions. In Brazil, strong mayors and state governments have partly succeeded in counterbalancing the federal policy by imposing lockdown measures at the local level. The Covid-19 crisis is special: as a global health crisis, it certainly requires more coordination and expert knowledge than most other types of crises. Hence, in all countries, epidemiologists have received particular attention, but even internationally the Swedish state epidemiologist Anders Tegnell stands out with regards to this.

In the webinar entitled “How did we end up here? Governance lessons from the Covid-19 pandemic” which was organized by CEPR, LSE IGA, SPP and SITE on June 18, economists Karolina Ekholm and Bengt Holmström discussed governance issues within the Covid-19 crisis with a special focus on the Nordic countries. Ekholm is a professor at Stockholm University, former deputy governor of the Swedish Central Bank and served as a state secretary at the Swedish Ministry of Finance until 2019. Holmström, professor at the MIT and Nobel prize laureate, has been part of the Finnish commission on corona. Finland’s approach to the Covid-19 crisis has been widely approved of: the country imposed an early lock-down which seems to have successfully contained the spread of the virus. Sweden, by contrast, has made headlines all over the world due to its relatively loose policy approach, and more recently, due to the high death toll the country has recorded so far. How have governance issues contributed to these very different outcomes and what can we learn from this for the larger picture?

A Transdisciplinary Approach for a Multidimensional Crisis

Holmström contributed with an instructive account of his experience advising the Finnish government. The initial forecast turned out to be overly pessimistic, according to him, partly because epidemiologists underestimated a driving force behind people´s behavior: fear. If people had not been so afraid of the virus, compliance with the restrictions may have been much lower. This is not to blame epidemiologists: economists have struggled for decades to understand people’s behavior better and to integrate it into their models, which is everything but an easy exercise. But what policymakers can certainly learn from the first wave of Covid-19 is that the societal appreciation of the urgency of the pandemic can make a crucial difference and will determine whether policies fail or succeed. This may be of vital importance if a second wave of the virus is to follow. Moreover, scientists need to remember to update their models. What has worked for the swine flu may not work for Covid-19. As noted by one of the webinar participants: what is needed now is a forward-looking approach to science.

The Pitfalls of Technocratic Rule

Economists tend to focus on the benefits of technocratic rule in opposition to government corruption. This may be true in certain contexts, but technocratic rule is not a panacea. A priori, health experts are better informed than politicians during a health crisis. The Swedish, as well as the Finnish and the UK governments, were following their health agencies’ advice at the beginning of the Covid-19 outbreak. Yet, the governments in Helsinki and London departed from this policy quite early. According to Ekholm, the Finnish government soon overruled expert advice because they expected that voters would punish politicians who did not prioritize saving lives. A reason which is often invoked to explain why the Swedish government has not followed the Finnish example is that the Swedish constitution does not allow ministerial rule. Yet, this is unlikely to be decisive in the comparison to Finland, which also has a tradition of autonomous government agencies. Ekholm thinks that the evaluation of the health agencies in Scandinavia made at the outset of the crisis did not differ much from each other – with the exception of the Swedish health agency being more pessimistic with regards to the possibility of suppressing the spread of the virus by going into lock-down. The Swedish health agency also still enjoys high approval and confidence both from politicians and the general public. However, why it took so long for the health agency to push for more testing capacity remains a mystery to the webinar speakers.

Holmström mentioned another reason for exercising caution: just as economists, epidemiologists tend to fall for their standard models and may not question them enough. Scientists are trained to reason along their disciplines’ main paradigms and models and this can limit their intellectual flexibility and ability to analyze new phenomena. In this sense, having a lot of experience can sometimes lead to being overly confident in solutions which have been “proven before” as for instance, the idea of “herd immunity”.

The Use of Scientific Evidence

Science is supposed to be objective and transparent, but from an epistemological point of view, things are ambiguous. Holmström named the example of face masks, which have become the symbol of the Covid-19 pandemic elsewhere, but which are still rare on the streets of Stockholm and Helsinki. The Swedish and Finnish health authorities have hesitated to endorse the use of face masks, mainly because there is little evidence of their efficiency. Yet, other countries have endorsed them, following the very argument that there is little evidence of their harmfulness. Which question you are asking – whether masks help fight the spread of the virus or whether they may cause any collateral damage – determines which conclusion you come to. While a priori this may appear mostly as a philosophical question, the stakes are high in a health crisis and the dimensions of the current pandemic may very well justify adherence to the principle of precaution, according to Holmström.

Efficiency vs. Resilience

Economists’ workhorse model by contrast tends to be that of optimization: minimizing costs and maximizing efficiency or welfare. Particularly in the context of healthcare, this approach has been subject to criticism, though. Ekholm confirmed that the health sector in Sweden has been slimmed down, partly following extensive privatizations. In Sweden, another issue has been the lack of coordination between the national, the regional (largely responsible of healthcare) and the local level (responsible of nursing homes). Ekholm believes that there are many lessons to be learned from the numerous failures in vertical and horizontal cooperation between different Swedish governance institutions. Conferring more responsibilities to the European level in the domain of health could be efficient but both speakers agree that, despite generally high approval of the European Union, the Swedish and the Finnish public are unlikely to agree to such measures.

Conclusions

All conclusions we draw at this point must necessarily be preliminary. First, the Covid-19 crisis has challenged local, regional, national and supranational governance more than any previous crisis. The reasons for this are manifold: Covid-19 has grown from a health emergency to becoming an economic, social, political and potentially financial crisis. Second, the merits and pitfalls of technocratic rule must be evaluated. No single expert authority can – or should – claim the sole power of interpretation when facing a multidimensional crisis such as the current one. Considering this, it seems advisable that scientists with different expertise be included in a transparent decision-making process that then is clearly and openly communicated to the public. Crucially, all decisions and rules must be updated constantly, as new evidence arises; there is no room for dogmatism. Finally, there is no doubt that society has to become more resilient in the future. Whether this is to be achieved via supranational integration, investments in research and healthcare, more efficient crisis management mechanisms, or a combination of all these, is to be evaluated.

List of Speakers

Karolina Ekholm, Professor, Stockholm University and Fellow, CEPR

Bengt Holmström, Paul A. Samuelson Professor of Economics, MIT

Chair and Moderator:

Erik Berglöf, Director, Institute of Global Affairs, LSE School of Public Policy and Fellow, CEPR

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Political Responsibility for Economic Crises

20180422 Political Responsibility for Economic Crises IMAGE 02

This brief summarizes the results of research on the political costs of large-scale economic crises. In a large historic sample of countries, we study the impact of different types of crises, such as sovereign and domestic defaults, banking crises and economic recessions, on political turnover of top politicians: heads of the state and central bank governors. According to the findings, only default on domestic debt increases the probability of politicians’ turnover but not the default on external debt. As argued, this is due to the fact that the latter is not directly felt by the voters. In addition, we find that although currency crises increase chances of head of central bank turnover, it does not affect tenures of heads of state. Presumably, this is the case since currency crises are in the eyes of the public the responsibility of CB governors. These findings are relevant for both developed and transition economies, but are especially important for the latter as political turmoil and economic recessions are more prevalent in developing nations.

Overview and Key Findings

Large-scale economic crises are associated   not only with the economic downturns, but also with political turnover. When the national economy is in a critical state, a default declaration often turns the economy back to growth as it is typically viewed as an act of  acknowledging a problem and showing readiness for changes. However, politicians responsible for the economy and leaders of the states are often reluctant to declare default and try to postpone it, which worsens the situation. One of the reasons behind such unwillingness to act is a fear of a political turnover following the open acknowledgement of a problem.

This brief summarizes the findings Lvovskiy and Shakhnov (2018). We investigate the statistical evidence of political costs related to different types of economic crises.

We find that the effects of a crisis depend on the crisis type and on whether it was in the area of responsibility of a given politician. For example, external sovereign defaults have no effect on political turnover, which we interpret as external sovereign default having a small impact on the general public. On the contrary, domestic sovereign defaults have a large impact on the country population and often lead to the replacement of the top executive. In turn, banking crises are followed by the downfall of the government at the level of chief executive as well as the governor of the central bank.

While there is large literature on career concerns of politicians and political turnover, the majority of papers either focus on the regular changes through elections in democratic regimes (Treisman, 2015) or study a particular non-democratic country, like China (Li and Zhou, 2005). However, throughout history, crises have often happened in transition, non-democratic or not fully democratic countries. Furthermore, even in democratic countries many changes of government have been irregular. Since a delay in default declaration usually harms economies it is important to understand the mechanisms behind it in different institutional settings. Our paper contributes to this understanding by analyzing the impact of economic crises on political survival in a wide set of countries and regimes. Better understanding of the political costs that the top executives face while making such decisions is crucial for the prediction of these decisions as well as for international default negotiations and consultations.

Below we describe our finding in some more detail.

Statistical Analysis and Results

Our analysis consists of two main parts. We start with the political turnover for heads of state, who are in charge of the performance of the whole economy, which we measure by the GDP growth. Then, we look at central bank (CB) governors, who are in charge of the monetary policy, price stability, stability of the financial sector and banking supervision.

Table 1. Head of state changes

Table 1 presents the estimated linear probability regression models for the head of state turnover. As expected, elections have a strong impact on the probability of the turnover of the head of state. Further, as Column 1 in Table 1 shows default on external debt has no significant impact on the head of state tenure while default on domestic debt increases the yearly chances of being displaced by 34 %. This supports the idea that voters care more about their own savings than about the general situation with the state’s budget. When we look at the effect of past crises (the predictor variable in this case is whether a crisis took place last year), Column 2 coefficients for both external and domestic defaults appear to no longer be statistically significant. Instead, banking crises become significant. This situation could be due to the fact that one of the common consequences of domestic defaults is an ongoing distortion  of savings  which often leads  to deposit runoffs, so the effect of the previous year’s domestic default now acts through a banking crisis.

Table 2. Central bank governor changes

Table 2 presents similar results but this time the left hand side variable is CB governor turnover. Similarly to the case with the head of state turnover, only default on domestic debt has a significant effect on the CB’s governor tenure and not the one on external debt. The main differences with Table 1 are that elections do not statistically predict turnover of CB heads while currency crises do. The former result is expected since in most countries there are no direct elections of central bank governors and central banks often have some degree of independence from the government. The latter result, that currency crises have a significant impact on CB governors’ tenures, implies that since currency control is one of the roles of a CB, its head is held accountable for currency crises and not the head of a state.

Conclusion

We examine the political cost of different types of economic crises, and find non-uniform effects of different types of crises on the political survival of various key officials. Domestic defaults, and recent banking crises are shown to be costly both for heads of states and central bank governors, while currency crises only have an impact on the political survival of the latter.

Interestingly and importantly, we find no evidence of the impact of (external) sovereign default on political turnover of the head of state or central bank governors. In other words, contrary to Yeyati and Panizza’s (2011) suggestion, it seems that there is no immediate political cost at the top associated with (external) sovereign default. One possible explanation is that the public does not  punish a politician for defaults because by defaulting, the politician makes the optimal decision.  In a modern world, many developing nations experience rapid growth of their sovereign debt. The presented evidence brings partial optimism that even if economic mistakes have already been made, top politicians would understand that acknowledging a problem and making steps toward its solution may not always be as costly for them as has previously been thought.

References

  • Li, Hongbin; Li-An Zhou, 2005. “Political turnover and economic performance: the incentive role of personnel control in China,” Journal of Public Economics, 89 (9), 1743 – 1762.
  • Lvovskiy, Lev; Shakhnov, Kirill, “Political Responsibility for Different Crises”, BEROC working paper #50, 2018
  • Treisman, Daniel “Income, Democracy, and Leader Turnover”, American Journal of Political Science,  2015, 59 (4), 927–942.
  • Yeyati, Eduardo Levy and Ugo Panizza, “The elusive costs of sovereign defaults,” Journal of Development Economics, January 2011, 94 (1), 95–105.