IMF International Monetary Fund : Research Bulletin, December 2016

IMF

B U L L E T I N

Volume 17, Number 4 December 2016

www.imf.org/researchbulletin

In This Issue

1 Tax Capacity and Growth: Is There a Tipping Point?

4 U.S. Shale Revolution and Its Spillover Effects on the Global Economy

7 Q&A: Seven Questions about the Relationship between Country Finance and Governance

1. Conference Call for Papers

2. IMF Working Papers

1. Recommended Readings from IMF Publications

2. IMF Economic Review

3. Staff Discussion Notes

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Tax Capacity and Growth: Is There a Tipping Point?

Vitor Gaspar, Laura Jaramillo, and Philippe Wingender

Is there a minimum tax-to-GDP ratio associated with a significant acceleration in the process of growth and development? We give an empirical answer to this question by investigating the existence of a tipping point in tax-to-GDP levels. We

use two separate databases: a novel contemporary database covering 139 countries from 1965 to 2011 and a historical database for 30 advanced economies from 1800 to 1980. We find that the answer to the question is yes. Estimated tipping points are similar at about 12¾ percent of GDP. For the contemporary dataset we find that a country just above the threshold will have GDP per capita 7.5 percent larger, after 10 years. The effect is tightly estimated and economically large.

Building tax capacity is closely linked to the process of economic development and growth. There is a long intellectual history behind this concept of the role of taxes and the state. Joseph Schumpeter, in his famous paper "The Crisis of the Tax State" (Schumpeter, 1918), links the state and tax so closely that he stresses

that "tax" in "tax state" can be regarded as almost redundant. He emphasizes that taxes are not only associated with the historical origin of the state, they are also active in shaping it. In his view, the organic development of taxation was associ- ated with the organic development of other dimensions of the state. For Schum- peter, the analysis of the consequences of taxation requires a long-run perspective that allows for structural and self-reinforcing evolutionary dynamics to play out in full. Those are not only economic, but also social and political.

In contemporary research, Besley and Persson (2011, 2013, 2014) emphasize the broader concept of state capacity to stand for a range of capabilities that are needed for the state to function effectively. We follow Besley and Persson and argue that state capacity is shaped by the interaction between tax capac- ity, legal capacity, and public administration capacity. Tax capacity provides a stable and elastic source of revenue for the government to finance govern-

ment activities. Also, a government with a larger stake in the economy through a developed tax system has stronger motives to play a productive role in the

Read more on page 2

IMF Research Bulletin

economy. Public administration capacity refers to the gov- ernment's effective and efficient use of public money. This directly impacts the ability of governments to implement policy and deliver public services, which in turn influences citizens' trust in government. Legal capacity refers to the government's ability to secure private property rights. This includes legal infrastructure such as building the court system and registering property.

The strength of tax capacity depends crucially on social norms of compliance. Kiser and Levi (2015) emphasize that the more a government is effective and trustworthy, the more legitimacy it is likely to attain, and the more it will

be able to elicit compliance without excessive monitoring or punitive action. The government can thereby achieve a

high degree of quasi-voluntary compliance with the taxation system as proposed by Levi (1988).

A shift in social norms can push a country out of a low tax compliance equilibrium into a high tax compliance equi- librium as discussed, for example, by Traxler (2010). Such enhanced tax capacity could then lead to a virtuous cycle in behavior and institutions that will have a positive impact on growth. The virtuous cycle could be triggered through sev-

2 eral channels. Greater tax compliance enlarges the tax base,

which can reduce the marginal cost of public funds. In turn, this enables greater spending by the government on state capacity building. An increase in cooperative behavior and trust can also make it easier to realize agglomeration effects in production as more individuals and firms participate in formal markets.

This raises the question: Is there a minimum tax-to-GDP ratio associated with a significant acceleration in the process of growth and development?

We argue that as countries approach and eventually exceed some revenue threshold, growth outcomes for these countries would then jump discontinuously. Card, Mas, and Rothstein (2008) demonstrate that tipping points can be identified and estimated through the use of regression dis- continuity design (RDD) methods. We apply the approach to the relation between tax-to-GDP levels and subsequent GDP growth. In particular, we look for levels of tax-to-GDP around which we observe sharp changes in subsequent GDP growth rates. We interpret our findings as suggestive of the possible presence of multiple equilibria in tax compliance and capacity: small variations in tax levels around a tipping point can lead to economies jumping from one equilibrium to another. This in turn can lead to large differences in growth as some countries reach the high compliance/high

growth equilibrium while others remain in the low compli- ance/low growth equilibrium.

Our empirical methodology draws on Card, Mas, and Rothstein (2008) by following a two-step approach to estimate the location of a tipping point and its impact on subsequent growth. First, we regress cumulative real per capita GDP growth on tax-to-GDP levels. The location of the tipping point is determined by partitioning tax-to-GDP lev- els in two non-overlapping ranges and finding the value for which such a partition maximizes the fit of the regression.

Second, we take the threshold value as if it were known and estimate the impact of crossing the tipping point on growth. We estimate the effect of the threshold by taking the differ- ence in average cumulative growth rates for countries that are just to the left and just to the right of the threshold. This enables us to measure the effect on real GDP growth of a representative country that "crosses" the threshold. We also document that the effect on growth is robust to the inclusion of a number of additional covariates and fixed effects.

We rely on two independent databases for our analysis: a contemporary database and a historical database. The contem- porary database assembles a large unbalanced panel consisting of tax-to-GDP and real GDP per capita for 139 countries from 1965 to 2011. The historical database is also an unbalanced panel consisting of tax-to-GDP ratios and real GDP per capita for 30 advanced countries between 1800 and 1980.

Using the contemporary dataset we find, from the first step in our procedure, that partitioning the range of values of tax-to-GDP levels in our sample around 12.88 of GDP provides the best fit across all horizons considered (Figure 1). The tipping point using cumulative GDP growth over

3, 5, 7 and 10 years are very similar, statistically significant and tightly estimated. The second step of our approach is illustrated in Figure 2. The figure shows clearly the effect of the threshold at the point of discontinuity around 12.88 per- cent of GDP: countries that are immediately to the left of the tipping point on average grow by around 20 to 25 percent

in real terms over 10 years, or around 2 percent annually. Countries immediately to the right of the threshold grow by more than 30 percent over 10 years, or 2.8 percent annually. This implies that a country just above the threshold will have real GDP per capita around 7.5 percent larger, after 10 years, than an otherwise similar country just below it. This effect is tightly estimated and economically large.

The scatter plot shows average GDP growth in 0.5-per- centage-point bins. The solid line is a local linear regression fit separately on either side of 12.88 using an Epanechnikov

December 2016

Figure 1. Searching for a Tax Tipping Point at Different Horizons

0.012

0.01

R-squared

0.008

0.006

0.004

0.002

Figure 2. Impact of the Tax Threshold on 10-Year Cumulative Growth

0.45

0.4

0.35

.3

0.25

0.2

0

5 10 15 20 25 30

Tax-to-GDP

3-year GDP growth 5-year GDP growth 7-year GDP 10-year GDP growth

0.15

5 10 15 20 25 30

Tax-to-GDP

Binned data Local linear regression Fourth-order polynomial

kernel and a bandwidth of 1.5. The dashed line is a global fourth order polynomial estimated separately on either side of the tipping point.

We also estimate the tipping point using the historical database. The historical dataset allows the estimation of the tipping point for advanced economies, as most of them were already above the estimated threshold in 1965, when the contemporary database starts. Remarkably, from the first step, we find a statistically significant threshold in government

tax revenue at 12.65 percent of GDP, very close to our result using contemporary data. The tipping point is also tightly estimated. The threshold impact on subsequent growth is also economically relevant, although not statistically significant, once time and country fixed effects are introduced.

Hence our answer to the initial question: "Is there a tipping point in the relation between tax capacity and growth?" is yes! Of particular note is that the tipping point occurs for both developing economies, in a contemporary dataset, as well as for advanced economies, in a historical dataset. These results raise the possibility that tax thresholds and tipping points are an inherent feature of the development of modern economies and the state and institutions that facilitate their emergence.

References

Besley, T. and T. Persson, 2011, Pillars of Prosperity: The Political Economics of Development Clusters. Princeton: Princeton University Press.

---, 2013, "Taxation and Development," Handbook of Public Economics, Volume 5. Edited by A. J. Auerbach, R. Chetty,

M. Feldstein, and E. Saez. North Holland: Elsevier.

---, 2014a, "Why Do Developing Countries Tax So Little?," 3

Journal of Economic Perspectives, Vol. 28, No. 4, Fall 2014,

pages 99-120.

Card, D., A. Mas, and J. Rothstein, 2008, "Tipping and the Dynamics of Segregation," The Quarterly Journal of Economics, 123(1): 177-218.

Kiser, E., and M. Levi, 2015, "Interpreting the Comparative History of Fiscal Regimes," in Fiscal Regimes and the Political Economy of Premodern States, edited by Andrew Monson and Walter Sheidel. Cambridge: Cambridge University Press.

Levi, M., 1988, Of Rule and Revenue. Berkeley and Los Angeles, CA: University of California Press

Schumpeter, J.S., 1918, Die Krisis des Steuerstaats, Zeitfragen aus dem Gebiete der Soziologie, 4, Graz and Leipzig: Leuschner & Lubensky, pp. 3-74 also available as "chapter 1, The Crisis of the Tax State," in Richard Swedberg (ed.), 1991, The Economics and Sociology of Capitalism / Joseph A

Schumpeter. Princeton: Princeton University Press.

Traxler, C., 2010, "Social Norms and Conditional Cooperative Taxpayers," European Journal of Political Economy, 26 (2010) 89-103.

IMF Research Bulletin

Research Summaries

U.S. Shale Revolution and Its Spillover Effects on the Global Economy

Ravi Balakrishnan, Keiko Honjo, Akito Matsumoto, and Andrea Pescatori

The U.S. oil industry experienced one of its most dramatic shifts in 2010-14, when a combination of high prices and tech- nological change (notably horizontal drilling) led to a doubling of U.S. crude oil production. Both the number and productiv- ity of rigs increased, with important implications for the oil market and the global economy more broadly. Following the 2014-15 oil price collapse, there has been active debate about the ability of the U.S. oil industry to absorb the shock and reequilibrate the global oil market. An important piece of this puzzle is understanding whether the shale industry can sustain

4 its past exponential productivity increases. This note proposes three scenarios for shale production and draws out the spillover

implications for some major oil importers and exporters.

T

he advent of shale oil production has added about

5 million barrels a day (mbd) to the crude oil market, contributing to a global supply glut. U.S. petroleum

production accounted for 60 percent of world petroleum sup- ply growth from 2011 to 2015. The supply glut is a key factor behind the dramatic decline in oil prices starting in mid-2014, from $108 a barrel to less than $30 in early 2016. Changes in

the strategic behavior of the Organization of the Petroleum Exporting Countries (OPEC) in November 2014 and the projected increase in Iranian exports were also important factors behind the glut. In recent meetings in September and November 2016, OPEC changed its strategy again to cut

production in order to stabilize prices. However, the targeted production, 32.5 mbd, is only 1.2 mbd lower than its highest level of production. In addition, OPEC members have tended to produce more than their quota in the past, which calls

the credibility of the production cut into question. On the demand side, downward revisions of global growth, especially in emerging markets, added downward price pressures-as did the turmoil in financial markets and the strong dollar.

Looking ahead, the secular drop in petroleum consumption in advanced economies and scaled-down potential growth for emerging markets point to modest growth for oil demand.

In this context, it is important to assess the resilience of shale oil production to low oil prices. U.S. shale oil pro- duction has been fairly resilient overall, in spite of low oil prices, thanks to continued phenomenal efficiency gains,

Figure 1. United States: Oil Price and Weekly Rig Count

2.5

(year over year change)

2

1.5

WTI

# of Oil Rig in Operation US shale production

1

0.5

0

-0.5

-1

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Source: Baker Hughes, Energy Information Administration, and Datastream