INCLUSIVE GLOBALIZATION &POLICY

Jonathan D. Ostry

International Monetary Fund
Challenges for a Better Globalization
The Brookings Institution

Washington, DC, May 25, 2018

Views expressed in this presentation are those of the author and should not be attributed to the IMF. This presentation
draws on joint work with Andy Berg, Davide Furceri, Siddharth Kothari, Prakash Loungani and Haris Tsangarides.

POLICIES ARE A KEY DRIVER OFINEQUALITY
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Global Trends

Policies

Mortality rate (+)

Chief Executive (+)

Share of Industry (-)

Currency crises (+)

Government Size (-)

Domest Finance (+)

Capital Account (+)

Trade (+)

Technology (+)

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Structural

Determinants of the Gini measure of inequality based on a panel regression (90 countries; 5-year averages over 1970-2015
period) estimated using weighted average least squares. Each bar shows the percentage point increase in the Gini from a 1
standard deviation increase in the variable.
Global trends: ‘Technology’ is share of ICT capital in total capital stock; ‘Trade’ is openness variable from Penn World Tables.
Policies: ‘Capital Account Liberalization’ is measured using the Chinn-Ito Index. ‘Domestic Financial Reform’ is measured as 2in Ostry et al (2009). ‘Government Size’ is share of government in GDP; note (-) impact: higher government size reduces
inequality. ‘Currency crisis’ is from Laeven and Valencia; Structural: ‘share of industry’ is manufacturing value added in GDP;
‘Chief Executive’ indicates whether govt. head is a military officer; ‘mortality rate’ (commonly included in inequality
regressions). Source: Ostry, Furceri & Loungani (2016).

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Globalization Rising; Inclusion Falling
1. AEs-share of countries with rising inequality since
the 90s (%)

2. EMDEs-share of countries with rising inequality since
the 90s (%)

Increased inequality makes growth more fragile (Berg & Ostry, 2011; Ostry et al., 2014)33

Fuelling support for protectionism
Change in the probability of a party with a nativist agenda at government , %6543
210-1-2-3-4

Inequality

Social spending

Redistribution

Note: estimates based on a panel regression framework relating inequality (social spending, redistribution) with theprobability of a party with a nativist agenda at government for a sample of 164 countries over the period 19902012. The effects of inequality (social spending, redistribution) are based on their interquartile differences andpanel regression coefficients. Social spending=education and health spending as share of GDP;
Redistribution=difference between market and net Gini.

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RELATIONSHIP OF FINDINGS TO ONGOINGDEBATES
 Great concern has been voiced about inequality recently --impact on social cohesion; political capture by elites, etc.
Our finding: there is a direct economic cost to inequality -- it leads tolower and less durable growth Retreat from globalization (Brexit, Trump etc.)

Concerns about distributional effects of trade Protests against migrants
 Our finding: the effects of financial globalization should be part of thediscussion -- it contributes as much to inequality as trade; it lowers
workers’ bargaining power and income shareIn fact, financial globalization can make it difficult to mitigate
distributional effects of international trade – it leads to a race to thebottom in taxation, eroding revenues needed for social benefits

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EFFICIENCY-EQUITY TRADEOFFS:
FINANCIAL GLOBALIZATION

FINANCIAL GLOBALIZATION: TWO PUZZLESo Financial globalization works well in theory, not so well in practice
Theory predicts output (efficiency) gains from both trade and financial globalization, but gains fromlatter have proven difficult to demonstrate.
Stiglitz: “Preconditions to make financial globalization work are lacking in many countries.”

Rodrik: “The association between capital account convertibility and economic growth isweak at best…there is a strong association between financial globalization and financial
crises over time”

Krugman (May 2017): “financial globalization hasn’t been the force for good that trade hasbeen”

Martin Wolf (2004): “the gains [from financial globalization] have been questionable and thecosts of crises enormous.”Eichengreen et al. (2001): evidence of a positive association between capital accountliberalization and growth is “decidedly fragile.”o Enormous literature on impact of trade on inequality, while financial globalization gets a free pass.
Financial globalization can affect inequality in theory; shouldn’t we look at whether it does so inpractice?

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CONTRIBUTIONS
We search for output effects: giving theory a chance▪

Use both de jure and de facto measures of financial globalizationoLarge changes in de jure measures = policy changes
oSupplement with information on capital flows (de facto measure)▪

Use sectoral as well as aggregate data, since causal effects hard to establish in macro dataoUse of country-time fixed effects allows for cleaner identification of effects of financial
globalization
oBetter identification of channels through which effects of financial globalization operate▪

Trace out evolution of output in aftermath of major financial globalization episodes rather
than look for permanent growth effects (Henry 2007).

We don’t turn a blind eye to distributional effects: taking the theory seriously▪

Impact on Gini coefficient (aggregate data) and labor shares (aggregate and sectoral data)

Bottom-line: Some evidence of output effects (better identification than in previous work helps),
but also strong distributional effects.
88IDENTIFICATION OF POLICY-DRIVEN GLOBALIZATIONEPISODES•

Policy restrictions on cross-border transactions are reported in the IMF’s Annual Report on
Exchange Arrangements and Exchange Restrictions (AREAER) database.

•Information in AREAER is combined by Chinn and Ito to construct an index of capital accountrestrictions.

•Examining behavior of output (or inequality) before and after removal of major policy restrictions
requires information on when restrictions were lifted; difficult to do for large sample of countries.

•We infer timing of major policy changes by looking at large changes in the Chinn-Ito index(Kaopen)oAssume liberalization takes place when, for a given country at a given time, the annualchange in the Kaopen indicator exceeds by two standard deviations the average annualchange over all observations.

This criterion identifies 224 episodes (over 1970-2010)—the majority occurring in the early 90s(when inequality started to increase).
Examples: several EU countries in the early 1990s; India and Brazil in the mid- and late 1990s.

9EMPIRICAL STRATEGY—MACRO LEVEL
DATA

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EMPIRICAL STRATEGY—SECTORAL LEVELDATA1111

Insignificant output gains butsignificant increases in inequalityPanel 1. Output (%)

Panel 2. Gini (%)

4736524130-10123452-11-20-1012345Note: The solid lines indicate the response of output (inequality) to a capital account liberalization episode; dotted lines correspond to 90 percent
confidence bands. The x-axis denotes time. t=0 is the year of the reform.

12…the results are robust to endogeneity
checksPanel 1. Output (%)—controlling for growth expectations

Panel 2. Gini (%)—controlling for growth expectations

36251403-1-101234521-20-3-1

Panel 3. Output (%)—IV234234550.5

40-11Panel 4. Gini (%)—IV1-0.50-101234532-1.5-2-2.5

10-1015Note: The solid lines indicate the response of output (inequality) to a capital account liberalization episode; dotted lines correspond to 90 percent
confidence bands. The solid black lines denote the baseline effect.

13But output & distributional effects
depend on institutions
Panel 1. Output (%)

Panel 2. Gini (%)
554*
3210-1-2-3-4-54**

**

***

3210*

Note: Medium-term effects (that is, after five years of the reform). ***,**,* denote significance at 1 percent, 5 percent and 10 percent, respectively.

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… and on the extent of capital flows(de facto measure)
Panel 1. Output (%)
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Panel 2. Gini (%)

**

65432
10-1-2-3
Large changes in Financial Small Change in FinancialOpennessOpenness

Large changes in Financial Small Change in FinancialOpenness
Openness

Note: Medium-term effects (that is, after five years of the reform). ***,**,* denote significance at 1 percent, 5 percent and 10 percent, respectively.
Blue (red) bars denote the medium-term response (that is, five years after the reform) of output (inequality). Flows defined as the cumulative 5-yearchange in total asset and liabilities as percent of GDP after the reform.

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CAPITAL SURGES AND FINANCIAL CRISES

16The panel on the left shows the total number of surges ending in a given year and those that end in a financial crisis. The panel on
the right compares capital flow reversal and growth between surges that end in a crisis and those that do not. The analysis isbased on data for 53 emerging market economies over 1980-2014. Source: Ghosh, Ostry and Qureshi (AER P&P, 2016)16

Sectorally, short-term output gains,significant decline in labor share
Panel 1. Output (%)—external financial dependencePanel 2. Labor share (ppt)—external financial dependence

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Panel 4. Labor share (ppt)—EOS >101-10-55-4

Panel 3. Labor share (ppt)—natural layoff rate-44-32-3

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1-11-10-101234501234-2-3-4-5-6Note: Solid line denotes the differential effect of capital account liberalization episodes between a sector with a high external financial dependence/layoff rate/elasticity ofsubstitution (at the 75th percentile) and a sector with a high external financial dependence/layoff rate/elasticity of substitution (at the 25th percentile).

17Results robust to controlling for domestic
finance reforms…(and trade reforms, andtechnology)
Panel 2. Labor share (ppt)—external financial dependencePanel 1. Output (%)—external financial dependence
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31-1012345-24545-4

Panel 4. Labor share (ppt)—EOS >101-10-3

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Panel 3. Labor share (ppt)—natural layoff rate-22-20-11-1

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0-1012

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Note: Solid blue line denotes the differential effect of capital account liberalization episodes between a sector with a high external financial
dependence/layoff rate/elasticity of substitution and a sector with a high external financial dependence/layoff rate/elasticity of substitution).
Black lines denote baseline effects.

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Less redistribution, even though needed
more
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Note: redistribution = difference between market Gini and net Gini. Vertical axis measure percent change. Estimatedimpact on growth following a capital account liberalization episode. Liberalization is measured using the Chinn-Itoindex. Estimates are based on an autoregressive distributed lag model. The horizontal scale is in years after theepisode. See Furceri, Loungani and Ostry (2017) for details.

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Sharing the benefits helps
1. Redistribution reduces the impact of financial
globalization on inequality…
**

2. …as does financial inclusion**

Note: estimated impact on net Gini following a capital account liberalization episode. Liberalization is measured using the Chinn-Ito index.
Estimates are based on an autoregressive distributed lag model. The horizontal scale is in years before or after the episode. The verticalscale shows percent change. ***, **, * denote significance at 1 percent, 5 percent and 10 percent, respectively. See Furceri, Loungani andOstry (2017) for details.

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THE BROAD MESSAGE…
o High inequality and low & fragile growth are two sides of the same coin--a dangerous
gamble therefore to 'go for growth' and assume equity will take care of itself

o Fear of using fiscal redistribution is overblown. In fact, on average in the data,
redistribution is a pro-growth policy through the greater equality it engenders. The 'leak'in Arthur Okun's bucket has not been large in practiceo Evidence on financial globalization

Costs in terms of increased volatility are highOutput benefits elusive and shared unevenly

Other effects: a race to the bottom on taxes? Reduced redistribution?

o Be cognizant of growth-equity tradeoffs in macro & structural policies

How can we design policies so growth benefits go up AND equity costs go down?
Use of complementary policies: “trampoline” policies—such as job retraining and assistance withsearch—to help workers bounce back from job displacement
Redistribution: greater reliance on wealth and property taxes, more progressive income
taxation, and better targeting of social benefitso On macro policies:
Case for paying down public debt is weak—living with debt is a better policy when fiscal space
ample

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