Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Is financial globalization welfare decreasing?

Marcel Schroder

Panel: Prema-chandra Athukorala, Paul Burke, Ippei Fujiwara

Crawford School PhD Conference

November 27, 2012

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Some Background

• For any open economy, net foreign asset position (NFA) is akey variable: It limits present value of future current accountdeficits.

• Net external asset position represents a country’s solvencyconstraint.

• Traditional view: ∆NFAt = CAt.

• But: Foreign assets and liabilities are measured at marketvalue.

• Market value variations occur due to changes in asset prices,asset returns, or exchange rate changes → ”Valuationeffects”.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

• Valuation effects are an important driver of NFA (Lane andMilesi-Ferreti, 2007; Gourinchas, 2007; Obstfeld, 2004):

∆NFAt = CAt + V ALt. (1)

• However, capital transfers (CAP) and unrecorded capitalflows/trade flows are also important:

∆NFAt = CAt + V ALt + CAPt + EOMt. (2)

• Can compute V ALt indirectly using Eq. 2.

• Magnitude of VAL is proportional to gross asset positions.

• Proliferation in asset trade (financial globalization) has led toa significant increase in the size of valuation adjustments.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Increasing volatility in valuation effects over time

Figure: Valuation-Effect Volatility and Financial Integration, 1980-2007

12

34

56

(A+L)/

GDP

.02.04

.06.08

.1Va

luatio

n−Eff

ect V

olatilit

y

1980 1990 2000 2010Year

VAL Financial_Integration

High Income

Note: Volatility measured as the rolling standard deviation over 10-year periods.Source: Compiled from Lane and Milesi-Ferretti (2007) and IMF BOP statistics.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Figure: Valuation-Effect Volatility and Financial Integration, 1980-2007

11.5

22.5

3(A

+L)/G

DP

.03.04

.05.06

.07Va

luatio

n−Eff

ect V

olatilit

y

1980 1990 2000 2010Year

VAL Financial_Integration

Emerging

Note: Volatility measured as the rolling standard deviation over 10-year periods.Source: Compiled from Lane and Milesi-Ferretti (2007) and IMF BOP statistics.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Figure: Valuation-Effect Volatility and Financial Integration, 1980-2007

.81

1.21.4

1.61.8

(A+L

)/GDP

.02.04

.06.08

.1Va

luatio

n−Eff

ect V

olatilit

y

1980 1990 2000 2010Year

VAL Financial_Integration

Developing

Note: Volatility measured as the rolling standard deviation over 10-year periods.Source: Compiled from Lane and Milesi-Ferretti (2007) and IMF BOP statistics.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Research Question

• How does the rising importance of VEs affect economicperformance?

• Empirically, this remains an open question.

• The purpose of the study is to fill this gap.

• Here, focus on welfare through consumption volatility.

• Currently, other channels not well understood theoretically.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Theoretical considerations

• Theoretical link between VEs and consumption is notclear-cut.

• Interpretation 1: Higher valuation-effect volatility causesgreater volatility in wealth ⇒ consumption should becomemore volatile as well.

• For risk averse agents this means a welfare loss stemmingfrom deviations from a smooth consumption path.

• Interpretation 2: VEs reflect flow payments of internationalrisk sharing → wealth not more volatile → no welfare costs.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

What to expect?

• The relationship between consumption and valuation-effectvariability is conditional on:

• The currency decomposition of a country’s balance sheet.• And/or its ability to share risk internationally.

• Since Eichengreen & Hausmann (1999) it is well known thatmost developing countries face problem of ”original sin”.

• Kose et al (2009): Developing economies still unable to sharerisk internationally despite financial globalization.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Empirical model

LV OLCit = β0+β1 LV OLV ALit+β2 LV OLGit+β3 LV OLINFLit+u†it.

• LV OLC: Volatility of real private consumption growth per capita.

• LV OLV AL: Volatility of valuation effects.

• LV OLG: Volatility of real GDP per capita growth.

• LV OLINFL: Volatility of inflation rate.

• Volatility defined as log of rolling standard deviation using 10yr windows.

• β1 insignificant: cannot reject that VEs reflect risk sharing.

• β1 positive significant: VE-volatility welfare decreasing, rejectrisk sharing interpretation.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Data

• Unbalanced panel, 82 countries. Period: 1980-2007.

• Data Sources:• LV OLC & LV OLG: PWT 7.1.• LV OLINFL: WDI.• LV OLV AL: Compiled from: EWN II (Lane and

Milesi-Ferretti, 2007) and IMF BOP statistics.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Estimation and resultsMethod

• Step 1: Investigate unit root properties of the variables.

• Step 2: Estimate long-run relationship between variables.

• Step 3: Test for cointegration.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Estimation: Dynamic OLS (Mark and Sul, 2003)

LV OLCit = αi + θt + λi t+ β′ xit + u†it,

u†it =

m∑−m

δ′i∆xi,t+m + uit.

• xit = [LV OLV ALit, LV OLGit, LV OLINFLit]′

• Assumptions:• Homogenous cointegrating vector, [1,−β′].

• u†it independent across countries.

• Group-specific heterogeneity accounted for by:

Fixed effects, time fixed effects, heterogeneous time trends,disparate short-run dynamics.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Results

Table: Baseline Regression Results

(1) (2) (3) (4)

Independent variable Full Sample High Income Emerging Developing

Valuation-Effect Volatility 0.085 (0.025)∗∗∗ -0.045 (0.050) 0.162 (0.052)∗∗∗ 0.082 (0.029)∗∗∗

Real GDP Growth Volatility 0.677 (0.036)∗∗∗ 0.978 (0.066)∗∗∗ 0.811 (0.086)∗∗∗ 0.458 (0.037)∗∗∗

Inflation Volatility 0.103 (0.013)∗∗∗ -0.009 (0.042) 0.093 (0.02)∗∗∗ 0.129 (0.021)∗∗∗

Country Specific Effects Yes Yes Yes YesHeterogeneous Time Trends Yes Yes Yes YesObservations 1629 423 391 815N 82 19 20 43IPS (p-value) 0.00 0.00 0.00 0.00

Notes: ∗∗∗, ∗∗, ∗ denote the level of statistical significance at 1, 5, and 10 percent. Standard errors in parentheses.IPS refers to the Im et al. (2003) unit root test performed on the residuals under the unit root null.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

• PBM predicts: Impact of VE-volatility on consumptionvolatility depends on currency decomposition of external debt.

• I construct subsamples based on the foreign currency exposureof countries’ external debt.

• I consider the following measure:• Weight of debt liabilities (portfolio debt and other debt)

denominated in foreign currency.

• Source: Lane and Shambaugh (2010).

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Table: Results for subsamples based on foreign currency exposure

(1) (2) (3)

Independent variable DL100 DL<100 DL100Non High Income Emerging

Valuation-Effect Volatility 0.116 (0.031)∗∗∗ 0.117(0.053)∗∗ 0.236 (0.097)∗∗

Real GDP Growth Volatility 0.536 (0.040)∗∗∗ 0.707 (0.086)∗∗∗ 1.042 (0.16)∗∗∗

Inflation Volatility 0.114 (0.015)∗∗∗ 0.103 (0.026)∗∗∗ 0.097 (0.027)∗∗∗

Country Specific Effects Yes Yes YesHeterogeneous Time Trends Yes Yes YesObservations 1001 205 204N 52 11 10IPS (p-value) 0.00 0.00 0.00

Notes: ∗∗∗, ∗∗, ∗ denote the level of statistical significance at 1, 5, and 10 percent. Standarderrors in parentheses. IPS refers to the Im et al. (2003) unit root test performed on the residualsunder the unit root null.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Conclusion

• The results are consistent with a priori theoretical predictions.

• They suggest that valuation-effect volatility imposes welfarecosts on countries with a high share of their liabilitiesdenominated in foreign currency.

• Implication of the findings is that financial globalizationdecreases welfare in emerging and developing economies thatface the problem of original sin (partial equilibrium).

• These types of countries should take a cautious approach toliberalizing their capital account transactions.

Background Research Question Theoretical considerations Empirical model and data Estimation and results Conclusion

Thank You!