Sex Ratios and Exchange Rates

NBER WORKING PAPER SERIES

SEX RATIOS AND EXCHANGE RATES

Qingyuan DuShang-Jin Wei

Working Paper 16788http://www.nber.org/papers/w16788

NATIONAL BUREAU OF ECONOMIC RESEARCH1050 Massachusetts Avenue

Cambridge, MA 02138February 2011

This research is supported by US National Science Foundation grant SES-1024574, which we gratefullyacknowledge. We thank Jeffrey Frankel, Kenneth West, conference/seminar participants at the NBER,UC Berkeley, UC Davis, Columbia University, Federal Reserve Bank of San Francisco, the WorldBank, the Bank for International Settlement, Reserve Bank of Australia, and University of Zurich forhelpful comments and Joy Glazener for editorial help. We are solely responsible for any possible errorsin the paper. The views expressed herein are those of the authors and do not necessarily reflect theviews of the National Bureau of Economic Research.

© 2011 by Qingyuan Du and Shang-Jin Wei. All rights reserved. Short sections of text, not to exceedtwo paragraphs, may be quoted without explicit permission provided that full credit, including © notice,is given to the source.

Sex Ratios and Exchange RatesQingyuan Du and Shang-Jin WeiNBER Working Paper No. 16788February 2011JEL No. F31,F41

ABSTRACT

A rise in the sex ratio (increasing relative surplus of men in the marriage market) in China and severalother economies, in theory, can simultaneously generate a decline in the real exchange rate (RER)and a rise in the current account surplus. We demonstrate this logic through both a savings channeland an effective labor supply channel. In this model, a low RER is not a cause of the current accountsurplus, nor is it a consequence of currency manipulations. Empirically, those economies with a highsex ratio tend to have a low real exchange rate, beyond what can be explained by the Balassa-Samuelsoneffect, financial underdevelopment, dependence ratio, and exchange rate regime classifications. Oncethese factors are accounted for, the Chinese real exchange rate is estimated to be undervalued by onlya relatively trivial amount.

Qingyuan DuEconomics DepartmentColumbia Universityqingyuandu@gmail.com

Shang-Jin WeiGraduate School of BusinessColumbia UniversityUris Hall 6193022 BroadwayNew York, NY 10027-6902and NBERshangjin.wei@columbia.edu

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1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5-0.4

sex ratio

ciation

RER depreciation vs sex ratio, kappa=0.8

x=2, sigma=0.01, p=0.02x=0.5, sigma=0.01, p=0.02x=2, sigma=0.05, p=0.02x=2, sigma=0.01, p=0.05

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50.12

sex ratio

Aggregate savings rate vs sex ratio, kappa=0.8

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50

sex ratio

CA/GDP vs sex ratio, kappa=0.8

Figure 1: RER, aggregate savings rate, CA/GDP vs sex ratio, no labor supply effect, kappa=0.8

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5-0.4

sex ratio

ciatio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50.12

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5-0.4

sex ratio

ciatio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50.12

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5-0.02

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5-0.4

sex ratio

ciatio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50.12

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50

sex ratio

Figure 4: RER, aggregate savings rate, CA/GDP vs sex ratio, with labor supply effect, kappa=0.8

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5-0.4

sex ratio

ciatio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50.12

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5-0.4

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50.12

sex ratio

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.50

sex ratio

0 2 4 6 8 10 12 14 16 18 20-0.12

sex ratio

RER depreciation

b=2.72

0 2 4 6 8 10 12 14 16 18 200.24

sex ratio

Aggregate savings rate

b=2.72

b=2b=4

0 2 4 6 8 10 12 14 16 18 200

sex ratio

Non-governmental CA/GDP

b=2.72

b=2b=4

Figure 7: Impulse responses of RER, aggregate savings rate and CA/GDP, !=20

Table 1: Summary statistics, 2004-2008 average

Variable Mean Median Standard deviation Min value Max value

Ln(RER) ‐0.74 ‐0.80 0.59 ‐2.22 0.41

(Private Sector) Current account ‐3.63 ‐2.93 9.32 ‐31.51 26.91

Real GDP per capita (US$) 12986 7747 13733 367 77057

Private credit (% of GDP) 56.63 38.70 52.26 2.08 319.72

Financial system sophistication 3.78 3.66 0.79 2.52 5.28

Sex ratio 1.04 1.04 0.02 1.00 1.13

Fiscal deficit (% of GDP) ‐1.47 ‐0.37 5.98 ‐25.98 11.38

Terms of trade 113 102 33.8 70.0 205.8

Capital account openness 0.53 0.118 1.64 ‐1.83 2.50

Dependency ratio 60.75 54.84 17.64 28.47 107.60

! The real exchange rate data is obtained from Penn World Tables 6.3. The variable “p” (called “price level of GDP”) in the Penn World Tables is equivalent to the real exchange rate relative to the US dollar: A lower value of p means a depreciation in the real exchange rate.

! Private Sector Current account = current account to GDP ratio minus the government savings to GDP ratio.

! For the ratio of private credit (% of GDP), we follow Allen, Qian and Qian (2004) and modify the measure for China by multiplying 0.2 to the credit to GDP ratio. This is to correct for the fact that only 20% of the bank loans go to private firms. Financial system sophistication from the Global Competitiveness Report is another measure for the financial development.

! Fiscal deficit data is obtained from IFS database. Terms of trade index is defined as the ratio of export price index to the import price index, which is from Worldbank database. We use the capital account openness index in Chinn and Ito (2008) to measure the degree of capital controls. A higher value means less capital control. Dependency ratio data can be obtained from Worldbank database.

Table 2: Ln(real exchange rate) and the sex ratio, using private credit to GDP ratio as the measure of financial development

countries

Excluding major

oil exporters

Excluding major

oil exporters

Excluding major

oil exporters

Excluding major

oil exporters

Sex ratio

‐4.290** ‐4.012** ‐3.193* ‐3.408** ‐3.500**

(1.667) (1.713) (1.797) (1.568) (1.754)

Ln(GDP per capita) 0.318** 0.190** 0.236** 0.233** 0.360** 0.402** 0.359**

(0.030) (0.038) (0.041) (0.044) (0.073) (0.063) (0.073)

Private credit (% of GDP)

0.004** 0.004** 0.004** 0.003** 0.002** 0.002**

(0.001) (0.001) (0.001) (0.001) (0.001) (0.001)

Fiscal deficit

‐0.007 0.002 ‐0.005

(0.009) (0.008) (0.009)

Terms of trade

0.0002 ‐0.001 0.0003

(0.001) (0.001) (0.001)

Capital account openness

0.060** 0.029 0.058**

(0.027) (0.024) (0.027)

Dependency ratio

0.009** 0.010** 0.008*

(0.004) (0.004) (0.004)

Crawling peg (RR)

‐0.397**

(0.075)

Managed floating (RR)

‐0.036

(0.077)

Free floating (RR)

‐0.081

(0.119)

Intermediate (LYS)

‐0.078

(0.092)

Float (LYS)

‐0.145*

(0.085)

Observations 142 132 132 123 92 89 92

R‐squared 0.444 0.542 0.564 0.579 0.706 0.801 0.716

Dependent variable = ln(RER). Standard errors are in parentheses, ** p<0.05, * p<0.1

Table 3: Ln(real exchange rate) and the sex ratio, using financial system sophistication as the measure of financial development

countries

Excluding major

oil exporters

Excluding major

oil exporters

Excluding major

oil exporters

Excluding major

oil exporters

Sex ratio

‐6.192** ‐6.255** ‐5.051* ‐4.664* ‐4.430

(1.964) (1.995) (2.500) (2.802) (2.908)

Ln(GDP per capita) 0.318** 0.480** 0.443** 0.447** 0.529** 0.526** 0.531**

(0.030) (0.082) (0.077) (0.088) (0.123) (0.119) (0.127)

Financial system sophistication

0.170* 0.252** 0.245** 0.099 0.034 0.086

(0.089) (0.086) (0.099) (0.110) (0.121) (0.116)

Fiscal deficit

‐0.022 ‐0.014 ‐0.025

(0.015) (0.015) (0.017)

Terms of trade

‐0.004 ‐0.006** ‐0.005

(0.003) (0.003) (0.003)

0.063 0.058 0.073

(0.042) (0.047) (0.047)

Dependency ratio

0.014** 0.017** 0.017*

(0.007) (0.007) (0.008)

Crawling peg (RR)

‐0.285*

(0.147)

(0.102)

Free floating (RR)

(0.173)

Intermediate (LYS)

‐0.052

(0.137)

Float (LYS)

(0.125)

Observations 142 54 54 49 43 42 43

R‐squared 0.444 0.748 0.791 0.797 0.844 0.866 0.845

! Dependent variable = log(RER). Standard errors are in parentheses, ** p<0.05, * p<0.1

Table 4: Non-governmental CA/GDP vs sex ratio, using private credit to GDP ratio as the measure of financial development

countries

Excluding major

oil exporters

Excluding major

oil exporters

Excluding major

oil exporters

Excluding major

oil exporters

Sex ratio

66.43* 78.43** 134.7** 111.6** 94.24

(37.09) (36.65) (37.52) (56.43) (56.51)

Ln(GDP per capita) 2.025** 3.683** 2.964** 2.050** 4.941** 4.035 3.834

(0.639) (0.876) (0.957) (0.975) (1.529) (3.415) (3.115)

Private credit (% of GDP)

‐0.048** ‐0.046** ‐0.030* ‐0.054** ‐0.053** ‐0.051**

(0.018) (0.018) (0.018) (0.018) (0.025) (0.024)

Fiscal deficit

0.079 ‐0.031 0.101

(0.187) (0.379) (0.345)

Terms of trade

0.021 0.127 0.131*

(0.029) (0.076) (0.076)

‐0.315 ‐0.017 ‐0.081

(0.563) (1.508) (1.353)

Dependency ratio

0.175* 0.209 0.439

(0.089) (0.745) (0.720)

Share of working age people

0.163 0.797

(1.884) (1.885)

Social security expenditure (% of GDP)

0.137 0.115

(0.250) (0.233)

Crawling peg (RR)

(3.694)

(2.840)

Free floating (RR)

(5.730)

Intermediate (LYS)

(2.911)

Float (LYS)

(2.469)

Continent dummies N N N N N Y Y

Observations 130 127 127 120 91 47 48

R‐squared 0.073 0.125 0.147 0.121 0.275 0.543 0.532

Table 5: Non-governmental CA/GDP vs sex ratio, using financial system sophistication as the measure of financial development

countries

Excluding major

oil exporters

Excluding major

oil exporters

Excluding major

oil exporters

Excluding major

oil exporters

Sex ratio

103.3** 77.57** 129.6** 51.98 13.34

(43.29) (37.42) (52.89) (96.33) (80.39)

Ln(GDP per capita) 2.025** 1.715 2.327 ‐0.470 2.009 3.752 ‐0.194

(0.639) (1.744) (1.688) (1.641) (2.613) (5.031) (3.845)

Financial system sophistication

‐0.925 ‐2.290 0.876 ‐0.477 4.029 3.480

(1.889) (1.896) (1.861) (2.337) (3.336) (2.951)

Fiscal deficit

‐0.185 0.081 0.385

(0.313) (0.533) (0.512)

Terms of trade

0.039 ‐0.070 0.0772

(0.055) (0.118) (0.105)

‐0.103 ‐1.300 ‐0.569

(0.879) (2.619) (1.765)

Dependency ratio

0.251 0.167 ‐1.807

(0.150) (5.527) (2.375)

Share of working age people

0.125 ‐3.446

(12.23) (5.400)

Social security expenditure (% of GDP)

0.056 ‐0.092

(0.302) (0.257)

Crawling peg (RR)

(5.893)

(3.055)

Free floating (RR)

‐8.510

(7.890)

Intermediate (LYS)

7.626**

(3.571)

Float (LYS)

‐3.593

(4.050)

Continent dummies N N N N N Y Y

Observations 130 54 54 49 43 32 33

R‐squared 0.073 0.023 0.123 0.118 0.200 0.478 0.505

Table 6: Real exchange rate undervaluation and excess current account: The Case of China

% of RER undervaluation Excess (non‐governmental) current account

Only BS

Add GD

+TT+KA

Only BS

Add GD

+TT+KA

Financial development index Private credit (% of GDP) 55.26 43.45 35.44 17.91 7.86 13.52 12.06 11.39 8.97 2.01

Financial system sophistication 55.26 46.38 31.31 16.78 2.24 13.52 10.26 10.11 7.97 0.37

Notes:

A. Excess RER undervaluation = model prediction – actual log RER. (A positive number describes % undervaluation).

B. Excess current account = private sector current account (i.e., current account net of government savings) – model prediction;

C. The five columns include progressively more regresors:

! (1) The only regressor (other than the intercept) is log income, a proxy for the Balassa-Samuelson (BS) effect;

! (2) Add financial development (FD) to the list of regressors;

! (3) Add government fiscal deficit (GD), terms of trade (TT), and capital account openness (KA);

! (4) Add the dependence ratio (DR);

! (5) Add the sex ratio (SR)

D. The last two rows correspond to estimates when two different proxies for financial development are used. The first row uses the ratio of credit to the private sector to GDP, and the second row uses an index of local financial system sophistication from the Global Competitiveness Report.

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